Abstract
Design for Human Safety (DfHS) is an approach to integrate knowledge of human safety in the design process. DfHS is multi-disciplinary in its nature, requiring many kinds of information and knowledge. Number of DfHS studies tried to apply Axiomatic Design (AD) to achieve their aims. The purpose of this paper is to review the literature on application of AD in DfHS in manufacturing systems and to propose a roadmap for future DfHS works. This paper examines the number and type of publications dealing with this context. The review covers papers published between 1990 (when AD was introduced first) and 2017. It is based on a range of combinations of the following keywords: “Axiomatic design” and “safety” or “accident” or “hazard” or risk”. This review has identified 15 research topics that were clustered into three main research groups: (1) application of AD in ergonomic design; (2) application of AD in human-computer interaction; and (3) application of AD in integrating safety systematically in design process. The authors also tried to identify which axiom of AD has been used in these researches.
Highlights
During recent decades, there has been a growing awareness of human safety in the design process
The two axioms of axiomatic design were adapted for ergonomic design purposes
Ergonomic design is defined as mapping from system-human compatibility needs to relevant compatibility requirements
Summary
There has been a growing awareness of human safety in the design process. Its goal is to “establish a scientific basis to improve design activities by providing the designer with a theoretical foundation based on logical and rational thought processes and tools” [4]. It insures an efficient approach fulfilling “what we need” by “How we are going to satisfy the requirements”. This theory consists of four fundamental concepts [4, 5]: 2.1.1 Design as a mapping process According to AD, design is made up of four domains. To produce the product specified in terms of DPs, AD develops a procedure characterized by Process Variables (PVs) in the process domain (Figure 1)
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