The manufacturing sector is a fast-growing sector demanded by the increasing population. The adoption of information technology is a boon in the manufacturing industry. The industrial transformation from the third generation to the fourth generation has significantly impacted sustainable development. On account of this, different sectors are adopting industry 4.0 technologies to smooth their process flows. The industry 4.0 technologies implementation in the manufacturing sector will not only enhance its productivity, but also lead to sustainable growth. In this regard, this study intended to examine the challenges associated with adopting industry 4.0 technologies in the manufacturing sector. A thorough literature review was carried out from the Scopus database, and a list of ten important challenges was shortlisted for analysis. The article uses interpretive structural modeling to analyse the challenges of industry 4.0 and make a structural model between identified challenges. “Lack of employee skills” and “lack of technological infrastructure” were identified as the topmost challenges in adopting industry 4.0 technologies in the manufacturing sector. This study will enable decision makers, policymakers, and industrial practitioners to effectively analyse the challenges of I4.0 for its smooth adoption in the manufacturing sector. Practical implications of the study and future research directions were also highlighted in the article.

The manufacturing sector has undergone significant growth due to the integration of technologies from the Fourth Industrial Revolution. Industry 4.0 has revolutionized industrial operations, leading to increased utilization of smart and automated systems in manufacturing. Among these technologies is additive manufacturing (AM), which has been widely adopted in various industries to enhance new product development with minimal time constraints. This research aimed to identify and analyze the potential enablers of AM that support its adoption in the manufacturing sector. This study identified 15 enablers through a literature review, and they were analyzed using a grey decision-making trial and evaluation laboratory (DEMATEL)-based multicriteria decision-making technique. The results were used to develop a causal diagram that depicts the enablers in cause and effect groups. This study provides insights that will help manufacturing firms adopt AM by identifying its enablers and benefits. Overall, this study is significant as it contributes to a deeper understanding of AM technology and its potential enablers, thus facilitating its adoption in the manufacturing sector.

To survive in highly competitive markets, industries focus on enhancing product quality and customer satisfaction. One specific iteration of this approach sees industries striving to optimize processes to improve product quality while generating minimum waste. This has encouraged companies to begin adopting management practices such as lean six sigma (LSS) and kaizen alongside their implementation of digital technologies of automating processing. This study aims to identify and analyze the barriers to integrating LSS practices with Industry 4.0 technologies for small and medium enterprises. Upon shortlisting fifteen barriers from an exhaustive literature review, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is used to analyze those shortlisted barriers and establish causal relations between barriers and outcomes. The findings identify the lack of available infrastructure, lack of training on LSS, and lack of consultants in the field as the most dominant barriers in the cause group. Furthermore, the influence map of barriers produced demonstrates the relationship between cause-and-effect barriers. This study’s findings will ensure that small and medium enterprises formulate business strategies that mitigate the barriers to integrating LSS with Industry 4.0. This study offers insights into overcoming the identified challenges by proposing strategies to enhance product quality and the accuracy of enterprise decision-making, thereby facilitating a successful integration and fostering sustainable growth in SMEs.

In recent years, unquestionable warnings like the negative effects of CO₂ emissions, the necessity of utilizing sustainable energy sources, and the rising demand for municipal electrification have been issued. Therefore, users are encouraged to provide off-grid and sustainable energy systems for their own homes and businesses, especially if they are located rurally and far from grids. Hence, this study aims to design an off-grid hybrid energy system, in order to minimize both the baseline cost of energy and the net current expenditure in the desired system. To construct such a system, wind generators (WG), photovoltaic arrays (PV), battery banks, and bi-directional converters are considered in the real case of a supermarket with a 20-year lifespan in Malmö, Sweden. Some significant assumptions, such as the usage of renewable energy resources only, electricity production close to the business location, and a maximum allowance of 0.1% unmet are incorporated. To optimize the considered problem, a particle swarm optimization (PSO) approach as developed to provide the load requirements and establish the number of WGs, PVs, and other equipment. Moreover, to verify the obtained results, the developed system was simulated using HOMER Pro software, and the results are compared and discussed. The results indicated that the designed hybrid energy system is able to perform completely off-grid, while satisfying 99.9% of the yearly electricity demand. The best results obtained by the proposed PSO offered 160, 5, and 350 PVs, WGs, and batteries, respectively, while the best solution found by the simulation method was the use of 384 PVs, 5 WGs, and 189 batteries for the considered off-grid system. This study contributes to decentralized local electrification by utilizing renewable energy sources that have the potential to revolutionize green energy solutions.

Corporate sustainability is one of the most challenging issues in superior organizations, and is always one of the main concerns of top managers. The importance of quality management in organizations—especially as total quality management—is considered to be one of the most important indicators of sustainability. We cannot achieve sustainability and its important sub-parameters—including economic and social sustainability—by merely employing the value of knowledge creation and knowledge sharing, without also focusing on customers, leadership, and process management. We designed appropriate questionnaires to test this premise, and then distributed and collected them from various reputable pharmaceutical companies in Turkey. We recorded the opinions of managers, supervisors, and deputies of different departments at various organizational levels. To analyze the data, SPSS software—one of the well-known applications in this field—was used. The new regular economy introduces new requirements for newly built public universities or pharmaceutical companies; therefore, their transformation and development are imminent. For example, colleges should comply with the new requirements of economic and social transformation for higher education, innovate their talent training models, and cultivate higher ideological standards and morality while instilling strong practical ability in their graduates to serve society. The results of this study not only illustrate the positive effects of total quality management on firms’ sustainability, but also validate knowledge management and its sub-variables, including knowledge creation and sharing. In addition, they confirm the mediating role of sub-variables, including knowledge creation and knowledge sharing in companies, influencing the effects of total quality management on the sustainability of companies.

Additive manufacturing (AM) is gaining significant importance, as demand for customized products is increasing nowadays. AM is one of the disruptive technologies of Industry 4.0, which can reduce waste generation, enabling sustainability. The adoption of sustainable practices in the manufacturing sector is due to the need of the current scenario to minimize harmful emissions and for human wellbeing. In this regard, AM technologies are integrated with sustainable manufacturing concepts to contribute toward sustainable AM (SAM), with various benefits from the design, manufacturing, use, and EoL perspectives. Still, many sustainability issues are associated with AM processes, namely limited speed and the uncertain performance of fabricated parts. From this viewpoint, it is essential to analyze the challenges associated with adopting SAM practices. This article presents identification and analysis of the potential challenges associated with adopting SAM practices. Fifteen SAM challenges have been identified from the literature survey and analyzed using the “Gray Technique for Order of Preference by Similarity to Ideal Solution” (G-TOPSIS) approach. The priority order of the challenges has been identified. The study identified that “training towards SAM benefits” and “limited materials recycling potential” were the significant challenges in adopting SAM practices in the manufacturing sector. The present study will help industry practitioners, decision makers, and researchers effectively analyze the challenges associated with SAM for its effective implementation. Researchers can utilize the findings of the study for establishing the guidelines for the adoption of SAM.