Assessing the Social Impacts of Additive Manufacturing Using Hierarchical Evidential Reasoning Approach

Mahathir Mohammad Bappy (), John Key (), Niamat Ullah Ibne Hossain () and Raed Jaradat ()
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Mahathir Mohammad Bappy: Mississippi State University
John Key: Mississippi State University
Niamat Ullah Ibne Hossain: Mississippi State University
Raed Jaradat: Mississippi State University

Global Journal of Flexible Systems Management, 2022, vol. 23, issue 2, No 3, 220 pages

Abstract: Abstract In recent times, the wider adoption and development of additive manufacturing is prominent in society, but the information regarding the social impacts of this technology is very limited. Due to this, assessing the social impacts of additive manufacturing technology is crucial. The assessment process to determine the social impacts of additive manufacturing information from factors, which are qualitative, incomplete, and uncertain in nature, is observed. The evidential reasoning (ER) approach is a method that can handle subjective, uncertain, and incomplete data. In this paper, the ER approach along with the analytical hierarchy process (AHP) is incorporated for the first time to build up a model for assessing the social impacts of additive manufacturing technology. Based on the experts’ opinion, AHP is applied to the relevant attributes of social impacts to rate and structure the attributes. In this research, the model will be tested using subjective judgmental belief structure data. The data will be aggregated using the ER approach and the attributes will be illustrated in a distributed manner. In the proposed model, Yager’s combination method is applied to compare the output of the D–S approach. The model output is comprised of the average state of social impact from additive manufacturing along with a level of uncertainty for each attribute. The proposed model is now available for utilization by the decision maker to assess the social impacts of additive manufacturing technology. Furthermore, the model could be used as a baseline for planning mitigation of impacts to or improvement to a current state of social impacts.

Keywords: Additive manufacturing; Data fusion; Dempster–Shafer (D–S) theory; Hierarchical evidential reasoning; Risk management; Social impacts assessment; Uncertainty modeling (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s40171-021-00295-5

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