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Manufacturing + operations

  • Prerequisites
    Modules 4-6; Wave 1 optimization/metrology

  • Exit capability
    Translate prototypes into processes with rate, yield, variation, quality, cost, maintenance, supply chain and learning curves.

  • Unlocks / transfers to
    Robot factories; orbital manufacturing; batteries at scale; biotech production; chip fabs; additive manufacturing; autonomous construction.

Weeks

Week 45

Spine: MIT 2.008 Spring 2025

Reading: Process physics and design-for-manufacturing lectures; machining/deforming/casting/additive overview

Know: Choose manufacturing processes from geometry/material/rate/quality/cost constraints.

Reconstruct: Regenerate chip/load/energy or material-flow scaling for one process and basic tolerance-stack logic.

Do: Take a Wave-2 component and compare machining, forming/casting and additive routes quantitatively.

Defend: Why is a manufacturable geometry different from an optimally shaped geometry?

Gate: Pass: process selection includes tooling, rate, tolerances, material utilization and inspection.

Source: source

Week 46

Spine: MIT 2.008 Spring 2025

Reading: Lectures 11-12 variation/quality/statistical process control

Know: Translate metrology into yield/capability/process control and diagnose variation sources.

Reconstruct: Derive Cp/Cpk intuition and control-limit standard-error scaling.

Do: Simulate process drift and compare inspection-only vs process-control strategies.

Defend: Why can 100% inspection still produce poor quality?

Gate: Pass: distinguish measurement error, common cause, special cause and specification.

Source: source

Week 47

Spine: MIT 2.008 Spring 2025

Reading: Lectures 15-19 manufacturing systems, planning, cost, lean, transfer lines

Know: Reason about capacity, bottlenecks, WIP, cycle time, utilization, flow and production economics.

Reconstruct: Derive Little's Law and bottleneck throughput bound.

Do: Scale a prior prototype to 10,000 units/year: routing, machines, staffing/automation, WIP, downtime and unit cost.

Defend: Why does maximizing machine utilization often hurt system throughput?

Gate: Pass: line design includes bottleneck, variability and recovery, not average cycle time only.

Source: source

Week 48

Spine: MIT 2.008 + Factory Physics/Groover reference

Reading: Integrated production-system studio

Know: Integrate process physics, quality, maintenance, supply chain, learning curve and capital deployment.

Reconstruct: Derive yield multiplication across serial process steps and simple learning-curve relation.

Do: Create manufacturing plan for a battery module, robot actuator, biosensor or spacecraft component with supplier and maintenance risks.

Defend: Where should redundancy live: product, process, supplier or inventory?

Gate: Module defense: credible 10k-unit plan with rate/cost/yield/quality/maintenance/supply evidence.

Source: source

Exit gate

Closed-book: 120 min: process selection, yield/capability, Little's Law, bottlenecks, cost, maintenance, learning curves.

Novel problem: Scale one previous prototype to 10,000 units/year with credible routing and quality system.

Artifact: Manufacturing plan with rate, WIP, yield, downtime, staffing/automation, tooling, suppliers and unit cost.

Defend: Defend bottleneck, variation, maintenance, supplier risk and make/buy choice.

Pass criterion: Pass if throughput/cost/yield numbers reconcile and recovery from disruption is modeled.

Transfer problems

Try these before consulting solutions or asking for the complete answer.

  1. Process selection: Choose process for 10k parts/year and justify material, geometry, tolerance, tooling and cost.

  2. Yield: Compute total line yield from serial step yields and identify highest-leverage improvement.

  3. Capability: Calculate Cp/Cpk and explain what they do not guarantee.

  4. SPC: Simulate drift and design detection rule balancing false alarms/delay.

  5. Little's Law: Relate throughput, WIP and cycle time in a production line.

  6. Bottleneck: Identify throughput bottleneck and quantify effect of adding capacity elsewhere.

  7. Downtime: Model OEE/availability impact of MTBF/MTTR changes.

  8. Learning curve: Estimate unit labor/cost after cumulative production doubles several times.

  9. Supply chain: Compare dual-source, safety stock and redesign strategies for a critical part.

  10. 10k plan: Produce routing, takt/rate, machines, shifts, QA, maintenance and unit-cost model for one prior build.

Textbooks

See the five-book resource page.