Production Planning and Scheduling Software

Convert customer orders, forecasts, and replenishment triggers into a prioritised production queue. The system applies S&OP (Sales and Operations Planning) logic to reconcile the demand plan with production capacity before committing to the schedule. Demand signals from your ERP -- whether from SAP SD, Oracle NetSuite sales orders, or a direct order management system -- are consumed in real time rather than in overnight batch runs. DDMRP (Demand Driven Material Requirements Planning) buffer sizing can be layered in to maintain strategic inventory buffers at decoupling points, reducing the bullwhip effect in mixed-mode environments.

The system checks due dates, customer priority, and current WIP position before generating the schedule. Planners see a ranked order list with demand dates and the calculated start date needed to meet them. Late orders are flagged before they become late. When new orders arrive mid-shift, the schedule is immediately recalculated using the current capacity snapshot, not the capacity snapshot from this morning's planning run. Priority tiers -- expedited, standard, and forecast replenishment -- are user-configurable so the scheduling logic matches the way your commercial team classifies demand, not a generic priority model.

Model your work centres, machines, and labour pools with their available hours, efficiency factors, and maintenance windows. Constraint-based scheduling applies finite capacity rules so no machine is overloaded. Bottleneck resources are identified using Theory of Constraints (TOC) methodology -- the system flags the capacity-limiting work centre in the current schedule and protects its throughput by keeping feeding operations from starving it and downstream operations from blocking it.

When orders are loaded against the schedule, the system checks available capacity and flags overloads before they are committed. Planners see machine loading by day or week in a Gantt-style resource view and can shift orders to balance the load. Changeover minimisation uses SMED (Single Minute Exchange of Die) methodology -- jobs are sequenced on shared machines to minimise total setup time based on the product family transition matrix. Labour constraints are checked alongside machine constraints so the schedule is feasible against both simultaneously, not in separate planning runs that produce conflicting output.

Run MRP II logic on demand rather than overnight. The system performs a full BOM explosion from the master production schedule, netting each component against on-hand inventory, open purchase orders, and scheduled receipts before generating requirements. Demand forecasting uses exponential smoothing to project forward consumption for make-to-stock items, with the smoothing coefficient configurable per item class. Lead time netting accounts for purchasing lead times, supplier lead times, and safety stock buffers defined in the item master.

Integration with SAP PP/APO or Oracle Demantra passes planned orders and purchase requisitions back to your ERP so procurement acts on system-generated recommendations rather than planner emails. Material shortages are linked to the specific production orders they affect so planners know exactly which orders are at risk and by how many days. When a purchase order receipt is confirmed in the ERP, the related material shortage is cleared and the production schedule adjusts automatically rather than waiting for the next overnight batch run.

Schedule production orders to specific machines with finite capacity constraints applied at every work centre simultaneously. The scheduler respects machine availability, setup times between product families, minimum run quantities, and tooling constraints that tie specific jobs to specific machines. Sequence-dependent setups are modelled using a machine-level setup matrix, so the scheduler picks the job order that minimises total setup hours across the week rather than sequencing blindly by due date.

No order is scheduled to a machine that doesn't have the capacity to run it in the required window -- overloads are flagged at scheduling time rather than discovered when the shift starts. Machine loading views show each machine's schedule by shift, broken down by order, run time, and setup time. Supervisors see what is planned without needing to ask the planning team. When a machine goes down unplanned, the affected orders are immediately surfaced with an impact assessment showing which customer due dates are at risk and by how many hours.

Interactive Gantt charts let planners drag and drop orders across machines and time, with the system validating capacity and material constraints as each move is made. If a drag operation would overload a machine or create a material shortage, the system flags the conflict before the move is committed rather than silently allowing it. Colour coding shows order status (released, in progress, complete), priority tier, and material availability at a glance, so the planner sees problem orders immediately without running a separate exception report.

Orders can be split across machines, merged into longer runs for efficiency, or locked to prevent the automatic scheduler from moving them. The lock function is useful for orders that are already kitted and in the queue -- the planner wants the optimizer to work around them rather than re-sequence them. Supervisors and production managers see a read-only Gantt view of the current schedule so they know what is planned for the shift without relying on a printed schedule from three hours ago. Schedule export to PDF is available for shift handover briefings on the floor.

Model capacity changes before committing to them. Add a machine, change shift patterns, bring in a subcontractor, adjust the product mix, or simulate the impact of a key material shortage, and see the effect on your schedule and customer delivery dates without touching the live plan. Scenarios are saved as named copies of the current schedule and can be compared side by side against the baseline or against each other, with an on-time delivery rate and average lead time shown per scenario to quantify the trade-offs.

The S&OP what-if layer lets supply chain planners model the next 8-to-13-week horizon, testing demand uplift assumptions against the finite capacity model before the monthly S&OP meeting. When a decision is made -- a new shift pattern approved, a subcontract arrangement confirmed -- the chosen scenario is promoted to the live schedule with a single action. All scenario history is retained for reference so the reasoning behind past capacity decisions is auditable. Capacity decisions are made on data from the scheduling model rather than on the planning team's best guess.