| name | design-for-cost |
| description | Design for cost (DFC) — target costing, cost drivers, material cost index, value engineering, activity-based costing, Rough Order of Magnitude estimation, should-cost analysis, teardown benchmarking. |
| metadata | {"priority":7,"promptSignals":{"phrases":["design for cost","DFC","target costing","should cost","cost reduction design","value engineering"],"minScore":3}} |
Design for Cost (DFC) — Complete Skill
Target Costing
Target cost = selling price - desired profit margin
C_target = P_market × (1 - margin%)
If C_estimated > C_target → design changes required to close gap
Cost gap closure sequence:
- Material substitution (material cost = 40–70% of total for machined parts)
- Feature elimination or simplification
- Tolerance relaxation → cheaper manufacturing process
- Part count reduction (DFA synergy)
- Process change (casting instead of machining; stamping instead of forging)
- Supply chain (global vs. domestic; tier-2 vs. tier-1)
Cost Estimation Methods
Rough Order of Magnitude (ROM)
± 30–50% accuracy; for early concept comparison:
C_ROM ≈ C_reference × (Q_new / Q_reference)^(1 - learning_curve_factor) × (complexity_factor)
Or: C_ROM = C_material + C_process (from similar-part databases)
Cost estimating relationships (CER):
Regression models from historical parts data
C = a + b × (weight)^c × (surface_area)^d × (tolerance_tightness)^e
Should-Cost Analysis
Bottom-up engineering estimate of what a part SHOULD cost:
- List all processes (operation list)
- Estimate cycle time per process step
- Apply machine rate ($/hr) and labor rate ($/hr)
- Sum material cost (weight × material price/kg)
- Add overhead % and profit %
Should-cost template (machined part):
C = C_material + Σ(t_op_i × R_machine_i) + Σ(t_handling × R_labor) + C_tooling_amort + overhead × C_direct + profit
C_material = mass × ρ × material_cost/kg × (1 + scrap_factor)
R_machine: CNC turning center: $60–120/hr; machining center: $80–150/hr; EDM: $80–200/hr
Activity-Based Costing (ABC)
Allocate overhead to activities, not hours:
- Identify cost drivers (machine setups, inspections, material moves)
- Calculate activity cost pools
- Allocate to parts based on activity consumption
Example — Setup cost driver:
Setup cost per part = Total setup cost per run / Batch size
High-mix low-volume: setup can dominate total cost → design for common setups
Material Cost Index
Relative cost vs. carbon steel (1.0 as baseline):
| Material | Relative cost index | Notes |
|---|
| Carbon steel (1020) | 1.0 | Reference |
| Low alloy steel (4140) | 1.3–1.8 | Heat treatable |
| 304 SS | 4–6 | Corrosion resistant |
| 316 SS | 5–8 | Higher Mo content |
| Aluminum 6061 | 3–5 | Lightweight |
| Titanium Ti-6Al-4V | 50–100 | Aerospace premium |
| Inconel 718 | 80–150 | High temp |
| PEEK (polymer) | 100–300 | High performance plastic |
| Carbon fiber composite | 200–500 | Depends on layup complexity |
Material price per kg (approximate 2024–2026 range):
Carbon steel: $0.5–1.5/kg; Al 6061: $3–5/kg; Ti-6Al-4V: $30–60/kg; Inconel 718: $60–100/kg
Buy-to-fly ratio (aerospace machining):
BTF = raw material weight / finished part weight
BTF = 5–20 for complex machined aerospace parts (significant waste)
Lower BTF by: near-net-shape forging, AM, optimized raw stock size
Process Cost Drivers
Machining cost drivers:
- Number of setups → each = 15–60 min at machine rate
- Number of operations (turning, milling, drilling, grinding, EDM)
- Surface finish requirement (Ra 0.8 μm → finish grind vs. Ra 3.2 μm → fine mill)
- Tolerance tightness (IT6 vs. IT11 → ×2–5 cost)
- Number of inspection steps
- Batch size (amortizes setup)
Tolerance-cost relationship:
Tolerance T → relative cost C_rel:
C_rel ≈ 1 + exp(3 × (T_nominal - T) / T_nominal) [steep increase below IT7]
Or from Ostwald chart: cost doubles for each 3× tightening of tolerance
Casting cost drivers:
Die cost: $20,000–$500,000 (die casting); break-even volume ≥ 10,000–100,000 parts
Parting line location, draft angle, cores, undercuts, secondary machining
Forgings:
Die cost: $5,000–$100,000; break-even: 1,000–10,000 parts
Flash trimming, heat treatment, straightening, inspection
Value Engineering
Function-cost analysis:
VA = F_value / C_cost [Value Analysis ratio; F = importance weight of function (1–10)]
Ranked list: lowest VA items = best opportunities for cost reduction
Worth vs. cost:
Worth = minimum cost to perform function (lowest-cost alternative)
Cost = actual cost of current design
Value index = Worth / Cost; < 0.5 → high improvement potential
VE/VA process (SAE J2583):
- Information phase: gather costs, functions, specifications
- Creative phase: brainstorm alternatives for each function
- Evaluation: feasibility, cost, risk, regulatory
- Development: engineering analysis, prototype
- Presentation: cost savings justification
Teardown Benchmarking
Competitive teardown:
Disassemble competitor product → cost-estimate each part → identify where they achieve lower cost
Metrics: cost/function, cost/weight, cost/performance
Teardown findings convert to design targets:
"Competitor uses stamped bracket vs. our machined bracket → 60% lower cost → design stamped version"
Learning Curves
Manufacturing cost decreases with cumulative production:
C_n = C₁ × n^(log b / log 2) [b = learning curve fraction (0.80–0.95 typical)]
C₁ = cost of first unit; n = cumulative production number
80% learning curve: each doubling of production → cost = 80% of previous
C₄ = C₁ × 0.8² = 0.64 × C₁ (4× production → 64% of original unit cost)
Learning curve exponent:
m = log(b) / log(2) [m = -0.322 for 80% curve]
C_n = C₁ × n^m
Cost Accounting Standards
| Standard | Scope |
|---|
| SAE J2583 | Value engineering methodology for automotive |
| DFMA (Boothroyd-Dewhurst software) | DFMA cost estimation tool |
| GAAP ASC 330 | Inventory costing (FIFO, LIFO) |
| CAS (Cost Accounting Standards) | US government contracts |
| ISO 15685 | Tool life experiments for cost estimation |
Output
Provide: target cost C_target [$/part], current should-cost estimate [$/part] with breakdown (material %, process %, overhead %), cost gap and top 3 reduction opportunities, material cost index for chosen material, tolerance-cost analysis (current IT grade, relaxation possible, cost impact), BTF ratio (if machined), batch size break-even for process change, value index (worth/cost) for highest-impact functions, learning curve estimate at target volume (b = [%]), and applicable framework (SAE J2583 VE, DFMA tool).
