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The purpose of this paper is to develop a comprehensive framework for improving intensive care unit performance.

The study introduces a quality management framework by combining cause and effect diagram and logical framework. An intensive care unit was identified for the study on the basis of its performance. The reasons for not achieving the desired performance were identified using a cause and effect diagram with the stakeholder involvement. A logical framework was developed using information from the cause and effect diagram and a detailed project plan was developed. The improvement projects were implemented and evaluated.

Stakeholders identified various intensive care unit issues. Managerial performance, organizational processes and insufficient staff were considered major issues. A logical framework was developed to plan an improvement project to resolve issues raised by clinicians and patients. Improved infrastructure, state‐of‐the‐art equipment, well maintained facilities, IT‐based communication, motivated doctors, nurses and support staff, improved patient care and improved drug availability were considered the main project outputs for improving performance. The proposed framework is currently being used as a continuous quality improvement tool, providing a planning, implementing, monitoring and evaluating framework for the quality improvement measures on a sustainable basis.

The combined cause and effect diagram and logical framework analysis is a novel and effective approach to improving intensive care performance. Similar approaches could be adopted in any intensive care unit.

The paper focuses on a uniform model that can be applied to most intensive care units.

In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners.

Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation.

The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. The method of validation depends on the practitioners’ knowledge on the relationship between cause and effect and controllability of the causes.

The roadmap thus evolved for the validation of root causes will be of great value to the practitioners as it is expected to help them understand the ground reality in an unambiguous manner resulting in a superior strategy for cause validation and corrective actions.

The fundamental concern of this research study is to learn the quality and efficiency of US healthcare services. It seeks to examine the impact of quality and efficiency on various stakeholders to achieve the best value for each dollar spent for healthcare. The study aims to offer insights on quality reformation efforts, contemporary healthcare policy and a forthcoming change shaped by the Federal healthcare fiscal policy and to recommend the improvement objective by comparing the US healthcare system with those of other developed nations.

The US healthcare system is examined utilizing various data on recent trends in: spending, budgetary implications, economic indicators, i.e. GDP, inflation, wage and population growth. Process maps, cause and effect diagrams and descriptive data statistics are utilized to understand the various drivers that influence the rising healthcare cost. A proposed cause and effect diagram is presented to offer potential solutions, for significant improvement in US healthcare.

At present, the US healthcare system is of vital interest to the nation's economy and government policy (spending). The US healthcare system is characterized as the world's most expensive yet least effective compared with other nations. Growing healthcare costs have made millions of citizens vulnerable. Major drivers of the healthcare costs are institutionalized medical practices and reimbursement policies, technology‐induced costs and consumer behavior.

Reviewing many articles, congressional reports, internet websites and related material, a simplified process map of the US healthcare system is presented. The financial process map is also created to further understand the overall process that connects the stakeholders in the healthcare system. Factors impacting healthcare are presented by a cause and effect diagram to further simplify the complexities of healthcare. This tool can also be used as a guide to improve efficiency by removing the “waste” from the system. Trend analyses are presented that display the crucial relationship between economic growth and healthcare spending.

There are many articles and reports published on the US healthcare system. However, very few articles have explored, in a comprehensive manner, the links between the economic indicators and measures of the healthcare system and how to reform this system. As a result of the US healthcare system's complex structure, process map and cause‐effect diagrams are utilized to simplify, address and understand. This study linked top‐level factors, i.e. the societal, government policies, healthcare system comparison, potential reformation solutions and the enormity of the recent trends by presenting serious issues associated with US healthcare.

Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables.

This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables.

Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes.

Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress.

This paper describes the use and application of a structured approach to the basic implementation of quality management tools and techniques such as the QC7 tools.

A methodology based around the application of a structured approach to the use of basic quality management tools is adopted, and provides a simple yet powerful means by which the steps of problem solving can be sequentially linked together.

Everyday process examples are used to highlight the benefits of such tools and techniques in contributing to a greater understanding of the process by the process operator or owner. For each example, the use of appropriate tools or techniques are examined and their application analysed. The paper then goes on to discuss the wider implications of quality management tool application within industry and business.

It is not suggested the examples detailed are thoroughly scientific in methodology but they do serve to illustrate that by applying the tools in a systematic manner, even the simplest of processes can be understood in greater detail.

The following are key for the successful implementation, use and success of applying the QC and M7 tools and techniques: in‐depth knowledge of the process; formal training in problem‐solving techniques; appropriateness of tools selected for use; and apply simple models at all levels in the organisation to aid communication and learning.

The paper concludes by arguing that the wider use of the tools, ideally by the process operatives themselves, tangibly lead to a fuller understanding of specific processes. This will ultimately impact upon their organisation.

The application of lean and quality improvement methods is very common in process improvement projects at organisational levels. The purpose of this research is to assess the adoption of Lean Six Sigma™ approaches for addressing a complex process-related issue in the coal industry.

The sticky coal problem was investigated from the perspective of process-related issues. Issues were addressed using a blended Lean value stream of supply chain interfaces and waste minimisation through the Six Sigma™ DMAIC problem-solving approach, taking into consideration cross-organisational processes.

It was found that the tendency to “solve the problem” at the receiving location without communication to the upstream was, and is still, a common practice that led to the main problem of downstream issues. The application of DMAIC Six Sigma™ helped to address the broader problem. The overall operations were improved significantly, showing the reduction of sticky coal/wagon hang-up in the downstream coal handling terminal.

The Lean Six Sigma approaches were adopted using DMAIC across cross-organisational supply chain processes. However, blending Lean and Six Sigma methods needs to be empirically tested across other sectors.

The proposed methodology, using a framework of Lean Six Sigma approaches, could be used to guide practitioners in addressing similar complex and recurring issues in the manufacturing sector.

This research introduces a novel approach to process analysis, selection and contextualised improvement using a combination of Lean Six Sigma™ tools, techniques and methodologies sustained within a supply chain with certified ISO 9001 quality management systems.

Industry 4.0 is regarded as a modern industrial phase wherein convergence between horizontal and vertical production systems, along with their interactions, would enable industries to obtain excellent industrial efficiency. This research thus explores the barriers relevant to Industry 4.0 and their cause and effect relations using the decision-making trial and evaluation laboratory (DEMATEL) technique, and this will assist in the implementation of Industry 4.0 in manufacturing industries.

A comprehensive literature review is carried out to outline the barriers for the Industry 4.0 implementation. The investigative techniques used in this research were conducted utilizing a questionnaire as an instrument for collecting data. The data collected were analysed using the method DEMATEL.

The findings indicate that key barriers to implementing Industry 4.0 include their cause and effect relationships. Reported “implementation costs” have been a critical barrier for Industry 4.0 implementation. Prioritization of barriers and their cause and effect relationships was achieved so that decision-makers could concentrate on overcoming such barriers for Industry 4.0 implementation.

The research is intended to assist executives in recognizing the barriers to Industry 4.0 implementation in their manufacturing industries. Furthermore, the strong functional and empirical importance of emerging and digital manufacturing technologies ensures that understanding the necessary barriers to implementation is important.

This is one of the first few empirical studies in the field of Indian manufacturing industries that uses the DEMATEL method framework as a foundation for recognizing cause-effect interactions among the barriers that affect Industry 4.0.

The purpose of this study is to analyze door-panel alignment defects seen in built-in ovens manufactured in one household appliances company's plant. Alignment defects in oven door panel substantially affect aesthetics of the product which is an important aspect in driving customer preference and satisfaction. Therefore, this study aimed to increase the initial 3.1 sigma level of oven-manufacturing process to at least 4 sigma level by decreasing a particular door-panel alignment defect, which constituted 67.7 percent of the overall alignment defects.

The goals were achieved through a structured Six Sigma implementation with lean element by utilizing various Six Sigma tools such as workflow, Pareto-analysis, measurement system analyses, control-charts, process capability analysis, cause-and effect-diagram and hypotheses tests. A non–value-added step was also eliminated through the lean approach.

Through Six Sigma implementation, the initial 3.1 sigma process performance level has been increased to 4.4 sigma level leading to substantial decrease in alignment defects.

In the quality management literature, not many papers directly deal with aesthetics and appearance problems of the products especially in the household appliances industry. Moreover, hypothesis testing is not frequently used in Six Sigma implementations in the literature. In addition to limited usage of hypothesis testing, very few studies conducted a thorough measurement system analysis. Considering these gaps in the Six Sigma literature, this study fills an important gap in research by implementing a detailed Six Sigma study, enhanced with hypothesis testing and a thorough measurement system analysis, on the aesthetics and appearance of the product.

Familiarizes the reader with various analytical tools and aids available to task groups and others. There are various steps that task groups commonly follow when tackling a problem, and each of these steps has several tools and aids that will assist the group members in visualizing, analysing and understanding the information at hand. Discusses brainstorming, brainwriting, multivoting, nominal group technique, flowcharting, work‐flow diagrams, Pareto charts, cause and effect diagrams, is/is‐not analysis, time plots and scatter diagrams. Offers tips to optimize use of each tool.