Quality Management Decision-making Research Articles

The application of operation research in the quality management engineering

The integration of Operations Research (OR) principles into Quality Management Engineering constitutes a powerful strategy for enhancing product and service quality throughout the entire lifecycle. This synergistic relationship unfolds within the context of OR, a discipline rooted in mathematical models, analytical methods, and decision-making tools, originally developed during World War II. Quality Management Engineering, built upon principles like Total Quality Management (TQM) and Six Sigma methodologies, systematically combines engineering principles with quality management techniques to ensure consistent high-quality outcomes. This interdisciplinary approach proves particularly critical in industries emphasizing precision, reliability, and efficiency. The application of OR in Quality Management Engineering encompasses diverse facets, including process optimization, supply chain management, quality control, root cause analysis, resource allocation, and risk management. This integration leverages mathematical modelling, statistical analysis, and optimization techniques to systematically improve and sustain product and process quality. Emphasizing continuous improvement, the collaboration integrates Lean principles, waste reduction strategies, and a commitment to ongoing assessment. The partnership between OR and Quality Management Engineering remains adaptable to changing business landscapes, addressing human factors, environmental considerations, and the era of data-driven decision-making. This abstract highlights the evolution of OR and its contribution to creating a structured, data-driven, and analytical approach to decision-making in quality management. Ultimately, this integration shapes efficient, resilient, and quality-focused organizations, positioning them for success and competitiveness in dynamic industries.

Enhancing Process Stability and Quality Management: A Comprehensive Analysis of Process Capability Indices

Process Capability Indices such as Process Capability Index (Cp) and Corrected Process Capability Index (Cpk), along with Process Performance Index (Pp) and Process Performance Corrected Index (Ppk), are most commonly used tools in quality management within manufacturing processes. They determine whether a process is capable of producing products within established tolerance limits, addressing both short-term and long-term variability. Despite widespread use, the analysis of Process Capability Indices often overlooks special variability within processes, which may lead to misleading interpretations of a process's capability, especially when the determination of tolerance limits is inadequately conducted. This article aims to verify the hypothesis that current analyses of Process Capability Indices fail to consider special variability, which could mislead the interpretation of a process's ability to meet its specifications. Statistical analyses were conducted using the Minitab software, based on dynamic viscosity measurements from the production process of solvent-based paint, to explore the implications of special variability on the interpretation of Process Capability Indices. The study revealed that while Process Capability Indices are useful for identifying quality management opportunities, their effectiveness is limited when special variability is present, often resulting in misinterpretations of a process's true capabilities. The findings highlight the need for methodologies that incorporate considerations of all forms of variability to ensure accurate process capability assessments. This gap in traditional analyses can affect the strategic decision-making in quality management, suggesting a critical area for further research and methodological development. The research confirms the need for a revised approach in analyzing Process Capability Indices, advocating for advanced methods that accurately reflect all forms of variability to improve quality management practices. Future research should focus on developing these methodologies to ensure more reliable and effective use of Process Capability Indices in quality management.

Decision-Making Procedures and Their Relation to Knowledge Management and Quality Management

The environment in which managers currently operate is dynamic and turbulent. This fact affects the great complexity and dynamism of changes. Thus, decision-making becomes more complex in the context of sustainability. Decisive decision-making is becoming rare, and the challenge of globalization is increasing. Under its influence, decision-making is no longer deterministic. Decision-making processes prevail in conditions of uncertainty. In this context, there is a very intense need to be acquainted with progressive tools to support decision-making and management and to apply the acquired knowledge in practice. This paper focuses on three related areas. We are talking about knowledge management in connection with the most important contributing element—decision-making with quality management. We deal with the characteristics of the individual areas, defining their mutual relationship on a systemic basis. The paper also points to the necessary connection between theory and practice. More specifically, it points to the practical applications of management to decision-making as a managerial function and, at the same time, related to decision-making in quality management. Subsequently, we define the links to knowledge management with an emphasis on the use of procedures, methods, and knowledge in the decision-making process, which we use in theory and practice in quality management.

Regional collaborative urban air quality management: case studies across Great Britain

Almost a third of local authorities across Great Britain have declared air quality management areas (AQMAs), which are the focus of concerted actions to reduce unacceptably high concentrations of prescribed air pollutants by a date specified in regulations. Local government has been provided with guidance from central governments on the use of modelling and monitoring tools, as part of a local air quality review and assessment process. Use of the various tools and the interpretation of the findings have not been consistent across Great Britain. As a result, AQMAs are neither uniform in shape nor in the decision-making processes leading to their declaration. Local authorities have collaborated in many parts of the country, using working groups to share experiences and resources. This paper examines groupings from three regions of Great Britain; London, the West Midlands and the former-Avon area of Southwest England. An examination of the methods and tools used collaboratively has illustrated variation in local air quality management decision-making and AQMA designation. This has implications for delivering the necessary improvements to achieve the UK's national air quality objectives.