Smart manufacturing process and system automation – A critical review of the standards and envisioned scenarios

Journal of Manufacturing Systems - Tập 56 - Trang 312-325 - 2020
Yuqian Lu1, Xun Xu1, Lihui Wang2
1Department of Mechanical Engineering, The University of Auckland, New Zealand
2KTH Royal Institute of Technology, Stockholm, Sweden

Tài liệu tham khảo

Wang, 2016, Challenges in smart manufacturing, J Manuf Syst, 40, 1, 10.1016/j.jmsy.2016.05.005 Coalition, 2011 Kagermann, 2013 Li, 2017, China’s manufacturing locus in 2025: With a comparison of “Made-in-China 2025” and “Industry 4.0, Technol Forecast Soc Change Lu, 2016, 22 MacDougall, 2014 Bitkom, 2013 2019 Kusiak, 2018, Smart manufacturing, Int J Prod Res, 56, 508, 10.1080/00207543.2017.1351644 Davis, 2012, Smart manufacturing, manufacturing intelligence and demand-dynamic performance, Comput Chem Eng, 47, 145, 10.1016/j.compchemeng.2012.06.037 Hu, 2013, Evolving paradigms of manufacturing: from mass production to mass customization and personalization, Procedia CIRP, 7, 3, 10.1016/j.procir.2013.05.002 Gu, 2018, Manufacturing system architecture for cost-effective mass-individualization, Manuf Lett, 16, 44, 10.1016/j.mfglet.2018.04.002 Koren, 2013 Mnih, 2015, Human-level control through deep reinforcement learning, Nature, 518, 529, 10.1038/nature14236 Chen, 2020, A review: knowledge reasoning over knowledge graph, Expert Syst Appl, 141, 10.1016/j.eswa.2019.112948 Wang, 2019, From intelligence science to intelligent manufacturing, Engineering, 5, 615, 10.1016/j.eng.2019.04.011 Wallace, 2013 Xu, 2017, Machine Tool 4.0 for the new era of manufacturing, Int J Adv Manuf Technol, 92, 1893, 10.1007/s00170-017-0300-7 Lu, 2020, Digital Twin-driven smart manufacturing: connotation, reference model, applications and research issues, Robot Comput Integr Manuf, 61, 10.1016/j.rcim.2019.101837 Kagermann, 2016 Industry 4.0 Standards. DIN - German Institute for Standardization n.d. https://www.din.de/en/innovation-and-research/industry-4-0/standards (accessed June 28, 2018). Adolph, 2016 2015 Bernstein, 2017, Contextualising manufacturing data for lifecycle decision-making, Int J Prod Lifecycle Manag, 10, 326, 10.1504/IJPLM.2017.090328 ISO, 2014 Wardhani, 2016, Model-based manufacturing based on STEP AP242, 1 Venkiteswaran, 2016, Semantic interoperability of GD&T data through ISO 10303 step AP242 Mabkhot, 2018, Requirements of the smart factory system: a survey and perspective, Machines, 6, 23, 10.3390/machines6020023 ISO, 2003 ISO, 2007 Hardwick, 2006, Lessons learned implementing STEP-NC AP-238, Int J Comput Integr Manuf, 19, 523, 10.1080/09511920600627170 Suh, 2003, Architecture and implementation of a shopfloor programming system for STEP-compliant CNC, Comput Des, 35, 1069 Nassehi, 2006, The application of multi-agent systems for STEP-NC computer aided process planning of prismatic components, Int J Mach Tools Manuf, 46, 559, 10.1016/j.ijmachtools.2005.06.005 Xu, 2006, Realization of STEP-NC enabled machining, Robot Comput Integr Manuf, 22, 144, 10.1016/j.rcim.2005.02.009 Shin, 2007, Reincarnation of G-code based part programs into STEP-NC for turning applications, Comput Des, 39, 1 Suh, 2006, STEP-compliant CNC system for turning: data model, architecture, and implementation, Comput Des, 38, 677 2013 Zivanovic, 2018, An approach for applying STEP-NC in robot machining, Robot Comput Integr Manuf, 49, 361, 10.1016/j.rcim.2017.08.009 Solvang, 2009, STEP-NC based industrial robot CAM system, IFAC Proceedings Volumes, 245, 10.3182/20090909-4-JP-2010.00043 Toquica, 2018, A STEP-NC compliant robotic machining platform for advanced manufacturing, Int J Adv Manuf Technol, 95, 3839, 10.1007/s00170-017-1466-8 Um, 2017, STEP-NC compliant process planning of additive manufacturing: remanufacturing, Int J Adv Manuf Technol, 88, 1215, 10.1007/s00170-016-8791-1 Bonnard, 2010, A new digital chain for additive manufacturing processes, Virtual Phys Prototyp, 5, 75, 10.1080/17452751003696916 AP 242 Edition 2 capabilities for Additive Manufacturing interoperability n.d. http://www.ap242.org/additive-manufacturing (accessed July 24, 2018). Sobel, 2015 Liu, 2019, A cyber-physical machine tools platform using OPC UA and MTConnect, J Manuf Syst, 51, 61, 10.1016/j.jmsy.2019.04.006 Helu, 2018, A standards-based approach for linking as-planned to as-fabricated product data, CIRP Ann., 67, 487, 10.1016/j.cirp.2018.04.039 Monnier, 2019, A proposed mapping method for aligning machine execution data to numerical control code, 66 DMSC. Home - QIF Standard n.d. http://qifstandards.org/ (accessed July 7, 2018). Morse, 2016, Interoperability: Linking Design and Tolerancing with Metrology, Procedia CIRP, 43, 13, 10.1016/j.procir.2016.04.106 Michaloski, 2013, Web-enabled, real-time, quality assurance for machining production systems, Procedia CIRP, 10, 332, 10.1016/j.procir.2013.08.051 2017 Lu, 2020, Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing, J Manuf Syst, 55, 348, 10.1016/j.jmsy.2020.05.001 Wollschlaeger, 2017, The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0, IEEE Ind Electron Mag, 11, 17, 10.1109/MIE.2017.2649104 Rowley, 2007, The wisdom hierarchy: representations of the DIKW hierarchy, J Inf Sci, 33, 163, 10.1177/0165551506070706 OPC Foundation. Unified Architecture - OPC Foundation n.d. https://opcfoundation.org/about/opc-technologies/opc-ua/ (accessed April 25, 2019). Miyazawa, 2011, OPC UA information model, data exchange, safety and security for IEC 61131–3, 1556 Trnka, 2012, OPC-UA information model for large-scale process control applications, 5793 Maka, 2011, OPC UA object oriented model for public transportation system, 311 Edrington, 2014, Machine monitoring system based on MTConnect technology, Procedia CIRP, 22, 92, 10.1016/j.procir.2014.07.148 Shin, 2016, Developing a virtual machining model to generate MTConnect machine-monitoring data from STEP-NC, Int J Prod Res, 54, 4487, 10.1080/00207543.2015.1064182 Grangel-Gonzalez, 2016, Towards a semantic administrative Shell for industry 4.0 components, 230 Grangel-Gonzalez, 2016, An RDF-based approach for implementing industry 4.0 components with administration shells, 1 Lu, 2018, Resource virtualization: a core technology for developing cyber-physical production systems, J Manuf Syst, 47, 128, 10.1016/j.jmsy.2018.05.003 Wang, 2009, Function block design for adaptive execution control of job shop machining operations, Int J Prod Res, 47, 3413, 10.1080/00207540701666212 Wang, 2008, Design of adaptive function blocks for dynamic assembly planning and control, J Manuf Syst, 27, 45, 10.1016/j.jmsy.2008.06.003 Wang, 2012, A review of function blocks for process planning and control of manufacturing equipment, J Manuf Syst, 31, 269, 10.1016/j.jmsy.2012.02.004 Wang, 2010, ASP: An adaptive setup planning approach for dynamic machine assignments, IEEE Trans Autom Sci Eng, 7, 2, 10.1109/TASE.2008.2011919 Hedberg, 2016, Testing the digital thread in support of model-based manufacturing and inspection, J Comput Inf Sci Eng, 16 Zhang, 2017, Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor, IEEE Trans Industr Inform, 13, 737, 10.1109/TII.2016.2618892 Chen, 2019, Improving cognitive ability of edge intelligent IIoT through machine learning, IEEE Netw, 33, 61, 10.1109/MNET.001.1800505 Adolphs, 2016 Gou, 1998, Holonic manufacturing scheduling: architecture, cooperation mechanism, and implementation, Comput Ind, 37, 213, 10.1016/S0166-3615(98)00100-6 Leitão, 2006, ADACOR: A holonic architecture for agile and adaptive manufacturing control, Comput Ind, 57, 121, 10.1016/j.compind.2005.05.005 Zambrano Rey, 2013, The control of myopic behavior in semi-heterarchical production systems: a holonic framework, Eng Appl Artif Intell, 26, 800, 10.1016/j.engappai.2012.08.011 Jana, 2013, Dynamic schedule execution in an agent based holonic manufacturing system, J Manuf Syst, 32, 801, 10.1016/j.jmsy.2013.07.004 Monostori, 2006, Agent-based systems for manufacturing, CIRP Ann Manuf Technol, 55, 697, 10.1016/j.cirp.2006.10.004 Leitão, 2009, Agent-based distributed manufacturing control: a state-of-the-art survey, Eng Appl Artif Intell, 22, 979, 10.1016/j.engappai.2008.09.005 Yeung, 2011, Behavioral modeling and verification of multi-agent systems for manufacturing control, Expert Syst Appl, 38, 13555 Chou, 2013, A bio-inspired mobile agent-based integrated system for flexible autonomic job shop scheduling, J Manuf Syst, 32, 752, 10.1016/j.jmsy.2013.01.005 Tharumarajah, 1996, Comparison of the bionic, fractal and holonic manufacturing system concepts, Int J Comput Integr Manuf, 9, 217, 10.1080/095119296131670 Ueda, 1997, Modelling of biological manufacturing systems for dynamic reconfiguration, CIRP Ann Manuf Technol, 46, 343, 10.1016/S0007-8506(07)60839-7 Wang, 2016, Combined strength of holons, agents and function blocks in cyber-physical systems, J Manuf Syst, 40, 25, 10.1016/j.jmsy.2016.05.002 Caesar, 2019, vol. 34, 191 Brennan, 2001, Evaluating the performance of reactive control architectures for manufacturing production control, Comput Ind, 46, 235, 10.1016/S0166-3615(01)00108-7 Buşoniu, 2008, A comprehensive survey of multiagent reinforcement learning, IEEE Trans Syst Man Cybern Part C, 38, 156, 10.1109/TSMCC.2007.913919 Panait, 2005, Cooperative multi-agent learning: the state of the art, Auton Agent Multi Agent Syst, 11, 387, 10.1007/s10458-005-2631-2 Lowe, 2017, Multi-agent actor-critic for mixed cooperative-competitive environments, Advances in Neural Information Processing Systems, Vol. 2017- December, Neural Information Processing Systems Foundation, 6380 Lu, 2019, Cloud-based manufacturing equipment and big data analytics to enable on-demand manufacturing services, Robot Comput Integr Manuf, 57, 92, 10.1016/j.rcim.2018.11.006 Xu, 2012, From cloud computing to cloud manufacturing, Robot Comput Integr Manuf, 28, 75, 10.1016/j.rcim.2011.07.002 Open Asset Administration Shell n.d. http://acplt.github.io/openAAS/ (accessed May 12, 2020). Smart Manufacturing Systems (SMS) Test Bed | NIST n.d. https://www.nist.gov/laboratories/tools-instruments/smart-manufacturing-systems-sms-test-bed (accessed May 12, 2020). Eclipse IoT - Leading open source community for IoT innovation n.d. https://iot.eclipse.org/ (accessed May 12, 2020).