Research in Engineering Design

Redesigning a product family entails carefully balancing the trade-offs between commonality and differentiation that are governed by the underlying platform architecture. Numerous metrics for commonality and variety exist to support product family and product platform design; however, rarely are they used in concert to help redesign platforms and families of products effectively. In this paper, we introduce an integrated approach that uses multiple product family metrics to establish an effective platform redesign strategy. Specifically, we present a detailed procedure to integrate the generational variety index, product line commonality index, and design structure matrix to prioritize components for redesign based on variety and commonality needs in a family of products. While all three of these tools exist in the literature and have been used extensively to support product family design, the novelty in our work lies in their integration to establish a redesign strategy for platform architectures that achieves a better balance between the commonality and variety within a product family. To demonstrate the proposed approach, case studies involving two generations of wireless computer mice and two families of dishwashers are presented. Ongoing and future work is also discussed.

The competition in global market continues to inspire companies to consider all aspects of design including human psychology to develop reliable, safe, maintainable, and novel systems (or products). An understanding of psychology of human values of the design personnel working in a team environment, in particular, is needed to give a boost to this effort. It is experienced that the inherent human values of the team members will reflect the characteristics of the product and inspire the entire design team for delivering a competitive product. This is termed as a team inspired approach. This paper presents a theoretical framework with an objective of development of systems from maintainability point of view, in general, and human psychology, in particular. For this, various Human Values Attributes affecting the performance of design personnel are identified and discussed. A procedure based on digraph and matrix method is applied to develop evaluation of Human Values Index of design team personnel. An example is illustrated to compare two design teams. The developed procedure is useful for design and development of maintainable systems and in analysing effectiveness of the personnel or teams (or organizations) for a given task and making comparisons among them.

A method for machine interpretation of architectural (or other) schematic drawings is presented. The central problem is to build an efficient drawing parser (i.e., a program that identifies the semantic entities, characteristics, and relationships that are represented in the drawing). The parser is built from specifications of the drawing grammar and an underlying spatial model. The grammar describes what to look for, and the spatial model enables the parser to find it quickly. Coupled with existing optical recognition technology, this technique enables the use of drawings directly as: (1) a database to drive various Architecture-Engineering-Construction (AEC) applications; (2) a communication protocol to integrate CAD systems; (3) a traditional user interface.

When designing new devices, engineers seldomly start their design from scratch. Instead, they redesign or compose existing ones. Finding candidate devices based on their properties is thus an essential design subtask. To be effective, future intelligent computer-aided design (CAD) systems must be able to compare and evaluate existing devices. Due to the large number of known devices, such systems must create and maintain a devices' knowledge base, indexed by the properties of the devices. This paper presents a new method to compare and classify mechanical devices according to their kinematic properties. Mechanism comparison determines when two mechanisms are kinematically equivalent. Mechanism classification organizes classes of equivalent mechanisms for efficient retrieval. Both tasks require describing mechanisms' behaviors from various perspectives and at multiple levels of abstraction. To produce such descriptions, we develop a set of operators to simplify and abstract kinematic descriptions derived from configuration spaces. Simplification operators ignore irrelevant information by incorporating constraints and assumptions. Abstraction operators ignore detail by defining multiple levels of resolution. The resulting hierarchy supports the design process throughout its evolution, from the conceptual to the detailed phase. It provides an explicit link between behavioral specifications and part geometry.

Designers routinely rank alternatives in a variety of settings using a staple of comparison, the pairwise comparison. In recent years questions have been raised about the use of such comparisons as a means of calculating and aggregating meaningful preference or choice data. Results on voting have been used to argue that the positional procedure known as the Borda count is the best pairwise voting procedure, or at least the only one that is not subject to a number of demonstrable problems. We show here that pairwise comparison charts (PCC) provide results that are identical to those obtained by the Borda count, and that the PCC is thus not subject to the arguments used against non-Borda count methods. Arrow's impossibility theorem has also been invoked to cast doubt upon any pairwise procedure, including the Borda count. We discuss the relevance of the Arrow property that is lost in the Borda count, the independence of irrelevant alternatives (IIA). While the theoretical consequences of IIA are devastating, it is not clear that the same is true of its practical consequences. Examples are presented to illustrate some primary objections to pairwise methods.

This paper evaluates the Pugh Controlled Convergence method and its relationship to recent developments in design theory. Computer executable models are proposed simulating a team of people involved in iterated cycles of evaluation, ideation, and investigation. The models suggest that: (1) convergence of the set of design concepts is facilitated by the selection of a strong datum concept; (2) iterated use of an evaluation matrix can facilitate convergence of expert opinion, especially if used to plan investigations conducted between matrix runs; and (3) ideation stimulated by the Pugh matrices can provide large benefits both by improving the set of alternatives and by facilitating convergence. As a basis of comparison, alternatives to Pugh’s methods were assessed such as using a single summary criterion or using a Borda count. These models suggest that Pugh’s method, under a substantial range of assumptions, results in better design outcomes than those from these alternative procedures.

In recent years, the works on design theory (and particularly the works of the design theory SIG of the design society) have contributed to reconstruct the science of design, comparable in its structure, foundations and impact to decision theory, optimization or game theory in their time. These works have reconstructed historical roots and the evolution of design theory, conceptualized the field at a high level of generality and uncovered theoretical foundations, in particular the logic of generativity, the “design-oriented” structures of knowledge, and the logic of design spaces. These results give the academic field of engineering design an ecology of scientific objects and models, which allows for expanding the scope of engineering education and design courses. They have contributed to a paradigm shift in the organization of R&D departments, supporting the development of new methods and processes in innovation departments, and to establishing new models for development projects. Emerging from the field of engineering design, design theory development has now a growing impact in many disciplines and academic communities. The research community may play a significant role in addressing contemporary challenges if it brings the insights and applicability of design theory to open new ways of thinking in the developing and developed world.

Complex systems are challenging to understand and design, and even more so when considering nanoscale reasoning. This paper introduces a synergistic cognitive and agent-based methodology for deriving effective strategies for human searches in optimization design tasks. The method consists of conducting cognitive studies to determine effective human search approaches, rapidly testing algorithmic variations of human strategies using software agent automation, and finally providing the highly effective agent-refined strategies to humans. The methodology was implemented by developing a graphical user interface (GUI) of myosin biomotors and conducting a baseline cognitive study to determine how users effectively search for optimal biosystem designs. The best human designers typically searched local to their current best solution, utilized univariate searches, and may have learned and applied parametric knowledge. These trends informed rule-based agent strategies, and testing variations of rules resulted in the discovery of highly effective strategies using initial random searches, univariate searches to learn parameter relationships, and greedy local searches to apply knowledge. The GUI was modified to aid users in implementing two of the highest performing agent strategies in a final cognitive study. These users provided with the agent-refined strategy performed better than users with no provided strategy during the baseline cognitive study. When agents and users were provided myosin domain knowledge prior to searching, convergence on high-quality designs occurred earlier, which suggests that even experts in the domain could benefit from the agent-derived strategies. These findings demonstrate the power of synergistic human- and agent-based approaches, in which cognitive-based findings can reveal strategies that are refined by agents that generate search strategies for greatly improved user performance. The synergistic methodology extends beyond nano-based applications and could generally aid designers in discovering effective decision-making approaches across a broad range of domains.