In today's manufacturing world, change is the order of the day: machines break down, customer orders change, materials are delayed. At the same time, reliable deliveries are expected, and calm and clarity on the shop floor are crucial for efficient processes. This is where the concept of stable production plans comes into play – a central component of resilient production planning.
What is a stable production plan?
A stable production plan remains largely constant despite necessary adjustments to current events, especially with regard to promised delivery dates. Such plans minimize short-term changes and ensure continuity in the production planning process without unnecessarily disrupting shop floor management processes.
Flexibility vs. stability in production planning
Regular plan adjustments are part of everyday industrial production: deviations in production progress, machine failures, and new orders. All of this requires reactions in production planning. This creates a conflict of objectives between optimization and stability:
- The plan must respond flexibly to current circumstances.
- At the same time, it should not be completely overturned with every adjustment.
Frequent short-term changes lead to uncertainty on the shop floor, increased communication efforts, and potential scheduling conflicts in shop floor management.
The role of the frozen zone in APS-based planning
One established means of stabilization is the so-called frozen zone. This is a period during which no changes, or only very specific changes, are permitted to the production plan. This phase prevents short-term plan changes and contributes to security in production control.
However, the frozen zone alone is not sufficient. It only stabilizes the short-term time horizon. Medium-term and long-term stability—especially with regard to delivery dates—remains unaffected if completely new deadlines arise with each new optimization.
How APS enables stable production plans with AI
Traditional, rule-based planning systems reach their limits when it comes to balancing stability and flexibility. Modern systems such as PAILOT therefore rely on artificial intelligence. AI-based detailed scheduling current data from production and the supply chain and uses it to create an intelligent production plan. The AI pursues two key objectives in this process:
- Keep delivery dates as far as possible
- Do not cause additional delays
New orders are integrated in a second planning phase in such a way that existing processes are affected as little as possible. This is an important basis for stable and responsive production optimization.
Stability as a success factor in production planning
Stable production plans are essential for reliable and efficient production. They relieve shop floor management, reduce disruptions, and ensure on-time delivery to customers and partners. With AI-supported detailed scheduling a modern APS system, this stability can be combined with the necessary responsiveness. This is a decisive step on the way to a smart factory and holistically optimized production planning.
