This study investigates the integration of Industry 4.0 (I4.0) and Lean Six Sigma (LSS) in automotive manufacturing, focusing on the relationships among Critical Success Factors (CSFs), Challenges (Ch), Workforce Skills (WS), Industry 4.0 Technologies (I4T), and Lean Six Sigma Tools (LSST), and their collective impact on Performance Measures (PM). An empirical survey of automotive manufacturing companies was conducted to test a conceptual model linking CSFs, Ch, WS, I4T, and LSST with performance improvement. Structural Equation Modeling (SEM) was employed to validate the hypothesized relationships. The analysis revealed that CSFs strongly influence I4T (0.510), LSST (0.520), and PM (0.471). LSST and I4T were also significantly improve the performance (0.538 and 0.371), indicating that combined structured process improvements and digital technologies enhanced operations. The findings are consistent with the existing literature (Sony et al. 2021; Vinodh and Wankhede 2021), emphasizing the importance of top management support, transformative leadership style, strategic business alignment, and organizational readiness. This study has the limitation of cross-sectional design and targeting a specific automotive segment. The future work should focus on longitudinal designs, environmental and market influences, and technology maturity to enhance knowledge on digital and lean transformation.

Purpose – This study identifies essential critical success factors (CSFs) for the integration of Industry 4.0 (I4.0) and Circular Economy (CE) concepts in the automotive sector, focusing on successful transitions toward sustainable manufacturing. Design/methodology/approach – A comprehensive literature review and experts' opinions were used to find key CSFs, which were ranked using Fuzzy Best-Worst Method (F-BWM), a robust multi-criteria decision-making approach. Findings – The study quantifies the global influence of these factors, with top CSFs being “Environmental Impact Reduction Technologies, ” “Technology Interoperability ” and “Sustainability Awareness, ” suggesting organizations to adopt more advanced and environmentally friendly technologies. Research limitations/implications – Nevertheless, the work has limitations, as it focuses on a narrow range of CSFs and employs a singular methodology that disregards interdependence. Moreover, the study's results may not be entirely generalized across other industries. Future studies can address the limitation to an extent by adding a proper description in terms of the CSFs list and methodologies like DEMATEL or ANP, considering the interrelationship among factors or exploring across-the-industry comparisons. Practical implications – The findings provide valuable insights for automotive organizations wishing to remain competitive through sustainable manufacturing practices. Originality/value – This research is unique in utilizing the F-BWM approach in the automobile industry, thus bridging the gap from the literature on I4.0.

Agriculture and its supply chain pose significant environmental threats. This study employs Life Cycle Assessment (LCA) to explore the environmental impact of fresh bell pepper production and distribution, comparing Urban and Peri-Urban Agriculture (UPA) with Rural Long-Distance Food Supply Systems (RLDFS). Four UPA scenarios (hydroponics, soil-based greenhouse, open-field conventional, and organic) and two RLDFS scenarios (soil-based greenhouse and open-field conventional) are evaluated using SimaPro, incorporating inputs from UPA practitioners and rural farmers. Results reveal an energy demand range of 0.011 to 5.5 kWh/kg eq., with urban greenhouses exhibiting the lowest consumption and hydroponics the highest due to lighting, ventilation, and irrigation. Hydroponics exhibits a global warming potential of 7.24 kg of CO2 eq·kg−1, with energy demand contributing over 95 %, surpassing other scenarios by 7–25 times, necessitating reduction for sustainability. RLDFS's environmental impact is dominated by transportation (over 70 %), meanwhile other UPA systems are influenced by irrigation, infrastructure, and fertilizers. Despite challenges, UPA-hydroponics proves to be 1.7 to 4.3 times more land-use-efficient than other scenarios, emphasizing its potential. The study highlights the need to address electricity usage in UPA-hydroponics for carbon footprint reduction. Despite challenges, hydroponics could contribute to sustainable food security, and RLDFS does not significantly lag in environmental performance compared to UPA other than Ozone layer depletion criteria attributed to fossil fuel usage in transportation. These insights offer valuable guidance for urban development and policy formulation, promoting sustainable agricultural practices and supporting policies for agronomic and supply chain sustainability.

Purpose: This article aims to focus on implementing Lean Six Sigma (LSS) in steel manufacturing to enhance productivity and quality in the galvanizing process line. In recent trends, manufacturing organizations have expressed strong interest in the LSS since they attempt to enhance its overall operations without imposing significant financial burdens. Design/methodology/approach: This article used lean tools and Six Sigma's DMAIC (Define, Measure, Analyze, Improve and Control) with Yin's case study approach. This study tried to implement the LSS for the steel galvanizing process in order to reduce the number of defects using various LSS tools, including 5S, Value stream map (VSM), Pareto chart, cause and effect diagram, Design of experiments (DoE). Findings: Results revealed a significant reduction in nonvalue-added time in the process, which led to improved productivity and Process cycle efficiency (PCE) attributed to applying lean-Kaizen techniques. By deploying the LSS, the overall PCE improved from 22% to 62%, and lead time was reduced from 1,347 min to 501 min. DoE results showed that the optimum process parameter levels decreased defects per unit steel sheet. Practical implications: This research demonstrated how successful LSS implementation eliminates waste, improves process performance and accomplishes operational distinction in steel manufacturing. Originality/value: Since low-cost/high-effect improvement initiatives have not been adequately presented, further research studies on adopting LSS in manufacturing sectors are needed. The cost-effective method of process improvement can be considered as an innovation.

Emerging technologies integrated Urban and peri-urban agriculture (UPA), such as Smart controlled environment agriculture (SCEA), an innovative form of crop cultivation that encourages sustainable, localized food production and security. However, due to perceived barriers by stakeholders, the adoption of SCEA initiatives is constrained in India. This research aims to explore the barriers to the smart transformation of UPA, examine them, and construct a framework to assist decision-making. The framework was developed using Total interpretive structural modeling (TISM) and Cross-impact matrix multiplication applied to classification (MICMAC). The findings revealed that cultural barriers, supply chain uncertainty, policy and regulations, and institutional support were driving barriers; technology and infrastructure, cold chain logistics, and environmentally sustainable practices were dependent barriers. The findings of this study will aid policymakers, government officials, urban farmers, and farming technology suppliers in developing a legal framework for adopting alternative food-growing technologies to achieve Sustainable development goals (SDGs).

Micro, small, and medium enterprises (MSMEs) play a vital role in India's economic growth. MSMEs operating in the scrap management sector encounter two main concerns about the transportation cost and scheduling of vehicles. To solve these issues, MSMEs are trying to adopt emerging technologies such as automatic scrap storage, inventory control, and retrieval systems. However, MSMEs are reluctant to implement these technologies due to their pre-assumption of high adoption costs and expected benefits. The present study focused on the effective IoT implementation in vehicle loading to reduce transportation costs and trips in MSMEs. The case study of the scrap managing company has been considered to show the benefits of IoT implementation in MSMEs. The simulation was performed using FlexSim, and the results have confirmed that the IoT implementation can improve vehicle loading by 38% and reduce transportation costs by 38.6%. The outcomes highlight the benefits of IoT deployment in MSMEs.

In recent years, Urban and peri-urban farming (UPF) research has experienced significant growth, but a comprehensive global overview is lacking. This study examined UPF research from 2002 to 2022 using an integrated literature review approach, including systematic literature review, bibliometric analysis, and thematic assessment. Analyzing 1,257 articles from the Web of Science database with Vosviewer and Bibliometrix, key keywords identified in the literature were urban agriculture, food security, local food systems, community gardens, and sustainable agriculture. Prominent research trends included the Internet of Things (IoT), resilience, Controlled environment agriculture (CEA), plant factories, Life cycle assessment (LCA), and vertical farming. Publications by US-affiliated authors received higher citations, and co-authorship collaborations from China, India, and Brazil were observed in UPF research network. Notable institutions with significant contributions and collaboration links in UPF research were the University Autonoma de Barcelona, the University of Kassel, and the National University of Singapore. This study's findings offer valuable insights for researchers and policymakers in the food and agriculture industry, providing a comprehensive overview of the UPF domain and suggesting future research directions. This review advances urban farming practices, informing decision-making processes, research priorities and developing the policies and initiatives to foster resilient and sustainable urban farming.

Purpose: This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work. Design/methodology/approach: Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS). Findings: From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers. Practical implications: This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic. Originality/value: The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.

The present study investigates the impact of novel ultrasonic-assisted squeeze casting parameters on the fabrication of AA2014/Al2O3 nanocomposites using the Taguchi Grey response surface methodology. The experiments were carried out using Taguchi's L16 orthogonal array, with five different controllable parameters of ultrasonic-assisted squeeze casting process such as ultrasonic power (1.5–2.25 kW), ultrasonic time (4–16 min.), pouring temperature (700–850 °C may result in premature solidification), squeeze pressure (50–200 MPa) and wt % of reinforcement (1-4). The process's performance measures included hardness, ultimate tensile strength, percentage of elongation and grain size. The microstructure of the nanocomposites was investigated using optical microscopy, high-resolution scanning electron microscopy and X-ray diffraction technique. The multiple responses were converted into a single Grey relational grade, which was then used in modelling and optimization using the response surface methodology. Analysis of variance and 3D surface plots were generated to investigate the most important parameters affecting the quality of AA2014/Al2O3 nanocomposites. The results showed that the optimum parameter settings were ultrasonic power of 2.2489 kW, ultrasonic time of 15.91min, pouring temperature of 700.67 °C, squeeze pressure of 41 MPa and wt % of reinforcement of 1.85. The results of TGRSM demonstrated that ultrasonic power had the strongest correlation with responses, with significant improvements in UTS and grain size. The confirmation experiment revealed an improvement of 0.201 in GRG.

In this study, magnesium alloy (AZ91D) matrix composites reinforced with 1 wt% of nano alumina (n-Al2O3) were fabricated using novel Ultrasonic Treatment (UST) assisted squeeze casting method. UST was carried out at four different levels of ultrasonic power namely, 0 W (without UST), 1500 W, 2000 W and 2500 W at constant frequency and time. The composites were heat-treated at T6 condition under argon gas protected environment. Microstructural analysis was done using optical microscopy and high-resolution scanning electron microscopy. Physical, mechanical and tribological properties of the composites were evaluated. A significant refinement in grain structure and improvement in porosity was seen on an increase in UST power. Improvement was seen in micro-hardness, yield strength, ultimate tensile strength and % of elongation of the composite fabricated at 2500 W by 18%, 48%, 28%, and 10% respectively compared to an untreated composite. The composite fabricated at 2500 W showed less wear rate and coefficient of friction when compared to other composites at all sliding conditions. Scanning electron microscope images of the worn surface of the composite pins revealed that the wear mechanisms dominated were abrasion, adhesion, oxidation and delamination.