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Presents a new procedure for quality control and quality assurance in scenarios where several variables and attributes have to be monitored. The proposed procedure, named integrated process control, begins with the definition of control stations on the production line, where a single chart that aggregates several variables and attributes is used. This procedure is complemented by using Pareto charts, which determine the quality characteristics contributing the most to the number of defectives. The integrated process control also uses traditional control charts; however, these are used selectively following the indication of the Pareto charts. The joint use of these tools facilitates the identification and solution of quality problems, allowing the improvement actions to be taken at the right time and place. The key advantages of the proposed procedure are: the ability to handle variables and attributes on a single integrated chart, the statistical approach, providing a solid basis for decision making, and the strong managerial appeal provided by the integrated charts.

The purpose of this paper is to propose an integrated framework to simultaneously identify and improve healthcare processes that are important from the healthcare provider's and patient's perspectives.

A modified quality function deployment (QFD) chart is introduced to the field of healthcare quality assurance. A healthcare service example is used to demonstrate the utility of the proposed chart.

The proposed framework is versatile and can be used in a wide variety of healthcare quality improvement contexts, wherein, two different perspectives are needed to be considered for identifying and improving critical healthcare processes.

The modified QFD chart used in conjunction with the stacked Pareto chart will facilitate the identification of key performance metrics from the patient's and the hospital's perspectives. Subsequently, the chief contributory factors at different levels are identified in a very efficient manner.

Healthcare quality improvement professionals will be able to use the proposed modified QFD chart in association with stacked Pareto chart for effective quality assurance.

This study aims to apply statistical process control (SPC) techniques to improve the quality and efficiency of the processes in a restaurant.

SPC tools such as check sheet, cause-and-effect analysis, Pareto chart, control charts and SERVQUAL methodology is adapted to measure and improve the quality of the system.

At the end, some suggestions for improving the quality of service system are proposed in this study to complete the research.

The most difficult part of this study was data collection. Because of the situation of the restaurant, the number of customers does not exceed 60 every day. Another limitation of this study is that the samples have been collected from the same population each day, and it may affect the final result.

The research is based on the present service system at a restaurant, located at a university campus in Cyprus.

A similar study can be applied in the social sector to evaluate and improve service quality.

In this paper, for the first time, SPC and SERVQUAL are used to evaluate and improve quality in the service sector.

This study aims to utilize DMAIC methodology along with value stream mapping and other Lean Six Sigma tools in a major automobile light manufacturing industry to reduce defect rates and increase production capacity in their manufacturing line. The study also proposes a modified framework based on lean principles and FlexSim to identify and reduce waste in the selected industry.

A Lean Six Sigma modified framework has been deployed with DMAIC to reduce the defect rate and increase the production rate. Various tools like value stream mapping, brainstorming, Pareto charts, 5S, kanban, etc. have been used at different phases of DMAIC targeting wastes and inventory in the production line. Also, a simulation model has been utilized for the automobile light manufacturing industry to improve the machine utilization time with varying batch sizes.

The results of the study indicated a 53% reduction in defect rates. Thus, there would be an expected improvement in sigma value from 3.78 to 3.89 and a reduction in defects per million opportunities (DPMO) from 11,244 to 8,493. Additionally, simulation model using FlexSim was developed, and the optimum ordering batch size of raw material was obtained. It was also analyzed that idle time for various stations could be reduced by up to 30%.

The utilized framework helps identify defects for managers to increase production efficiency. The workers, operators and supervisors on the production line also need to be trained regularly for identifying the areas of improvement.

The modified Lean Six Sigma framework used in this study includes FlexSim simulation to make the framework robust, which has not been used with LSS tools in the literature studied. Also, the LSS finds very less application in the manufacturing domain, considering which this study tends to add value in existing literature taking a case of an automobile light manufacturing industry.

The purpose of this paper is to present the application of a procedure for the quality control of stainless steel tubes produced for automotive exhaust systems from a leading company in the steel sector, based on the Delphi method in accordance with the ISO/TS 16949:2009 and the ISO 9000:2008. Using Delphi methodology, it was possible to identify the main problems in the production lines object of the study, the main defects and their causes. Statistical methods were used to monitor process compliance and capacity. The panel of experts involved in Delphi method was able to identify causes of non‐compliance and suggest corrective actions.

The quality procedure implemented involves the application of the Delphi method and the ISO/TS 16949:2009 standard in conjunction with ISO 9000:2008 to the production line of welded tubes for exhaust systems. The statistical methods used to monitor the process were mainly control charts. Capability index, Cp and Cpk, were used to measure the process attitude to produce compliant outputs. Dimensional data were acquired by non‐destructive testing on diameters and X‐R charts were used to graphically represent the process state of control. Destructive tests were performed to monitor the welding quality and P‐chart were used to assess the proportion of nonconforming units.

In this work, a procedure was developed in order to characterize the production process of TXM tubes realized in the line 31 of the leader company plant. The use of Delphi methodology, in order to incorporate experts opinions in the quality control of stainless steel tubes, was one of the main points of this work. The panel of experts worked together to identify process issues, define their causes and propose corrective actions. The paper provides an overview about the quality approach of one of the world's largest companies in the production of steel and shows also how the statistical tools are used in order to manage process behavior.

The value of this paper is to illustrate an innovative approach to a real life quality problem; it demonstrates how the application of qualitative and quantitative quality instruments in accordance with technical specification can help in increasing and maintaining product compliance and in optimizing the management of resources.

This study aims to introduce the reader to some problems faced by safety practitioners operating within an airline safety department, particularly risk assessment subjectivity, and processing of flight data monitoring events. In doing so, it attempts to propose solutions to these issues.

Quality management tools, including six sigma, in combination with flight data monitoring, are proposed as a solution to the issues identified.

The proposed solutions reduce the subjectivity of some risk assessments and help airlines to efficiently process flight data monitoring events.

This paper presents a two-part case study of how these issues have been dealt with by an airline. However, as demonstrated by the literature review, there seems to exist further advanced methods, some of them still in a developmental stage, to deal more effectively with the problems discussed.

This study is particularly directed and more valuable to small-scale airlines. These are more susceptible to the lack of resources needed to implement advanced approaches into the safety management system, but still want to adopt a systematic way of conducting business. Furthermore, it highlights common issues faced by safety practitioners in airlines and should hopefully stimulate the discussion around the topic and promote other academics/practitioners to share viable solutions.

Traditional statistical tools are subject to certain constraints when they are applied to quality control in industries where the number of faults per working day is limited. An effective quality monitoring and analyzing tool is therefore needed to meet the specific requirements of these industrial sectors. Proposes a so‐called “Cause‐classified Control Chart”, based on fieldwork in the Nanchang Telecommunications Office of China. Trial results from several posts and telecommunications offices in China in recent years have positively shown that the Cause‐Classified Control Chart is an effective tool for quality enhancement in these specific industrial sectors.

The purpose of this paper is to apply the Six Sigma DMAIC methodology in order to reduce the rejections experienced in the manufacturing of the doors belonging to a telecommunication cabinet.

The process involved joining of sheet metal and hinge using welding operations with the help of a fixture. The methodology used is the structured DMAIC method in order to identify the root cause for the rejections and solve it.

The paper provides insights about the identification of the root cause for the defects and the solution to overcome it, and also the benefits that were obtained as a result of the application of the solution.

This methodology has been applied to the variation observed in the dimensions of a particular component to be welded with a main part. This approach can be used to find such dimensional variations.

This study has been successfully carried out in a medium-scale industry which has total quality management in practice.

Six Sigma DMAIC was necessary for the identification and reduction of the defects which arose in the sheet metal and welding operations, and had to be resolved in order to increase the bottom-line.

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.

Quality management (QM) cannot be assured unless some objective assessments are undertaken. A number of tools and techniques are available to conduct such analysis. Although some of them are product or service specific, however, a few basic tools and techniques are commonly used in manufacturing firms. This study focuses on the state of application of QM tools and techniques in small and medium industries (SMIs). The findings reveal that by‐and‐large, lack of methodical analysis is a major weakness of SMIs. Still some rule‐of‐thumb and subjective observations are dominating over objective evaluation in the process of quality control decisions. A few case studies which have been conducted, and one that has been briefly reported here, also support this conclusion. The methodology of the study has three folds: literature review, survey in SMIs and case studies.