Search results

This paper aims to unearth the essential components of Six Sigma for successful deployment and sustainment of service quality in four different organizations in the United Arab Emirates (UAE). More specifically, the paper is intended to determine the motivation to apply Six Sigma, Voice of Customer, Key Performance Indicators (KPIs), Critical-to-Quality (CTQ), readiness factors, Critical Success Factors, sustainment measures, tools and techniques used, challenges/barriers and performance impact on the company.

An exploratory research methodology with multiple case study analyses was adopted to determine the answers to the research objectives. Four case studies from different service processes of four companies were analyzed. The case studies were collated from these companies via a case study protocol with pre-defined criteria.

The analysis shows that service operation improvement projects are primarily dependent on the voice of the internal customer, with return on investment in savings as the KPI of the process. Most organizations prefer cycle time and errors as the CTQs in the Six Sigma projects. Even novice users can effectively apply the Six Sigma methodology with external experts’ assistance, mentoring and interventions. Across the case studies, it is observed that the projects were successfully deployed due to the support of top management leadership, effective communication and cross-functional teams. Employee resistance to change is the common barrier observed during the case study analysis. Eventually, in all the four case studies, Six Sigma is executed with standard tools and techniques within the define, measure, analyze, improve, control (DMAIC) approach.

The present study’s findings cannot be generalized due to the limited number of case study analyses in different ecosystems in the UAE. The authors would like to analyse and report more case studies in service quality improvement through the Six Sigma methodology to comprehend and develop a generic roadmap for the deployment of Six Sigma in the UAE service industry.

The study’s findings provide insights into commonalities and differences between the essential factors of Six Sigma deployment and sustainability in UAE companies.

The study results might help the policymakers and key decision makers in UAE and other countries understand the effectiveness of Six Sigma in service quality improvement with its essential factors for deployment.

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.

There is increasing interest in the connection between Industry 4.0 (I4.0) and operational excellence approaches; however, studies on the integration between Six Sigma (SS) and I4.0 have been absent from the literature. Integration with I4.0 technologies can maximize the positive effects of SS. The purpose of this study is to understand what types of relationships exist between SS and I4.0 and with I4.0's technologies, as well as the benefits derived from this integration and future directions for this field of study.

A Systematic Literature Review (SLR) was carried out to analyze studies about connections between I4.0 technologies and SS. SLR analyzed 59 articles from 2013 to 2021 extracted from the Web of Science and Scopus databases, including documents from journals and conferences.

The SLR identified relationships between SS and several I4.0 technologies, the most cited and with the greatest possibilities of relationships being Big Data/Big Data Analytics (BDA) and Internet of Things (IoT). Three main types of relationships were identified: (1) support of I4.0 technologies to SS; (2) assistance from the SS to the introduction of I4.0 technologies, and, to a lesser extent; (3) incompatibilities between SS and I4.0 technologies. The benefits are mainly related to availability of large data sets and real-time information, enabling better decision-making in less time.

In addition, the study can help managers to understand the integration relationships, which may encourage companies to adopt SS/Lean Six Sigma (LSS) in conjunction with I4.0 technologies. The results also drew attention to the incompatibilities between SS and I4.0 to anticipate potential barriers to implementation.

The study focuses on three previously unexplored subjects: the connection between SS and I4.0, the existing relationships with different technologies and the benefits resulting from the relationships. In addition, the study compiled and structured different types of relationships for SS and I4.0 and I4.0's technologies, identifying patterns and presenting evidence on how these relationships occur. Finally, exposes current trends and possible research directions.

This study investigates the overall publications of The TQM Journal since its inception with an aim to identify the trending topics and emerging trends.

The quantitative bibliometric and social network analysis techniques composed of keywords, co-occurrence network and keyword cluster detection are employed to conduct the investigation. A total of 968 papers published in The TQM Journal till August 2022 were sourced from the SCOPUS database to conduct the analysis.

The research identifies five themes from the published articles namely, customer service experience and satisfaction; quality management and organizational performance; quality measurement tools and models; quality and sustainable development; and quality and competitive advantage. The study also identifies the most significant articles, authors and countries published in the journal and shows that Industry 4.0 is the trending topic and quality 4.0 the new emerging trend in the journal.

The analysis is carried out only for papers published in The TQM Journal till August 2022; those after this month are not included in the analysis. The outcome of this study is dynamic in nature and subject to change over time as more papers, citations and collaborations are added to the list.

This is the first article of its kind to explore The TQM Journal publications with an aim to identify trending and emerging topics and also the most valuable authors based on the number of publications and citations through the bibliometric analysis.

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 objective of this study is to systematically identify, categorize and assess the driving factors and interdependencies associated with various types of healthcare waste. The study specifically focuses on waste that has been managed or is recommended for treatment through the application of Lean Six Sigma (LSS) methodologies.

To accomplish the study’s objectives, interpretive structural modeling (ISM) was utilized. This analytical tool aided in quantifying the driving power and dependencies of each form of healthcare waste, referred to as “enablers,” as well as their related variables. As a result, these enablers were classified into four distinct categories: autonomous, dependent, linkage and drivers or independents.

In the healthcare sector, the “high cost” (HC) emerges as an autonomous variable, operating with substantial independence. Conversely, variables such as skill wastage, poor service quality and low patient satisfaction are identified as dependent variables. These are distinguished by their low driving power and high dependency. On the flip side, variables related to transportation, production, processing and defect waste manifest strong driving forces and minimal dependencies, categorizing them as independent factors. Notably, inventory waste (IW) is highlighted as a salient issue within the healthcare domain, given its propensity to engender additional forms of waste.

Employing the ISM model, along with comprehensive case study analyses, provides a detailed framework for examining the complex hierarchies of waste existing within the healthcare sector. This methodological approach equips healthcare leaders with the tools to accurately pinpoint and eliminate unnecessary expenditures, thereby optimizing operational efficiency and enhancing patient satisfaction. Of particular significance, the study calls attention to the key role of IW, which often acts as a trigger for other forms of waste in the sector, thus identifying a crucial area requiring focused intervention and improvement.

This research reveals new insights into how waste variables are structured in healthcare, offering a useful guide for managers looking to make their waste-reduction strategies more efficient. These insights are highly relevant not just for healthcare providers but also for the administrators and researchers who are helping to shape the industry. Using the classification and ranking model developed in this study, healthcare organizations can more easily spot and address common types of waste. In addition, the model serves as a useful tool for practitioners, helping them gain a deeper, more detailed understanding of how different factors are connected in efforts to reduce waste.

The present study aims to explore the barriers to Lean Six Sigma (LSS) implementation in the healthcare sector and develop the ranking of finalized barriers using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach under a fuzzy environment.

The LSS barriers are identified through the literature review and validated by the expert's opinion and statistical analysis. A total of 124 experts were identified through the purposive sampling method for conducting this study. A questionnaire survey method is used to collect the data related to identified LSS barriers in the healthcare sector. The screened barriers are ranked through the Fuzzy DEMATEL approach.

In this study, a total of 21 barriers were identified with the help of a systematic literature review and screened 13 significant barriers by the expert opinions of healthcare personnel. The result reveals that “Lack of top management commitment and support, lack of awareness about LSS”, “resistance to culture change and inadequate resources emerges as the most critical barriers”. The prioritization of barriers facilitates the managers to make effective policies and guidelines for LSS implementation in healthcare organizations.

To avoid LSS implementation failure, the practitioners and researchers need to focus on LSS barriers as per suggested ranking more conventionally and make plans and adoption policies accordingly.

This study is unique in terms of investigation and empirical analysis of LSS implementation barriers in the healthcare sector in the Indian context. The outcomes of the present study will help the managers of healthcare organizations to make the strategies and policies for LSS implementation as per the recommended LSS barriers.

The aim of this research is to enlighten the methodology model of Industrial Design Structure (IDeS) that integrates the internal and external customer feedback embodied both in methods of quality function deployment (QFD) and as basis of design for six sigma (DFSS) steps to systematically bring the information across the entire organization, saving overall product development time and resources.

The paper describes the state of the art enlightened to establish the disadvantages and challenges of other methods taken into consideration in the study like QFD and DFSS that, together with the need of companies to react fast to changes they need to straightforwardly implement product development information across all departments, leading to a mass customization infrastructure. Several application trials of this methodology have been cited.

The IDeS method has established to been able to integrate other well-known methodologies to gather technical specifications starting from voice of customers (VOCs) like QFD that served to canalize the generalist approach of define, measure, analyze, design and verify (DMADV) of DFSS in order to reach into a larger share of the organization and englobe by following the overall product design steps of an industrial project.

The research approach chosen for this document presents the concept of a methodology ought to operate most internal branches in a company driven by product design requirements and guidelines. Therefore, researchers are encouraged to develop further studies on the IDeS method are required in order to adapt this methodology to specific management tools that would help to ease information gathering for immediate analysis and modification.

The paper implicates that a need to interchange information systematically across all subdivisions in the organization, as brisk response to VOC reactions is needed to thrive in the market nowadays, leading to a fast product customization scene. However, the industry is heading into adopting an individual customer-centered product conceptualization ought to be driven by design as a key for individualizing an object. Afterward by taking this concept broadly and adopting it would lead to implement a company organization that would be directly affected by the customer's input.

The methodology described aims to enable organizations to portray fast and accurate product prototyping, by exploiting technologies from Industry 4.0.

This concept proposes a method to canalize the implementation of DFSS by using the DMADV approach, whilst assessing the challenges of adaptation and keeping up with cultural pace that impacts the behavior of buying and consumption and moreover implementing a seamless communication within all departments in the organization to share the development progress and change requests by using similar information technology tools. This would imply important savings in resources, whilst delivering quality products to the society.

The effectiveness of Six Sigma programs has varied across different industries and organizations, and leadership styles have been identified as a critical success factor for the installation of Six Sigma initiatives. Therefore, this study aims to investigate the specific elements of leadership styles that are linked with the successful deployment of Six Sigma programs in the automobile industry.

To conduct the study, the researchers utilized a Likert scale questionnaire with a rating system of 1–7 and a simple random sampling method. The survey was distributed to 2,325 potential participants, with 573 responses received, mostly from Germany, the United Kingdom and Sweden. Out of those responses, 260 completed questionnaires were received. The study utilized a mixed-methods research design and exploratory research approaches to investigate the implication of leadership style on the success of Six Sigma implementation. The research employed several analysis techniques, including Structural Equation Modeling (SEM), exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and Survey methods.

Through various SEM methods, such as EFA and CFA, the study revealed two vital leadership elements: (1) the long-term success of Six Sigma depends on leadership’s support and recognition of it as an improvement strategy and (2) leadership must commit to the organization’s suppliers to ensure quality and the provision of defect-free products.

By incorporating the identified key elements of leadership into their strategies, organizations and researchers can ensure the sustainable implementation of Six Sigma.

This research presents a distinct contribution to the evaluation of leadership style components within the European automotive sector, utilizing a mixed-methods research design and incorporating a variety of descriptive statistics.

The purpose of this study was conducted at an enterprise that produces fasteners and is one of the leading companies in the sector in terms of market share. Possible defects in the coating of bolts and nuts either lead to products being scrapped or all of the coating process being repeated from beginning to end. In both cases, the enterprise faces a waste of time and excessive costs. Through this project, the six sigma theory and its means were effectively used to improve the efficiency and quality management of the company. The selection of the six sigma project has also contributed to the creation of various documents to be used for project screening and evaluation of financial results.

Six sigma is an optimization strategy that is used to improve the profitability of businesses, avoid waste, scrap and losses, reduce costs and improve the effectiveness of all activities to meet or exceed customers’ needs and expectations. Six sigma’s process improvement model, known as Definition-Measurement-Analysis-Improvement-Control, contributes to the economic and technical achievements of businesses. The normal distribution of a process should be within ±3 sigma of the mean. This represents a scale of 99.7% certainty. However, improving the process through the utilization of the six sigma rule, which accepts normal variabilities of processes twice as strict, will result in an error rate of 3.4 per million instead of 2,700 per million for each product or service.

Using six sigma practices to reduce the costs associated with low quality and to increase economic added value became a cultural practice. With this, the continuation of six sigma practices throughout the Company was intended. The annual cost reduction achieved with the utilization of six sigma practices can be up to $21,780. When time savings are also considered, a loss reduction of about $30,000 each year can be achieved. The coating thickness efficiency increased from 85% to 95% after the improvements made through the six sigma project. There is a significant increase in the efficiency of coating thickness. In addition, the coating thickness efficiency is also close to the target value of 95%–97%.

The results of the study were optimized with the help of deep learning. The performance of the model created in deep learning was quite close to the actual performance. This result implicates the validity of the improvement work. The results may act as a guide for the use of deep learning in new projects.