A computational simulation-based framework for estimating potential product impact during product design

The impact of engineered products is a topic of concern in society. Product impact may fall under the categories of economic, environmental or social impact, with the last category defined as the effect of a product on the day-to-day life of people. Design teams lack sufficient tools to estimate the...

Full description

Bibliographic Details
Main Authors: Christopher S. Mabey, Andrew G. Armstrong, Christopher A. Mattson, John L. Salmon, Nile W. Hatch, Eric C. Dahlin
Format: Article
Language:English
Published: Cambridge University Press 2021-01-01
Series:Design Science
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S2053470121000160/type/journal_article
Description
Summary:The impact of engineered products is a topic of concern in society. Product impact may fall under the categories of economic, environmental or social impact, with the last category defined as the effect of a product on the day-to-day life of people. Design teams lack sufficient tools to estimate the social impact of products, and the combined impacts of economic, environmental and social impacts for the products they are designing. This paper aims to provide a framework for the estimation of product impact during product design. To estimate product impact, models of both the product and society are required. This framework integrates models of the product, scenario, society and impact into an agent-based model to estimate product impact. Although this paper demonstrates the framework using only social impact, the framework can also be applied to economic or environmental impacts individually or all three concurrently. Agent-based modelling has been used previously for product adoption models, but it has not been extended to estimate product impact. Having tools for impact estimation allows for optimising the product design parameters to increase the potential positive impact and reduce potential negative impact.
ISSN:2053-4701