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First is to develop the time truncated median control chart for the Rayleigh distribution (RD) and generalized RD (GRD), respectively. Second is to evaluate the performance of the proposed attribute control chart which depends on the average run length (ARL) and third is to include real life examples for application purpose of the proposed attribute control chart.

(1) Select a random sample of size n from each subgroup from the production process and put them on a test for specified time t, where t = ? × µe. Then, count the numbers of failed items in each subgroup up to time t. (2) Step 2: Using np chart, define D = np, the number of failures, which also a random variable follows the Binomial distribution. It is better to use D = np chart rather than p chart because the authors are using number of failure rather than proportion of failure p. When the process is in control, then the parameters of the binomial distribution are n and p0, respectively. (3) Step 3: The process is said to be in control if LCL = D = UCL; otherwise, the process is said to be out of control. Hence, LCL and UCL for the proposed control chart.

From the findings, it is concluded that the GRD has smaller ARL values than the RD for specified values of parameters, which indicate that GRD performing well for out of control signal as compared to the RD.

This developed control chart is applicable when real life situation coincide with RD and GRD.

Researcher can directly use presented study and save consumers from accepting bad lot and also encourage producers to make good quality products so that society can take benefit from their products.

This article dealt with time truncated attribute median control chart for non-normal distributions, namely, the RD and GRD, respectively. The structure of the proposed control chart is developed based on median lifetime of the RD and GRD, respectively.

This paper aims to explore a framework for implementing Lean Construction (LC) to provide corrective actions for quality defects, customer dissatisfaction and value creation during the construction of megaprojects.

This paper presents a case study involving the construction of the Mohamed VI Tower in Morocco. It is the tallest tower in Africa, with 55 floors and a total height of 250 m. This study of the quality of the work and the involvement of the LC was carried out using the Define–Measure–Analysis–Improve–Control approach from Lean six sigma. It describes the Critical to Quality and analyses the root causes of quality defects, customer dissatisfaction and variation in the quality process.

Firstly, the results of this study map the causal factors of lack of quality as established in the literature. Secondly, the LC tools have reduced non-value-added sources of quality waste and, consequently, improved critical quality indicators.

This document focuses on one part of the tower’s construction and is limited to a project case in a country where LC is rarely used.

This study reinforces the literature reviews, surveys and the small number of case studies that have validated the potential of LC and further clarifies future directions for the practical emergence of this quality improvement approach, especially for large-scale projects.

Effective total quality management (TQM) practices rely on the accurate classification of critical success factors (CSFs). The impact matrix cross-reference multiplication technique for classification (MICMAC) or/and fuzzy MICMAC (FMICMAC) can be used to identify key factors in the complex set. However, TQM includes both “hard” and “soft” factors, limiting application of the traditional MICMAC/FMICMAC method.

Previous literature on TQM was reviewed, CSFs were identified, and factors were sorted into soft and hard categories. The combined fuzzy integration and dual-aspect MICMAC (fuzzy dual-aspect MICMAC approach) was then applied to identify, cluster and prioritize the CSFs of TQM.

A total of 20 factors (10 soft and 10 hard) were identified and isolated to assess the manufacturing- and service-related TQM practices of the Pearl River Delta Region of China. Seven driver factors and one linkage factor emerged as the key CSFs that managers should prioritize.

A major limitation of this study is the dependency of the results on the definitions of linguistic labels. If the linguistic definitions of TQM CSFs do not closely correspond to the expert opinion data, then the analysis results may be inaccurate. Additionally, although expert opinions are utilized in the proposed method for comprehensive assessments, these opinions may influence the final results due to their inherent subjectivity.

A novel fuzzy dual-aspect MICMAC approach was developed to identify and classify CSFs for optimal TQM practices. This approach allows clustering of CSFs so that decision-makers can prioritize factors according to their dependence and driving powers. Practitioners should concentrate on the CSFs with higher driving powers for successful TQM.

Interrelationships among some common factors of human resource (HR) management and quality management are still unexplored. Changes in work patterns due to the Covid-19 pandemic have aroused interest in some of these factors, such as working-hours, work pressure, work–life balance practices, job satisfaction. The purpose of this study is to explore the interrelationships among such factors. Specifically, the influence of work hours, work pressure, job rotation and work–life balance on job satisfaction is evaluated both directly and under the mediating influence of working conditions.

A questionnaire-based survey was conducted in Indonesia among diversified organisations. A total of 432 responses were gathered, and they were examined using hypothesis testing and partial least square based structural equation modelling.

The study confirms the statistically proven impact of work pressure, job rotations and work–life-balance practices on working conditions. Job rotations, work–life balance practices and working conditions directly influenced job satisfaction. Work pressure did not influence job satisfaction directly, but it significantly influenced working conditions, which eventually affected job satisfaction. Working hours neither affected working conditions nor job satisfaction in a significant manner.

Covid-19 necessitated working from home, which is a peculiar work–life balance situation. The findings are helpful for organisations in planning strategies related to work–life-balance, working hours, multi-skilling, working conditions and other quality of work life factors in both regular working conditions and under Covid-19 conditions.

The proven influence of work pressure and work–life-balance practices may result in the formation of informal organisations, social groups and increased social networking. As working hours are not diagnosed as an influencing factor for job satisfaction, organisations may think about increasing them, affecting the social fabric of the working community.

Previously unexplored interrelationships among various quality of work life factors are established. Under Covid-19 circumstances, factors such as working hours, work–life-balance and work pressure are investigated in a novel manner. The factors and their interrelationships are important to both quality management professionals and HR professionals.

This study intends to improve the quality of venous thromboembolism (VTE) prophylaxis practices including proper VTE risk assessment and the appropriate prophylaxis measures for surgical urology patients.

The authors applied the Six-Sigma define, measure, analyze, improve and control (DMAIC) improvement methodology in a pre–post interventional study that involved all adult patients above 18 years old indicated and scheduled for urology surgical interventions including endoscopic urological surgeries in a urology specialized 60-bed hospital. The pre-intervention sample included all patients meeting the inclusion criteria over a period of six months. Post-intervention sample included all patients meeting the inclusion criteria over a period of six months. The improvement areas included both the VTE risk assessment as well as the VTE prophylaxis prescription.

DMAIC methodology has achieved a substantial sustained improvement in surgical urology VTE prophylaxis practices with an average of 70% on both levels; VTE risk assessment practices and VTE prophylaxis prescribing practices were statistically significant. The post-intervention results also showed a statistically controlled process with no special cause variations. Based on the study results, the Six-Sigma DMAIC methodology can be considered of high value when applied in healthcare clinical practice improvement projects.

The project study includes some pitfalls that can be addressed as follows: 1. The lack of VTE rate incidence tracking. This limitation can be partly refuted when the authors conduct a literature review and explore that the VTE prophylaxis effectiveness had been proven with sufficient evidence to an extent that pushed several scientific societies to develop their own guidelines to support VTE prophylaxis. (Algattas et al., 2018). 2. Another limitation of this study can be that it handled only surgical patients and more specifically surgical urology patients. Of course, VTE prophylaxis is a crucial life-threatening problem not only for the surgical admitted patients but also for all the medical admitted patients either in hospital wards or ICUs. However, the prediction that surgical patients especially surgical urology patients are more prone to VTE development risk as they have -in several cases-two or three main additive risk factors which are age, procedure duration and malignancy in elderly men. (Tikkinen et al., 2014). So, the authors consider the study project to be a prototype that hopefully can be utilized for future study projects that will manage both other surgical specialty patients and medical patients on the national level and can track accurately and effectively report the VTE incidence rates.

Several recommendations can be extracted from the research project that is summarized in the following points: Paying focused attention to continuous healthcare quality improvement initiatives and projects as a main approach for healthcare improvement especially for the public health-related problems. This might be achieved through periodic region-specific or specialty-specific focus groups from which public health problems could be addressed and prioritized to be considered as a part of country healthcare campaigns regarding cost-utility and feasibility studies. The adoption of a system thinking approach in dealing with the improvement strategies; all efforts and resources are to be employed to achieve a common objective. This includes the generation of a national-wide electronic health information system that can aid in healthcare resource allocation and direct the healthcare efforts towards the most important, high-priority public health problems. Electronic national-wide health record is really an effort, and resources consuming activity, but actually, it's worth exerting efforts, and its valuable outcomes may be seen several years later. 3. Development of unified national specialized VTE prophylaxis pathways to standardize the patient-specific VTE prophylaxis plans. Standardization of healthcare pathways enables healthcare professionals to follow an evidence-based practice which will be reflected on the improvement of healthcare quality level, cost-effectiveness enhancement, and timely patient care on all levels especially in high critical areas like ER and ICU. 4. Incorporation of VTE prophylaxis costs in the universal health insurance diagnosis-related group (DRG) insurance packages and service pricing. Universal health insurance is a nationwide strategy that is aiming to cover all Egypt residents by the year 2030. Universal health insurance is being following the DRG reimbursement policy that is thought to control all the healthcare-associated costs so, the VTE prophylaxis costs shall be added as the main cost item to encourage all healthcare facilities to follow an evidence-based VTE prophylaxis pathway taking into consideration the high-risk patient categories who will definitely represent a high-cost burden on the long run if they suffer a VTE event.

DMAIC improvement methodology applications in healthcare are still relatively limited, especially on the clinical level. The study can be considered one of a kind in Egypt dealing with a comprehensive DMAIC methodology application on the clinical level.

The purpose of this paper is to understand the post-COVID-19 fluctuations in the building construction demand from various angles at the national, regional, and sectoral levels. Despite the significant impact of COVID-19 on the building construction industry, a detailed quantitative analysis of the COVID-19 impact on the building construction demand is still lacking. The current study aims to (1) establish a statistical approach to quantify the COVID-19 impact on the building construction demand; (2) investigate the post-COVID-19 fluctuations in the construction demand of different building services, regional markets, and building sectors using the historical time series of the architecture billings index (ABI); and (3) identify vulnerable market and sector and discuss the post-COVID-19 recovery strategies.

The research methodology follows four steps: (1) collecting national, regional, and sectoral ABIs; (2) creating seasonal autoregressive integrated moving average models; (3) illustrating cumulative sum control charts to identify significant ABI deviations; and (4) quantifying the post-COVID-19 ABI fluctuations.

The results show that all the ABIs experienced a statistically significant decrease after COVID-19. The project inquiries index reduced more but recovered faster than billings and design contracts indices. The midwest billings index decreased the most among the regional ABIs and the commercial/industrial billing index dropped the most among the sectoral ABIs.

This study is unique in the way that it utilized the ABI data and the approach using SARIMA models and CUSUM control charts to assess the post-COVID-19 building construction demand represented by ABI fluctuations.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

In a packaging olives manufacturing system, the drained weight of the product plays a decisive role in customer’s satisfaction as well as in financial saving for the organization. The purpose of this study is to minimize the variation of the drained weight of olives in the production system to avoid the negative consequences.

The research develops a practical implementation step-by-step of Six Sigma define, measure, analyze, improve and control (DMAIC) in reducing the variation of the drained weight of olives.

Data analysis was used at various phases of the project to identify the root causes of rejection and rework. As a result of the necessary interventions and actions to optimize the manufacturing process, the standard deviation of drained weight was significantly reduced by 51.02%, with a 99.97% decrease in the number of parts per million defectives. Thus, the yield of the production process was improved by 8.24%. The estimated annual savings from this project were US$ 228,000 resulting from reduced rejection and rework.

This research may be used in packaging olives production systems as a tool for managers and engineers planning to increase productivity and efficiency while also improving product quality. The study also provided the organization with helpful actions that will be used to guide future Six Sigma operations management on the system. Thus, practical guidelines and solutions are provided.

In this project, for the first time, the Six Sigma methodology has been applied to solve a real-world problem in the packaging olives manufacturing system and to show that the DMAIC approach may assist to improve the efficiency of their operations and hence contribute to their quest toward continuous improvement.

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.

This paper explores Lean Six Sigma principles and the DMAIC (define, measure, analyze, improve, control) methodology to propose a new Lean Six Sigma 4.0 (LSS 4.0) framework for employee occupational exams and address the real-world issue of high-variability exams that may arise.

This study uses mixed methods, combining qualitative and quantitative data collection. A detailed case study assesses the impact of LSS interventions on the exam management process and tests the applicability of the proposed LSS 4.0 framework for employee occupational exams.

The results reveal that changing the health service supplier in the explored organization caused a substantial raise in occupational exams, leading to increased costs. By using syntactic interoperability, lean, six sigma and DMAIC approaches, improvements were identified, addressing process deviations and information requirements. Implementing corrective actions improved the exam process, reducing the number of exams and associated expenses.

It is important to acknowledge certain limitations, such as the specific context of the case study and the exclusion of certain exam categories.

The practical implications of this research are substantial, providing organizations with valuable managerial insights into improving efficiency, reducing costs and ensuring regulatory compliance while managing occupational exams.

This study fills a research gap by applying LSS 4.0 to occupational exam management, offering a practical framework for organizations. It contributes to the existing knowledge base by addressing a relatively novel context and providing a detailed roadmap for process optimization.