PAI-150 · Education

Manufacturing Physical AI

Take a part from a clean CAD model to a humming, optimized production line inside a browser-native virtual-factory twin — deciding how to make it, generating its process plan, taming tolerance and variation, balancing the line, and optimizing a whole factory against throughput, cost, and yield.

Beginner → Skilled·5 modules·15 lessons
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Module 1

From Design to Manufacturable

Read a CAD part and decide how it could actually be made — choose a material and a process, and flag the geometry that fights manufacturing.

  1. L0What "manufacturable" meansGiven the sensor-mount CAD part, identify at least 3 manufacturability problems and state why each is a problem — each mapped to the correct defect class on a fixed grader seed.→
  2. L1Choosing a material and a processFor the sensor-mount part and a stated requirement (strength, cost, count), select a material+process pairing and justify it against at least two alternatives, using the twin's estimated cost, time, and feasibility.→
  3. L1Designing for the process (DFM)Modify the part's geometry to remove ≥2 flagged DFM violations while preserving its functional dimensions, and verify the inspector now passes.→
Module 2

CAD → CAM: Toolpaths & Process Plan

Turn a manufacturable design into the concrete instructions that make it — toolpaths, cutting parameters, and a datum-consistent operation sequence.

  1. L1From geometry to toolpathGenerate a valid roughing + finishing toolpath for a pocket and explain how tool diameter and stock define what the path can and cannot reach.→
  2. L1Process parametersChoose spindle speed, feed, and depth-of-cut that complete the cut with no overload and an acceptable surface-finish score, and state the trade-off each parameter drives.→
  3. L1Sequencing a process planOrder a multi-operation plan into a valid sequence, choosing setups, and justify why the order is forced by datums and the surfaces each operation creates.→
Module 3

Tolerances, Process Simulation & Variation

Understand and quantify why real parts deviate from their nominal design, and specify tolerances that keep parts functional despite that variation.

  1. L2Tolerances: the band a part must live inAssign tolerances to ≥2 critical dimensions and predict how tightening or loosening each changes cost and fit — reaching a functioning fit at the lowest cost.→
  2. L2Where variation comes fromRun a batch, read the output distribution, identify which process parameter drives the spread, and reduce it.→
  3. L2Tolerance stack-upPredict whether a chain of toleranced parts will assemble using both worst-case and statistical (RSS) stacks, and state when each method applies.→
Module 4

Assembly & the Production Line

Compose individual parts into an assembly and a balanced production line, reasoning about sequencing, throughput, and bottlenecks.

  1. L2Assembly sequencingProduce a feasible assembly order for a multi-part product and explain at least one constraint (access, fastening, fit) that forbids an alternative order.→
  2. L2Throughput & the BottleneckFind a line's bottleneck — the station with the slowest per-machine cycle — and fix it so the line meets its throughput target.→
  3. L2Balancing the LineBalance a multi-station line so no single station dominates — including the SECOND bottleneck that appears once you fix the first — to hit a high throughput target.→
Module 5

Quality, Yield & Optimization + Capstone

Connect tolerance, process, and line decisions to yield and cost, and optimize a full virtual factory against competing throughput, cost, and yield targets.

  1. L2Yield, scrap & process capabilityCompute a line's yield and process-capability index (Cp/Cpk) from a batch, and raise yield above a target by centering and/or narrowing the process.→
  2. L2Optimizing Under Competing TargetsHit the throughput target at MINIMUM cost — every machine costs money, so add capacity only where it actually buys throughput (the bottleneck), staying within budget.→
  3. L2Capstone: Run & Optimize a Virtual FactoryTake a full five-station line from below target to meeting both a throughput spec and a tight machine budget — the whole manufacturing toolkit (bottleneck, balancing, cost) at once.→