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

17.9 References

Apel85 Appelrath, H.J., “Von Datenbanken zu Expertensystemen,” Informatik Fachberichte 102, Springer, Berlin, 1985
APIC16 Pittman, P. et al., APICS Dictionary, 15th Edition, APICS, Chicago, IL, 2016
EiHi91Eigner, M., Hiller, C., Schindewolf, S., Schmich, M., “Engineering Data­base: Strategische Komponente in CIM-Konzepten,” Hanser, München, 1991
Pels92 Pels, H.J., Wortmann, J.C., “Integration in Production Management Systems,” North-Holland, Amsterdam, 1992
Schi01Schierholt, K., “Process Configuration — Mastering Knowledge-Intensive Planning Tasks,” vdf Hochschulverlag, Zurich, 2001
Schö01Schönsleben, P., “Integrales Informations­management: Informations­systeme für Geschäfts­prozesse — Management, Modellierung, Lebenszyklus und Technologie,” 2. Auflage, Springer Verlag, Berlin, 2001
Schö88a Schönsleben, P., “Flexibilität in der computergestützten Produktionsplanung und -steuerung,” 2. Auflage, AIT-Verlag, D-Hallbergmoos, 1988
Schw96 Schwarze, S., “Configuration of Multiple Variant Products,” BWI-Reihe Forschungs­berichte für die Unternehmenspraxis, vdf Hochschulverlag, Zürich, 1996
SöLe96 Schönsleben, P., Leuzinger, R., “Innovative Gestaltung von Versicherungs­produkten: Flexible Industriekonzepte in der Assekuranz,” Gabler, Wiesbaden, 1996
Veen92 Veen, E.A., “Modelling Product Structures by Generic Bills of Material,” Elsevier Science, Amsterdam, 1992


Course sections and their intended learning outcomes

  • Course 17 – Representation and System Management of Logistic Objects

    Intended learning outcomes: Describe order data in sales, distribution, production, and procurement. Explain in detail master data for products and processes. Disclose extensions arising from the variant-oriented and the processor-oriented concepts. Produce an overview on the management of product and engineering data.

  • 17.1 Order Data in Sales, Distribution, Production, and Procurement

    Intended learning outcomes: Present the data structure of customers and suppliers. Describe the general data structure of orders in sales and distribution, production, and procurement. Disclose the data structure of the order and partial order header as well as the order position.

  • 17.2 The Master Data for Products and Processes

    Intended learning outcomes: Describe master data of products, product structure, components, and operations. Explain the data structure of item master, bill of material, and where-used list. Disclose the data structure of work center master data, the work center hierarchy, as well as for operation, routing sheet, production equipment, bill of production equipment, and bill of tools.

  • 17.3 Extensions Arising from the Variant-Oriented Concept

    Intended learning outcomes: Produce an overview on expert systems and knowledge-based systems. Explain the implementation of production rules. Present a data model for parameterized representation of a product family.

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