Production Planning and Scheduling
Production planning answers the question: how do we allocate capacity to meet demand on time, at cost, without running out of materials or overwhelming the shop floor? The tools range from straightforward MRP-driven scheduling to finite capacity optimisation and constraint-based sequencing. For small manufacturers, the gap between "we plan using spreadsheets and gut feel" and "we have a workable schedule" is usually about data quality and discipline — not software sophistication.
This guide covers planning and scheduling methods, capacity calculation, inventory formulas, and how to evaluate scheduling software. Articles are linked below as they publish.
The three levels of production planning
Production planning operates at three time horizons, each with a different tool and purpose:
| Level | Horizon | Unit | Purpose | Tool |
|---|---|---|---|---|
| Sales and Operations Planning (S&OP) | 3–18 months | Product families | Align supply and demand at the business level; set inventory and capacity targets | Spreadsheet or ERP S&OP module |
| Master Production Schedule (MPS) | 4–12 weeks | Finished products | Commit to specific quantities in specific weeks; drive MRP | ERP MPS module |
| Detailed scheduling / dispatch | Days to 2 weeks | Individual work orders / operations | Sequence jobs at each work centre; manage priorities; respond to changes | ERP shop floor module, APS software, or manual |
Many small manufacturers skip S&OP entirely and struggle to maintain a reliable MPS — they plan primarily by reacting to orders. This works until lead times become a competitive issue or materials shortages begin causing late deliveries.
How to calculate production capacity
Capacity is the maximum output a work centre or factory can produce in a given period. The calculation at the work centre level:
Theoretical capacity = (shifts per day) × (hours per shift) × (days per period)
Effective (demonstrated) capacity = theoretical capacity × utilisation × efficiency
Where:
- Utilisation = actual time the machine is producing ÷ time available (accounts for planned maintenance, breaks, changeovers). A realistic figure for a well-run discrete manufacturing cell is 75–85%.
- Efficiency = actual output ÷ standard output (are jobs running at standard time?). Well-run operations: 90–100%.
Worked example: A machining cell runs 2 shifts × 8 hours × 20 working days/month = 320 theoretical hours/month. Utilisation is 80% (256 hours available for production after changeovers and maintenance). Efficiency is 95% (jobs average 5% over standard time). Effective capacity = 256 × 0.95 = 243 hours/month. If your MPS requires 280 hours, you have a capacity gap.
Finite vs infinite capacity scheduling
This is the most common source of confusion in production planning software:
Infinite capacity scheduling
- Assumes unlimited capacity at every work centre
- Schedules all jobs based on lead time offsets, ignoring overloads
- Standard MRP scheduling method
- Fast to compute; works well when capacity is rarely constrained
- Produces infeasible schedules when capacity is tight
- Requires manual planner intervention to resolve overloads
Finite capacity scheduling
- Respects actual capacity limits at each work centre
- Queues and sequences jobs based on available capacity
- Produces a feasible schedule (one that can actually be executed)
- Requires accurate work centre capacity and routing data to work
- Software-intensive; Advanced Planning and Scheduling (APS) tools
- Worth the investment when the bottleneck is well-defined and overloads are frequent
Most small manufacturers run infinite-capacity MRP and resolve overloads manually with a capacity requirements planning (CRP) report. Finite scheduling is valuable when you have a clear bottleneck, frequent schedule failures, and the data quality to support it. Do not invest in APS software until your routing and work centre data is reliable — the schedule is only as good as the inputs.
Job shop scheduling methods
A job shop produces a wide variety of custom or low-volume products, each with a different routing through the shop. Scheduling is harder here than in repetitive manufacturing because every job competes for different work centres in different sequences.
Common sequencing rules used in job shops:
- FIFO (First In, First Out) — process jobs in the order they arrived. Simple; does not optimise for due dates or capacity.
- EDD (Earliest Due Date) — sequence jobs by due date, earliest first. Minimises late jobs but can cause a few jobs to be very early while others are late.
- Critical Ratio (CR) — CR = (time remaining until due date) ÷ (remaining work time). Jobs with CR < 1 are behind schedule; prioritise lowest CR. A practical real-world rule.
- Shortest Processing Time (SPT) — run the shortest job first. Minimises average flow time and WIP, but long jobs can get starved.
- Johnson's Rule — optimal sequence for two-machine flow-shop problems. Limited applicability but exact where it applies.
In practice, most job shops use a hybrid: a dispatch list sorted by Critical Ratio or due date, with supervisor override for strategic customers or hot jobs. This is what most ERP shop-floor dispatch reports produce.
Safety stock and reorder point formulas
Safety stock protects against demand variability and supply lead time variability. The basic formula:
Safety stock = Z × σLT × √LT
Where:
- Z = service level factor (1.28 for 90% service level; 1.645 for 95%; 1.96 for 97.5%)
- σLT = standard deviation of demand during the lead time period
- LT = average lead time in the same units as demand
Reorder point = (average daily demand × lead time in days) + safety stock
Worked example: A component has average daily demand of 50 units, standard deviation of 12 units/day, and a supplier lead time of 10 days. Target service level 95% (Z = 1.645).
- Safety stock = 1.645 × 12 × √10 = 1.645 × 12 × 3.162 = 62.4 units → round to 63
- Reorder point = (50 × 10) + 63 = 500 + 63 = 563 units
When on-hand inventory drops to 563 units, place a replenishment order. The safety stock of 63 units buffers against demand spikes or late supplier delivery.
Production scheduling software options
For most small manufacturers, the first scheduling tool is the MPS/MRP module in their ERP. Moving to dedicated Advanced Planning and Scheduling (APS) software makes sense when:
- ERP infinite scheduling produces overloaded work centres regularly, and planners spend significant time manually re-sequencing.
- You have a well-defined bottleneck and need constraint-based scheduling (Theory of Constraints/Drum-Buffer-Rope).
- You need "what-if" scenario modelling for quoting lead times or evaluating new orders.
- Your routings, work centre data and standard times are accurate and maintained.
Do not buy APS software if your standard times are unreliable or your routings are incomplete — the schedule will be wrong and trust in the system will collapse quickly.
Articles in this section
In-depth articles on finite vs infinite scheduling, job shop methods, capacity calculations, safety stock formulas, and scheduling software publish here as they are researched and written.
Articles publishing soon — covering finite vs infinite capacity scheduling, how to calculate production capacity, safety stock formula examples, and job-shop scheduling methods.