An integrated fuzzy DEA–Fuzzy simulation approach for optimization of operator allocation with learning effects in multi products CMS

Azadeh, A.; Sheikhalishahi, Mohammad; Koushan, Mona

doi:10.1016/j.apm.2013.05.039

Cited by 24 publications

(13 citation statements)

References 30 publications

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“…

{\tilde{x}}_{i j}

and

{\tilde{y}}_{i j}

are input and output variables of DEA which are asymmetrical triangular-shaped fuzzy numbers as discussed before.

{\tilde{x}}_{i p}

and

{\tilde{y}}_{r p}

are the upper bound for input variables

({\tilde{x}}_{i j})

and lower bound for output variables

({\tilde{y}}_{i j})

, respectively [27]. Substituting fuzzy values

{\tilde{x}}_{i j}

and

{\tilde{y}}_{i j}

with

{\tilde{x}}_{i j} = (x_{i j}^{p}, x_{i j}^{m}, x_{i j}^{o})

and

{\tilde{y}}_{i j} = (y_{i j}^{p}, y_{i j}^{m}, y_{i j}^{o})

, respectively, and using α-cut method, the abovementioned model can be expressed as follows:…”

Section: Methodsmentioning

confidence: 99%

“…It should be noted that since the input indicators including research and educational expenses, teaching hours, and the number of human resources is crisp, their most likely, pessimistic, and optimistic values are the same

(i .e ., x_{i j}^{m} = x_{i j}^{p} = x_{i j}^{o})

. Since the objective of this study was to analyze the efficiency of branches (DMUs) based on output indicators, the output-oriented Banker, Charnes, and Cooper model has been utilized and the efficiency and rank of each branch have been determined based on the second model for different α-cuts [27].…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant

Azadeh

Salehi

Mirzayi

2016

Safety and Health at Work

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BackgroundResilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors—self-organization, teamwork, redundancy, and fault-tolerance—in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment.MethodsThe required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different α-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four above-mentioned factors.ResultsThe results showed that as α approached 0 and the system became fuzzier (α = 0.3 and α = 0.1), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as α approached 1 and the fuzzy system went toward a certain mode (α = 0.9 and α = 1), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors.ConclusionThe approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.

show abstract

“…

{\tilde{x}}_{i j}

and

{\tilde{y}}_{i j}

are input and output variables of DEA which are asymmetrical triangular-shaped fuzzy numbers as discussed before.

{\tilde{x}}_{i p}

and

{\tilde{y}}_{r p}

are the upper bound for input variables

({\tilde{x}}_{i j})

and lower bound for output variables

({\tilde{y}}_{i j})

, respectively [27]. Substituting fuzzy values

{\tilde{x}}_{i j}

and

{\tilde{y}}_{i j}

with

{\tilde{x}}_{i j} = (x_{i j}^{p}, x_{i j}^{m}, x_{i j}^{o})

and

{\tilde{y}}_{i j} = (y_{i j}^{p}, y_{i j}^{m}, y_{i j}^{o})

, respectively, and using α-cut method, the abovementioned model can be expressed as follows:…”

Section: Methodsmentioning

confidence: 99%

(i .e ., x_{i j}^{m} = x_{i j}^{p} = x_{i j}^{o})

Section: Methodsmentioning

confidence: 99%

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant

Azadeh

Salehi

Mirzayi

2016

Safety and Health at Work

View full text Add to dashboard Cite

show abstract

“…Azadeh, Rezaei-Malek, Evazabadian, and Sheikhalishahi (2015) proposed decisionmaking styles of operators (as an index of operator's personal characteristics) and an innovative mathematical programming model for clustering parts, machines and workers at the same time. Azadeh, Sheikhalishahi, & Koushan, (2013) presented fuzzy data envelopment analysis (FDEA) and fuzzy computer simulation approach, in which learning effects, server breakdowns, and multi products were considered. They calculated the efficiency and the number of operators in CMS while the rate of demand and the transfer batch size were changing.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Heydarian

Jolai

2018

Production & Manufacturing Research

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This paper investigates the operator allocation problem with learning effects and server breakdown in cellular manufacturing systems (CMSs) using fuzzy computer simulation and response surface methodology (RSM). The primary contribution of this study is incorporating combined server breakdowns and learning effects in CMS under uncertainty. Machine breakdowns of all the machines as well as the probability related to each entity should be delivered in good order are considered. Also, previous studies did not consider fuzzy simulation and RSM to deal with environmental and data uncertainty in operator allocation problems. The superiority of the presented model, in comparison with the traditional one, is shown according to the number of required iterations. The proposed simulation model is run in uncertain state to obtain the total processing time. RSM algorithm identifies a fitted function in terms of the value of allocated capital to each server and total processing time. This is a practical approach for decisionmakers of all Cellular Manufacturing Systems.

show abstract

“…In real world problems, when the input and output values of the data are vague and not exact, some fuzzy models have been presented for dealing with uncertainty in the data envelopment analysis. Fuzzy DEA is one of the methods that output and input variables are asymmetrical triangular shaped fuzzy numbers and there is a lower bound and upper bound for the input and output variables of DMU values [23]. Consider ̃= ( , , 0 ) fuzzy values of the input variable and = ( , , 0 ) fuzzy values of the output variable which have three pessimistic, mean and optimistic values.…”

Section: Fdeamentioning

confidence: 99%

Optimizing Maintenance in Project Management by Considering HSE and Resilience Engineering

Einabadi¹,

Memari

Ghaderi

2018

Annals of Computer Science and Information Systems

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One of the most important objectives of project management is to complete the project within the specified completion date of the project. Another important objective of project is to terminate the project by minimum rate of injuries and damage to the environment. One of the important factors which affect the time objective of the project is the failures or breakdowns of the project Machines and Equipment. Also, Health, Safety, Environment (HSE) factors are crucial in the efficient execution of the project. Resilience engineering is a new concept that will improve the safety and reliability of a high-risk system such as power plant construction project. Previous studies didn't consider the resilience engineering (RE) factors which could help the project to achieve its goals. Related data was collected from a power plant construction project and fuzzy DEA and Znumber DEA were utilized to analyze the Data and Best DEA model is selected according to maximum average efficiency and also for identifying most effective factors sensitivity analysis was done, and we found that flexibility, and project percent progress, system downtime, reporting culture and HSE costs are the most important factors on maintenance of the project. To the best of our knowledge, this is the first study considering RE and HSE factors to optimize maintenance of the project.

show abstract

An integrated fuzzy DEA–Fuzzy simulation approach for optimization of operator allocation with learning effects in multi products CMS

Cited by 24 publications

References 30 publications

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant

The Impact of Redundancy and Teamwork on Resilience Engineering Factors by Fuzzy Mathematical Programming and Analysis of Variance in a Large Petrochemical Plant

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Optimizing Maintenance in Project Management by Considering HSE and Resilience Engineering

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