Framework for the Continuous Increase of Product Performance by Analyzing Product Usage Data

Abstract

Today's manufacturing companies in the machinery and plant engineering sector are facing increasingly shorter innovation and technology cycles. As a consequence, admired features of their products are rapidly changing to standard features in the customer's perception. Thus, product optimizations during the product life cycle are gaining in importance. Taking this into consideration, subscription models provide a business framework which aims for a continuous improvement of product performance in return for a periodic payment during the product use phase. In order to define this performance, the challenge is to precisely focus on those product features providing the highest contribution to the specific customer benefit and to detect optimization potentials on the existing product. Smart products, which permanently provide product usage data through chips, processors and embedded systems, offer new possibilities on both tracking the current status of a product feature and deduce optimization potentials. This paper introduces a framework to increase product performance by investigating specific product features. Optimization measures shall be identified and deduced by the systematic analysis of product usage data.