A real case
A housing drawn for 3-axis machining because the last generation was, with a forecast that just moved from 150 a year to 5,000. One upload screens six process families with the constraint behind each verdict, and solves the exact quantity where one process gets cheaper than another.
The situation
A 6082 aluminium lever housing, one STEP file, gate review a week on Friday. The part is drawn for 3-axis machining from bar — sharp internal corners, no draft anywhere, a boss that a die would have to core around — because the previous generation was machined from bar and nobody re-asked the question when this one started. At the last program review the forecast moved from 150 a year to 5,000. The geometry has not caught up with that number, and every week it stays as drawn the machining assumption gets harder to unpick: the corners, the draft and the boss are all an afternoon's work now and a redesign after release.
Step by step
One STL or STEP model goes in, exactly as it sits in CAD today. You do not redraw the part for casting to find out whether it casts, and you do not need the volume decided before you upload. Detected holes come back named with their own confidence, alongside the overall envelope and the part's face counts.
Casting, molding, forging, machining, sheet metal and additive are screened together off that single upload, each coming back feasible, marginal or infeasible with the constraint that drove the verdict. A missing draft, an undercut a closed die cannot core, a wall the process cannot fill — each arrives named, which is the difference between a score you have to take on faith and a specific thing you can design against without ever having run the process yourself.
Every feasible process carries a should-cost curve across quantities, and the exact quantity where one process gets cheaper than another is solved in closed form rather than eyeballed off two lines on a chart. At 150 a year you read the curve at 150. At 5,000 you read it at 5,000, and whether the crossover sits between those two numbers is the entire question the gate is actually asking.
One block-and-machining tool-cost model prices dies, molds, patterns and core boxes, and amortizes that cost into the per-piece curve rather than leaving it beside the curve as a lump sum. Amortization is the thing that moves a crossover quantity, so a tool number sitting in a separate cell on a spreadsheet is exactly how the decision gets made wrong.
Every cost line traces to a named rate, posture setting or engine rule instead of an opaque total, and every result carries a confidence value that states its basis — a published prior, shop-calibrated actuals, a deterministic rule, or a flag that it needs human review. Every panel mounts against the same job, so moving from a process verdict into its cost detail is a panel switch rather than another upload.
What you get
You leave with a verdict per process, the constraint that produced each one, and a curve you can read at both forecast quantities. At 150 a year the billet route may well still win, and now you have said so with a solved number rather than an inherited habit. At 5,000 the answer may be a different family altogether — and the geometry changes that go with it, the draft, the corner a die can fill, the boss moved off the pull direction, are an afternoon now rather than a redesign later. Where this stops matters as much as what it does. The screen ranks processes for this part at this quantity; it is not a tolerance stack-up, a joining study or a part-consolidation exercise, and none of those exist here. The assembly work that does ship is a costed BOM roll-up and a coarse advisory clearance screen, nothing further. Partimation is decision support, not a guarantee — confirm the fit with your supplier and your own engineering judgment before tooling is committed.
Already shipped
Built into PartDFM.
Built into ProcessDFM.
Built into CostDFM.
Built into ToolDFM.
Built into CostDFM.
Built into CostDFM.
Built into AssemblyDFM.
Built into ProcessDFM.
FAQ
One model, exactly as drawn, is enough. Casting, molding, forging, machining, sheet metal and additive are screened together off a single upload, each returning feasible, marginal or infeasible with the constraint that drove the verdict — so a part drawn for machining from bar still gets a casting verdict, and the named reason behind it if that verdict is no.
Draft, undercuts and wall thickness are the three that usually decide it, and the screen names which one it was rather than returning a score. An infeasible verdict arrives with the constraint attached, which is a specific thing to design against — open the corner, add the draft, move the boss off the pull direction — rather than a general warning that casting might be difficult.
Closed-form solution of the two should-cost curves, not a reading taken off a chart. Every feasible process carries a curve across quantities with tool cost amortized into the per-piece figure rather than sitting beside it as a lump sum, and the quantity where one curve overtakes another is solved directly — which is exactly why the tooling assumption moves the answer.
Named constraints and an itemized ledger are what survive that room. Each process comes back feasible, marginal or infeasible with the constraint that drove the verdict, every cost line traces to a named rate, posture setting or engine rule instead of an opaque total, and every result carries a confidence value stating its basis — a published prior, shop-calibrated actuals, a deterministic rule, or a flag that it needs human review.
Where this fits
You design the part. Somebody else has to make it, and they tell you weeks late. Upload the model before release: manufacturability findings come back before a process is picked, and six process families are screened with the constraint behind each verdict and a should-cost curve across quantities.
Cast because the last one was cast. Machined because the shop machines. Partimation screens a part against casting, molding, forging, machining, sheet metal and additive together — each verdict naming the constraint behind it — and solves the exact quantity where a cheaper process takes over.
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