Decision Frameworks — Production Scheduling

Decision Frameworks — Production Scheduling

This reference provides the detailed decision logic, scheduling algorithms, optimisation methodologies, and capacity planning techniques for production scheduling in discrete and batch manufacturing. It is loaded on demand when the agent needs to make or recommend nuanced scheduling decisions.

All thresholds, formulas, and time assumptions reflect discrete and batch manufacturing operations running 3–8 production lines with 50–300 direct-labour headcount per shift.

1. Job Scheduling Algorithms

1.1 Dispatching Rules — When to Use Each

Dispatching rules are heuristics applied at a work centre when multiple jobs compete for the same resource. No single rule dominates in all situations. The choice depends on the plant's primary performance objective.

Algorithm Selection Decision Tree

1. Is schedule adherence the primary KPI and are there contractual delivery penalties? → Use EDD as the primary rule. Insert CR checks for jobs where CR < 0.8 — these need immediate attention regardless of EDD rank.

2. Is throughput/output the primary KPI with flexible delivery windows? → Use SPT to minimise average flow time. Monitor maximum lateness; if it exceeds the acceptable threshold, switch to a hybrid SPT-EDD (SPT within a due date window).

3. Do jobs have significantly different economic values (margin, penalty, customer tier)? → Use WSJF. Weight = customer tier multiplier × margin contribution. This is the appropriate rule for job shops with heterogeneous order portfolios.

4. Are setup times sequence-dependent and significant (>15 minutes between families)? → No pure dispatching rule handles this. Use a setup-aware scheduling heuristic (Section 2) that groups jobs by setup family and optimises within groups using EDD.

5. Is the environment stable with balanced flow and predictable demand? → FIFO is acceptable and preferred for its simplicity and shop floor trust.

1.2 Multi-Rule Hybrid Approaches

In practice, most schedulers use a hybrid approach layered as follows:

Layer 1 — Hard Constraints (filter) Remove any job from the queue that lacks material, tooling, or a qualified operator. These jobs are not schedulable regardless of priority.

Layer 2 — Urgency Override (force-rank) Jobs with CR < 0.8 or that are already past-due are force-ranked to the top, ordered by customer penalty exposure descending.

Layer 3 — Primary Dispatching Rule (sort remaining) Apply the selected dispatching rule (EDD, SPT, WSJF, etc.) to remaining jobs.

Layer 4 — Setup Optimisation (local reorder) Within the primary sequence, perform adjacent-swap improvements to reduce total setup time, subject to the constraint that no swap causes a due date violation for either swapped job.

Layer 5 — Labour Levelling (validate) Check that the resulting sequence does not create labour peaks that exceed available headcount for any hour of the shift. If it does, defer the lowest- priority job creating the peak to the next available slot.

1.3 Critical Ratio in Detail

Critical Ratio is the most versatile single dispatching rule for mixed environments.

Formula:

CR = (Due Date − Current Date) / Remaining Total Processing Time

Where Remaining Total Processing Time includes:

• Setup time for the current operation
• Run time for the current operation
• Queue time estimates for remaining operations (use historical average queue times)
• Setup + run times for all remaining operations in the routing

Interpretation:

Updating CR: Recalculate CR at every operation completion and at the start of every shift. A job with CR = 1.5 at shift start that encounters a 4-hour unplanned delay mid-shift may drop to CR = 0.7 — the shift supervisor needs to know this in real time.

1.4 Weighted Scheduling for Customer Tiers

Manufacturing plants serving multiple customer tiers need a weighting system:

WSJF with Customer Tier:

Priority Score = (Customer Tier Weight × Days Until Due / Remaining Processing Time)

Lower score = higher priority (more urgent). Negative scores = past-due.

2. Changeover Optimisation

2.1 SMED Implementation Phases — Step by Step

Phase 0 — Document the Current State (2–4 weeks)

1. Video-record 3–5 changeovers on the target machine/line. Include the full duration from last good piece of the outgoing product to first good piece of the incoming product.
2. Create a changeover element sheet listing every task performed, the performer (operator, setup tech, maintenance), the duration, and whether the machine was stopped.
3. Categorize each element:
   • Internal (IED): Must be performed with the machine stopped.
   • External (OED): Can be performed while the machine is still running.
   • Waste: Not necessary at all — holdover from old procedures, redundant checks, waiting.

Typical finding: 30–50% of changeover time is either external work incorrectly performed during machine stoppage, or pure waste (searching for tools, waiting for approval, walking to the tool crib).

Phase 1 — Separate Internal and External (2–4 weeks)

1. Move all external elements to pre-changeover preparation:
   • Pre-stage next-job tooling, dies, fixtures at the machine before the changeover begins.
   • Pre-mix materials, pre-heat moulds, pre-program CNC settings.
   • Pre-print work order documentation and quality checklists.
2. Create a standardised changeover preparation checklist. The setup technician begins executing it 30–60 minutes before the scheduled changeover time.
3. Expected result: 25–40% reduction in machine-stopped time with no capital investment.

Phase 2 — Convert Internal to External (4–8 weeks)

1. Standardise die/fixture heights and mounting interfaces so that alignment and adjustment happen before the die reaches the machine, not after.
2. Implement intermediate jigs — set up the next tool in a staging fixture that mirrors the machine's mounting interface. When the changeover begins, the pre-assembled unit drops in with minimal adjustment.
3. Pre-condition materials: if the incoming product requires a different temperature, viscosity, or chemical mix, start conditioning in a parallel vessel.
4. Expected result: additional 15–25% reduction in machine-stopped time. May require modest investment in duplicate tooling or staging fixtures.

Phase 3 — Streamline Remaining Internal Elements (4–12 weeks)

1. Replace bolt-on fasteners with quick-release clamps, cam locks, or hydraulic clamping. Every bolt removed saves 15–30 seconds.
2. Eliminate adjustments through poka-yoke: centre pins, guide rails, fixed stops that guarantee first-piece alignment without trial-and-error.
3. Standardise utility connections: colour-coded quick-disconnect fittings for air, water, hydraulic, and electrical. One-motion connect/disconnect.
4. Parallel operations: two people working simultaneously on different sides of the machine can halve the internal time. Requires choreographed procedures and safety protocols.
5. Expected result: additional 10–20% reduction. Often requires capital investment in quick-change tooling.

Phase 4 — Eliminate Adjustments and Verify (ongoing)

1. Implement first-piece verification jigs that confirm dimensions without full inspection.
2. Use statistical process control (SPC) from the first piece — if the first piece is within control limits, the changeover is validated without a trial run.
3. Document the final standardised changeover procedure with photos, time targets per element, and a sign-off sheet.
4. Target: changeover time under 10 minutes (single-minute exchange of die) for the machine-stopped portion.

2.2 Sequence-Dependent Setup Matrices

For operations where setup time varies by product-to-product transition, build a setup time matrix:

Example — Paint Line Setup Matrix (minutes):

Observations from this matrix:

• Light-to-dark transitions (White → Black: 25 min) are cheaper than dark-to-light (Black → White: 30 min).
• Within colour families, transitions are minimal (Red → Orange: 12 min vs. Red → White: 25 min).
• The optimal sequence for all six colours in a campaign would be: White → Yellow → Orange → Red → Blue → Black (total: 8+8+8+15+10 = 49 min) vs. random sequence averaging 17 min per transition (85 min total).

Using the matrix in scheduling:

1. Group jobs by colour family when possible (campaign scheduling within families).
2. When inter-family transitions are required, optimise the transition sequence using the nearest-neighbour heuristic, then improve with 2-opt swaps.
3. If a specific colour is due earliest but the optimal setup sequence would delay it, compute the cost of the suboptimal sequence (extra setup minutes × constraint hourly rate) vs. the cost of late delivery. Choose the lower-cost option.

2.3 Campaign Length Optimisation

Economic Production Quantity (EPQ):

EPQ = √((2 × D × S) / (H × (1 − D/P)))

Where:

• D = demand rate (units per period)
• S = setup cost per changeover (labour + scrap + lost output opportunity cost)
• H = holding cost per unit per period
• P = production rate (units per period), P > D

Practical adjustments:

• Round EPQ up to the nearest full shift or full batch to avoid mid-shift changeovers.
• If EPQ results in WIP that exceeds available staging space, constrain to physical capacity.
• If EPQ results in a campaign longer than the longest customer lead time tolerance, shorten it to maintain responsiveness even at higher changeover frequency.

Campaign vs. mixed-model decision:

3. Theory of Constraints (TOC) Implementation

3.1 Drum-Buffer-Rope — Step by Step

Step 1: Identify the Constraint

Run a capacity analysis for each work centre over the next planning horizon (1–4 weeks):

Utilisation = Σ(Setup Time + Run Time for all scheduled jobs) / Available Time

Available Time = shift hours × number of machines × (1 − planned maintenance %)

The work centre with the highest utilisation ratio is the drum. If multiple work centres exceed 90% utilisation, the one with the least flexibility (fewest alternate routings, most specialised equipment) is the primary constraint.

Validation test: If you could add 10% more capacity to the suspected constraint (one more machine, one more shift hour, or a 10% speed increase), would total plant output increase by approximately 10%? If yes, it is the true constraint. If output increases less (because a second work centre immediately becomes the bottleneck), you have an interactive constraint pair that requires different treatment.

Step 2: Exploit the Constraint

Maximise the output of the constraint with no capital investment:

1. Eliminate idle time: The constraint should never wait for material, tooling, operators, quality inspection, or information. Pre-stage everything.
2. Minimise changeovers on the constraint: Move changeover to non-constraint resources where the time cost is lower. If the constraint must change over, ensure SMED discipline is applied rigorously.
3. Prevent quality defects reaching the constraint: Inspect before the constraint operation, not after. Every defective piece processed at the constraint is wasted constraint capacity.
4. Run through breaks and shift changes: Stagger operator lunches so the constraint never stops for a break. Assign a relief operator.
5. Eliminate micro-stops: Address every source of 1–5 minute stoppages (sensor trips, material jams, tool wear alarms) that individually seem trivial but cumulatively steal 2–5% of capacity.

Step 3: Subordinate Everything to the Constraint

1. Upstream work centres: Release work to upstream operations only at the rate the constraint can consume it. This is the "rope." If the constraint processes 100 units/hour, the upstream release rate should not exceed 100 units/hour regardless of upstream capacity.
2. Downstream work centres: Must maintain enough sprint capacity to clear constraint output without becoming a secondary bottleneck. If the constraint produces a batch every 2 hours, downstream must be able to process that batch within 2 hours.
3. Scheduling non-constraints: Do not optimise non-constraint schedules in isolation. A non-constraint running at 100% utilisation when the constraint runs at 85% is producing excess WIP that clogs the shop floor and slows the constraint's material flow.

Step 4: Establish the Buffer

The constraint buffer is a time buffer, not an inventory buffer:

Buffer Duration = Planned Lead Time from release to constraint × Buffer Factor

Typical buffer factors:

• Stable, reliable upstream operations: 0.3 × lead time
• Moderate reliability, some variability: 0.5 × lead time (most common starting point)
• Unreliable upstream, frequent disruptions: 0.75 × lead time

Buffer sizing example: If the upstream lead time from raw material release to the constraint work centre is 8 hours, and upstream reliability is moderate, set the buffer at 4 hours. This means material should arrive at the constraint staging area at least 4 hours before the constraint is scheduled to process it.

Step 5: Monitor Buffer Penetration

Track buffer penetration trends over 2–4 weeks. Persistent yellow indicates a systemic upstream issue (not random variation) that needs corrective action.

Step 6: Elevate the Constraint (only if Steps 1–5 are exhausted)

If after full exploitation and subordination the constraint still limits plant output below demand requirements:

1. Add overtime or a weekend shift at the constraint only.
2. Add a parallel machine or alternate routing capability.
3. Outsource constraint-specific operations to a qualified subcontractor.
4. Invest in faster constraint equipment (capital expenditure).

Each elevation step is progressively more expensive. Never elevate before fully exploiting — most plants have 15–25% hidden capacity at the constraint that exploitation recovers at minimal cost.

3.2 Buffer Management Advanced Patterns

Shipping Buffer: Protects customer due dates from internal variability. Typically 50% of the lead time from the constraint to shipping. If the constraint-to-shipping lead time is 2 days, the shipping buffer is 1 day — work should arrive at the shipping staging area 1 day before the committed ship date.

Assembly Buffer: In plants with convergent product structures (multiple components feeding a common assembly), each feeder path to the assembly point needs its own buffer. The assembly can only proceed when ALL components are present, so the slowest feeder path determines the effective buffer.

Dynamic Buffer Adjustment:

• If buffer penetration is consistently in the green zone (>80% of jobs arrive with buffer intact over a 4-week rolling window), reduce the buffer by 10–15%. Excess buffer means excess WIP and longer lead times.
• If buffer penetration frequently reaches red zone (>20% of jobs in a 4-week window), increase the buffer by 15–20% while investigating the root cause upstream.
• Never adjust buffers more frequently than every 2 weeks. Buffer management requires stable data over multiple cycles.

4. Disruption Recovery Protocols

4.1 Structured Disruption Response Framework

When a disruption occurs, follow this decision tree:

Step 1: Classify the Disruption

Step 2: Assess Constraint Impact

Step 3: Execute Recovery

1. Immediate (0–30 minutes): Assess duration and impact. Notify affected parties. Freeze in-process work.
2. Short-term (30 min – 4 hours): Re-sequence remaining work. Activate alternate routings. Assign backup operators. Request emergency maintenance.
3. Medium-term (4–24 hours): Negotiate overtime or shift extensions. Contact subcontractors. Update customer ETAs. Recalculate the full planning horizon.
4. Long-term (>24 hours): Capacity rebalancing. Possible order reallocation to alternate sites. Customer negotiations on delivery schedules. Insurance/force majeure documentation if applicable.

4.2 Material Shortage Response

1. Confirm the shortage: Verify physical inventory vs. system count. Phantom inventory is common — conduct a physical count before declaring a shortage.
2. Identify substitutes: Check BOM alternates, engineering-approved substitutions, and customer-approved equivalent materials. In regulated industries (aerospace, pharma), only pre-approved substitutes are permissible.
3. Partial build strategy: Can you complete operations up to the point where the short material is consumed, then hold semi-finished WIP for completion when material arrives? This keeps upstream work centres productive and preserves lead time on the non-missing portions of the routing.
4. Re-sequence: Pull forward all work orders that do not consume the short material. This keeps the plant productive even during the shortage.
5. Expedite procurement: Emergency purchase order at premium freight. Quantify: is the cost of expedited material + freight less than the cost of lost constraint time × hours of delay? If yes, expedite without hesitation.
6. Customer communication: If the shortage will impact customer deliveries, notify within 4 hours of confirmation. Provide a revised delivery date and a recovery plan.

4.3 Quality Hold Management

When an in-process quality issue is discovered:

1. Contain immediately: Quarantine all affected WIP — the batch in process, any completed units from the same batch, and any downstream assemblies that consumed units from the batch.
2. Assess scope: How many units are affected? Which customer orders consume these units? What is the rework cost vs. scrap cost vs. customer rejection cost?
3. Reschedule: Remove the held inventory from the active schedule. Recalculate all downstream operations that depended on this inventory.
4. Decision tree for held material:
   • Rework possible and economical: Schedule rework operations. Add rework time to the routing and re-sequence downstream.
   • Rework possible but not economical (rework cost > material + labour cost of remaking): Scrap the held batch and schedule a replacement production order from scratch.
   • Cannot rework, cannot scrap (regulatory hold pending investigation): Exclude from schedule indefinitely. Plan as though the inventory does not exist.
5. Root cause: While the schedule adjusts, quality engineering should be isolating the root cause. The scheduler needs to know: is this a one-time event, or will subsequent batches also be affected? If systemic, reduce yield assumptions for the affected operation in the scheduling parameters until the root cause is resolved.

5. Capacity Planning vs. Finite Scheduling

5.1 Rough-Cut Capacity Planning (RCCP)

RCCP is a medium-term planning tool (4–16 weeks out) that validates whether the MPS is feasible at a high level before detailed scheduling.

Process:

1. Take the MPS (production plan by product family by week).
2. Multiply by the routing hours per unit at each key work centre (typically only the constraint and 1–2 near-constraints).
3. Compare total required hours against available hours per week at each work centre.
4. If required hours exceed available hours, flag the overloaded weeks for action: demand shaping (move orders to adjacent weeks), overtime, subcontracting, or MPS revision.

RCCP Load Profile Example:

Actions for W25 overload:

• Can 22 hours of load shift to W24 or W26 without missing customer dates? Check due dates.
• If not shiftable: overtime (22 hrs ÷ 8 hrs/shift = 3 extra shifts, or 3 Saturday shifts).
• If overtime not available: which orders have the most flexible delivery dates? Negotiate.
• Last resort: subcontract 22 hours of work. Assess quality and lead time implications.

5.2 Finite Capacity Scheduling (FCS) Detail

FCS goes beyond RCCP by scheduling individual operations on specific resources at specific times, respecting:

1. Resource capacity: Number of machines × hours per shift × shifts per day, minus planned maintenance windows.
2. Sequence-dependent setups: Setup time varies based on the preceding job (see setup matrix in Section 2.2).
3. Material availability: An operation cannot start until all BOM components are available at the work centre.
4. Tooling constraints: A job requiring tooling set ABC cannot run simultaneously with another job requiring the same tooling.
5. Labour constraints: A job requiring a certified operator cannot be scheduled when no certified operator is on shift.
6. Operation dependencies: Operation 20 on a work order cannot start until Operation 10 is complete (routing precedence).
7. Transfer batches: Overlap operations can start before the full batch from the preceding operation is complete, if the transfer batch size is defined.

FCS Scheduling Algorithm (simplified):

1. Sort all operations by priority (using the hybrid dispatching approach from Section 1.2).
2. For the highest-priority unscheduled operation: a. Find the earliest feasible time slot on the required resource, considering capacity, material availability, tooling, labour, and predecessor completion. b. Schedule the operation in that slot. c. Update resource availability.
3. Repeat for the next-highest-priority operation.
4. After all operations are scheduled, run a post-optimisation pass looking for setup reduction opportunities (adjacent-swap improvements) that don't violate due dates.

5.3 Capacity Buffers and Protective Capacity

Non-constraint work centres should maintain protective capacity — deliberately planned idle time that absorbs variability and prevents WIP accumulation.

Target utilisation by work centre type:

Warning signs of insufficient protective capacity:

• WIP queues growing at non-constraint work centres over time.
• Non-constraint work centres occasionally becoming the bottleneck (shifting bottleneck).
• Overtime at non-constraint work centres "to keep up."
• Material handlers constantly expediting between non-constraint operations.

6. Multi-Constraint Scheduling

6.1 Interactive Constraints

When two or more work centres both exceed 85% utilisation and share a material flow path, they interact — improving throughput at one may starve or overload the other.

Identification: Two work centres are interactive constraints if:

1. They are on the same routing (material flows from one to the other), AND
2. Both exceed 85% utilisation, AND
3. Adding capacity at one causes the other's utilisation to exceed 95%.

Scheduling Strategy for Interactive Constraints:

1. Schedule the primary constraint first (the one with higher utilisation or the one closer to the customer).
2. Subordinate the secondary constraint to the primary's schedule — the secondary constraint processes work in the order and at the pace dictated by the primary constraint's output schedule.
3. Place a buffer between them — even though both are constraints, the upstream one should feed a time buffer to the downstream one to absorb variability.
4. Never optimise them independently. A setup sequence that is optimal for the primary constraint may create an impossible sequence for the secondary constraint if setups are sequence-dependent at both. Solve jointly.

6.2 Machine + Labour Dual Constraints

Common in environments where machines are semi-automated and require an operator for setup, first-piece inspection, or monitoring but can run unattended for portions of the cycle.

Scheduling approach:

1. Schedule machine capacity first (finite capacity by machine).
2. Overlay labour capacity (finite capacity by skill/certification).
3. Identify conflicts: time slots where the machine schedule requires an operator but no qualified operator is available.
4. Resolve conflicts by:
   • Shifting the job to a different machine that a different operator is qualified on.
   • Shifting the operator from a lower-priority job to the conflicting job.
   • Scheduling the operator's setup/inspection tasks at the start of the job and allowing unattended running thereafter.

6.3 Tooling as a Shared Constraint

When specialised tooling (moulds, dies, fixtures, gauges) is shared across machines:

1. Treat tooling as a resource in the scheduling system — the same way you schedule machines and labour, schedule tooling.
2. Two jobs requiring the same mould cannot run simultaneously on different machines.
3. Tooling changeover time between machines adds to the total changeover. If Mould A moves from Machine 1 to Machine 2, add the mould extraction time (Machine 1) + transport time + mould installation time (Machine 2).
4. Optimise by grouping: If three jobs all require Mould A, schedule them consecutively on the same machine to avoid mould transfers.

7. Line Balancing for Mixed-Model Production

7.1 Takt Time Calculation

Takt Time = Available Production Time per Shift / Customer Demand per Shift

Example: 480 minutes available per shift (8 hours × 60 min, minus 30 min breaks), customer demand is 240 units per shift.

Takt Time = 450 / 240 = 1.875 minutes per unit

Every workstation on the line must complete its tasks within 1.875 minutes per unit. If any station exceeds takt, it becomes the bottleneck and the line cannot meet demand.

7.2 Workstation Balancing

1. List all tasks with their duration and precedence relationships.
2. Assign tasks to workstations such that no workstation exceeds takt time.
3. Minimise the number of workstations (to minimise labour cost).
4. Measure balance efficiency:

Balance Efficiency = Σ(Task Times) / (Number of Stations × Takt Time) × 100%

Target: >85%. Below 80% indicates significant idle time at some stations.

7.3 Mixed-Model Sequencing (Heijunka)

When a line produces multiple models with different task times:

1. Calculate the weighted average cycle time across models.
2. Determine the model mix ratio (e.g., Model A: 60%, Model B: 30%, Model C: 10%).
3. Create a repeating pattern that levels the workload. For A:B:C = 6:3:1, a 10-unit cycle would be: A-B-A-A-C-A-B-A-B-A.
4. Validate that the bottleneck station can handle every model within takt. If Model C takes 2.5 minutes at Station 3 while takt is 1.875 minutes, Model C must be spaced sufficiently that Station 3 can catch up between occurrences.

8. Scheduling with Regulatory and Compliance Constraints

8.1 Traceability-Driven Scheduling

In regulated industries (pharmaceutical, food, aerospace), lot traceability requirements constrain scheduling flexibility:

• No lot mixing: A work order for Lot A and a work order for Lot B cannot share equipment simultaneously unless the equipment is fully cleaned between lots and the cleaning is documented.
• Dedicated equipment campaigns: When allergen or contamination controls require dedicated equipment, the scheduling window for Product X on Line 1 is limited to the dedicated campaign period. Scheduling outside this window requires re-validation.
• Operator qualification records: The schedule must record which operator performed each operation, and that operator must be certified at the time of execution.

8.2 Clean-In-Place (CIP) Scheduling

In food, beverage, and pharma, CIP cycles are mandatory between certain product transitions:

Schedule CIP cycles as fixed blocks in the schedule, not as "setup time" that can be compressed. Under-estimating CIP time is a common scheduling error that creates cascading delays and regulatory risk.

9. Schedule Stability and Frozen Zones

9.1 Frozen / Slushy / Liquid Planning Horizons

Why frozen zones matter: Every schedule change triggers a cascade — material handlers re-stage kits, operators re-read work orders, quality pre-inspections may need repeating, and changeover sequences recalculate. A plant that changes the schedule 10 times per shift has more disruption from schedule changes than from actual production problems.

9.2 Schedule Change Cost Model

Before approving a schedule change in the frozen or slushy zone, estimate the total cost:

Change Cost = Changeover Cost Delta + Material Restaging Cost + Labour Disruption Cost
              + Quality Re-inspection Cost + Customer Impact Risk

If Change Cost > Benefit of Change, reject the change and hold the current schedule. Document the decision for the post-shift review.

10. Overtime and Shift Extension Decision Framework

10.1 When to Authorise Overtime

Overtime is a scheduling lever, not a default. Use the following decision tree:

1. Is the overtime required at the constraint?

   • Yes → Calculate: overtime cost vs. throughput value of additional constraint hours. If 4 hours of constraint overtime at $1,200 total cost enables $20,000 of shipments, approve immediately. The ROI threshold for constraint overtime is typically 3:1 (value:cost) or higher.
   • No → The overtime at a non-constraint does not increase plant output. It only makes sense if: (a) the non-constraint is starving the constraint and buffer penetration is yellow/red, or (b) the non-constraint output is needed for a specific customer shipment that cannot wait for the next regular shift.

2. Is the overtime voluntary or mandatory?

   • Check union contract or labour regulations. Many agreements require offering overtime by seniority before mandating it. Mandatory overtime may require 24–48 hours' notice.
   • Violating overtime assignment rules costs more in grievances and morale damage than the production it generates. Always comply.

3. Fatigue and safety risk:

   • Operators who have already worked 10+ hours should not be assigned to the constraint or to safety-critical operations. Error rates increase 25–40% in hours 11–12.
   • If the overtime extends a 12-hour shift to 16 hours, assign the extended operator to non-critical monitoring tasks and bring in a fresh operator for the constraint.

10.2 Shift Pattern Comparison for Scheduling

Handover quality matters for scheduling: Each handover is a potential point of information loss — the incoming shift may not know about a developing quality issue, a material shortage workaround, or a verbal schedule change. Fewer handovers (12-hour shifts) improve information continuity but increase fatigue risk. Balance based on operation complexity and error tolerance.

11. Subcontracting Decision Framework

11.1 When to Subcontract

Subcontracting is the scheduling lever of last resort for capacity shortfalls.

Decision criteria (all must be met):

1. Internal capacity at the required work centre is fully consumed through the delivery deadline, including available overtime.
2. The operation is not at the constraint (subcontracting from the constraint usually means the constraint needs elevation, not a one-time fix).
3. A qualified subcontractor exists who can meet the quality specification and delivery timeline.

…(truncated)