Design and Development a Model to Present Practices for Implementation Cloud Manufacturing System

The purpose of this paper is to identify and classify the main factors implementing the cloud manufacturing systems in the internet service providers company by fuzzy cognitive map methodology. Through expert opinions, 20 main factors were identified and classified based on the importance and then a fuzzy cognitive map approach was applied for obtaining the relationship between the factors, and all of the impact factors are outputs of expert opinion. The outcomes of the study highlighted that three factors, including customer scoring, R&D, and method development were the most important factors impressing the implementation cloud manufacturing systems. Present practices for implementation cloud manufacturing system is and the relationship between the main factors also impressing cloud manufacturing system by employing the fuzzy cognitive map approach in the Iranian internet service provider company. The model obtained in this study guides the managers to identify and classify the important factors of the cloud manufacturing and finally implement it successfully.

[1]  Xun Xu,et al.  Virtualize Manufacturing Capabilities in the Cloud: Requirements and Architecture , 2013 .

[2]  Xun Xu,et al.  Development of a Hybrid Manufacturing Cloud , 2014 .

[3]  Jose L. Salmeron,et al.  Ranking fuzzy cognitive map based scenarios with TOPSIS , 2012, Expert Syst. Appl..

[4]  Zhinan Zhang,et al.  Distributed Resource Environment: A Cloud-Based Design Knowledge Service Paradigm , 2014 .

[5]  Xudong Chai,et al.  High-performance cloud simulation platform advanced research of cloud simulation platform , 2011 .

[6]  許鉅秉,et al.  國際期刊 Transportation Research-Part E---Logistics and Transportation Review 特刊編輯補助 , 2006 .

[7]  Wolfgang Ortner,et al.  Flexibility and Improved Resource Utilization Through Cloud Based ERP Systems: Critical Success Factors of SaaS Solutions in SME , 2012, ERP Future.

[8]  Weidong Li,et al.  A Streaming Technology of 3D Design and Manufacturing Visualization Information Sharing for Cloud-Based Collaborative Systems , 2013 .

[9]  Assessing the reliability and validity of the Danish version of Organizational Readiness for Implementing Change (ORIC) , 2018, Implementation Science.

[10]  Jose L. Salmeron,et al.  Modeling maintenance projects risk effects on ERP performance , 2014, Comput. Stand. Interfaces.

[11]  Holger Schrödl,et al.  Adoption of Cloud Computing in Supply Chain Management Solutions: A SCOR-Aligned Assessment , 2012, APWeb Workshops.

[12]  Markus Stumptner,et al.  Ontology-based Process Modeling and Execution Using STEP/EXPRESS , 2008, SEKE.

[13]  Areti Kontogianni,et al.  How do you perceive environmental change? Fuzzy Cognitive Mapping informing stakeholder analysis for environmental policy making and non-market valuation , 2012, Appl. Soft Comput..

[14]  Dimitris Mourtzis,et al.  Cloud-based cyber-physical systems and quality of services , 2016 .

[15]  Abraham Kandel,et al.  Automatic construction of FCMs , 1998, Fuzzy Sets Syst..

[16]  Alexander Fink,et al.  Scenario Management: An Approach to Develop Future Potentials , 1998 .

[17]  Bart Kosko,et al.  Fuzzy Engineering , 1996 .

[18]  Tajje-eddine Rachidi,et al.  Employing Fuzzy Cognitive Maps to support environmental policy development , 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[19]  Nachiappan Subramanian,et al.  Integration of logistics and cloud computing service providers: Cost and green benefits in the Chinese context , 2014 .

[20]  Tiago Oliveira,et al.  Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors , 2014, Inf. Manag..

[21]  Xun Xu,et al.  From cloud computing to cloud manufacturing , 2012 .

[22]  Jose L. Salmeron,et al.  Dynamic risks modelling in ERP maintenance projects with FCM , 2014, Inf. Sci..

[23]  Michel Godet,et al.  The Art of Scenarios and Strategic Planning - Tools and Pitfalls , 2000 .

[24]  Xun Xu,et al.  An interoperable solution for Cloud manufacturing , 2013 .

[25]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[26]  Lihui Wang,et al.  Manufacturing System on the Cloud: A Case Study on Cloud-based Process Planning , 2017 .

[27]  A. B. Susanto,et al.  Organizational Readiness for Change: A Case Study on Change Readiness in a Manufacturing Company in Indonesia , 2008 .

[28]  Elpiniki I. Papageorgiou,et al.  Review study on fuzzy cognitive maps and their applications during the last decade , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

[29]  Benjamin T. Hazen,et al.  Adoption of cloud computing technologies in supply chains: An organizational information processing theory approach , 2012 .

[30]  Adil Baykasoglu,et al.  Training Fuzzy Cognitive Maps via Extended Great Deluge Algorithm with applications , 2011, Comput. Ind..

[31]  Lihui Wang,et al.  From Cloud manufacturing to Cloud remanufacturing: A Cloud-based approach for WEEE recovery , 2014 .

[32]  Jose L. Salmeron,et al.  Methods and Algorithms for Fuzzy Cognitive Map-based Modeling , 2014, Fuzzy Cognitive Maps for Applied Sciences and Engineering.

[33]  Giovanni Schiuma,et al.  Intelligent decision-making model based on minority game for resource allocation in cloud manufacturing , 2020 .

[34]  István Mezgár,et al.  ManuCloud: The Next-Generation Manufacturing as a Service Environment , 2010, ERCIM News.

[35]  Nan Yang,et al.  A Cloud Computing-Based ERP System under The Cloud Manufacturing Environment , 2012 .

[36]  Tom Van Woensel,et al.  Cloud manufacturing service selection optimization and scheduling with transportation considerations: mixed-integer programming models , 2018 .

[37]  Lihui Wang,et al.  Ubiquitous manufacturing system based on Cloud , 2017 .

[38]  Jonathan Corney,et al.  Cloud-based manufacturing-as-a-service environment for customized products , 2011 .

[39]  P. Nilsen Making sense of implementation theories, models and frameworks , 2015, Implementation Science.

[40]  Hanieh Arazmjoo,et al.  A multi-dimensional meta-heuristic model for managing organizational change , 2019, Management Decision.

[41]  Angela Wilkinson Scenarios Practices: In Search of Theory , 2009 .

[42]  Jörg Leukel,et al.  Supply Chain as a Service: A Cloud Perspective on Supply Chain Systems , 2011, IEEE Systems Journal.

[43]  Chrysostomos D. Stylios,et al.  An integrated two-level hierarchical system for decision making in radiation therapy based on fuzzy cognitive maps , 2003, IEEE Transactions on Biomedical Engineering.

[44]  Benjamin T. Hazen,et al.  Cloud Computing in Support of Supply Chain Information System Infrastructure: Understanding When to go to the Cloud , 2013 .

[45]  Sandhya Samarasinghe,et al.  Mixed-method integration and advances in fuzzy cognitive maps for computational policy simulations for natural hazard mitigation , 2013, Environ. Model. Softw..

[46]  Sajjad Shokouhyar,et al.  Scenario analysis of smart, sustainable supply chain on the basis of a fuzzy cognitive map , 2019, Management Research Review.

[47]  Jose L. Salmeron,et al.  Augmented fuzzy cognitive maps for modelling LMS critical success factors , 2009, Knowl. Based Syst..

[48]  Dazhong Wu,et al.  Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation , 2015, Comput. Aided Des..

[49]  D. Ruan,et al.  Belief Degree-Distributed Fuzzy Cognitive Maps , 2010, 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering.