Abstract
With the emergence of new materials, personalized requirements for product performance, and new application background in polymer material industry, a new manufacturing mode is supposed to be studied. Based on cloud computing (CC) and big data techniques, a specific cloud manufacturing (CMfg) mode of polymer material industry has been proposed, which is different from that of continuous industries and that of discrete industries. The critical technologies of CMfg, including forecasting and demand management, storage and transportation management, advanced process control, manufacturing execution system, enterprise resource planning, etc., have been discussed. Besides the service composition optimal-selection (SCOS) algorithm for flexible manufacturing and the flexible polymer manufacturing system (FPMS), a typical product mode of CMfg is studied. Finally as a case, computer-aided process planning for blending material (CAPP-BM) was explored and a kind of fast searching algorithm for blending material crafts was proposed. The algorithm was applied to search target craft in more than 60,000 sections of the standard processes, production data, and environmental data, and finished its search within 10 min.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ji X, Li ZM, Zhu LJ (2004) Application of data mining in the producing techniques of blending materials. Polym Mater Sci Eng 20(03):29–32
Tao F, Zhang L, Liu Y, Cheng Y, Wang L, Xu X (2015) Manufacturing service management in cloud manufacturing: overview and future research directions. J Manuf Sci Eng. doi:10.1115/1.4030510
Lartigau J, Xu X, Nie L, Zhan D (2015) Cloud manufacturing service composition based on QoS with geo-perspective transportation using an improved artificial bee colony optimisation algorithm. Int J Prod Res 53(14):4380–4404. doi:10.1080/00207543.2015.1005765
Li C, Wang S, Kang L, Guo L, Cao Y (2014) Trust evaluation model of cloud manufacturing service platform. Int J Adv Manuf Technol 75(1–4):489–501. doi:10.1007/s00170-014-6112-0
Song T, Liu H, Wei C, Zhang C (2014) Common engines of cloud manufacturing service platform for SMEs. Int J Adv Manuf Technol 73(1–4):557–569. doi:10.1007/s00170-014-5863-y
Li BH, Zhang L, Ren L, Chai XD, Tao F, Wang YZ, Yin C, Huang P, Zhao XP, Zhou ZD (2012) Typical characteristics, technologies and applications of cloud manufacturing. Comput Integr Manuf Syst 18(07):1345–1356. doi:10.13196/j.cims.2012.07.4.libh.006
Tao F, Cheng Y, Xu LD, Zhang L, Li BH (2014) CCIoT-CMfg: cloud computing and internet of things-based cloud manufacturing service system. IEEE Trans Indl Inf 10(2):1435–1442. doi:10.1109/TII.2014.2306383
Tao F, LaiLi Y, Xu L, Zhang L (2013) FC-PACO-RM: a parallel method for service composition optimal-selection in cloud manufacturing system. IEEE Trans Ind Inf 9(4):2023–2033. doi:10.1109/TII.2012.2232936
Tao F, Zuo Y, Xu LD, Zhang L (2014) IoT-based intelligent perception and access of manufacturing resource toward cloud manufacturing. IEEE Trans Ind Inf 10(2):1547–1557. doi:10.1109/TII.2014.2306397
Seki H, Ogawa M, Itoh T, Ootakara S, Murata H, Hashimoto Y, Kano M (2010) Plantwide control system design of the benchmark vinyl acetate monomer production plant. Comput Chem Eng 34(8):1282–1295. doi:10.1016/j.compchemeng.2009.11.022
Li J, Tao F, Cheng Y, Zhao L (2015) Big data in product lifecycle management. Int J Adv Manuf Technol. doi:10.1007/s00170-015-7151-x
Pinto-Varela T, Barbosa-Póvoa APFD, Novais AQ (2011) Bi-objective optimization approach to the design and planning of supply chains: economic versus environmental performances. Comput Chem Eng 35(8):1454–1468. doi:10.1016/j.compchemeng.2011.03.009
Gu J, Goetschalckx M, McGinnis LF (2010) Research on warehouse design and performance evaluation: a comprehensive review. Eur J Oper Res 203(3):539–549. doi:10.1016/j.ejor.2009.07.031
Baker P, Canessa M (2009) Warehouse design: a structured approach. Eur J Oper Res 193(2):425–436. doi:10.1016/j.ejor.2007.11.045
Ji X, Zhu L, Zhao FTJ (2006) Research on knowledge modeling system oriented to knowledge management for process enterprises. Comput Integr Manuf Syst 12(03):382–388. doi:10.13196/j.cims.2006.03.64.jix.011
Floudas CA, Lin X (2004) Continuous-time versus discrete-time approaches for scheduling of chemical processes: a review. Comput Chem Eng 28(11):2109–2129. doi:10.1016/j.compchemeng.2004.05.002
Chan CW (1995) The development and application of a knowledge modeling technique. J Exp Theor Artif Intell 7(2):217–236. doi:10.1080/09528139508953807
Li BM, Xie SQ, Xu X (2011) Recent development of knowledge-based systems, methods and tools for One-of-a-Kind Production. Knowl-Based Syst 24(7):1108–1119. doi:10.1016/j.knosys.2011.05.005
Yang HB, Yan HS (2008) An adaptive approach to dynamic scheduling in knowledgeable manufacturing cell. Int J Adv Manuf Technol 42(3–4):312–320. doi:10.1007/s00170-008-1588-0
Yu J-B, Yu Y, Wang L-N, Yuan Z, Ji X (2014) The knowledge modeling system of ready-mixed concrete enterprise and artificial intelligence with ANN-GA for manufacturing production. J Intell Manuf. doi:10.1007/s10845-014-0923-6
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Qiu, X., He, G. & Ji, X. Cloud manufacturing model in polymer material industry. Int J Adv Manuf Technol 84, 239–248 (2016). https://doi.org/10.1007/s00170-015-7580-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-015-7580-6