Investigating additive manufacturing implementation factors using integrated ISM-MICMAC approach. Issue 10 (23rd October 2020)

• Record Type: Journal Article
• Authors: Sonar, Harshad; Khanzode, Vivek; Akarte, Milind
• Is Part Of: Rapid prototyping journal. Volume 26:Issue 10(2020)
• Page Start: 1837
• Page End: 1851
• Publication Date: 2020-10-23
• Subjects: Additive manufacturing -- 3D printing -- Interpretive structural modeling (ISM) -- Implementation factors -- Fuzzy-MICMAC -- Indian manufacturing sector; Engineering design -- Periodicals; 620.004205
• DOI: 10.1108/RPJ-02-2020-0038
• Languages: English
• ISSNs: 1355-2546

Abstract

Abstract : Purpose: The purpose of this paper is to identify various factors influencing additive manufacturing (AM) implementation from operational performance in the Indian manufacturing sector and to establish the hierarchical relationship among them. Design/methodology/approach: The methodology includes three phases, namely, identification of factors through systematic literature review (SLR), interviews with experts to capture industry perspective of AM implementation factors and to develop the hierarchical model and classify it by deriving the interrelationship between the factors using interpretive structural modeling (ISM), followed with the fuzzy Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis. Findings: This research has identified 14 key factors that influence the successful AM implementation in the Indian manufacturing sector. Based on the analysis, top management commitment is an essential factor with high driving power, which exaggerates other factors. Factors, namely, manufacturing flexibility, operational excellence and firm competitiveness are placed at the top level of the model, which indicates that they have less driving power and organizations need to focus on those factors after implementing the bottom-level factors. Research limitations/implications: Additional factors may be considered, which are important for AM implementation from different industry contexts. The variations from different industry contexts and geographical locations can foster the theoretical robustness of the model. Practical implications: The proposed ISM model sets the directions for business managers in planning the operational strategies for addressing AM implementation issues in the Indian manufacturing sector. Also, competitive strategies may be framed by organizations based on the driving and dependence power of AM implementation factors. Originality/value: This paper contributes by identification of AM implementation factors based on in-depth literature review as per SLR methodology and validation of these factors from a variety of industries and developing hierarchical model by integrative ISM-MICMAC approach.