Search results

Every company or manufacturing system is vulnerable to breakdowns. This research aims to analyze the role of Multi-Agent Technology (MAT) in minimizing breakdown probabilities in Manufacturing Industries.

This study formulated a framework of six factors and twenty-eight variables (explored in the literature). A hybrid approach of Multi-Criteria Decision-Making Technique (MCDM) was employed in the framework to prioritize, rank and establish interrelationships between factors and variables grouped under them.

The research findings reveal that the “Manufacturing Process” is the most essential factor, while “Integration Manufacturing with Maintenance” is highly impactful on the other factors to eliminate the flaws that may cause system breakdown. The findings of this study also provide a ranking order for variables to increase the performance of factors that will assist manufacturers in reducing maintenance efforts and enhancing process efficiency.

The ranking order developed in this study may assist manufacturers in reducing maintenance efforts and enhancing process efficiency. From the manufacturer’s perspective, this research presented MAT as a key aspect in dealing with the complexity of manufacturing operations in manufacturing organizations. This research may assist industrial management with insights into how they can lower the probability of breakdown, which will decrease expenditures, boost productivity and enhance overall efficiency.

This study is an original contribution to advancing MAT’s theory and empirical applications in manufacturing organizations to decrease breakdown probability.

This study aims to conceptualize and measure strategic leadership capabilities within research and development (R&D) teams pursuing high-tech innovation at public-funded R&D organizations in India.

A rigorous five-stage multi-method approach defines, conceptualizes and validates the core construct “strategic leadership capabilities for innovation” (SLCI). The first stage correlates the insights generated from theoretical analysis and expert opinions on the importance of leadership for innovation. The second study identifies a three-dimensional factor structure underlying the SLCI construct and the third validates it through a confirmatory factor analysis. Replication provides additional validation.

SLCI emerges as a three-dimensional construct with sub-dimensions: dynamic envisioning, ambidextrous resource utilization and empowering support for innovation.

Conceptualization of the SLCI construct and its measurement through a 15-item scale that has been empirically validated in the public-funded R&D organizations in India.

3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental quality management. This new technology needs a supportive ecosystem, and thus, this paper identifies and models the enablers for adopting 3D printing technology toward a sustainable food supply chain.

The enablers were identified through an extensive literature review and verified by domain experts. The identified enablers were modelled through the hybrid total interpretive structural modelling approach (TISM) and the decision-making trial and evaluation laboratory (DEMATEL) approach.

It emerged that stakeholders need technical know-how about the 3D printing technology, well supported by a legal framework for clear intellectual property rights ownership. Also, the industry players must have focused and clear strategic planning, considering the need for sustainable supply chains. Moreover, required product innovation as per customer needs may enhance the stakeholders' readiness to adopt this technology.

The framework proposed in this research provides managers with a hierarchy and categorization of adoption enablers which will help them adopt 3D food printing technology and improve environmental quality.

This research offers a framework for modelling the enablers for 3D food printing to develop a sustainable food supply chain using the TISM and DEMATEL techniques.