In this paper a decision support framework is presented for the design of flexible engineering systems. The framework draws on concepts from multi-objective optimization, consumer choice theory, and utility theory. The framework supports the necessary decisions in the design of flexible engineering systems or systems that can change their functionality and embodiment to satisfy multiple performance requirements. The goal of the framework is to determine a design configuration that maximizes corporate utility while setting attribute and budget constraints for the conceptual design phase. The details of the framework are covered and then applied to a simple case study.
In this paper, a framework for the concept of flexibility in complex system design is presented. This is one of the first of many steps toward developing new design methods for designers that will aid them in the development of customizable systems that meet the requirements of multiple customers and multiple tasks. The hope is that this paper will provide both a starting point from which academia and industry can move forward in developing new design methods for flexible systems and a basis for establishing a standard lexicon for use when referring to flexible system design.
In this article, an argument for validation of design-decision methods is presented. In the process of justifying the need for validation, several criteria for a valid design-decision method are introduced. These criteria represent a starting point from which the research community can continue to debate and ponder the validation issue. Under these criteria, a critical empirical investigation of two popular decision support methods, the House of Quality and Suh’s Axiomatic Design, is presented via a simple design problem and both are shown to violate some portion of the proposed definition of validity. The goal of this article is to raise awareness of potential flaws in popular design-decision aids and to promote debate on design validation within the concurrent engineering research community.
The evolution of design thinking has seen numerous challenges and advances in transforming information into knowledge for engineers to design systems, products, and processes. These transformations occur in three stages throughout a design process. In simple form, the early, middle, and late stages of a design process serve to develop an understanding of the customer’s needs, arrive at the final concept of the design, and analyze and support the performance and usage profile of the deployed product, respectively. The quality and accuracy of the input information and the effectiveness of each transformation determine the success or failure of the product. Capturing good information and converting it to knowledge are two important tasks that have motivated a long history of research in design processes and tools. In this paper, we propose Design Analytics (DA) as a new paradigm for significantly enhancing the core information-to-knowledge transformations. The overall aim is to capture, store, and leverage digital information about artifacts, their performance, and their usage. The information is transformed into knowledge in each of the three stages using various analytics and cyber-enabled tools such as design repositories and concept generators. The ultimate result is better performing and functioning products. As web analytics has transformed how companies interact with consumers on the internet, we expect DA to transform how companies design products with and for consumers. An illustrative case study is performed to demonstrate some of the foundations of DA in the redesign of a refrigerator.
Purpose-The House of Quality (HoQ) is a popular design tool that supports information processing and decision making in the engineering design process. While its application is an aid to conceptual aspects of the design process, its use as a quantitative information tool in engineering design is potentially flawed. This flaw is a result of potential designer interpretation of the HoQ resultsinterpretation which is invalid given the assumptions and information sources behind the HoQ-and is viewed as a critical limitation on the results of the method which can lead to potentially invalid and/or poor decisions. In this paper this limitation and its implications are explored both experimentally and through simulated application. Design/methodology/approach-The approach taken in this research is to first study the HoQ through a "digital experiment" in order to identify the key factors that drive the quantitative results within the tool. Based on the results of the experiment, an example HoQ for a hair dryer is used to empirically study the resulting dangers of the quantitative information which results from the HoQ. Findings-Through this research study of the HoQ, it is determined that while the tool offers conceptual support to the design process, the quantitative information that results is largely invalid. Research implications/limitations-For the research community the results in this paper create motivation for continued improvement of the HoQ tool from a conceptual, qualitative design aid to a sound quantitative tool. The results indicate exactly where the methodology must be improved. Originality/value-For users of QFD, specifically the HoQ, the results of this research provide evidence to the limitations of the tool in providing quantitative information for design.
Introduced nearly 25 years ago, the paradigm of mass customization (MC) has largely not lived up to its promise. Despite great strides in information technology, engineering design practice, and manufacturing production, the necessary process innovations that can produce products and systems with sufficient customization and economic efficiency have yet to be found in wide application. In this paper, the state-of-the-art in MC is explored in order to answer the question of “why not?” and to highlight areas for specific research in the MC paradigm. To establish perspective for this work, we consider MC to be a product development approach which allows for the production of goods — after a customer places an order — which minimize the tradeoff between the ideal product and the available product by fulfilling the needs and preferences of individuals functionally, emotionally and anthropologically. Results of this research were generated by reviewing 88 papers from various journals that span three domains of interest (marketing, engineering, and distribution) and explore proposed methodologies, specific information inputs and outputs, proposed metrics, and barriers toward the implementation of MC. Qualitatively, we show that the lack of MC in application is due to two factors: 1) a lack of marketing tools capable of capturing individual needs that can be mapped to the technical space; and 2) a lack of information relation mechanisms that connect the domains of marketing, engineering, and distribution. In the end it is our belief that MC is realizable and that eventually it will emerge as a dominant paradigm in the design and delivery of products and systems. However, pursuing the opportunities for research presented in this work will hopefully speed this emergence.
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