nach oben

Journal of Intelligent Manufacturing

Erschienen in:

08.10.2014

Intelligent assembly system for mechanical products and key technology based on internet of things

verfasst von: Mingzhou Liu, Jing Ma, Ling Lin, Maogen Ge, Qiang Wang, Conghu Liu

Erschienen in: Journal of Intelligent Manufacturing | Ausgabe 2/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The Internet of Things (IoT) has a significant effect on the development of manufacturing technology. Therefore, according to the analysis of the challenges and opportunities faced by manufacturing industry, this study uses the assembly process of mechanical products as the research object and analyzes the characteristics of IoT-based manufacturing systems. To improve the interconnection, perception, efficiency, and intelligence of the assembly system, this study proposes the concept of IoT-enabled intelligent assembly system for mechanical products (IIASMP). The IIASMP framework, which is based on advanced techniques such as information and communication technology, sensor network, and radio-frequency identification, is then presented. Key technologies under this framework, including assembly resources identification, information interaction technology, multi-source data perception and fusion, intelligent assembly agent, and value-added data and dynamic self-adaptive optimization, are described. Finally, the current results of IIASMP are described in the case study. The proposed framework and methods aims to have an important reference value for applying the key technologies and be used widely in the intelligent manufacturing field.

Vorheriger Artikel Variation source identification for deep hole boring process of cutting-hard workpiece based on multi-source information fusion using evidence theory

Nächster Artikel A packet scheduler for real-time 6LoWPAN wireless networks in manufacturing systems

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Aguilar-Ponce, R., Kumar, A., Tecpanecatl-Xihuitl, J. L., & Bayoumi, M. (2007). A network of sensor-based framework for automated visual surveillance. Journal of Network and Computer Applications, 30(3), 1244–1271.CrossRef

Al-Habaibeh, A., & Parkin, R. (2003). An autonomous low-cost infrared system for the online monitoring of manufacturing processes using novelty detection. International Journal of Advanced Manufacturing Technology, 22(3–4), 249–258.CrossRef

Atlas, L. E., Bernard, G. D., & Narayanan, S. B. (1996). Applications of time-frequency analysis to signals from manufacturing and machine monitoring sensors. Proceedings of the IEEE, 84(9), 1319–1329.CrossRef

Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805.CrossRef

Bargelis, A., Hoehne, G., & Cesnulevicius, A. (2004). Intelligent functional model for costs minimization in hybrid manufacturing systems. Informatica, 15(1), 3–22.

Beach, R., Muhlemann, A. P., Price, D. H. R., Paterson, A., & Sharp, J. A. (2000). A review of manufacturing flexibility. European Journal of Operational Research, 122(1), 41–57.CrossRef

Changfeng, Y., Dinghua, Z., Wenli, P., & Kun, B. (2006). Research on resources optimisation deployment model and algorithm for collaborative manufacturing process. International Journal of Production Research, 44(16), 3279–3301.CrossRef

Chaves, L. W., & Nochta, Z. (2011). Breakthrough towards the internet of things. In D. C. Ranasinghe, Q. Z. Sheng & S. Zeadally (Eds.), Unique Radio Innovation For The 21st Century (pp. 25–38). Berlin: Springer. http://link.springer.com/chapter/10.1007/978-3-642-03462-6_2 .

Chen, R. S., & Tu, M. A. (2009). Development of an agent-based system for manufacturing control and coordination with ontology and RFID technology. Expert Systems with Applications, 36(4), 7581–7593.CrossRef

Chen, K. Y. (2012). Cell controller design for RFID based flexible manufacturing systems. International Journal of Computer Integrated Manufacturing, 25(1), 35–50.CrossRef

Chiu, S. W. (2008). An optimization problem of manufacturing systems with stochastic machine breakdown and rework process. Applied Stochastic Models in Business and Industry, 24(3), 203–219.CrossRef

Choudhary, A. K., Harding, J. A., & Tiwari, M. K. (2009). Data mining in manufacturing: A review based on the kind of knowledge. Journal of Intelligent Manufacturing, 20(5), 501–521.CrossRef

Chryssolouris, G., Mavrikios, D., Papakostas, N., Mourtzis, D., Michalos, G., & Georgoulias, K. (2009). Digital manufacturing: History, perspectives, and outlook. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(5), 451–462.CrossRef

Cutting-Decelle, A. F., Young, R. I., Michel, J. J., Grangel, R., Le Cardinal, J., & Bourey, J. P. (2007). ISO 15531 MANDATE: A product-process-resource based approach for managing modularity in production management. Concurrent Engineering, 15(2), 217–235.CrossRef

Dai, Q., Zhong, R., Huang, G. Q., Qu, T., Zhang, T., & Luo, T. (2012). Radio frequency identification-enabled real-time manufacturing execution system: A case study in an automotive part manufacturer. International Journal of Computer Integrated Manufacturing, 25(1), 51–65.CrossRef

Deshpande, S., & Cagan, J. (2004). An agent based optimization approach to manufacturing process planning. Journal of Mechanical Design, 126(1), 46–55.CrossRef

Drath, R., Luder, A., Peschke, J., & Hundt, L. (2008). AutomationML-the glue for seamless automation engineering. In IEEE international conference on emerging technologies and factory automation, 2008. ETFA 2008. (pp. 616–623). doi:10.1109/ETFA.2008.4638461.

Edinbarough, I., Balderas, R., & Bose, S. (2005). A vision and robot based online inspection monitoring system for electronic manufacturing. Computers in Industry, 56(8–9), 986–996.CrossRef

Giusto, D., Lera, A., Morabito, G., & Atzori, L. (2010). The Internet of Things. Berlin: Springer.CrossRef

Golnabi, H., & Asadpour, A. (2007). Design and application of industrial machine vision systems. Robotics and Computer-Integrated Manufacturing, 23(6), 630–637.CrossRef

Guo, Q., & Zhang, M. (2008). Research on intelligent manufacturing system based on multi-agent. In C. Xiong, H. Liu, Y. Huang & Y. Xiong (Eds.), Intelligent Robotics and Applications (pp. 829–838). Berlin: Springer. http://link.springer.com/chapter/10.1007/978-3-540-88518-4_89.

Guo, Q., & Zhang, M. (2009). A novel approach for multi-agent-based intelligent manufacturing system. Information Sciences, 179(18), 3079–3090.CrossRef

Huang, C. Y. (2002). Distributed manufacturing execution systems: A workflow perspective. Journal of Intelligent Manufacturing, 13(6), 485–497.CrossRef

Jain, A., Jain, P. K., Chan, F. T., & Singh, S. (2013). A review on manufacturing flexibility. International Journal of Production Research, 51(19), 5946–5970.CrossRef

Jardim-Goncalves, R., Sarraipa, J., Agostinho, C., & Panetto, H. (2011). Knowledge framework for intelligent manufacturing systems. Journal of Intelligent Manufacturing, 22(5), 725–735.CrossRef

Jiang, C. Y., Wang, J. B., & Jiang, J. J. (2006). Research on analyzing and coding technology of manufacturing information resource based on granularity-structure. In C. Jiang, G. Liu, D. Zhang & X. Xu (Eds.), Materials science forum (Vol. 532, pp. 1080–1083). Pune: Trans Tech Publications. http://www.scientific.net/MSF.532-533.1080.

Kletti, J. (2007). Manufacturing execution systems-MES. Berlin: Springer.CrossRef

Kumar, P., Barua, P., & Gaindhar, J. (2000). Quality optimization (multi-characteristics) through Taguchi’s technique and utility concept. Quality and Reliability Engineering International, 16(6), 475–485.CrossRef

Lee, C. S., Jiang, C. C., & Hsieh, T. C. (2006). A genetic fuzzy agent using ontology model for meeting scheduling system. Information Sciences, 176(9), 1131–1155.CrossRef

Liu, W., Zheng, L., Sun, D., Liao, X., Zhao, M., Su, J., et al. (2012). RFID-enabled real-time production management system for Loncin motorcycle assembly line. International Journal of Computer Integrated Manufacturing, 25(1), 86–99.CrossRef

Luck, M., & d’Inverno, M. (2001). A conceptual framework for agent definition and development. The Computer Journal, 44(1), 1–20.CrossRef

Madejski, J. (2007). Survey of the agent-based approach to intelligent manufacturing. Journal of Achievements in Materials and Manufacturing Engineering, 21(1), 67–70.

Makris, S., Michalos, G., & Chryssolouris, G. (2012). RFID driven robotic assembly for random mix manufacturing. Robotics and Computer-Integrated Manufacturing, 28(3), 359–365.CrossRef

McFarlane, D., Sarma, S., Chirn, J. L., Wong, C. Y., & Ashton, K. (2003). Auto-ID systems and intelligent manufacturing control. Engineering Applications of Artificial Intelligence, 16(4), 365–376.CrossRef

Michalos, G., Makris, S., Papakostas, N., Mourtzis, D., & Chryssolouris, G. (2010). Automotive assembly technologies review: Challenges and outlook for a flexible and adaptive approach. CIRP Journal of Manufacturing Science and Technology, 2(2), 81–91.CrossRef

Mitchell, H. B. (2007). An introduction. In MultiSensor data fusion (pp. 3–13). Berlin: Springer.

Monostori, L., & Prohaszka, J. (1993). A step towards intelligent manufacturing: Modelling and monitoring of manufacturing processes through artificial neural networks. CIRP Annals-Manufacturing Technology, 42(1), 485–488.CrossRef

Nasr, E. S. A., & Kamrani, A. K. (2008). Intelligent design and manufacturing. In A. K. Kamrani & E. S. Abouel Nasr (Eds.), Collaborative engineering (pp. 103–125). New York: Springer. http://link.springer.com/chapter/10.1007/978-0-387-47321-5_6.

Nearchou, A. C., & Omirou, S. L. (2006). Differential evolution for sequencing and scheduling optimization. Journal of Heuristics, 12(6), 395–411.CrossRef

Oztemel, E. (2010). Intelligent manufacturing systems. In L. Benyoucef & B. Grabot (Eds.), Artificial intelligence techniques for networked manufacturing enterprises management (pp. 1–41). London: Springer. http://link.springer.com/chapter/10.1007/978-0-387-47321-5_6.

Oztemel, E., & Tekez, E. K. (2009). A general framework of a reference model for intelligent integrated manufacturing systems (REMIMS). Engineering Applications of Artificial Intelligence, 22(6), 855–864.CrossRef

Qu, T., Yang, H., Huang, G. Q., Zhang, Y., Luo, H., & Qin, W. (2012). A case of implementing RFID-based real-time shop-floor material management for household electrical appliance manufacturers. Journal of Intelligent Manufacturing, 23(6), 2343–2356.CrossRef

Ruiz, N., Giret, A., Botti, V., & Feria, V. (2011). Agent-supported simulation environment for intelligent manufacturing and warehouse management systems. International Journal of Production Research, 49(5), 1469–1482.CrossRef

Sabar, M., Montreuil, B., & Frayret, J.-M. (2012). An agent-based algorithm for personnel shift-scheduling and rescheduling in flexible assembly lines. Journal of Intelligent Manufacturing, 23(6), 2623–2634.CrossRef

Saenz de Ugarte, B., Artiba, A., & Pellerin, R. (2009). Manufacturing execution system—a literature review. Production Planning and Control, 20(6), 525–539.CrossRef

Silvestre, J., & Sempere, V. (2007). An architecture for flexible scheduling in Profibus networks. Computer Standards & Interfaces, 29(5), 546–560.CrossRef

Sung, W. T., & Hsu, Y. C. (2011). Designing an industrial real-time measurement and monitoring system based on embedded system and ZigBee. Expert Systems with Applications, 38(4), 4522–4529.CrossRef

Thiesse, F., Floerkemeier, C., Harrison, M., Michahelles, F., & Roduner, C. (2009). Technology, standards, and real-world deployments of the EPC network. IEEE Internet Computing, 13(2), 36–43.CrossRef

Trappey, A. J., Lu, T.-H., & Fu, L.-D. (2009). Development of an intelligent agent system for collaborative mold production with RFID technology. Robotics and Computer-Integrated Manufacturing, 25(1), 42–56.CrossRef

Tseng, M. C., & Lin, W. Y. (2001). Mining generalized association rules with multiple minimum supports. In Y. Kambayashi, W. Winiwarter & M. Arikawa (Eds.), Data warehousing and knowledge discovery (pp. 11–20). Berlin, Springer. http://link.springer.com/chapter/10.1007/3-540-44801-2_2.

Tu, M., Lin, J. H., Chen, R. S., Chen, K. Y., & Jwo, J. S. (2009). Agent-based control framework for mass customization manufacturing with UHF RFID technology. Ieee Systems Journal, 3(3), 343–359.

Wang, X. Z., & McGreavy, C. (1998). Automatic classification for mining process operational data. Industrial & Engineering Chemistry Research, 37(6), 2215–2222. doi:10.1021/ie970620h.CrossRef

Youssef, S. M., & Salem, R. M. (2007). Automated barcode recognition for smart identification and inspection automation. Expert Systems with Applications, 33(4), 968–977.CrossRef

Zayati, A., Biennier, F., Moalla, M., & Badr, Y. (2012). Towards lean service bus architecture for industrial integration infrastructure and pull manufacturing strategies. Journal of Intelligent Manufacturing, 23(1), 125–139.CrossRef

Zhang, H. P., Gen, M. S., & Seo, Y. H. (2006). An effective coding approach for multiobjective integrated resource selection and operation sequences problem. Journal of Intelligent Manufacturing, 17(4), 385–397.

Zhang, Y., Huang, G. Q., Qu, T., & Ho, O. (2010). Agent-based workflow management for RFID-enabled real-time reconfigurable manufacturing. International Journal of Computer Integrated Manufacturing, 23(2), 101–112.CrossRef

Zhang, Y., Jiang, P., Huang, G., Qu, T., Zhou, G., & Hong, J. (2012). RFID-enabled real-time manufacturing information tracking infrastructure for extended enterprises. Journal of Intelligent Manufacturing, 23(6), 2357–2366.CrossRef

Zijm, W. (2000). Towards intelligent manufacturing planning and control systems. OR-Spektrum, 22(3), 313–345.CrossRef

Titel: Intelligent assembly system for mechanical products and key technology based on internet of things
verfasst von: Mingzhou Liu
Jing Ma
Ling Lin
Maogen Ge
Qiang Wang
Conghu Liu
Publikationsdatum: 08.10.2014
Verlag: Springer US
Erschienen in: Journal of Intelligent Manufacturing / Ausgabe 2/2017
Print ISSN: 0956-5515
Elektronische ISSN: 1572-8145
DOI: https://doi.org/10.1007/s10845-014-0976-6

Premium Partner

Marktübersichten

Die im Laufe eines Jahres in der „adhäsion“ veröffentlichten Marktübersichten helfen Anwendern verschiedenster Branchen, sich einen gezielten Überblick über Lieferantenangebote zu verschaffen.

Zur Marktübersicht

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 2/2017

A multi-objective scheduling algorithm with self-evolutionary feature for job-shop-like knowledgeable manufacturing cell

Detection of defective embedded bearings by sound analysis: a machine learning approach

New dynamic heuristic for the optimization of opportunities to use new and remanufactured spare part in stochastic degradation context

Modified genetic algorithm for simple straight and U-shaped assembly line balancing with fuzzy processing times

Measures of reconfigurability and its key characteristics in intelligent manufacturing systems

Simultaneous order scheduling and mixed-model sequencing in assemble-to-order production environment: a multi-objective hybrid artificial bee colony algorithm

Premium Partner

Marktübersichten