A Framework for Smart Production-Logistics Systems Based on CPS and Industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems.

[1]  P. Conway,et al.  Towards Industrial Internet of Things: Crankshaft Monitoring, Traceability and Tracking Using RFID , 2016 .

[2]  S. Carlsen,et al.  WirelessHART Versus ISA100.11a: The Format War Hits the Factory Floor , 2011, IEEE Industrial Electronics Magazine.

[3]  Luc Bongaerts,et al.  Reference architecture for holonic manufacturing systems: PROSA , 1998 .

[4]  Lida Xu,et al.  Internet of Things for Enterprise Systems of Modern Manufacturing , 2014, IEEE Transactions on Industrial Informatics.

[5]  Gang Feng,et al.  Output Consensus of Heterogeneous Linear Multi-Agent Systems by Distributed Event-Triggered/Self-Triggered Strategy , 2017, IEEE Transactions on Cybernetics.

[6]  Hartmut Schmeck,et al.  Ant colony optimization for resource-constrained project scheduling , 2000, IEEE Trans. Evol. Comput..

[7]  Fei Tao,et al.  IoT-Based Intelligent Perception and Access of Manufacturing Resource Toward Cloud Manufacturing , 2014, IEEE Transactions on Industrial Informatics.

[8]  Lars Wischhof,et al.  Information dissemination in self-organizing intervehicle networks , 2005, IEEE Transactions on Intelligent Transportation Systems.

[9]  A. Valenzano,et al.  Synchronize Your Watches: Part II: Special-Purpose Solutions for Distributed Real-Time Control , 2013, IEEE Industrial Electronics Magazine.

[10]  Mohsen Guizani,et al.  Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications , 2015, IEEE Communications Surveys & Tutorials.

[11]  Jayant Rajgopal,et al.  Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study , 2007 .

[12]  Ray Y. Zhong,et al.  Analytical target cascading for optimal configuration of cloud manufacturing services , 2017 .

[13]  Carlos A. Coello Coello,et al.  Handling multiple objectives with particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[14]  Fei Tao,et al.  CCIoT-CMfg: Cloud Computing and Internet of Things-Based Cloud Manufacturing Service System , 2014, IEEE Transactions on Industrial Informatics.

[15]  Giacomo Liotta,et al.  Optimization and Simulation of Collaborative Networks for Sustainable Production and Transportation , 2016, IEEE Transactions on Industrial Informatics.

[16]  Ting Qu,et al.  Synchronized production and logistics via ubiquitous computing technology , 2017 .

[17]  Yingfeng Zhang,et al.  Real-time information capturing and integration framework of the internet of manufacturing things , 2015, Int. J. Comput. Integr. Manuf..

[18]  Carlos Eduardo Pereira,et al.  The Migration from Conventional Manufacturing Systems for Multi-Agent Paradigm: the First Step , 2015, DoCEIS.

[19]  Jay Lee,et al.  A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems , 2015 .

[20]  Xu Yang,et al.  Simulation studies of information propagation in a self-organizing distributed traffic information system , 2005 .

[21]  Philippe Lacomme,et al.  Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles , 2013 .

[22]  Samuel H. Huang,et al.  Computer-assisted supply chain configuration based on supply chain operations reference (SCOR) model , 2005, Comput. Ind. Eng..

[23]  Hong Wen,et al.  Cooperative Jamming for Physical Layer Security Enhancement in Internet of Things , 2018, IEEE Internet of Things Journal.

[24]  Wu He,et al.  Internet of Things in Industries: A Survey , 2014, IEEE Transactions on Industrial Informatics.

[25]  A. Gunasekaran,et al.  Agile manufacturing: The drivers, concepts and attributes , 1999 .

[26]  Anne L'Anton,et al.  A modeling framework for manufacturing services in Service-oriented Holonic Manufacturing Systems , 2016, Eng. Appl. Artif. Intell..

[27]  George Q. Huang,et al.  IoT-based real-time production logistics synchronization system under smart cloud manufacturing , 2016 .

[28]  Luis Ribeiro,et al.  Collaborative routing of products using a self-organizing mechatronic agent framework - A simulation study , 2015, Comput. Ind..

[29]  Gamboa QuintanillaFrancisco,et al.  A modeling framework for manufacturing services in Service-oriented Holonic Manufacturing Systems , 2016 .

[30]  Damien Trentesaux,et al.  A holonic multi-agent methodology to design sustainable intelligent manufacturing control systems , 2017 .

[31]  Ray Y. Zhong,et al.  Visualization of RFID-enabled shopfloor logistics Big Data in Cloud Manufacturing , 2015, The International Journal of Advanced Manufacturing Technology.

[32]  Haibin Zhu,et al.  Adaptive Collaboration Systems: Self-Sustaining Systems for Optimal Performance , 2015, IEEE Systems, Man, and Cybernetics Magazine.

[33]  Miquel Angel Piera,et al.  A coloured Petri net-based hybrid heuristic search approach to simultaneous scheduling of machines and automated guided vehicles , 2016 .

[34]  W. D. Grover,et al.  Self-organizing broad-band transport networks , 1997, Proc. IEEE.

[35]  Sebastian VanSyckel,et al.  A survey on engineering approaches for self-adaptive systems , 2015, Pervasive Mob. Comput..

[36]  Chunjie Zhou,et al.  Anomaly Detection Based on Zone Partition for Security Protection of Industrial Cyber-Physical Systems , 2018, IEEE Transactions on Industrial Electronics.

[37]  Roman Obermaisser,et al.  Incremental, Distributed, and Concurrent Scheduling in Systems-of-Systems with Real-Time Requirements , 2015, 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing.

[38]  Christian Diedrich,et al.  Integration of Classical Components Into Industrial Cyber–Physical Systems , 2016, Proceedings of the IEEE.

[39]  Kun Zhu,et al.  An Evolutionary Game for Distributed Resource Allocation in Self-Organizing Small Cells , 2015, IEEE Transactions on Mobile Computing.

[40]  José Barbosa,et al.  Dynamic self-organization in holonic multi-agent manufacturing systems: The ADACOR evolution , 2015, Comput. Ind..

[41]  László Monostori,et al.  Cooperative control in production and logistics , 2015, Annu. Rev. Control..

[42]  George Q. Huang,et al.  Agent-based workflow management for RFID-enabled real-time reconfigurable manufacturing , 2010, Int. J. Comput. Integr. Manuf..

[43]  Yingfeng Zhang,et al.  CPS-Based Smart Control Model for Shopfloor Material Handling , 2018, IEEE Transactions on Industrial Informatics.

[44]  Song Han,et al.  Online Mode Switch Algorithms for Maintaining Data Freshness in Dynamic Cyber-Physical Systems , 2016, IEEE Transactions on Knowledge and Data Engineering.

[45]  Paulo Leitão,et al.  Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges , 2016, Comput. Ind..

[46]  Gianluca Cena,et al.  On the Performance of IEEE 802.11e Wireless Infrastructures for Soft-Real-Time Industrial Applications , 2010, IEEE Transactions on Industrial Informatics.

[47]  Yingfeng Zhang,et al.  A Timed Colored Petri Net Simulation-Based Self-Adaptive Collaboration Method for Production-Logistics Systems , 2017 .

[48]  George Q. Huang,et al.  A generic analytical target cascading optimization system for decentralized supply chain configuration over supply chain grid , 2010 .

[49]  Paul Conway,et al.  Towards industrial internet of things , 2016 .

[50]  Ying Liu,et al.  Agent and Cyber-Physical System Based Self-Organizing and Self-Adaptive Intelligent Shopfloor , 2017, IEEE Transactions on Industrial Informatics.

[51]  A. Valenzano,et al.  Synchronize your watches: Part I: General-purpose solutions for distributed real-time control , 2013, IEEE Industrial Electronics Magazine.

[52]  Alasdair Gilchrist.  Introducing Industry 4.0 , 2016 .

[53]  J. E. Rooda,et al.  An augmented Lagrangian relaxation for analytical target cascading using the alternating direction method of multipliers , 2006 .

[54]  Athanasios V. Vasilakos,et al.  A Survey of Self-Organization Mechanisms in Multiagent Systems , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

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

[56]  Donald D. Eisenstein,et al.  Self-organizing logistics systems , 2010, Annu. Rev. Control..