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

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.



7.8.1 Adaptive Techniques for Product Families

Figure 7.2.2.2 showed an example of the variant master schedule. The example revealed that, in practice, this technique would not be applied for that case, because the number of variants turns out to be too high. How­ever, the present exercise is aimed to aid better understanding of the technique, and it is thus useful for all cases where the number of variants is significantly smaller than the total demand quantity for the product family.

Suppose that the demand of the product family P for January was 200 instead of 100. Again, suppose an equal option percentage — with a deviation of 20% — of the variants of the demand at the product family P level. What would have been the total number of variants V1 + V2+ … + V100 in the master production schedule for January?

Solution: 300. In fact, for 100 variants, an equal option percentage would result in 2 units per variant. If a deviation of 20% has to be considered for each variant, an additional (safety) demand of 0.4 units must be added. Because no fraction of a unit can be ordered, this value has to be rounded up to the next integer value, which is 1. Therefore, for each variant, 3 units will be in the MPS for January, or 300 in total.

For the month of March, where the demand of the product family was 150, can you explain why two units have to be considered in the MPS for each variant?

Solution: An equal option percentage would result in 1.5 units. The deviation of 20% can be included in the calculation before we round up to the next integer value. Thus, the deviation, that is, 20% of 1.5, equals 0.3, resulting in a total of 1.8 units per variant. This value is rounded up to the next integer, or 2 units.

For April, where the demand of the product family was 120, can you explain why only one unit has been considered in the MPS for each variant?

Solution: An equal option percentage would be 1.2 units. The deviation, that is, 20% of 1.2, equals 0.24, resulting in a total of 1.44 units per variant. As the units were rounded up by 0.8 in January and 0.2 in March, the 0.44 units in April are covered in any case. Therefore, it is sufficient to have only 1 unit in the MPS for April.


7.8.2 Generative Techniques — the Use of Production Rules in Order Processing

Look at the excerpt from the parameterized bill of material for the fire damper in Figure 7.3.3.1. What are the positions/variants selected in Figure 7.3.3.1 with the following parameter values?

Type = 2, drive = right, width = 1000, height = 200

Solution: Position/variant: 130/05, 140/01, 150/03, 160/09


7.8.3 Generative Techniques — Setting the Parameters of a Product Family

Figure 7.8.3.1 shows a product family (umbrellas) with some of the possible individual products.

Fig. 7.8.3.1        A product family and five product variants of this family.

What are the parameters that generate the product family, if they should generate the five variants at the least?

Answer: There are at least 6 parameters. The diameter of the umbrella is one parameter, for example.

What are possible ranges of values for these parameters?

Answer: For “continuous” parameters (e.g., diameter), assume reasonable incre­ments (e.g., 10 cm), as well as a reasonable minimum (e.g., 60 cm) and maximum (e.g., 150 cm). For parameters representing a set of discrete values (e.g., pattern), assume a reasonable number of different values (e.g., 30).

How many physically different umbrellas can be generated within that product family?

Answer: Combine each value of a parameter with each value of another parameter (compare Figure 7.3.1.2). Your result depends on the number of parameters you detected in question a., as well as the ranges of values you determined in question b. Thus, your answer will be different from your colleagues’ results.

Are there incompatibilities, that is, ranges of values that a parameter can assume, that are partly dependent on other parameters?

Answer: For example, if the diameter of the umbrella is greater than 120 cm, then the handle of the umbrella must be longer than 100 cm.




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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