The methodology proposed in this chapter aims to address the link between the evolution of product feature relevance and the implications to product platform and product family design. By quantifying relevant/irrelevant product features to be included in next-generation product platform design, designers can identify the stand-alone or platform sharing components required to achieve desired product functionality. A data mining algorithm is introduced that uses time series data (consisting of product features) to determine the standard, nonstandard, and obsolete product features in the design of next-generation products. Product features are then mapped to engineering components/modules by employing data mining Natural Language Processing techniques that quantify the functionality requirements that are needed for a given set of product features. The goal of this work is to demonstrate the value of incorporating evolving product feature trends in the market space directly into product platform and product family sharing decisions.
|Original language||English (US)|
|Title of host publication||Advances in Product Family and Product Platform Design|
|Subtitle of host publication||Methods and Applications|
|Publisher||Springer New York|
|Number of pages||31|
|State||Published - Jan 1 2014|
All Science Journal Classification (ASJC) codes