Prioritizing Competitive Capabilities in Additive Manufacturing Systems Using Best-Worst Method

Vishwas Dohale (), Milind Akarte () and Priyanka Verma ()
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Vishwas Dohale: National Institute of Industrial Engineering
Milind Akarte: National Institute of Industrial Engineering
Priyanka Verma: National Institute of Industrial Engineering

A chapter in Advances in Best-Worst Method, 2023, pp 117-128 from Springer

Abstract: Abstract Additive manufacturing systems (AMS) have been realized as one of the cutting-edge technologies that can revolutionize the traditional way of producing goods. It is expected that by deploying AMS, the manufacturing firms can effectively manage the trade-off between volume-variety and cost-flexibility. This study is developed at the outset to explore the level of competitive capabilities, namely cost, quality, delivery speed and reliability, flexibility, performance, and innovativeness, achieved by deploying AMS through an operations management lens. In this work, the Best-Worst method (BWM) is used to compute the weights of the competitive capabilities within AMS using the opinions of five informed respondents from AM domain. The competitive capabilities are further prioritized based on their aggregated weights. The results demonstrated that flexibility and innovativeness are the most critical competitive capabilities that can be retained through AMS implementation. Contrary, when employing AMS, delivery speed and cost are the least achieved capabilities over which firms need to make a possible compromise. This study will benefit academicians and readers in understanding the core competencies of AMS. Based on the desired competitive capabilities, a particular firm can align its production facilities in line with AMS.

Keywords: Additive manufacturing system; Manufacturing strategy; Competitive capabilities; Best-Worst Method (BWM); Prioritization (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-24816-0_10

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