Metal - LPBF (SLM / DMLS)
How to price metal Laser Powder Bed Fusion parts using a machine-time-dominated model based on build volume and laser build rate.
Why this process is unique
Laser Powder Bed Fusion (LPBF) - also called SLM, DMLS is expensive AM process to run. Cost is dominated almost entirely by machine time, not material.
Key characteristics:
- Machine cost per hour: €80-250+ (inert gas consumption, laser wear, maintenance)
- Layer heights: 0.02-0.06mm - far thinner than polymer processes
- Print speeds: much slower than MJF or FDM per cm³
- Supports are mandatory and made of metal - dense, slow to print, costly to remove
- Heat treatment (stress relief, HIP) is typically mandatory post-process
- Material is expensive: Ti-6Al-4V ~€300-500/kg, 316L ~€80-120/kg, Inconel ~€400+/kg
Despite high material costs, machine time typically accounts for 60-80% of a metal part's price.
Core methodology
Use a simplified time model based on build volume and laser scanning speed:
Print time = (layer count × area per layer) ÷ scan speed + overhead
Or, simpler and nearly as accurate for quoting:
Print time ≈ (shrinkWrapVolume + support volume) ÷ build rate
Where buildRate = mm³/hour of actual metal deposited (a material variable, calibrated per machine and material).
Numerical example
Part: 30 × 30 × 60 mm bracket, volume = 10,000 mm³, convexHullVolume = 13,000 mm³
| Parameter | Value |
|---|---|
| Material: 316L stainless steel | |
| Density | 7.9 g/cm³ |
| Material cost per kg | €100 |
buildRateMm3PerHour | 5,000 |
machineCostPerHour | €130 |
setupCost | €150 |
Support volume: (13,000 − 10,000) × 0.40 = 1,200 mm³ (dense metal supports) Print volume: 10,000 + 1,200 = 11,200 mm³ Print time: 11,200 / 5,000 = 2.24 hours Machine cost: 2.24 × 130 = €291 Material mass: (10,000 / 1,000) × 7.9 / 1,000 = 79g = 0.079 kg Material cost: 0.079 × 100 = €7.90 Setup (1 part): €150 Total: €449 - machine time is 65% of cost
Complete algorithm
const { volume, convexHullVolume, length, width, height } = specification
const { quantity } = requisition
// Chamber limits — adjust to your machine (e.g. EOS M290 = 250×250×325mm)
const CHAMBER_LENGTH = 250
const CHAMBER_WIDTH = 250
const CHAMBER_HEIGHT = 325
const buildRateMm3PerHour = material.variables['buildRateMm3PerHour']
const machineCostPerHour = material.variables['machineCostPerHour']
const setupCost = material.variables['setupCost']
const materialDensity = material.variables['materialDensity']
const materialCostPerKg = material.variables['materialCostPerKg']
// Support volume (metal supports are denser than FDM — use 35–45%)
const hullGap = convexHullVolume - volume
const supportVolume = variable('supportVolume', round(hullGap * 0.40, 0))
// Print time based on build rate
const printVolume = volume + supportVolume
const printTimeHours = variable('printTime', round(printVolume / buildRateMm3PerHour, 2))
const machineCost = round(printTimeHours * machineCostPerHour, 2)
// Material cost (part only, not support — support is removed)
const massKg = (volume / 1_000_000) * materialDensity // mm³ → cm³ → g → kg... wait
// volume in mm³. density in g/cm³. 1 cm³ = 1000 mm³
const massGrams = (volume / 1000) * materialDensity
const materialCost = round((massGrams / 1000) * materialCostPerKg, 2)
// Setup amortised (typically one part per build for LPBF unless batch run)
const setupPerPart = round(setupCost / quantity, 2)
const baseCost = machineCost + materialCost + setupPerPart
const unitPrice = variable('unitPrice', round(baseCost, 2))
const oversized = length > CHAMBER_LENGTH || width > CHAMBER_WIDTH || height > CHAMBER_HEIGHT
// Also flag open mesh — geometry errors cause metal build failures
const reviewRequired = oversized || revision.watertight === 0
done(unitPrice, printTimeHours, reviewRequired)Material variables: buildRateMm3PerHour, machineCostPerHour, setupCost, materialDensity, materialCostPerKg
When to use this
All laser powder bed fusion of metals: SLM, DMLS, LPBF, DMP. Works for steel, titanium, aluminium, Inconel, copper. Adjust buildRateMm3PerHour and machineCostPerHour per alloy and machine.
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