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Jean-Michel LAMBOUR: Formerly R&D project manager, automotive paints
INTRODUCTION
You've just launched the production of an object or product. This industrial sector needs to be sustained over a fairly long period.
You may legitimately wonder whether this manufacturing process is operating at maximum capacity in terms of quality (with a hint of a robustness correction coefficient) and economic profitability.
You therefore run three essential risks:
Not being at the best quality level: this is one way of being overtaken by a competitor in the field; even if your quality level is sufficient, optimization will enable you to "race ahead"; in other words, you'll avoid seeing a competitor emerge, at least in terms of quality.
Lack of robustness in the process: this is the risk of having your parameters set at such a level that you can't absorb the fluctuations inherent in an industrial application; this often leads to fluctuating quality and therefore a double risk: being displaced by a competitor with more stable production, or significant rejects or downgrades.
The risk can also be financial, if you fail to optimize costs, but it can also become capacity-related, i.e. if you reach a certain ratio of rejected products, your facilities will no longer be able to produce enough objects or products acceptable to the customer.
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Website
Method and mathematical exercises around the simplex :
homepages.ulb.ac.be/~sfiorini/math-f-306/chap_03_exercices.pdf
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