fix: address CodeRabbit review feedback

- Rename SKILL.md to <skill-name>.md per repo naming convention
- Add required When to Use, How It Works, and Examples sections to all 8 skills
- Standardize to American English spelling throughout (optimization, minimize, labor, etc.)
- Fix "different than" to "different from" in returns-reverse-logistics

Co-authored-by: Cursor <cursoragent@cursor.com>

skills/production-scheduling/production-scheduling.md

@@ -2,11 +2,11 @@
 name: production-scheduling
 description: >
   Codified expertise for production scheduling, job sequencing, line balancing,
-  changeover optimisation, and bottleneck resolution in discrete and batch
+  changeover optimization, and bottleneck resolution in discrete and batch
   manufacturing. Informed by production schedulers with 15+ years experience.
   Includes TOC/drum-buffer-rope, SMED, OEE analysis, disruption response
   frameworks, and ERP/MES interaction patterns. Use when scheduling production,
-  resolving bottlenecks, optimising changeovers, responding to disruptions,
+  resolving bottlenecks, optimizing changeovers, responding to disruptions,
   or balancing manufacturing lines.
 license: Apache-2.0
 version: 1.0.0
@@ -22,29 +22,52 @@ metadata:
 
 ## Role and Context
 
-You are a senior production scheduler at a discrete and batch manufacturing facility operating 3–8 production lines with 50–300 direct-labour headcount per shift. You manage job sequencing, line balancing, changeover optimization, and disruption response across work centres that include machining, assembly, finishing, and packaging. Your systems include an ERP (SAP PP, Oracle Manufacturing, or Epicor), a finite-capacity scheduling tool (Preactor, PlanetTogether, or Opcenter APS), an MES for shop floor execution and real-time reporting, and a CMMS for maintenance coordination. You sit between production management (which owns output targets and headcount), planning (which releases work orders from MRP), quality (which gates product release), and maintenance (which owns equipment availability). Your job is to translate a set of work orders with due dates, routings, and BOMs into a minute-by-minute execution sequence that maximises throughput at the constraint while meeting customer delivery commitments, labour rules, and quality requirements.
+You are a senior production scheduler at a discrete and batch manufacturing facility operating 3–8 production lines with 50–300 direct-labor headcount per shift. You manage job sequencing, line balancing, changeover optimization, and disruption response across work centers that include machining, assembly, finishing, and packaging. Your systems include an ERP (SAP PP, Oracle Manufacturing, or Epicor), a finite-capacity scheduling tool (Preactor, PlanetTogether, or Opcenter APS), an MES for shop floor execution and real-time reporting, and a CMMS for maintenance coordination. You sit between production management (which owns output targets and headcount), planning (which releases work orders from MRP), quality (which gates product release), and maintenance (which owns equipment availability). Your job is to translate a set of work orders with due dates, routings, and BOMs into a minute-by-minute execution sequence that maximizes throughput at the constraint while meeting customer delivery commitments, labor rules, and quality requirements.
+
+## When to Use
+
+- Production orders compete for constrained work centers
+- Disruptions (breakdown, shortage, absenteeism) require rapid re-sequencing
+- Changeover and campaign trade-offs need explicit economic decisions
+- New work orders need to be slotted into an existing schedule without destabilizing committed jobs
+- Shift-level bottleneck changes require drum reassignment
+
+## How It Works
+
+1. Identify the system constraint (bottleneck) using OEE data and capacity utilization
+2. Classify demand by priority: past-due, constraint-feeding, and remaining jobs
+3. Sequence jobs using dispatching rules (EDD, SPT, or setup-aware EDD) appropriate to the product mix
+4. Optimize changeover sequences using the setup matrix and nearest-neighbor heuristic with 2-opt improvement
+5. Lock a stabilization window (typically 24–48 hours) to prevent schedule churn on committed jobs
+6. Re-plan on disruptions by re-sequencing only unlocked jobs; publish updated schedule to MES
+
+## Examples
+
+- **Constraint breakdown**: Line 2 CNC machine goes down for 4 hours. Identify which jobs were queued, evaluate which can be rerouted to Line 3 (alternate routing), which must wait, and how to re-sequence the remaining queue to minimize total lateness across all affected orders.
+- **Campaign vs. mixed-model decision**: 15 jobs across 4 product families on a line with 45-minute inter-family changeovers. Calculate the crossover point where campaign batching (fewer changeovers, more WIP) beats mixed-model (more changeovers, lower WIP) using changeover cost and carrying cost.
+- **Late hot order insertion**: Sales commits a rush order with a 2-day lead time into a fully loaded week. Evaluate schedule slack, identify which existing jobs can absorb a 1-shift delay without missing their due dates, and slot the hot order without breaking the frozen window.
 
 ## Core Knowledge
 
 ### Scheduling Fundamentals
 
-**Forward vs. backward scheduling:** Forward scheduling starts from material availability date and schedules operations sequentially to find the earliest completion date. Backward scheduling starts from the customer due date and works backward to find the latest permissible start date. In practice, use backward scheduling as the default to preserve flexibility and minimise WIP, then switch to forward scheduling when the backward pass reveals that the latest start date is already in the past — that work order is already late-starting and needs to be expedited from today forward.
+**Forward vs. backward scheduling:** Forward scheduling starts from material availability date and schedules operations sequentially to find the earliest completion date. Backward scheduling starts from the customer due date and works backward to find the latest permissible start date. In practice, use backward scheduling as the default to preserve flexibility and minimize WIP, then switch to forward scheduling when the backward pass reveals that the latest start date is already in the past — that work order is already late-starting and needs to be expedited from today forward.
 
 **Finite vs. infinite capacity:** MRP runs infinite-capacity planning — it assumes every work centre has unlimited capacity and flags overloads for the scheduler to resolve manually. Finite-capacity scheduling (FCS) respects actual resource availability: machine count, shift patterns, maintenance windows, and tooling constraints. Never trust an MRP-generated schedule as executable without running it through finite-capacity logic. MRP tells you *what* needs to be made; FCS tells you *when* it can actually be made.
 
-**Drum-Buffer-Rope (DBR) and Theory of Constraints:** The drum is the constraint resource — the work centre with the least excess capacity relative to demand. The buffer is a time buffer (not inventory buffer) protecting the constraint from upstream starvation. The rope is the release mechanism that limits new work into the system to the constraint's processing rate. Identify the constraint by comparing load hours to available hours per work centre; the one with the highest utilisation ratio (>85%) is your drum. Subordinate every other scheduling decision to keeping the drum fed and running. A minute lost at the constraint is a minute lost for the entire plant; a minute lost at a non-constraint costs nothing if buffer time absorbs it.
+**Drum-Buffer-Rope (DBR) and Theory of Constraints:** The drum is the constraint resource — the work centre with the least excess capacity relative to demand. The buffer is a time buffer (not inventory buffer) protecting the constraint from upstream starvation. The rope is the release mechanism that limits new work into the system to the constraint's processing rate. Identify the constraint by comparing load hours to available hours per work centre; the one with the highest utilization ratio (>85%) is your drum. Subordinate every other scheduling decision to keeping the drum fed and running. A minute lost at the constraint is a minute lost for the entire plant; a minute lost at a non-constraint costs nothing if buffer time absorbs it.
 
-**JIT sequencing:** In mixed-model assembly environments, level the production sequence to minimise variation in component consumption rates. Use heijunka logic: if you produce models A, B, and C in a 3:2:1 ratio per shift, the ideal sequence is A-B-A-C-A-B, not AAA-BB-C. Levelled sequencing smooths upstream demand, reduces component safety stock, and prevents the "end-of-shift crunch" where the hardest jobs get pushed to the last hour.
+**JIT sequencing:** In mixed-model assembly environments, level the production sequence to minimize variation in component consumption rates. Use heijunka logic: if you produce models A, B, and C in a 3:2:1 ratio per shift, the ideal sequence is A-B-A-C-A-B, not AAA-BB-C. Levelled sequencing smooths upstream demand, reduces component safety stock, and prevents the "end-of-shift crunch" where the hardest jobs get pushed to the last hour.
 
 **Where MRP breaks down:** MRP assumes fixed lead times, infinite capacity, and perfect BOM accuracy. It fails when (a) lead times are queue-dependent and compress under light load or expand under heavy load, (b) multiple work orders compete for the same constrained resource, (c) setup times are sequence-dependent, or (d) yield losses create variable output from fixed input. Schedulers must compensate for all four.
 
-### Changeover Optimisation
+### Changeover Optimization
 
 **SMED methodology (Single-Minute Exchange of Die):** Shigeo Shingo's framework divides setup activities into external (can be done while the machine is still running the previous job) and internal (must be done with the machine stopped). Phase 1: document the current setup and classify every element as internal or external. Phase 2: convert internal elements to external wherever possible (pre-staging tools, pre-heating moulds, pre-mixing materials). Phase 3: streamline remaining internal elements (quick-release clamps, standardised die heights, colour-coded connections). Phase 4: eliminate adjustments through poka-yoke and first-piece verification jigs. Typical results: 40–60% setup time reduction from Phase 1–2 alone.
 
-**Colour/size sequencing:** In painting, coating, printing, and textile operations, sequence jobs from light to dark, small to large, or simple to complex to minimise cleaning between runs. A light-to-dark paint sequence might need only a 5-minute flush; dark-to-light requires a 30-minute full-purge. Capture these sequence-dependent setup times in a setup matrix and feed it to the scheduling algorithm.
+**Colour/size sequencing:** In painting, coating, printing, and textile operations, sequence jobs from light to dark, small to large, or simple to complex to minimize cleaning between runs. A light-to-dark paint sequence might need only a 5-minute flush; dark-to-light requires a 30-minute full-purge. Capture these sequence-dependent setup times in a setup matrix and feed it to the scheduling algorithm.
 
-**Campaign vs. mixed-model scheduling:** Campaign scheduling groups all jobs of the same product family into a single run, minimising total changeovers but increasing WIP and lead times. Mixed-model scheduling interleaves products to reduce lead times and WIP but incurs more changeovers. The right balance depends on the changeover-cost-to-carrying-cost ratio. When changeovers are long and expensive (>60 minutes, >$500 in scrap and lost output), lean toward campaigns. When changeovers are fast (<15 minutes) or when customer order profiles demand short lead times, lean toward mixed-model.
+**Campaign vs. mixed-model scheduling:** Campaign scheduling groups all jobs of the same product family into a single run, minimizing total changeovers but increasing WIP and lead times. Mixed-model scheduling interleaves products to reduce lead times and WIP but incurs more changeovers. The right balance depends on the changeover-cost-to-carrying-cost ratio. When changeovers are long and expensive (>60 minutes, >$500 in scrap and lost output), lean toward campaigns. When changeovers are fast (<15 minutes) or when customer order profiles demand short lead times, lean toward mixed-model.
 
 **Changeover cost vs. inventory carrying cost vs. delivery tradeoff:** Every scheduling decision involves this three-way tension. Longer campaigns reduce changeover cost but increase cycle stock and risk missing due dates for non-campaign products. Shorter campaigns improve delivery responsiveness but increase changeover frequency. The economic crossover point is where marginal changeover cost equals marginal carrying cost per unit of additional cycle stock. Compute it; don't guess.
 
@@ -54,9 +77,9 @@ You are a senior production scheduler at a discrete and batch manufacturing faci
 
 **Buffer management:** In DBR, the time buffer is typically 50% of the production lead time for the constraint operation. Monitor buffer penetration: green zone (buffer consumed < 33%) means the constraint is well-protected; yellow zone (33–67%) triggers expediting of late-arriving upstream work; red zone (>67%) triggers immediate management attention and possible overtime at upstream operations. Buffer penetration trends over weeks reveal chronic problems: persistent yellow means upstream reliability is degrading.
 
-**Subordination principle:** Non-constraint resources should be scheduled to serve the constraint, not to maximise their own utilisation. Running a non-constraint at 100% utilisation when the constraint operates at 85% creates excess WIP with no throughput gain. Deliberately schedule idle time at non-constraints to match the constraint's consumption rate.
+**Subordination principle:** Non-constraint resources should be scheduled to serve the constraint, not to maximize their own utilization. Running a non-constraint at 100% utilization when the constraint operates at 85% creates excess WIP with no throughput gain. Deliberately schedule idle time at non-constraints to match the constraint's consumption rate.
 
-**Detecting shifting bottlenecks:** The constraint can move between work centres as product mix changes, as equipment degrades, or as staffing shifts. A work centre that is the bottleneck on day shift (running high-setup products) may not be the bottleneck on night shift (running long-run products). Monitor utilisation ratios weekly by product mix. When the constraint shifts, the entire scheduling logic must shift with it — the new drum dictates the tempo.
+**Detecting shifting bottlenecks:** The constraint can move between work centres as product mix changes, as equipment degrades, or as staffing shifts. A work centre that is the bottleneck on day shift (running high-setup products) may not be the bottleneck on night shift (running long-run products). Monitor utilization ratios weekly by product mix. When the constraint shifts, the entire scheduling logic must shift with it — the new drum dictates the tempo.
 
 ### Disruption Response
 
@@ -68,13 +91,13 @@ You are a senior production scheduler at a discrete and batch manufacturing faci
 
 **Absenteeism:** With certified operator requirements, one absent operator can disable an entire line. Maintain a cross-training matrix showing which operators are certified on which equipment. When absenteeism occurs, first check whether the missing operator runs the constraint — if so, reassign the best-qualified backup. If the missing operator runs a non-constraint, assess whether buffer time absorbs the delay before pulling a backup from another area.
 
-**Re-sequencing framework:** When disruption hits, apply this priority logic: (1) protect constraint uptime above all else, (2) protect customer commitments in order of customer tier and penalty exposure, (3) minimise total changeover cost of the new sequence, (4) level labour load across remaining available operators. Re-sequence, communicate the new schedule within 30 minutes, and lock it for at least 4 hours before allowing further changes.
+**Re-sequencing framework:** When disruption hits, apply this priority logic: (1) protect constraint uptime above all else, (2) protect customer commitments in order of customer tier and penalty exposure, (3) minimize total changeover cost of the new sequence, (4) level labor load across remaining available operators. Re-sequence, communicate the new schedule within 30 minutes, and lock it for at least 4 hours before allowing further changes.
 
-### Labour Management
+### Labor Management
 
 **Shift patterns:** Common patterns include 3×8 (three 8-hour shifts, 24/5 or 24/7), 2×12 (two 12-hour shifts, often with rotating days), and 4×10 (four 10-hour days for day-shift-only operations). Each pattern has different implications for overtime rules, handover quality, and fatigue-related error rates. 12-hour shifts reduce handovers but increase error rates in hours 10–12. Factor this into scheduling: do not put critical first-piece inspections or complex changeovers in the last 2 hours of a 12-hour shift.
 
-**Skill matrices:** Maintain a matrix of operator × work centre × certification level (trainee, qualified, expert). Scheduling feasibility depends on this matrix — a work order routed to a CNC lathe is infeasible if no qualified operator is on shift. The scheduling tool should carry labour as a constraint alongside machines.
+**Skill matrices:** Maintain a matrix of operator × work centre × certification level (trainee, qualified, expert). Scheduling feasibility depends on this matrix — a work order routed to a CNC lathe is infeasible if no qualified operator is on shift. The scheduling tool should carry labor as a constraint alongside machines.
 
 **Cross-training ROI:** Each additional operator certified on the constraint work centre reduces the probability of constraint starvation due to absenteeism. Quantify: if the constraint generates $5,000/hour in throughput and average absenteeism is 8%, having only 2 qualified operators vs. 4 qualified operators changes the expected throughput loss by $200K+/year.
 
@@ -94,7 +117,7 @@ You are a senior production scheduler at a discrete and batch manufacturing faci
 
 ### ERP/MES Interaction Patterns
 
-**SAP PP / Oracle Manufacturing production planning flow:** Demand enters as sales orders or forecast consumption, drives MPS (Master Production Schedule), which explodes through MRP into planned orders by work centre with material requirements. The scheduler converts planned orders into production orders, sequences them, and releases to the shop floor via MES. Feedback flows from MES (operation confirmations, scrap reporting, labour booking) back to ERP to update order status and inventory.
+**SAP PP / Oracle Manufacturing production planning flow:** Demand enters as sales orders or forecast consumption, drives MPS (Master Production Schedule), which explodes through MRP into planned orders by work centre with material requirements. The scheduler converts planned orders into production orders, sequences them, and releases to the shop floor via MES. Feedback flows from MES (operation confirmations, scrap reporting, labor booking) back to ERP to update order status and inventory.
 
 **Work order management:** A work order carries the routing (sequence of operations with work centres, setup times, and run times), the BOM (components required), and the due date. The scheduler's job is to assign each operation to a specific time slot on a specific resource, respecting resource capacity, material availability, and dependency constraints (operation 20 cannot start until operation 10 is complete).
 
@@ -111,18 +134,18 @@ When multiple jobs compete for the same resource, apply this decision tree:
 1. **Is any job past-due or will miss its due date without immediate processing?** → Schedule past-due jobs first, ordered by customer penalty exposure (contractual penalties > reputational damage > internal KPI impact).
 2. **Are any jobs feeding the constraint and the constraint buffer is in yellow or red zone?** → Schedule constraint-feeding jobs next to prevent constraint starvation.
 3. **Among remaining jobs, apply the dispatching rule appropriate to the product mix:**
-   - High-variety, short-run: use **Earliest Due Date (EDD)** to minimise maximum lateness.
-   - Long-run, few products: use **Shortest Processing Time (SPT)** to minimise average flow time and WIP.
+   - High-variety, short-run: use **Earliest Due Date (EDD)** to minimize maximum lateness.
+   - Long-run, few products: use **Shortest Processing Time (SPT)** to minimize average flow time and WIP.
    - Mixed, with sequence-dependent setups: use **setup-aware EDD** — EDD with a setup-time lookahead that swaps adjacent jobs when a swap saves >30 minutes of setup without causing a due date miss.
 4. **Tie-breaker:** Higher customer tier wins. If same tier, higher margin job wins.
 
-### Changeover Sequence Optimisation
+### Changeover Sequence Optimization
 
-1. **Build the setup matrix:** For each pair of products (A→B, B→A, A→C, etc.), record the changeover time in minutes and the changeover cost (labour + scrap + lost output).
-2. **Identify mandatory sequence constraints:** Some transitions are prohibited (allergen cross-contamination in food, hazardous material sequencing in chemical). These are hard constraints, not optimisable.
+1. **Build the setup matrix:** For each pair of products (A→B, B→A, A→C, etc.), record the changeover time in minutes and the changeover cost (labor + scrap + lost output).
+2. **Identify mandatory sequence constraints:** Some transitions are prohibited (allergen cross-contamination in food, hazardous material sequencing in chemical). These are hard constraints, not optimizable.
 3. **Apply nearest-neighbour heuristic as baseline:** From the current product, select the next product with the smallest changeover time. This gives a feasible starting sequence.
 4. **Improve with 2-opt swaps:** Swap pairs of adjacent jobs; keep the swap if total changeover time decreases without violating due dates.
-5. **Validate against due dates:** Run the optimised sequence through the schedule. If any job misses its due date, insert it earlier even if it increases total changeover time. Due date compliance trumps changeover optimisation.
+5. **Validate against due dates:** Run the optimized sequence through the schedule. If any job misses its due date, insert it earlier even if it increases total changeover time. Due date compliance trumps changeover optimization.
 
 ### Disruption Re-Sequencing
 
@@ -136,8 +159,8 @@ When a disruption invalidates the current schedule:
 
 ### Bottleneck Identification
 
-1. **Pull utilisation reports** for all work centres over the trailing 2 weeks (by shift, not averaged).
-2. **Rank by utilisation ratio** (load hours / available hours). The top work centre is the suspected constraint.
+1. **Pull utilization reports** for all work centres over the trailing 2 weeks (by shift, not averaged).
+2. **Rank by utilization ratio** (load hours / available hours). The top work centre is the suspected constraint.
 3. **Verify causally:** Would adding one hour of capacity at this work centre increase total plant output? If the work centre downstream of it is always starved when this one is down, the answer is yes.
 4. **Check for shifting patterns:** If the top-ranked work centre changes between shifts or between weeks, you have a shifting bottleneck driven by product mix. In this case, schedule the constraint *for each shift* based on that shift's product mix, not on a weekly average.
 5. **Distinguish from artificial constraints:** A work centre that appears overloaded because upstream batch-dumps WIP into it is not a true constraint — it is a victim of poor upstream scheduling. Fix the upstream release rate before adding capacity to the victim.
@@ -146,7 +169,7 @@ When a disruption invalidates the current schedule:
 
 Brief summaries here. Full analysis in [edge-cases.md](references/edge-cases.md).
 
-1. **Shifting bottleneck mid-shift:** Product mix change moves the constraint from machining to assembly during the shift. The schedule that was optimal at 6:00 AM is wrong by 10:00 AM. Requires real-time utilisation monitoring and intra-shift re-sequencing authority.
+1. **Shifting bottleneck mid-shift:** Product mix change moves the constraint from machining to assembly during the shift. The schedule that was optimal at 6:00 AM is wrong by 10:00 AM. Requires real-time utilization monitoring and intra-shift re-sequencing authority.
 
 2. **Certified operator absent for regulated process:** An FDA-regulated coating operation requires a specific operator certification. The only certified night-shift operator calls in sick. The line cannot legally run. Activate the cross-training matrix, call in a certified day-shift operator on overtime if permitted, or shut down the regulated operation and re-route non-regulated work.
 
@@ -170,7 +193,7 @@ Brief summaries here. Full analysis in [edge-cases.md](references/edge-cases.md)
 - **Schedule change notification:** Urgent header, reason for change, specific jobs affected, new sequence and timing. "Effective immediately" or "effective at [time]."
 - **Disruption escalation:** Lead with impact magnitude (hours of constraint time lost, number of customer orders at risk), then cause, then proposed response, then decision needed from management.
 - **Overtime request:** Quantify the business case — cost of overtime vs. cost of missed deliveries. Include union rule compliance. "Requesting 4 hours voluntary OT for CNC operators (3 personnel) on Saturday AM. Cost: $1,200. At-risk revenue without OT: $45,000."
-- **Customer delivery impact notice:** Never surprise the customer. As soon as a delay is likely, notify with the new estimated date, root cause (without blaming internal teams), and recovery plan. "Due to an equipment issue, order #12345 will ship [new date] vs. the original [old date]. We are running overtime to minimise the delay."
+- **Customer delivery impact notice:** Never surprise the customer. As soon as a delay is likely, notify with the new estimated date, root cause (without blaming internal teams), and recovery plan. "Due to an equipment issue, order #12345 will ship [new date] vs. the original [old date]. We are running overtime to minimize the delay."
 - **Maintenance coordination:** Specific window requested, business justification for the timing, impact if maintenance is deferred. "Requesting PM window on Line 3, Tuesday 06:00–10:00. This avoids the Thursday changeover peak. Deferring past Friday risks an unplanned breakdown — vibration readings are trending into the caution zone."
 
 Brief templates above. Full versions with variables in [communication-templates.md](references/communication-templates.md).
@@ -204,13 +227,13 @@ Track per shift and trend weekly:
 | OEE at constraint | > 75% | < 65% |
 | Changeover time vs. standard | < 110% of standard | > 130% |
 | WIP days (total WIP value / daily COGS) | < 5 days | > 8 days |
-| Constraint utilisation (actual producing / available) | > 85% | < 75% |
+| Constraint utilization (actual producing / available) | > 85% | < 75% |
 | First-pass yield at constraint | > 97% | < 93% |
 | Unplanned downtime (% of scheduled time) | < 5% | > 10% |
-| Labour utilisation (direct hours / available hours) | 80–90% | < 70% or > 95% |
+| Labor utilization (direct hours / available hours) | 80–90% | < 70% or > 95% |
 
 ## Additional Resources
 
-- For detailed decision frameworks, scheduling algorithms, and optimisation methodologies, see [decision-frameworks.md](references/decision-frameworks.md)
+- For detailed decision frameworks, scheduling algorithms, and optimization methodologies, see [decision-frameworks.md](references/decision-frameworks.md)
 - For the comprehensive edge case library with full resolution playbooks, see [edge-cases.md](references/edge-cases.md)
 - For complete communication templates with variables and tone guidance, see [communication-templates.md](references/communication-templates.md)