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How to Learn from Intelligent Products; The Structuring of Incoherent Field Feedback Data in Two Case Studies

  • Renate de Bruin
  • Yuan Lu
  • Aarnout Brombacher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5617)

Abstract

A growing number of products - particularly highly innovative and intelligent products - are being returned by customers, while analysis shows that many of these products are in fact functioning according to their technical specifications. Product developers are recognizing the need for information that gives more detail about the reason for these product returns, in order to find the root cause of the problems. Traditionally a lot of information from the field is stored in departments like sales and service (helpdesks and repair centers). Combining these data sources with new field feedback data sources, like customer experiences on the internet and product log files, could provide product developers with more in-depth and accurate information about the actual product performance and the context of use. Case studies were done at two different industries: a company from consumer electronic industry and a company from professional medical system industry. The Maturity Index on Reliability (MIR) method, a method to assess capability for businesses to respond to product reliability related issues, was combined with Contextual Design, a method for user context mapping and requirement definition, and explored as a means to analyze the structure and capability of the current field feedback process in supporting the development of complex and innovative products .

Keywords

Field Feedback Data Product Failure Root Cause Analysis Business Information Flow MIR Method Contextual Design 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Renate de Bruin
    • 1
  • Yuan Lu
    • 1
  • Aarnout Brombacher
    • 1
  1. 1.Department of Industrial Design, Business ProcessEindhoven University of TechnologyEindhovenThe Netherlands

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