State of the art in multi-stage production systems is End-Of-Line (EOL) quality control. The main drawback of EOL inspection is the off-line inspection at the final stage of the manufacturing chain, where already all possible defects of the production chain have been accumulated. Thus, a defective workpiece is machined wasting time, money and energy resources for creating a final product, which is out of tolerances and has to be recycled or scrapped. To overcome this drawback it is necessary to create solutions to reduce either defect generation or defect propagation. This paper focusses on the second approach, which aims at repairing defective workpieces by adapting consecutive process parameters in a multi-stage production system (downstream repair). By applying this concept to the production of electrical drives for power train applications, the effort needed for EOL testing can be reduced by shifting testing steps into the previous process chain. The currently used total flux measurement of laminated steel stacks is replaced by a space-resolved measurement. This permits the identification and local allocation of deviations in the magnetic field due to defective or weak magnets. The downstream repair strategy solves an optimization problem in order to compensate deviations in the magnetic field of single laminated steel stacks by adapting the assembly stage. Two repair strategies are discussed within this paper, namely sequential and selective assembly. In the proper assembling sequence, the laminated steel stacks are then assembled on the rotor according to the optimal assembling policy. Thus deviations of the laminated steel stacks are compensated.


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    Title :

    Proactive quality control system for defect reduction in the production of electric drives


    Contributors:
    Coupek, D. (author) / Verl, A. (author) / Aichele, J. (author) / Colledani, M. (author)


    Publication date :

    2013-10-01


    Size :

    599822 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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