Details

Autor(en) / Beteiligte

• Lorenz, Rafael
• Senoner, Julian
• Sihn, Wilfried
• Netland, Torbjørn

Titel

Using process mining to improve productivity in make-to-stock manufacturing

Ist Teil von

• International journal of production research, 2021-08, Vol.59 (16), p.4869-4880

Ort / Verlag

London: Taylor & Francis

Erscheinungsjahr

2021

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manufacturing processes in an automated manner. This way, manufacturers can leverage data to overcome the limitations of existing process mapping methods, which only provide static snapshots of process flows. By bridging data and process science, process mining can exploit hitherto untapped potential for productivity improvement. The proposed procedure is empirically validated at a leading manufacturer of sanitary products. The field test leads to three concrete improvement suggestions for the company. This research contributes to the literature on production research by demonstrating a novel use of process mining in manufacturing and by guiding practitioners in its implementation.