Designing After-Sale Service Model in World Class
with Soft System Methodology approach (The Case:
LPG Industry)
Amir
Mehdiabadi
PhD Candidate in Industrial Management, Islamic
Azad University, South Tehran Branch, Tehran, Iran
author
Adel
Azar
Professor, Faculty of Economics and Management,
Tarbiat Modares University, Tehran, Iran
author
AbuTurab
Alirezaee
Associate Professor, Islamic Azad University, South
Tehran Branch, Tehran, Iran
author
Ghanbar
Abbaspour Esfeden
Assistant Professor, Islamic Azad University, South
Tehran Branch, Tehran, Iran
author
text
article
2021
per
The Soft System Methodology (SSM), one of the OR techniques, is used tosolve complex real-world problems. Since to design of the after-sales servicemodels for the liquefied gas industry, various groups, such as refineries,mopeds, silencers, taps, standardized organizations, and the consumer rightsprotection organization should be considered, so decision making in thissituations are very complicated issue. In this study, using the aboveapproach, the problem of non-structured model design at the world-classlevel is explained and then, by specifying its boundaries, the image of thevarious actors of the system and their benefits are depicted. In the third step,the CATWOE approach is used to explain the basic definition of the aftersales service model in this industry, and in the fourth stage, a conceptualmodel of activities is presented using the root definition. This paper usesintegration of ISM-Fuzzy Delphi in the process of problem solving. In thefifth step, the developed model is compared with the real world. In the sixthstage, desirable and feasible changes were identified and explained by theIPA method. Finally, using the results of the previous stages, andsuggestions for the development of the model to reach the world class levelare presented to the authorities and stakeholders.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
1
49
https://jims.atu.ac.ir/article_12579_983ddb17982e1415ef519db3b9c4dce5.pdf
dx.doi.org/10.22054/jims.2019.38105.2218
Hybrid of System Dynamics- Agent Based Analysis of Mobile
Operators Revenue
The Case: Digital Service Entry of MCCI Company
Navid
Nadimi
Department of Industrial Management' Central Tehran Branch' Islamic Azad University ' Tehran' Iran
author
Abbas
Toloei Eshlaghy
, Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
author
Mohammad Ali
Afshar kazemi
. Department of Industrial Management, Central Tehran Branch, , Islamic Azad University, Tehran, Iran
author
text
article
2021
per
With the tremendous progress in communications in the world, the transformation andbehavior of mobile operators and their digitalization, which in the past were onlyservice providers, as well as the creation of different experiences for customers, isinevitable.The purpose of this study is to create a hybrid simulation of systemdynamics and agent based model in order to analyze the revenue of the first operator inthe country to enter the field of digital platform and development of nativeapplications. Using the model proposed, first operators need to enter the digital areaand produce native applications was expressed. Then, the factors that affect the mobileecosystem which, affect the production of applications and the development ofrequired platforms were described. By utilizing hybrid simulation of system dynamicsand agent based modeling, the income of mobile operator in entering and not enteringthe digital arena and producing native applications were examined. The results showthat with the entry of the operator into the field of production of native applicationsand the adoption of digital approach, consumers tended to use more data services, butdue to different tariffs for data and voice, the operator's income up to 2 Next years willnot change much.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
51
84
https://jims.atu.ac.ir/article_12574_921220d4b629acebf653628baf90646d.pdf
dx.doi.org/10.22054/jims.2021.57381.2584
A Supply Chain Network Design for Managing
Hospital Solid Waste
Mohammad
Nikzamir
Islamic Azad University, Tehran North Branch
author
vahid
baradaran
دانشیار، گروه مهندسی صنایع ، دانشگاه آزاد اسلامی واحد تهران شمال، تهران، ایران
author
Yunes
Panahi
Pharmacotherapy Department, School of Pharmacy, Baqiyatallah University of Medical Sciences, Tehran, Iran.
author
text
article
2021
per
Health care solid wastes include all types of waste that are produced as a result ofmedical and therapeutic activities in hospitals and health centers. About 15% to20% of these waste materials are infectious waste, which falls within the categoryof hazardous materials. Infectious waste is the one that must be treated beforedisposal or recycling. Hence, this paper seeks to develop a bi-objective mixedinteger programming model for the infectious waste management. In the proposedmodel, in addition to minimizing the chain costs, the reduction of risks for thepopulation exposed to the spread of contamination resulting from infectious wasteis also considered. For this purpose, a multi-echelon chain is proposed by takinginto account the green location-routing problem, which involves the location ofrecycling, disposal, and treatment centers through various treatment technologiesand routing of vehicles between treatment levels and the hospital. The routingproblem has been considered to be multi-depot wherein the criterion of reducingthe cost of fuel consumption of heterogeneous cars is used for green routing.Finally, a hybrid meta-heuristic algorithm based on ICA and GA is developedand, following its validation, its function in solving large-scale problems has beeninvestigated. Results show that the proposed algorithm is effective and efficient.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
85
120
https://jims.atu.ac.ir/article_12576_b51874fb1136be1c10f74d48f2be4992.pdf
dx.doi.org/10.22054/jims.2021.40574.2283
Mapping Factors Affecting IoT Deployment in
Storage Sector of Wheat Supply Chain
Mohsen
Rajabzadeh
دانشجوی دکتری مدیریت فناوری اطلاعات، دانشگاه تربیت مدرس، تهران، ایران
author
Shaban
Elahi
Associate Prof. in Information Technology Management, Management and Economy School, Tarbiat Modares University, Tehran, Iran
author
Alireza
Hasanzadeh
Associate Prof. in Information Technology Management, Management and Economy School, Tarbiat Modares University, Tehran, Iran
author
Mohammad
mehrain
Prof. in Management, Management and Economy School, Ferdowsi University of Mashhad, Mashhad, Iran
author
text
article
2021
per
Studies show that there are shortcomings in the deployment of the Internet ofThings (IoT) in the supply chain of agricultural products, especially in thefield of quality control in the logistics sector, and researchers can model theexisting theoretical gaps through modeling and optimization. Therefore, thepurpose of this paper is to identify the most important categories affectingthe deployment of the Internet of Things in the wheat supply chain storagesector and explain and mapping the relationship between these categories.For this purpose, the present article uses meta-synthesis method by searchingWeb of Science and Scopus citation databases. Then, the grounded theorycoding procedures were used to determine categories and themes. Finally,the results of meta-synthesis lead to the identification and extraction of 3macro categories; IoT technology, the main category (IoT-based storage),and the results and consequences of IoT deployment.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
121
143
https://jims.atu.ac.ir/article_12578_7687db1d679b5c7a75f6d7a5e28a3579.pdf
dx.doi.org/10.22054/jims.2021.54482.2528
A Bi-Objective Robust Model for Location-Routing and
Capacity Sharing in Districting Regions under Uncertainty
Ramin
Saedinia
Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
Behnam
Vahdani
Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
Farhad
Etebari
Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
Behroz
Afshar Nadjafi
Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
text
article
2021
per
One of the most important approaches that can lead to the creation of various advantagesfor enterprises is the districting regions into the service offering locations and the demandunits, which causes the increase in level of customers’ access to get the service. On theother hand, if vehicle routing is carried out in districting regions in order to deliver productsto customers, the planning of customer service can be improved. However, in none of theresearch conducted in the area of design supply chain, vehicle routing in districting regionshas been not investigated. Therefore, in the current study, a bi-objective mathematicalmodel is presented to simultaneously focus on districting regions, facility location–allocation, service sharing, intra-district service transfer and vehicle routing. The firstobjective function minimizes the total cost of designing the CLSC network, which includescosts of opening facility and vehicle routing. The second objective function minimizes themaximum volume of surplus demand from service providers in order to achieve anappropriate balance in demand volume across all regions. Moreover, a robust optimizationapproach is used to take into account uncertainty in some parameters of the proposedmodel. In addition, the validity of the proposed mathematical model and the proposedsolution has been investigated on a real case in the oil and gas industry.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
145
192
https://jims.atu.ac.ir/article_11469_26a0d18ef3b7bcf5ed1dcc6e51a63e3e.pdf
dx.doi.org/10.22054/jims.2019.41330.2303
A The Evaluation of Knowledge Management in Supply
Chain Using EFQM Framework, Fuzzy Multi-Attribute
Decision Making and Multi-Objective Programming
S.jamal’aldin
Hosseini
Assistance professor, faculty of Industrial engineering, university of Qom, Qom, Iran
author
Jalal
Rezaeenour
Head of ICT Center, University of Qom,
Dean of Department of Industrial Engineering, University of Qom
author
mohammad
masoumi
MSc of Industrial Engineering, Faculty of Technology and Engineering, University of Qom, Qom, Iran
author
Amir Hosein
Akbari
MSc of Information Technology Engineering, Faculty of Technology and Engineering, University of ،Tehran, Tehran, Iran
author
text
article
2021
per
One Knowledge Management (KM) as one of the Supply Chain performanceimprovement factors can be strengthened through frameworks like EFQM ExcellenceModel in order to achieve competitive advantage. First, the KM enablers in SC areclassified based on EFQM enabler criteria. Then, the importance of each KM enabler isevaluated by fuzzy DEMATEL-ANP. In addition, Analytical Hierarchy Process (AHP) isapplied to evaluate the importance of each KM enabler in knowledge sharing amongsupply chain people. In the research, the multi-objective mixed integer programming isused to optimize knowledge management and select KM strategy in each part of SC.Likewise, it is approved to select suitable members of SC for Research and Development(R&D) unit of SC. Results show that each part of SC should focus on developing someKM enablers, and selection of a suitable strategy. These results also emphasis theeffectiveness of each KM enabler and their development in selecting of suitable membersfor R&D unit of SC.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
193
235
https://jims.atu.ac.ir/article_12575_08d95b9da31a281d5a7378d9fdfb7c1f.pdf
dx.doi.org/10.22054/jims.2021.40704.2289
Mathematical Model and Meta-Heuristic Algorithm for
Dual Resource Constrained Hybrid Flow-Shop
Scheduling Problem with Job Rejection
Mohammadreza
Dabiri
Ph.D. Student, Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
Mehdi
Yazdani
Assistant Prof., Department of Industrial Engineering, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
author
bahman
naderi
Associate Prof., Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran
author
Hasan
Haleh
Assistant Prof., Department of Industrial Engineering, Golpayegan University of Technology, Golpayegan, Iran
author
text
article
2021
per
In the real world, firms with hybrid flow-shop manufacturing environment generally facethe human resource constraint, salary cost increasment and efforts to make better use oflabor, in addition to machine constraint. Given the limitations of these resources, productdelivery requierements to customers have made the job rejection essential in order to meetdistinct customer requirements. Therefore, this research has studied the dual resourceconstrained hybrid flow-shop scheduling problem with job rejection in order to minimizethe total net cost (the sum of the total rejection cost and the total tardiness cost of jobs)which is widely used in many industries. In this article, a mixed integer linear programmingmodel has developed for the research problem. In addition, an improved sooty ternoptimization algorithm (ISTOA) has proposed to solve the large-sized problems as well asa decoding method due to the NP-hardness of the problem. In order to evaluate theproposed optimization algorithm, five well-known algorithms in the literature including(immunoglobulin-based artificial immune system (IAIS), genetic algorithm (GA), discreteartificial bee colony (DABC), improved fruit fly optimization (IFFO), effective modifiedmigrating birds optimization (EMBO)) have adapted with the proposed problem. Finally,the performance of the proposed optimization algorithm has investigated against theadapted algorithms. Results and evaluations show the good performance of the improvedsooty tern optimization algorithm.
Industrial Management Studies
Allameh Tabataba'i University
2251-8029
19
v.
60
no.
2021
237
284
https://jims.atu.ac.ir/article_12577_eb5e07f9904d095c19a0c7f5746a989c.pdf
dx.doi.org/10.22054/jims.2021.48976.2425