Industrial intelligence - a business intelligence-based approach to enhance manufacturing engineering in industrial companies

Flexibility, resource efficiency, and time-to-market are key success factors for industrial enterprises. Essential settings are set during early phases of product development as well as manufacturing. In later product lifecycle phases, the responses from the market (e.g. complains or the amount of damage cases) show the maturity stage of the products. Quality methods like TQM or EFQM pursue the goal to permanently learn from this information. Therefore it is necessary to have an adequate information supply. This article focuses on this problem in the context of maturity stage management in manufacturing engineering. The research therefore first identifies a huge gap between the theoretically discussed information supply, based on encompassing data bases, and the real existing heterogeneous IT landscapes, which have grown in history. On basis of empirical findings, industrial businesses lack in concepts that put them in a position of adequate information supply. Therefore, a generic Business Intelligence concept, developed through research activities, seems to be a promising approach. It is thus possible to combine information from product features and manufacturing information with the traditional dimensions of managerial analysis, in order to identify impacts of engineering decisions on the product lifecycle. © 2012 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of Professor Roberto Teti.