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A majority of products for manufacturing or consumers have multiple characteristics that must meet the requirements of the customer. For example, a steel beam any have dimensional tolerances on its length, width, or height and functional tolerances on its strength. The characteristics are influenced by different processes that create the product. For an individual characteristic, process capability measures exist that convey the degree to which the characteristic meets the specification requirements. Such measures may indicate the proportion of nonconforming product related to the particular characteristic, under some distributional assumptions of the characteristic. For products with multiple characteristics, the unit costs of rectification may be different, making the satisfaction of some characteristics meeting customer requirements more important than others. In this paper, an aggregate process capability performance measure is developed that considers the relative importance of the characteristic based on unit costs of nonconformance. Based on the aggregate measure, appropriate process capability measures for the individual measures are also derived. Bounds on the aggregate capability measures are also established.

The study aims to introduce two new models of project scheduling by incorporating potential quality loss cost (PQLC) in time–cost tradeoff problems by overcoming the drawbacks of the existing Kim, Khang and Hwang (KKH) model. The proposed methods are named the Revised KKH-I (RKKH-I) and Revised KKH-II (RKKH-II) models for project scheduling.

The performance of the existing KKH model has been tested using a numerical example followed by the identification of the main shortcomings of the KKH method. Later, a concrete effort has been made to address its shortcomings while improving its performance significantly. The comparative analysis of the Revised KKH models with the original model has also been presented along with sensitivity analyses.

The study recognizes that the construct on which the original KKH method was built is important; however, certain drawbacks make it unable to consider PQLC in projects, thus making its practical use questionable. The comparative analysis of the proposed methodology with the original method demonstrated that the new models (RKHH-I and II) are more comprehensive and intelligent than the existing KKH model.

The comparative analysis of the original KKH model and its improved version reveals that the revised model is far more suitable for project scheduling. The study is important for project managers who recognize project scheduling being one of the key parameters associated with project management process, crucial to control every day during the management of projects.

The purpose of this paper is to develop an optimization model to better allocate cost of quality (COQ) in the supply chain (SC). In addition, the paper provides a roadmap based on COQ that allocates limited given budget among the SC entities.

This paper presents a comprehensive SC model while introducing six different scenarios, where each scenario minimizes fixed costs and COQ of the SC.

The results showed that the highest portion of the COQ should be allocated at the retailer echelon while the lowest portion should be kept at the manufacturer echelon. The findings also presented that the retailer should always maintain the highest quality level (QL) compared to the manufacturer and supplier.

Considering prevention, appraisal and failure (PAF) cost model, this research defines the tradeoff among PA, F costs, QL and material flow in the SC network; no work has been published regarding integrating PAF, QL and material flow into SC modeling.

Though the components and concepts of cost of quality (COQ) are well understood in the domain of manufacturing, only limited data are available from the construction industry for various reasons. The present study seeks to establish a relationship between project defect score (pds), representing the quality of construction in the project, and the COQ in the building construction industry. The study also seeks to estimate the contributions of the various components to the overall COQ in the construction industry, along with their distribution and interrelationships among themselves.

A framework for estimating COQ was developed, and the data regarding prevention, appraisal and failure cost were collected from 122 projects. Various mathematical and statistical tools like Pearson's correlation, multiple linear regression (MLR) and curve fitting have been used for data analysis.

The prevention–appraisal–failure (PAF) model was found to be appropriate to estimate COQ, and the prevention, appraisal, conformance cost (CC) and failure cost were found to vary between 0.19 and 8%, 0.05 and 5%, 0.3 and 10% and 0.01 and 5%, respectively, whereas the overall COQ varied from 3.5 to 10.01% of the project cost. The correlations between various components of COQ were found to be significant. MLR suggested that appraisal cost is more impactful in reducing failure cost than prevention cost. Using curve fitting, the cubic model appropriately represented all interrelationships. The optimal overall COQ was found to be 3.86%, and the reasons for low COQ have been explored.

The study evaluates the applicability of available models for COQ calculations for the construction industry and presents a framework to estimate its components. The study also explores the interrelationship between the various components of COQ and presents a generalized relationship between COQ and the pds.

The purpose of this paper is to present an integrated cost of quality ‐ activity‐based costing (COQ‐ABC) framework for measuring quality costs under ABC. The main deficiencies of most COQ systems are: (1) no consensus method to allocate overhead costs to COQ elements, (2) the failure to trace quality costs to their sources, and (3) the lack of information about how indirect workers spend their time on various activities. These deficiencies can be easily overcome under ABC together with work sampling. The cost and nonfinancial information achieved from the integrated COQ‐ABC system can be used to identify the magnitude of the quality improvement opportunities, to identify where the quality improvement opportunities exist, and to continuously plan the quality improvement programs and control quality costs. The ultimate goal of the integrated COQ‐ABC system will be to continuously improve processes/activities/quality so that no defects at all are produced and quality cost measurement ultimately becomes unnecessary.

As the complexity of the multi-component products increases the quality of these products becomes increasingly difficult to control throughout the supply chain. The first step to manufacturing a quality product is to ensure that the product components from suppliers meet specifications. Product quality can be controlled through sampling inspection of the components. The paper aims to discuss these issues.

The model presented in this paper was developed to determine the optimal sampling levels for incoming lots containing parts for production and assembly of multi-component systems. The main objective of the model is to minimize the expected cost that is associated with a nonconforming item reaching assembly.

In this research, the results showed that even with limited time available for inspection, performing sampling inspection significantly reduced the expected cost of a nonconforming item reaching assembly. The model, solved by the evolutionary algorithm, was able to provide a meaningful, near optimal solution to the problem.

In this model the time available for inspection is limited, the distribution of defects is assumed to follow the binomial distribution, and the distribution of accepting the lot with defects follows the hypergeometric distribution. In addition, the inspection is considered to be accurate and, if a nonconforming item is found in the inspected sample, the entire lot is rejected. An example is given with real world data and the results are discussed as they relate to supply chain management and quality.

The purpose of this paper is to explore the impact of the cost of quality (COQ) expenditure allocations on a capacitated supply chain (SC) network.

This paper proposes a non-linear optimization model which integrates the opportunity cost (OC) (i.e. customer satisfaction cost), into the COQ with consideration of the QL in the supply chain network design decisions. In addition, it examines the effect of considering an investment at each SC echelon to ensure the best overall QL. A numerical example is presented to illustrate the behavior of the model.

The results show how the QL, COQ and facility location decisions change when incorporating the OC, investments and transportation costs into the SC model.

The novelty of this paper is that it considers the effect of OC, investment at each echelon and transportation costs on SC design by minimizing the overall spending on the COQ. These issues have not been explored, and for that reason, this paper contributes to the understanding of the critical factors that optimizes the SC COQ.

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.

Describes the quality journey that began as quality control circles, moved to implement an international quality management system, and now continues its TQM programme called “Quest for excellence”. Kowloon‐Canton Railway Corporation is the first railway company in Asia to have a part of its operations ISO 9001 certified. Examines some of the important lessons learned when several hundred non‐English‐speaking employees were required to be involved in the process of preparing for certification.