ProVSA – Employing process mining methods for value stream analysis and optimization of production planning and control processes in high-variant production

The research project ProVSA aims to develop a procedure that enables digital value stream analysis in high-variant production. Furthermore, the goal is to facilitate the prediction of relevant key figures (e.g. throughput time) and system states as well as the prescription of production parameters based upon the findings of the value stream analysis. Findings from the descriptive and predictive analyses as well as the prescription should contribute to the increase of the efficiency of production and planning processes for users.

Motivation

The growing demand for customized products leads to increased product and process variance and thus to increased complexity in production. To master this complexity, transparency must be created. However, the manual value stream analysis established for creating transparency in production cannot be applied economically in high-variant production environments. The use of digitally available data from production and the application of methods from the field of data mining offer the potential to apply value stream analysis efficiently in high-variant production environments.

Objective

The goal is to use data that is already available in production to enable digital value stream analysis and, based on this, enable predictive and prescriptive analyses to improve production and planning processes.

Approach

Initially, the database necessary for meaningful value stream analyses and relevant IT systems must be determined. Furthermore, process or data mining methods must be evaluated with regard to the predefined analysis tasks and an approach for the structured integration of the results to optimize production and planning processes must be developed. The goal is to combine all findings into a standardized procedure for digital value stream analysis.

Acknowledgement

The iwb would like to thank the Bavarian Ministry of Economic Affairs, Regional Development and Energy as well as the project management agency VDI/VDE for funding this research project.