Abstract
Industrial robots (IRs) are the important driving force to enable the production activities more automotive and highly efficient in modern manufacturing systems. However, in order to realize the effective employment and intelligent configuration of IRs in cloud manufacturing environment, it is required that the sustainable manufacturing capabilities of IRs can be described in a unified and formal manner. In this paper, a unified sustainable manufacturing capability (SMC) of the IR model is constructed in terms of functional attributes, structural information, activities and process condition. A hybrid logic description method integrating Ontology Web Language with dynamic description logic (DLL) is adopted to provide a semantical representation to both the static and dynamic characteristics of SMC. An interval-state description method is proposed to present energy consumption during the IR’s process in sections. Based on the constructed model, three types of rules are defined to reason the capability of IRs, including stability, energy consumption and production capacity. Finally, a cloud-based prototype system architecture is illustrated. An IR service platform is developed and implemented to verify the proposed model and the defined rules.
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Li BH, Zhang L, Wang SL, Tao F, Cao JW, Jiang XD, Song X, Cai XD (2010) Cloud manufacturing: a new service-oriented networked manufacturing model [J]. Comput Integr Manuf Syst 16(1):1–7
Xu X (2012) From cloud computing to cloud manufacturing [J]. Robot Comput Integr Manuf 28(1):75–86
** WV, Xun W (2013) Xu, An interoperable solution for cloud manufacturing [J]. Robot Comput Integr Manuf 29(4):232–247
Tao F, Zhang L, Guo H, Luo YL, Ren L (2011) Typical characteristics of cloud manufacturing and several key issues of cloud service composition [J]. Comput Integr Manuf Syst 17(3):477–486
Ren L, Zhang L, Wang L, Chai FTX (2014) Cloud manufacturing: key characteristics and applications [J]. Int J Comput Integr Manuf:1–15
Tao F, Feng Y, Zhang L, Liao TW (2014) CLPS-GA: a case library and Pareto solution-based hybrid genetic algorithm for energy-aware cloud service scheduling [J]. Appl Soft Comput 19:264–279
Wadhwa RS, Lien TK (2013) Manufacturing automation for environmentally sustainable foundries. In: In Re-engineering manufacturing for sustainability, pp 171–174 Springer Singapore
Tao F, Bi LN, Zuo Y, Nee AYC (2016) A hybrid group leader algorithm for green material selection with energy consideration in product design [J]. CIRP Annals-Manufacturing Technology 65(1):9–12
Abele E, Weigold M, Rothenbücher S (2007) Modeling and identification of an industrial robot for machining applications. CIRP Ann Manuf Technol 56(1):387–390
Appleton, E., and Williams, D. Industrial robot applications. Springer Science & Business Media, 2012
Chen YH, Dong FH (2013) Robot machining: recent development and future research issues. Int J Adv Manuf Technol 66(9–12):1489–1497
Bugmann G, Siegel M, Burcin R (2011) A role for robotics in sustainable development? IEEE (Institute of Electrical and Electronics Engineers) Africon:13–15
Brossog M, Bornschlegl M, Franke J (2015) Reducing the energy consumption of industrial robots in manufacturing systems[J]. Int J Adv Manuf Technol 78(5–8):1315–1328
Meeussen W, Hsu J, Diankov R L, URDF—Unified Robot Description Format (April 2012), http://www.ros.org/wiki/urdf. Accessed online 10/30/2016
**ao WL, Ji H, Dong SX (2014) A STEP-compliant industrial robot data model for robot off-line programming systems [J]. Robot Comput Integr Manuf 20(3):114–123
Kunze, L, Roehm T, and Beetz M. (2011) Towards semantic robot description languages. Robotics and Automation (ICRA), 2011 I.E. International Conference on. IEEE.
Prestes E, Carbonera JL, Fiorini SR, Jorge AM, V, Mara A, Madhavan R, Locoro A, Goncalves P, Barreto ME, Habib M, Chibani A, Gerard S, Amirat Y, Schlenoff C (2013) Towards a core ontology for robotics and automation[J]. Robot Auton Syst 61(11):1193–1204
Vergnano A, Lennartson B, Pellicciari M, Biller S (2012) Modeling and optimization of energy consumption in cooperative multi-robot systems [J]. IEEE Trans Autom Sci Eng 9(2):423–428
Matthias Brossog P, Kohl J, Merhof J, Spreng S, Franke J (2014) Energy consumption and dynamic behavior analysis of a six-axis industrial robot in an assembly system[C]. Procedia CIRP23:131–136
Wolter F, Zakharyaschev M (1998) Dynamic description logics [J]. Advances in Modal Logic 2:431–446
Chang L, Shi Z, Gu T, Zhao L (2012) A family of dynamic description logics for representing and reasoning about actions[J]. J Autom Reason 49(1):1–52
Mousavi S, Gagnol V, Bouzgarrou BC, Ray P (2016) Dynamic modeling and stability prediction in robotic machining[J]. Int J Adv Manuf Technol:1–13
Niu B, Zhang H. Model based control of industrial robot and implementation of its gain scheduling robust control[C]//Robotics and Biomimetics (ROBIO), 2011 I.E. International Conference on IEEE. 2011: 2156–2162.
Estévez E, Sánchez-García A, Gámez-García J, Gomez-Ortega J, Satorres-Martinez S (2016) A novel model-driven approach to support development cycle of robotic systems[J]. Int J Adv Manuf Technol 82(1–4):737–751
Steele JW, Wysk RA, Ferreira JCE (2008) A resource-oriented tolerance representation scheme for the planning of robotic machine tending operations in automated manufacturing systems [J]. Int J Adv Manuf Technol 38(7–8):741–756
Vichare P, Nassehi A, Kumar S, Newman S (2009) A unified manufacturing resource model for representing CNC machining systems[J]. Robot Comput Integr Manuf 25(6):999–1007
Niles I and Pease A. (2001) Towards a standard upper ontology[C]. Proceedings of the international conference on Formal Ontology in Information Systems-Volume 2001. ACM, : 2–9.
Fiorini SR, Carbonera JL, Gonçalves P, Jorge AM, V, Fortes Ray V, Haidegger T, Abel M, Redfield SA, Balakirsky S, Ragavan V, Li H, Schlenoff C, Prestes E (2015) Extensions to the core ontology for robotics and automation[J]. Robot Comput Integr Manuf 33:3–11
Rao RV, Patel BK, Parnichkun M (2011) Industrial robot selection using a novel decision making method considering objective and subjective preferences[J]. Robot Auton Syst 59(6):367–375
Kootbally Z, Kootbally Z (2016) Industrial robot capability models for agile manufacturing[J]. Ind Robot: An Int J 43(5):481–494
Kahraman C, Çevik S, Ates NY, Gülbay M (2007) Fuzzy multi-criteria evaluation of industrial robotic systems. Comput Ind Eng 52(4):414–433
Chemnitz, M., Schreck, G., and Krüger, J. Analyzing energy consumption of industrial robots. 16th IEEE Conference in Emerging Technologies & Factory Automation (ETFA), Toulouse, 2011, September 1–4.
Ystgaard P, Gjerstad T B, Lien T K and Nyen P A (2012) Map** energy consumption for industrial robots.19th CIRP International Conference on Life Cycle Engineering, Berkeley : 251–256.
Matthias Brossog P, Bornschlegl M, Franke J (2015) Reducing the energy consumption of industrial robots in manufacturing systems[J]. Int J Adv Manuf Technol 78(5–8):1315–1328
Rassolkin A, Hoimoja H, Teemets R (2011) Energy saving possibilities in the industrial robot IRB 1600 control. Compat Power Electron IEEE:226–229
Meike D, Pellicciari M, Berselli G (2014) Energy efficient use of multirobot production lines in the automotive industry: detailed system modeling and optimization. IEEE Trans Autom Sci Eng 11(3):798–809
Pellicciari M, Berselli G, Leali F, Vergnano A (2013) A method for reducing the energy consumption of pick-and-place industrial robots[J]. Mechatronics 23(3):326–334
Standard I S O. 8373: 1994[J]. Manipulating industrial robots–Vocabulary,1994.
Garetti M, Taisch M (2012) Sustainable manufacturing: trends and research challenges[J]. Prod Plan Control 23(2–3):83–104
Joung CB, Carrell J, Sarkar P, Feng SC (2013) Categorization of indicators for sustainable manufacturing[J]. Ecol Indic 24:148–157
Xu W J, Yu J J, Zhou Z D, **e Y Q, Pham D T, and Ji C (2015) Dynamic modelling of manufacturing equipment capability using condition information in cloud manufacturing" Journal of Manufacturing Science and Engineering,137:(4).
Li-min CLC (2011) Action theory based on the dynamic description logic DDL[J]. Comput Sci 7:045
Grosof B N, Horrocks I, Volz R and Decker S (2003) Description logic programs: combining logic programs with description logic[C]. Proceedings of the 12th international conference on World Wide Web. ACM,: 48–57.
Chang L, Shi ZZ, Qiu LR, Lin F (2008) A tableau decision algorithm for dynamic description logic[J]. Chin J Comput 31(6):896–909
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Zhao, Y., Liu, Q., Xu, W. et al. Dynamic and unified modelling of sustainable manufacturing capability for industrial robots in cloud manufacturing. Int J Adv Manuf Technol 93, 2753–2771 (2017). https://doi.org/10.1007/s00170-017-0634-1
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DOI: https://doi.org/10.1007/s00170-017-0634-1