1. Evaluation of critical success determinants to the implementation of additive manufacturing technology in the spare parts supply chain: a grey causal modelling approach.
- Author
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Singh, Shubhendu, Misra, Subhas, and Singh, Gaurvendra
- Subjects
SPARE parts ,CAUSAL models ,SUPPLY chains ,SUPPLY chain management ,CRITICAL success factor ,REVERSE logistics - Abstract
Purpose: Additive Manufacturing technology (AMT) is swiftly gaining prominence to induce automation and innovation in manufacturing systems. It holds immense potential to change supply chain dynamics by providing the possibility of printing objects on demand. This study thus formulates and analyzes the framework to incorporate AMT to handle the spare parts supply chain management (SPSCM) in capital-intensive industries by identifying and assessing the critical success factors (CSFs). Design/methodology/approach: Assessment of the CSFs is performed using the novel Grey Causal Modeling method (GCM) with the objective of making SPSCM resilient and efficient. GCM conducts causal analysis by taking into consideration cause, effects, the objectives, and the situations. Findings: Findings indicate that; Logistics Lead Time (SD4), Time to manufacture (SD3), Management Support (SD11), and Risk Management (SD20) are the most prominent causal factor having a maximum impact when incorporating AMT in SPSCM. The results also reveal that the performance of manufacturing organizations that adopt AMT is substantially influenced by internal and external factors such as Management Support (SD11) and Government Regulations (SD16). Research limitations/implications: This research provides valuable information for getting the global spare parts supply chain equipped for the post-COVID age, where digital technologies such as AMT will be fundamental for bolstering supply chain resilience and efficiency. Originality/value: This research proposes a framework for performance assessment when incorporating AMT in SPSCM. Study also demonstrates methodological application of novel Grey Causal Modelling technique using a real case in a spare parts manufacturing industry in India. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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