Kemper Lewis

Collaborative, Sequential, and Isolated Decisions in Design

The Massachusetts Institute of Technology (MIT) Commission on Industrial Productivity, in their report Made in America, found that six recurring weaknesses were hampering American manufacturing industries. The two weaknesses most relevant to product development were 1) technological weakness in development and production, and 2) failures in cooperation. The remedies to these weaknesses are considered the essential twin pillars of CE: 1) improved development process, and 2) closer cooperation. In the MIT report, it is recognized that total cooperation among teams in a CE environment is rare in American industry, while the majority of the design research in mathematically modeling CE has assumed total cooperation. In this paper, we present mathematical constructs, based on game theoretic principles, to model degrees of collaboration characterized by approximate cooperation, sequential decision making and isolation. The design of a pressure vessel and a passenger aircraft are included as illustrative examples.

A Comprehensive Robust Design Approach for Decision Trade-Offs in Complex Systems Design

In this paper we introduce a technique to reduce the effects of uncertainty and incorporate flexibility in the design of complex engineering systems involving multiple decisionmakers. We focus on the uncertainty that is created when a disciplinary designer or design team must try to predict or model the behavior of other disciplinary subsystems. The design of a complex system is performed by many different designers and design teams, each of which may only have control over a portion of the total set of system design variables. Modeling the interaction among these decisionmakers and reducing the effect caused by lack of global control by any one designer is the focus of this paper. We use concepts from robust design to reduce the effects of decisions made during the design of one subsystem on the performance of the rest of the system. Thus, in a situation where the cost of uncertainty is high, these tools can be used to increase the robustness, or independence, of the subsystems, enabling designers to make more effective decisions. This approach includes uncertainty caused by control factor variation (Type II robust design) and uncertainty caused by unknown nonlocal design information (Type I robust design). To demonstrate the usefulness of this approach, we consider a case study involving the design of a passenger aircraft.

Modeling Interactions in Multidisciplinary Design: A Game Theoretic Approach

The development, implementation, and application of approaches to modeling the interactions in multidisciplinary design is illustrated. Given that the design of complex systems involves multiple disciplinary design teams and their associated analysis and synthesis tools, the task is to model the real interactions among the designers and their tools in order to predict the resulting design. Our approach to this problem is to abstract the interactions in multidisciplinary design as a sequence of games among a set of players, which are embodied by the design teams and their computer-based tools. The developments are applied to a subsonic passenger aircraft design case study to illustrate the rich insights and results that can be generated by exercising different realistic protocols between disciplinary players in modern design processes.

Robust Design Approach for Achieving Flexibility in Multidisciplinary Design

The interdisciplinary nature of complex systems design presents challenges associated with computational burdens and organizational barriers as these issues cannot be resolved with faster computers and more efficient optimization algorithms. There is a need to develop design methods that could model different degrees of collaboration and help to resolve the conflicts between different disciplines. In this paper, an approach to providing flexibility in resolving the conflicts between the interests of multiple disciplines is proposed. We propose to integrate the robust design concept into the existing game protocol, in particular the Stackelberg leader/follower protocol. Specifically, the solution for the design parameters which involve the coupled information between multiple players (disciplines) are developed as a range of solutions rather than a single point solution. This additional flexibility provides more freedom to the discipline that takes the role of follower while the performance of the discipline that takes leaders role is stable within a tolerable range. The method is demonstrated by a passenger aircraft design problem. NOMENCLATURE

Flexible and reconfigurable systems: Nomenclature and review

The demands on today’s products have become increasingly complex as customers expect enhanced performance across a variety of diverse and changing system operating conditions. Reconfigurable systems are capable of undergoing changes in order to meet new objectives, function effectively in varying operating environments, and deliver value in dynamic market conditions. Research in the design of such responsive and changeable systems, however, currently faces impediments in effective and clear discourse due to ambiguity in terminology. Definitions of the terms flexibility and reconfigurability, two related concepts in reconfigurable system design, are explored based on their original lexical meanings and current understanding in design literature. Design techniques that incorporate flexibility both in the design (form) and performance (function) space are presented. Based upon this literature survey, a classification scheme for flexibility is proposed, and its application to reconfigurable system design is explored. This paper also presents recent methodologies for reconfigurable system design and poses important research questions that remain to be investigated.

A framework for flexible systems and its implementation in multiattribute decision making

In this paper, we present a framework for the concept of flexibility in complex system design. This is one of the first of many steps toward developing new design methods for designers that will aid them in 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.

VISUALIZATION OF MULTIDIMENSIONAL DESIGN AND OPTIMIZATION DATA USING CLOUD VISUALIZATION

As our ability to generate more and more data for increasingly large engineering models improves, the need for methods for managing that data becomes greater. Information management from a decision-making perspective involves being able to capture and represent significant information to a designer so that they can make effective and efficient decisions. However, most visualization techniques used in engineering, such as graphs and charts, are limited to twodimensional representations and at most three-dimensional representations. In this paper, we present a new visualization technique to capture and represent engineering information in a multidimensional context. The new technique, Cloud Visualization, is based upon representing sets of points as clouds in both the design and performance spaces. The technique is applicable to both single and multiobjective optimization problems and the relevant issues with each type of problem are discussed. A multiobjective case study is presented to demonstrate the application and usefulness of the Cloud Visualization techniques. 1 Motivation

A decision support framework for flexible system design

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.

Effective Development of Reconfigurable Systems Using Linear State-Feedback Control

As the complexity of system design has substantially increased, so, too, has the need for incorporating tradeoffs into the design process. When such tradeoffs are incorporated, the optimal system performance of each objective is sacrificed to increase the overall range of the system’s functionality. Reconfigurable systems have been defined as systems designed to maintain a high level of performance through real-time change in their configuration when operating conditions or requirements change in a predictable or unpredictable way. When effectively applied, these reconfigurable systems have the ability to achieve the optimal performance for all system objectives, while also meeting the different constraints of each objective. A method of designing effective reconfigurable systems is presented that focuses on determining how the design variables of a system change, as well as investigating the stability of a reconfigurable system through the application of a state-feedback controller. This method is then applied to a study involving the design of a reconfigurable Formula One race car traversing a predefined racetrack where the design variables change values to achieve maximum performance.

THE OTHER SIDE OF MULTIDISCIPLINARY DESIGN OPTIMIZATION: ACCOMODATING A MULTIOBJECTIVE, UNCERTAIN AND NON-DETERMINISTIC WORLD

The evolution of multidisciplinary design optimization (MDO) over the past several years has been one of rapid expansion and development. In this paper, the evolution of MDO as a field is investigated as well as the evolution of its individual linguistic components: multidisciplinary, design and optimizaiion. The theory and application of each component have indeed evolved on their own, but the true net gain for MDO is how these piecewise evolutions coalesce to form the basis for MDO, present and future. Originating in structural applications, MDO technology has also branched out into diverse fields and applications arenas. The evolution and diversification of MDO as a discipline is explored but details are left to the references cited.