Organizational learning II: Theory, method and practice

A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

Design Prototypes: A Knowledge Representation Schema for Design

House of Quality

During the past 20 years, research in the behavioral sciences has become increasingly sophisticated. New findings concerning the brain and behavior have forced upon us the unpleasant necessity of reexamining our models. Concepts once useful, such as "the unconscious," "regression," and "motivation," no longer serve to adequately encompass the data. Ashby is a representative of this new order of sophistication in research, as he proceeds to investigate the problem of the brain's orderliness. He accepts, as fact, that the nervous system behaves adaptively and assumes that it is, in its essentials, mechanistic. These two data are approached as not irreconcilable. From this point, he proceeds to examine dynamic systems from the standpoint of rigorous scientific —dominantly mathematical—logic until he has evolved a theoretical counterpart of brain functioning. He then builds and experiments with a prototype electronic model, which he names the "Homeostat," and tests various aspects of his theories of

Design for a Brain

Harvard Business Review : 抄録雑誌の概要

Many models of the design and development process have been published over the years, representing it for different purposes and from different points of view. This article contributes an organising framework that clarifies the topology of the literature on these models and thereby relates the main perspectives that have been developed. The main categories of model are introduced. Their contexts, advantages, and limitations are considered through discussion of selected examples. It is demonstrated that the framework integrates coverage of earlier reviews and as such provides a new perspective on the literature. Finally, key characteristics of design and development process models are discussed considering their applications in practice, and opportunities for further research are suggested. Overall, the article should aid researchers in positioning new models and new modelling approaches in relation to state-of-the-art. It may also be of interest to practitioners and educators seeking an overview of developments in this area.

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Process models in design and development

Models of designing

Change propagates, potentially affecting many aspects of a design and requiring much rework to implement. This article introduces a cross-domain approach to decompose a design and identify possible change propagation linkages, complemented by an interactive tool that generates dynamic checklists to assess change impact. The approach considers the information domains of requirements, functions, components, and the detail design process. Laboratory experiments using a vacuum cleaner suggest that cross-domain modelling helps analyse a design to create and capture the information required for change prediction. Further experiments using an electronic product show that this information, coupled with the interactive tool, helps to quickly and consistently assess the impact of a proposed change.

Change impact on a product and its redesign process: a tool for knowledge capture and reuse

Design, development, and other projects inevitably involve iteration. Iteration has positive effects, such as enabling progressive generation of knowledge, enabling concurrency, and integrating necessary changes, but it also increases duration and cost of a project. Managing iteration is thus an important issue in practice, but can be challenging due in part to a profusion of issues and terminologies. This article contributes a literature summary and integrating taxonomy to clarify the different perspectives on iteration. It brings together insights into iteration gained from different research communities (mainly design and product development, alongside selected work in construction management and software project management) and different research approaches (including conceptual frameworks, mathematical and simulation models, case studies and surveys, and protocol studies). By differentiating the issues and providing a uniform terminology, the article maps insights developed to date and may help situate future analyses of iterative processes.

Perspectives on iteration in design and development

This paper examines design iteration and its modelling in the simulation of New Product Development (NPD) processes. A framework comprising six perspectives of iteration is proposed and it is argued that the importance of each perspective depends upon domain-specific factors. Key challenges of modelling iteration in process simulation frameworks such as the Design Structure Matrix are discussed, and we argue that no single model or framework can fully capture the iterative dynamics of an NPD process. To conclude, we propose that consideration of iteration and its representation could help identify the most appropriate modelling framework for a given process and modelling objective, thereby improving the fidelity of design process simulation models and increasing their utility.

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David C. Wynn

Papers

Process models in design and development

Models of designing

Change impact on a product and its redesign process: a tool for knowledge capture and reuse

Perspectives on iteration in design and development

Modelling Iteration in Engineering Design