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Automatic Composition of Rough Solution Possibilities in the Target Planning of Factory Planning Projects by Means of Combinatory Logic

  • Jan WinkelsEmail author
  • Julian Graefenstein
  • Tristan Schäfer
  • David Scholz
  • Jakob Rehof
  • Michael Henke
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11247)

Abstract

Increasing competition, stronger customer focus, shorter product lifecycles and accelerated technological developments imply that companies are faced with the challenge of adapting their own production to the circumstances at ever shorter intervals. The factory planning project is becoming increasingly complex, but there is less and less time available for adaptation. Particularly in the initial planning phase, targets are defined without reliable planning information for the further course, which have far-reaching consequences for the outcome of a successful planning. This paper shows a possibility to generate meaningful solution alternatives at an early stage of the target planning in order to enable an efficient planning process in terms of time and costs. With the help of a constraint-based variant compilation on the basis of previously defined target and frame parameters as well as existing information on the current factory system, various possible solution variants for target planning are to be created. A specific use case scenario was used to develop and test the presented methodology. By comparing combinations of the most diverse possible solutions, the use of a combinatory logic approach enables the first rough and plausible solution variants to be generated automatically, on the basis of which the detailed planning process for achieving the determined solution variant can be created. This way, planning bottlenecks due to the wrong choice of variants as well as large time expenditure for the creation of solution variants can be avoided.

Keywords

Automatic composition Combinatory logic Factory planning Target planning 

Notes

Acknowledgement

The study presented in this paper was partly funded by the GRK 2193 (www.grk2193.tu-dortmund.de/de/) and the Center of Excellence for Logistics and IT (www.leistungszentrum-logistik-it.de/) located in Dortmund.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jan Winkels
    • 1
    Email author
  • Julian Graefenstein
    • 2
  • Tristan Schäfer
    • 1
  • David Scholz
    • 2
  • Jakob Rehof
    • 1
  • Michael Henke
    • 2
  1. 1.TU DortmundDortmundGermany
  2. 2.TU DortmundDortmundGermany

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