Bottom-Up Cost Modelling
Author: Dr Andrzej M Kotas | ORCID: 0009-0009-5497-5384
Methodology Context: This cost benchmarking framework has been developed through 25+ years of steel industry consulting experience across feasibility studies, due diligence assessments, and competitive analysis projects. The methodology supports strategic decision-making for steel producers, investors, and industry analysts requiring accurate production cost assessment.
Key Terms
- Cash Cost
- Variable costs only — relevant for short-term operating decisions; excludes depreciation and fixed overheads
- Total Cost
- Full production cost including fixed costs — required for investment appraisal and competitive benchmarking
- Yield Loss
- Material lost during rolling as crop ends, scale, and cobbles — typically 2–5% in bar mills; recovered scrap generates a cost credit
- MHPT
- Man-Hours Per Tonne — labour productivity measure; benchmark for a 500kt rebar mill is approximately 1.25 MHPT
- Cold Charging
- Reheating ambient-temperature billet before rolling — consumes ~1.75 GJ/t versus ~1.2 GJ/t for hot charging
- SG&A
- Selling, General & Administrative costs — fixed overhead typically $7.50–$10/tonne at mill level
- Depreciation
- Capital recovery cost — for a $200/tonne investment with 20-year asset life, equals $10/tonne of production capacity
Overview
Steel cost benchmarking requires a systematic bottom-up approach that captures all major cost components while allowing for regional variations in input costs, technology levels, and operational practices. This methodology demonstrates cost calculation for a typical rebar mill, providing a template that can be adapted to other steel products and production routes.
The framework distinguishes between fixed and variable costs, enabling analysis of production economics at different capacity utilisation levels. This distinction is critical for strategic decisions regarding capacity additions, plant closures, or competitive positioning assessments. For frequently asked questions about steel production costs and broader context on cost components, see our steel production costs FAQ guide.
Model Scope and Product Specification
Product and Location Specifications
The cost model describes production of 12mm diameter commodity-grade deformed rebar as at early 2026. Calculations are shown per metric tonne for a typical size rebar mill at an unidentified location. This generic approach allows users to substitute location-specific input costs while maintaining the analytical framework.
The model assumes scrap cost of $350/tonne and billet cost of $450/tonne as baseline inputs. These prices should be adjusted to reflect actual market conditions or specific procurement arrangements when applying the methodology to real-world cases. The strategic implications of scrap pricing and availability — including how decarbonisation is reshaping scrap supply chains globally — are examined in the Steel Scrap Supply podcast episode.
Major Cost Components
Raw Materials
Billet Input: With approximately 3.5% yield loss, the billet input factor is 1.036 tonnes per tonne of finished product. At $450/tonne billet cost, this represents the largest variable cost component at $466.32/tonne.
Zero delivery costs are assumed for in-house manufactured billet, though external procurement would add freight charges.
Labour Costs
Productivity Assumptions: Model assumes mill capacity of 500kt/year operating at 90% utilisation (450kt output) with 270 employees, corresponding to productivity of 1.25 man-hours per tonne (MHPT).
Labour costs factor in social costs with net wage of $50k/year per blue collar employee plus 4% social cost, equating to gross labour cost of $25/hour. Of this, 25% is treated as fixed cost and 75% as variable.
Energy Costs
Natural Gas: Cold charging practice assumed with consumption of 1.75 GJ/tonne at $9.5/GJ, totaling $16.63/tonne. Hot charging would reduce this to approximately 1.2 GJ/tonne.
Electricity: Typical performance of 90 kWh/tonne at industrial rate of $0.09/kWh results in $8.10/tonne electricity cost.
Consumables
Work Rolls: Standard carbon steel rebar production incurs modest roll costs of approximately $2/tonne in well-managed mills. Costs increase significantly for smaller product sizes or hard steel grades.
Other Consumables: Lubricants, greases, and water collectively estimated at $1/tonne.
Scrap Credits
Yield losses generate scrap that can typically be recovered at 80% efficiency. With 2.9% steel recovery and scrap value of $350/tonne, this provides a credit of $10.16/tonne against total costs.
Fixed Costs
Depreciation: Assuming capital investment of $200/tonne capacity and 20-year asset lifetime, depreciation is $10/tonne.
SG&A Costs: Selling, general, and administrative costs vary by organisational structure but typically range $7.50-$10/tonne at mill level.
Fixed versus Variable Cost Allocation
The methodology explicitly separates fixed and variable costs to support different analytical purposes:
- Cash Cost Analysis: Relevant for short-term operating decisions, considering only variable costs of $507.33/tonne
- Total Cost Analysis: Required for long-term strategic decisions, investment evaluations, and competitive benchmarking, totaling $532.64/tonne
- Incremental Cost Analysis: Useful for pricing decisions on marginal production volumes
Labour cost allocation (25% fixed, 75% variable) reflects realistic flexibility where core workforce represents fixed overhead while additional shifts or contractors provide variable capacity. In the long run, all labour costs become variable.
Key Assumptions and Parameters
Yield and Material Flow
Yield Loss Assumptions: The model assumes approximately 3.5% yield loss, resulting in a billet input factor of 1.036 tonnes per tonne of finished product. Industry benchmarks suggest bar mill yield losses typically range from 2-5%, with well-managed operations achieving the lower end of this range.
Yield losses arise from crop-end removal, cobbles, and quality rejections; as well as from reheat furnace scale. Recovery of this scrap at 80% efficiency (2.9% of input tonnage) provides an important cost credit that should not be overlooked in cost modelling. EAF-based operations generate additional recoverable streams — slag, baghouse dust, and electrode stubs — whose value is often underestimated; the economics of these by-products are covered in the EAF By-Products podcast episode.
Labour Productivity and Costs
Capacity and Manning: The model assumes annual mill capacity of 500kt operating at 90% utilisation rate (450kt output) with workforce of 270 employees. Based on 52 weeks per year and 40-hour working weeks, this corresponds to productivity of 1.25 man-hours per tonne produced.
Compensation Structure: Labour costs incorporate social costs and benefits. Assuming net wage of $50,000/year per blue collar employee with modest social cost loading of 4%, total gross labour cost is $25/hour. This should be adjusted for specific locations considering local wage rates, social security requirements, and benefit packages.
Fixed/Variable Split: MCI typically assumes 25% of labour costs are fixed (core permanent workforce) and 75% variable (additional shifts, temporary workers, overtime). This allocation should be reconsidered for each specific case based on labour practices and union agreements.
Energy Consumption
Natural Gas Usage: Energy consumption depends significantly on charging practice. Cold charging typically requires 1.75 GJ/tonne compared to hot charging consumption of approximately 1.2 GJ/tonne. This 30% difference can materially impact production economics in high natural gas price environments.
Current model assumes cold charging practice with consumption of 1.75 GJ/tonne. Natural gas cost of $9.5/GJ corresponds to World Bank commodity price of $10/mmBTU (using conversion factor: 1 mmBTU = 1.05506 GJ).
Electricity: Power consumption of 90 kWh/tonne represents typical performance for medium-size bar mills. Actual consumption varies with mill configuration (continuous vs semi-continuous), number of rolling stands, reduction ratios, and product size range. Smaller sections require more energy per tonne due to additional rolling passes.
Industrial electricity price of $0.09/kWh reflects US Energy Information Administration data for industrial users including applicable taxes. This should be adjusted for specific locations as industrial rates vary significantly by region and may include demand charges, time-of-use pricing, or renewable energy surcharges.
Consumable Costs
Work Roll Costs: Roll costs of $2/tonne assume well-managed bar mill producing commodity carbon steel grades. These costs increase significantly with:
- Smaller product sizes (more passes, higher contact pressures per unit area)
- Hard steel grades (alloy steels, high-carbon grades increase wear)
- High reduction ratios
- Poorer roll quality or suboptimal rolling parameters
Other Consumables: Lubricants, greases, and water collectively estimated at $1/tonne. This is a relatively minor cost component but should be verified against actual plant records when available.
Capital Cost and Depreciation
Investment Basis: Capital investment assumption of $200/tonne capacity reflects typical bar mill equipment costs including reheating furnace, rolling mill stands, cooling beds, cutting equipment, and finishing facilities. Actual costs vary with:
- Mill capacity and configuration
- Level of automation
- Product size range capability
- Quality control equipment
- Regional cost variations for fabrication and installation
Depreciation Calculation: 20-year asset lifetime assumption is standard for steel rolling equipment. With capital cost of $200/tonne, annual depreciation is $10/tonne capacity. This calculation supports total cost analysis required for investment decisions and long-term strategic planning.
Whether depreciation should be included depends on analytical purpose. Cash cost analysis (relevant for short-term operating decisions) excludes depreciation, while total cost analysis (required for investment evaluations and competitive benchmarking) includes it.
Overhead Allocation
SG&A Costs: Selling, general, and administrative costs of $7.50/tonne represent typical allocation at mill level. Actual costs vary significantly depending on whether these expenses are:
- Allocated at mill level versus recognised as central overhead
- Including corporate functions (finance, legal, IT)
- Incorporating sales and marketing expenses
- Reflecting standalone versus integrated operations
Industry benchmarks suggest SG&A typically ranges $7.50-$10/tonne at mill level. Higher values may indicate corporate overhead allocation or standalone operations without economies of scale benefits.
Data Sources and Verification
Primary Data Sources
Yield Loss Benchmarks: Industry literature suggests bar mill yield losses of 2-5% depending on product mix and operational practices. The LinkedIn steel industry professional network reports typical range of 2-3%, while steel industry directories suggest approximately 5%. The model's 3.5% assumption represents conservative middle ground suitable for generic benchmarking.
Energy Prices: Natural gas prices obtained from the World Bank monthly commodity price database, which provides benchmark pricing in $/mmBTU. Electricity costs for industrial users sourced from US Energy Information Administration monthly energy review (Table 9.11), which tracks average revenue per kilowatt-hour by sector including applicable taxes.
Hot Charging Benefits: Analysis of hot charging impact on energy consumption documented in SteelOnTheNet hot charging insights article, demonstrating approximately 30% reduction in reheating energy requirements.
Capital Investment Costs: Equipment costs derived from MCI's proprietary capital investment database, covering bar rolling mills globally. Detailed bar mill capex analysis available at bar rolling mill capital costs page, showing typical investments near $200/tonne capacity.
Scrap Prices: Current scrap pricing obtained from Fastmarkets steel scrap price assessments or UN Comtrade database (HS code 720449) for imported scrap prices by destination market. These provide free access to historical price data enabling trend analysis and regional comparisons.
Sensitivity Analysis and Model Validation
Cost models should incorporate sensitivity analysis to understand impact of key variable changes on total production costs. Major sensitivity factors include:
- Raw Material Prices: Billet or scrap costs represent largest cost component, with 10% price change impacting total costs by approximately 8-9%
- Energy Costs: Natural gas price volatility can significantly impact costs, particularly for cold charging operations
- Capacity Utilisation: Fixed cost allocation changes dramatically with utilisation rate, affecting competitiveness during market downturns
- Labour Productivity: Manning levels and productivity directly impact per-tonne labour costs
Model validation should compare calculated costs against:
- Published cost curves from industry consultancies
- Company financial disclosures and investor presentations
- Regional market prices adjusted for profit margins
- Expert judgement based on plant visits and operational knowledge.
Applications and Use Cases
This cost benchmarking methodology supports multiple analytical applications:
- Competitive Positioning: Comparing production costs across different mills, technologies, or geographic regions to assess competitive advantages
- Investment Analysis: Evaluating new mill projects or capacity expansions through financial modelling including capital recovery
- Technology Assessment: Quantifying cost impacts of technology choices (hot vs cold charging, EAF vs BOF routes, etc.) Carbon cost is an increasingly material factor in this comparison — use our Steel Production Emissions Calculator to estimate Scope 1 and Scope 2 CO2 emissions across different process routes.
- Strategic Planning: Informing make-vs-buy decisions, vertical integration analysis, and capacity rationalisation studies
- Market Analysis: Establishing floor prices for market analysis and understanding industry profitability dynamics
- Due Diligence: Verifying operational cost claims in acquisition or financing transactions
Adapting the Methodology
This rebar mill example provides a template that can be adapted to other steel products and production routes by:
- Substituting appropriate raw material inputs (billet, slab, or scrap)
- Adjusting yield loss factors for specific products (wire rod, sections, flat products)
- Modifying energy consumption for different processes (EAF vs integrated route, hot strip mill vs plate mill)
- Scaling labour requirements and productivity for different plant sizes
- Incorporating product-specific costs (galvanising, coating, precision rolling)
The fundamental framework of separating fixed and variable costs and building up from individual cost components remains applicable across steel product types.
Information Quality and Limitations
Cost modelling accuracy depends on quality of input assumptions. Key limitations to recognise:
- Regional Variations: Input costs vary significantly by location due to energy prices, labour costs, and raw material logistics
- Technology Differences: Mill age, automation level, and process technology affect both capital and operating costs
- Product Mix Effects: Actual costs depend on product mix; smaller sizes or special grades increase costs per tonne
- Operating Practices: Maintenance philosophy, inventory management, and operational excellence drive cost variations
- Market Conditions: Input costs fluctuate with commodity markets, requiring regular model updates
Users should treat modelled costs as indicative benchmarks rather than precise predictions for any specific operation. Site-specific cost analysis requires detailed operational data and local market intelligence.
Quality Standards and Expert Review
This cost benchmarking methodology incorporates quality assurance through:
- Industry Benchmarking: Comparing modelled costs against published industry cost curves and analyst estimates
- Operational Experience: Drawing on 25+ years of steel plant visits, operational assessments, and consulting engagements
- Data Triangulation: Cross-referencing steel plant key performance indicators against multiple independent data sources
- Peer Review: Expert validation of technical assumptions and calculation methodologies
- Continuous Refinement: Regular updates incorporating latest industry developments and price trends
This rigorous approach ensures cost models provide reliable foundation for strategic decision-making on investments, competitive positioning, and business development initiatives.
Related Methodologies
- Steel Plant Material Flow Analysis Methodology - Framework for assessing integrated plant operations and capacity utilisation
- Aggregate Steel Demand Calculation Methodology - Bottom-up approach for regional steel consumption analysis
- New Steel Producer Market Positioning — Five-check due diligence framework for validating a new producer's market share, export orientation, import displacement, ramp-up profile, and capacity utilisation benchmark.
- Steel Plant SWOT Analysis - A steel-specific diagnostic methodology for plant-level assessment of strengths, weaknesses, opportunities and threats.
- General Research Methodology - Overview of data sources and quality assurance framework
Frequently Asked Questions
Further Information
For questions about this methodology or to discuss applying cost benchmarking to specific projects, please contact us. We provide consulting services including:
- Steel plant concept study appraisal
- Feasibility studies for new steel plants or capacity expansions
- Due diligence for steel company acquisitions
- Competitive cost benchmarking and strategic positioning analysis
- Technology assessment and optimisation studies
- Investment analysis and business case development
See our consulting services page or expert credentials for additional information.