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The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.

The market's intense competition, the unpredictability of customer demands and technological advancements are compelling organizations to adopt new approaches, such as agile new product development (ANPD), which enables the introduction of new products to the market in a short span. The existing ANPD literature review articles are lacking in portraying recent developments, potential fields of adoption and the significance of ANPD in organizational development. The primary goal of this article is to investigate emerging aspects, current trends and conduct a meta-analysis using a systematic review of 177 ANPD articles published in peer-reviewed journals between 1998 and 2020.

The articles were categorized based on their year of publication, publishers, journals, authors, countries, universities, most cited articles, etc. The authors attempted to identify top journals, authors, most cited articles, enablers, barriers, performance metrics, etc. in the ANPD domain through the presented study.

The major themes of research articles, gaps and future trends are identified to assist academicians and ANPD practitioners. This study will benefit ANPD professionals by providing them with information on available literature and current ANPD trends.

Through meta-analysis, this study is one of the unique attempt to categorize ANPD articles to identify research gaps and highlight future research trends. A distinguishing feature of the presented study is the identification of active journals, publishers and authors, as well as enablers, barriers and performance metrics.

A reconfigurable manufacturing system (RMS) can provide manufacturing flexibility, meet changing market demands and deliver high performance, among other benefits. However, adoption and performance improvement are critical activities in it. The current study aims to identify the important factors influencing RMS adoption and validate a conceptual model as well as develop a structural model for the identified factors.

An extensive review of RMS articles was conducted to identify the eight factors and 47 sub-factors that are relevant to RMS adoption and performance improvement. For these factors, a conceptual framework was developed as well as research hypotheses were framed. A questionnaire was developed, and 117 responses from national and international domain experts were collected. To validate the developed framework and test the research hypothesis, structural equation modeling was used, with software tools SPSS and AMOS.

The findings support six hypotheses: “advanced technologies,” “quality and safety practice,” “strategy and policy practice,” “organizational practices,” “process management practices,” and “soft computing practices.” All of the supported hypotheses have a positive impact on RMS adoption. However, the two more positive hypotheses, namely, “sustainability practices” and “human resource policies,” were not supported in the analysis, highlighting the need for greater awareness of them in the manufacturing community.

The current study is limited to the 47 identified factors; however, these factors can be further explored and more sub-factors identified, which are not taken into account in this study.

Managers and practitioners can use the current work’s findings to develop effective RMS implementation strategies. The results can also be used to improve the manufacturing system’s performance and identify the source of poor performance.

This paper identifies critical RMS adoption factors and demonstrates an effective structural-based modeling method. This can be used in a variety of fields to assist policymakers and practitioners in selecting and implementing the best manufacturing system.

Uncertainties in manufacturing and changing customer demands force manufacturing industries to adopt new strategies, such as the reconfigurable manufacturing system (RMS). To improve the implementation and performance of RMS, it is necessary to review the available literature and identify future trends in this field. This paper aims to analyze existing literature and to see trends in RMS-related research.

The systematic literature review and analysis of RMS-related research papers from 1999 to 2020 is carried out in this literature. The selected studies are analyzed based on the year of publication, journals, publishers, active authors, research design, countries, enablers, barriers, performance evaluation parameters and universities.

After the analysis of selected RMS-related research papers, the top countries, universities, journals, publishers and authors are identified in this domain. Research themes and trends in research are identified in this study. Besides, it has been noted that there is a need for further research in this domain and for the creation of a generalized framework that can guide researchers and practitioners to increase RMS adoption.

Research insights, guidance and observations from this paper are provided to RMS-related researchers and practitioners. Important research gaps are identified in this study, which can provide direction for future research and trends in RMS research.

The study presented focuses mainly on the method of collecting, organizing, capturing, interpreting and analyzing data to provide more insight into RMS to identify future trends in research.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.

The purpose of this paper is to conduct a systematic bibliometric analysis of reconfigurable manufacturing system (RMS) articles using VOSviewer to identify their research themes and future research trends and investigate their interconnectivity. This paper also aims to identify prominent authors, publishers, organizations, countries and their collaborations in the RMS domain.

In this study, the Scopus database is used to retrieve 454 RMS articles published between 1988 and 2020. These articles are then investigated using VOSviewer to determine their interconnectedness, clusters and citations, as well as to generate a map based on text data. The network visualization diagrams and clusters obtained for documents, authors, sources, organizations and countries are explored to determine the current state and future trends in RMS research.

A bibliometric analysis of selected articles is performed, and current research hotspots in this domain are identified. This work also investigates the current status and future research trends in this domain. The work presented also identifies top researchers, journals, countries and documents in RMS.

This paper can provide academics, researchers and practitioners with additional research insights. At the same time, the research trends identified here can help to direct research and benefit researchers.

The study is the first attempt to review selected documents in the RMS domain using bibliometric analysis tools, and it presents a method for collecting articles, organizing them and analyzing the data.

Sustainable supply chain management (SSCM) is a new subfield of supply chain management. The purpose of this research is to develop a framework for assessing the impact of agile new product development (ANPD) practices on the environmental SSCM performance.

The ANPD practices and SSCM environmental performance metrics (SEPMs) are identified through the literature review. The shortlisted ANPD practices are categorized into five major criteria each with an own set of sub-criteria. A four-level conceptual framework is developed. The weights of these ANPD practices are computed using the Pythagorean fuzzy Analytical Hierarchy Process (PFAHP), and the SEPMs are ranked using the Pythagorean fuzzy Combined Compromise Solution (PFCoCoSo).

The results show that the major criterion “Innovation Aspects” is the most important with a weightage of 0.2368, followed by “Policy Aspects” having 0.2228, “Technology Aspects” with 0.1959, “Organisation Aspects” having 0.1786 and “Executive Aspects” with 0.1658 weightage. The SEPMs “Frequency of NPD” is ranked first with an assessment value (Ki) of 2.5569, followed by “Lead time reduction” and “Number of design iterations” with Ki of 2.4482 and 2.3897, respectively. The research findings show that the ANPD practices like customer need assessment, availability of multidisciplinary team and Industry 4.0 technology usage contribute more to achieving environmental SSCM.

Managers can enhance environmental SSCM performance by adopting the ANPD practices and prioritizing SEPMs. Corporate effectiveness will be increased by the practices that promote SSCM and the use of technological innovations.

This study identified a unique set of 22 performance metrics that quantitatively measure NPD performance as well as environmental SSCM performance by adopting the 31 ANPD practices that were shortlisted. The proposed framework is a novel synthesis of literature from various disciplines such as new product development (NPD), environmental management, SSCM and performance evaluation.

The United Nation's Sustainable Development Goals (SDGs), introduced in 2015, connect several manufacturing strategies and promote sustainable practices in an organization. Manufacturing companies are struggling to meet changing market demands while also addressing social and biological issues. The current study aims to develop a framework that can assist practitioners and managers contribute to the attainment of the SDGs through the adoption of reconfigurable manufacturing system (RMS) practices and Industry 4.0 technologies.

An extensive literature review was carried out to identify RMS-Industry 4.0 practices and their interconnection, as well as their contribution to achieving the SDGs. The stepwise weight assessment ratio analysis (SWARA) method was then used to compute the weights of the selected RMS-Industry 4.0 practices, whereas the weighted aggregated sum product assessment (WASPAS) method was used to prioritize performance metrics. The developed framework's robustness was tested using a sensitivity analysis across five different organizations.

The findings show that advanced technologies practices have the most importance, followed by customization and rapid adjustment of capacity and functionality practices. The sensitivity analysis revealed the robustness of the developed framework as well as its adaptability among the chosen organizations.

This research will assist in the adoption of RMS and includes recent technologies that can help in the attainment of industrial SDGs. Managers will also be able to evaluate RMS in the context of industrial SDGs. Researchers and practitioners can now address the various RMS-Industry 4.0 practices while keeping the social and environmental aspects in mind.

No previous research has investigated the SDGs through the nexus effect of Industry 4.0 and RMS practices.

The COVID-19 pandemic era has severely hampered the economy over the globe. However, the manufacturing organizations across all the countries have struggled heavily, as they were among the least who worked on online mode. The organizations are adopting various innovative quality methodologies to improve their performance. In this regard, they are adopting the Sustainable Lean Six Sigma (SLSS) concept and Industry 4.0 technologies to develop products at a faster rate. The use of Industry 4.0 technologies may reduce material movement and supply chain disruptions with the help of smart intelligent systems. There is a strong synergy between SLSS and Industry 4.0 technologies, resulting in an integrated approach for adoption. This study aims to develop a framework that practitioners can use to adopt Industry 4.0-SLSS practices effectively.

This study portrays 31 Industry 4.0-SLSS practices and 22 performance metrics identified through a literature review to improve the manufacturing supply chain performance. To compute the weights of these practices, the Robust Best–Worst Method (RBWM) is used. The Pythagorean fuzzy combined compromise solution (PF-CoCoSo) method is used to rank performance metrics.

According to the RBWM results, “Process Development Practices (PDP)” are first among the major criteria, followed by “Organizational Management Practices (OMP)” at second, “Technology Adoption Practices (TAP)” at third, “Strategy Management Practices (SMP)” at fourth and “Executive Management Practices (EMP)” at fifth, whereas the PF-CoCoSo method resulted in the performance metric “On time product delivery” ranking first.

The identified practices have the potential to significantly improve the performance of the manufacturing supply chain. Practices that encourage a sustainable manufacturing supply chain and the usage of emerging technology will benefit organizational effectiveness. Managers can assess performance using prioritized performance metrics.

During the COVID-19 pandemic era, this is one of the unique attempts to provide a framework to improve the manufacturing supply chain performance. This study integrates and identifies Industry 4.0-SLSS practices and performance metrics for enhancing overall performance.