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The aim of this paper is to provide insights into the processes that can be and have been adopted by UK business schools as they attempt to meet the Quality Assurance Agency's concern with the standard of quality management and enhancement.

A review of the literature provides interpretations of quality, quality management and quality enhancement. The paper continues by identifying the ways in which priorities in need of improvement are identified. The different “quality” models that are employed are then evaluated in terms of their implementation within business schools.

The paper concludes with emerging reflections that highlight that the most significant aspect in terms of taking forward different models, processes and approaches is the importance of organisational culture.

It is argued that without an awareness of the existing organisational culture the introduction of any model, process or approach will not in itself create or sustain a quality enhancement culture.

This paper aims to show that the extent to which convergence/divergence of a company's quality policies and practices towards/away from those of Six Sigma benchmark policies and practices mirror and anticipate the divergence of its sigma metric (SMs) from quantitative Six Sigma benchmarks. Further, the paper proposes to evaluate the robustness of the quality processes of these three companies and to compare them to that of the Six Sigma benchmark by subjecting these processes to the twin performance shocks of the benchmark Six Sigma 1.5σ allowance for process drift and a 25 percent tightening of customer requirements.

Using a novel methodology more appropriate to the critical quality characteristics of typical service industry companies, the paper computes a set of SMs for each company that is richer and broader than the metrics found in standard Six Sigma tables. This new methodology is based on the empirically observed defect rates that are currently being generated by a service process. Further, based on the available empirical data, the paper compared these metrics to the Six Sigma benchmarks.

First, the paper shows that it is possible to compute a broad array of Six Sigma metrics for service businesses based on defect rate data. Second, the results confirm the central proposition of the research to the effect that the divergence/convergence of the qualitative characteristics of a company's quality system from benchmark Six Sigma policies and practices mirror and anticipate the convergence/divergence of the company's quality metrics from the Six Sigma benchmark. Third, the research produced the unanticipated result that the quantitative quality performance of high‐performing service businesses on the Six Sigma metrics are much lower than anticipated and below what is normally achieved by their manufacturing counterparts. The results were also used to do an evaluation of the Taguchi robustness of service processes.

First, the paper demonstrates that traditional Six Sigma computational methodology for generating Six Sigma metrics that is prevalent in manufacturing applies equally to service businesses. Second, the parallel convergence of the qualitative characteristics of a company's quality system towards Six Sigma practices and its quantitative metrics towards the Six Sigma benchmark means that primacy must be given to quality practices as the drivers of quality improvement. Third, the fact that high‐performing service businesses achieve Six Sigma measures that are so low compared to their manufacturing counterparts seems to point either to some key measurement challenges in deploying Six Sigma in service industries or to the need to further change Six Sigma methodology to make it more applicable to these businesses.

This study empirically examines the effect of shop‐floor communication on implementation effectiveness of process management practices, and on the corresponding quality performance gained through process management implementation. It deals with four types of communication on the shop floor (small group problem solving, feedback, instructive communication, supervisory interaction facilitation) and three process management practices (process control, preventive maintenance, housekeeping).

Analysis of variance (ANOVA) and regression techniques were used to test the hypothesized relationships. Data were collected from 238 manufacturing plants through a questionnaire survey conducted in eight countries to develop reliable and valid measurement scales for operations management.

The statistical results demonstrate the positive effect of shop‐floor communication on the implementation of process management practices and the resultant quality performance. The results also suggest that each type of shop‐floor communication differently affects the way in which process management practices are implemented to influence quality performance.

Although the existing literature of quality management highlights the importance of communication and information management for the successful implementation of quality management, little detailed study has been conducted on how specific types of communication support quality management practices to obtain quality performance. This study contributes to the literature by breaking down communication into four types and providing specific empirical evidence on the relationship between each type of communication, process management practices, and quality performance.

Important management practices that lead to the achievement of quality and high performance fall under the areas of leadership, information management, strategic planning, human resource management, product development, process management, and customer focus, which represent the principal focus areas of the Malcolm Baldrige National Quality Award criteria. Aims to identify the key practices that lead to competitive success from a process viewpoint, and provide examples from Baldrige winners and other leading companies.

The intention of this paper is to propose a methodology for interactions between the two quality tools of quality function deployment (QFD) and failure mode effects analysis (FMEA), and place an emphasis on their common features. The paper will also emphasise the value that both tools have when used throughout the product development cycle. An example of the method described will be highlighted within Ford Motor Company that will demonstrate the quality and resource benefits achievable when these two tools are used in conjunction with one another. This example will illustrate how, through the use of crossfunctional and multidisciplined teamwork, QFD and FMEA can be linked into systems engineering and a quality operating system with far‐reaching benefits.

This special “Anbar Abstracts” issue of Industrial Management & Data Systems is split into six sections covering abstracts under the following headings: Industrial Management; Industrial Engineering and Work Study; Industrial Design; Quality Management; Manufacturing Strategy and Production; Information Systems.

The purpose of this paper is to establish mechanisms for process improvement so that production efficiency and product quality can be expected, and create a sustainable development in terms of circular economy.

The authors obtain a critical value from statistical hypothesis testing, and thereby construct a process capability indices chart, which both lowers the chance of quality level misjudgment caused by sampling error and provides reference for the processes improvement in poor quality levels. The authors used the bottom bracket of bicycles as an example to demonstrate the model and methods proposed in this study.

This approach enables us to plot multiple quality characteristics, despite varying attributes and specifications, onto the same process capability analysis chart. And it therefore increases accuracy and precision to reduce rework and scrap rates (reduce), increase product availability, reduce maintenance frequency and increase reuse (reuse), increase the recycle rates of components (recycle) and lengthen service life, which will delay recovery time (recovery).

Parts manufacturers in the industry chain can upload their production data to the cloud platform. The quality control center of the bicycle manufacturer can utilized the production data analysis model to identify critical-to-quality characteristics. The platform also offers reference for improvement and adds the improvement achievements and experience to its knowledge management to provide the entire industry chain. Feedback is also given to the R&D department of the bicycle manufacturer as reference for more robust product designs, more reasonable tolerance designs, and selection criteria for better parts suppliers, thereby forming an intelligent manufacturing loop system.

The purpose of this paper is to describe a structured framework to implement and sustain a quality costing system (QCS) based on process cost modeling (PCM) in process industries.

After reviewing and analyzing various cost accounting methodologies practiced by companies the research objectives were achieved by acknowledging the need to attach fuzziness to notion of “quality”. The imprecise, vague, and complex information related to cost items under Prevention, Appraisal and Failure (PAF) segments is synthesized using well‐established fuzzy principles. A case based approach from process industry is discussed to implement and sustain quality costing system after prioritizing the processes.

While conforming on the results of prior research on practice of quality costing approaches and the problems faced by the companies in implementing a quality management system the fuzzy approach (owing to its sound logic and effectiveness in identifying the vagueness and imprecision in human judgment) is successfully applied to elicit expert opinion regarding the importance of cost items. The information so obtained after fuzzy synthesis is used to set up priority with respect to the processes which can provide necessary help to managers/practioneners to invest efforts in reduction of cost of non‐conformances (CONC) and optimal allocation of resources.

The approach discussed in the paper will be helpful to managers; quality practitioners to set up/improve various quality improvement initiatives for successful implementation of quality costing system.

The framework discussed in the paper provides a novel approach to implement QCS by using PCM after judicious selection of the processes and cost items.

This research is elucidating quality control theories to reduce variation in chocolate manufacturing process in the UK food company that will help maintain the processes stable and predictable. The purpose of this paper is to reduce defects of the output; to identify the root causes of variation; to establish and implement solutions to this variation problem; and to establish a control system to monitor and report any variation in the process.

The authors use experimental case study of a chocolate company to achieve the objective. In this paper, the authors predominantly use established theory define–measure–analyse–improve–control, customised to the case of the chocolate factory to reduce variations in production processes.

The results confirm that customised-traditional theoretical quality models will support manufacturing companies to maintain customer satisfaction while enhancing quality and reliability.

Implementation of customised approach reduced the rate of defect from 8 to 3.7 per cent. The implications of reduced variation are improved product quality; reprocessing elimination; and a more stable process that support sustainability and reliability in producing chocolates to meet customer needs.

The authors used an experimental-based case study approach to test with one company. Testing in multiple case companies may help to generalise results.

The research study experimentally tested quality approach with a real case company and hence the findings of this study can be applied to other cases working in similar settings.

Total quality management does improve organizational performance and remains the most viable long‐term business strategy around. These were the findings of a recent report entitled “TQM: Forging a Need or Falling Behind?”, commissioned by Development Dimensions International of Pittsburgh, the Quality & Productivity Management Association of Schaumburg, Illinois, and Industry Week, which were based on interviews with 6,500 people in 84 organizations. However, on considering the various elements which help or hinder TQM implementation, training emerged as the one successful theme in successful programmes.