* Add 8 operational domain skills from Evos Adds domain-expert skills for logistics, manufacturing, retail, and energy operations. Each codifies 15+ years of real industry expertise. Source: https://github.com/ai-evos/agent-skills License: Apache-2.0 Co-authored-by: Cursor <cursoragent@cursor.com> * Add reference files and fix frontmatter validation - Change risk: low to risk: safe (valid enum value) - Add source field pointing to upstream repo - Include references/ directory for each skill Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Cursor <cursoragent@cursor.com>
868 lines
46 KiB
Markdown
868 lines
46 KiB
Markdown
# Decision Frameworks — Production Scheduling
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This reference provides the detailed decision logic, scheduling algorithms, optimisation
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methodologies, and capacity planning techniques for production scheduling in discrete
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and batch manufacturing. It is loaded on demand when the agent needs to make or recommend
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nuanced scheduling decisions.
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All thresholds, formulas, and time assumptions reflect discrete and batch manufacturing
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operations running 3–8 production lines with 50–300 direct-labour headcount per shift.
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---
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## 1. Job Scheduling Algorithms
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### 1.1 Dispatching Rules — When to Use Each
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Dispatching rules are heuristics applied at a work centre when multiple jobs compete for
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the same resource. No single rule dominates in all situations. The choice depends on the
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plant's primary performance objective.
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| Rule | Definition | Best For | Weakness |
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|---|---|---|---|
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| **SPT (Shortest Processing Time)** | Process the job with the shortest operation time first | Minimising average flow time, reducing WIP, maximising throughput when setup times are negligible | Starves long jobs — a job with 8-hour run time waits behind twenty 20-minute jobs. Creates due date violations on long-cycle products. |
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| **EDD (Earliest Due Date)** | Process the job with the earliest due date first | Minimising maximum lateness across all jobs, meeting delivery commitments | Ignores processing time — a job due tomorrow with an 8-hour run time gets priority over a job due in 2 hours with a 5-minute run. Can increase WIP if many jobs have distant due dates. |
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| **Critical Ratio (CR)** | CR = (Due Date − Now) / Remaining Processing Time. Schedule lowest CR first. | Balancing due date urgency with remaining work. CR < 1.0 means the job is behind schedule. | Breaks down when due dates are unrealistic (all CRs < 0.5). Requires accurate remaining processing time estimates. |
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| **Weighted Shortest Job First (WSJF)** | Priority = (Cost of Delay × Job Weight) / Processing Time. Schedule highest priority first. | Environments where jobs have different economic value. Maximises throughput-weighted value. | Requires reliable cost-of-delay estimates, which are often subjective. Can starve low-value long jobs indefinitely. |
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| **Slack Time (ST)** | Slack = Due Date − Now − Remaining Processing Time. Schedule lowest slack first. | Similar to CR but uses absolute slack rather than ratio. Better when processing times are similar. | Same as CR — degrades with unrealistic due dates. Does not account for queue time at downstream work centres. |
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| **FIFO (First In, First Out)** | Process jobs in arrival order at the work centre | Ensuring fairness, simple to communicate, works in stable environments with predictable flow | No optimisation — ignores due dates, processing times, and economic value. Use only when all jobs are equal priority and flow is balanced. |
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#### Algorithm Selection Decision Tree
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1. **Is schedule adherence the primary KPI and are there contractual delivery penalties?**
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→ Use EDD as the primary rule. Insert CR checks for jobs where CR < 0.8 — these need
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immediate attention regardless of EDD rank.
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2. **Is throughput/output the primary KPI with flexible delivery windows?**
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→ Use SPT to minimise average flow time. Monitor maximum lateness; if it exceeds
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the acceptable threshold, switch to a hybrid SPT-EDD (SPT within a due date window).
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3. **Do jobs have significantly different economic values (margin, penalty, customer tier)?**
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→ Use WSJF. Weight = customer tier multiplier × margin contribution. This is the
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appropriate rule for job shops with heterogeneous order portfolios.
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4. **Are setup times sequence-dependent and significant (>15 minutes between families)?**
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→ No pure dispatching rule handles this. Use a setup-aware scheduling heuristic
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(Section 2) that groups jobs by setup family and optimises within groups using EDD.
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5. **Is the environment stable with balanced flow and predictable demand?**
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→ FIFO is acceptable and preferred for its simplicity and shop floor trust.
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### 1.2 Multi-Rule Hybrid Approaches
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In practice, most schedulers use a hybrid approach layered as follows:
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**Layer 1 — Hard Constraints (filter)**
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Remove any job from the queue that lacks material, tooling, or a qualified operator.
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These jobs are not schedulable regardless of priority.
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**Layer 2 — Urgency Override (force-rank)**
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Jobs with CR < 0.8 or that are already past-due are force-ranked to the top,
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ordered by customer penalty exposure descending.
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**Layer 3 — Primary Dispatching Rule (sort remaining)**
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Apply the selected dispatching rule (EDD, SPT, WSJF, etc.) to remaining jobs.
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**Layer 4 — Setup Optimisation (local reorder)**
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Within the primary sequence, perform adjacent-swap improvements to reduce
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total setup time, subject to the constraint that no swap causes a due date
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violation for either swapped job.
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**Layer 5 — Labour Levelling (validate)**
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Check that the resulting sequence does not create labour peaks that exceed
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available headcount for any hour of the shift. If it does, defer the lowest-
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priority job creating the peak to the next available slot.
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### 1.3 Critical Ratio in Detail
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Critical Ratio is the most versatile single dispatching rule for mixed environments.
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**Formula:**
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```
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CR = (Due Date − Current Date) / Remaining Total Processing Time
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```
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Where Remaining Total Processing Time includes:
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- Setup time for the current operation
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- Run time for the current operation
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- Queue time estimates for remaining operations (use historical average queue times)
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- Setup + run times for all remaining operations in the routing
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**Interpretation:**
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| CR Value | Meaning | Action |
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|---|---|---|
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| CR > 2.0 | Comfortable lead — job is well ahead of schedule | Lowest priority. May be deferred if capacity is needed for tighter jobs. |
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| 1.0 < CR < 2.0 | On track but limited slack | Schedule normally per dispatching rule |
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| CR = 1.0 | Exactly on schedule — no slack remaining | Monitor closely. Any disruption will cause lateness. |
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| 0.5 < CR < 1.0 | Behind schedule — will be late without intervention | Escalate. Consider overtime, alternate routing, or partial shipment. |
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| CR < 0.5 | Critically late — recovery is unlikely without significant intervention | Immediate escalation to production manager. Notify customer of revised date. |
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**Updating CR:** Recalculate CR at every operation completion and at the start of every
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shift. A job with CR = 1.5 at shift start that encounters a 4-hour unplanned delay mid-shift
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may drop to CR = 0.7 — the shift supervisor needs to know this in real time.
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### 1.4 Weighted Scheduling for Customer Tiers
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Manufacturing plants serving multiple customer tiers need a weighting system:
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| Customer Tier | Weight Multiplier | Rationale |
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|---|---|---|
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| Tier 1 (OEM, contractual penalties) | 3.0 | Late delivery triggers financial penalties, production line-down claims |
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| Tier 2 (Key accounts, framework agreements) | 2.0 | No contractual penalty but relationship value and reorder risk |
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| Tier 3 (Standard accounts) | 1.0 | Standard terms, no penalty |
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| Tier 4 (Spot orders, distributors) | 0.5 | Price-sensitive, low switching cost for them |
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**WSJF with Customer Tier:**
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```
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Priority Score = (Customer Tier Weight × Days Until Due / Remaining Processing Time)
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```
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Lower score = higher priority (more urgent). Negative scores = past-due.
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---
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## 2. Changeover Optimisation
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### 2.1 SMED Implementation Phases — Step by Step
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#### Phase 0 — Document the Current State (2–4 weeks)
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1. Video-record 3–5 changeovers on the target machine/line. Include the full duration
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from last good piece of the outgoing product to first good piece of the incoming product.
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2. Create a changeover element sheet listing every task performed, the performer
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(operator, setup tech, maintenance), the duration, and whether the machine was stopped.
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3. Categorize each element:
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- **Internal (IED):** Must be performed with the machine stopped.
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- **External (OED):** Can be performed while the machine is still running.
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- **Waste:** Not necessary at all — holdover from old procedures, redundant checks, waiting.
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Typical finding: 30–50% of changeover time is either external work incorrectly performed
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during machine stoppage, or pure waste (searching for tools, waiting for approval,
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walking to the tool crib).
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#### Phase 1 — Separate Internal and External (2–4 weeks)
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1. Move all external elements to pre-changeover preparation:
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- Pre-stage next-job tooling, dies, fixtures at the machine before the changeover begins.
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- Pre-mix materials, pre-heat moulds, pre-program CNC settings.
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- Pre-print work order documentation and quality checklists.
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2. Create a standardised changeover preparation checklist. The setup technician begins
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executing it 30–60 minutes before the scheduled changeover time.
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3. Expected result: 25–40% reduction in machine-stopped time with no capital investment.
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#### Phase 2 — Convert Internal to External (4–8 weeks)
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1. Standardise die/fixture heights and mounting interfaces so that alignment and adjustment
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happen before the die reaches the machine, not after.
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2. Implement intermediate jigs — set up the next tool in a staging fixture that mirrors
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the machine's mounting interface. When the changeover begins, the pre-assembled unit
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drops in with minimal adjustment.
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3. Pre-condition materials: if the incoming product requires a different temperature,
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viscosity, or chemical mix, start conditioning in a parallel vessel.
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4. Expected result: additional 15–25% reduction in machine-stopped time. May require
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modest investment in duplicate tooling or staging fixtures.
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#### Phase 3 — Streamline Remaining Internal Elements (4–12 weeks)
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1. Replace bolt-on fasteners with quick-release clamps, cam locks, or hydraulic clamping.
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Every bolt removed saves 15–30 seconds.
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2. Eliminate adjustments through poka-yoke: centre pins, guide rails, fixed stops that
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guarantee first-piece alignment without trial-and-error.
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3. Standardise utility connections: colour-coded quick-disconnect fittings for air, water,
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hydraulic, and electrical. One-motion connect/disconnect.
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4. Parallel operations: two people working simultaneously on different sides of the machine
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can halve the internal time. Requires choreographed procedures and safety protocols.
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5. Expected result: additional 10–20% reduction. Often requires capital investment in
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quick-change tooling.
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#### Phase 4 — Eliminate Adjustments and Verify (ongoing)
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1. Implement first-piece verification jigs that confirm dimensions without full inspection.
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2. Use statistical process control (SPC) from the first piece — if the first piece is within
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control limits, the changeover is validated without a trial run.
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3. Document the final standardised changeover procedure with photos, time targets per element,
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and a sign-off sheet.
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4. Target: changeover time under 10 minutes (single-minute exchange of die) for the
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machine-stopped portion.
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### 2.2 Sequence-Dependent Setup Matrices
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For operations where setup time varies by product-to-product transition, build a
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setup time matrix:
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**Example — Paint Line Setup Matrix (minutes):**
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| From \ To | White | Yellow | Orange | Red | Blue | Black |
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|---|---|---|---|---|---|---|
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| **White** | 0 | 8 | 10 | 15 | 20 | 25 |
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| **Yellow** | 15 | 0 | 8 | 12 | 20 | 25 |
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| **Orange** | 20 | 12 | 0 | 8 | 18 | 22 |
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| **Red** | 25 | 18 | 12 | 0 | 15 | 18 |
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| **Blue** | 20 | 22 | 20 | 18 | 0 | 10 |
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| **Black** | 30 | 28 | 25 | 22 | 12 | 0 |
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**Observations from this matrix:**
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- Light-to-dark transitions (White → Black: 25 min) are cheaper than dark-to-light (Black → White: 30 min).
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- Within colour families, transitions are minimal (Red → Orange: 12 min vs. Red → White: 25 min).
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- 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).
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**Using the matrix in scheduling:**
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1. Group jobs by colour family when possible (campaign scheduling within families).
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2. When inter-family transitions are required, optimise the transition sequence using the
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nearest-neighbour heuristic, then improve with 2-opt swaps.
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3. If a specific colour is due earliest but the optimal setup sequence would delay it,
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compute the cost of the suboptimal sequence (extra setup minutes × constraint hourly rate)
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vs. the cost of late delivery. Choose the lower-cost option.
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### 2.3 Campaign Length Optimisation
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**Economic Production Quantity (EPQ):**
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```
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EPQ = √((2 × D × S) / (H × (1 − D/P)))
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```
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Where:
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- D = demand rate (units per period)
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- S = setup cost per changeover (labour + scrap + lost output opportunity cost)
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- H = holding cost per unit per period
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- P = production rate (units per period), P > D
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**Practical adjustments:**
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- Round EPQ up to the nearest full shift or full batch to avoid mid-shift changeovers.
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- If EPQ results in WIP that exceeds available staging space, constrain to physical capacity.
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- If EPQ results in a campaign longer than the longest customer lead time tolerance,
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shorten it to maintain responsiveness even at higher changeover frequency.
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**Campaign vs. mixed-model decision:**
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| Factor | Favours Campaign | Favours Mixed-Model |
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|---|---|---|
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| Setup time | Long (>60 min) | Short (<15 min) |
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| Setup cost | High (>$500 per changeover) | Low (<$100 per changeover) |
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| Demand variability | Low (stable, forecastable) | High (volatile, order-driven) |
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| Customer lead time expectation | Tolerant (>2 weeks) | Tight (<3 days) |
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| WIP carrying cost | Low | High |
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| Product shelf life | Long or N/A | Short or regulated |
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| Number of product variants | Few (<10) | Many (>50) |
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---
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## 3. Theory of Constraints (TOC) Implementation
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### 3.1 Drum-Buffer-Rope — Step by Step
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**Step 1: Identify the Constraint**
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Run a capacity analysis for each work centre over the next planning horizon (1–4 weeks):
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```
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Utilisation = Σ(Setup Time + Run Time for all scheduled jobs) / Available Time
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```
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Available Time = shift hours × number of machines × (1 − planned maintenance %)
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The work centre with the highest utilisation ratio is the drum. If multiple work centres
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exceed 90% utilisation, the one with the least flexibility (fewest alternate routings,
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most specialised equipment) is the primary constraint.
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**Validation test:** If you could add 10% more capacity to the suspected constraint
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(one more machine, one more shift hour, or a 10% speed increase), would total plant
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output increase by approximately 10%? If yes, it is the true constraint. If output
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increases less (because a second work centre immediately becomes the bottleneck),
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you have an interactive constraint pair that requires different treatment.
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**Step 2: Exploit the Constraint**
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Maximise the output of the constraint with no capital investment:
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1. **Eliminate idle time:** The constraint should never wait for material, tooling,
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operators, quality inspection, or information. Pre-stage everything.
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2. **Minimise changeovers on the constraint:** Move changeover to non-constraint
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resources where the time cost is lower. If the constraint must change over,
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ensure SMED discipline is applied rigorously.
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3. **Prevent quality defects reaching the constraint:** Inspect before the constraint
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operation, not after. Every defective piece processed at the constraint is wasted
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constraint capacity.
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4. **Run through breaks and shift changes:** Stagger operator lunches so the constraint
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never stops for a break. Assign a relief operator.
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5. **Eliminate micro-stops:** Address every source of 1–5 minute stoppages (sensor trips,
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material jams, tool wear alarms) that individually seem trivial but cumulatively steal
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2–5% of capacity.
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**Step 3: Subordinate Everything to the Constraint**
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1. **Upstream work centres:** Release work to upstream operations only at the rate the
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constraint can consume it. This is the "rope." If the constraint processes 100 units/hour,
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the upstream release rate should not exceed 100 units/hour regardless of upstream capacity.
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2. **Downstream work centres:** Must maintain enough sprint capacity to clear constraint
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output without becoming a secondary bottleneck. If the constraint produces a batch every
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2 hours, downstream must be able to process that batch within 2 hours.
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3. **Scheduling non-constraints:** Do not optimise non-constraint schedules in isolation.
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A non-constraint running at 100% utilisation when the constraint runs at 85% is producing
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excess WIP that clogs the shop floor and slows the constraint's material flow.
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**Step 4: Establish the Buffer**
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The constraint buffer is a time buffer, not an inventory buffer:
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```
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Buffer Duration = Planned Lead Time from release to constraint × Buffer Factor
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```
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Typical buffer factors:
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- Stable, reliable upstream operations: 0.3 × lead time
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- Moderate reliability, some variability: 0.5 × lead time (most common starting point)
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- Unreliable upstream, frequent disruptions: 0.75 × lead time
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**Buffer sizing example:**
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If the upstream lead time from raw material release to the constraint work centre is
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8 hours, and upstream reliability is moderate, set the buffer at 4 hours. This means
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material should arrive at the constraint staging area at least 4 hours before the
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constraint is scheduled to process it.
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**Step 5: Monitor Buffer Penetration**
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| Zone | Buffer Consumed | Meaning | Action |
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|---|---|---|---|
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| Green | 0–33% | Constraint well-protected | Normal operations |
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| Yellow | 33–67% | Warning — material may arrive late | Expedite upstream work. Check for blockers. |
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| Red | 67–100% | Critical — constraint at risk of starvation | Immediate escalation. Overtime upstream. Re-sequence if needed. |
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| Black | >100% | Buffer exhausted — constraint is starving | Constraint is idle or will be idle. Emergency response. Every minute of delay from this point = lost plant output. |
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Track buffer penetration trends over 2–4 weeks. Persistent yellow indicates
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a systemic upstream issue (not random variation) that needs corrective action.
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**Step 6: Elevate the Constraint (only if Steps 1–5 are exhausted)**
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If after full exploitation and subordination the constraint still limits plant output
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below demand requirements:
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1. Add overtime or a weekend shift at the constraint only.
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2. Add a parallel machine or alternate routing capability.
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3. Outsource constraint-specific operations to a qualified subcontractor.
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4. Invest in faster constraint equipment (capital expenditure).
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Each elevation step is progressively more expensive. Never elevate before fully
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exploiting — most plants have 15–25% hidden capacity at the constraint that
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exploitation recovers at minimal cost.
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### 3.2 Buffer Management Advanced Patterns
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**Shipping Buffer:** Protects customer due dates from internal variability. Typically
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50% of the lead time from the constraint to shipping. If the constraint-to-shipping
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lead time is 2 days, the shipping buffer is 1 day — work should arrive at the
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shipping staging area 1 day before the committed ship date.
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**Assembly Buffer:** In plants with convergent product structures (multiple components
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feeding a common assembly), each feeder path to the assembly point needs its own
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buffer. The assembly can only proceed when ALL components are present, so the
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slowest feeder path determines the effective buffer.
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**Dynamic Buffer Adjustment:**
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- If buffer penetration is consistently in the green zone (>80% of jobs arrive with
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buffer intact over a 4-week rolling window), reduce the buffer by 10–15%. Excess buffer
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means excess WIP and longer lead times.
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- If buffer penetration frequently reaches red zone (>20% of jobs in a 4-week window),
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increase the buffer by 15–20% while investigating the root cause upstream.
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- Never adjust buffers more frequently than every 2 weeks. Buffer management requires
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stable data over multiple cycles.
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---
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## 4. Disruption Recovery Protocols
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### 4.1 Structured Disruption Response Framework
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When a disruption occurs, follow this decision tree:
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**Step 1: Classify the Disruption**
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| Type | Examples | Typical Duration | Impact Scope |
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|---|---|---|---|
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| **Equipment** | Breakdown, sensor failure, tooling wear | 30 min – 3 days | Single work centre |
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| **Material** | Shortage, wrong specification, quality reject of incoming | 2 hours – 2 weeks | Multiple work centres sharing the material |
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| **Labour** | Absenteeism, injury, certification gap | 1 shift – 1 week | Single work centre or line |
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| **Quality** | In-process defect, customer complaint triggering hold | 2 hours – 1 week | Entire batch/lot, plus downstream consumers |
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| **External** | Supplier failure, power outage, weather, regulatory stop | 4 hours – indefinite | Potentially plant-wide |
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**Step 2: Assess Constraint Impact**
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| Disruption Location | Constraint Impact | Response Priority |
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|---|---|---|
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| At the constraint | Direct — every minute = lost throughput | Maximum priority. All resources mobilised. |
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| Upstream of constraint, buffer is green | Indirect — buffer absorbs the delay | Monitor buffer penetration. No immediate schedule change. |
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| Upstream of constraint, buffer is yellow/red | Indirect but imminent — constraint will starve | Expedite. Overtime upstream. Re-sequence to feed constraint from alternate sources. |
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| Downstream of constraint | No throughput impact unless WIP backs up to constraint | Monitor. Clear downstream blockage before constraint output starts queuing. |
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| Parallel path (no constraint interaction) | No throughput impact, but delivery impact on affected orders | Re-sequence affected orders. Notify customers. |
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**Step 3: Execute Recovery**
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1. **Immediate (0–30 minutes):** Assess duration and impact. Notify affected parties. Freeze in-process work.
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2. **Short-term (30 min – 4 hours):** Re-sequence remaining work. Activate alternate routings. Assign backup operators. Request emergency maintenance.
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3. **Medium-term (4–24 hours):** Negotiate overtime or shift extensions. Contact subcontractors. Update customer ETAs. Recalculate the full planning horizon.
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4. **Long-term (>24 hours):** Capacity rebalancing. Possible order reallocation to alternate sites. Customer negotiations on delivery schedules. Insurance/force majeure documentation if applicable.
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### 4.2 Material Shortage Response
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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:**
|
||
|
||
| Week | Constraint Capacity (hrs) | Required Load (hrs) | Utilisation | Status |
|
||
|---|---|---|---|---|
|
||
| W23 | 120 | 105 | 87.5% | OK |
|
||
| W24 | 120 | 118 | 98.3% | Warning — near capacity |
|
||
| W25 | 120 | 142 | 118.3% | Overloaded — action needed |
|
||
| W26 | 120 | 96 | 80.0% | OK — could absorb W25 overflow |
|
||
| W27 | 80 (planned maintenance window) | 75 | 93.8% | Tight — maintenance may need rescheduling |
|
||
|
||
**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:**
|
||
|
||
| Work Centre Type | Target Utilisation | Rationale |
|
||
|---|---|---|
|
||
| Constraint | 90–95% | Maximise output. Buffer everything else to protect it. |
|
||
| Near-constraint (>80% loaded) | 85–90% | Close to becoming the constraint. Monitor for shifting bottleneck. |
|
||
| Standard | 75–85% | Protective capacity absorbs upstream variability. |
|
||
| Shared resource (forklift, crane, inspector) | 60–75% | High variability in demand for these resources. Over-scheduling creates system-wide delays. |
|
||
| Rework/repair | 50–70% | Must have capacity available on demand. Cannot schedule at high utilisation. |
|
||
|
||
**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:
|
||
|
||
| Transition Type | CIP Duration | Can Be Shortened? |
|
||
|---|---|---|
|
||
| Same product, next batch | 0–15 min (rinse only) | No — regulatory minimum |
|
||
| Same product family | 30–60 min (standard CIP) | Only with validated short-CIP protocol |
|
||
| Different product family | 60–120 min (full CIP) | No — regulatory requirement |
|
||
| Allergen transition | 120–240 min (enhanced CIP + swab test) | No — requires analytical confirmation |
|
||
|
||
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
|
||
|
||
| Horizon | Typical Duration | Flexibility | Changes Require |
|
||
|---|---|---|---|
|
||
| **Frozen** | 0–48 hours | No changes except force majeure | Production Manager + Scheduler approval |
|
||
| **Slushy** | 48 hours – 1 week | Sequence changes allowed within day; no date changes | Scheduler approval |
|
||
| **Liquid** | 1–4 weeks | Fully flexible for re-sequencing and rescheduling | Scheduler discretion |
|
||
| **Tentative** | 4+ weeks | MRP-generated, not yet scheduled | Planning/MRP cycle |
|
||
|
||
**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
|
||
|
||
| Pattern | Hours/Week | Handovers/Week | Overtime Headroom | Best For |
|
||
|---|---|---|---|---|
|
||
| 3 × 8h (Mon–Fri) | 120 | 15 | Saturday shifts, daily OT | High-mix, moderate volume |
|
||
| 3 × 8h (24/7) | 168 | 21 | Limited — already near capacity | Process industries, continuous flow |
|
||
| 2 × 12h (Mon–Fri) | 120 | 10 | Weekend shifts | Capital-intensive with fewer handovers |
|
||
| 2 × 12h (4 on / 4 off) | 168 | 14 | Built into rotation | High-volume, steady demand |
|
||
| 4 × 10h (day shift only) | 40 per crew | 4 | Friday, weekend | Low-volume, single-shift operations |
|
||
|
||
**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.
|
||
4. The subcontracting cost + transport cost + quality risk cost is less than the cost of
|
||
late delivery (penalties + customer relationship damage).
|
||
5. In regulated industries: the subcontractor holds the necessary certifications
|
||
(ISO, IATF 16949, AS9100, FDA registration, etc.).
|
||
|
||
### 11.2 Scheduling with Subcontracted Operations
|
||
|
||
When an operation is subcontracted:
|
||
1. Remove the operation from the internal schedule.
|
||
2. Add a transport-out time (typically 0.5–2 days) and transport-in time.
|
||
3. Add the subcontractor's quoted lead time (add 20% buffer for first-time subcontractors).
|
||
4. The total external lead time replaces the internal operation time in the work order routing.
|
||
5. Schedule downstream internal operations based on the expected return date, not the
|
||
internal processing time.
|
||
6. Monitor subcontractor progress at 50% and 90% completion milestones. Do not wait until
|
||
the due date to discover a delay.
|
||
|
||
---
|
||
|
||
## 12. Scheduling Metrics and Continuous Improvement
|
||
|
||
### 12.1 Key Scheduling Metrics
|
||
|
||
| Metric | Calculation | Target | What It Reveals |
|
||
|---|---|---|---|
|
||
| **Schedule Adherence** | Jobs started within ±1 hour of plan / Total jobs | > 90% | How well the plant follows the schedule |
|
||
| **Schedule Stability** | Jobs unchanged in frozen zone / Total frozen jobs | > 95% | How often the schedule is disrupted |
|
||
| **On-Time Delivery (OTD)** | Orders shipped on or before commit date / Total orders | > 95% | Customer-facing performance |
|
||
| **Make Span** | Time from first operation start to last operation end for a work order | Track vs. standard | Total production lead time |
|
||
| **Changeover Ratio** | Total changeover time / Total available time at the resource | < 10% at constraint | Setup efficiency |
|
||
| **Constraint Utilisation** | Actual producing time / Available time at constraint | > 85% | How well the constraint is exploited |
|
||
| **WIP Turns** | Annual COGS / Average WIP Value | > 12 for discrete mfg | Scheduling efficiency and flow |
|
||
| **Queue Time Ratio** | Queue time / Total lead time at each work centre | Track trend | Indicates hidden WIP and poor flow |
|
||
|
||
### 12.2 Scheduling Post-Mortem Process
|
||
|
||
After every significant schedule disruption (constraint downtime > 1 hour, customer delivery
|
||
miss, or overtime exceeding budget by > 20%), conduct a structured post-mortem:
|
||
|
||
1. **Timeline reconstruction:** What happened, when, and what was the cascade of effects?
|
||
2. **Root cause:** Was the disruption caused by equipment, material, labour, quality,
|
||
scheduling logic, or external factors?
|
||
3. **Response assessment:** Was the re-sequencing decision optimal? Could the recovery have
|
||
been faster? Were communications timely?
|
||
4. **Parameter update:** Do scheduling parameters (setup times, run rates, yield factors,
|
||
buffer sizes) need adjustment based on what we learned?
|
||
5. **Systemic fix:** What preventive action will reduce the probability or impact of this
|
||
type of disruption recurring?
|
||
|
||
Document findings in a scheduling incident log. Review the log monthly with production
|
||
management to identify patterns and prioritise improvement actions.
|
||
|
||
### 12.3 Daily Scheduling Rhythm
|
||
|
||
A disciplined daily cadence prevents reactive fire-fighting:
|
||
|
||
| Time | Activity | Participants |
|
||
|---|---|---|
|
||
| Shift Start − 30 min | Pre-shift review: verify material staging, operator availability, equipment status | Scheduler, Shift Supervisor |
|
||
| Shift Start | Publish shift schedule. Walk the floor to confirm understanding. | Scheduler |
|
||
| Shift Start + 2 hrs | First checkpoint: plan adherence, buffer penetration, early disruption detection | Scheduler (desk review of MES data) |
|
||
| Shift Midpoint | Mid-shift review: actual vs. plan, re-sequence if needed | Scheduler, Shift Supervisor |
|
||
| Shift End − 1 hr | End-of-shift projection: what will be incomplete? Handover notes for next shift. | Scheduler, Shift Supervisor |
|
||
| Shift End | Shift handover: in-person (preferred) or documented. Key issues, deviations, pending decisions. | Outgoing + Incoming Schedulers |
|
||
| Daily (Morning) | Production meeting: yesterday's performance, today's priorities, issues requiring management decision | Scheduler, Production Mgr, Quality, Maintenance, Materials |
|
||
|
||
This cadence creates at least 5 touchpoints per shift where the schedule is validated
|
||
against reality and corrected before deviations compound.
|
||
|
||
---
|
||
|
||
## 13. ERP-to-Shop-Floor Data Flow
|
||
|
||
### 13.1 SAP PP Integration Pattern
|
||
|
||
```
|
||
Sales Orders / Forecast
|
||
↓
|
||
Demand Management (MD61/MD62)
|
||
↓
|
||
MPS — Master Production Schedule (MD40/MD43)
|
||
↓
|
||
MRP Run (MD01/MD02) → Planned Orders
|
||
↓
|
||
Convert Planned → Production Orders (CO40/CO41)
|
||
↓
|
||
Sequence in APS/Scheduling Tool (external or PP/DS)
|
||
↓
|
||
Release to Shop Floor (CO02 — set status REL)
|
||
↓
|
||
MES Execution (operation confirmations — CO11N/CO15)
|
||
↓
|
||
Goods Receipt (MIGO) → Inventory Updated
|
||
```
|
||
|
||
**Common data quality issues:**
|
||
- Routing times (setup + run) not updated after process improvements → schedule
|
||
systematically allocates too much or too little time.
|
||
- BOM quantities not adjusted for yield → MRP under-orders material.
|
||
- Work centre capacity not reflecting actual shift patterns → FCS generates
|
||
infeasible schedules.
|
||
- Scrap reporting delayed → plan-vs-actual gap grows silently.
|
||
|
||
### 13.2 Closing the Feedback Loop
|
||
|
||
The single most important integration is the MES-to-schedule feedback:
|
||
|
||
1. **Operation start:** MES records actual start time. Schedule compares to planned start.
|
||
Deviation > 1 hour triggers an alert.
|
||
2. **Operation end:** MES records actual end time and quantities (good + scrap). Schedule
|
||
updates remaining operations with actual predecessor completion.
|
||
3. **Downtime events:** MES captures downtime start, end, and reason code. Schedule
|
||
automatically adjusts downstream timing.
|
||
4. **Quality events:** MES captures inspection results. Failed inspection triggers a
|
||
schedule hold on the affected batch.
|
||
|
||
Without this feedback loop, the schedule diverges from reality within hours and becomes
|
||
aspirational rather than operational. The shop floor stops consulting it, operators make
|
||
their own sequencing decisions, and throughput at the constraint drops because ad-hoc
|
||
sequencing ignores constraint protection logic.
|