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


Flexibility to fulfill customer demands varies in degree. In the fashion industry, for example, there are “off-the-rack” products, prêt-à-porter (ready-to-wear) products, and haute couture, or creations made for individual customers. In gastronomy, there are standard dinner menus, à la carte concepts, and even customer-specific menu creations. Other industries, including service industries distinguish similar levels of adapting to customer demands using their own terminology.


Course section 7.1: Subsections and their intended learning outcomes

  • 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.

  • 7.1.1 High-Variety Manufacturing and Low-Variety Manufacturing

    Intended learning outcomes: Identify values of characteristic features for high-variety manufacturing. Explain long- and medium-term planning for manufacturing according to customer specification or of product families with many variants. Disclose values of characteristic features for low-variety manufacturing.

  • 7.1.2 Different Variant-Oriented Techniques, and the Final Assembly Schedule (FAS)

    Intended learning outcomes: Differentiate between adaptive and generative variant-oriented techniques. Disclose typical sets of characteristics and production types that arise frequently with the four product variety concepts. Describe how the MPS concerns the highest structure level still having a small number of different items. Identify FAS / MPS / OPP patterns in dependency on the product variety concept and their relation to the patterns of the T analysis.



Course 7: Sections and their intended learning outcomes

  • 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.

  • 7.4 Generative and Adaptive Techniques for Engineer-to-Order (ETO)

    Intended learning outcomes: Differentiate between the classical procedure and different archetypes of engineer-to-order. Describe the approach for basic and for repeatable engineer-to-order.

  • 7.5 Cooperation between R&D and Engineering in ETO Companies

    Intended learning outcomes: Describe different means used for cooperation between the R&D and the order-specific engineering departments. Present the portfolio of cooperation types between R&D and engineering in ETO companies.

Print Top Down Previous Next