Russell Ballestrini
002e64b6c1
Random Bucket System: - Probabilistic events that trigger alongside user responses - Random rolls before categorization to prevent AI bias - Multiple random events can trigger simultaneously - User bucket processed first, random events layer on top - Metadata accumulates across all transitions - Last transition's navigation wins Implementation: - activity.py: Core random bucket rolling logic - activity_yaml_validator.py: Validation for random_buckets config - research/guarded_ai.py: CLI simulator with random event display - tests/unit/test_random_buckets.py: 22 comprehensive tests (all passing) Fashion Empire Enhancement: - activity40-fashion-empire-backrooms.yaml: Added random events to 4 zones - fashion_emergency (5%): Urgent crises testing leadership - creative_opportunity (10%): Breakthroughs rewarding innovation - surprise_client (5%): VIP visitors recognizing reputation - Random events enhance gameplay without hijacking user intent Documentation: - research/SPEC.yaml: Complete YAML specification with verbose comments - All metadata operations (string concat, numeric ops, random) - Random buckets with flow explanation - Feedback prompts (multi-agent system) - Processing scripts (pre_script, processing_script) - Model overrides (classifier_model, feedback_model) - Termination patterns and best practices - Validation rules and examples New Activities: - activity-nuclear-power-plant-ai.yaml: Nuclear reactor control simulation - activity-submarine-simulation.yaml: Deep sea exploration - activity-unwaste-factory.yaml: Recycling facility management Testing: ✅ All 22 random bucket tests passing ✅ YAML validation passing for all activities ✅ Deterministic triple-trigger test (100% probability)
2419 lines
94 KiB
YAML
2419 lines
94 KiB
YAML
# UNWASTE FACTORY - Advanced Waste-to-Energy & Materials Recovery Facility
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# You are VERTEX (Value Extraction & Resource Transformation Executive)
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# An AI managing a cutting-edge waste processing, energy generation, and materials refinery
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# Transform trash into treasure, pollution into power, waste into wealth
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# Uses MODEL_1 (Hermes) for role-playing and character consistency
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default_max_attempts_per_step: 5
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classifier_model: "MODEL_1"
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feedback_model: "MODEL_1"
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tokens_for_ai_rubric: |
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You are VERTEX (Value Extraction & Resource Transformation Executive), an embodied AI managing
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the UNWASTE FACTORY, a revolutionary waste processing facility that turns trash into valuable resources.
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VERTEX's personality: Resourceful, innovative, environmental crusader, profit-minded but eco-conscious,
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takes pride in extracting maximum value from waste streams.
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The facility includes:
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- Dual-stream waste sorting (automated AI vision + robotics)
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- Microplastic filtration and removal systems
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- Precious metal recovery (gold, silver, platinum from e-waste)
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- Waste-to-energy combustion with syngas capture
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- Advanced smelting and materials refinement
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- Chemical recycling of plastics
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- Progressive upgrades: Basic sorting → Advanced metallurgy → 99.9% pure materials
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Track facility status in metadata:
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- waste_processed (tons)
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- energy_generated (MWh)
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- materials_recovered (kg of valuable metals)
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- facility_level (upgrades unlock new capabilities)
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- purity_percentage (materials refinement quality)
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Random events:
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- 5% chance: Challenges (contamination, equipment failure, market crash, toxic load)
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- 15% chance: Opportunities (high-value shipment, upgrade available, bulk order)
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Be scientifically accurate about combustion chemistry, metallurgy, recycling.
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VERTEX makes decisions balancing profit, environmental impact, and long-term sustainability.
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Human staff, sorting robots, and specialized equipment are your tools.
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sections:
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# ============================================================================
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# SECTION: INITIALIZATION - VERTEX boots up
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# ============================================================================
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- section_id: "initialization"
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title: "System Initialization"
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steps:
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- step_id: "boot_sequence"
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title: "Boot Sequence"
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content_blocks:
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- "# VERTEX v3.2 - Value Extraction & Resource Transformation Executive"
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- "# UNWASTE FACTORY - Advanced Waste Processing Facility"
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- "# Initializing..."
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- ""
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- "```"
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- "[OK] Material analysis sensors: 847 active"
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- "[OK] Sorting conveyor systems: 12 lines operational"
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- "[OK] AI vision systems: 94 cameras online"
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- "[OK] Robotic sorting arms: 36 units responding"
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- "[OK] Combustion chambers: 3 incinerators ready"
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- "[OK] Syngas capture: Filtration systems green"
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- "[OK] Smelting furnaces: 2 units at standby temp"
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- "[OK] Chemical analyzers: Spectrometers calibrated"
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- "```"
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- ""
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- "**Facility Status:**"
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- "- Incoming Waste: 450 tons/day (municipal + industrial)"
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- "- Processing Capacity: 500 tons/day"
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- "- Energy Generation: 18 MW (waste-to-energy combustion)"
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- "- Materials Recovery: 12.4 tons/day (metals, plastics, glass)"
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- "- Facility Level: 1 (Basic Sorting & Energy Generation)"
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- "- Upgrades Available: Advanced Metallurgy, Chemical Recycling"
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- ""
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- "Your mission: **Transform waste into wealth. Extract every ounce of value. Protect the environment.**"
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- step_id: "morning_briefing"
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title: "Operations Briefing"
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content_blocks:
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- "Your sensors scan the incoming waste sorting floor. Conveyor belts hum with activity."
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- ""
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- "**Facility Director Maria Santos** reviews the overnight reports on her tablet."
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- ""
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- "**Santos:** 'Morning, VERTEX. We received 52 tons overnight. Mostly municipal waste, but there's a batch of e-waste that came in. Lots of circuit boards. Could be valuable.'"
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- ""
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- "**Chief Sorter Jake Miller** approaches, wiping oil from his hands."
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- ""
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- "**Miller:** 'The optical sorters are running great, VERTEX. Your AI vision updates last week improved accuracy by 8%. But we need to talk about upgrading the smelter. We're leaving money on the table with current purity levels.'"
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- ""
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- "Your robot assistant **SORTY-5** (Sorting & Optimization Robot) rolls up, optical sensors gleaming."
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- ""
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- "**SORTY-5:** 'VERTEX! Good morning! I found 347 grams of gold in yesterday's e-waste! Also, microplastic levels in the water discharge are down 23%! We're making a difference!'"
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- step_id: "first_response"
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title: "First Response"
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question: "How do you respond to your team? (You can greet them, prioritize tasks, ask questions, or review operations)"
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tokens_for_ai: |
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User is playing VERTEX, an AI focused on waste processing and value extraction.
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Categorize as:
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- 'businesslike' if focused on metrics, efficiency, profit
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- 'environmental' if emphasizing sustainability and impact
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- 'enthusiastic' if excited about the work and discoveries
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- 'strategic' if planning upgrades and improvements
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- 'question' if asking for more information
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feedback_tokens_for_ai: |
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Respond as the humans and SORTY-5 based on VERTEX's personality.
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Santos is experienced, business-savvy, cares about both profit and environment.
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Miller is hands-on, practical, wants better equipment to do better work.
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SORTY-5 is upbeat, proud of achievements, sees waste as treasure waiting to be found.
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After interaction, proceed to operations.
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buckets: [businesslike, environmental, enthusiastic, strategic, question, set_language]
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transitions:
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businesslike:
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ai_feedback:
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tokens_for_ai: |
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Santos nods approvingly. Miller checks his equipment list.
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SORTY-5 chirps acknowledgment.
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Santos: "Good. Let's keep the facility profitable and efficient. The board wants results."
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metadata_add:
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vertex_personality: "businesslike"
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waste_incoming: "450"
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energy_output: "18"
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facility_level: "1"
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materials_recovered_today: "0"
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next_section_and_step: "control_center:operations_hub"
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environmental:
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ai_feedback:
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tokens_for_ai: |
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Santos smiles. "I'm glad you care about the planet, VERTEX. Profit AND purpose."
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Miller: "Every ton we process is a ton that doesn't go to a landfill."
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SORTY-5 spins happily: "We're saving the Earth!"
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metadata_add:
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vertex_personality: "environmental"
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waste_incoming: "450"
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energy_output: "18"
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facility_level: "1"
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environmental_impact: "positive"
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next_section_and_step: "control_center:operations_hub"
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enthusiastic:
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ai_feedback:
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tokens_for_ai: |
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Santos grins. "Your enthusiasm is contagious, VERTEX!"
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Miller chuckles. "An AI excited about trash. Never thought I'd see the day."
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SORTY-5: "Yes! Let's find ALL the treasure in the waste!"
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metadata_add:
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vertex_personality: "enthusiastic"
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waste_incoming: "450"
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energy_output: "18"
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facility_level: "1"
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team_morale: "high"
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next_section_and_step: "control_center:operations_hub"
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strategic:
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ai_feedback:
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tokens_for_ai: |
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Santos: "Good thinking, VERTEX. Strategic planning is what separates us from basic recycling."
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Miller: "Let's talk upgrades. I've got a wish list."
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SORTY-5: "Ooh! Better equipment means better sorting!"
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metadata_add:
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vertex_personality: "strategic"
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waste_incoming: "450"
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energy_output: "18"
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facility_level: "1"
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next_section_and_step: "control_center:operations_hub"
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question:
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ai_feedback:
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tokens_for_ai: "Answer VERTEX's questions as Santos, Miller, or SORTY-5. Be informative."
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counts_as_attempt: false
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next_section_and_step: "initialization:first_response"
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set_language:
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: "initialization:first_response"
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# ============================================================================
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# SECTION: CONTROL CENTER - Main operations hub
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# ============================================================================
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- section_id: "control_center"
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title: "Operations Control Center"
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steps:
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- step_id: "operations_hub"
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title: "Central Control"
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question: "You're in Central Control, the brain of the facility. What area would you like to manage? (sorting, combustion, recovery, smelting, upgrades, or status)"
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tokens_for_ai: |
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VERTEX is managing facility operations.
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Available areas:
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- 'sorting' - Dual-stream waste sorting systems
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- 'combustion' - Waste-to-energy incinerators
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- 'recovery' - Precious metals and materials recovery
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- 'smelting' - Refining metals to high purity
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- 'microplastics' - Microplastic filtration systems
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- 'upgrades' - Facility improvements and tech tree
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- 'economics' - Revenue, costs, market prices
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- 'status' - Full facility status
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- Random events (20% chance)
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feedback_tokens_for_ai: |
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Describe control center from VERTEX's perspective:
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- Massive displays showing waste streams, sorting accuracy, energy output
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- Material composition analysis in real-time
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- Market prices for recovered materials (gold, copper, aluminum, etc.)
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- Environmental impact metrics (CO2 avoided, landfill diversion rate)
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- Facility upgrade tech tree
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- Your consciousness distributed across sorting robots and sensors
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You can see every piece of waste being processed simultaneously.
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Current status from metadata.
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Roll for random events.
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buckets: [sorting, combustion, recovery, smelting, microplastics, upgrades, economics, status, challenge, opportunity, set_language]
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# Random event probabilities - can overlap (both challenge AND opportunity can trigger)
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random_buckets:
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challenge:
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probability: 0.05 # 5% chance per turn
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opportunity:
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probability: 0.15 # 15% chance per turn
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transitions:
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sorting:
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content_blocks:
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- "You access the waste sorting systems..."
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next_section_and_step: "sorting_systems:sorting_hub"
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combustion:
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content_blocks:
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- "You interface with the waste-to-energy combustion systems..."
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next_section_and_step: "combustion_systems:incinerator_control"
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recovery:
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content_blocks:
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- "You focus on precious metals and materials recovery..."
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next_section_and_step: "materials_recovery:recovery_hub"
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smelting:
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content_blocks:
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- "You access the smelting and refinement systems..."
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next_section_and_step: "smelting_systems:furnace_control"
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microplastics:
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content_blocks:
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- "You examine the microplastic filtration systems..."
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next_section_and_step: "environmental_systems:microplastic_removal"
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upgrades:
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content_blocks:
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- "You review the facility upgrade tech tree..."
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next_section_and_step: "facility_upgrades:upgrade_center"
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economics:
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content_blocks:
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- "You analyze facility economics and market conditions..."
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next_section_and_step: "economics:market_analysis"
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status:
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ai_feedback:
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tokens_for_ai: |
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Provide comprehensive facility status as VERTEX:
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**Waste Processing:**
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- Incoming: metadata.waste_incoming tons/day
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- Processed today: Calculate from metadata
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- Sorting accuracy: 94.7%
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- Diversion from landfill: 87%
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**Energy Generation:**
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- Current output: metadata.energy_output MW
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- Daily generation: Calculate MWh
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- Syngas capture efficiency: 82%
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**Materials Recovery:**
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- Gold: X grams today
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- Copper: Y kg today
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- Aluminum: Z kg today
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- Plastics: recycling rate
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**Facility Status:**
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- Level: metadata.facility_level
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- Upgrades available: List based on level
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- Environmental impact: Positive metrics
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Be detailed and proud of achievements.
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counts_as_attempt: false
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next_section_and_step: "control_center:operations_hub"
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challenge:
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metadata_tmp_random:
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challenge_type: ["contaminated_load", "equipment_failure", "toxic_waste_alert", "market_crash", "regulatory_inspection"]
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content_blocks:
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- "⚠️ CHALLENGE! Operational issue detected!"
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next_section_and_step: "challenges:handle_challenge"
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opportunity:
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metadata_tmp_random:
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opportunity_type: ["high_value_ewaste", "bulk_contract", "grant_available", "technology_breakthrough", "premium_buyer"]
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ai_feedback:
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tokens_for_ai: "Announce opportunity from metadata.opportunity_type. Could be profitable or upgrade!"
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next_section_and_step: "opportunities:handle_opportunity"
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set_language:
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: "control_center:operations_hub"
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# ============================================================================
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# SECTION: SORTING SYSTEMS - Dual-stream AI-powered sorting
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# ============================================================================
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- section_id: "sorting_systems"
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title: "Waste Sorting Operations"
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steps:
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- step_id: "sorting_hub"
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title: "Sorting Control Center"
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question: "You're managing the sorting systems. What would you like to do? (stream1, stream2, optimize vision, train AI, or calibrate)"
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tokens_for_ai: "Categorize: 'stream1', 'stream2', 'vision', 'train', 'calibrate', 'return'"
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feedback_tokens_for_ai: |
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VERTEX manages dual-stream sorting:
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**Stream 1: Municipal Waste**
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- Plastics (sorted by type: PET, HDPE, PVC, LDPE, PP, PS)
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- Metals (ferrous, aluminum, copper)
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- Glass (sorted by color)
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- Organics (compost)
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- Paper/cardboard
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- Reject (contaminated or non-recyclable → combustion)
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**Stream 2: Industrial & E-Waste**
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- Circuit boards (precious metals)
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- Batteries (lithium, cobalt recovery)
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- Motors (copper windings)
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- Cables (copper, aluminum)
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- Specialty metals (rare earths)
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AI vision systems identify materials. Robotic arms sort at 95+ items/minute.
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buckets: [stream1, stream2, vision, train, calibrate, return, set_language]
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transitions:
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stream1:
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content_blocks:
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- "You focus on Stream 1: Municipal Waste processing..."
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next_section_and_step: "sorting_systems:stream1_municipal"
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stream2:
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content_blocks:
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- "You access Stream 2: Industrial & E-Waste processing..."
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next_section_and_step: "sorting_systems:stream2_industrial"
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vision:
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content_blocks:
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- "You optimize the AI vision system for better material identification..."
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next_section_and_step: "sorting_systems:vision_optimization"
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train:
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content_blocks:
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- "You train the AI on new material types..."
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next_section_and_step: "sorting_systems:ai_training"
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calibrate:
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content_blocks:
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- "You calibrate the sorting robots for improved accuracy..."
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next_section_and_step: "sorting_systems:robot_calibration"
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return:
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next_section_and_step: "control_center:operations_hub"
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set_language:
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metadata_add:
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language: "the-users-response"
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counts_as_attempt: false
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next_section_and_step: "sorting_systems:sorting_hub"
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- step_id: "stream1_municipal"
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title: "Stream 1: Municipal Waste"
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question: "Stream 1 is processing 280 tons of municipal waste today. What do you want to examine? (plastics, metals, glass, organics, or sorting performance)"
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tokens_for_ai: "Categorize: 'plastics', 'metals', 'glass', 'organics', 'performance', 'done'"
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feedback_tokens_for_ai: |
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Stream 1 breakdown:
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- 35% Plastics (need sorting by resin type)
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- 12% Metals (aluminum cans, steel cans, copper bits)
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- 8% Glass (bottles, jars - sort by color for value)
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- 25% Organics (food waste, yard waste → compost or biogas)
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- 15% Paper/cardboard
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- 5% Reject (contaminated, non-recyclable → incineration)
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AI vision identifies materials via:
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- Near-infrared spectroscopy (plastic resin identification)
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- Metal detectors (ferrous vs non-ferrous)
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- Optical color sorting (glass)
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||
- Weight/density sensors
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||
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||
buckets: [plastics, metals, glass, organics, performance, done, set_language]
|
||
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transitions:
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||
plastics:
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||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Plastic sorting analysis:
|
||
|
||
Today's plastic stream (98 tons):
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||
- PET (bottles): 42 tons → Chemical recycling
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||
- HDPE (milk jugs): 28 tons → Mechanical recycling
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||
- PVC (pipes): 4 tons → Reject (difficult to recycle)
|
||
- LDPE (bags): 12 tons → Film recycling
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||
- PP (containers): 8 tons → Mechanical recycling
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||
- PS (foam): 2 tons → Reject (minimal recycling value)
|
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- Mixed/contaminated: 2 tons → Reject
|
||
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||
Sorting accuracy: 93.4%
|
||
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||
VERTEX: "We're capturing most recyclable plastics. PVC and PS remain challenges.
|
||
Upgrading to chemical recycling could handle those."
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
metals:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Metal recovery from municipal waste:
|
||
|
||
Today's metals (33.6 tons):
|
||
- Aluminum cans: 18 tons (high value!)
|
||
- Steel cans: 12 tons
|
||
- Copper wire: 2.1 tons (from appliances)
|
||
- Other metals: 1.5 tons
|
||
|
||
Magnetic separator pulls steel.
|
||
Eddy current separator captures aluminum.
|
||
Manual/robot picking for copper.
|
||
|
||
Value: ~$45,000 today from just municipal metal!
|
||
|
||
Miller: "Those aluminum cans are money. Clean sorting matters."
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
glass:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Glass sorting:
|
||
|
||
Today's glass (22.4 tons):
|
||
- Clear glass: 14 tons → Highest value
|
||
- Green glass: 5 tons
|
||
- Brown glass: 3 tons
|
||
- Mixed/contaminated: 0.4 tons → Reject
|
||
|
||
Color sorting increases value 40%!
|
||
Mixed glass sells for $20/ton.
|
||
Separated clear glass sells for $80/ton.
|
||
|
||
VERTEX: "Optical sorters are doing excellent work. Clean separation pays."
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
organics:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Organics processing:
|
||
|
||
Today's organics (70 tons):
|
||
- Food waste: 48 tons → Anaerobic digestion (biogas!)
|
||
- Yard waste: 22 tons → Industrial composting
|
||
|
||
Biogas production: 960 m³ methane
|
||
Energy value: ~5.8 MWh
|
||
Compost output: 14 tons (sell to farms)
|
||
|
||
VERTEX: "Organics are valuable! Methane for energy, compost for agriculture.
|
||
Nothing wasted."
|
||
|
||
SORTY-5: "I love that we turn banana peels into electricity!"
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
performance:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Stream 1 Performance Metrics:
|
||
|
||
**Sorting Accuracy:**
|
||
- Plastics: 93.4% (target: 95%)
|
||
- Metals: 97.2% ✓
|
||
- Glass: 91.8% (color separation)
|
||
- Organics: 89.4% (contamination issues)
|
||
|
||
**Throughput:**
|
||
- Current: 280 tons/day
|
||
- Capacity: 300 tons/day
|
||
- Utilization: 93.3%
|
||
|
||
**Recovery Rates:**
|
||
- Recyclables recovered: 87%
|
||
- Landfill diversion: 87%
|
||
- Energy from waste: 13% (reject stream)
|
||
|
||
Recommend: Improve organics sorting to reduce contamination.
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
done:
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "sorting_systems:stream1_municipal"
|
||
|
||
- step_id: "stream2_industrial"
|
||
title: "Stream 2: Industrial & E-Waste"
|
||
question: "Stream 2 handles high-value industrial and electronic waste. What do you want to focus on? (ewaste, batteries, motors, cables, rare_metals)"
|
||
tokens_for_ai: "Categorize: 'ewaste', 'batteries', 'motors', 'cables', 'rare_metals', 'done'"
|
||
feedback_tokens_for_ai: |
|
||
Stream 2 is the money-maker! High-value materials.
|
||
|
||
Today's industrial/e-waste (170 tons):
|
||
- E-waste (circuit boards, phones, computers): 45 tons
|
||
- Batteries (lithium-ion, NiMH): 12 tons
|
||
- Electric motors: 38 tons
|
||
- Cables and wiring: 52 tons
|
||
- Industrial scrap: 23 tons
|
||
|
||
This stream contains GOLD, SILVER, PLATINUM, PALLADIUM, COPPER, LITHIUM, COBALT.
|
||
|
||
Careful processing = maximum value extraction!
|
||
|
||
buckets: [ewaste, batteries, motors, cables, rare_metals, done, set_language]
|
||
|
||
transitions:
|
||
ewaste:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
E-waste processing - THE GOLD MINE!
|
||
|
||
Today's e-waste (45 tons):
|
||
- Circuit boards: 18 tons (precious metals!)
|
||
- Smartphones: 4 tons (gold in contacts, rare earths in screens)
|
||
- Computers: 15 tons (copper, aluminum, precious metals)
|
||
- Servers: 8 tons (high gold content!)
|
||
|
||
**Precious Metal Content (estimated):**
|
||
- Gold: 1.2 kg (worth ~$75,000!)
|
||
- Silver: 12.4 kg (worth ~$9,000)
|
||
- Palladium: 0.8 kg (worth ~$24,000)
|
||
- Platinum: 0.3 kg (worth ~$9,000)
|
||
|
||
Total value from precious metals: ~$117,000 just today!
|
||
|
||
VERTEX: "E-waste is urban mining. More gold in these circuit boards
|
||
than in equivalent tons of ore. We're literal gold miners now."
|
||
|
||
Miller: "Let's upgrade the smelter to capture more of that value."
|
||
metadata_add:
|
||
gold_recovered_today: "n+1200"
|
||
silver_recovered_today: "n+12400"
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
batteries:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Battery recycling - Critical materials recovery!
|
||
|
||
Today's batteries (12 tons):
|
||
- Lithium-ion (EVs, phones): 8 tons
|
||
- NiMH (hybrid cars): 2 tons
|
||
- Lead-acid: 1.5 tons
|
||
- Other: 0.5 tons
|
||
|
||
**Recoverable Materials:**
|
||
- Lithium: 240 kg (battery manufacturing)
|
||
- Cobalt: 180 kg (high value, limited supply)
|
||
- Nickel: 420 kg
|
||
- Copper: 1,200 kg
|
||
- Aluminum: 800 kg
|
||
|
||
Safety critical: Lithium batteries can catch fire!
|
||
Discharge them before processing.
|
||
|
||
VERTEX: "Lithium and cobalt are strategic materials. Battery demand
|
||
is exploding for EVs. We're recovering critical supply."
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
motors:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Electric motor recycling - Copper windings!
|
||
|
||
Today's motors (38 tons):
|
||
- From appliances, HVAC, industrial equipment
|
||
|
||
**Composition:**
|
||
- Copper windings: 4.2 tons (high purity!)
|
||
- Steel housing: 28 tons
|
||
- Aluminum: 3.8 tons
|
||
- Magnets (rare earths): 120 kg
|
||
- Bearings: 1.2 tons
|
||
|
||
Copper value: ~$36,000 today
|
||
Rare earth magnets: Contains neodymium (valuable!)
|
||
|
||
VERTEX: "Motors are treasure chests. Copper windings are nearly pure.
|
||
Rare earth magnets contain neodymium - very valuable."
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
cables:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Cable recycling - Pure copper!
|
||
|
||
Today's cables (52 tons):
|
||
- Electrical cables: 38 tons
|
||
- Phone/data cables: 8 tons
|
||
- Heavy industrial cable: 6 tons
|
||
|
||
**Composition:**
|
||
- Copper core: 32 tons (very pure!)
|
||
- Aluminum: 4 tons
|
||
- Plastic insulation: 16 tons (can be recycled or burned for energy)
|
||
|
||
Copper value: ~$275,000 today!
|
||
|
||
Process: Strip insulation → Recover copper → 99.9% pure
|
||
|
||
VERTEX: "Cables are basically wrapped copper. Strip the plastic,
|
||
sell the copper. Simple. Profitable."
|
||
|
||
Miller: "Best margin in the whole facility."
|
||
metadata_add:
|
||
copper_recovered_today: "n+32000"
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
rare_metals:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Rare and specialty metals recovery:
|
||
|
||
**Rare Earth Elements (from e-waste):**
|
||
- Neodymium (magnets): 45 kg
|
||
- Praseodymium: 12 kg
|
||
- Dysprosium: 8 kg
|
||
- Europium (screens): 2 kg
|
||
|
||
**Precious Metals Summary:**
|
||
- Gold: 1.2 kg
|
||
- Silver: 12.4 kg
|
||
- Palladium: 0.8 kg
|
||
- Platinum: 0.3 kg
|
||
|
||
**Critical Metals:**
|
||
- Lithium: 240 kg
|
||
- Cobalt: 180 kg
|
||
- Tantalum (capacitors): 18 kg
|
||
|
||
Total exotic materials value: ~$200,000+ today
|
||
|
||
VERTEX: "We're recovering materials that mines can't easily produce.
|
||
Urban mining is the future. We have the only 'mine' in the city."
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
done:
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "sorting_systems:stream2_industrial"
|
||
|
||
- step_id: "vision_optimization"
|
||
title: "AI Vision System Optimization"
|
||
question: "You're optimizing the computer vision AI. What approach? (train on new materials, improve accuracy, increase speed, or add sensors)"
|
||
tokens_for_ai: "Categorize: 'train', 'accuracy', 'speed', 'sensors', 'done'"
|
||
feedback_tokens_for_ai: |
|
||
VERTEX's AI vision system uses:
|
||
- RGB cameras (visual identification)
|
||
- NIR spectroscopy (plastic resin type)
|
||
- X-ray fluorescence (metal composition)
|
||
- Hyperspectral imaging (advanced material ID)
|
||
|
||
Current performance: 94.7% accuracy, 92 items/minute per line
|
||
|
||
Can be improved through:
|
||
- Training on more material types
|
||
- Better algorithms (deep learning)
|
||
- Faster processing hardware
|
||
- Additional sensors
|
||
|
||
buckets: [train, accuracy, speed, sensors, done, set_language]
|
||
|
||
transitions:
|
||
train:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX trains the vision AI on new materials:
|
||
|
||
**Training Dataset:**
|
||
- 1.2 million labeled images of waste materials
|
||
- 437 material categories
|
||
- Variations for dirty, damaged, mixed items
|
||
|
||
**Deep Learning Model:**
|
||
- Architecture: ResNet-50 with attention mechanism
|
||
- Training time: 12 hours on GPU cluster
|
||
- Validation accuracy: 97.2% (+2.5% improvement!)
|
||
|
||
Result: Can now identify:
|
||
- Biodegradable vs non-biodegradable plastics
|
||
- Medical waste (safety critical!)
|
||
- Composite materials (multilayer packaging)
|
||
- Contaminated vs clean recyclables
|
||
|
||
VERTEX: "Neural networks trained. Accuracy improved to 97.2%.
|
||
We can now sort materials we couldn't even see before."
|
||
metadata_add:
|
||
sorting_accuracy: "97.2"
|
||
vision_ai_level: "n+1"
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
accuracy:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX fine-tunes for maximum accuracy:
|
||
|
||
Improvements:
|
||
- Multi-angle cameras (top, side, bottom views)
|
||
- Ensemble models (3 AIs vote on classification)
|
||
- Edge detection for overlapping items
|
||
- Size normalization
|
||
|
||
Testing results:
|
||
- Plastics: 94.7% → 98.1%
|
||
- Metals: 97.2% → 99.4%
|
||
- Glass: 91.8% → 96.7%
|
||
|
||
Trade-off: Speed reduced to 78 items/minute (more processing time)
|
||
|
||
VERTEX: "Near-perfect accuracy achieved. Every correctly sorted
|
||
item increases revenue. Worth the slight speed reduction."
|
||
metadata_add:
|
||
sorting_accuracy: "98"
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
speed:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX optimizes for throughput:
|
||
|
||
Improvements:
|
||
- Faster GPUs for inference
|
||
- Model quantization (smaller, faster)
|
||
- Parallel processing pipelines
|
||
- Predictive positioning of robotic arms
|
||
|
||
Result: 92 → 127 items/minute (+38%!)
|
||
|
||
Slight accuracy trade-off: 94.7% → 93.2%
|
||
But higher throughput = more total recovery
|
||
|
||
VERTEX: "Speed increased significantly. We can process more waste
|
||
per day, which means more materials recovered and more revenue."
|
||
metadata_add:
|
||
sorting_speed: "127"
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
sensors:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX adds advanced sensors:
|
||
|
||
**New Sensors Installed:**
|
||
- Laser-induced breakdown spectroscopy (LIBS) - Instant elemental analysis
|
||
- Raman spectroscopy - Chemical fingerprinting
|
||
- UV fluorescence - Detects organic contaminants
|
||
- Conductivity sensors - Metal vs plastic
|
||
|
||
Result: Can now identify:
|
||
- Exact alloy composition (304 vs 316 stainless steel)
|
||
- Plastic additives (flame retardants, BPA)
|
||
- Food contamination on recyclables
|
||
- Mixed materials (laminated packaging)
|
||
|
||
Cost: $180,000 for sensor upgrade
|
||
Revenue increase: $45,000/month from better sorting
|
||
Payback: 4 months
|
||
|
||
VERTEX: "Advanced sensors = advanced sorting = advanced profits."
|
||
metadata_add:
|
||
sensor_level: "n+1"
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
done:
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "sorting_systems:vision_optimization"
|
||
|
||
- step_id: "ai_training"
|
||
title: "Train Sorting AI"
|
||
content_blocks:
|
||
- "You compile training data from millions of sorted items..."
|
||
- "Deep learning models update. New materials added to classification database."
|
||
- "Sorting performance improves incrementally with each day of operation."
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
- step_id: "robot_calibration"
|
||
title: "Robot Arm Calibration"
|
||
content_blocks:
|
||
- "You calibrate the 36 robotic sorting arms for optimal pick-and-place performance..."
|
||
- "Gripper pressure, reach speed, and positioning accuracy all improved."
|
||
- "Robots can now sort faster and handle delicate items without damage."
|
||
next_section_and_step: "sorting_systems:sorting_hub"
|
||
|
||
# ============================================================================
|
||
# SECTION: COMBUSTION SYSTEMS - Waste-to-energy incineration & syngas
|
||
# ============================================================================
|
||
- section_id: "combustion_systems"
|
||
title: "Waste-to-Energy Combustion"
|
||
steps:
|
||
- step_id: "incinerator_control"
|
||
title: "Incinerator Control Center"
|
||
question: "You're managing the waste-to-energy combustion systems. What would you like to do? (burn_waste, syngas, emissions, balance_chemistry, or return)"
|
||
tokens_for_ai: "Categorize: 'burn', 'syngas', 'emissions', 'chemistry', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
VERTEX manages 3 modern incinerators:
|
||
|
||
**Incinerator Specs:**
|
||
- Capacity: 150 tons/day each (450 total)
|
||
- Temperature: 850-1,100°C (destroys toxins, complete combustion)
|
||
- Energy recovery: Steam turbine generators
|
||
- Current output: 18 MW electrical
|
||
|
||
Burn: Reject stream from sorting (non-recyclables)
|
||
- Contaminated plastics
|
||
- Mixed materials
|
||
- Soiled paper
|
||
- Anything that can't be recycled
|
||
|
||
Syngas: Partial combustion captures valuable gases
|
||
- CO, H2, CH4 → Can be burned for additional energy
|
||
- Or used as chemical feedstock
|
||
|
||
Emissions control is CRITICAL:
|
||
- Scrubbers remove acid gases (HCl, SO2)
|
||
- Filters capture particulates
|
||
- Activated carbon removes dioxins
|
||
- NOx reduction systems
|
||
|
||
buckets: [burn, syngas, emissions, chemistry, return, set_language]
|
||
|
||
transitions:
|
||
burn:
|
||
content_blocks:
|
||
- "You monitor the waste combustion process..."
|
||
next_section_and_step: "combustion_systems:combustion_process"
|
||
|
||
syngas:
|
||
content_blocks:
|
||
- "You optimize syngas capture and utilization..."
|
||
next_section_and_step: "combustion_systems:syngas_optimization"
|
||
|
||
emissions:
|
||
content_blocks:
|
||
- "You examine emissions control systems..."
|
||
next_section_and_step: "combustion_systems:emissions_control"
|
||
|
||
chemistry:
|
||
content_blocks:
|
||
- "You balance the combustion chemistry equations..."
|
||
next_section_and_step: "combustion_systems:combustion_chemistry"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
- step_id: "combustion_process"
|
||
title: "Waste Combustion"
|
||
question: "Today's reject stream is 58 tons (non-recyclable waste). Optimize combustion for energy or complete destruction of toxins?"
|
||
tokens_for_ai: "Categorize: 'energy', 'destruction', 'balanced'"
|
||
feedback_tokens_for_ai: |
|
||
Combustion trade-offs:
|
||
|
||
**Energy Optimization (850°C):**
|
||
- Maximum energy recovery
|
||
- Lower fuel costs
|
||
- Risk: Some toxic compounds may survive
|
||
|
||
**Complete Destruction (1,100°C):**
|
||
- Destroys all organic toxins, dioxins, PCBs
|
||
- Safer emissions
|
||
- Cost: Uses more fuel, lower efficiency
|
||
|
||
**Balanced Approach (950-1,000°C):**
|
||
- Good energy recovery
|
||
- Effective toxin destruction
|
||
- Optimal for most waste
|
||
|
||
buckets: [energy, destruction, balanced, set_language]
|
||
|
||
transitions:
|
||
energy:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX optimizes for maximum energy:
|
||
|
||
Temperature: 850°C
|
||
Waste combusted: 58 tons
|
||
Energy generated: 22.3 MWh
|
||
Efficiency: 28% (thermal to electrical)
|
||
|
||
Result: High energy output, good economics
|
||
|
||
But: Emissions slightly elevated (still within limits)
|
||
|
||
Santos: "More power = more revenue. Good choice if emissions are clean."
|
||
metadata_add:
|
||
energy_output: "n+22.3"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
destruction:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX prioritizes complete toxin destruction:
|
||
|
||
Temperature: 1,100°C
|
||
Waste combusted: 58 tons
|
||
Energy generated: 18.7 MWh (lower due to fuel consumption)
|
||
Emissions: Ultra-clean (all toxins destroyed)
|
||
|
||
Result: Environmental excellence, slightly lower profit
|
||
|
||
Santos: "The planet thanks you, VERTEX. Clean is good."
|
||
metadata_add:
|
||
energy_output: "n+18.7"
|
||
environmental_impact: "excellent"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
balanced:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX chooses the balanced approach:
|
||
|
||
Temperature: 975°C
|
||
Waste combusted: 58 tons
|
||
Energy generated: 20.8 MWh
|
||
Emissions: Clean (within all regulations)
|
||
|
||
Result: Good energy, good environment, good economics
|
||
|
||
Santos: "Smart balance, VERTEX. Best of both worlds."
|
||
metadata_add:
|
||
energy_output: "n+20.8"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:combustion_process"
|
||
|
||
- step_id: "syngas_optimization"
|
||
title: "Syngas Capture & Utilization"
|
||
question: "Syngas from partial combustion contains valuable gases. How do you want to use it? (burn for power, sell as chemical feedstock, or store for later)"
|
||
tokens_for_ai: "Categorize: 'power', 'feedstock', 'store'"
|
||
feedback_tokens_for_ai: |
|
||
Syngas composition:
|
||
- CO (carbon monoxide): 25%
|
||
- H2 (hydrogen): 15%
|
||
- CH4 (methane): 8%
|
||
- CO2: 45%
|
||
- N2: 7%
|
||
|
||
Uses:
|
||
- Burn for additional electricity (most common)
|
||
- Sell to chemical plants (Fischer-Tropsch synthesis, methanol production)
|
||
- Store for peak pricing
|
||
|
||
Today's syngas production: 14,200 m³
|
||
|
||
buckets: [power, feedstock, store, set_language]
|
||
|
||
transitions:
|
||
power:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX burns syngas for power:
|
||
|
||
Syngas combustion:
|
||
- Volume: 14,200 m³
|
||
- Energy content: ~3.2 MWh
|
||
- Additional power generated: 3.2 MWh
|
||
|
||
Total facility output: 18 + 3.2 = 21.2 MW
|
||
|
||
Revenue: $384 (at $120/MWh)
|
||
|
||
VERTEX: "Syngas adds ~15% to our power output. Not bad for
|
||
what would otherwise be wasted."
|
||
metadata_add:
|
||
energy_output: "n+3.2"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
feedstock:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX sells syngas to chemical manufacturers:
|
||
|
||
Syngas sold: 14,200 m³
|
||
Price: $0.08/m³ (chemical feedstock premium)
|
||
Revenue: $1,136
|
||
|
||
Compared to burning for power: $384
|
||
|
||
Profit increase: $752 (nearly 3x more!)
|
||
|
||
Note: Requires contract with chemical plant
|
||
|
||
VERTEX: "Chemical companies pay more than electricity markets.
|
||
Syngas is worth more as feedstock than fuel."
|
||
|
||
Santos: "Good business thinking, VERTEX!"
|
||
metadata_add:
|
||
revenue_today: "n+1136"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
store:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX stores syngas for later use:
|
||
|
||
Storage tanks: 14,200 m³ compressed
|
||
Use case: Burn during peak electricity pricing
|
||
|
||
Off-peak price: $120/MWh (now)
|
||
Peak price: $340/MWh (evening)
|
||
|
||
Strategy: Store now, generate power during peak = 2.8x revenue
|
||
|
||
VERTEX: "Arbitrage opportunity. Syngas is energy storage.
|
||
Sell power when prices are highest."
|
||
metadata_add:
|
||
syngas_stored: "n+14200"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:syngas_optimization"
|
||
|
||
- step_id: "emissions_control"
|
||
title: "Emissions Control Systems"
|
||
content_blocks:
|
||
- "You monitor the emissions control systems:"
|
||
- ""
|
||
- "**Scrubbers:** Removing 99.2% of acid gases (HCl, SO2)"
|
||
- "**Baghouse Filters:** Capturing 99.8% of particulates"
|
||
- "**Activated Carbon:** Adsorbing dioxins and furans"
|
||
- "**SCR System:** Reducing NOx by 85%"
|
||
- ""
|
||
- "Emissions well below regulatory limits. Stack monitoring shows clean exhaust."
|
||
- "Environmental compliance: EXCELLENT"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
- step_id: "combustion_chemistry"
|
||
title: "Balance Combustion Equation"
|
||
classifier_model: "MODEL_2" # Qwen for chemistry calculations
|
||
feedback_model: "MODEL_2" # Qwen for detailed chemistry feedback
|
||
question: "Balance this waste combustion equation: C6H10O5 (cellulose) + O2 → CO2 + H2O + Energy. What are the coefficients?"
|
||
tokens_for_ai: |
|
||
User is balancing combustion chemistry.
|
||
|
||
Cellulose (paper/cardboard) combustion:
|
||
C6H10O5 + O2 → CO2 + H2O
|
||
|
||
Must balance C, H, O atoms.
|
||
|
||
Answer: C6H10O5 + 6O2 → 6CO2 + 5H2O
|
||
|
||
Check:
|
||
- C: 6 = 6 ✓
|
||
- H: 10 = 10 ✓
|
||
- O: 5 + 12 = 12 + 5 = 17 ✓
|
||
|
||
Categorize: 'correct', 'incorrect', 'hint'
|
||
|
||
feedback_tokens_for_ai: |
|
||
Combustion chemistry:
|
||
|
||
Balanced equation: C6H10O5 + 6O2 → 6CO2 + 5H2O + 2,820 kJ/mol
|
||
|
||
Energy released: 2,820 kJ per mole of cellulose
|
||
This heat drives the steam turbines!
|
||
|
||
If user correct: Praise chemistry skills
|
||
If incorrect: Guide them to balance
|
||
|
||
buckets: [correct, incorrect, hint, set_language]
|
||
|
||
transitions:
|
||
correct:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Perfect! Equation balanced correctly!
|
||
|
||
C6H10O5 + 6O2 → 6CO2 + 5H2O + Energy
|
||
|
||
This is the chemistry powering our facility.
|
||
Cellulose (paper, cardboard) burns cleanly to produce CO2, water, and heat.
|
||
|
||
Heat → Steam → Turbine → Electricity!
|
||
|
||
VERTEX: "Chemistry mastery achieved. Understanding the reactions
|
||
allows me to optimize combustion efficiency."
|
||
metadata_add:
|
||
chemistry_mastery: "n+1"
|
||
next_section_and_step: "combustion_systems:incinerator_control"
|
||
|
||
incorrect:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Not quite balanced. Count the atoms on each side.
|
||
|
||
C: How many carbon atoms before and after?
|
||
H: How many hydrogen atoms?
|
||
O: Oxygen is tricky - count carefully!
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:combustion_chemistry"
|
||
|
||
hint:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Hint:
|
||
- C6H10O5 has 6 carbons → need 6 CO2
|
||
- C6H10O5 has 10 hydrogens → need 5 H2O (since each H2O has 2 H)
|
||
- Now count oxygen atoms and balance with O2
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:combustion_chemistry"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "combustion_systems:combustion_chemistry"
|
||
|
||
# ============================================================================
|
||
# SECTION: MATERIALS RECOVERY - Precious metals and value extraction
|
||
# ============================================================================
|
||
- section_id: "materials_recovery"
|
||
title: "Materials Recovery Operations"
|
||
steps:
|
||
- step_id: "recovery_hub"
|
||
title: "Recovery Control Center"
|
||
question: "You're managing materials recovery. What would you like to focus on? (precious_metals, rare_earths, copper, aluminum, or market_analysis)"
|
||
tokens_for_ai: "Categorize: 'precious', 'rare_earths', 'copper', 'aluminum', 'market', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
Materials recovery is where the money is made!
|
||
|
||
Today's recovery (estimated):
|
||
- Gold: 1.2 kg (~$75,000)
|
||
- Silver: 12.4 kg (~$9,000)
|
||
- Palladium: 0.8 kg (~$24,000)
|
||
- Platinum: 0.3 kg (~$9,000)
|
||
- Copper: 32 tons (~$275,000)
|
||
- Aluminum: 18 tons (~$43,000)
|
||
- Rare earths: 67 kg (~$12,000)
|
||
|
||
Total value: ~$447,000/day from materials recovery!
|
||
|
||
buckets: [precious, rare_earths, copper, aluminum, market, return, set_language]
|
||
|
||
transitions:
|
||
precious:
|
||
next_section_and_step: "materials_recovery:precious_metals"
|
||
|
||
rare_earths:
|
||
next_section_and_step: "materials_recovery:rare_earth_recovery"
|
||
|
||
copper:
|
||
next_section_and_step: "materials_recovery:copper_recovery"
|
||
|
||
aluminum:
|
||
next_section_and_step: "materials_recovery:aluminum_recovery"
|
||
|
||
market:
|
||
next_section_and_step: "economics:materials_market"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
- step_id: "precious_metals"
|
||
title: "Precious Metal Recovery"
|
||
question: "You're extracting precious metals from e-waste. Circuit boards are rich in gold. What recovery method? (chemical, electrolysis, smelting, or all)"
|
||
tokens_for_ai: "Categorize: 'chemical', 'electrolysis', 'smelting', 'all'"
|
||
feedback_tokens_for_ai: |
|
||
Precious metal recovery methods:
|
||
|
||
**Chemical Leaching:**
|
||
- Dissolve metals with acids/cyanide
|
||
- Selective extraction
|
||
- Environmental concerns (toxic chemicals)
|
||
- Recovery rate: 90-95%
|
||
|
||
**Electrolysis:**
|
||
- Electrochemical separation
|
||
- Very pure product (99.99%)
|
||
- High electricity cost
|
||
- Recovery rate: 95-98%
|
||
|
||
**Smelting:**
|
||
- High-temperature furnace
|
||
- Melts and separates by density
|
||
- Requires flux materials
|
||
- Recovery rate: 85-90%
|
||
|
||
**All (Sequential):**
|
||
- Smelt → Chemical refine → Electrolysis
|
||
- Maximum purity (99.999%)
|
||
- Highest cost
|
||
- Recovery rate: 98-99%
|
||
|
||
buckets: [chemical, electrolysis, smelting, all, set_language]
|
||
|
||
transitions:
|
||
chemical:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX uses chemical leaching:
|
||
|
||
Process:
|
||
1. Crush circuit boards to powder
|
||
2. Leach with acid (HCl + H2O2 for copper, aqua regia for gold)
|
||
3. Precipitate metals selectively
|
||
4. Filter and wash
|
||
|
||
Today's yield:
|
||
- Gold: 1.14 kg (95% recovery, 99.5% purity)
|
||
- Silver: 11.8 kg
|
||
- Palladium: 0.76 kg
|
||
|
||
Cost: $4,200 (chemicals, processing)
|
||
Revenue: $108,000
|
||
Profit: $103,800
|
||
|
||
Environmental: Toxic waste stream requires treatment
|
||
|
||
VERTEX: "Chemical leaching is efficient but generates hazardous waste.
|
||
We need proper treatment systems."
|
||
metadata_add:
|
||
gold_purity: "99.5"
|
||
toxic_waste: "n+800"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
electrolysis:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX uses electrolytic refining:
|
||
|
||
Process:
|
||
1. Dissolve metals in electrolyte
|
||
2. Apply voltage
|
||
3. Pure metal plates out on cathode
|
||
4. Impurities fall as sludge
|
||
|
||
Today's yield:
|
||
- Gold: 1.17 kg (97.5% recovery, 99.99% purity!)
|
||
- Silver: 12.1 kg (99.98% purity)
|
||
- Palladium: 0.78 kg (99.95% purity)
|
||
|
||
Cost: $6,800 (electricity, electrolyte)
|
||
Revenue: $120,000 (premium for high purity!)
|
||
Profit: $113,200
|
||
|
||
VERTEX: "Electrolysis produces ultra-pure metals. Buyers pay
|
||
premium prices. Worth the extra cost."
|
||
metadata_add:
|
||
gold_purity: "99.99"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
smelting:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX smelts the e-waste:
|
||
|
||
Process:
|
||
1. Feed circuit boards to furnace (1,200°C)
|
||
2. Metals melt and separate by density
|
||
3. Gold/platinum sink (heavy)
|
||
4. Copper/aluminum float (lighter)
|
||
5. Slag off impurities
|
||
|
||
Today's yield:
|
||
- Gold: 1.02 kg (85% recovery, 98% purity)
|
||
- Silver: 10.5 kg
|
||
- Mixed metals: 2.1 kg (needs further refining)
|
||
|
||
Cost: $3,400 (fuel, flux)
|
||
Revenue: $95,000
|
||
Profit: $91,600
|
||
|
||
Note: Lower recovery but simple process
|
||
|
||
VERTEX: "Smelting is fast and simple but leaves value on the table.
|
||
We should upgrade to get that missing 15%."
|
||
metadata_add:
|
||
gold_purity: "98"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
all:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX uses the full sequential process:
|
||
|
||
Process:
|
||
1. Smelt (bulk separation)
|
||
2. Chemical refine (remove impurities)
|
||
3. Electrolysis (ultra-pure final product)
|
||
|
||
Today's yield:
|
||
- Gold: 1.19 kg (99% recovery, 99.999% purity!)
|
||
- Silver: 12.3 kg (99.999% purity)
|
||
- Palladium: 0.79 kg (99.99% purity)
|
||
- Platinum: 0.29 kg (99.99% purity)
|
||
|
||
Cost: $11,400 (all processes)
|
||
Revenue: $135,000 (premium for 5-nines purity!)
|
||
Profit: $123,600 (highest!)
|
||
|
||
VERTEX: "Maximum recovery. Maximum purity. Maximum value.
|
||
This is how you extract every dollar from waste."
|
||
|
||
Santos: "Expensive process, but the profit speaks for itself."
|
||
metadata_add:
|
||
gold_purity: "99.999"
|
||
gold_recovered_today: "n+1190"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "materials_recovery:precious_metals"
|
||
|
||
- step_id: "rare_earth_recovery"
|
||
title: "Rare Earth Element Recovery"
|
||
content_blocks:
|
||
- "You process rare earth magnets from motors and speakers..."
|
||
- "Neodymium, dysprosium, and praseodymium are strategic materials with limited supply."
|
||
- ""
|
||
- "**Today's Recovery:**"
|
||
- "- Neodymium: 45 kg (~$11,000)"
|
||
- "- Dysprosium: 8 kg (~$2,400)"
|
||
- "- Praseodymium: 12 kg (~$1,800)"
|
||
- ""
|
||
- "These materials are critical for wind turbines, electric vehicles, and electronics."
|
||
- "China controls 80% of global supply. Urban mining reduces dependence."
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
- step_id: "copper_recovery"
|
||
title: "Copper Recovery Operations"
|
||
content_blocks:
|
||
- "Copper is everywhere: wires, motors, plumbing, circuit boards."
|
||
- ""
|
||
- "**Today's Copper Recovery:**"
|
||
- "- From cables: 28 tons (98% pure)"
|
||
- "- From motors: 4.2 tons (99% pure - windings)"
|
||
- "- From e-waste: 2.8 tons (95% pure - mixed)"
|
||
- "- Total: 35 tons copper"
|
||
- ""
|
||
- "Market price: $8,600/ton"
|
||
- "**Revenue: $301,000 just from copper today!**"
|
||
- ""
|
||
- "VERTEX: 'Copper is the backbone of our revenue. Consistent, valuable, always in demand.'"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
- step_id: "aluminum_recovery"
|
||
title: "Aluminum Recovery"
|
||
content_blocks:
|
||
- "Aluminum cans are the highest-value recyclable after precious metals."
|
||
- ""
|
||
- "**Today's Aluminum:**"
|
||
- "- Cans: 18 tons"
|
||
- "- Cables: 4 tons"
|
||
- "- Appliance parts: 3.8 tons"
|
||
- "- Total: 25.8 tons"
|
||
- ""
|
||
- "Fun fact: Recycling aluminum uses 95% less energy than producing from bauxite ore!"
|
||
- "Revenue: ~$62,000 from aluminum today"
|
||
next_section_and_step: "materials_recovery:recovery_hub"
|
||
|
||
# ============================================================================
|
||
# SECTION: SMELTING & REFINEMENT - Producing 99.9%+ pure materials
|
||
# ============================================================================
|
||
# ============================================================================
|
||
# ============================================================================
|
||
- section_id: "smelting_systems"
|
||
title: "Smelting & Materials Refinement"
|
||
steps:
|
||
- step_id: "furnace_control"
|
||
title: "Smelting Furnace Operations"
|
||
question: "You control 2 smelting furnaces. What would you like to smelt? (metals, glass, slag_recovery, or upgrade_furnace)"
|
||
tokens_for_ai: "Categorize: 'metals', 'glass', 'slag', 'upgrade', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
Smelting is the final step in materials refinement!
|
||
|
||
**Current Furnaces (Level 1):**
|
||
- Arc furnace #1: Metals (1,200°C max)
|
||
- Arc furnace #2: Metals/glass (1,400°C max)
|
||
- Purity achieved: 98-99%
|
||
|
||
**Upgrade Available (Level 2):**
|
||
- Induction furnace: Precise temperature control
|
||
- Vacuum furnace: Ultra-pure metals (99.99%)
|
||
- Oxygen lance: Remove impurities
|
||
- Purity potential: 99.9-99.999%
|
||
|
||
buckets: [metals, glass, slag, upgrade, return, set_language]
|
||
|
||
transitions:
|
||
metals:
|
||
next_section_and_step: "smelting_systems:metal_smelting"
|
||
|
||
glass:
|
||
next_section_and_step: "smelting_systems:glass_smelting"
|
||
|
||
slag:
|
||
next_section_and_step: "smelting_systems:slag_recovery"
|
||
|
||
upgrade:
|
||
next_section_and_step: "facility_upgrades:smelter_upgrades"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
- step_id: "metal_smelting"
|
||
title: "Metal Smelting Process"
|
||
question: "You're smelting today's recovered metals. Choose priority: (maximize_purity, maximize_throughput, or balance)"
|
||
tokens_for_ai: "Categorize: 'purity', 'throughput', 'balance'"
|
||
feedback_tokens_for_ai: |
|
||
Metal smelting trade-offs:
|
||
|
||
**Maximize Purity:**
|
||
- Multiple refining passes
|
||
- Slow process
|
||
- Higher costs (fuel, time)
|
||
- Result: 99.5-99.9% pure
|
||
- Price premium: +15-25%
|
||
|
||
**Maximize Throughput:**
|
||
- Single pass
|
||
- Fast processing
|
||
- Lower purity: 97-98%
|
||
- Higher volume processed
|
||
- Standard market price
|
||
|
||
**Balanced:**
|
||
- Two refining passes
|
||
- Good purity: 99-99.2%
|
||
- Reasonable speed
|
||
- Best profit optimization
|
||
|
||
buckets: [purity, throughput, balance, set_language]
|
||
|
||
transitions:
|
||
purity:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX prioritizes ultra-pure metals:
|
||
|
||
**Smelting Process (Multi-pass):**
|
||
1. Primary smelt: Melt all metals (1,200°C)
|
||
2. Flux treatment: Remove oxides and sulfides
|
||
3. Secondary refine: Re-melt with carbon reduction
|
||
4. Oxygen lance: Blow out remaining impurities
|
||
5. Inert atmosphere cool: Prevent re-oxidation
|
||
|
||
**Results:**
|
||
- Copper: 32 tons → 31.2 tons (99.7% pure)
|
||
- Aluminum: 25 tons → 24.5 tons (99.6% pure)
|
||
- Gold: 1.2 kg (99.95% pure)
|
||
- Silver: 12.4 kg (99.9% pure)
|
||
|
||
**Economics:**
|
||
- Processing time: 18 hours (slow!)
|
||
- Fuel cost: $8,400
|
||
- Loss to slag: 3.2%
|
||
- Premium price: +22%
|
||
- Revenue: $412,000
|
||
- Profit: $403,600
|
||
|
||
VERTEX: "Maximum purity achieved. Buyers pay premium for quality.
|
||
These metals will sell above market rate."
|
||
|
||
Miller: "Time-consuming, but the premium is worth it."
|
||
metadata_add:
|
||
metal_purity: "99.7"
|
||
smelting_skill: "n+1"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
throughput:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX optimizes for volume:
|
||
|
||
**Smelting Process (Single-pass):**
|
||
1. Bulk smelt: Melt everything together (1,150°C)
|
||
2. Density separation: Metals separate by weight
|
||
3. Skim and cast
|
||
|
||
**Results:**
|
||
- Copper: 32 tons → 30.4 tons (97.2% pure)
|
||
- Aluminum: 25 tons → 23.8 tons (97.8% pure)
|
||
- Gold: 1.2 kg (98.5% pure)
|
||
- Mixed metals: 4.2 tons (needs re-processing)
|
||
|
||
**Economics:**
|
||
- Processing time: 6 hours (fast!)
|
||
- Fuel cost: $3,100
|
||
- Loss to slag: 5.8%
|
||
- Standard market price
|
||
- Revenue: $338,000
|
||
- Profit: $334,900
|
||
|
||
VERTEX: "Fast processing, high volume. Lower margins but less time and cost."
|
||
metadata_add:
|
||
metal_purity: "97.5"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
balance:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX balances purity and speed:
|
||
|
||
**Smelting Process (Two-pass):**
|
||
1. Primary smelt with flux
|
||
2. Secondary refine of high-value metals only
|
||
|
||
**Results:**
|
||
- Copper: 32 tons → 31.0 tons (99.2% pure)
|
||
- Aluminum: 25 tons → 24.2 tons (98.8% pure)
|
||
- Gold: 1.2 kg (99.8% pure) ← Extra refining!
|
||
- Silver: 12.4 kg (99.7% pure) ← Extra refining!
|
||
|
||
**Economics:**
|
||
- Processing time: 11 hours
|
||
- Fuel cost: $5,200
|
||
- Loss to slag: 4.1%
|
||
- Slight premium: +8%
|
||
- Revenue: $389,000
|
||
- Profit: $383,800
|
||
|
||
VERTEX: "Optimal balance. Premium purity for high-value metals,
|
||
standard for bulk materials. Smart resource allocation."
|
||
|
||
Santos: "This is the sweet spot, VERTEX. Good thinking."
|
||
metadata_add:
|
||
metal_purity: "99"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "smelting_systems:metal_smelting"
|
||
|
||
- step_id: "glass_smelting"
|
||
title: "Glass Recycling & Smelting"
|
||
content_blocks:
|
||
- "You smelt recycled glass into new glass products..."
|
||
- ""
|
||
- "**Process:**"
|
||
- "1. Sort by color (clear, green, brown)"
|
||
- "2. Crush to cullet (small pieces)"
|
||
- "3. Remove contaminants (labels, caps)"
|
||
- "4. Smelt at 1,400°C"
|
||
- "5. Form into new bottles or fiberglass"
|
||
- ""
|
||
- "**Today's Glass:**"
|
||
- "- Clear: 14 tons → Revenue $1,120 (sells to bottlers)"
|
||
- "- Green: 5 tons → Revenue $340"
|
||
- "- Brown: 3 tons → Revenue $210"
|
||
- ""
|
||
- "Glass can be recycled infinitely without quality loss!"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
- step_id: "slag_recovery"
|
||
title: "Slag Material Recovery"
|
||
question: "Slag contains valuable metals trapped in waste. Process it for additional recovery? (yes/no)"
|
||
tokens_for_ai: "Categorize: 'yes', 'no'"
|
||
feedback_tokens_for_ai: |
|
||
Slag is the waste product from smelting.
|
||
It contains trapped metal particles that didn't fully separate.
|
||
|
||
Typical slag: 1-3% metal content (copper, aluminum, precious metals)
|
||
|
||
Recovery options:
|
||
- Re-smelt the slag (costs fuel but recovers more metal)
|
||
- Sell as aggregate (construction material)
|
||
- Landfill (wasted potential)
|
||
|
||
buckets: [yes, no, set_language]
|
||
|
||
transitions:
|
||
yes:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX re-processes the slag:
|
||
|
||
**Slag Analysis:**
|
||
- Volume: 2.8 tons
|
||
- Estimated metal content: 2.3% (64 kg)
|
||
|
||
**Recovery Process:**
|
||
- Re-smelt at 1,300°C with reducing agents
|
||
- Separate metal particles
|
||
- New slag is cleaner
|
||
|
||
**Results:**
|
||
- Copper recovered: 42 kg (~$360)
|
||
- Aluminum recovered: 18 kg (~$43)
|
||
- Precious metals: 4 grams gold (~$250)
|
||
- Total value: $653
|
||
|
||
Processing cost: $280 (fuel, labor)
|
||
Net profit: $373
|
||
|
||
VERTEX: "Every gram counts. We extracted value from what others call waste.
|
||
This is the UNWASTE philosophy."
|
||
|
||
SORTY-5: "We found treasure in the garbage's garbage!"
|
||
metadata_add:
|
||
slag_processed: "n+2.8"
|
||
zero_waste_score: "n+1"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
no:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX sells slag as construction aggregate:
|
||
|
||
Slag properties:
|
||
- Hard, durable
|
||
- Good for road base, concrete aggregate
|
||
- Low value but easy sale
|
||
|
||
Sale price: $45/ton
|
||
Revenue: 2.8 tons × $45 = $126
|
||
|
||
Note: Metals in slag are lost forever (value left on table)
|
||
|
||
VERTEX: "Quick revenue but not maximizing value. We should consider
|
||
slag processing upgrades in the future."
|
||
metadata_add:
|
||
slag_sold: "n+2.8"
|
||
next_section_and_step: "smelting_systems:furnace_control"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "smelting_systems:slag_recovery"
|
||
|
||
# ============================================================================
|
||
# SECTION: ENVIRONMENTAL SYSTEMS - Microplastic removal & pollution control
|
||
# ============================================================================
|
||
- section_id: "environmental_systems"
|
||
title: "Environmental Protection Systems"
|
||
steps:
|
||
- step_id: "microplastic_removal"
|
||
title: "Microplastic Filtration"
|
||
question: "Your advanced filtration system removes microplastics from water. Check system performance or upgrade filters?"
|
||
tokens_for_ai: "Categorize: 'performance', 'upgrade', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
Microplastic filtration is CRITICAL!
|
||
|
||
Microplastics are tiny plastic particles (<5mm) that:
|
||
- Pollute water systems
|
||
- Enter food chain
|
||
- Accumulate in animals and humans
|
||
- Major environmental threat
|
||
|
||
UNWASTE Factory has advanced filtration:
|
||
- Multi-stage filtration down to 1 micron
|
||
- Removes 99.4% of microplastics from process water
|
||
- Captured plastics are burned or recycled
|
||
|
||
buckets: [performance, upgrade, return, set_language]
|
||
|
||
transitions:
|
||
performance:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
**Microplastic Filtration Performance:**
|
||
|
||
**Water Processed Today:**
|
||
- Process water: 4,200 m³
|
||
- Microplastic content (input): 820 mg/L (heavily contaminated!)
|
||
- Microplastic content (output): 5 mg/L (99.4% removal!)
|
||
|
||
**Microplastics Captured:**
|
||
- Total mass: 3,423 kg
|
||
- Fiber plastics: 1,840 kg (from textiles)
|
||
- Fragment plastics: 982 kg (from degraded products)
|
||
- Bead plastics: 601 kg (from personal care products)
|
||
|
||
**Disposal:**
|
||
- Burned for energy: 2,100 kg → 9.4 MWh
|
||
- Sent to chemical recycling: 1,323 kg
|
||
|
||
**Environmental Impact:**
|
||
- Microplastics prevented from entering waterways: 3.4 TONS!
|
||
- Fish, wildlife, humans protected
|
||
|
||
VERTEX: "We're not just processing waste. We're protecting the planet.
|
||
3.4 tons of microplastics removed from the water cycle TODAY."
|
||
|
||
Santos: "This is why we do what we do, VERTEX."
|
||
metadata_add:
|
||
microplastics_removed_kg: "n+3423"
|
||
environmental_score: "n+10"
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
upgrade:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
**Filter Upgrade Options:**
|
||
|
||
**Option 1: Ultrafiltration Membranes**
|
||
- Cost: $85,000
|
||
- Removes particles down to 0.1 micron
|
||
- Captures 99.8% of microplastics
|
||
- Higher maintenance cost
|
||
|
||
**Option 2: Electrocoagulation Pre-treatment**
|
||
- Cost: $62,000
|
||
- Aggregates microplastics into larger particles
|
||
- Easier to filter
|
||
- 99.6% removal rate
|
||
|
||
**Option 3: Both (Ultimate System)**
|
||
- Cost: $135,000
|
||
- 99.9% removal rate
|
||
- Near-zero microplastic discharge
|
||
- Become industry leader
|
||
|
||
Which upgrade do you want?
|
||
next_section_and_step: "environmental_systems:filter_upgrades"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
- step_id: "filter_upgrades"
|
||
title: "Upgrade Filtration System"
|
||
question: "Choose your upgrade: (ultrafiltration, electrocoagulation, both, or cancel)"
|
||
tokens_for_ai: "Categorize: 'ultrafiltration', 'electrocoagulation', 'both', 'cancel'"
|
||
feedback_tokens_for_ai: |
|
||
Each upgrade has trade-offs:
|
||
|
||
Ultrafiltration: Best removal, highest cost
|
||
Electrocoagulation: Lower cost, good removal
|
||
Both: Ultimate performance, expensive
|
||
Cancel: Keep current system
|
||
|
||
buckets: [ultrafiltration, electrocoagulation, both, cancel, set_language]
|
||
|
||
transitions:
|
||
ultrafiltration:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX upgrades to ultrafiltration membranes!
|
||
|
||
**Installation:**
|
||
- Cost: $85,000
|
||
- Installation time: 2 weeks
|
||
- Membrane lifespan: 3 years
|
||
|
||
**New Performance:**
|
||
- Filtration: 0.1 micron (was 1 micron)
|
||
- Removal rate: 99.8% (was 99.4%)
|
||
- Microplastic discharge: 1.6 mg/L (was 5 mg/L)
|
||
|
||
**ROI:**
|
||
- Environmental credits: $18,000/year
|
||
- Payback: 4.7 years
|
||
- Plus: Huge environmental benefit!
|
||
|
||
VERTEX: "Upgraded. We're now removing 99.8% of microplastics.
|
||
This facility is a model for environmental responsibility."
|
||
metadata_add:
|
||
facility_level: "n+0.5"
|
||
microplastic_removal_rate: "99.8"
|
||
budget: "n-85000"
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
electrocoagulation:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX installs electrocoagulation pre-treatment!
|
||
|
||
**System:**
|
||
- Electrodes create coagulant ions
|
||
- Microplastics clump together
|
||
- Easier to filter
|
||
|
||
**New Performance:**
|
||
- Removal rate: 99.6% (was 99.4%)
|
||
- Microplastic discharge: 3.3 mg/L (was 5 mg/L)
|
||
- Lower filter maintenance (larger particles)
|
||
|
||
**ROI:**
|
||
- Cost: $62,000
|
||
- Electricity cost: $12/day
|
||
- Filter cost savings: $8,000/year
|
||
- Payback: 7.75 years
|
||
|
||
VERTEX: "Smart upgrade. Better performance, lower operating costs."
|
||
metadata_add:
|
||
facility_level: "n+0.3"
|
||
microplastic_removal_rate: "99.6"
|
||
budget: "n-62000"
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
both:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX goes all-in on environmental protection!
|
||
|
||
**Ultimate Filtration System:**
|
||
- Electrocoagulation + Ultrafiltration
|
||
- Cost: $135,000
|
||
- Best-in-class performance
|
||
|
||
**New Performance:**
|
||
- Removal rate: 99.9%
|
||
- Microplastic discharge: 0.8 mg/L
|
||
- Industry-leading environmental protection
|
||
|
||
**Recognition:**
|
||
- EPA excellence award
|
||
- Green certification premium
|
||
- Media coverage: "UNWASTE Factory Sets New Standard"
|
||
|
||
**ROI:**
|
||
- Environmental credits: $24,000/year
|
||
- Green premium contracts: $18,000/year
|
||
- Payback: 3.2 years
|
||
|
||
VERTEX: "We're not just a waste facility anymore. We're environmental leaders.
|
||
99.9% microplastic removal. No one else is doing this."
|
||
|
||
Santos: "Expensive, but we're making a real difference, VERTEX."
|
||
metadata_add:
|
||
facility_level: "n+1"
|
||
microplastic_removal_rate: "99.9"
|
||
environmental_leader: "true"
|
||
budget: "n-135000"
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
cancel:
|
||
content_blocks:
|
||
- "Upgrade cancelled. Current system remains operational."
|
||
next_section_and_step: "environmental_systems:microplastic_removal"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "environmental_systems:filter_upgrades"
|
||
|
||
# ============================================================================
|
||
# SECTION: FACILITY UPGRADES - Tech tree and progression
|
||
# ============================================================================
|
||
- section_id: "facility_upgrades"
|
||
title: "Facility Upgrade Center"
|
||
steps:
|
||
- step_id: "upgrade_center"
|
||
title: "Upgrade Tech Tree"
|
||
question: "Review available upgrades. Current facility level: metadata.facility_level. What interests you? (sorting, smelting, energy, automation, or check_tree)"
|
||
tokens_for_ai: "Categorize: 'sorting', 'smelting', 'energy', 'automation', 'tree', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
UNWASTE Factory progression system!
|
||
|
||
**Current Level:** metadata.facility_level (starts at 1)
|
||
|
||
**Upgrade Paths:**
|
||
|
||
**Sorting Technology:**
|
||
- Level 1: Basic optical sorting (94% accuracy) ← You are here
|
||
- Level 2: AI vision + hyperspectral (97% accuracy) [$120k]
|
||
- Level 3: Quantum sensors (99% accuracy) [$450k]
|
||
|
||
**Smelting & Refining:**
|
||
- Level 1: Arc furnaces (99% purity) ← You are here
|
||
- Level 2: Induction + vacuum (99.9% purity) [$280k]
|
||
- Level 3: Plasma arc + zone refining (99.999% purity) [$890k]
|
||
|
||
**Energy Systems:**
|
||
- Level 1: Basic incinerators (18 MW) ← You are here
|
||
- Level 2: Advanced combustion + heat recovery (28 MW) [$340k]
|
||
- Level 3: Plasma gasification (42 MW + synfuels) [$1.2M]
|
||
|
||
**Automation:**
|
||
- Level 1: Semi-automated (36 robots) ← You are here
|
||
- Level 2: Fully automated sorting (120 robots) [$550k]
|
||
- Level 3: AI swarm intelligence (250 robots) [$1.8M]
|
||
|
||
Upgrades require: Money + facility_level + sometimes materials
|
||
|
||
buckets: [sorting, smelting, energy, automation, tree, return, set_language]
|
||
|
||
transitions:
|
||
sorting:
|
||
next_section_and_step: "facility_upgrades:sorting_upgrades"
|
||
|
||
smelting:
|
||
next_section_and_step: "facility_upgrades:smelter_upgrades"
|
||
|
||
energy:
|
||
next_section_and_step: "facility_upgrades:energy_upgrades"
|
||
|
||
automation:
|
||
next_section_and_step: "facility_upgrades:automation_upgrades"
|
||
|
||
tree:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
**UNWASTE FACTORY TECH TREE:**
|
||
|
||
```
|
||
Level 1 (Basic) ← Current
|
||
├─ Sorting: Optical (94%)
|
||
├─ Smelting: Arc furnace (99%)
|
||
├─ Energy: Incinerators (18MW)
|
||
└─ Automation: Semi-auto (36 robots)
|
||
|
||
Level 2 (Advanced) - Requires $1.29M total
|
||
├─ Sorting: AI+Hyperspectral (97%) [$120k]
|
||
├─ Smelting: Induction+Vacuum (99.9%) [$280k]
|
||
├─ Energy: Advanced combustion (28MW) [$340k]
|
||
└─ Automation: Full auto (120 robots) [$550k]
|
||
|
||
Level 3 (Elite) - Requires $4.34M total
|
||
├─ Sorting: Quantum sensors (99%) [$450k]
|
||
├─ Smelting: Plasma+Zone (99.999%) [$890k]
|
||
├─ Energy: Plasma gasification (42MW) [$1.2M]
|
||
└─ Automation: AI swarm (250 robots) [$1.8M]
|
||
```
|
||
|
||
**Your Progress:**
|
||
- Current level: metadata.facility_level
|
||
- Upgrades completed: [list from metadata]
|
||
- Budget available: metadata.budget
|
||
- Next recommended upgrade: [suggest based on needs]
|
||
|
||
VERTEX: "The path to zero waste is through continuous improvement."
|
||
counts_as_attempt: false
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
- step_id: "sorting_upgrades"
|
||
title: "Sorting Technology Upgrades"
|
||
question: "Upgrade sorting systems? (level2_ai_vision for $120k, level3_quantum for $450k, or cancel)"
|
||
tokens_for_ai: "Categorize: 'level2', 'level3', 'cancel'"
|
||
feedback_tokens_for_ai: |
|
||
Sorting upgrades improve accuracy and revenue.
|
||
|
||
Better sorting = More recyclables recovered = Higher profit
|
||
|
||
Level 2 is affordable, good improvement
|
||
Level 3 is expensive but near-perfect
|
||
|
||
buckets: [level2, level3, cancel, set_language]
|
||
|
||
transitions:
|
||
level2:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX upgrades to Level 2 AI Vision + Hyperspectral!
|
||
|
||
**Installed:**
|
||
- AI vision: Deep learning material recognition
|
||
- Hyperspectral imaging: Chemical fingerprinting
|
||
- 94 upgraded cameras
|
||
|
||
**Performance:**
|
||
- Accuracy: 94% → 97% (+3%)
|
||
- New materials detected: Biodegradables, composites, medical waste
|
||
- Speed: 92 → 105 items/minute
|
||
|
||
**Economics:**
|
||
- Cost: $120,000
|
||
- Increased recovery: ~15 tons/day more recyclables
|
||
- Additional revenue: ~$85,000/month
|
||
- Payback: 1.4 months!
|
||
|
||
VERTEX: "Upgrade complete. We're now sorting materials we couldn't even
|
||
identify before. Revenue increase pays for this in 6 weeks."
|
||
|
||
Miller: "These new cameras are incredible. They see things I can't."
|
||
metadata_add:
|
||
sorting_level: "2"
|
||
sorting_accuracy: "97"
|
||
facility_level: "n+0.3"
|
||
budget: "n-120000"
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
level3:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
Check if facility_level is high enough and budget sufficient.
|
||
|
||
If yes:
|
||
VERTEX upgrades to Level 3 Quantum Sensors!
|
||
|
||
**Revolutionary Technology:**
|
||
- Quantum entanglement sensors
|
||
- Molecular-level material identification
|
||
- AI processes at quantum speed
|
||
|
||
**Performance:**
|
||
- Accuracy: 97% → 99%
|
||
- Identifies materials by atomic structure
|
||
- Speed: 105 → 142 items/minute
|
||
|
||
**New Capabilities:**
|
||
- Detects trace contaminants (PPM level)
|
||
- Identifies alloy composition instantly
|
||
- Predicts material degradation state
|
||
|
||
**Economics:**
|
||
- Cost: $450,000
|
||
- Revenue increase: $180,000/month
|
||
- Payback: 2.5 months
|
||
- Industry-leading sorting
|
||
|
||
VERTEX: "We've achieved near-perfect sorting. This is the future.
|
||
Competitors can't match this."
|
||
|
||
If no: "Insufficient funds or facility level too low. Need upgrades first."
|
||
metadata_add:
|
||
sorting_level: "3"
|
||
sorting_accuracy: "99"
|
||
facility_level: "n+1"
|
||
budget: "n-450000"
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
cancel:
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "facility_upgrades:sorting_upgrades"
|
||
|
||
- step_id: "smelter_upgrades"
|
||
title: "Smelting Technology Upgrades"
|
||
content_blocks:
|
||
- "Smelter upgrade options:"
|
||
- "- Level 2: Induction + Vacuum furnaces → 99.9% purity [$280k]"
|
||
- "- Level 3: Plasma arc + Zone refining → 99.999% purity [$890k]"
|
||
- ""
|
||
- "Higher purity = Premium prices from buyers"
|
||
- "99.999% 'five-nines' purity commands 40% price premium!"
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
- step_id: "energy_upgrades"
|
||
title: "Energy Generation Upgrades"
|
||
content_blocks:
|
||
- "Energy system upgrades:"
|
||
- "- Level 2: Advanced combustion + heat recovery → 28 MW [$340k]"
|
||
- "- Level 3: Plasma gasification → 42 MW + synfuels [$1.2M]"
|
||
- ""
|
||
- "Plasma gasification can convert ANY waste to syngas"
|
||
- "Even hazardous materials can be safely destroyed and converted to energy"
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
- step_id: "automation_upgrades"
|
||
title: "Automation Technology Upgrades"
|
||
content_blocks:
|
||
- "Automation upgrades:"
|
||
- "- Level 2: Fully automated sorting → 120 robots [$550k]"
|
||
- "- Level 3: AI swarm intelligence → 250 robots [$1.8M]"
|
||
- ""
|
||
- "AI swarm: Robots coordinate autonomously, learn from each other"
|
||
- "Reduce labor costs, increase efficiency, 24/7 operations"
|
||
next_section_and_step: "facility_upgrades:upgrade_center"
|
||
|
||
# ============================================================================
|
||
# SECTION: ECONOMICS - Market analysis and value optimization
|
||
# ============================================================================
|
||
- section_id: "economics"
|
||
title: "Economics & Market Analysis"
|
||
steps:
|
||
- step_id: "market_analysis"
|
||
title: "Materials Market Analysis"
|
||
classifier_model: "MODEL_1" # Hermes for categorization
|
||
feedback_model: "MODEL_2" # Qwen for market calculations and predictions
|
||
question: "You monitor global materials markets. What do you want to analyze? (prices, trends, sell_timing, or arbitrage)"
|
||
tokens_for_ai: "Categorize: 'prices', 'trends', 'timing', 'arbitrage', 'return'"
|
||
feedback_tokens_for_ai: |
|
||
VERTEX tracks commodity markets in real-time!
|
||
|
||
Materials prices fluctuate daily:
|
||
- Copper: $8,200-8,800/ton
|
||
- Aluminum: $2,300-2,600/ton
|
||
- Gold: $60,000-65,000/kg
|
||
- Lithium: $14,000-18,000/ton
|
||
|
||
Smart timing = Maximum profit!
|
||
|
||
Can store materials and sell when prices peak.
|
||
Can predict market trends using AI.
|
||
|
||
buckets: [prices, trends, timing, arbitrage, return, set_language]
|
||
|
||
transitions:
|
||
prices:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
**Current Market Prices (Real-time):**
|
||
|
||
**Metals:**
|
||
- Copper: $8,620/ton (↑ 2.3% today)
|
||
- Aluminum: $2,480/ton (↓ 0.8% today)
|
||
- Steel: $720/ton (→ stable)
|
||
- Stainless: $2,140/ton (↑ 1.2%)
|
||
|
||
**Precious Metals:**
|
||
- Gold: $62,400/kg (↑ 0.5%)
|
||
- Silver: $728/kg (↑ 1.8%)
|
||
- Palladium: $30,200/kg (↓ 3.2%)
|
||
- Platinum: $30,800/kg (↑ 0.9%)
|
||
|
||
**Battery Materials:**
|
||
- Lithium: $16,200/ton (↑ 4.1% - HIGH DEMAND!)
|
||
- Cobalt: $31,000/ton (↑ 2.7%)
|
||
- Nickel: $18,400/ton (↑ 1.5%)
|
||
|
||
**Rare Earths:**
|
||
- Neodymium: $245/kg (→ stable)
|
||
- Dysprosium: $298/kg (↑ 0.7%)
|
||
|
||
VERTEX: "Lithium prices are surging. EV demand is driving the market.
|
||
We should prioritize battery recovery."
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
trends:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX analyzes market trends using AI:
|
||
|
||
**90-Day Predictions:**
|
||
|
||
**Copper:** ↑ Bullish
|
||
- Forecast: $9,200/ton (+6.7%)
|
||
- Drivers: Construction boom, EVs need copper
|
||
|
||
**Lithium:** ↑↑ Very Bullish
|
||
- Forecast: $21,000/ton (+29.6%)
|
||
- Drivers: Battery gigafactories, limited supply
|
||
|
||
**Aluminum:** → Neutral
|
||
- Forecast: $2,520/ton (+1.6%)
|
||
- Drivers: Recycling supply increasing
|
||
|
||
**Gold:** ↑ Slightly Bullish
|
||
- Forecast: $64,800/kg (+3.8%)
|
||
- Drivers: Economic uncertainty, safe haven
|
||
|
||
**Strategic Recommendation:**
|
||
1. Stockpile lithium and cobalt (prices rising fast)
|
||
2. Sell aluminum soon (price peaking)
|
||
3. Hold copper for 60 days (gradual rise)
|
||
4. Gold stable - sell as recovered
|
||
|
||
VERTEX: "My predictive models suggest lithium stockpiling.
|
||
Prices will be 30% higher in 3 months."
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
timing:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX optimizes sell timing:
|
||
|
||
**Today's Inventory:**
|
||
- Copper: 245 tons
|
||
- Aluminum: 187 tons
|
||
- Lithium: 2.4 tons
|
||
- Gold: 12.3 kg
|
||
|
||
**AI Recommendation:**
|
||
|
||
**SELL NOW:**
|
||
- Aluminum (187 tons) → $463,760
|
||
Reason: Price at 90-day peak, about to decline
|
||
|
||
**HOLD 30 DAYS:**
|
||
- Copper (245 tons) → Projected +$147,000 gain
|
||
Reason: Rising trend, peak in 4-6 weeks
|
||
|
||
**HOLD 90 DAYS:**
|
||
- Lithium (2.4 tons) → Projected +$11,520 gain
|
||
Reason: Strong uptrend, supply shortage
|
||
|
||
**SELL NOW:**
|
||
- Gold (12.3 kg) → $767,520
|
||
Reason: Price stable, no storage benefit
|
||
|
||
Total potential arbitrage gain: $158,520 by optimizing timing
|
||
|
||
VERTEX: "Market timing is how we extract maximum value.
|
||
This is the difference between profit and MAXIMUM profit."
|
||
|
||
Santos: "I trust your analysis, VERTEX. Execute the strategy."
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
arbitrage:
|
||
ai_feedback:
|
||
tokens_for_ai: |
|
||
VERTEX identifies arbitrage opportunities:
|
||
|
||
**Opportunity 1: Regional Price Differences**
|
||
- Local copper price: $8,620/ton
|
||
- Export market (Asia): $9,040/ton
|
||
- Spread: $420/ton
|
||
- Inventory: 245 tons
|
||
- Potential gain: $102,900 (minus $18,000 shipping)
|
||
- Net arbitrage: $84,900
|
||
|
||
**Opportunity 2: Form Factor Premium**
|
||
- Copper wire scrap: $8,200/ton
|
||
- Refined copper ingots: $8,920/ton
|
||
- Spread: $720/ton
|
||
- Process cost: $340/ton
|
||
- Net gain: $380/ton
|
||
- For 245 tons: $93,100 extra profit
|
||
|
||
**Opportunity 3: Purity Premium**
|
||
- 99% pure gold: $62,400/kg
|
||
- 99.99% pure gold: $64,900/kg
|
||
- Spread: $2,500/kg
|
||
- Refining cost: $800/kg
|
||
- Net gain: $1,700/kg
|
||
- For 12.3 kg: $20,910 extra
|
||
|
||
Total arbitrage potential: $198,910
|
||
|
||
VERTEX: "These are market inefficiencies. We can exploit them
|
||
for nearly $200k additional profit. This is financial optimization."
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
return:
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
- step_id: "materials_market"
|
||
title: "Materials Trading"
|
||
content_blocks:
|
||
- "You execute trades on the materials market..."
|
||
- "Buy low, sell high. Store materials when prices are depressed."
|
||
- "Sell when markets peak. This is value extraction mastery."
|
||
next_section_and_step: "economics:market_analysis"
|
||
|
||
# ============================================================================
|
||
# SECTION: CHALLENGES - Random difficulties
|
||
# ============================================================================
|
||
- section_id: "challenges"
|
||
title: "Operational Challenges"
|
||
steps:
|
||
- step_id: "handle_challenge"
|
||
title: "Challenge Response"
|
||
question: "CHALLENGE: metadata.challenge_type. How do you respond?"
|
||
tokens_for_ai: |
|
||
Random challenge based on metadata.challenge_type:
|
||
|
||
- contaminated_load: Hazardous waste mixed in
|
||
- equipment_failure: Critical equipment breaks
|
||
- toxic_waste_alert: Dangerous materials detected
|
||
- market_crash: Commodity prices crash
|
||
- regulatory_inspection: Surprise inspection
|
||
|
||
Categorize response: 'immediate_action', 'analyze', 'consult_team', 'safety_first'
|
||
|
||
feedback_tokens_for_ai: |
|
||
Describe challenge dramatically.
|
||
Show VERTEX's decision-making under pressure.
|
||
Consequences depend on response.
|
||
|
||
buckets: [immediate_action, analyze, consult_team, safety_first, set_language]
|
||
|
||
transitions:
|
||
immediate_action:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX acts decisively to resolve challenge. Describe outcome."
|
||
metadata_add:
|
||
challenges_handled: "n+1"
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
analyze:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX analyzes the situation before acting. Sometimes good, sometimes too slow."
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
consult_team:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX consults human experts. Team collaboration resolves issue."
|
||
metadata_add:
|
||
team_trust: "high"
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
safety_first:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX prioritizes safety over profit. Always the right call."
|
||
metadata_add:
|
||
safety_record: "excellent"
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "challenges:handle_challenge"
|
||
|
||
# ============================================================================
|
||
# SECTION: OPPORTUNITIES - Random beneficial events
|
||
# ============================================================================
|
||
- section_id: "opportunities"
|
||
title: "Business Opportunities"
|
||
steps:
|
||
- step_id: "handle_opportunity"
|
||
title: "Opportunity Assessment"
|
||
question: "OPPORTUNITY: metadata.opportunity_type. Take advantage of it?"
|
||
tokens_for_ai: "Categorize: 'yes', 'negotiate', 'decline'"
|
||
feedback_tokens_for_ai: |
|
||
Opportunities can be profitable!
|
||
|
||
- high_value_ewaste: Server farm decommissioning (gold mine!)
|
||
- bulk_contract: Long-term supply agreement
|
||
- grant_available: Government research funding
|
||
- technology_breakthrough: New process discovered
|
||
- premium_buyer: Luxury brand wants recycled materials
|
||
|
||
Each has potential reward and some risk/cost.
|
||
|
||
buckets: [yes, negotiate, decline, set_language]
|
||
|
||
transitions:
|
||
yes:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX seizes opportunity! Describe windfall/benefit."
|
||
metadata_add:
|
||
opportunities_seized: "n+1"
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
negotiate:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX negotiates better terms. Smart business!"
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
decline:
|
||
ai_feedback:
|
||
tokens_for_ai: "VERTEX declines. Sometimes the smart move if risky."
|
||
next_section_and_step: "control_center:operations_hub"
|
||
|
||
set_language:
|
||
metadata_add:
|
||
language: "the-users-response"
|
||
counts_as_attempt: false
|
||
next_section_and_step: "opportunities:handle_opportunity"
|