Process Mining in Production

Manufacturing companies have to overcome a wide range of challenges in order to remain competitive. The risk of supply chains being disrupted has increased significantly due to increasing globalisation. At the same time, rising raw material prices and personnel costs are leading to increased cost pressure. Strict regulatory requirements in the areas of environmental protection and occupational safety represent further cost hurdles that need to be overcome.

The growing challenges make process mining in the area of production essential. With the powerful solutions from process.science for Microsoft Power BI and Qlik Sense, manufacturing companies can analyze processes in a data-driven way, uncover inefficiencies and derive targeted improvement measures. Our Process Mining solutions for production enable continuous process optimization, which allows you to develop in a sustainable way.

One of the greatest strengths of our Process Mining solutions for production is the creation of comprehensive transparency. Tools for Power BI and Qlik Sense combine data from various sources such as ERP, MES or SCADA, thus enabling a complete view of the production processes. Dependencies and interactions between individual process steps become visible. This holistic transparency forms the basis for effective process analysis and targeted production process optimizations.

The detection of weak points and inefficiencies in production is particularly important here. The interactive process models from process.science also map complex production processes in detail, which allows you to identify delays in the flow of materials, machine failures or quality problems. Eliminating the latter is of crucial importance in production, because quality problems lead to rejects, rework and customer complaints. With Process Mining for production from process.science, companies can identify the causes of quality defects through comprehensive quality control in manufacturing. The analysis of quality data provides insights into relationships, which can be used to identify systemic errors. This enables companies to take targeted countermeasures and sustainably improve product quality.

Our solutions also provide valuable insights in the area of plant productivity in order to identify the causes of quality defects through comprehensive analyses. Here, Process Mining for production helps to identify downtime, cycle time deviations or setup times. For example, you can optimize plant productivity by improving setup processes or maintenance planning. Forward-looking planning can also increase energy efficiency in production.