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This paper presents a method based on multiattribute utility theory (MAUT) that facilitates the selection of a product line. The method helps select the subset of products to manufacture based on criteria at the: (1) product level (e.g., manufacturing cost, profit); and (2) product family level (e.g., commonality, component reuse, variety, market coverage). An example involving a family of staplers is used to demonstrate the method and to provide a well-documented engineering application of MAUT in product family design.

This paper describes the fundamental pieces of design information that compose the University of Missouri Rolla’s (UMR) design repository schema. Knowledge-based systems along with similar design information-capture schemas are reviewed. Repository schema conventions and specific implementation details are outlined to provide an understanding of the system connections and information relationships. Next, the repository schema is divided into seven main categories of design information including: artifact-, function-, failure-, physical-, performance-, sensory- and media-related information types. Each of the seven types of design information are described in detail to illustrate what elements of design information are recorded and how their relationships are established. An overview of the entire repository database is also presented. The result is a complete description and specification of the repository framework and allowable design information types such that the schema and repository could be recreated. Finally, a brief comparison is made between the UMR repository and its antecedent NIST repository framework.

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As companies are pressured to decrease product development costs concurrently with increasing product variety, the need to develop products based upon common components and platforms is growing. Determining why a platform worked, or alternatively why it did not, is an important step in the successful implementation of product families and product platforms in any industry. Unfortunately, published literature on platform identification and product family analysis using product dissection and reverse engineering methods is surprisingly sparse. This paper introduces two platform identification methodologies that use different combinations of tools that can be readily applied based on information obtained directly from product dissection. The first methodology uses only the Bills-of-Materials and Design Structure Matrices while the second utilizes function diagrams, Function-Component Matrices, Product-Vector Matrices, and Design Structure Matrices to perform a more in-depth analysis of the set of products. Both methodologies are used to identify the platform elements in a set of five single-use cameras available in the market. The proposed methodologies identify the film advance and shutter actuation platform elements of the cameras, which include seven distinct components. The results are discussed in detail along with limitations of these two methodologies.Downloaded From: http://proceedings.asmedigitalcollection.asme.org/ on 03/29/2015 Terms of Use: http://asme.org/terms