In search of an optimal cost of quality: an integrated framework of operational efficiency and strategic effectiveness

Yasin, Mahmoud M.; Czuchry, Andrew J.; Dorsch, Jeffrey J.; Small, Michael H.

doi:10.1016/s0923-4748(99)00004-1

Cited by 22 publications

(32 citation statements)

References 6 publications

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“…The authors employed simulated annealing to determine a heuristic solution to the proposed model. Yasin et al (1999) introduced a framework for applying optimal control theory to the second method of Lundvall and Juran (Juran et al, 1974). This framework was also employed in a building project that focuses on the impact of failures (Hall and Tomkins, 2001).…”

Section: Literature Reviewmentioning

confidence: 99%

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Cost-of-Quality Optimization via Zero-One Polynomial Programming

Lim¹,

Sherali

Glickman

2014

IIE Transactions

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This article considers a Cost-of-Quality (CoQ) optimization problem that finds an optimal allocation of prevention and inspection resources to minimize the expected total quality costs under a prevention-appraisal-failure framework, where the quality costs in the proposed model are involved with prevention, inspection, and correction of internal and external failures. Commencing with a simple structure of the problem, the complexity of the problem is progressively increased by accommodating realistic scenarios regarding preventive, appraisal, and corrective actions. The resulting problem is formulated as a zero-one polynomial program, which can be solved either directly using a mixed-integer nonlinear programming solver such as BARON or using a more conventional Mixed-Integer Linear Programming (MILP) solver such as CPLEX after performing an appropriate linearization step. Two case studies from the literature (related to a lamp manufacturing context and an order entry process) are examined to illustrate how the proposed model can be utilized to find optimal inspection and prevention strategies, as well as to analyze sensitivity with respect to different cost parameters. A comparative numerical study of using the aforementioned solvers to optimize the respective model formulations is provided. The results provide insights into the use of such quantitative methods for optimizing the CoQ and indicate the efficacy of using the linearized MILP model for this purpose.

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Section: Literature Reviewmentioning

confidence: 99%

“…Nonetheless, the resolution between these two viewpoints depends on the specific process and the related cost parameters (Castillo-Villa et al, 2011). Furthermore, as indicated in Yasin et al (1999), practice managers still face decision-making problems in order to determine how much to spend on quality improvement initiatives.…”

Section: Introductionmentioning

confidence: 99%

Cost-of-Quality Optimization via Zero-One Polynomial Programming

Lim¹,

Sherali

Glickman

2014

IIE Transactions

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“…Critical quality costs are found with the help of Pareto analysis and are shown in figure 3. This is based on Pareto law, which tells that there are only a few cost items or heads which are responsible for major share in the total cost of quality [8].This gives the indication to the management to emphasis more on these quality costs rather than to all. This will save the money as well as the time.…”

Section: Pareto Analysis Of Quality Costsmentioning

confidence: 99%

Development of Model for Quality Costing in a Medium Scale Industry-A Case Study

Sahu¹

2013

IOSR-JMCE

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Quality c o s t s pl ay s v i t a l r ol e in improving productivity. These costs are typically categorized into costs of prevention, appraisal, internal and external failure. Like other activities of business, quality costs can be programmed, budgeted, measured and analyzed to attain the objective of better quality at lower cost. Quality costs is the basis by which investments in quality programs may be evaluated in terms of cost improvement , profit enhancement and other benefits for plants and companies from these programs. The cost of quality is an increasingly important issue in the debates over quality. There was a mistaken notion that achievement of better quality requires higher costs. It was the myth that prevented many Indian companies to invest more on quality cost related programs. In this article the authors made an attempt to identify the different types of quality costs in a medium scale industry because the small and medium scale industries pay very little attention towards finding and developing a system for knowing & optimizing the cost of achieving quality. A model is proposed to identify the different quality costs in a medium scale industry and is further implemented. It has been found some quality costs are more critical and require greater attention.

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“…Finally, the model also implies that there exists a trade-off between prevention appraisal costs and failure costs. [3] The traditional model only concerned about the relationship between prevention appraisal costs and the cost of failure, and neglected the impact of enterprises' external environment or enterprises' strategy on the quality management. The quality management is an entire system whose optimization is decided by the outside force strategic objective.…”

Section: The Model Of Quality Costs Based On Strategic Coordinationmentioning

confidence: 99%

The Study of Quality Costs Optimization Based on Particle Swarm Optimization Algorithm and Strategic Coordination

Jia

Gong

2009

2009 Fifth International Conference on Natural Computation

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The optimization of the quality costs is the important content of quality management. In this paper, we studied the relationship between the quality level and the quality costs, and we found that the traditional curve of quality costs only concerned about the relationship of the internal factors of quality costs, and neglected the external factors of the quality costs which decide the entire costs of quality. We had proposed a framework for addressing the optimal COQ (cost of quality) within the context of strategic coordination. And then we developed the quality costs model based on strategic coordination. We described an operation mechanism about how the strategic objective decides quality costs through intermediate variable 'customer satisfaction'. Besides we developed a new mathematics model of quality costs optimization, and adopted the PSO (Particle Swarm Optimization) algorithm to get the solution. The example showed that the method is rational and effective.

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In search of an optimal cost of quality: an integrated framework of operational efficiency and strategic effectiveness

Cited by 22 publications

References 6 publications

Cost-of-Quality Optimization via Zero-One Polynomial Programming

Cost-of-Quality Optimization via Zero-One Polynomial Programming

Development of Model for Quality Costing in a Medium Scale Industry-A Case Study

The Study of Quality Costs Optimization Based on Particle Swarm Optimization Algorithm and Strategic Coordination

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