Real-Time Information-Driven Production Scheduling System

During traditional manufacturing process, it’s hard to achieve real-time production scheduling because of the inefficient feedback of real-time information in the shop floor. To address the mentioned challenge, a framework of real-time information-driven production system is designed in this chapter. It’s also used to bridge the gap between production planning and control. The real-time information-driven production system consists of four modules. They are equipment agent, capability evaluation agent, real-time scheduling agent, and production execution monitor agent. Equipment agent is employed to capture and process real-time information in the shop floor. In the process planning stage, capability evaluation agent is used to accomplish the optimal tasks allocation according to the real-time utilization ratio of each machine. As the name suggests, real-time scheduling agent is responsible for the manufacturing tasks scheduling or rescheduling according to the traced real-time information. Production execution monitor agent aims to track and trace the real-time status of different manufacturing processes. The running mechanism of each agent is described in detail in this chapter.

[1]  Yu-Cheng Lin,et al.  Developing mobile 2D barcode/RFID-based maintenance management system , 2014 .

[2]  Mehmet Emin Aydin,et al.  A multi-agent based approach for change management in manufacturing enterprises , 2015, J. Intell. Manuf..

[3]  Rubén Ruiz,et al.  Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics , 2005, Eur. J. Oper. Res..

[4]  Pingyu Jiang,et al.  RFID-based wireless manufacturing for walking-worker assembly islands with fixed-position layouts , 2007 .

[5]  Vittaldas V. Prabhu,et al.  A Dynamic Algorithm for Distributed Feedback Control for Manufacturing Production, Capacity, and Maintenance , 2015, IEEE Transactions on Automation Science and Engineering.

[6]  Astghik Babayan,et al.  Solving the n-job 3-stage flexible flowshop scheduling problem using an agent-based approach , 2004 .

[7]  Amy J. C. Trappey,et al.  Development of an intelligent agent system for collaborative mold production with RFID technology , 2009 .

[8]  N. K.C. Krothapalli,et al.  Design of negotiation protocols for multi-agent manufacturing systems , 1999 .

[9]  Nebil Buyurgan,et al.  Application of the analytical hierarchy process for real-time scheduling and part routing in advanced manufacturing systems , 2008 .

[10]  Wai Keung Wong,et al.  Genetic optimization of order scheduling with multiple uncertainties , 2008, Expert Syst. Appl..

[11]  Dong-Ho Lee,et al.  Real-time scheduling for reentrant hybrid flow shops: A decision tree based mechanism and its application to a TFT-LCD line , 2011, Expert Syst. Appl..

[12]  Michael J. Shaw,et al.  A multi-agent framework for the coordination and integration of information systems , 1998 .

[13]  Ying Yan,et al.  A two-layer dynamic scheduling method for minimising the earliness and tardiness of a re-entrant production line , 2012 .

[14]  Xiwen Lu,et al.  Integrated scheduling of production and delivery on a single machine with availability constraint , 2015, Theor. Comput. Sci..

[15]  Ting Qu,et al.  Agent-based smart objects management system for real-time ubiquitous manufacturing , 2011 .

[16]  Aldo R. Vecchietti,et al.  An intelligent agent for ERP's data structure analysis based on ANSI/ISA-95 standard , 2015, Comput. Ind..

[17]  Guan-Chun Luh,et al.  A multi-modal immune algorithm for the job-shop scheduling problem , 2009, Inf. Sci..

[18]  Michael Baldea,et al.  A time scale-bridging approach for integrating production scheduling and process control , 2015, Comput. Chem. Eng..

[19]  Birgit Vogel-Heuser,et al.  Coupling heterogeneous production systems by a multi-agent based cyber-physical production system , 2014, 2014 12th IEEE International Conference on Industrial Informatics (INDIN).

[20]  T. N. Wong,et al.  An ontology based approach to organize multi-agent assisted supply chain negotiations , 2013, Comput. Ind. Eng..

[21]  Arun Kumar,et al.  An agent-based framework for collaborative negotiation in the global manufacturing supply chain network , 2006 .

[22]  Michael Grüninger,et al.  Combining RFID with ontologies to create smart objects , 2010 .

[23]  El Houssaine Aghezzaf,et al.  Production , Manufacturing and Logistics Production planning and warehouse management in supply networks with inter-facility mold transfers , 2007 .

[24]  Chou-Jung Hsu,et al.  An unrelated parallel machine scheduling problem with past-sequence-dependent setup time and learning effects , 2010, The 40th International Conference on Computers & Indutrial Engineering.

[25]  Manoj Kumar Tiwari,et al.  Integration of process planning and scheduling using mobile-agent based approach in a networked manufacturing environment , 2016, Comput. Ind. Eng..

[26]  Pravin Varaiya,et al.  Real-Time Scheduling of Distributed Resources , 2013, IEEE Transactions on Smart Grid.

[27]  Chien-Yi Huang,et al.  Innovative parametric design for environmentally conscious adhesive dispensing process , 2015, J. Intell. Manuf..

[28]  Stefano Giordani,et al.  A distributed multi-agent production planning and scheduling framework for mobile robots , 2013, Comput. Ind. Eng..

[29]  Ting Qu,et al.  Agent-based Smart Gateway for RFID-enabled real-time wireless manufacturing , 2011 .

[30]  Hao Luo,et al.  Real-time scheduling for hybrid flowshop in ubiquitous manufacturing environment , 2015, Comput. Ind. Eng..

[31]  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).

[32]  Suh-Jenq Yang,et al.  Unrelated parallel-machine scheduling problems with multiple rate-modifying activities , 2013, Inf. Sci..

[33]  George Q. Huang,et al.  Wireless manufacturing: a literature review, recent developments, and case studies , 2009 .

[34]  Jerry Y. H. Fuh,et al.  An adaptive and upgradable agent-based system for coordinated product development and manufacture , 2004 .

[35]  Paulo Tabuada,et al.  Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks , 2007, IEEE Transactions on Automatic Control.

[36]  S. Subramaniam,et al.  Real time shop floor monitoring system for a better production line management , 2007, 2007 Asia-Pacific Conference on Applied Electromagnetics.

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

[38]  Jose Arturo Garza-Reyes,et al.  A multi-agent architecture for outsourcing SMEs manufacturing supply chain , 2015 .

[39]  Shuang Chen,et al.  An RFID-based digital warehouse management system in the tobacco industry: a case study , 2010 .

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

[41]  Dimitris Kiritsis,et al.  Modelling for product information tracking and feedback via wireless technology in closed-loop supply chains , 2009, Int. J. Comput. Integr. Manuf..

[42]  Jie Zhang,et al.  A Multi-Agent-Based Agile Shop Floor Control System , 2002 .

[43]  Joseph Y.-T. Leung,et al.  Integrated scheduling of production and distribution to minimize total cost using an improved ant colony optimization method , 2015, Comput. Ind. Eng..

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

[45]  Luis Ribeiro,et al.  An Axiomatic Design of a Multiagent Reconfigurable Mechatronic System Architecture , 2015, IEEE Transactions on Industrial Informatics.

[46]  Hyacinth S. Nwana,et al.  An Introduction to Agent Technology , 1997, Software Agents and Soft Computing.

[47]  James H. Anderson,et al.  Parallel Real-Time Task Scheduling on Multicore Platforms , 2006, 2006 27th IEEE International Real-Time Systems Symposium (RTSS'06).

[48]  José Manuel Galán,et al.  Multi-agent technology for scheduling and control projects in multi-project environments. An Auction based approach , 2009, Inteligencia Artif..

[49]  Javad Sattarvand,et al.  Long term production planning of open pit mines by ant colony optimization , 2015, Eur. J. Oper. Res..

[50]  Omar Chiotti,et al.  An autonomous multi-agent approach to supply chain event management , 2012 .

[51]  Xiao Wang,et al.  Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system , 2016, J. Intell. Manuf..

[52]  John W. Sutherland,et al.  A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction , 2011 .