A general paradigm for routine design—theory and implementation

Abstract

The concept of discretization of a design space is used to make initial selection of prior designs using specification matching, and to direct redesign with evaluation and iteration. A general paradigm for routine design has been developed and implemented in a system called IDS (Initial Design Selection.) For a given design domain, certain characteristics are identified that allow all specifications and models (which represent prior designs) in that design domain to be described in terms of their values or intervals that these values may lie in. These characteristics are seen as dimensions of a design space discretized into a finite number of partitions. Each partition is represented by a model, thought of as occupying its center. Each such model is associated with a deep model, which contains sufficient information for the modeled device, process, or system to be realized. Despite the fact that the models inhabiting the space are shallow, the paradigm comprises a relatively rich mathematical structure. This paper describes in detail a computational methodology to implement this domain-independent paradigm. The IDS paradigm presents a convenient and structured framework for acquiring and representing domain knowledge. This paper also briefly discusses an enhanced version of the system, which attempts iterative redesign directed by the particular mismatch between a specification and an otherwise promising model. To date, this methodology has been applied in a variety of design domains, including mechanism design, hydraulic component selection, assembly methods, and non-destructive testing methods.

Modelling concept design evaluation

“…In most engineering design domains, the number of Dch's is large and needs to be reduced to allow manageable searching through the design space for suitable models. One approach, as used by Esterline and Kota (1992) in their IDS system, is first to identify certain critical char-acteristics that must be satisfied if the design is to be acceptable. The critical characteristics can then be eliminated from further consideration.…”

“…DCA uses the theory of fuzzy measure to quantify the compatibility evaluation, termed the match index (MI), of the design with the requirements within the design specification. Esterline and Kota (1992) use the concept of discretization of design space to make an initial design selection (IDS) of prior designs using specification matching to direct redesign with evaluation and iteration.…”

General Framework for Configuration Design: Part 1— Methodology

“…A generic device, such as a hydraulic cylinder, may be characterized by the stroke length (10.0, 14.0), representing all catalogued hydraulic cylinders with stroke length from as small as 10.0 ern to as large as 14.0 cm. By matching the specifications and model intervals, we establish an index, called the goodness-of-match index [24] Frameworkfor Configuration Design: Part 1 285 reflecting the feasibility of a particular generic device in fulfilling a particular function in the context of given constraints. The matching procedure is recursively applied during the component selection stage to select the most appropriate component.…”

General Framework for Configuration Design: Part 2— Application to Hydraulic Systems Configuration

“…Therefore, the details of the parameter design are not significant, so are omitted. A detailed discussion on computational networks for parameter design is given by Esterline and Kota [3].…”

“…Weights are used to indicate the designer's preferences. See Esterline and Kota[3] for details on the computation network. Each functional module in the network is eventually mapped to a specific catalog component.Fig.…”