Differential Entropy As a Measure of Information Content in Axiomatic Design

Abstract

Abstract Axiomatic design theory aims to put the design process on a more scientific footing and is based on two axioms, viz., the independence axiom and the information axiom. Several quantitative measures to determine the degree of independence between functional requirement have been defined in the past and their use illustrated through numerous examples. However, very little work exists on quantifying information content of a design. In this paper, we outline the existing measures of information content and propose a more general quantitative measure. This measure is based on the concept of entropy from information theory. The case of discrete as well as differential entropy is examined in the context of axiomatic design. Differential entropy is proposed as a measure of information content. A case study is presented which demonstrates and compares the use of quantitative measures of information content in a design. It is shown that differential entropy offers a more general measure of information content in a design than Sun’s information measure or Taguchi’s signal-to-noise ratio and, therefore, may serve as a decision criterion in engineering design.