Sagar Ghuge, Milind Akarte and Rakesh Raut
The study aims to explore the available academic literature on the decision-making frameworks used in additive manufacturing management (AMM).
Abstract
Purpose
The study aims to explore the available academic literature on the decision-making frameworks used in additive manufacturing management (AMM).
Design/methodology/approach
This research formulates a systematic literature review to determine the research trend of the decision-making framework in AMM. Further, the theory, context, characteristics, and methodology (TCCM) framework is used to identify the research gaps and suggest future research directions.
Findings
The systematic literature review (SLR) delves into overarching research themes within decision-making frameworks in AMM. Additionally, it uncovers trends in article publication, geographical distribution, methodologies utilized, and industry applications. This review not only reveals research gaps but also proposes directions for future exploration.
Originality/value
The key novelty of this research lies in revealing the five most contributing themes of decision-making frameworks in AMM, with the highest contributing theme being AM process selection, followed by part selection for AM. This finding enables decision-makers to make informed decisions to address similar problems while exploring AM technology. Moreover, this research introduces an AM part fabrication roadmap inspired by the literature review. Lastly, the paper highlights key research gaps for future research.
Details
Keywords
Devarshi Kapil, Rakesh Raut, Kirti Nayal, Mukesh Kumar and Milind M. Akarte
The study aims to provide a comprehensive review of digital twin (DT) literature and examine how various industrial sectors utilize the potential of DT.
Abstract
Purpose
The study aims to provide a comprehensive review of digital twin (DT) literature and examine how various industrial sectors utilize the potential of DT.
Design/methodology/approach
This study’s systematic literature review (SLR) and bibliometric analysis focus on utilizing DT in the supply chain (SC) and its applications across various industries between 2017 and 2024. The use of DT for information management and risk management in SCM, which have been investigated in many sectors, is the primary focus of this article. The article also examines the various digital technologies used in digital twin literature.
Findings
The following are the main conclusions drawn from the research on digital twins and their implementation: Digital twins have been studied to improve visibility, traceability, resilience, risk identification and assessment, information sharing and decision-making in SC of various sectors. According to the literature review, most research was conducted in the manufacturing industry. Also, the integration of DT with digital technologies (like AI, BD, AI, ML and CPS) in SC has been explored less.
Originality/value
A multisectoral examination has been done to identify any needs or requirements and unknown areas of study and make recommendations for future directions for study on the interface between SC and DT.