Improvement in product development: Application of back-end data
Paper i proceeding, 2012
Working with Quality Management there is emphasis on moving efforts upstream, i.e. to work on improvements as early as possible in the design phases. Less is done on how to use, and work with, data from the back-end of the product development process to support upstream improvement. In this paper the purpose is to suggest practices on how data from the back-end of the product development process can be fed back to the early design phases as a basis for improvements. The case studied will have a special focus on how use of claim data, one type of back-end data, can support robust design methodology.
This paper is based on a case study at a medium-sized Swedish manufacturing company. The study has encompassed interviews, direct observations, participation, and document analysis. Interviews were semi-structured; the questions mainly addressing use of the back-end data in product development. Data collection was based on real-time feedback and observations in order to assess the outcome, and its contribution towards improvements in product development.
The back-end data, when analyzed and fed back into the product development process, aids in closing the product development loop from claims to improvement in the design phase. Further, the use of back-end data in improvement work extends the usage of the claim database to various users, e.g. designers or developers. This can be facilitated through the establishment of links from the claim database to existing tools such as FMEA. Finally, continuous reporting and use of back-end data creates awareness of improvement needs and provides an opportunity to monitor performance over time in relation to customer usage variations.
The paper addresses an area that has not previously been explored in depth, namely the use of back-end data as a basis for upstream efforts. Principles of robust design methodology are applied in product development through systematic analysis of the claims data, where failures during product use stage are addressed in connection to noise factors.
claims analysis
robust design methodology
Back-end data
product development.