Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

7.9 References


APIC16Pittman, P. et al., APICS Dictionary, 15th Edition, APICS, Chicago, IL, 2016
Schi01Schierholt, K., “Process Configuration — Mastering Knowledge-Intensive Planning Tasks,” vdf Hochschul-verlag, Zurich, 2001
Schö88aSchönsleben, P., “Flexibilität in der computergestützten Produktionsplanung und -steuerung,” 2nd Edition, AIT-Verlag, D-Hallbergmoos, 1988
Schö88bSchönsleben, P., “Expertensysteme als Hilfsmittel der variantenreichen Produkt­konfiguration,” in Informatik, Forschung und Entwicklung, Springer, Berlin, 1988
Schö12Schönsleben, P., “Methods and tools that support a fast and efficient design-to-order process for parameterized product families,” Annals of the CIRP, 61/1:179-182, 2012
Schw96Schwarze, S., “Configuration of Multiple Variant Products,” BWI-Reihe Forschungsberichte für die Unternehmenspraxis, vdf Hochschulverlag, Zurich, 1996
SöLe96Schönsleben, P., Leuzinger, R., “Innovative Gestaltung von Versicherungs­produkten: Flexible Industrie­konzepte in der Assekuranz,” Gabler, Wiesbaden, 1996
WiPo15Willner, O., Powell, D., Gerschberger, M., Schönsleben, P., “Exploring the Archetypes of Engineer-to-Order: An Empi­rical Analysis,” International Journal of Operations and Production Management, DOI - 10.1108/IJOPM-07-2014-0339, 2015


Course 7: Sections and their intended learning outcomes

  • Course 7 – The Concept for Product Families and One-of-a-Kind Production

    Intended learning outcomes: Produce logistics characteristics of a product variety concept. Explain adaptive and generative techniques in detail. Describe the use of generative and adaptive techniques for engineer-to-order. Differentiate various ways of cooperation between R&D and Engineering in ETO Companies.

  • 7.1 Logistics Characteristics of a Product Variety Concept

    Intended learning outcomes: Differentiate between high-variety and low-variety manufacturing. Describe different variant-oriented techniques, and the final assembly schedule.

  • 7.2 Adaptive Techniques

    Intended learning outcomes: Explain techniques for standard products with few variants as well as techniques for product families.

  • 7.3 Generative Techniques

    Intended learning outcomes: Disclose the combinatorial aspect and the problem of redundant data. Present variants in bills of material and routing sheets as production rules of a knowledge-based system. Explain the use of production rules in order processing.

  • 7.8 Scenarios and Exercises

    Intended learning outcomes: Apply adaptive techniques for product families. Disclose the use of production rules in order processing. Elaborate the setting the parameters of a product family.

  • 7.9 References

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