Paper
17 November 2005 Impact of design features upon perceived tool usability and safety
Steven F. Wiker, Mun-Su Seol
Author Affiliations +
Proceedings Volume 5999, Intelligent Systems in Design and Manufacturing VI; 59990R (2005) https://doi.org/10.1117/12.631306
Event: Optics East 2005, 2005, Boston, MA, United States
Abstract
While injuries from powered hand tools are caused by a number of factors, this study looks specifically at the impact of the tools design features on perceived tool usability and safety. The tools used in this study are circular saws, power drills and power nailers. Sixty-nine males and thirty-two females completed an anonymous web-based questionnaire that provided orthogonal view photographs of the various tools. Subjects or raters provided: 1) description of the respondents or raters, 2) description of the responses from the raters, and 3) analysis of the interrelationships among respondent ratings of tool safety and usability, physical metrics of the tool, and rater demographic information. The results of the study found that safety and usability were dependent materially upon rater history of use and experience, but not upon training in safety and usability, or quality of design features of the tools (e.g., grip diameters, trigger design, guards, etc.). Thus, positive and negative transfer of prior experience with use of powered hand tools is far more important than any expectancy that may be driven by prior safety and usability training, or from the visual cues that are provided by the engineering design of the tool.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven F. Wiker and Mun-Su Seol "Impact of design features upon perceived tool usability and safety", Proc. SPIE 5999, Intelligent Systems in Design and Manufacturing VI, 59990R (17 November 2005); https://doi.org/10.1117/12.631306
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KEYWORDS
Safety

Injuries

Photography

Visualization

Intelligence systems

Manufacturing

Principal component analysis

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