Artificial intelligence optimizes production planning (SUPPORT)

Production planning and control (PPC) in companies influences profitability as well as material flows, machine utilization and the actual deployment of employees. Current methods for planning optimization reach their limits due to the high level of complexity and usually only focus on increasing the productivity of a production process.

The aim of the ‘Sustainable and Human-centered Production Planning and Control Based on Reinforcement Learning Techniques (SUPPORT)’ project is to simplify complex production planning. This is to be achieved through reinforcement learning. Reinforcement learning is a form of machine learning and can therefore be classified as artificial intelligence (AI). The advantage of reinforcement learning is that it can also find solutions to very complex problems. The AI is not shown which action is best in which situation, but instead receives a reward at a certain time, which can also be negative. However, a simulation model is required for training. As manual creation is time-consuming, the model is to be created automatically within the scope of the project ‘SUPPORT’. In addition to the previous optimization parameters, the workload of employees is also to be taken into account so that productivity can be increased in harmony with the employees. This should make it possible to solve complex PPS tasks efficiently and sustainably with little effort.