Simultaneous optimization of multiple performance characteristics of carbonitrided pellets: a case study

John, Boby

doi:10.1007/s00170-011-3751-2

Cited by 7 publications

(3 citation statements)

References 19 publications

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“…Step 2: using (1) to identify the optimum values of x k , k ¼ 1, 2, … which would bring the output characteristic y to target t. Since there are multiple output characteristics, identify the optimum values of x k , k¼ 1, 2, …, which would simultaneously bring multiple output characteristics y l , l ¼ 1, 2, … to respective targets t l . This can be achieved through a multiple response optimization methodology, namely, Derringer's desirability function methodology (Derringer, 1994;John, 2013;Goethals and Cho, 2011), Taguchi's loss function approach (Wu, 2002;Antony et al, 2006;John, 2012;Reddy et al, 1998), gray relational analysis (Saha and Mandal, 2013), data envelopment method (Liao, 2004;Liao and Chen, 2002), mean square criteria (Koksoy and Yalcinoz, 2006;John et al, 2017), neural networks (Hsu, 2004), etc. In this study, the fuzzy logic methodology is used for simultaneously optimizing the output characteristics.…”

Section: Suggested Methodologymentioning

confidence: 99%

An application of integrated EPC–SPC methodology for simultaneously monitoring multiple output characteristics

John

Singhal

2019

IJQRM

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Purpose The purpose of this paper is to develop an integrated engineering process control (EPC)–statistical process control (SPC) methodology for simultaneously monitoring and controlling autocorrelated multiple responses, namely, brightness and viscosity of the pulp bleaching process. Design/methodology/approach The pulp bleaching is a process of separating cellulose from impurities present in cooked wood chips through chemical treatment. More chemical dosage or process adjustments may result in better brightness but adversely affect viscosity. Hence, the optimum chemical dosage that would simultaneously minimize the deviation of pulp brightness and viscosity from their respective targets needs to be determined. Since the responses are autocorrelated, dynamic regression is used to model the responses. Then, the optimum chemical dosage that would simultaneously optimize the pulp brightness and viscosity is determined by fuzzy optimization methodology. Findings The suggested methodology is validated in 12 cases. The validation results showed that the optimum dosage simultaneously minimized the variation in brightness and viscosity around their respective targets. Moreover, suggested solution has been found to be superior to the one obtained by optimizing the responses independently. Practical implications This study provides valuable information on how to identify the optimum process adjustments to simultaneously ensure autocorrelated multiple responses on or close to their respective targets. Originality/value To the best of the authors’ knowledge, this paper is the first to provide application of the integrated EPC–SPC methodology for simultaneously monitoring multiple responses. The study also demonstrates the application of dynamic regression to model autocorrelated responses.

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Section: Suggested Methodologymentioning

confidence: 99%

An application of integrated EPC–SPC methodology for simultaneously monitoring multiple output characteristics

John

Singhal

2019

IJQRM

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“…Taguchi design stages consist of system, parameter and tolerance designs (Reddy et al . ; John ; Lin et al . ,).…”

Section: Compromise Simplex Methods (Csm)mentioning

confidence: 99%

Multiobjective Optimization of Cryogenic Freezing Conditions of Chicken Drumstick via Compromise Simplex Method

Luangpaiboon

Uporn

2014

Journal of Food Processing and Preservation

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Because frozen foods have various quality characteristics, an optimization of a cryogenic freezing process is a complex task. This study proposes a compromise simplex method (CSM) using regression analysis to determine four optimal controllable process parameters corresponding to multiresponses for the level of three product quality characteristics. The results of the experimental process for the modified simplex method and multiple response surface optimization model both outperformed the results of the existing operating conditions, thus verifying that the CSM result in food preservation with the product quality measures close to customer satisfaction. The four recommended optimal conditions were as follows: the freezer set temperature of −100C, exhaust fan speed at 10 Hz, retention time of 12 min and counter-current nitrogen flow. PRACTICAL APPLICATIONSThis study optimized multiple responses for chicken drumsticks in a cryogenic freezing process. This optimization method has potential for practical application. All compromised quality characteristics are of topmost importance to the frozen food industry. This method, with some modifications, can also be used in further studies of related food products.

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“…Many papers on a wide variety of applications of Taguchi's loss function is published in the recent past (Liao & Kao, 2010;Pi & Low, 2006;Antony, 2000;Antony, 2001;Wu, 2004;Kethley, 2002;Chan & Ibrahim, 2004;Cho & Cho, 2008;John, 2012). The QLP method is to…”

Section: Methodsmentioning

confidence: 99%

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

John¹

2015

10.5267/j.ijiec

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The powder coating is an economic, technologically superior and environment friendly painting technique compared with other conventional painting methods. However large variation in coating thickness can reduce the attractiveness of powder coated products. The coating thickness variation can also adversely affect the surface appearance and corrosion resistivity of the product. This can eventually lead to customer dissatisfaction and loss of market share. In this paper, the author discusses a dual response surface optimization methodology to minimize the thickness variation around the target value of powder coated industrial enclosures. The industrial enclosures are cabinets used for mounting the electrical and electronic equipment. The proposed methodology consists of establishing the relationship between the coating thickness & the powder coating process parameters and developing models for the mean and variance of coating thickness. Then the powder coating process is optimized by minimizing the standard deviation of coating thickness subject to the constraint that the thickness mean would be very close to the target. The study resulted in achieving a coating thickness mean of 80.0199 microns for industrial enclosures, which is very close to the target value of 80 microns. A comparison of the results of the proposed approach with that of existing methodologies showed that the suggested method is equally good or even better than the existing methodologies. The result of the study is also validated with a new batch of industrial enclosures.

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Simultaneous optimization of multiple performance characteristics of carbonitrided pellets: a case study

Cited by 7 publications

References 19 publications

An application of integrated EPC–SPC methodology for simultaneously monitoring multiple output characteristics

An application of integrated EPC–SPC methodology for simultaneously monitoring multiple output characteristics

Multiobjective Optimization of Cryogenic Freezing Conditions of Chicken Drumstick via Compromise Simplex Method

A dual response surface optimization methodology for achieving uniform coating thickness in powder coating process

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