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Circular construction offers sustainable solutions and opportunities to disentangle a project’s life cycle, including demolition, deconstruction and repurposing of architectural, civil engineering and infrastructure projects from the extraction of natural resources and their wasteful usage. However, it introduces additional layers of novel risks and uncertainties in the delivery of projects. The purpose of this study is to review the relevant literature to discover, classify and theorize the critical risk factors for circular construction projects.

The paper conducted a systematic literature review to investigate the risks of circular construction projects. It deployed a multistage approach, including literature search and assessment, metadata extraction, citation frequency analysis, Pareto analysis and total interpretive structural modeling.

Sixty-eight critical risk factors were identified and categorized into nine broad taxonomies: material risks, organizational risks, supply chain risks, technological risks, financial risks, design risks, health and safety risks, regulatory risks and stakeholder risks. Using the Pareto analysis, a conceptual map of 47 key critical risk factors was generated for circular construction projects. A hierarchical model was further developed to hypothesize the multiple possible connections and interdependencies of the taxonomies, leading to chain reactions and push effects of the key risks impacting circular construction projects.

This study constitutes the first systematic review of the literature, consolidating and theorizing the chain reactions of the critical risk factors for circular construction projects. Thus, it provides a better understanding of risks in circular construction projects.

Amid rapid technological progress, the construction industry is embracing Construction 4.0, redefining work practices through emerging technologies. However, the implications of Construction 4.0 technologies to enhancing well-being are still poorly understood. Particularly, the challenge lies in selecting technologies that critically contribute to well-being enhancement. Therefore, this study aims to evaluate the implications of Construction 4.0 technologies to enhancing well-being.

A list of Construction 4.0 technologies was identified from a national strategic plan on Construction 4.0, using Malaysia as a case study. Fourteen construction industry experts were selected to evaluate the implications of Construction 4.0 technologies on well-being using fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The expert judgment was measured using linguistic variables that were transformed into fuzzy values. Then, the collected data was analyzed using the following analyses: fuzzy TOPSIS, Pareto, normalization, sensitivity, ranking performance and correlation.

Six Construction 4.0 technologies are critical to enhancing well-being: cloud & real-time collaboration, big data & predictive analytics, Internet of Things, building information modeling, autonomous construction and augmented reality & virtualization. In addition, artificial intelligence and advanced building materials are recommended to be implemented simultaneously as a very strong correlation exists between them.

The novelty of this study lies in a comprehensive understanding of the implications of Construction 4.0 technologies to enhancing well-being. The findings can assist researchers, industry practitioners and policymakers in making well-informed decisions to select Construction 4.0 technologies when targeting the enhancement of the overall well-being of the local construction industry.

The purpose of this study was to improve the overall equipment effectiveness (OEE) of the production process of the shredder operation of ABC company, an industrial waste management company which supplies pre-processed industrial waste as alternative fuel to a cement plant.

This case study investigated all possible availability and performance losses that caused the shredder system’s OEE and various problem-solving techniques, such as root cause analysis and Pareto analysis, were used to find the root cause of the reduced OEE.

After analysing this case study, three significant loss factors were identified from all the availability and performance losses, which caused the shredder system’s OEE losses. Practical solutions were found for the effect of those loss factors to improve the machine’s OEE and productivity.

This case study has been concentrated on only analysing of losses and improvement of OEE in the production process and not about cost analysis between loss and improvements.

This paper shows how to improve the OEE of a production process through various problem-solving techniques by identifying its losses and how to achieve the best solutions for those losses in a practical manner.

The global resolution of embracing dynamic and intertwined production systems has made it necessary to adopt viable systems like circular economy (CE) to ensure excellency in the business. However, in emerging countries, it is challenging to implement the CE practices due to the existing problems in the supply chain network, as well as due to the vulnerable financial condition of the business after the deadly hit of COVID-19. The main aim of this research is to determine the barriers to implementing CE considering the recent pandemic and suggest strategies to organizations to ensure CE for a cleaner environment and greener economy.

After an extensive literature review and validation from experts, 24 sub-barriers under the class of 6 main barriers are finalized by Pareto analysis, which is further analyzed via the best-worst method to determine the weight and rank of the barriers Further, fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to rank the proposed startegies to overcome the analysed barriers.

The results identified “unavailability of initial funding capital”, “need long time investment”, “lack of integrating production system using advance technology” and “lack of strategic planning” as the most acute sub-barriers to CE implementation. Further, fuzzy TOPSIS method is used to suggest the best strategy to mitigate the ranked barriers. The results indicated “integrated design facility to CE”, “ensuring large scale funding for CE facility” as the best strategy.

This study will motivate managers to implement CE practices to enjoy proper utilization of the resources, sustainable benefits in business, and gain competitive advantage.

Periodically, a lot of work is done on CE practices but none of them highlighted the issues in the domain of the leather products industry (LPI) and COVID-19 toward achieving sustainability in production and consumption. Thus, some significant barriers and strategies to implement CE for achieving sustainability in LPI are highlighted in this study, which is a unique contribution to the literature.

Policymakers are developing national strategic plans to encourage organizations to adopt Construction 4.0 technologies. However, organizations often adopt the recommended technologies without aligning with organizational vision. Furthermore, there is no prioritization on which Construction 4.0 technology should be adopted, including the impact of the technologies on different criteria such as safety and health. Therefore, this study aims to evaluate Construction 4.0 technologies listed in a national strategic plan that targets the enhancement of safety and health.

A list of Construction 4.0 technologies from a national strategic plan is evaluated using the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method. Then, the data are analyzed using reliability, fuzzy TOPSIS, normalization, Pareto, sensitivity, ranking and correlation analyses.

The analyses identified six Construction 4.0 technologies that are critical in enhancing safety and health: Internet of Things, autonomous construction, big data and predictive analytics, artificial Intelligence, building information modeling and augmented reality and virtualization. In addition, six pairs of Construction 4.0 technologies illustrate strong relationships.

This study contributes to the existing body of knowledge by ranking a list of Construction 4.0 technologies in a national strategic plan that targets the enhancement of safety and health. Decision-makers can use the study findings to prioritize the technologies during the adoption process. Also, to the best of the authors’ knowledge, this study is the first to evaluate the impact of Construction 4.0 technologies listed in a national strategic plan on a specific criterion.

This study aims to prioritize barriers responsible for impeding the successful implementation of maintenance practices in Northern Indian small and medium enterprises (SMEs). Maintenance practices play a crucial role in a company's long-term competitiveness in the manufacturing sector, significantly affecting production, quality and cost. Maintenance practices are equally vital in SMEs, because SMEs are the heart of the large industries, as these units are dependent on SMEs for their parts and sub-assemblies. However, due to many obstacles, SMEs have been confronted with various challenges in implementing maintenance practices.

First, a review of the published articles and survey of 216 Indian organizations has been conducted to identify the maintenance implementation barriers in SMEs. The Pareto analysis and the VlseKriterijumska Optimizcija Kompromisno Resenje in Serbian (VIKOR) approach have been deployed to rank the significant challenges in implementing maintenance practices in Northern Indian SMEs.

The present study aims to recognize and rank the barriers to effective maintenance implementation practices in SMEs, in order to initiate appropriate corrective actions to improve maintenance function performance.

The study will help maintenance managers in preparing an action plan to overcome the obstacles to maintenance practice's performance for realizing significant manufacturing performance improvements.

The main purpose of this study is to revisit Ishikawa's statement: “95% of problems in processes can be accomplished using the original 7 Quality Control (QC) tools”. The paper critically investigates the validity of this statement in higher education institutions (HEIs). It involves analysis of the usage of the 7 QC tools and identifying the barriers, benefits, challenges and critical success factors (CSFs) for the application of the 7 QC tools in a HEI setting.

An online survey instrument was developed, and as this is a global study, survey participants were contacted via social networks such as LinkedIn. Target respondents were HEIs educators or professionals who are knowledgeable about the 7 QC tools promulgated by Dr Ishikawa. Professionals who work in administrative sectors, such as libraries, information technology and human resources were included in the study. A number of academics who teach the 7 basic tools of QC were also included in the study. The survey link was sent to over 200 educators and professionals and 76 complete responses were obtained.

The primary finding of this study shows that the diffusion of seven QC tools is not widespread in the context of HEIs. Less than 8% of the respondents believe that more than 90% of process problems can be solved by applying the 7 QC tools. These numbers show that modern-quality problems may need more than the 7 basic QC basic tools and there may be a need to revisit the role and contribution of these tools to solve problems in the higher education sector. Tools such as Pareto chart and cause and effect diagram have been widely used in the context of HEIs. The most important barriers highlighted are related to the lack of knowledge about the benefits and about how and when to apply these tools. Among the challenges are the “lack of knowledge of the tools and their applications” and “lack of training in the use of the tools”. The main benefits mentioned by the respondents were “the identification of areas for improvement, problem definition, measurement, and analysis”. According to this study, the most important factors critical for the success of the initiative were “management support”, “widespread training” and “having a continuous improvement program in place”.

The exploratory study provides an initial understanding about the 7 QC tools application in HEIs, and their benefits, challenges and critical success factors, which can act as guidelines for implementation in HEIs. Surveys alone cannot provide deeper insights into the status of the application of 7 QC tools in HEIs, and therefore qualitative studies in the form of semi-structured interviews should be carried out in the future.

This article contributes with an exploratory empirical study on the extent of the use of 7 QC tools in the university processes. The authors claim that this is the first empirical study looking into the use of the 7 QC tools in the university sector.

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.

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).

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.

This research demonstrated how successful LSS implementation eliminates waste, improves process performance and accomplishes operational distinction in steel manufacturing.

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.

The main purpose of this study is to investigate Ishikawa’s statement that “95% of problems in processes can be accomplished using the 7 Quality Control (QC) tools” and explore its validity within the health-care sector. The study will analyze the usage of the 7 QC tools in the health-care service sector and the benefits, challenges and critical success factors (CSFs) for the application of the 7 QC tools in this sector.

In order to evaluate Ishikawa’s statement and how valid his statement is for the health-care sector, an online survey instrument was developed, and data collection was performed utilizing a stratified random sampling strategy. The main strata/clusters were formed by health-care professionals working in all aspects of health-care organizations and functions. A total of 168 participants from European health-care facilities responded to the survey.

The main finding of this study is that 62% of respondents were trained in the 7 QC tools. Only 3% of participants in the health-care sector perceived that the seven tools of QC can solve above 90% of quality problems as originally claimed by Dr Ishikawa. Another relevant finding presented in this paper is that Histograms, Cause and Effect diagrams and check sheets are the most used tools in the health-care sector. The least used tools are Stratification and Scatter diagrams. This paper also revealed that the 7 QC tools proposed by Dr Ishikawa were most used in hospital wards and in administration functions. This work also presents a list of CSFs required for the proper application of the 7 QC tools in healthcare.

This research was carried out in European health-care facilities – and there is an opportunity to expand the study across global health-care facilities. There is also an opportunity to study the use of the tools and their impact on hospital performance using the Action Research methodology in a health-care organization.

To the best of the authors’ knowledge, this is the very first research within the health-care sector that focused on investigating the usage of all the 7 basic tools and challenging Dr Ishikawa’s statement: “95% of problems in processes can be accomplished using the 7 Quality Control (QC) tools” from his book “What is Quality Control?” The results of this study represent an important first step toward a full understanding of the applicability of these tools in the health-care sector.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.