Furnace Group Strategy Documentation¶

Overview¶

The technology strategy system for furnace groups operates through a two-function architecture that separates economic analysis from strategic decision-making:

Economic Analysis Engine: `optimal_technology_name()`¶

The optimal_technology_name function in the FurnaceGroup class is a critical economic analysis component that evaluates the financial viability of technology transitions in steel production facilities. It is a pure analytical function that returns economic metrics without making decisions or modifying any state. It performs a comprehensive Net Present Value (NPV) analysis by:

Calculating the Cost of Stranded Assets (COSA) for abandoning current technology
Evaluating NPV for each allowed technology transition
Accounting for subsidies, carbon costs, and operational differences
Comparing greenfield (new) vs brownfield (retrofit) installations

Strategic Decision Orchestrator: `evaluate_furnace_group_strategy()`¶

The evaluate_furnace_group_strategy function in the Plant class is the strategic decision-maker that uses NPV analysis to make investment decisions, thereby modifying the state of furnace groups. It:

Calls optimal_technology_name() to obtain economic analysis
Applies business logic (affordability checks, capacity limits, risk assessment)
Makes strategic decisions based on economic and operational constraints
Generates actionable commands (renovate, switch technologies, or close facilities)
Updates plant balance sheets to reflect investment costs

Architecture: How the Functions Interact¶

evaluate_furnace_group_strategy (Plant)
  │
  ├─> Stage 1-4: Pre-flight checks
  │   ├─> Check plant financial health
  │   ├─> Check furnace group status
  │   ├─> Evaluate forced closure
  │   └─> Filter allowed transitions
  │
  ├─> Stage 5: Call optimal_technology_name (FurnaceGroup)
  │   │
  │   │   [Economic Analysis - No Decisions Made]
  │   │   ├─> Calculate COSA
  │   │   ├─> Evaluate NPV for each allowed technology
  │   │   │   ├─> Brownfield (renovation): reduced capex
  │   │   │   └─> Greenfield (new tech): full capex + COSA penalty
  │   │   └─> Return: NPV dict, CAPEX dict, COSA, BOM dict
  │   │
  │   └─< Returns economic metrics
  │
  ├─> Stage 6-8: Analyze results
  │   ├─> Check if any option is profitable
  │   ├─> Identify optimal technology
  │   └─> Select technology (weighted random or deterministic)
  │
  ├─> Stage 9-10: Execute decision path
  │   ├─> Path A: Renovation (same tech, lifetime expired)
  │   └─> Path B: Technology switch (different tech)
  │
  ├─> Stage 11-12: Final checks
  │   ├─> Probabilistic adoption filter
  │   └─> Capacity limit enforcement
  │
  └─> Stage 13: Return command
      ├─> RenovateFurnaceGroup
      ├─> ChangeFurnaceGroupTechnology
      ├─> CloseFurnaceGroup
      └─> None (no action)

Part 1: Economic Analysis¶

Overview¶

Function: FurnaceGroup.optimal_technology_name

Purpose: Pure NPV calculation and economic evaluation - determines the optimal technology by comparing economic returns across all allowed technology transitions.

Key Characteristics:

No decisions made - only returns economic metrics
No side effects - does not modify any state
Comprehensive evaluation - calculates NPV for all allowed transitions
COSA-adjusted - accounts for stranded asset costs when switching

High-Level Workflow:

Start
  │
  ├─> Stage 1: Initialize and import dependencies
  │
  ├─> Stage 2: Prepare Operating Expenses List and Calculate Operating Subsidies
  │
  ├─> Stage 3: Calculate Carbon Costs for Current Technology and Combine with Subsidised OPEX
  │
  ├─> Stage 4: Calculate Cost of Stranded Assets (COSA)
  │
  ├─> Stage 5: Check for allowed technology transitions
  │     └─> If no transitions allowed: Return empty results
  │
  ├─> Stage 6-9: For each allowed technology:
  │     ├─> Check if technology has capex data
  │     ├─> Check special requirements (e.g., BOF needs smelter)
  │     ├─> Branch A (Current Tech): Brownfield evaluation
  │     │     ├─> Apply brownfield capex reduction
  │     │     ├─> Use existing BOM and emissions
  │     │     └─> Calculate carbon costs
  │     ├─> Branch B (New Tech): Greenfield evaluation
  │     │     ├─> Fetch average BOM
  │     │     ├─> Match business cases
  │     │     ├─> Calculate new emissions
  │     │     └─> Calculate carbon costs
  │     ├─> Stage 8: Calculate NPV if valid BOM exists
  │     │     ├─> Apply subsidies (capex and opex)
  │     │     ├─> Calculate full NPV
  │     │     └─> Store results
  │     └─> Stage 9: Adjust NPV for COSA (if switching)
  │
  └─> Stage 10: Return results (NPVs, capex dict, COSA, BOMs)

Detailed Stage Breakdown¶

Stage 1: Initialize and Import Dependencies¶

Purpose: Set up logging and import required calculation functions
Debug prefix: [OPTIMAL TECHNOLOGY]:
Key actions:
- Log current furnace group state
- Import cost and emissions calculation functions
- Initialize return dictionaries

Stage 2: Prepare Operating Expenses List and Calculate Operating Subsidies¶

Purpose: Apply OPEX subsidies to the current OPEX value
Output: List of subsidised OPEX values by year for the period of remaining lifetime

Stage 3: Calculate Carbon Costs for Current Technology and Combine with Subsidised OPEX¶

Purpose: Determine carbon cost series for existing operations
Key decision: Use current emissions and chosen boundary
Inputs: Current emissions, carbon price series, emission boundary
Output: List of carbon costs over facility lifetime combined with list of subsidised OPEX values

Stage 4: Calculate Cost of Stranded Assets (COSA)¶

Purpose: Determine the cost of abandoning current technology
Key calculation: NPV of remaining debt + operating costs
Decision: COSA = max(calculated_COSA, remaining_debt)
Rationale: Must at minimum pay off remaining debt

Stage 5: Check for Allowed Technology Transitions¶

Decision point: Are transitions defined for current technology?
- If no: Return empty results (no switch possible)
- If yes: Continue to evaluation
Key check: allowed_furnace_transitions dictionary

Stage 6: Evaluate Each Allowed Technology¶

For each technology in allowed transitions:
- Decision 1: Does technology have capex data?
  - If no: Skip this technology
- Decision 2: Special requirements check
  - BOF requires smelter furnace
  - If not met: Skip this technology

Stage 7: Branch Based on Technology Type¶

Branch A: Current Technology (Brownfield)¶

Characteristics:
- Retrofit of existing facility
- Reduced capex (typically 20% of greenfield)
- Uses existing BOM and utilization rate
- Uses existing emissions profile
Key adjustments:
- Apply brownfield_capex_share multiplier
- Validate existing BOM structure

Branch B: New Technology (Greenfield)¶

Characteristics:
- Complete replacement with new technology
- Full capex cost
- Requires fetching average BOM
- Must calculate new emissions profile
Process:
1. Fetch average BOM for technology
2. Match business cases with BOM
3. Calculate emissions for new technology
4. Determine carbon costs based on new emissions

Stage 8: Calculate NPV¶

Prerequisite: Valid BOM must exist
Process:
1. Store BOM for technology
2. Get market price for product type
3. Calculate operating subsidies
4. Apply capex subsidies
5. Calculate full NPV including:
  - Capex (after subsidies)
  - Operating costs and revenues
  - Carbon costs
  - Debt service
Key parameters: Capacity, utilization, lifetime, financing costs

Stage 9: Adjust NPV for COSA¶

Decision: Is this a technology switch?
- If yes (tech != current): Subtract COSA from NPV
- If no (same tech): No COSA adjustment
Rationale: Switching technologies incurs stranded asset cost

Stage 10: Return Results¶

Outputs:
1. npv_dict: NPV values for each technology (COSA-adjusted)
2. npv_capex_dict: Effective capex after subsidies
3. cosa: Cost of Stranded Assets value
4. bom_dict: Bill of Materials for each technology

Key Dependencies and Interactions¶

External Functions Called¶

calculate_emissions_cost_series: Converts emissions to monetary costs
calculate_opex_subsidies: Determines operating subsidy values
stranding_asset_cost: Calculates COSA
get_bom_from_avg_boms: Retrieves average BOMs for technologies
materiall_bill_business_case_match: Matches feedstocks to BOMs
calculate_emissions: Computes emission profiles
calculate_capex_with_subsidies: Applies capital subsidies
calculate_variable_opex: Computes variable operating costs
calculate_npv_full: Performs complete NPV calculation

Data Dependencies¶

self.bill_of_materials: Current technology’s BOM
self.emissions: Current emission profile
self.lifetime: Facility lifetime information
self.debt_repayment_per_year: Debt service schedule
self.utilization_rate: Current capacity utilization
self.production: Current production volume

Input Parameters¶

Required Market Data¶

market_price_series: Product prices by type (steel, iron, etc.)
carbon_cost_series: Carbon prices over time
cost_of_debt: Interest rate on debt
cost_of_equity: Required return on equity

Technology Configuration¶

capex_dict: Capital costs by technology
capex_renovation_share: Retrofit cost multipliers (brownfield)
technology_fopex_dict: Fixed operating costs
allowed_furnace_transitions: Valid technology switches
dynamic_business_cases: Feedstock configurations

Subsidy Information¶

tech_capex_subsidies: Capital subsidies by technology
tech_opex_subsidies: Operating subsidies by technology
tech_debt_subsidies: Debt subsidies by technology

Common Issues and Debugging Tips¶

Issue 1: No Transitions Found¶

Symptom: Function returns empty NPV dictionary
Check: allowed_furnace_transitions contains current technology
Debug: Look for "NO TRANSITIONS ALLOWED" in logs

Issue 2: Technology Skipped¶

Symptom: Expected technology not in results
Possible causes:
- Missing capex data
- BOF without smelter
- Failed BOM retrieval
Debug: Look for "SKIPPING" messages in logs

Issue 3: Invalid BOM Structure¶

Symptom: Technology evaluation fails
Check: BOM contains both “materials” and “energy” keys
Debug: Look for "Invalid or missing BOM" warnings

Issue 4: Negative NPV After COSA¶

Symptom: All technologies show negative NPV
Explanation: COSA exceeds benefits of switching
Debug: Check COSA calculation and remaining debt

Part 2: Strategic Decision-Making¶

Overview¶

Function: Plant.evaluate_furnace_group_strategy

Purpose: Strategic decision orchestrator that uses NPV analysis to make investment decisions

Key Characteristics:

Makes decisions - determines which action to take
Has side effects - updates plant balance sheet
Business logic - applies affordability checks, capacity limits, probabilistic adoption
Command generation - returns executable commands for the simulation

Decision Workflow

The function follows a 13-stage workflow from pre-flight checks through command generation:

Stage 1-4: Pre-Flight Checks
  ├─> Plant financial health
  ├─> Furnace group status
  ├─> Forced closure evaluation
  └─> Technology transition filtering

Stage 5: Economic Analysis
  └─> Call optimal_technology_name() → Get NPV analysis

Stage 6-8: Results Analysis
  ├─> Check profitability (any NPV > 0?)
  ├─> Identify optimal technology
  └─> Technology selection (weighted random or deterministic)

Stage 9-10: Decision Execution
  ├─> Renovation path (if best tech = current tech)
  └─> Technology switch path (if best tech ≠ current tech)

Stage 11-13: Final Checks & Command Generation
  ├─> Probabilistic adoption filter
  ├─> Capacity limit enforcement
  └─> Generate command (Renovate/Switch/Close/None)

Detailed Stage Breakdown¶

Stage 1: Check Plant Financial Health¶

Decision: Can the plant afford to invest?

Check: plant.balance >= 0
If negative: Return None (no action possible)
Rationale: Negative balance = no capital available for investment

Stage 2: Check Furnace Group Status¶

Decision: Is the furnace group eligible for strategy evaluation?

Check: Status is not “operating pre-retirement”
If pre-retirement: Return None (already scheduled to close)
Rationale: Don’t invest in facilities about to close

Stage 3: Check for Forced Closure¶

Decision: Have accumulated losses exceeded write-off threshold?

Threshold calculation: CAPEX × capacity
Check: furnace_group.historic_balance < -threshold
If exceeded: Return CloseFurnaceGroup command
Rationale: Losses too great - better to close than continue operating

Example:

CAPEX: $800/tonne
Capacity: 5,000,000 tonnes (5 Mt)
Threshold: -$4,000,000,000
Historic balance: -$4,500,000,000 → Close

Stage 4: Filter Allowed Technology Transitions¶

Purpose: Narrow down technology options based on what’s allowed in the current year

Process: Intersect allowed_techs[current_year] with allowed_furnace_transitions[current_tech]
Example:
- Current tech: BF-BOF
- All possible transitions: [BF-BOF, EAF, DRI-EAF, H2-DRI-EAF]
- Allowed in 2030: [BF-BOF, EAF, DRI-EAF] (H2-DRI-EAF not yet available)
- Filtered transitions: [BF-BOF, EAF, DRI-EAF]

Stage 5: Calculate NPV for All Technology Options¶

Key Action: Call furnace_group.optimal_technology_name() to get economic analysis

Inputs passed to analysis engine:

Market price forecasts
Technology costs (CAPEX, OPEX, financing)
Bill of materials function
Carbon cost projections
Subsidy configurations

Outputs received:

tech_npv_dict: NPV for each technology (already COSA-adjusted)
npv_capex_dict: Subsidized CAPEX for each technology
cosa: Cost of stranded assets
bom_dict: Bills of materials for each technology

Stage 6: Check if Any Technology Option is Profitable¶

Decision: Is investing worthwhile?

Check: max(tech_npv_dict.values()) > 0
If all NPVs ≤ 0: Return None (no profitable option exists)
Rationale: Don’t invest if all options lose money

Stage 7: Identify Optimal Technology¶

Process: Find technology with highest NPV

Calculation: optimal_tech = max(tech_npv_dict, key=tech_npv_dict.get)
Check: Is current technology already optimal?
- is_current_best = (current_tech == optimal_tech)

Stage 8: Technology Selection¶

Decision Mode: Weighted random (realistic) or deterministic (pure optimization)

If Current Tech is NOT Optimal:¶

Weighted Random Selection (when probabilistic_agents=True):

Purpose: Model real-world decision uncertainty and strategic preferences
Process:
1. Filter out invalid NPVs (NaN, infinite)
2. Calculate weights: weight = max(NPV, 0) (negative NPVs get zero weight)
3. Randomly select technology with probability ∝ NPV
Example:
- BF-BOF: NPV = $5M → weight = 5M → 37% selection probability
- EAF: NPV = $8.5M → weight = 8.5M → 63% selection probability
- DRI-EAF: NPV = -$1M → weight = 0 → 0% selection probability

If Current Tech IS Optimal:¶

Selection: Keep current technology

Stage 9: Handle Renovation Scenario¶

Condition: Best technology = current technology AND lifetime expired

Decision Path:

Calculate renovation cost:
- CAPEX = subsidized renovation CAPEX from NPV analysis
- Cost = CAPEX × capacity × equity_share
Affordability check:
- If renovation_cost > plant.balance → Return CloseFurnaceGroup
- Rationale: Can’t afford to renovate, must close
Execute renovation:
- Deduct cost from plant balance: plant.balance -= renovation_cost
- Return RenovateFurnaceGroup command

Example Calculation:

Subsidized renovation CAPEX: $160/tonne
Capacity: 5 Mt
Equity share: 30%
Renovation cost: $160 × 5,000,000 × 0.30 = $240,000,000
Plant balance: $300,000,000 → Affordable, renovate

Stage 10: Handle Technology Switch Scenario¶

Condition: Best technology ≠ current technology

Process:

Calculate switching cost:
- CAPEX = subsidized greenfield CAPEX from NPV analysis
- Cost = CAPEX × capacity × equity_share
Affordability check:
- If switch_cost > plant.balance → Return None
- Rationale: Can’t afford to switch
Continue to probabilistic adoption (Stage 11)

Example Calculation:

Subsidized greenfield CAPEX: $650/tonne
Capacity: 5 Mt
Equity share: 30%
Switch cost: $650 × 5,000,000 × 0.30 = $975,000,000
Plant balance: $1,200,000,000 → Affordable, proceed

Stage 11: Probabilistic Adoption Decision¶

Purpose: Model real-world hesitation in technology adoption (financing risk, permit delays, market uncertainty)

Formula:

acceptance_probability = exp(-switch_cost / NPV)

Interpretation:

Higher cost relative to benefit → Lower probability
Cost << NPV → High probability (close to 100%)
Cost ≈ NPV → Moderate probability (≈37%)
Cost >> NPV → Low probability (close to 0%)

Example:

Switch cost: $975M
NPV: $8.5M
Ratio: 975 / 8.5 = 114.7
Acceptance probability: exp(-114.7) ≈ 0% (very unlikely)

Alternative Example (more favorable):

Switch cost: $100M
NPV: $200M
Ratio: 100 / 200 = 0.5
Acceptance probability: exp(-0.5) ≈ 61%

Decision Process:

Calculate acceptance probability
Draw random number (0-1)
If random_draw < acceptance_probability AND furnace has no CCS/CCU → Proceed to Stage 12
Otherwise → Return None (probabilistic rejection)

Special Case: Furnaces with CCS/CCU equipment are never switched (representing significant sunk investment)

Stage 12: Check Capacity Limits¶

Purpose: Enforce annual capacity expansion limits (supply chain constraints)

Context:

Total annual capacity is limited (default: 100 Mt for both steel and iron)
Limit is split between:
- New plants: Greenfield facilities (handled by Geospatial Model)
- Expansions & switches: Capacity added to existing plants (handled by PAM)

Calculation:

total_installed_capacity = installed_capacity_in_year(product)  # All new capacity this year
new_plant_capacity = new_plant_capacity_in_year(product)        # Greenfield only
expansion_and_switch_capacity = total - new_plant_capacity      # Existing plants

if expansion_and_switch_capacity + furnace_capacity > expansion_limit:
    BLOCKED

Example:

Product: Steel
Total expansion limit for steel: 100 Mt/year
New plant share: 40% → New plant limit: 40 Mt, Expansion/switch limit: 60 Mt
Current new expansion/switch capacity already installed this year: 55 Mt
Furnace capacity to switch: 8 Mt
Total after switch: 55 + 8 = 63 Mt > 60 Mt → BLOCKED

If within limits: Proceed to Stage 13

Stage 13: Execute Technology Switch¶

Final Actions:

Update plant balance: plant.balance -= switch_cost
Generate command: Return ChangeFurnaceGroupTechnology

Command includes:

Technology change details (old → new)
Economic metrics (NPV, COSA)
Cost details (CAPEX with/without subsidies, cost of debt)
Technical details (BOM, utilization, capacity)
Subsidy configurations

Command Types Returned¶

1. `RenovateFurnaceGroup`¶

When: Current tech optimal AND lifetime expired AND affordable
Includes: Renovation CAPEX, subsidies, cost of debt

2. `ChangeFurnaceGroupTechnology`¶

When: Different tech selected AND affordable AND passes probability filter AND within capacity limits
Includes: Full technology switch details, NPV, COSA, BOM, subsidies

3. `CloseFurnaceGroup`¶

When:
- Forced closure (historic losses exceed threshold)
- Cannot afford renovation when lifetime expired
Includes: Plant ID and furnace group ID

4. `None`¶

When:
- Plant has negative balance
- Furnace group pre-retirement
- All NPVs negative or zero
- Cannot afford switch
- Probabilistic rejection
- Capacity limit exceeded
- Current tech optimal but lifetime not expired

Data Dependencies¶

For Strategic Decisions (`evaluate_furnace_group_strategy`)¶

plant.balance: Available capital for investment
furnace_group.status: Operating status
furnace_group.historic_balance: Cumulative profit/loss
furnace_group.lifetime.expired: Whether renovation is needed
furnace_group.has_ccs_or_ccu: CCS/CCU equipment flag

External Functions Called¶

furnace_group.optimal_technology_name(): Gets NPV analysis
filter_active_subsidies(): Filters subsidies by year
calculate_debt_with_subsidies(): Applies debt subsidies

Function Relationship Summary¶

Division of Responsibilities¶

Aspect	`optimal_technology_name()`	`evaluate_furnace_group_strategy()`
Role	Economic analyst	Strategic decision-maker
Question	“What are the economics?”	“What should we do?”
Type	Pure function (no side effects)	Impure function (updates state)
Returns	NPV dictionaries, COSA, BOMs	Command objects or None
Considers	Market prices, costs, subsidies	Affordability, risk, capacity limits
Modifies	Nothing	Plant balance sheet
Calls	Calculate_costs functions	optimal_technology_name()
Level	FurnaceGroup level	Plant level

Why This Architecture?¶

Separation of Concerns¶

Economic analysis is complex and reusable
Strategic decisions depend on context (plant finances, capacity limits, policy)
Separating them allows testing economics independently of business rules

Testability¶

Can test NPV calculations without mocking entire decision system
Can test decision logic with predetermined NPV inputs

Clarity¶

Clear distinction between “what’s optimal economically” and “what’s feasible practically”
Makes code easier to understand and maintain

Flexibility¶

Can change decision rules without touching NPV calculations
Can add new economic factors without changing decision logic

Key Metrics to Monitor¶

Economic Analysis Metrics¶

COSA vs NPV: If COSA > NPV, switch is unprofitable
Utilization rates: Lower utilization reduces NPV
Carbon cost impact: Rising carbon prices favor cleaner technologies
Subsidy effectiveness: Track NPV changes with/without subsidies
Brownfield advantage: Compare brownfield vs greenfield NPVs

Decision Metrics¶

Acceptance rate: % of positive-NPV switches actually executed
Capacity utilization: How close to annual limits
Rejection reasons: Categorize why switches don’t happen
Technology distribution: Which technologies are being adopted

Performance Indicators¶

Average NPV of executed switches: Quality of decisions
Renovation vs. switch ratio: Technology transition pace
Closure rate: Industry health indicator
Balance sheet health: Plant financial sustainability

Glossary¶

COSA: Cost of Stranded Assets - economic loss from abandoning existing technology (includes remaining debt and foregone profits)
NPV: Net Present Value - present value of future cash flows minus initial investment
BOM: Bill of Materials - resource requirements for production (materials and energy)
Brownfield: Retrofit/upgrade of existing facility (reduced CAPEX)
Greenfield: Complete new installation (full CAPEX)
CAPEX: Capital Expenditure - upfront investment cost
OPEX: Operating Expenditure - ongoing operational costs
FOPEX: Fixed Operating Expenditure - costs independent of production volume
VOPEX: Variable Operating Expenditure - costs that scale with production
Equity Share: Fraction of investment paid from company funds (vs. debt financing)
Utilization Rate: Actual production as percentage of capacity
Acceptance Probability: Likelihood of executing a switch given positive NPV (models risk aversion)

Furnace Group Strategy Documentation¶

Overview¶

Economic Analysis Engine: optimal_technology_name()¶

Strategic Decision Orchestrator: evaluate_furnace_group_strategy()¶

Architecture: How the Functions Interact¶

Part 1: Economic Analysis¶

Overview¶

Detailed Stage Breakdown¶

Stage 1: Initialize and Import Dependencies¶

Stage 2: Prepare Operating Expenses List and Calculate Operating Subsidies¶

Stage 3: Calculate Carbon Costs for Current Technology and Combine with Subsidised OPEX¶

Stage 4: Calculate Cost of Stranded Assets (COSA)¶

Stage 5: Check for Allowed Technology Transitions¶

Stage 6: Evaluate Each Allowed Technology¶

Stage 7: Branch Based on Technology Type¶

Branch A: Current Technology (Brownfield)¶

Branch B: New Technology (Greenfield)¶

Stage 8: Calculate NPV¶

Stage 9: Adjust NPV for COSA¶

Stage 10: Return Results¶

Key Dependencies and Interactions¶

External Functions Called¶

Data Dependencies¶

Input Parameters¶

Required Market Data¶

Technology Configuration¶

Subsidy Information¶

Common Issues and Debugging Tips¶

Issue 1: No Transitions Found¶

Issue 2: Technology Skipped¶

Issue 3: Invalid BOM Structure¶

Issue 4: Negative NPV After COSA¶

Part 2: Strategic Decision-Making¶

Overview¶

Detailed Stage Breakdown¶

Stage 1: Check Plant Financial Health¶

Stage 2: Check Furnace Group Status¶

Stage 3: Check for Forced Closure¶

Stage 4: Filter Allowed Technology Transitions¶

Stage 5: Calculate NPV for All Technology Options¶

Stage 6: Check if Any Technology Option is Profitable¶

Stage 7: Identify Optimal Technology¶

Stage 8: Technology Selection¶

If Current Tech is NOT Optimal:¶

If Current Tech IS Optimal:¶

Stage 9: Handle Renovation Scenario¶

Stage 10: Handle Technology Switch Scenario¶

Stage 11: Probabilistic Adoption Decision¶

Stage 12: Check Capacity Limits¶

Stage 13: Execute Technology Switch¶

Command Types Returned¶

1. RenovateFurnaceGroup¶

2. ChangeFurnaceGroupTechnology¶

3. CloseFurnaceGroup¶

4. None¶

Data Dependencies¶

For Strategic Decisions (evaluate_furnace_group_strategy)¶

External Functions Called¶

Function Relationship Summary¶

Division of Responsibilities¶

Why This Architecture?¶

Separation of Concerns¶

Testability¶

Clarity¶

Flexibility¶

Key Metrics to Monitor¶

Economic Analysis Metrics¶

Decision Metrics¶

Performance Indicators¶

Glossary¶

Economic Analysis Engine: `optimal_technology_name()`¶

Strategic Decision Orchestrator: `evaluate_furnace_group_strategy()`¶

1. `RenovateFurnaceGroup`¶

2. `ChangeFurnaceGroupTechnology`¶

3. `CloseFurnaceGroup`¶

4. `None`¶

For Strategic Decisions (`evaluate_furnace_group_strategy`)¶