Prioritisation of influence variables for a flexible and efficient production

Influence variables can have a huge impact on the process and machine's behaviour during the production process and as a result on the product quality. Although process knowledge, methods for data base and regression analyses are available, it is still difficult to identify all relevant parameters and find their effect on the process. The method, described in this paper, shows how all relevant parameters can be found by using a holistic approach. Through filtering, the total number of variables can be diminished as far as possible. For each variable a description about its impact on the process is designed and based on this, different actions can be derived to compensate or minimize the influences.