An adaptability index system for product development

Author:

Agostinho Oswaldo Luiz1,da Silva Iris Bento2

Affiliation:

1. Department of Manufacturing Engineering and Materials, School of Mechanical Engineering, University of Campinas, Campinas, Brazil

2. Department of Mechanical Engineering, School of Engineering of Sao Carlos, University of Sao Paulo, Sao Carlos, Brazil

Abstract

This study proposes an adaptability index system for product development to enhance engineering system management. The index system takes into account the need to reduce the time required to market new products. The adaptability index is defined by the relationship between the time to develop a current product and the time to develop a subsequent (next) one, so that the recommended index will be useful when a new product with shorter execution times than those of the previous one is introduced into the product design and manufacturing process. Implementing an adaptability system’s parameters are derived from responsiveness, competitiveness, engineering, and marketing activities as reflected in adaptability indices. The study’s methodology is case study through questionnaires, interviews, and records. The authors recommend increasing adaptability by reducing complexity through computer-integrated manufacturing, standardization, and others methodologies. The significant outcome based on the case study is the assessment that is enabled by the proposed adaptability index. This index will guide engineering companies in the selection of the most relevant development processes, protocols, production tools, and procedures aimed at reducing the time-to-market required to generate new products, thus allowing it to meet market demand, increase product diversification, and reduce product lifetimes.

Publisher

SAGE Publications

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Failure prognosis of the components with unlike degradation trends: A data-driven approach;Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability;2022-08-19

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