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Comparing concepts for shop floor control of information-processing services in a job shop setting: a case from the financial services sector

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  • Michael Leyer
  • Jürgen Moormann

Abstract

Controlling information-based service processes in the short term is a major challenge. Within these processes, information is collected, generated and transformed while customers are directly involved. Typically, such processes are characterised by a job shop layout that increases complexity relating to shop floor control. In contrast to manufacturing, such settings have rarely been addressed in the literature to date. This is surprising, as information-processing services exist in every industry. Thus, evidence about the impact of concepts for shop floor control in such pure service environments is needed. As a case study, we use one of the most intense information-processing industries – the financial services sector. A simulation model is built using process mining as a novel approach to gather a major part of the relevant data from business information systems. We identify nine concepts for shop floor control and simulate the usage of these in six scenarios. The results show that the concept that prioritises customer orders with the longest expected processing time is superior in cycle time over all six scenarios. The application of this concept leads to a reduction of the average cycle time of almost 50% in the case study.

Suggested Citation

  • Michael Leyer & Jürgen Moormann, 2015. "Comparing concepts for shop floor control of information-processing services in a job shop setting: a case from the financial services sector," International Journal of Production Research, Taylor & Francis Journals, vol. 53(4), pages 1168-1179, February.
  • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:4:p:1168-1179
    DOI: 10.1080/00207543.2014.950356
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    Cited by:

    1. Prajogo, Daniel & Toy, Jordan & Bhattacharya, Ananya & Oke, Adegoke & Cheng, T.C.E., 2018. "The relationships between information management, process management and operational performance: Internal and external contexts," International Journal of Production Economics, Elsevier, vol. 199(C), pages 95-103.
    2. Christopher A. Boone & Benjamin T. Hazen & Joseph B. Skipper & Robert E. Overstreet, 2018. "A framework for investigating optimization of service parts performance with big data," Annals of Operations Research, Springer, vol. 270(1), pages 65-74, November.

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