A hybrid framework for supporting scheduling in extended manufacturing environments

In the current marketplace, enterprises face enormous competitive pressures. Global competition for customers that demand customized products with shorter due dates and the advancement in information technologies, marked the introduction of the Extended Enterprise. In these EMEs (Extended Manufacturing Environments), lean, virtual, networked and distributed enterprises, form MO (Meta-Organizations), which collaborate to respond to the dynamic marketplace. MO members share resources, customers and information. In this paper we present a hybrid framework based on a DKBS (Distributed Knowledge Base System), which includes information about scheduling methods for collaborative enterprises sharing their problems. A core component of this system includes an inference engine as well as two indexes, to help in the classification of the usefulness of the information about the problems and solving methods. A more structured approach for expanding the MO concept is presented, with the HO (Hyper-Organization). The manner in which MO-DSS can communicate, cooperate and share information, in the context of the HO is also detailed.

[1]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[2]  Maria Manuela Cunha,et al.  Web-based Technologies Integration for Distributed Manufacturing Scheduling in a Virtual Enterprise , 2012, Int. J. Web Portals.

[3]  Maria Leonilde Rocha Varela,et al.  WEB-BASED DECISION SUPPORT SYSTEM FOR INDUSTRIAL OPERATIONS MANAGEMENT , 2010 .

[4]  Liu Tingting,et al.  JINI-based design for dynamic scheduling decision system , 2009, 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009).

[5]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[6]  Ivo Pereira,et al.  Self-organization for scheduling in agile manufacturing , 2011, 2011 IEEE 10th International Conference on Cybernetic Intelligent Systems (CIS).

[7]  S.G. Kang,et al.  An integrated platform for distributed knowledge-based production scheduling , 2005, Sixth International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'05).

[8]  Peter Brucker,et al.  On the Complexity of Scheduling , 2009, Introduction to Scheduling.

[9]  Ming Kim Lim,et al.  Dynamically Integrated Manufacturing Systems (DIMS)—A Multiagent Approach , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[10]  Lihui Wang,et al.  Wise-ShopFloor: An Integrated Approach for Web-Based Collaborative Manufacturing , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[11]  Vcs Vincent Wiers,et al.  A framework for decision support in production scheduling tasks , 1997 .

[12]  Ivo Pereira,et al.  Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties , 2010, 2010 10th International Conference on Hybrid Intelligent Systems.

[13]  Rita Almeida Ribeiro,et al.  Collaborative Dynamic Decision Making: A Case Study from B2B Supplier Selection , 2011, EWG-DSS.

[14]  Goran D. Putnik,et al.  A Web-Based Decision Support System for Supply Chain Operations Management Towards an Integrated Framework , 2013, EWG-DSS.

[15]  Ana Madureira,et al.  Proposal of multi-agent based model for dynamic scheduling in manufacturing , 2005 .

[16]  Suling Jia,et al.  Design of the Model Base Architecture for Production Scheduling System Based on Multi-agent System and Dual-Service-Bus , 2010, 2010 International Conference on Innovative Computing and Communication and 2010 Asia-Pacific Conference on Information Technology and Ocean Engineering.

[17]  S. Dashkovskiy,et al.  Production Planning & Control , 2013 .

[18]  Maria Leonilde R. Varela,et al.  An Ontology For A Model Of Manufacturing Scheduling Problems To Be Solved On The Web , 2008, BASYS.

[19]  Joaquim Santos,et al.  A Hybrid Intelligent System for Distributed Dynamic Scheduling , 2009, Natural Intelligence for Scheduling, Planning and Packing Problems.

[21]  Rita Almeida Ribeiro,et al.  Collaborative Network Platform for Multi-site Production , 2011, EWG-DSS.

[22]  Shaofeng Liu,et al.  Decision Support Systems – Collaborative Models and Approaches in Real Environments , 2011, Lecture Notes in Business Information Processing.

[23]  Vincent C. S. Wiers,et al.  The complexity of scheduling in practice , 1996 .

[24]  Gong Wang,et al.  A study on multi-agent supply chain framework based on network economy , 2008, Comput. Ind. Eng..

[25]  Dipak Chaudhuri,et al.  Dynamic scheduling—a survey of research , 1993 .

[26]  Goran D. Putnik,et al.  Alternative approaches analysis for scheduling in an Extended Manufacturing Environment , 2014, 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014).

[27]  Ana Madureira,et al.  Resource-oriented scheduling for real world manufacturing systems , 2003, Proceedings of the IEEE International Symposium onAssembly and Task Planning, 2003..

[28]  Enrico Motta,et al.  A generic library of problem solving methods for scheduling applications , 2006, IEEE Transactions on Knowledge and Data Engineering.

[29]  C. Ramos,et al.  A coordination mechanism for real world scheduling problems using genetic algorithms , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[30]  Maria Leonilde Rocha Varela,et al.  Experimental Platform for Collaborative Inter and Intra Cellular Fuzzy Scheduling in an Ubiquitous Manufacturing System , 2011 .

[31]  G. G. Meyer,et al.  Lecture notes in business information processing , 2009 .

[32]  Maria Leonilde Rocha Varela,et al.  Comparing extended neighborhood search techniques applied to production scheduling , 2010 .

[33]  F. Frank Chen,et al.  The state of the art in intelligent real-time FMS control: a comprehensive survey , 1996, J. Intell. Manuf..

[34]  Maria Leonilde Rocha Varela,et al.  Distributed Manufacturing Scheduling Based on a Dynamic Multi-criteria Decision Model , 2014 .

[35]  Rita Almeida Ribeiro,et al.  A Model for B2B Supplier Selection , 2011, Eurofuse.