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The advent of Internet of Things, cloud computing and advanced computing has endowed smart manufacturing environments with resilience, reconfigurability and intelligence, resulting in the emergence of novel capabilities. These capabilities have significantly reshaped the manufacturing ecosystem, enabling it to effectively navigate uncertainties. The purpose of this study is to assess the operational transformations resulting from the implementation of smart manufacturing, which distinguish it from conventional systems.

A list of qualitative and quantitative smart manufacturing performance metrics (SMPMs) are initially suggested and categorized into strategic, tactical and operational levels. The SMPMs resemble the capabilities of smart manufacturing systems to manage disruptions due to uncertainties. Then, industry and academia experts validate the SMPMs through the utilization of the Delphi method, enabling the ranking of the SMPMs.

The proposition of the SMPMs serves as a metric to assess the digital transformation capabilities of smart manufacturing systems. In addition, the ranking of the proposed SMPMs shows a degree of relevance of the measures in smart manufacturing deployment and managing the disruptions caused due to the COVID-19 pandemic

The findings benefit managers, consultants, policymakers and researchers in making appropriate decisions for deploying and operationalizing smart manufacturing systems by focusing on critical SMPMs.

The research provides a metric to assess the operational transformations during the deployment of smart manufacturing systems. Also, it states the role of the metric in managing the potential disruptions that can alter the performance of the business due to the COVID-19 pandemic.

This study aims to evaluate the sustainable supply chain performance indicators. At a macro level, the identification of the sustainable supply chain management (SSCM) performance indicators is done through exhaustive literature survey and interviews with experts. Furthermore, these indicators are evaluated through a hybrid approach, i.e. total weighted interpretive structural modelling (TWISM) followed by analytic hierarchical process (AHP).

Micro small and medium enterprises (MSMEs) in India are a major contributor to nation’s GDP. However, this sector struggles to comprehend benefits from implementation of SSCM due to a lack of appropriate performance evaluation metrics. The purpose of this paper is to contribute to the body of knowledge in SSCM by proposing and evaluating a set of SSCM performance indicators.

The paper highlights the SSCM performance indicators and concludes that business strategies, implementation planning and impact of stakeholders are the top SSCM performance indicators (SPIs). Therefore, the decision-makers must initially focus on strategic requirements which foster the implementation of SSCM, thereby ensuring profitability for all stakeholders.

Although the proposed framework was validated through a case study on Indian automobile component manufacturing MSMEs, future research would explore the extension of the framework to other industries.

The originality of this study lies in the application of the novel TWISM-AHP tool. Furthermore, the SPIs identified in the study, consider the integration of the triple bottom line from the MSME perspective. The TWISM-AHP analysis will be beneficial for SC decision-makers to enhance the SSCM performance based on the identified indicators and their criticality.

The emerging industrial revolution referred to as Industry 5.0 is focusing on leveraging human creativity with intelligent and autonomous systems to derive user-friendly work environment for the businesses. Industry 5.0 stresses on people centric work ecosystem, zero accident policy and the well-being of labour within the production processes. This approach of Industry 5.0 to obtain human-centric safety solutions through the deployment of digital technologies deduces workplace accidents and costs leading to the development of Safety 4.0. This chapter aims to investigate the opportunities and challenges of Safety 4.0 and its enabling technologies aspiring towards the greater impact on safety management. Further, we have proposed a framework for the role of human centric digital transformations concerning safety in the manufacturing industry propelling Safety 4.0. Concluding, we discuss the implications for managers and practitioners. We found that Safety 4.0 will strengthen industrial safety, and instead of reacting to accidents, the concept evolved towards a preventive and proactive approach for a healthy industrial ecosystem.