Gradient method in solving nonlinear cost of quality functions in supply chain network design

Alzaman, Chaher; Ramudhin, Amar; Bulgak, Akif Asil

doi:10.1080/17509653.2010.10671132

Cited by 7 publications

(6 citation statements)

References 17 publications

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“…Examining the impact of CoQ on health outcomes (Elbireer et al, 2010), financial returns of quality investments (Abdul-Kader et al, 2010), each supplier and the supply chain network design (Alzaman et al, 2010), performance of companies (Al-Tmeemy et al, 2012;Mijoc et al, 2014;Pires et al, 2017), the effectiveness of continuing education for health professionals (Vukovic et al, 2015) and the quality levels of the endproduct (Chatzipetrou and Moschidis, 2016)…”

Section: Coq Effectsmentioning

confidence: 99%

“…Studying the integration of CoQ method with the supply chain management (Alzaman et al, 2010;Yoo et al, 2012;Castillo-Villar et al, 2012a;Castillo-Villar et al, 2012b;Khataie and Bulgak, 2013;Alglawe et al, 2019), the Six Sigma methodology (Rodin and Beruvides, 2012), the ISO 9001 standard implementation (Chiarini, 2015) and maintenance strategy (Peimbert-Garcia et al, 2016) CoQ failure factors…”

Section: Coq Integration With Other Management Approachesmentioning

confidence: 99%

See 1 more Smart Citation

Future research avenues of cost of quality: a systematic literature review

Dimitrantzou

Psomas

Vouzas

2020

TQM

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PurposeThe purpose of this paper is to identify the future research suggestions which have been made by several authors with regard to cost of quality (CoQ) and to group them into respective themes.Design/methodology/approachThis study was based on a systematic literature review (SLR) of 97 peer-reviewed journal articles in the field of CoQ published in well-known academic databases, such as Emerald, Elsevier, SpringerLink, Taylor & Francis, Wiley and Scopus. The time horizon for reviewing the literature was 9 years, particularly in the period between 2010 and 2018. The “Affinity diagram” was applied to group the future research suggestions into logical themes and the “Pareto diagram” to further categorize and prioritize these themes.FindingsA plethora of future research suggestions identified in the literature are analytically presented. Moreover, the analysis showed that the future research suggestions in the field of CoQ can be grouped under eleven meaningful themes, which are further categorized into two broad categories, meaning the vital and the useful.Research limitations/implicationsThis SLR was based on only fully accessed English articles published in international, peer-reviewed journals of the selected publishers. The restricted number of keywords used and the subjectivity in applying the “affinity diagram” are also limitations of this study.Practical implicationsThis paper provides insights into the future research perspectives in the field of CoQ. Thus, this analysis can serve as a resource for both researchers and practitioners to further develop this area according to the future research suggestions and the respective themes revealed.Originality/valueTo the best of the authors' knowledge, this is the first SLR presenting and analyzing the future research suggestions of CoQ.

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Section: Coq Effectsmentioning

confidence: 99%

Section: Coq Integration With Other Management Approachesmentioning

confidence: 99%

Future research avenues of cost of quality: a systematic literature review

Dimitrantzou

Psomas

Vouzas

2020

TQM

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“…It is widely agreed that the total cost functions of the four COQ are convex functions. Hence, the COQ is also convex (Feigenbaum, 1983; Juran and Gryna, 1993; Campanella, 1990; Shank and Govindarajan, 1994; Alzaman et al , 2010).…”

Section: Literature Review On the Coqmentioning

confidence: 99%

“…Measuring the QL in monetary terms facilitates understanding of the SC performance to the SC shareholders (Srivastava, 2008; Prakash and Mohanty, 2017). Even though, COQ has been considered by several authors within the manufacturing SC, such as Ramudhin et al (2008), Castillo-Villar et al (2012a, 2014) and Alzaman et al (2010), there is no a comprehensive COQ model for designing a capacitated SC in the literature. Therefore, this research aims at modeling COQ in the form of PA, F and opportunity cost (OC) in a four-echelon SC with consideration of the QL in all SC facilities.…”

Section: Introductionmentioning

confidence: 99%

Supply chain network design based on cost of quality and quality level analysis

Alglawe

Schiffauerova

Kuzgunkaya

et al. 2019

TQM

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Purpose 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. Design/methodology/approach 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. Findings The results show how the QL, COQ and facility location decisions change when incorporating the OC, investments and transportation costs into the SC model. Originality/value 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.

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“…The total quality cost at a supplier is represented by the CoQ at any given defective rate. This model was further extended to include the total quality at plants by Alzaman et al (2010), where a gradient search method was proposed for solving the GMINLP. Castillo-Villa et al (2011) presented an alternative zero-one nonlinear program for optimizing a supply chain design, where the objective function is the profit that is given by the expected revenue minus the CoQ at the plants, minus the costs incurred for materials, production, and transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

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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Gradient method in solving nonlinear cost of quality functions in supply chain network design

Cited by 7 publications

References 17 publications

Future research avenues of cost of quality: a systematic literature review

Future research avenues of cost of quality: a systematic literature review

Supply chain network design based on cost of quality and quality level analysis

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

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