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Traditional, single time‐period models of quality cost expenditures assume static conditions and ignore the impact of the learning curve effect on a firm’s product quality, and that of quality improvement efforts by the competitors. In this paper we incorporate both factors in a dynamic model of quality cost expenditures. The interactions not only show how firms can remain competitive, but also how they can achieve a competitive advantage. In addition, the dynamic model shows that quality learning will always lead to fewer product defects, but that total quality cost on a per unit basis will vary according to the interaction of these two factors. This model should also help managers plan, evaluate, and justify voluntary quality cost expenditures.

Existing quality‐cost models have been criticized for their imprecision and inadequate theoretical justification. Attempts to remedy these deficiencies by using systems dynamics to build a generic model relating quality conformance levels to the quality‐cost categories of prevention, appraisal and failure (PAF). Outlines in depth the assumptions underlying the model’s structure and links model parameters to published empirical data. Explores the model’s sensitivities to changes in factors including different initial values of conformance quality. Determines the potential for improvements in quarterly and cumulative quality costs by changing the PAF cost levels.

The purpose of this paper is to critically examine existing models for cost of quality. Having identified issues and limitations of historic models, develop and implement a novel, structured hybrid cost of quality model to identify and effectively manage cost of company’s product.

A theoretical framework is proposed based on an integration of three existing, historical cost of quality models into a structured hybrid model. Subsequently, an exploratory pilot case study in a manufacturing environment is described that illustrates the value of the model.

The paper manages to find how a hybrid model can help identify cost of quality more accurately than the traditional models. Thanks to the new model, the author shows how gaps between product’s theoretical and actual costs can be highlighted. This allows management to drive down cost of quality and improve business performance.

The model would benefit from a company-wide implementation. The present study provides a starting point for further research in the international manufacturing sector.

The framework improves the knowledge of cost of quality by providing a new case study with full results and analysis from a UK-based manufacturing company. It provides a critical re-evaluation of available literature, including the most recent publications as far as practically possible within timescale available. The study shows the importance of comprehensive cost collection if companies are to have the right data needed to manage business excellence.

The paper presents a development of the first structured hybrid model for measuring cost of quality using the strongest points of main three approaches and addresses their limitations. It gives new arguments against allocation of some cost elements within BS 6143-2:1990, resulting in recommendations for further brainstorming of pros and cons of the suggestion.

Traditionally, process improvement is considered a defect prevention effort. Current cost models consider the coupled effect of both prevention and appraisal costs on the cost of failure. This paper proposes a new model for the cost of quality, which captures the value of continuous process improvement in achieving economic operation. The model is developed to incorporate two cost functions. The first accounts for quality related costs incurred while maintaining a stable level of operation, while the second accounts for the cost of process improvement. Using incremental economics, the two cost functions are assembled and an economic criterion for evaluating improvement alternatives is developed. Numerical examples are used to illustrate potential applications and performance of the model.

The theory and practice of Quality Assurance in Health is drawn from and involves many disciplines and professions. The dangers of imprecisions in the use of terms can lead to confusion. The glossary prepared by the author aims to provide a firm foundation of definition, thereby avoiding squabbles over semantics.

Quality improvement decisions are the catalyst for substantial technological improvements being made in the manufacturing sector. The new technology, however, has developed faster than techniques for evaluating capital investments in such improvements. This is largely because the benefits of quality improvement technology are difficult to quantify. The Taguchi loss function is incorporated into a net present value capital budgeting technique to provide an estimate of these benefits. Describes the loss function in relation to key quality costs: appraisal and prevention costs, and internal and external failure costs. External failure cost savings are generated by reducing variability in the manufacturing process. These savings are then compared with the cost of the quality improving technology. Results indicate that these savings can be substantial, depending on the achieved reduction in the process variability, the cost of capital, and on the estimate of the cost of processing a customer’s return of the product.

This paper proposes a decision support model that can be used to help decide the destination of defective products, for mass production industries. The objective of this model is to reduce the cost of the defect, and consequently reduce the total quality costs.

The decision model was developed based on the theory of quality costs and decision-making models, considering the practical aspects of reality through data collection, observation and experience in Industrial Pole of Manaus (Brazil) industries. A decision model adjusted to reality assists in the construction of the decision process, indicating the facts, data collection and the planning of the actions to choose the best alternative.

The specific contributions of this research are: (1) define a sequential structure of actions, effects and costs associated with defective items; (2) allow a comprehensive approach to failure costs, including various elements of lost opportunity costs; (3) minimize failure costs, and consequently reduce total quality costs, without necessarily investing in prevention and assessment; (4) describe the use and application of the built theory; (5) identify the quality cost elements most representative in existence of defective items; and (6) identify improvement points in the management of possible future defective items.

Much of the work of implementation of quality cost models do not emphasize the analysis of the destination of defective items. Also, there are no studies that use decision models with identification, accounting and evaluation of effects and criteria of quality, productivity and cost to define the destination of manufacture defective items.

There is consensus that money invested in quality programs provides a high rate of return, but disagreement on how the optimal level of quality investment can be modeled. It has been postulated that there is no correct cost of quality (COQ) model since quality costs are dynamic and firm specific. Firms tend to move to new quality levels over time as they increase their prevention activities aimed at detecting and eliminating cause of variation. Many firms tend to misallocate quality spending by investing the greatest percentage of quality costs to the lowest yielding categories and the lowest percentage of quality costs to the highest yielding categories. Examines the various COQ models that have been proposed and explains the misallocation of quality investment by firms. Describes why quality initiatives undertaken by a firm are generally consistent with corporate goals and strategy, the maturity level of a firm, and management commitment.