A Methodology to Support Product Family Redesign using Genetic Algorithm and Commonality Indices,"

ABSTRACT Many of today's manufacturing companies are using platform-based product development to realize families of products with sufficient variety to meet customers' demands while keeping costs relatively low. The challenge when designing or redesigning a product family is in resolving the tradeoff between product commonality and distinctiveness. Several methodologies have been proposed to redesign existing product families; however, a problem with most of these methods is that they require a considerable amount of information that is not often readily available, and hence their use has been limited. In this research, we propose a methodology to help designers during product family redesign. This methodology is based on the use of a genetic algorithm and commonality indices -metrics to assess the level of commonality within a product family. Unlike most other research in which the redesign of a product family is the result of many human computations, the proposed methodology reduces human intervention and improves accuracy, repeatability, and robustness of the results. Moreover, it is based on data that is relatively easy to acquire. As an example, a family of computer mice is analyzed using the Product Line Commonality Index. Recommendations are given at the product family level (assessment of the overall design of the product family), and at the component level (which components to redesign and how to redesign them). The methodology provides a systematic methodology for product family redesign

Product Family Design Knowledge Representation, Aggregation, Reuse, and Analysis

A flexible information model for systematic development and deployment of product families during all phases of the product realization process is crucial for product-oriented organizations. In current practice, information captured while designing products in a family is often incomplete, unstructured, and is mostly proprietary in nature, making it difficult to index, search, refine, reuse, distribute, browse, aggregate, and analyze knowledge across heterogeneous organizational information systems. To this end, we propose a flexible knowledge management framework to capture, reorganize, and convert both linguistic and parametric product family design information into a unified network, which is called a networked bill of material (NBOM) using formal concept analysis (FCA); encode the NBOM as a cyclic, labeled graph using the Web Ontology Language (OWL) that designers can use to explore, search, and aggregate design information across different phases of product design as well as across multiple products in a product family; and analyze the set of products in a product family based on both linguistic and parametric information. As part of the knowledge management framework, a PostgreSQL database schema has been formulated to serve as a central design repository of product design knowledge, capable of housing the instances of the NBOM. Ontologies encoding the NBOM are utilized as a metalayer in the database schema to connect the design artifacts as part of a graph structure. Representing product families by preconceived common ontologies shows promise in promoting component sharing, and assisting designers search, explore, and analyze linguistic and parametric product family design information. An example involving a family of seven one-time-use cameras with different functions that satisfy a variety of customer needs is presented to demonstrate the implementation of the proposed framework

Examination of Platform and Differentiating Elements in Product Design

The problems of mass customization, portfolio design, and platforming all pose a common challenge to the designer: knowing how to partition a set of product variants to maximize commonality and simultaneously achieve sufficient differentiation for purposes of customization. This research focuses on the particular issue of how differences between platform elements and differentiating elements are evidenced in the product layout or configuration. The premise of this research is that certain architectural properties, such as modularity, vary between platform and differentiating elements. In particular, certain measures of commonality offer an appropriate set of indices for evaluating these differences in a systematic and repeatable manner. Both function and physical solution commonality provide a descriptor with which to distinguish and rank platform and differentiating elements. By evaluating components of a product in terms of function commonality, physical solution commonality, and modularity, a comparison can be made between platforms and differentiating elements with respect to these indices. The hypothesis of this work is that platforms are integrated and the non-common differentiating elements are, relative to the platforms, more modular. While anecdotal evidence exists to support this idea, the purpose of this work is to evaluate two existing product families as a means for analyzing this hypothesized relation. The result of this research is a descriptive set of knowledge that illustrates the distinguishing factors between platform and differentiating elements. The data specifically demonstrate the differences in architecture between platforms and differentiating elements, thus suggesting how these design aspects can and should be addressed at the conceptual stage of design. While not the focus of this study, future research involving a more prescriptive approach to conceptual design can directly benefit from the results. The knowledge gained in this work serves as a foundation for addressing portfolio design where both customization and commonality are key issues

Examination of Platform and Differentiating Elements in Product Family Design

The problems of mass customization, portfolio design, and platform design all pose a common challenge to the designer: knowing how to partition a set of product variants to maximize commonality and simultaneously achieve sufficient differentiation for purposes of customization. This research focuses on the particular issue of how differences between platform elements and differentiating elements are evidenced in the product layout or configuration. The premise of this research is that certain architectural properties, such as modularity, vary between platform and differentiating elements. In particular, certain measures of commonality offer an appropriate set of indices for evaluating these differences in a systematic and repeatable manner. Both function and physical solution commonality provide a descriptor with which to distinguish and rank platform and differentiating elements. by evaluating components of a product in terms of function commonality, physical solution commonality, and modularity, a comparison can be made between platforms and differentiating elements with respect to these indices. The hypothesis of this work is that platforms are integrated and the non-common differentiating elements are, relative to the platforms, more modular. While anecdotal evidence exists to support this idea, the purpose of this work is to evaluate two existing product families as a means for analyzing this hypothesized relation. The result of this research is a descriptive set of knowledge that illustrates distinguishing factors between platform and differentiating elements. The data specifically demonstrates the differences in modularity between platforms and differentiating elements, thus suggesting how this design aspect can and should be addressed during design. While not the focus of this study, future research involving a more prescriptive approach to design can directly benefit from the results. The knowledge gained in this work serves as a foundation for addressing portfolio design where both customization and commonality are key issues

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Using product family evaluation graphs in product family design

Product family design and platform-based product development have garnered much attention. They have been used to provide nearly customised products to satisfy individual customer requirements and simultaneously achieve economies of scale during production. The inherent challenge in product family design is to balance the trade-off between product commonality (how well the components and functions can be shared across a product family) and variety (the range of different products in a product family). Quantifying this trade-off at the product family planning stage in a way that supports the engineering design process has yet to be accomplished. In this paper, we introduce a graphical evaluation method, the product family evaluation graph (PFEG), that allows designers to choose the \u27best\u27 product family design option among sets of alternatives based on their performance with respect to an ideal commonality/variety trade-off determined by a company\u27s particular competitive focus, and guides designers towards a more desirable trade-off between commonality and variety in an existing product family. Two necessary supporting pieces for developing the PFEG are also proposed. One piece is the development of commonality and variety indices to quantitatively capture the degree of commonality and variety in a product family and its functions and components. We introduce two sets of commonality and variety indices-the CDI (commonality versus diversity index) for commonality (CDIC) and variety (CDIV), and the CMC (comprehensive metric for commonality) for commonality (CMCC) and variety (CMCV)-to achieve this. The other supporting piece is the development of a quantitative representation of the ideal trade-off between commonality and variety in a product family, known as the commonality/variety trade-off angle , based on the elements that characterise a company\u27s competitive focus and their industry-wide competitors. A linear regression model is used to link the qualitative competitive focus to a quantitative engineering perspective, and then to estimate the ideal trade-off angle. The commonality/variety trade-off angle can then be applied to the PFEG to help designers evaluate a product family or compare product family design alternatives. Most importantly, the PFEG is not just the graph of the two sets of indices; it is the representation of the commonality/variety trade-off relative to the desired competitive focus. Four families of power tools are used to illustrate how the computation of such indices supports product family design evaluation in the PFEG. In this paper, we only use the CDI in the example application, but the CMC can be computed using the same approach

Frameworks for product family design and development

In today\u27s market, products must meet or exceed customers\u27 needs while being competitively priced and developed in the shortest time possible. While product platforms address many of these requirements, they can incur additional development challenges with regards to coordination, time, and cost. Companies therefore need to use a concurrent engineering process to develop product families and product platforms efficiently; however, no concurrent engineering process models exist to support product family development. Based on concurrent engineering principles, four processes are proposed for systematic product family design using two platforming approaches - top-down and bottom-up - and two development drivers: product-driven and platform-driven. The first objective of this study is to propose a consistent product family development process terminology. The second objective is to detail representative frameworks and processes for the four proposed product family design processes based on the two approaches and two drivers. Several industry examples highlight the context and illustrate the four proposed processes. © Sage Publications