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Problem 1

What relevance does something as abstract as a 鈥渟cience of manufacturing鈥 have to manufacturing management?

Problem 2

Discuss the 鈥渇allacy of affirming the consequent鈥 in which if A implied B and B is true, we conclude A is true. Give an example from either a beer commercial or a clothing advertisement.

Problem 3

How many consistent observations does it take to prove a conjecture? How many inconsistent observations does it take to disprove a conjecture?

Problem 4

How can the concept of 鈥渃onjectures and refutations鈥 be used in a practical problem-solving environment?

Problem 5

Give a new example of a tautology.

Problem 6

List some dimensions along which manufacturing environments differ. How might these affect the 鈥渓aws鈥 governing their behavior? Do you think that a single science of manufacturing is possible for every manufacturing environment?

Problem 7

Indicate how each of the following might promote and impede the objective to maximize long-run profitability: (a) Decrease average cycle time (b) Decrease WIP (c) Increase product diversity (d) Improve product quality (e) Improve machine reliability (f) Reduce setup times (g) Enhance worker cross-training (h) Increase machine utilization

Problem 8

Why do you think that many writers in the lean and Six Sigma literature are loath to acknowledge the existence of trade-offs? Do you think this has had positive, negative, or both effects?

Problem 9

Why might the objective to maximize profits be difficult to use at the plant level? What advantages, or disadvantages, are there to using 鈥渕inimize unit cost鈥 instead?

Problem 10

We have suggested net profit and return on investment as firm-level measures. Do these capture the essence of a healthy firm? What characteristics are not adequately reflected in these measures? Can you suggest alternatives?

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