Chelsea C. White

Customer-driven product development through Quality Function Deployment in the U.S. and Japan

Quality Function Deployment is a tool for bringing the voice of the customer into the product development process from conceptual design through to manufacturing. It begins with a matrix that links customer desires to product engineering requirements, along with competitive benchmarking information, and further matrices can be used to ultimately link this to design of the manufacturing system. Unlike other methods originally developed in the U.S. and transferred to Japan, the QFD methodology was born out of Total Quality Control (TQC) activities in Japan during the 1960s and has been transferred to companies in the U.S. This article reports on the results of a 1995 survey of more than 400 companies in the U.S. and Japan using QFD. The research questions investigated in this study were developed both inductively from QFD case studies in the U.S. and Japan and deductively from the literature. The reported results are in part counterintuitive. The U.S. companies reported a higher degree of usage, management support, cross-functional involvement, use of QFD driven data sources, and perceived benefits from using QFD. For the most part, the main uses of QFD in the U.S. were restricted to the first matrix (“House of Quality”) that links customer requirements to product engineering requirements and rarely was this carried forward to later matrices. U.S. companies were more apt to use newly collected customer data sources (e.g., focus groups) and methods for analyzing customer requirements. Japanese companies reported using existing product data (e.g., warranty) and a broader set of matrices to a greater extent. The use of analytical techniques in conjunction with QFD (e.g., simulation, design of experiments, regression, mathematical target setting, and analytic hierarchy process) was not wide spread in either country. U.S. companies were more likely to report benefits of QFD in improving cross-functional integration and better decision-making processes compared to Japanese companies. Possible reasons for these cross-national differences as well as their implications are discussed.

A Survey of solution techniques for the partially observed Markov decision process

We survey several computational procedures for the partially observed Markov decision process (POMDP) that have been developed since the Monahan survey was published in 1982. The POMDP generalizes the standard, completely observed Markov decision process by permitting the possibility that state observations may be noise-corrupted and/or costly. Several computational procedures presented are convergence accelerating variants of, or approximations to, the Smallwood-Sondik algorithm. Finite-memory suboptimal design results are reported, and new research directions involving heuristic search are discussed.

Multiobjective, preference-based search in acyclic OR-graphs☆

We consider the problem of determining a most preferred path from a start node to a goal node set in an acyclic OR-graph, given a multiattribute preference function, a multiobjective reward structure, and heuristic information about this reward structure. We present an algorithm which is shown to terminate with a most preferred path, given an admissible heuristic set. The algorithm illustrates how Artificial Intelligence techniques can be productively employed to solve multiobjective problems.

Application of multiattribute decision analysis to quality function deployment for target setting

In the product design and development process, quality function deployment (QFD) provides a comprehensive, systematic approach to support the design of new products intended to meet or exceed customer expectations. The authors use multiattribute value theory to support new product design and hence to augment a design teams experience and judgment. We introduce the concept of a target set, the set of all value score vectors that are at least as preferred as the value score vectors of any of the given design alternatives. Assuming mutually preferential independence, we characterize the target set and indicate how it can be used to support selecting targets: 1) for the level of customer satisfaction to be attained by the new product, for each customer requirement and 2) for design requirements, presumably based in part on information from engineering competitive assessments. We then use the target set concept to augment the product planning phase of QFD. The concepts are illustrated and evaluated through the retrospective application of the methodology to an actual surgical product (universal converter). Although the analysis was performed retrospectively, without knowledge of the market success of the product and its competitors, the results were consistent with product acceptance and provided valuable insights to the lead engineer.

A descriptive multi-attribute model for reconfigurable machining system selection that examines buyer-supplier relationships

Presents a model of the machining system selection process that is focused on capital intensive, complex machining systems that are intended to provide service over a long time horizon. This model was developed based on interviews with both machine tool suppliers and buyers. The systems considered here increasingly face potentially conflicting demands such as: the ability to be quickly and inexpensively upgraded and reconfigured in order to have quick new product change‐over and ramp‐up time; and high product variety at close to mass production costs. This new “reconfigurability” capability increases the importance of the supplier‐buyer relationship after the machining system has been selected. We also remark that the selection process can serve as the basis for internal consensus and team building within the buyer firm and for enhancing supplier base quality.

A new route optimization algorithm for rapid decision support

We describe a new heuristic search algorithm, Interruptible A (IA), that we have implemented in a real-world decision aid for use of public transit. IA is appropriate for shortest path problems where there is value to a suboptimal path returned quickly. We offer an example in which IA returns an optimal path in single iteration, and another where the algorithm finds a suboptimal path quickly before converging to the optimal path. Two admissibility condition are presented, along with empirical results indicating that IA is effective in both admissible and inadmissible cases.

Question selection for multi-attribute decision-aiding

Abstract A decision-maker (DM), or a group of DMs, must select a most preferred alternative from a finite set of alternatives. Each alternative has a single consequence. There are multiple and conflicting attributes. All value scores are known precisely. However, all that is known about the vector of trade-off weights is that it is a member of a given set, the trade-off weight set. A facilitator can ask questions and use the responses to update the trade-off weight set and hence the set of non-dominated alternatives, i.e., those alternatives that are candidates for being a most preferred alternative. The DM can terminate this process at any point. Termination typically occurs when the non-dominated set contains a sufficiently small number of alternatives. The facilitator’s role is to ask questions that efficiently lead the DM to a most preferred alternative. The objective of this research is to aid the facilitator in selecting the best question to ask next. We model the question-response process as a sequential decision-making problem under uncertainty and develop a dynamic programming-based approach that guarantees a finite, and hence potentially computable, representation of the expected optimal cost-to-go function. An example serves to illustrate the approach.

Road to Transactions on Intelligent Transportation Systems: A Decade's Success

The paper discusses the journal efforts on intelligent transport systems. 2009 marks the end of the first decade of our IEEE Transactions on Intelligent Transportation Systems (T-ITS). Over the past ten years, we have experienced various ups and downs, but we survived, and now, we thrive. In this last issue of the passing decade, the Founding, Past, and Current Editors in Chief would like to join everyone in celebrating the tenth anniversary of this great journal. We would like to take this opportunity to share some ideas and reflections on the past, present, and future of this publication.

An analytical approach to the dynamic topology problem

Currently, it is possible to modify (say, hourly) the topology of a data communications network by adding or deleting network links and/or by increasing or decreasing bandwidth on existing links in response to changing traffic loads and/or projected network conditions. The intent of this paper is to study a Markov decision process (MDP) model of the dynamic topology problem (DTP), the problem of activating and/or deleting links, as a function of the current traffic in the network and of the most recent network topology design. We present a decomposition of this model and structural results for the decomposition. The decomposition and structural results enhance the tractability of procedures for determining optimal link control policies. A numerical example is used to illustrate these results.

Intelligent transportation systems: integrating information technology and the surface transportation system

Transportation of people and goods, enhanced by the processing and transmission of information, has a critical affect on our living standards and our quality of life. In the United States in 1992, transportation services accounted for 17% of the total gross domestic product, 12% of personal consumption expenditure, 10% of total employment, 13% of all capital outlays, and 75% of rubber consumption. Several forces are now affecting how the surface transportation system supports the movement of people and goods. These include increasing congestion, the increasing cost of adding lane miles to the existing road system, the reduction in the use of public transit, the need to support best practices in manufacturing such as just-in-time pickup and delivery, and the application of new information technologies. The intent of this plenary is to present an overview of Intelligent Transportation Systems, its promise, and how it is contributing to the efficiency of the surface transportation system. Particular attention will be focused on the trucking service industry due to the enormous role that this industry plays in the movement of freight and hence in the US economy.