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This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

Bangladesh's ready-made garment (RMG) industry plays a vital role in the economic growth of this country. As the global trend in the fashion market has introduced a high-mix, low-volume ordering style, manufacturers are facing an increased number of changeovers in their production systems. However, most of the Bangladeshi RMG manufacturers are not yet ready to respond to such small orders and to improve the flexibility of their production systems. Consequently, the industry is falling behind in global market competition. Thus, this study aims to advance the current performance of RMG manufacturing operations to respond to the fast-fashion industry's challenges effectively using quick changeover.

In this study, a Single-Minute Exchange of Dies (SMED) is applied to attain quick changeover following the best practices of lean manufacturing.

This study examined the performance of the SMED technique to reduce changeover time in two case organisations. The changeover time was reduced by 70.76% from 434.56 min to 127.08 min and 42.12% from 2,664 min to 1,542 min for the case organisations, respectively. The results of this study show that companies require improved changeover times to address the demand for high-mix, low-volume orders.

This study will certainly guide practitioners of the RMG industry to adopt SMED to reduce changeover time to meet small batch production.

This paper aims to systematically understand the development of rapid setup, quantitatively analyze the landscape and reveal new trends and challenges.

Based on 192 literature studies (1987–2021) collected from Scopus and Google Scholar, the papers are classified by: publication time and source; research type and data analysis of papers; pattern of authorship and country; sector-wise focus of the paper; improvement method used in the setup. And CiteSpace is used to analyze the cooccurrence and timeline of keywords.

There has been substantial progress in the past 35 years, including the rapid growth in the number of papers, the expansion in different disciplines, the participation of developing countries, the application in the service industry and the significant impact of setup on cost. And there are still some deficiencies.

There is concern that Google Scholar lacks the quality control needed for its use as a bibliometric tool. Future work is encouraged to conduct an in-depth discussion on high-quality papers.

In small batch production, rapid setup is increasingly essential. Clarifying the research focus and main improvement methods is of great significance for enterprises to meet the changing market needs.

To the best of the authors’ knowledge, this study is the first literature review on rapid setup. It is decided to consider a detailed set of data for better introspection and trace the history reflections and the research future in setup time.

Saudi Arabia's 2030 vision targets an increase of 34% in non-oil revenue participation in the GDP, thus the need for automation and digital transformation. The Company ER is a market leader producing high-quality dairy products in the Kingdom and is a pioneer in the production industry. The company has recently increased the capacity of its milk factory to meet its vision. An investment was made to automate the pallet handling procedures at the milk factory to provide increased production for daily consumption. The new automation transition in Company ER's milk factory provides a unique opportunity to utilize lean management tools to improve the current automated processes before commercialization.

OEE (overall equipment effectiveness) will monitor losses for different operational losses in the new automated system and indicate system improvements, with 85% as the target. Based on DMADV (design, measure, analyze, design and validate) methodology, this study analyzes the entire automated pallet handling system. It uses lean tools to identify areas for improvement, identify waste elements and propose solutions to achieve Company ER's OEE targets.

In this paper, the outcomes will be presented as documented solutions that address the losses encountered in the production system, showing a 12.8% increase in the system's OEE.

Owing the time and resource constraint, this study only involved automated pallet handling procedures in a milk production facility. Hence, the generalization of the result is slightly limited. More studies in several different processes and sectors are required.

This study provided a valuable tool for researchers for gaining deeper understanding regarding the lean manufacturing and its implementation. For practitioners, it is useful to evaluate the degree of lean manufacturing tools in their material handling systems.

This study is the first attempt to develop lean manufacturing constructs for evaluating the automated pallet handling procedures in a milk production facility.

Shorter lead time with low price and quality product demand is pivotal in the garment industry. Pressure on production lead time stresses the importance of reducing style changeover time in manufacturing factories, and this paper aims to contribute to solving the challenge by showing how the single minute exchange of die (SMED) methodology in practice can be adapted to garment factories in developing countries.

The paper investigates three cases of SMED implementation integrated with responsible, accountable, consulted, informed (RACI) matrices in garment factories in an action research approach. Both quantitative and qualitative methods are applied.

The study shows a reduction of 50% to 64% of changeover time with SMED implementation measured with two key indicators – throughout time and time to reach peak production. Moreover, the implementation depends on the application of the RACI matrix for the distribution of responsibility as well as integration with the basic production flow before and after the application of SMED.

The study can guide better SMED implementation in garment factories with limited investment by stressing the need to adapt to the specifics of the garment industry, secure the division of responsibility and integrate SMED in the production flow before and after the changeover.

Limited research on the application of SMED in the garment industry. This paper contributes to understanding the specific conditions for successful implementation in the garment industry in developing countries and addresses additional activities that help secure a sustainable implementation process.

Organizations have released the importance of lean manufacturing practices (LMPs) and total quality management (TQM) in enhancing competitiveness. However, the implementation of LMPs and TQM becomes more complex when discerning the environmental sustainability position. The complexity stems from the fact that LMPs and TQM are more intricate because of cultural differences. Thus, this study aims to tackle the aforementioned phenomenon by investigating the impact of LMPs and TQM on environmental sustainability moderated by quality culture.

A survey was distributed among small and medium enterprises (SMEs) in Jordan; thus, 315 valid responses were received. Partial least square structural equation modelling was used to analyze the data and test hypotheses.

The findings showed that environmental sustainability was significantly impacted by all the LMP practices except Kanban and all the TQM practices except statistical process control. Moreover, quality culture significantly and negatively moderated the relationship between TQM and environmental sustainability. However, the influence of LMPs on environmental sustainability was not significantly moderated by quality culture.

This study has implications for policymakers in SMEs, supply chain managers and academics regarding the importance of LMPs and TQM systems for implementing environmental sustainability and the role of quality culture.

This study provides guidelines for decision-makers on the pathways that enable them to sustain the environment to safeguard the natural ecosystem and natural resources for upcoming generations.

The originality of this study stems from the alignment of LMPs and TQM in enhancing environmental sustainability, taking into consideration the role of quality culture in SMEs, where previous studies failed short to investigate this phenomenon.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

It is crucial for the Indian micro, small and medium enterprises (MSMEs) to implement a few of the most important Industry 4.0 (I4.0) technologies and reap maximum benefits of sustainability. This paper aims to prioritize I4.0 technologies that can help achieve the sustainable operations and sustainable industrial marketing performance of Indian manufacturing MSMEs.

I4.0-based sustainability model was developed. The model was analyzed using data collected from MSMEs by deploying analytic hierarchy process and utility-function-based goal programming. To have a better understanding, interviews were conducted.

Predictive analytics, machine learning and real-time computing were found to be the most important I4.0 technologies for sustainable performance. Sensitivity analysis further confirmed the robustness of the results. Business-to-business sustainable marketing is prioritized as per the sustainability need of operations of industrial MSME buyers.

This study uniquely integrates literature and practitioners’ insights to explore I4.0’s role in MSMEs sustainability in emerging economies. It fills a research gap by aligning sustainability goals of industrial buyers with suppliers’ marketing strategies. Additionally, it offers practical recommendations for implementing technologies in MSMEs, contributing to both academia and industry practices.

The study aims to develop and test a supply chain wide green product development framework of focal firms and their major suppliers, in the context of the Chinese automotive industry.

An in-depth case studies approach is adopted for this study. Three automotive sector upstream supply chains involving 17 firms and 51 experts as respondents were interviewed on the importance and implementation effectiveness of 6Rs (reduce, redesign, recover, remanufacture, reuse and recycle) across the manufacturer and their respective tier 1 and tier 2 suppliers.

The results indicate that the Chinese automotive sector supply chains are mainly focused on “reduce” practices with immediate environmental and economic benefits. The investigated firms however had future implementation plans for “redesign” and “recovery” practices to become comprehensive in green product development (GPD).

The study facilitates automotive firms, industry policymakers and researchers the understanding of incorporating comprehensive GSCM practices across the upstream supply chain to achieve circularity. The study focused on upstream supply chain due to the concentration of major production practices in this section of the supply chain. However, the downstream supply chain equally deserve attention as well as the need to understand the mediating and moderating roles of the different Rs to tease out the pros and cons of achieving overall environmental sustainability.

There are very limited studies on comprehensive GPD for achieving optimal GSCM and sustainability. By simultaneous looking at a focal firm and its upstream supply chains GSCM practices, this study addresses a system-wide comprehensive GPD issues from implementation of 6Rs perspectives in the supply chain.