Abstract

In domains where the “human factor” plays a major role in maintaining a stable process, knowledge transfer is a key technique to increase the company’s reactive resilience. We consider a manufacturing process on a fine blanking plant as an example. Workers operate complex machines that break from time to time. As downtime generates high cost, the worker has to identify the cause of the fault fast. In this paper, we present an application to assist novice workers in making crucial, time­sensitive decisions based on the knowledge of their expert peers

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