A multi-agent architecture for scheduling in platform-based smart manufacturing systems

During the past years, a number of smart manufacturing concepts have been proposed, such as cloud manufacturing, Industry 4.0, and Industrial Internet. One of their common aims is to optimize the collaborative resource configuration across enterprises by establishing platforms that aggregate distributed resources. In all of these concepts, a complete manufacturing system consists of distributed physical manufacturing systems and a platform containing the virtual manufacturing systems mapped from the physical ones. We call such manufacturing systems platform-based smart manufacturing systems (PSMSs). A PSMS can therefore be regarded as a huge cyber-physical system with the cyber part being the platform and the physical part being the corresponding physical manufacturing system. A significant issue for a PSMS is how to optimally schedule the aggregated resources. Multi-agent technology provides an effective approach for solving this issue. In this paper we propose a multi-agent architecture for scheduling in PSMSs, which consists of a platform-level scheduling multi-agent system (MAS) and an enterprise-level scheduling MAS. Procedures, characteristics, and requirements of scheduling in PSMSs are presented. A model for scheduling in a PSMS based on the architecture is proposed. A case study is conducted to demonstrate the effectiveness of the proposed architecture and model.

[1]  Lei Ren,et al.  Cloud manufacturing: a new manufacturing paradigm , 2014, Enterp. Inf. Syst..

[2]  Lihui Wang,et al.  Process planning and scheduling for distributed manufacturing , 2007 .

[3]  Dimitris Mourtzis,et al.  Cloud-Based Adaptive Shop-Floor Scheduling Considering Machine Tool Availability , 2015 .

[4]  Lihui Wang,et al.  Multi-agent-based scheduling in cloud manufacturing with dynamic task arrivals , 2018 .

[5]  Lihui Wang,et al.  Scheduling in cloud manufacturing: state-of-the-art and research challenges , 2019, Int. J. Prod. Res..

[6]  Lihui Wang,et al.  Combined strength of holons, agents and function blocks in cyber-physical systems , 2016 .

[7]  Stefano Giordano,et al.  A Novel Auction Based Scheduling Algorithm in Industrial Internet of Things Networks , 2018, CN.

[8]  Fei Tao,et al.  An Extensible Model for Multitask-Oriented Service Composition and Scheduling in Cloud Manufacturing , 2016, Journal of Computing and Information Science in Engineering.

[9]  Laurence T. Yang,et al.  Subtask Scheduling for Distributed Robots in Cloud Manufacturing , 2017, IEEE Systems Journal.

[10]  Xiaofei Xu,et al.  Artificial Bee Colony Optimized Scheduling Framework Based on Resource Service Availability in Cloud Manufacturing , 2014, 2014 International Conference on Service Sciences.

[11]  Weiming Shen,et al.  Distributed Manufacturing Scheduling Using Intelligent Agents , 2002, IEEE Intell. Syst..

[12]  Wei Chen,et al.  A Mobile Cloud Based Scheduling Strategy for Industrial Internet of Things , 2018, IEEE Access.

[13]  Alexandre Dolgui,et al.  A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0 , 2016 .

[14]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

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

[16]  Chin Soon Chong,et al.  Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system , 2017, J. Intell. Manuf..

[17]  Sang-Hwa Chung,et al.  Enhanced time-slotted channel hopping scheduling with quick setup time for industrial Internet of Things networks , 2017, Int. J. Distributed Sens. Networks.

[18]  Sang Do Noh,et al.  Smart manufacturing: Past research, present findings, and future directions , 2016, International Journal of Precision Engineering and Manufacturing-Green Technology.

[19]  Fei Tao,et al.  Energy adaptive immune genetic algorithm for collaborative design task scheduling in Cloud Manufacturing system , 2011, 2011 IEEE International Conference on Industrial Engineering and Engineering Management.

[20]  Jinliang Ding,et al.  Two-objective stochastic flow-shop scheduling with deteriorating and learning effect in Industry 4.0-based manufacturing system , 2017, Appl. Soft Comput..

[21]  W. Xiang,et al.  Ant colony intelligence in multi-agent dynamic manufacturing scheduling , 2008, Eng. Appl. Artif. Intell..

[22]  Weiming Shen,et al.  Agent-based distributed manufacturing process planning and scheduling: a state-of-the-art survey , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[23]  Xiaofei Xu,et al.  Scheduling Methodology for Production Services in Cloud Manufacturing , 2012, 2012 International Joint Conference on Service Sciences.

[24]  Panos M. Pardalos,et al.  Uniform parallel machine scheduling problems with fixed machine cost , 2018, Optim. Lett..

[25]  Stefano Riemma,et al.  A negotiation scheme for autonomous agents in job shop scheduling , 2002, Int. J. Comput. Integr. Manuf..

[26]  Richard Y. K. Fung,et al.  Dynamic shopfloor scheduling in multi-agent manufacturing systems , 2006, Expert Syst. Appl..

[27]  Hai Wan,et al.  Multitask Oriented Virtual Resource Integration and Optimal Scheduling in Cloud Manufacturing , 2014, J. Appl. Math..

[28]  Sicheng Zhang,et al.  Flexible job-shop scheduling/rescheduling in dynamic environment: a hybrid MAS/ACO approach , 2017, Int. J. Prod. Res..

[29]  Sanja Petrovic,et al.  SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS , 2006 .

[30]  Dimitris Mourtzis,et al.  A cloud-based cyber-physical system for adaptive shop-floor scheduling and condition-based maintenance , 2018 .

[31]  Ray Y. Zhong,et al.  Workload-based multi-task scheduling in cloud manufacturing , 2017 .

[32]  Jin Wang,et al.  Game Theory Based Real‐Time Shop Floor Scheduling Strategy and Method for Cloud Manufacturing , 2017, Int. J. Intell. Syst..

[33]  Fei Tao,et al.  Cloud manufacturing based service encapsulation and optimal configuration method for injection molding machine , 2019, J. Intell. Manuf..

[34]  Yang Cao,et al.  A TQCS-based service selection and scheduling strategy in cloud manufacturing , 2016 .

[35]  Lyes Khoukhi,et al.  Industrial IoT Data Scheduling Based on Hierarchical Fog Computing: A Key for Enabling Smart Factory , 2018, IEEE Transactions on Industrial Informatics.

[36]  Yongkui Liu,et al.  Industry 4.0 and Cloud Manufacturing: A Comparative Analysis , 2016 .

[37]  Lihui Wang,et al.  GA-based adaptive setup planning toward process planning and scheduling integration , 2009 .

[38]  Jie Zhang,et al.  Multi-agent-based hierarchical collaborative scheduling in re-entrant manufacturing systems , 2016 .

[39]  W. Art Chaovalitwongse,et al.  Multi-objective optimal scheduling of reconfigurable assembly line for cloud manufacturing , 2017, Optim. Methods Softw..

[40]  Tie Qiu,et al.  EABS: An Event-Aware Backpressure Scheduling Scheme for Emergency Internet of Things , 2018, IEEE Transactions on Mobile Computing.

[41]  Kagermann Henning.  Recommendations for implementing the strategic initiative INDUSTRIE 4.0 , 2013 .