Cognitive factors in distributed design

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Abstract

Engineering design is being carried out by distributed design teams in an effort to use expert human resources more efficiently. The support needs of distributed design are reviewed from a cognitive viewpoint using five broad categories: design methodology, collaboration, teamwork, knowledge management and design representation. Web-based implementation of iterative, structured design methodologies allow greater accessibility to tools and methodologies and more consistent interfaces. Collaboration requires successful and efficient sharing of knowledge, negotiation, coordination and management of activities. In distributed environments, organizational factors and decisions that foster teamwork must be mediated by technology. Design intent, rationale and history are important basic types of knowledge that knowledge management systems are required to capture, organize and manipulate to help generate new design knowledge. Efficient methods of representing design artefacts in different forms are needed that allow designers to interact most efficiently as well as support knowledge capture, transformation and collaborative activities.

Introduction

The globalization of manufacturing is based on the principal of making the most efficient use of resources possible for whatever task needs to be done. In product design, this principal means exploiting the knowledge and expertise of all parties involved, including marketing, engineering, design, management, suppliers, production, etc., in the design team, no matter how these parties are distributed geographically and organisationally.

As such, the support needs of distributed design teams have become an important area of research though the field remains in its infancy. The goal of this manuscript is to provide an overview of recent research into the underlying cognitive nature of design, from publications in the fields of cognitive science, design and engineering, and review the impact this has had or could potentially have on supporting the distributed design. To help group related research work, the support needs of distributed design are classified using a number of broad categories: design methodology, collaboration, teamwork, knowledge management and design representation. It is acknowledged that integration is also highly important to distributed design but a review of research into this area has been left to a future survey, though a brief comment is included in the summary.

The impact of recent cognitive research in each of the five broad categories listed earlier is reviewed in the following sections, while Section 7 summarises our findings and suggests courses for future research and implementation.

Section snippets

Design methodology

The design activity transforms available information and knowledge and expertise to construct a mapping from an expressed need to a solution. The transformation has been viewed as an iterative evolution of design from the abstract to concrete. Design problems can vary in type from ill defined to parametric. A broad range of activities may need to be undertaken with the major steps including:

  • needs analysis/problem clarification,

  • information gathering/research,

  • ideation/creative thinking,

Collaboration

Collaboration is an activity where a large task is achieved by a team. Often the task is only achievable when the collective resources are assembled. Contributions to the work are negotiated and mediated through communications and sharing of knowledge. It is worth noting that the boundary between teamwork and collaboration is not well defined. Successful collaboration requires effectiveness in a number of areas:

  • cognitive synchronisation/reconciliation,

  • developing shared meaning,

  • developing shared

Teamwork

The sociological aspect of collaborative design is teamwork. Teamwork is important in maintaining focus and commitment. The development of teams is largely due to organisational factors and decisions, but must be mediated by technology in a distributed environment. Technical aids should be focused on the problems of:

  • ownership and commitment,

  • shared design workspaces,

  • organisation incentives (team spirit, reputation, co-operation),

  • member assumed roles and responsibilities.

Teamwork can make or

Knowledge management

A great deal of knowledge is used and generated in a design. The capture and expression of this knowledge is vital if teams are to be able to use both existing knowledge and generate new knowledge for future activities. There are three basic types of design knowledge that are important:

  • design intent,

  • design rationale,

  • design history.

While design from first principles is always possible and often can result in innovative solutions, the majority of designs are derived from existing designs. One

Design representation

Designs are instantiated in a number of different forms. These forms can consist of different representations of artefacts, protoartefacts, prototypes, process plans, etc. The forms serve as the instantiation of the artefact under design and catalysts for further development and evolution. Representations of the artefact in different domains and at different levels of abstraction and certainty are often needed. Fruchter et al. [38] describe a system for mechatronic design, which provides

Summary

Currently, the computational needs of design activities are well supported through a large variety of commercially available tools and systems. The integration of the tools and systems is increasing through a variety of research and commercial efforts. However, the flexibility to adapt to the range of different design problems and domains is still lacking.

Integration is a highly discussed issue with regards to improving design support systems, let alone collaborative systems. Without

Sherman Y.T. Lang is a native of Victoria, BC, Canada. He obtained BASc, MASc and PhD degrees in systems design engineering from the University of Waterloo. Dr. Lang has held positions with the Laboratory for Biomedical Engineering of the Medical Engineering Section of the Division of Electrical Engineering of the National Research Council of Canada, the Autonomous Systems Laboratory of the Institute for Information Technology of the National Research Council of Canada, and the Department of

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    Sherman Y.T. Lang is a native of Victoria, BC, Canada. He obtained BASc, MASc and PhD degrees in systems design engineering from the University of Waterloo. Dr. Lang has held positions with the Laboratory for Biomedical Engineering of the Medical Engineering Section of the Division of Electrical Engineering of the National Research Council of Canada, the Autonomous Systems Laboratory of the Institute for Information Technology of the National Research Council of Canada, and the Department of Manufacturing Engineering and Engineering Management of the City University of Hong Kong. He is currently with the Integrated Manufacturing Technologies Institute of the National Research Council of Canada. His research interests include mobile robots, autonomous guided vehicles, mechatronic systems, vision and sensor systems, intelligent production systems and integrated design systems.

    John Dickinson is a registered Professional Engineer and received a Bachelor’s in applied science in 1991 from Queen’s University, Kingston, a Master’s of mathematics in 1993 from the University of Waterloo and a Doctorate in mechanical engineering in 1999 from the University of Western Ontario. He has been working as a Research Officer at the Integrated Manufacturing Technologies Institute of the National Research Council of Canada since 1999 and is actively researching in the area of early design optimisation, focussing on building tools to aid in capturing and using design concepts, and perform trade-off analysis and design optimisation.

    Ralph O. Buchal is an Associate Professor in the Department of mechanical and materials engineering at the University of Western Ontario. He received a BASc (1980), MASc (1984) and PhD (1987) from the University of British Columbia. His research interests include collaboration tools for concurrent engineering, computer support for conceptual design, agile manufacturing, engineering education, path planning for automated inspection, and robotics.

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