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The paper reports a study into set‐up time reduction and mistake proofing methods in a small company involved in the machining of precision components in small batches with high variety for the aerospace industry. The company has made some set‐up reductions mainly using work study related methods and in one manufacturing cell by the use of the Single Minute Exchange of Die (SMED) methodology. Mistake proofing devices in the form of fouling pins and offset holes have been developed for the family of components manufactured in this cell. Until recently the set‐up times were not measured and worse still were considered as productive hours. As a consequence, there was a lack of awareness and motivation amongst operational personnel to reduce set‐up times and knowledge of SMED was limited to a small group of individuals. This, along with the lack of investment in mechanisms to aid set‐up time reductions and prevent errors, has restricted the use of this type of methods and technology. However, there is evidence that the demands made by the company’s major customer will lead to increased efforts to put into place these types of changes.

Micro-enterprises have a vital role in the development of a nation by creating employment, encouraging entrepreneurship, balancing social income and educating the workforce. Yet, micro-enterprises face significant operational challenges such as low productivity, high production costs and long changeover times. These challenges are often overlooked by researchers and practitioners but have a drastic impact on micro-enterprises' operational performance. With over 95% of the economy consisting of micro-enterprises, it is vital to improve operational performance and competitiveness of the micro-enterprises.

Considering the data availability and practical challenges of gathering data from micro-enterprises, an action research methodology was selected as a suitable research method. Following the initial diagnostic visits, planned interventions were prepared and results were observed to gather data and draw conclusions.

Findings suggest that commonly adapted performance improvement initiatives by large enterprises cannot be directly applied in micro-enterprises to enhance operational performance. Micro-enterprises lack the critical resources and company culture to easily adapt these initiatives. On the other hand, when these performance improvement initiatives are filtered according to specific needs of micro-enterprises, continuous improvement initiatives were often found to be effective in improving operational performance. Specifically, 5S, single-minute exchange of dies (SMED), suggestion schemes, layout improvements, management coaching, visual management, empowerment were found to be useful and suitable to address command and control culture, low productivity, unorganised workspace, undelegated authority, low skilled employees and unwillingness to take responsibility problems.

Further research is required to investigate the specific factors that affect the adaptation of continuous improvement initiatives such as culture and industry type.

This research extends and contributes the current literature on continuous improvement initiatives by revealing how performance improvement initiatives need to be filtered according to the specific needs of micro-enterprises, and how these initiatives can be used to address specific problems to improve operational efficiency. It provides a conceptual framework to guide the decision-making process on operational performance improvement in micro-enterprises.

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.

The purpose of the study reported in this paper was to examine how manufacturing organisations used set‐up time reduction and mistake proofing methods. The study was conducted in companies involved in manufacturing precision components. It was found that the companies were approaching the application of these concepts mainly through traditional work‐study type methods rather than using Shingo’s single minute exchange of die and poka‐yoke or mistake proofing methodologies. There was clear evidence that the four companies are reducing set‐up time through supporting mechanisms such as kaizen teams. The main poka‐yoke devices used were jigs, gauges, pegs, lights and buzzers. Total productive maintenance, suggestion schemes and quality management tools and techniques were also employed to reduce set‐up times and mistake proof processes. The main barriers to the application of these methods include traditional methods of working and resistance to change.

Business model change (BMC) is a process new ventures are frequently involved in, especially in dynamic environments like the digital industry: copying with it is a key issue for entrepreneurs attempting to shorten the transition between current and new business models (BMs) and avoid losses in terms of revenue, image and customer retention, while acquiring experience and validated learning in the process. The purpose of this paper is to propose a lean framework to support digital new ventures in the BMC process.

The study builds its contribution on two pillars: a review on BM and the lean thinking theories, and a multiple case study on three digital new ventures which underwent BMC.

The study shows how BMC in a digital context can beneficially follow lean principles, and how these principles can be integrated in an original lean framework to experiment on, validate and subsequently change a BM.

The authors provide the “single minute exchange of die” for BMC framework that extends and complements lean startup approaches to further relate lean thinking and BMC, thus operationalizing the process of BM experimenting and validation that enables change.

This study aims to research the usage of virtual reality as a tool to train employees in a changeover process in a company, and if it guarantees the same level of quality. Moreover, another goal is to understand how it can influence the machines’ availability, reducing the number of hours a machine is stopped to perform training sessions.

To achieve the goals proposed, the action research strategy was used. After defining the context and purpose, two full cycles were applied, composed by five activities: diagnosis, action planning, action taking, action evaluation and specify the learning.

The results are extremely satisfactory. On the one hand, it can be concluded that virtual reality is a reliable training tool, guaranteeing proper training to the employees. On the other hand, based on the previous point, the researchers were able to conclude that it is possible to increase machines’ availability, reducing by 50% the time needed to have the machines stopped to run a changeover training.

To the authors’ knowledge, this is the first study to use the action research strategy to develop a virtual reality simulation as a training tool for machines’ changeover in the automotive industry.

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.

The purpose of this paper is to contribute to the implementation of best practices of collaboration between university and industrial small‐ and medium‐sized enterprises (SMEs).

This paper presents the experience carried on by a university group fostering the collaboration with SME companies involving young engineering students and researchers in projects designed for the resolution of real industrial problems. A collaboration model is proposed and described. Four real case studies are presented.

The purposed model promotes the involvement of the young engineers with authentic industrial experiences, enables the build‐up of their practical framework and encourages their entrepreneurial growth. It also promotes the innovation process in SME companies through the close collaboration with universities.

The collaboration between universities and SME companies should be based on a small projects base. These projects must be focus in localized and specific problematic areas in the industrial companies, where the potential of improvement and innovation is large, must diagnose the problematic situation and propose new and efficient solutions supported by technical/scientific methodologies. The involvement of managers and collaborators of SME companies and the clearly definition of their roles in the project are fundamental issues for the collaboration success.

The model presented in this paper describes an innovative step‐by‐step procedure, easy to be implemented by the universities. It emphasises the impact of some details during the collaboration process that enhance the success potential of university‐SME companies' projects, the quality of the research work produced and the quality of young future engineers training. It also fits with the SME companies' demands of a mix of structured knowledge and empirical experience.

The purpose of this paper is to present the “Assessment Model of Lean Effect” (AMLE), a theoretical model that measures Lean manufacturing implementation effect over the global performance of a company.

AMLE model is divided in two criteria types: the “Facilitators criteria” and the “Results criteria”. “Results criteria” are inspired from the European Foundation for Quality Management (EFQM), Global Reporting Initiative (GRI) and ISO 26000. The “Facilitators criteria” are based on the main philosophy of the Lean manufacturing, which is the total elimination of all types of waste. The development of the scoring scale was based on the results, approach, deployment, assessment and review (RADAR) philosophy and the experience of nine consultants from the automotive field; the choice of the consultants was based on three conditions. Furthermore, each consultant has his\her own weight according to its expertise. Lastly, the AMLE was validated via a case study set in an automotive industry company called FEBA. The validation process is divided in two different steps: the first step is related to Facilitators assessment and scoring; via the evaluation of the different projects implemented by FEBA to eliminate the different types of waste. The second step concerns Results assessment and scoring, via the evaluation of the performance measurements used by FEBA to assess the effect of the Facilitators' implementation.

The developed model (AMLE) enabled the Lean manufacturing effect assessment on the global performance of a firm from the automotive field. The case study results reveal that the aforementioned firm does not give priority to social measurements. Consequently, the performance of the firm was negatively impacted.

The criteria of AMLE are inspired from the definition of the Lean manufacturing given by Taiichi Ohno, from ISO 26000 and from GRI; meaning that these criteria could be adjusted if other references existed or developed. In addition, the scoring rules are established according to the experience of a limited number of consultants from the automotive field. The scoring rules establishment would lead to meaningful outcomes, if the number of participants was increased. During the assessment of the global performance, the perception of the auditor plays an important role in terms of scoring because the scoring rules allow the possibility to the auditor to give from the minimum to the maximum of the score, according to his perception and experience. For the case study, the validation of the developed model requires starting with the “Facilitators” implementation process and then measure the generated global performance. However, due to time constraints and limited opportunities for new projects, the validation was based only on existing projects managed by the firm. To address the study limitations, it is envisaged to detail and explain the scoring rules while extending the number of consultants. Furthermore, the assessment of Lean manufacturing global performance through the AMLE model may be subjective and requires a mathematical modeling. In fact, the Lean manufacturing performance assessment via the developed model could have a degree of subjectivity; that is why the design of a mathematical model seems required.

The research findings may direct practitioners and decision makers to the importance of assessing the global effect of the Lean manufacturing on the overall performance of the firm. The AMLE model is a tool allowing the assessment of Lean manufacturing effect over economic, environmental and social performances.

The developed model is the first one assessing the global performance generated by the elimination of waste via the application of the Lean manufacturing.

Lean Six Sigma 4.0 has brought about a paradigm shift in customization, automation, value creation and digitalization to achieve excellence in human factors, operations and sustainable development. Despite its potential, LSS 4.0 is still in its nascent stage, with researchers striving to identify the key and relevant components of LSS in relation to Industry 4.0. The present study aims to address this knowledge gap through a literature review and subsequently provide a conceptual framework for LSS within the context of digital transformation.

In this study, the authors have conducted a thorough review of reputable articles published between 2011 and 2022, focusing on the integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0). By using appropriate keywords, the authors identified around 85 relevant articles. The main objective of this integrative literature review was to analyze and extract valuable knowledge from the existing literature on LSS and I4.0. Based on the authors’ findings, a conceptual framework was developed.

The review revealed the motivators, building blocks, tools and challenges of LSS 4.0. The conceptual framework delves into the key aspects of LSS 4.0, focusing on the dimensions of people, process and technology, as well as their subdimensions. These subdimensions serve as the building blocks for developing LSS 4.0 capabilities. The proposed framework visually represents the conceptualization and the relationships among its components.

Only a few conceptual approaches to LSS are developed that include the concepts, new roles and elements of I4.0. As a result, this research investigates the gap in current LSS models preceding I4.0 and develops a conceptual framework to provide a novel and comprehensive summary of the new concepts and components driving nascent and current LSS practices in the digital era.

This study offers practical guidance for implementing LSS in the context of I4.0, emphasizing digital transformation. The findings highlight motivators, building blocks, tools, challenges and spread of LSS 4.0 practices, and present a conceptual framework of LSS 4.0. These insights can help organizations enhance their LSS capabilities and achieve excellence in human factors, operations and sustainable development.

This study aims to make a significant contribution to the model-building efforts of researchers focusing on LSS 4.0. By offering practical guidance, the points discussed in this study help enhance the implementation efforts of practitioners and organizations in the context of I4.0, with a specific focus on digital transformation. The guidance provided takes into account the perspectives of people, processes and technology, providing valuable insights for successful integration.