The new generation of advanced planning and scheduling overcomes many of current limitations by applying optimization algorithms instead of fixed logic that can trade off priorities and alternatives to come up with a more feasible plan that balances both resources and material date and quantities. But even optimization algorithms, as good as they are, still have their limitations. It takes a dedicated, knowledgeable human planner to interpret and apply the recommendations in the context of what’s really happening out on the plant floor and in the customer’s world by using intelligence that is not found in the data.
The production planning systems “learn” by collecting a massive amount of data and thoroughly analyzing it for cause and effect to build a model of the process. Then, as new information comes in, the system can perform thousands of what-if simulations to find the best path forward. The model is also refined based on additional data as these scenarios play out.
Production planning systems that incorporate AI capabilities will not replace human planners — at least, not anytime soon. It will take some time to build up the necessary level of confidence needed to trust a computer to carry out this vital task. That being said, AI-developed plans and schedules will undoubtedly be better than any human could create. Plants will run more efficiently, product quality will improve and more work will be completed on time and at a lower cost.
So, what will the planner do after AI takes over the job of production planning in manufacturing? In addition to adding the “sanity check” on plans and planning system operations, human planners can focus on managing any special exceptions that the system might not be able to address. In addition, human insight and ingenuity can be directed toward process improvement.
Using optimization algorithms in production planning has several obvious benefits:
- Reduced disruptions on the production line
- Fewer late orders (resulting in reduced use of premium freight)
- More efficient use of resources
- Decreased inventory needs (with the potential for an increasingly lean supply stream)
- More efficient use of time for planners (enabling them to add value in other areas)