Does the system integrate with SAP PP (Production Planning) module?

Yes. We build bi-directional integration with SAP PP, pulling planned orders and material requirements and pushing the optimised production sequence back to SAP. We also integrate with Syspro, Sage X3, and most South African ERP systems used in manufacturing.

How does the system handle rush orders from our OEM customers?

Rush orders are entered into the system with a priority flag and due date. The AI immediately calculates the impact on all existing scheduled orders and presents the scheduler with the optimal insertion point - showing which existing orders will be affected and by how much. The planner approves the recommendation in one click.

Can the system manage scheduling across multiple production lines and shifts?

Yes. The system supports unlimited production lines, work centres, and shift patterns. It optimises across all lines simultaneously and handles cross-line dependencies where a part must be processed on multiple lines in sequence. Multi-shift scheduling with different capacity profiles per shift is fully supported.

What happens if we don't have accurate machine capacity data to start with?

We begin with your best available capacity estimates and refine the model using actual production data collected during the first 30 days. The AI learns actual cycle times and setup durations from the production data, progressively improving the accuracy of capacity constraints without requiring an extensive upfront data collection project.

Integrates With SAP, Sage & SysproLoad Shedding Schedule Built-InLive in 21 Days

AI Production Scheduling That Adapts to Load Shedding and Demand Shifts in Real Time

Manual production scheduling in South Africa means constant replanning around load shedding stages, last-minute customer orders, and machine breakdowns. Our AI scheduling engine optimises your production plan automatically - maximising throughput, meeting delivery dates, and minimising overtime costs without human replanning effort.

"Our production planner was working 12-hour days just to keep up with replanning around load shedding…"

Petrus van Niekerk, Operations Director

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AI Production Scheduling That Adapts to Load Shedding and Demand Shifts in Real Time

Manual Production Scheduling Cannot Keep Up With South Africa's Manufacturing Reality

South African production planners are among the most challenged in the world. They must simultaneously manage unpredictable load shedding windows, volatile raw material availability, OEM just-in-time delivery requirements, and a workforce whose effective hours shrink every time Eskom announces Stage 4 or above. Spreadsheet-based scheduling simply cannot optimise across all these variables simultaneously.

Load shedding at Stage 4-6 eliminates 4-8 productive hours per day, forcing planners to resequence the entire production plan manually - typically taking 2-3 hours each time
Customer demand variability from APDP-protected automotive OEMs means production plans change weekly, creating constant WIP inventory imbalances and material shortages
Machine capacity is rarely modelled accurately, leading to bottleneck workcentres that throttle throughput while other machines sit idle
Overtime decisions are made reactively and intuitively rather than based on optimised cost-versus-delivery-penalty calculations
Sequence-dependent setup times between product changeovers are ignored in manual scheduling, costing 15-25% of available productive time

Illustrative example, not a client result.

Every Hour of Suboptimal Scheduling Is an Hour of Margin You Cannot Recover

South African manufacturers operating under MIDP and APDP frameworks face thin margins and demanding OEM customer schedules. A production plan that is even 10% less efficient than optimal translates directly to higher overtime costs, missed JIT deliveries, and excess WIP inventory tying up working capital. AI scheduling optimisation typically recovers 15-22% of lost productive capacity.

15-22%

productive capacity recovered by manufacturers switching from manual to AI-optimised production scheduling

2-3hrs

wasted by SA production planners every time a load shedding event forces a manual plan resequence

R1.1M

average annual overtime cost reduction achieved by mid-size SA manufacturers after AI scheduling implementation

Illustrative example, not a client result.

Your AI-Powered Production Scheduling Engine

We build an advanced planning and scheduling (APS) system tailored for South African manufacturing conditions - integrating your ERP customer orders, machine capacity, material availability, and the Eskom load shedding schedule to produce an optimised, continuously updated production plan.

Load Shedding-Aware Scheduling

The AI integrates the Eskom load shedding schedule and automatically reschedules power-intensive operations to available windows. When the schedule changes, the production plan updates in minutes - not the 2-3 hours your planners currently spend replanning manually.

Constraint-Based Optimisation

AI simultaneously optimises across machine capacity, tooling availability, operator skills, material stock, and customer due dates - finding the sequence that maximises on-time delivery rate while minimising setup time, overtime, and WIP inventory.

What-If Scenario Planning

Planners can model the impact of a new urgent order, a machine breakdown, or a material shortage in seconds. The AI generates alternative schedule scenarios with the cost and delivery impact of each option - enabling faster, better-informed decisions.

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"Our production planner was working 12-hour days just to keep up with replanning around load shedding and customer changes. The AI scheduling system now handles 90% of the replanning automatically. Our on-time delivery rate went from 71% to 96% and our overtime bill dropped by R840,000 in the first year."

Petrus van Niekerk

Operations Director, Van Niekerk Precision Engineering, Gauteng

96%

Average on-time delivery rate achieved by clients post-implementation - up from 71%

18%

Average increase in overall equipment effectiveness (OEE) within 6 months

21 days

From kickoff to live AI scheduling engine integrated with your ERP

Illustrative example, not a client result.

Optimise Production Scheduling for Manufacturing

South African Market Perspective

Production scheduling in South African manufacturing must balance customer demand, raw material availability, machine maintenance windows, and the increasingly unpredictable load shedding schedule published by Eskom. AI scheduling systems can integrate all these variables to create optimised production plans that maximise output during available power windows, schedule energy-intensive processes during off-peak tariff periods, and automatically reschedule when load shedding stages change: reducing the production losses that currently cost manufacturers an average of 8-12% of potential output.

Illustrative example, not a client result.

How It Works

Scheduling Audit & Capacity Modelling (Day 1-5)

We audit your current scheduling process, ERP data quality, machine capacity model, and shift patterns. We analyse 12 months of production data to identify bottlenecks, sequence-dependent setup time patterns, and load shedding impact on throughput - building the constraint model for the AI engine.

APS System Build & ERP Integration (Day 6-16)

We build the AI scheduling engine and integrate it with your ERP system - SAP, Syspro, Sage, or Pastel - to pull live customer orders, material stock levels, and machine availability data. The load shedding schedule integration is configured and validated against historical scheduling decisions.

Go Live & Planner Transition (Day 17-21+)

The AI takes over primary scheduling responsibility. Your production planner shifts from reactive replanning to exception management - reviewing AI recommendations and approving the daily schedule in minutes. We provide weekly performance reporting showing OEE improvement and delivery performance.

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