Abstract

Product and system designers face many challenges in the modern world. Designing products that will be subject to emerging or uncertain requirements can be one of the most significant of these challenges. A major risk associated with emerging or uncertain requirements is premature obsolescence. Large-scale, complex engineered systems, such as, aircraft, spacecraft, large seagoing vessels, communication and power systems are especially susceptible to this issue. However, this challenge is not limited to only large-scale complex systems. Even relatively simple products can suffer from premature obsolescence and even failure to be initially accepted, due to inadequately understood or changing requirements. One approach to mitigating this challenge is to increase the product's flexibility and adaptability, thus enabling it to evolve or adapt to meet unforeseen requirements. The flexibility of a product to adapt to new or changing requirements has been shown to increase acceptance rates and reduce the risk of premature obsolescence. Methodologies to accomplish this include product family platform design, transformable product design, reconfigurable product design and modular product design. The literature presents several techniques to aid designers, such as design structure matrices (DSM), change propagation analysis, change modes and effects analysis (CMEA), metrics and guides. These techniques address the challenge by seeking to understand and manage the relationships and interfaces between functions or components within the design. While these are excellent techniques, they do not provide quantifiable functions or models for the design alternatives. Quantifiable functions and models are of value to designers, because they enable numerical design aids. Numerical optimization techniques have been shown to aid designers in efficiently determining appropriate design parameters. This dissertation identifies, analyzes and presents new techniques, which are based on designed-in excess capabilities and to which numerical optimization can be directly applied. There are four parts to the dissertation. In the first part, a technique is presented for determining the relative value of a product, which has been over-designed (excess capabilities) to address future requirements versus redesigning the product once the future requirements emerge. It is shown that in many cases the over-design approach provides greater benefit. In the second part, a numerical metric for the evolvability of a product based on excess capability is presented. An important result of this metric is that the evolvability of a product and the usability of each excess capability can be numerically determined. The third part presents a technique to design products for increased adaptability, based on optimally designed-in excess. Deterministic, and non-deterministic conditions are included in this optimization. Once a numerical model of the design is available the issue of uncertain requirements can be mitigated by directly focusing on the uncertainties. In the fourth part, a technique employing optimization and sensitivity analysis is used to systematically and efficiently guide the designer toward minimizing or eliminating the most critical uncertainties.

Degree

PhD

College and Department

Ira A. Fulton College of Engineering and Technology; Mechanical Engineering

Rights

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