Abstract
The description of process efficiency remains a key factor for manufacturing companies competing in volatile markets. Since describing the process performance requires the consideration of all order-fulfilling activities, focussing on the end-to-end order processing process is crucial. Classical techniques for process description are time- and cost-intensive while relying on situational impressions. Consequently, improvement approaches are based on gut feelings and cannot consider dynamic process behaviour. Process mining can be used for fact-based and objective process descriptions. However, today’s process mining applications are mainly conducted in partial processes with similar order types. In the end-to-end order processing, multiple orders with one-to-many and many-to-many relationships exist that need an object-centric process mining approach. This paper presents a methodology for the application of process mining in end-to-end order processing with multiple order types. Based on data from software infrastructure, the integration of the methodology provides manufacturing companies with process models and process performance indicators to describe their PP in end-to-end order processing processes.
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Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy—EXC-2023 Internet of Production—390621612.
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Schuh, G., Gützlaff, A., Schmitz, S., Kuhn, C., Klapper, N. (2022). A Methodology to Apply Process Mining in End-To-End Order Processing of Manufacturing Companies. In: Agarwal, R.K. (eds) Recent Advances in Manufacturing Engineering and Processes. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-3934-0_15
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