A data driven decision model for assessing the enablers of quality dimensions: Context of industry 4.0. (November 2021)

• Record Type: Journal Article
• Authors: Kumar, Lalith; Ibne Hossain, Niamat Ullah; Fazio, Steven A.; Awasthi, Anjali; Jaradat, Raed; Babski-Reeves, Kari
• Is Part Of: CIRP journal of manufacturing science and technology. Volume 35(2021)
• Page Start: 896
• Page End: 910
• Publication Date: 2021-11
• Subjects: Quality dimensions -- Best Worst decision-making -- Industry 4.0 -- Polymer industry -- Optimal solution -- Manufacturing; Manufacturing processes -- Periodicals; 670.5
• DOI: 10.1016/j.cirpj.2021.10.003
• Languages: English
• ISSNs: 1755-5817

Abstract

Abstract: Producing high-quality products while sustaining minimal costs is the mandate of all successful manufacturing firms. While quality is at the heart of this model, extant literature neglects an analysis and hierarchical classification of its dimensions, especially for 4.0 polymer industry. To address this gap, this paper identifies an array of quality dimensions critical to 4.0 polymer industry and prioritizes them leveraging a vector based multi-criteria decision-making method named Best-Worst method (BWM). A real polymer film manufacturer located in the state of Mississippi is considered as testing ground, and relevant industry expert opinions are incorporated within the Best-Worst method MCDM framework. Results yield conformance to standards, performance, and durability as the critical dimensions for 4.0 polymer industry managers pursuing waste reduction and strategy-focused quality improvement. Appreciation of this framework may guide practitioners and decision-makers to discern the relative importance of critical quality dimensions and subsequently support developmental areas to overcome challenges, ultimately achieving higher quality polymer products.