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Smart manufacturing: Past research, present findings, and future directions

Kang, Hyoung Seok, Lee, Ju Yeon, Choi, SangSu, Kim, Hyun, Park, Jun Hee, Son, Ji Yeon, Kim, Bo Hyun, Noh, Sang Do·2016·International Journal of Precision Engineering and Manufacturing-Green Technology

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  1. Kagermann, H., Helbig, J., Hellinger, A., and Wahlster, W., “Recommendations for Implementing the Strategic Initiative Industrie 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group,” Forschungsunion, 2013.
  2. Smart Manufacturing Leadership Coalition, “Implementing 21st century smart manufacturing,” https://smartmanufacturingcoalition. org/sites/default/files/implementing_21st_century_smart_manufact uring_report_2011_0pdf (Accessed 20 December 2015)
  3. Smart Process Manufacturing Engineering Virtual Organization Steering Committee, “Smart Process Manufacturing: An Operations and Technology Roadmap,” https://smartmanufacturingcoalitionorg/ sites/default/files/spm_-_an_operations_and_technology_roadmappdf (Accessed 20 December 2015)
  4. Korea Institute for the Advancement of Technology, “Research Trend of Smart Manufacturing in the U.S.,” June, 2014.
  5. Roland Berger Strategy Consultants GMBH, “Industry 4.0: The New Industrial Revolution-How Europe will Succeed,” http:// wwwrolandbergercom/media/pdf/Roland_Berger_TAB_Industry_4 _0_20140403pdf (Accessed 20 December 2015)
  6. Wang, S., Wan, J., Li, D., and Zhang, C., “Implementing Smart Factory of Industrie 4.0: An Outlook,” International Journal of Distributed Sensor Networks, Article ID: 681806, 2015.
  7. Anderl, I. R., “Industrie 4.0-Advanced Engineering of Smart Products and Smart Production,” Proc. of 19th International Seminar on High Technology, 2014.
  8. Brettel, M., Friederichsen, N., Keller, M., and Rosenberg, M., “How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective,” International Journal of Science, Engineering and Technology, Vol. 8, No. 1, pp. 37–44, 2014.
  9. Choi, S., Jun, C., Zhao, W. B., and Noh, S. D., “Digital Manufacturing in Smart Manufacturing Systems: Contribution, Barriers, and Future Directions,” Advances in production Management Systems: Innovative Production Management towards Sustainable Growth, pp. 21–29, 2015. · DOI
  10. Radziwon, A., Bilberg, A., Bogers, M., and Madsen, E. S., “The Smart Factory: Exploring Adaptive and Flexible Manufacturing Solutions,” Procedia Engineering, Vol. 69, pp. 1184–1190, 2014. · DOI · Paper page
  11. Lucke, D., Constantinescu, C., and Westkämper, E., “Smart Factory: A Step towards the Next Generation of Manufacturing,” Manufacturing Systems and Technologies for the New Frontier, pp. 115–118, 2008. · DOI · Paper page
  12. Zuehlke, D., “Smartfactory-towards a Factory-of-Things,” Annual Reviews in Control, Vol. 34, No. 1, pp. 129–138, 2010. · DOI · Paper page
  13. Ivanov, D., Dolgui, A., Sokolov, B., Werner, F., and Ivanova, M., “A Dynamic Model and an Algorithm for Short-Term Supply Chain Scheduling in the Smart Factory Industry 4.0,” International Journal of Production Research, DOI No. 10.1080/00207543.2014.999958, 2015. · DOI · Paper page
  14. Choi, S., Kim, B. H., and Noh, S. D., “A Diagnosis and Evaluation Method for Strategic Planning and Systematic Design of a Virtual Factory in Smart Manufacturing Systems,” Int. J. Precis. Eng. Manuf., Vol. 16, No. 6, pp. 1107–1115, 2015. · DOI
  15. Hellinger, A. and Seeger, H., “Cyber-Physical Systems. Driving Force for Innovation in Mobility, Health, Energy and Production,” Acatech Position Paper, National Academy of Science and Engineering, 2011.
  16. Geisberger, E. and Broy, M., “Integrierte Forschungsagenda Cyber-Physical Systems,” Acatech Position Paper, National Academy of Science and Engineering, 2012.
  17. Sztipanovits, J., Ying, S., Cohen, I., Corman, D., Davis, J., et al., “Strategic R&D Opportunities for 21st Century Cyber-Physical Systems,” Technical Report for Steering Committee for Foundation in Innovation for Cyber-Physical Systems: Chicago, 2013.
  18. Lee, J., Bagheri, B., and Kao, H.-A., “A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems,” Manufacturing Letters, Vol. 3, pp. 18–23, 2015. · DOI · Paper page
  19. Dworschak, B. and Zaiser, H., “Competences for Cyber-Physical Systems in Manufacturing-First Findings and Scenarios,” Procedia CIRP, Vol. 25, pp. 345–350, 2014. · DOI
  20. Seiger, R., Keller, C., Niebling, F., and Schlegel, T., “Modelling Complex and Flexible Processes for Smart Cyber-Physical Environments,” Journal of Computational Science, Vol. 10, pp. 137–148, 2014. · DOI
  21. Monostori, L., “Cyber-Physical Production Systems: Roots, Expectations and R&D Challenges,” Procedia CIRP, Vol. 17, pp. 9–13, 2014. · DOI · Paper page
  22. Genge, B., Fovino, I. N., Siaterlis, C., and Masera, M., “Analyzing Cyber-Physical Attacks on Networked Industrial Control Systems,” Critical Infrastructure Protection V, pp. 167–183, 2011. · DOI
  23. Wang, Y., Vuran, M. C., and Goddard, S., “Cyber-Physical Systems in Industrial Process Control,” ACM Sigbed Review, Vol. 5, No. 1, Article No. 12, 2008.
  24. Niggemann, O., Biswas, G., Kinnebrew, J. S., Khorasgani, H., Volgmann, S., et al., “Data-Driven Monitoring of Cyber-Physical Systems Leveraging on Big Data and the Internet-of-Things for Diagnosis and Control,” http://ceur-wsorg/Vol-1507/dx15paper24pdf (Accessed 30 December 2015)
  25. Lee, J., Bagheri, B., and Kao, H.-A., “Recent Advances and Trends of Cyber-Physical Systems and Big Data Analytics in Industrial Informatics,” Proc. of International Conference on Industrial Informatics, 2014.
  26. Wan, J., Chen, M., Xia, F., Di, L., and Zhou, K., “From Machine-to-Machine Communications towards Cyber-Physical Systems,” Computer Science and Information Systems, Vol. 10, No. 3, pp. 1105–1128, 2013. · DOI
  27. Lu, T., Zhao, J., Zhao, L., Li, Y., and Zhang, X., “Towards a Framework for Assuring Cyber Physical System Security,” International Journal of Security&Its Applications, Vol. 9, No. 3, pp. 25–40, 2015. · doi:10.14257/ijsia.2015.9.3.04
  28. Colombo, A. W., Karnouskos, S., and Bangemann, T., “Towards the Next Generation of Industrial Cyber-Physical Systems,” Industrial Cloud-Based Cyber-Physical Systems, pp. 1–22, 2014. · DOI
  29. Colombo, A. W., Bangemann, T., Karnouskos, S., Delsing, J., Stluka, P., et al., “Industrial Cloud-Based Cyber-Physical Systems,” The IMC-AESOP Approach, 2014.
  30. Wu, D., Greer, M. J., Rosen, D. W., and Schaefer, D., “Cloud Manufacturing: Drivers, Current Status, and Future Trends,” Proc. of ASME 2013 International Manufacturing Science and Engineering Conference Collocated with the 41st North American Manufacturing Research Conference, Paper No. V002T002A003, 2013.
  31. Wu, D., Greer, M. J., Rosen, D. W., and Schaefer, D., “Cloud Manufacturing: Strategic Vision and State-of-the-Art,” Journal of Manufacturing Systems, Vol. 32, No. 4, pp. 564–579, 2013. · DOI · Paper page
  32. Wu, D., Rosen, D. W., Wang, L., and Schaefer, D., “Cloud-Based Design and Manufacturing: A New Paradigm in Digital Manufacturing and Design Innovation,” Computer-Aided Design, Vol. 59, pp. 1–14, 2015. · DOI · Paper page
  33. Ren, L., Zhang, L., Wang, L., Tao, F., and Chai, X., “Cloud Manufacturing: Key Characteristics and Applications,” International Journal of Computer Integrated Manufacturing, DOI No. 10.1080/0951192X.2014.902105, 2014. · DOI · Paper page
  34. Ren, L., Zhang, L., Tao, F., Zhao, C., Chai, X., et al., “Cloud Manufacturing: From Concept to Practice,” Enterprise Information Systems, Vol. 9, No. 2, pp. 186–209, 2015. · DOI · Paper page
  35. Wu, D., Rosen, D. W., and Schaefer, D., “Cloud-Based Design and Manufacturing: Status and Promise,” Cloud-Based Design and Manufacturing (CBDM), pp. 1–24, 2014.
  36. Wu, D., Rosen, D. W., Wang, L., and Schaefer, D., “Cloud-Based Manufacturing: Old Wine in New Bottles?” Procedia CIRP, Vol. 17, pp. 94–99, 2014. · doi:10.1016/j.procir.2014.01.035
  37. Zhang, L., Luo, Y., Tao, F., Li, B. H., Ren, L., et al., “Cloud Manufacturing: A New Manufacturing Paradigm,” Enterprise Information Systems, Vol. 8, No. 2, pp. 167–187, 2014. · DOI · Paper page
  38. Tao, F., Cheng, Y., Da Xu, L., Zhang, L., and Li, B. H., “CCIoTCMfg: Cloud Computing and Internet of Things-Based Cloud Manufacturing Service System,” IEEE Transactions on Industrial Informatics, Vol. 10, No. 2, pp. 1435–1442, 2014. · DOI · Paper page
  39. Karnouskos, S., Colombo, A. W., Bangemann, T., Manninen, K., Camp, R., et al., “A SOA-Based Architecture for Empowering Future Collaborative Cloud-Based Industrial Automation,” Proc. of IECON 2012–38th Annual Conference on IEEE Industrial Electronics Society, pp. 5766–5772, 2012. · DOI
  40. He, W. and Xu, L., “A State-of-the-Art Survey of Cloud Manufacturing,” International Journal of Computer Integrated Manufacturing, Vol. 28, No. 3, pp. 239–250, 2015. · DOI
  41. Luo, Y., Zhang, L., Tao, F., Ren, L., Liu, Y., et al., “A Modeling and Description Method of Multidimensional Information for Manufacturing Capability in Cloud Manufacturing System,” The International Journal of Advanced Manufacturing Technology, Vol. 69, No. 5–8, pp. 961–975, 2013. · DOI
  42. Laili, Y., Tao, F., Zhang, L., and Sarker, B. R., “A Study of Optimal Allocation of Computing Resources in Cloud Manufacturing Systems,” The International Journal of Advanced Manufacturing Technology, Vol. 63, No. 5–8, pp. 671–690, 2012. · doi:10.1007/s00170-012-3939-0
  43. Wang, L., “Machine Availability Monitoring and Machining Process Planning towards Cloud Manufacturing,” CIRP Journal of Manufacturing Science and Technology, Vol. 6, No. 4, pp. 263–273, 2013. · DOI
  44. Wang, T., Guo, S., and Lee, C.-G., “Manufacturing Task Semantic Modeling and Description in Cloud Manufacturing System,” The International Journal of Advanced Manufacturing Technology, Vol. 71, No. 9–12, pp. 2017–2031, 2014. · doi:10.1007/s00170-014-5607-z
  45. Pisching, M. A., Junqueira, F., Santos Filho, D. J., and Miyagi, P. E., “Service Composition in the Cloud-Based Manufacturing Focused on the Industry 4.0,” Technological Innovation for Cloud-Based Engineering Systems, pp. 65–72, 2015. · DOI
  46. Lee, J., Kao, H.-A., and Yang, S., “Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment,” Procedia CIRP, Vol. 16, pp. 3–8, 2014. · DOI · Paper page
  47. Shahbaz, M., Masood, S. A., Shaheen, M., and Khan, A., “Data Mining Methodology in Perspective of Manufacturing Databases,” Life Science Journal, Vol. 9, No. 3, pp. 13–22, 2012.
  48. Shao, G., Brodsky, A., Shin, S.-J., and Kim, D. B., “Decision Guidance Methodology for Sustainable Manufacturing Using Process Analytics Formalism,” Journal of Intelligent Manufacturing, pp. 1–18, 2014.
  49. Ündey, C., Ertunç, S., Mistretta, T., and Looze, B., “Applied Advanced Process Analytics in Biopharmaceutical Manufacturing: Challenges and Prospects in Real-Time Monitoring and Control,” Journal of Process Control, Vol. 20, No. 9, pp. 1009–1018, 2010. · DOI
  50. Meidan, Y., Lerner, B., Rabinowitz, G., and Hassoun, M., “Cycle-Time Key Factor Identification and Prediction in Semiconductor Manufacturing Using Machine Learning and Data Mining,” IEEE Transactions on Semiconductor Manufacturing, Vol. 24, No. 2, pp. 237–248, 2011. · DOI
  51. Bagchi, S., Baseman, R. J., Davenport, A., Natarajan, R., Slonim, N., et al., “Data Analytics and Stochastic Modeling in a Semiconductor Fab,” Applied Stochastic Models in Business and Industry, Vol. 26, No. 1, pp. 1–27, 2010. · doi:10.1002/asmb.828
  52. Gröger, C., Niedermann, F., and Mitschang, B., “Data Mining-Driven Manufacturing Process Optimization,” Proc. of the World Congress on Engineering, Vol. 3, pp. 4–6, 2012.
  53. Çiflikli, C. and Kahya-Özyirmidokuz, E., “Implementing a Data Mining Solution for Enhancing Carpet Manufacturing Productivity,” Knowledge-Based Systems, Vol. 23, No. 8, pp. 783–788, 2010. · DOI
  54. Shin, S.-J., Woo, J., and Rachuri, S., “Predictive Analytics Model for Power Consumption in Manufacturing,” Procedia CIRP, Vol. 15, pp. 153–158, 2014. · DOI
  55. Zhong, R. Y., Lan, S., Xu, C., Dai, Q., and Huang, G. Q., “Visualization of RFID-Enabled Shopfloor Logistics Big Data in Cloud Manufacturing,” The International Journal of Advanced Manufacturing Technology, pp. 1–12, 2015.
  56. ITU, “Internet of Things Global Standards Initiative,” http:// wwwituint/en/ITU-T/gsi/iot/Pages/defaultaspx (Accessed 20 December 2015)
  57. Williams, J., “Harvard Business Review Internet of Things: Science Fiction or Business Fact (Report and Resources),” Verizon, 2014.
  58. Vermesan, O. and Friess, P., “Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems,” River Publishers, 2013.
  59. Lopez Research LLC, “An Introduction to the Internet of Things(IoT),” https://wwwciscocom/web/solutions/trends/iot/ introduction_to_IoT_novemberpdf (Accessed 20 December 2015)
  60. Gérald, S., “The Internet of Things: Between the Revolution of the Internet and the Metamorphosis of Objects,” http://cordiseuropaeu/ fp7/ict/enet/documents/publications/iot-between-the-internetrevolution. pdf (Accessed 20 December 2015)
  61. Mattern, F. and Floerkemeier, C., “From the Internet of Computers to the Internet of Things,” From Active Data Management to Event-Based Systems and More, pp. 242–259, 2010. · DOI · Paper page
  62. Cognizant, “Reaping the Benefits of the Internet of Things,” http:// wwwcognizantcom/InsightsWhitepapers/Reaping-the-Benefits-ofthe-Internet-of-Thingspdf (Accessed 20 December 2015)
  63. Löffler, M. and Tschiesner, A., “The Internet of Things and the Future of Manufacturing,” http://wwwfuturenauticscom/wpcontent/ uploads/2013/10/Internet-of-Things-and-future-ofmanufacturing. pdf (Accessed 20 December 2015)
  64. Bi, Z., Da Xu, L., and Wang, C., “Internet of Things for Enterprise Systems of Modern Manufacturing,” IEEE Transactions on Industrial Informatics, Vol. 10, No. 2, pp. 1537–1546, 2014. · DOI · Paper page
  65. Dias, R. A., Mendonça, I. T., and Regis, A., “Integrated Manufacturing Management Using Internet of Things,” International Journal of Computer Applications, Vol. 51, No. 11, pp. 20–25, 2012. · doi:10.5120/8086-1553
  66. Guinard, D., Trifa, V., Karnouskos, S., Spiess, P., and Savio, D., “Interacting with the Soa-Based Internet of Things: Discovery, Query, Selection, and On-Demand Provisioning of Web Services,” IEEE Transactions on Services Computing, Vol. 3, No. 3, pp. 223–235, 2010. · DOI · Paper page
  67. Tao, F., Zuo, Y., Da Xu, L., and Zhang, L., “IoT-Based Intelligent Perception and Access of Manufacturing Resource toward Cloud Manufacturing,” IEEE Transactions on Industrial Informatics, Vol. 10, No. 2, pp. 1547–1557, 2014. · DOI · Paper page
  68. Zhang, Y., Zhang, G., Wang, J., Sun, S., Si, S., et al., “Real-Time Information Capturing and Integration Framework of the Internet of Manufacturing Things,” International Journal of Computer Integrated Manufacturing, DOI No. 10.1080/0951192X.2014. 900874, 2014. · doi:10.1080/0951192x.2014
  69. Butala, P., Vrabiè, R., and Oosthuizen, G., “Distributed Manufacturing Systems and the Internet of Things: A Case Study,” https://ujdigispaceujacza/bitstream/handle/10210/13015/565–2012-1-PBpdf?sequence=1&isAllowed=y (Accessed 20 December 2015)
  70. Chris, T. and Steven, A., “Wireless Sensor Networks: Principles and Applications,” Retrieved, 2011.
  71. Zhuang, L., Goh, K. M., and Zhang, J.-B., “The Wireless Sensor Networks for Factory Automation: Issues and Challenges,” Proc. of IEEE Conference on Emerging Technologies and Factory Automation, pp. 141–148, 2007.
  72. Flammini, A., Ferrari, P., Marioli, D., Sisinni, E., and Taroni, A., “Wired and Wireless Sensor Networks for Industrial Applications,” Microelectronics Journal, Vol. 40, No. 9, pp. 1322–1336, 2009. · DOI
  73. Chi, Q., Yan, H., Zhang, C., Pang, Z., and Da Xu, L., “A Reconfigurable Smart Sensor Interface for Industrial WSN in IoT Environment,” IEEE Transactions on Industrial Informatics, Vol. 10, No. 2, pp. 1417–1425, 2014. · DOI · Paper page
  74. Zhang, Y., Qu, T., Ho, O. K., and Huang, G. Q., “Agent-Based Smart Gateway for RFID-Enabled Real-Time Wireless Manufacturing,” International Journal of Production Research, Vol. 49, No. 5, pp. 1337–1352, 2011. · DOI
  75. Zhang, Y., Huang, G. Q., Qu, T., Ho, O., and Sun, S., “Agent-Based Smart Objects Management System for Real-Time Ubiquitous Manufacturing,” Robotics and Computer-Integrated Manufacturing, Vol. 27, No. 3, pp. 538–549, 2011. · doi:10.1016/j.rcim.2010.09.009
  76. Lee, S. C., Jeon, T. G., Hwang, H.-S., and Kim, C.-S., “Design and Implementation of Wireless Sensor Based-Monitoring System for Smart Factory,” Computational Science and Its Applications-ICCSA 2007, pp. 584–592, 2007. · doi:10.1007/978-3-540-74477-1_54
  77. Wright, P., Dornfeld, D., and Ota, N., “Condition Monitoring in End-Milling Using Wireless Sensor Networks (WSNS),” Transactions of NAMRI/SME, Vol. 36, pp. 177–183, 2008.
  78. Kortuem, G., Alford, D., Ball, L., Busby, J., Davies, N., et al., “Sensor Networks or Smart Artifacts? An Exploration of Organizational Issues of an Industrial Health and Safety Monitoring System,” Springer, pp. 465–482, 2007.
  79. Pal, D., Patil, N., Nikoukar, M., Zeng, K., Kutty, K. H., et al., “An Integrated Approach to Cyber-Enabled Additive Manufacturing using Physics Based, Coupled Multi-Scale Process Modeling,” Proc. of SFF Symposium, pp. 12–14, 2013.
  80. Campbell, I., Bourell, D., and Gibson, I., “Additive Manufacturing: Rapid Prototyping Comes of Age,” Rapid Prototyping Journal, Vol. 18, No. 4, pp. 255–258, 2012. · DOI · Paper page
  81. Huang, Y. and Leu, M. C., “Frontiers of Additive Manufacturing Research and Education,” http://plazaufledu/yongh/2013NSFAM WorkshopReportpdf (Accessed 20 December 2015)
  82. Wong, K. V. and Hernandez, A., “A Review of Additive Manufacturing,” ISRN Mechanical Engineering, Vol. 2012, Article ID: 208760, 2012. · DOI · Paper page
  83. Huang, S. H., Liu, P., Mokasdar, A., and Hou, L., “Additive Manufacturing and Its Societal Impact: A Literature Review,” The International Journal of Advanced Manufacturing Technology, Vol. 67, No. 5–8, pp. 1191–1203, 2013. · DOI · Paper page
  84. Berman, B., “3-D Printing: The New Industrial Revolution,” Business Horizons, Vol. 55, No. 2, pp. 155–162, 2012. · DOI · Paper page
  85. Espalin, D., Muse, D. W., MacDonald, E., and Wicker, R. B., “3D Printing Multifunctionality: Structures with Electronics,” The International Journal of Advanced Manufacturing Technology, Vol. 72, No. 5–8, pp. 963–978, 2014. · DOI · Paper page
  86. Kerbrat, O., Mognol, P., and Hascoët, J.-Y., “A New DFM Approach to Combine Machining and Additive Manufacturing,” Computers in Industry, Vol. 62, No. 7, pp. 684–692, 2011. · doi:10.1016/j.compind.2011.04.003
  87. Witherell, P., Feng, S., Simpson, T. W., Saint John, D. B., Michaleris, P., et al., “Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models,” Journal of Manufacturing Science and Engineering, Vol. 136, Paper No. MANU-14–1275, 2014. · doi:10.1115/1.4028533
  88. Lu, Y., Choi, S., and Witherell, P., “Towards an Integrated Data Schema Design for Additive Manufacturing: Conceptual Modeling,” Proc. of the ASME International Design Engineering Technical Conferences&Computers and Information in Engineering Conference, 2015.
  89. Seow, Y. and Rahimifard, S., “A Framework for Modelling Energy Consumption within Manufacturing Systems,” CIRP Journal of Manufacturing Science and Technology, Vol. 4, No. 3, pp. 258–264, 2011. · DOI
  90. Vijayaraghavan, A. and Dornfeld, D., “Automated Energy Monitoring of Machine Tools,” CIRP Annals-Manufacturing Technology, Vol. 59, No. 1, pp. 21–24, 2010. · doi:10.1016/j.cirp.2010.03.042
  91. Duflou, J. R., Sutherland, J. W., Dornfeld, D., Herrmann, C., Jeswiet, J., et al., “Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach,” CIRP Annals-Manufacturing Technology, Vol. 61, No. 2, pp. 587–609, 2012. · DOI · Paper page
  92. Herrmann, C., Thiede, S., Kara, S., and Hesselbach, J., “Energy Oriented Simulation of Manufacturing Systems-Concept and Application,” CIRP Annals-Manufacturing Technology, Vol. 60, No. 1, pp. 45–48, 2011. · DOI · Paper page
  93. Rahimifard, S., Seow, Y., and Childs, T., “Minimising Embodied Product Energy to Support Energy Efficient Manufacturing,” CIRP Annals-Manufacturing Technology, Vol. 59, No. 1, pp. 25–28, 2010. · doi:10.1016/j.cirp.2010.03.048
  94. Herrmann, C. and Thiede, S., “Process Chain Simulation to Foster Energy Efficiency in Manufacturing,” CIRP Journal of Manufacturing Science and Technology, Vol. 1, No. 4, pp. 221–229, 2009. · DOI · Paper page
  95. Weinert, N., Chiotellis, S., and Seliger, G., “Methodology for Planning and Operating Energy-Efficient Production Systems,” CIRP Annals-Manufacturing Technology, Vol. 60, No. 1, pp. 41–44, 2011. · DOI · Paper page
  96. Mouzon, G., Yildirim, M. B., and Twomey, J., “Operational Methods for Minimization of Energy Consumption of Manufacturing Equipment,” International Journal of Production Research, Vol. 45, No. 18–19, pp. 4247–4271, 2007. · DOI · Paper page
  97. Katsutomo, T., Hiroshi, W., and Akira, E., “Enerize E3 Factory Energy Management System,” Yokogawa Technical Report English Edition, Vol. 53, No. 1, pp. 23–26, 2010.
  98. Endo, M., Nakajima, H., and Hata, Y., “Simplified Factory Energy Management System Based on Operational Condition Estimation by Sensor Data,” Proc. of IEEE International Conference on Automation Science and Engineering (CASE), pp. 14–19, 2012.
  99. Hetzler, J., Beder, S., and Feldmann, H., “Hologram and Method of Manufacturing an Optical Element Using a Hologram,” US Patent, No. 7848031 B2, 2010.
  100. Schillke, F., Beder, S., and Hetzler, J., “Method of Manufacturing an Optical Element using a Hologram,” US Patent, No. 7061626 B1, 2006.
  101. Nee, A. Y. C., Ong, S. K., Chryssolouris, G., and Mourtzis, D., “Augmented Reality Applications in Design and Manufacturing,” CIRP Annals-Manufacturing Technology, Vol. 61, No. 2, pp. 657–679, 2012. · DOI · Paper page
  102. Smart Manufacturing Leadership Coalition, “SMLC Forum: Priorities, Infrastructure, and Collaboration for Implementation of Smart Manufacturing,” https://smartmanufacturingcoalitionorg/sites/ default/files/smlc_forum_report_vf_0pdf (Accessed 20 December 2015)

Cited by

Metadata

Authors
Kang, H. S., Lee, J. Y., Choi, S., Kim, H., Park, J. H., Son, J. Y., Kim, B. H., & Noh, S. D.
Venue
International Journal of Precision Engineering and Manufacturing-Green Technology
Published
2016-01
Volume
3
Issue
1
Pages
111-128
ISSN
  • 2198-0810 (ISSN-L)
  • 2288-6206
OpenAlex
W2254884657
Cited by
1,362
References
2
FWCI
155.97
Type
journal article
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)

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