DFMA: SHOULD COSTING
DFMA: PRODUCT SIMPLIFICATION
What is manufacturing cost estimation?
Manufacturing cost estimation is the practice of predicting the cost to produce a part or product based on its design, material, manufacturing process, and production volume. It is used throughout product development—from early concept screening through detailed design, sourcing, and production planning.
A good cost estimate answers a specific question: what should this part cost to make, given these design choices and this production scenario? The answer depends on how the estimate is built. Different methods produce different levels of accuracy, transparency, and usefulness for decision-making.
This guide compares the major estimation methods, explains when each is appropriate, and shows how process-based estimation provides the transparency needed for design optimization and supplier negotiation.
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Why manufacturing cost estimation matters
Cost estimation is the foundation of every cost-related decision in product development. Without an accurate estimate, teams cannot set targets, evaluate alternatives, or negotiate effectively.
- Design to cost: set a target and iterate toward it with real cost feedback
- Should-cost analysis: build an independent benchmark for supplier negotiation
- Make vs. buy: compare internal production cost to supplier quotes
- Process selection: evaluate machining vs. casting vs. molding for the same part
- Global sourcing: compare cost across manufacturing regions
- Design decisions are made without cost visibility
- Cost overruns are discovered at first supplier quotes—too late
- Supplier negotiations become arguments about price, not cost drivers
- Make-vs-buy decisions rely on intuition rather than analysis
- Target costs are set top-down without engineering basis
The three estimation methods
Manufacturing cost estimation methods fall into three categories. Each has different data requirements, accuracy profiles, and levels of transparency. Understanding the trade-offs is essential for choosing the right approach at each stage of product development.
Compare the new part to a similar part with known cost. Adjust for differences in size, complexity, or material. Common in early screening when little design detail is available.
- Fast: minutes per estimate
- Requires historical cost database
- Accuracy: ±25–40%
- No visibility into cost drivers
- Anchored to past conditions
Use statistical relationships (cost-per-kilogram, cost-per-feature, regression models) derived from historical data. The estimate is driven by a few high-level parameters rather than detailed process modeling.
- Moderate speed: minutes to hours
- Requires calibrated cost models
- Accuracy: ±15–30%
- Limited driver visibility
- Breaks down for novel designs
Model the actual manufacturing process: operations, cycle times, machine rates, material usage, tooling, and secondary ops. Each cost component is calculated from the design and process parameters.
- Most accurate: ±5–15%
- Full visibility into cost drivers
- Supports design iteration
- Works with or without 3D CAD
- Transparent, auditable, defensible
Method comparison: accuracy, speed & transparency
The right estimation method depends on where you are in the product lifecycle, how much design detail is available, and what you need the estimate to do.
| Dimension | Analogous | Parametric | Process-based |
|---|---|---|---|
| Accuracy | ±25–40% | ±15–30% | ±5–15% |
| Speed | Minutes | Minutes to hours | Minutes to hours |
| Design detail required | Minimal (similar part reference) | Key parameters (weight, features) | Geometry + process + material |
| 3D CAD required? | No | No | No (features can be described) |
| Cost driver visibility | None | Limited (correlations only) | Full (each operation costed) |
| Supports design iteration? | No | Weakly | Yes—change specs, see cost shift |
| Useful for negotiation? | No (no driver detail) | Somewhat | Yes—transparent driver breakdown |
| Novel/redesigned parts? | Poor (no analogous reference) | Risky (outside model range) | Strong (models from first principles) |
| Best use case | Quick screening, budget estimates | Portfolio-level analysis, early gating | Design-to-cost, should-cost, negotiation |
How process-based estimation works
Process-based estimation builds a cost model from the manufacturing process itself. Rather than relying on statistical correlations or historical analogy, it simulates what actually happens on the factory floor: how material is consumed, how long each operation takes, what tooling is required, and what secondary operations are needed.
This approach produces estimates that are transparent and auditable. Every number in the estimate traces back to an identifiable assumption—machine rate, cycle time, material cost, yield—that can be verified, discussed, and adjusted. This is what makes process-based estimates useful for supplier negotiation and design optimization, not just budgeting.
- Material: stock form, utilization, scrap, material grade pricing
- Primary process: cycle time from geometry (machining passes, injection fill, casting cooling)
- Setup: number of orientations, fixture changes, program loads
- Tooling: tool cost, tool life, amortization over production volume
- Secondary ops: deburr, finish, inspect, test—each costed individually
- Overhead: machine rate captures depreciation, energy, maintenance, floor space
- Design feedback: change a tolerance, switch a material, add a feature—see the cost impact instantly
- Process comparison: evaluate machining vs. casting vs. forging for the same geometry
- Regional comparison: model the same part produced in different countries with local labor, energy, and material costs
- Negotiation power: walk into a supplier meeting with a transparent cost breakdown, not just a target price
- Defensibility: every assumption is visible and adjustable—no black boxes
Estimating cost without a finished CAD model
A common misconception is that accurate manufacturing cost estimation requires a finished 3D CAD model. It does not. Process-based tools like DFMA allow engineers to describe a part’s features, select materials and processes, and generate cost estimates from design parameters—without importing CAD geometry.
This capability is critically important because the highest-leverage cost decisions happen at concept stage, when CAD models often do not exist yet. Waiting for detailed CAD before estimating cost means the biggest cost-driving decisions—architecture, part count, process selection, material choice—have already been made without cost visibility.
- Import STEP, STL, or IGES files
- Geometry-driven feature extraction
- Automatic process routing suggestions
- Highest accuracy (geometry fully specified)
- Describe features: holes, pockets, bends, wall sections
- Select material and process from libraries
- Specify key dimensions and tolerances
- Useful estimates at concept stage—when it matters most
Both paths produce the same transparent, driver-level cost breakdown. The difference is input method, not output quality. This means cost estimation can begin at the moment design decisions are being made—not weeks later when the CAD model is complete and the supplier quotes come back.
For more on the design-stage cost estimation workflow, see Design to Cost.
Worked example: three methods, one part
Consider an aluminum die-cast housing, 280g, moderate complexity, production volume of 25,000 units/year. Here is how each estimation method approaches the same part—and what each reveals:
| Method | Approach | Estimate | What you learn |
|---|---|---|---|
| Analogous | Compare to similar housing from last program; adjust +10% for added features | $6.20 | A starting point. No visibility into why it costs $6.20 or what would change it. |
| Parametric | Apply cost-per-kg curve for aluminum die castings at this volume range | $5.80 | Volume-adjusted estimate. Still no visibility into which features or tolerances drive cost. |
| Process-based | Model: die-cast cycle (42s), trim, 2 machined datums, tumble deburr, inspect | $5.45 | Full breakdown: $1.85 material, $1.20 casting, $0.95 machining, $0.80 tooling (amortized), $0.65 secondary ops. The two machined datums account for 17% of unit cost. |
Key takeaway: all three methods produce a number. Only the process-based estimate tells you that the two machined datum surfaces account for 17% of unit cost—and that relaxing their tolerance from ±0.05mm to ±0.10mm could eliminate the secondary machining entirely, saving $0.95/unit ($23,750/year at volume).
Values are illustrative. Actual costs depend on geometry, material, machine rates, and regional cost factors. DFMA calculates these from your specific part and process assumptions.
Choosing the right estimation method and tool
The best estimation approach depends on your situation. Here is a decision framework:
- You need a rough budget estimate in minutes
- The part is very similar to something you have produced before
- You are screening dozens of concepts and need fast go/no-go
- No design detail is available beyond weight and general type
- You need to hit a cost target (design to cost)
- You are negotiating with suppliers (should-cost)
- You need to compare manufacturing processes or regions
- The design is new or significantly different from past parts
- You need to understand what drives cost, not just what cost is
What to look for in estimation software
| Capability | Why it matters |
|---|---|
| Process-specific models | Generic models miss process-specific cost drivers (cooling time in molding, passes in machining, strokes in stamping). Look for models built from manufacturing physics, not just regressions. |
| Transparent assumptions | If you cannot see and adjust the underlying assumptions (machine rate, cycle time, material cost, yield), the estimate is a black box. Transparency is essential for negotiation and iteration. |
| Works without CAD | Estimates at concept stage—when cost leverage is highest—require a tool that accepts feature descriptions, not just 3D models. |
| Regional cost data | Global sourcing decisions require cost models that reflect regional differences in labor, energy, material, and overhead. Look for regularly updated country profiles. |
| Editable libraries | Material costs, machine rates, and labor rates change. The software should let you update these to reflect your actual supply chain, not just vendor defaults. |
| Fast iteration | If re-estimating after a design change takes hours, engineers will not use it. Process-based tools should update cost in seconds when a spec changes. |
DFMA Should Costing is a process-based estimation tool with transparent, editable models across 15+ manufacturing processes, global cost data for 22 countries, and the ability to estimate with or without 3D CAD. For a detailed comparison of estimation approaches, see Should Cost Analysis.
Frequently asked questions
What is manufacturing cost estimation?
Manufacturing cost estimation is the process of predicting what a part or product will cost to produce before production begins. Accurate estimates are used to set price targets, evaluate design alternatives, negotiate with suppliers, and make make-vs-buy decisions. The best estimates model the actual manufacturing process rather than relying on historical averages.
What are the main methods of manufacturing cost estimation?
The three main methods are analogous estimation (comparing to similar past parts), parametric estimation (using statistical relationships like cost-per-kilogram), and process-based estimation (modeling the actual manufacturing operations, cycle times, and cost drivers). Process-based estimation is the most accurate and transparent, especially for new or redesigned parts.
Do I need a 3D CAD model to estimate manufacturing cost?
Not always. Process-based tools like DFMA allow engineers to estimate cost from design parameters, feature descriptions, and process selections without requiring a finished 3D CAD model. This means cost estimation can begin at concept stage, when design changes are cheapest, rather than waiting for detailed CAD to be complete.
What is the difference between a cost estimate and a should-cost?
A cost estimate predicts what a part will cost to produce. A should-cost is a specific type of estimate that models what the part should cost under efficient manufacturing conditions. Should-costs are used as benchmarks for supplier negotiation, identifying gaps between quoted price and achievable cost. Learn more about should cost analysis.
How accurate is manufacturing cost estimation software?
Accuracy depends on the method. Historical and parametric methods typically achieve ±20–30%. Process-based methods like DFMA, which model actual manufacturing operations and cost drivers, typically achieve ±5–15%, with accuracy improving as more design detail is specified.
When should cost estimation happen in product development?
As early as possible. Roughly 80% of manufacturing cost is determined by design decisions. Estimating cost at concept stage—when changes are inexpensive—produces far better outcomes than waiting for supplier quotes after design is locked. Tools that work without finished CAD enable this early-stage estimation.
What is the difference between manufacturing cost estimation and quoting?
Manufacturing cost estimation predicts the cost of production based on engineering analysis. Quoting is the commercial process of setting a price for a customer or receiving a price from a supplier. Quotes reflect cost plus margin, market conditions, and commercial strategy. Cost estimates provide the analytical foundation that makes quotes defensible.
Estimate the real cost of your part
Bring a cost-critical part or assembly. We will show the process-based cost breakdown—material, cycle time, tooling, secondary ops—and demonstrate how design changes move each component.
