A Feature-based Concept for Decision Support to Cope with Product Variety

Abstract Industrial companies face the situation that customers demand more and more individualized products. This results in an increasing number of product variations and in batch sizes which tend to one. The essential decisions to ensure resource efficiency in this context are part of the product development. It has to be decided if it is possible to fulfill customers’ requirements by adapting existing products and parts, or if a new design is necessary. On the one hand, this is a technical question, but on the other hand, it is important to be able to estimate the costs of such decisions reliably. State of the art is that relevant information is spread across a company in different information systems and rarely available within an appropriate time. But an important step to support such decisions is to identify similarities between products based on their technical properties and to combine this with relevant economic information. This paper proposes a concept for the aforesaid task. The applied methodology is based on the design science approach: Various interviews with experts from German industrial companies deliver the requirements for the concept. The approach uses feature-technology which is the basis of the digital product model. Each part is described completely by the total amount of all features and their corresponding parameters. Features extracted from computer aided design (CAD) systems and loaded into a Business Intelligence infrastructure offer the possibility to analyze various parts on the feature-level. The results reveal that Business Intelligence is able to provide an adequate basis for decision-making in this context. It is possible to combine the relevant manufacturing and economic information with original product data from engineering and, therefore, to deal with an increasing product variety.