INDUSTRIAL INTELLIGENCE – DESIGN SCIENCE RESEARCH ON A BI-BASED APPROACH TO ENHANCE INFORMATION SUPPLY IN INDUSTRIAL COMPANIES
Flexibility, resource efficiency, and time-to-market are key success factors for industrial enterprises. Essential courses are set during early phases of product development as well as manufacturing. During these processes decisions are made without being able to evaluate their final impacts on (long term) key success factors like life-cycle costs or sustainability aspects. Thus e.g. operational design systems are not able to offer detailed semantic data concerning already existing features of other products. This is essential to analyse consequences of design changes on product life cycle and product range or to anticipate them on the basis of comparable historic data, respectively.
A generic business-intelligence-concept developed by research activities seems to be a promising approach in this case. One foundation pillar of this concept is the extension of business intelligence environments by product-orientated and machine-orientated data warehouses which contain semantic product data as well as manufacturing data. It is possible to combine information from product features and manufacturing information with the traditional indicators of managerial analysis in order to identify impacts of design-oriented and/or manufacturing decisions on product life cycle.
First insights promise high utility to industrial enterprises. An evaluation of the technical feasibility is still outstanding and part of an ongoing research project founded by the German Federal Ministry of Education and Research.
Lasi, Heiner and Kemper, Hans-Georg, "INDUSTRIAL INTELLIGENCE – DESIGN SCIENCE RESEARCH ON A BI-BASED APPROACH TO ENHANCE INFORMATION SUPPLY IN INDUSTRIAL COMPANIES" (2011). MCIS 2011 Proceedings. 75.
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