Industry 4.0: Smart Scheduling

References

• Ahn, G., Y. J. Park, and S. Hur. 2018. “Performance Computation Methods for Composition of Tasks with Multiple Patterns in Cloud Manufacturing.” International Journal of Production Research 16: 1–14. doi: 10.1080/00207543.2018.1451664
   Web of Science ®Google Scholar
• Ahuja, R. K., and J. B. Orlin. 2001. “Inverse Optimization.” Operations Research 49 (5): 771–783. doi: 10.1287/opre.49.5.771.10607
   Web of Science ®Google Scholar
• Al-Hinai, N., and T. Y. ElMekkawy. 2011. “Robust and Stable Flexible Job Shop Scheduling with Random Machine Breakdowns Using a Hybrid Genetic Algorithm.” International Journal of Production Economics 132 (2): 279–291. doi: 10.1016/j.ijpe.2011.04.020
   Web of Science ®Google Scholar
• Bożek, A., and M. Wysocki. 2015. “Flexible Job Shop with Continuous Material Flow.” International Journal of Production Research 53 (4): 1273–1290. doi: 10.1080/00207543.2014.955925
   Web of Science ®Google Scholar
• Brucker, P., and N. V. Shakhlevich. 2009. “Inverse Scheduling with Maximum Lateness Objective.” Journal of Scheduling 12 (5): 475–488. doi: 10.1007/s10951-009-0117-9
   Web of Science ®Google Scholar
• Brucker, P., and N. V. Shakhlevich. 2011. “Inverse Scheduling: Two-Machine Flow-Shop Problem.” Journal of Scheduling 14 (3): 239–256. doi: 10.1007/s10951-010-0168-y
   Web of Science ®Google Scholar
• Dolgui, A., D. Ivanov, S. P. Sethi, and B. Sokolov. 2018. “Scheduling in Production, Supply Chain and Industry 4.0 Systems by Optimal Control: Fundamentals, State-of-the-art and Applications.” International Journal of Production Research. doi:10.1080/00207543.2018.1442948.
   PubMed Web of Science ®Google Scholar
• Framinan, J. M., R. Leisten, and R. R. García. 2014. Manufacturing Scheduling Systems. London: Springer.
   Google Scholar
• Framinan, J. M., and R. Ruiz. 2010. “Architecture of Manufacturing Scheduling Systems: Literature Review and an Integrated Proposal.” European Journal of Operational Research 205 (2): 237–246. doi: 10.1016/j.ejor.2009.09.026
   Web of Science ®Google Scholar
• Gao, R., L. Wang, R. Teti, D. Dornfeld, S. Kumara, M. Mori, and M. Helu. 2015. “Cloud-Enabled Prognosis for Manufacturing.” CIRP Annals 64 (2): 749–772. doi: 10.1016/j.cirp.2015.05.011
   Web of Science ®Google Scholar
• Garey, M. R., D. S. Johnson, and R. Sethi. 1976. “The Complexity of Flowshop and Jobshop Scheduling.” Mathematics of Operations Research 1 (2): 117–129. doi: 10.1287/moor.1.2.117
   Google Scholar
• Hermann, M., T. Pentek, and B. Otto. 2016, January. “Design Principles for Industrie 4.0 Scenarios.” In 2016 49th Hawaii International Conference on System Sciences (HICSS), 3928–3937. IEEE.
   Google Scholar
• Heuberger, C. 2004. “Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results.” Journal of Combinatorial Optimization 8 (3): 329–361. doi: 10.1023/B:JOCO.0000038914.26975.9b
   Web of Science ®Google Scholar
• Katragjini, K., E. Vallada, and R. Ruiz. 2013. “Flow Shop Rescheduling Under Different Types of Disruption.” International Journal of Production Research 51 (3): 780–797. doi: 10.1080/00207543.2012.666856
   Web of Science ®Google Scholar
• Koulamas, C. 2005. “Inverse Scheduling with Controllable job Parameters.” International Journal of Services and Operations Management 1 (1): 35–43. doi: 10.1504/IJSOM.2005.006316
   Google Scholar
• Lee, E. A. 2008, May. Cyber Physical Systems: Design Challenges. In 2008 11th IEEE International Symposium on Object Oriented Real-Time Distributed Computing (ISORC), 363–369. IEEE.
   Google Scholar
• Lee, J., B. Bagheri, and H. A. Kao. 2015. “A Cyber-Physical Systems Architecture for Industry 4.0-Based Manufacturing Systems.” Manufacturing Letters 3: 18–23. doi: 10.1016/j.mfglet.2014.12.001
   Google Scholar
• Li, J. Q., Q. K. Pan, and K. Mao. 2015. “A Discrete Teaching-Learning-Based Optimisation Algorithm for Realistic Flowshop Rescheduling Problems.” Engineering Applications of Artificial Intelligence 37: 279–292. doi: 10.1016/j.engappai.2014.09.015
   Web of Science ®Google Scholar
• Liu, Y., L. Wang, X. V. Wang, X. Xu, and L. Zhang. 2018. “Scheduling in Cloud Manufacturing: State-of-the-Art and Research Challenges.” International Journal of Production Research, 1–26.
   Web of Science ®Google Scholar
• McKay, K. N., and J. A. Buzacott. 2000. “The Application of Computerized Production Control Systems in job Shop Environments.” Computers in Industry 42 (2-3): 79–97. doi: 10.1016/S0166-3615(99)00063-9
   Web of Science ®Google Scholar
• Monostori, L. 2014. “Cyber-Physical Production Systems: Roots, Expectations and R&D Challenges.” Procedia CIRP 17: 9–13. doi: 10.1016/j.procir.2014.03.115
   Google Scholar
• Ouelhadj, D., and S. Petrovic. 2009. “A Survey of Dynamic Scheduling in Manufacturing Systems.” Journal of Scheduling 12 (4): 417–431. doi: 10.1007/s10951-008-0090-8
   Web of Science ®Google Scholar
• Pinedo, M. 2012. Scheduling. New York: Springer.
   Google Scholar
• Rossit, D., and F. Tohmé. 2018. “Scheduling Research Contributions to Smart Manufacturing.” Manufacturing Letters 15 (B): 111–114. doi: 10.1016/j.mfglet.2017.12.005
   Google Scholar
• Rossit, D. A., F. Tohmé, and M. Frutos. 2018. “The non-Permutation Flow-Shop Scheduling Problem: a Literature Review.” Omega 77: 143–153. doi: 10.1016/j.omega.2017.05.010
   Web of Science ®Google Scholar
• Rossit, D., F. Tohmé, M. Frutos, J. Bard, and D. Broz. 2016. “A non-Permutation Flowshop Scheduling Problem with Lot Streaming: A Mathematical Model.” International Journal of Industrial Engineering Computations 7 (3): 507–516. doi: 10.5267/j.ijiec.2015.11.004
   Google Scholar
• Tao, F., Y. Cheng, L. Zhang, and A. Y. Nee. 2017. “Advanced Manufacturing Systems: Socialization Characteristics and Trends.” Journal of Intelligent Manufacturing 28 (5): 1079–1094. doi: 10.1007/s10845-015-1042-8
   Web of Science ®Google Scholar
• Vieira, G. E., J. W. Herrmann, and E. Lin. 2003. “Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods.” Journal of Scheduling 6 (1): 39–62. doi: 10.1023/A:1022235519958
   Web of Science ®Google Scholar
• Wang, P., R. X. Gao, and Z. Fan. 2015. “Cloud Computing for Cloud Manufacturing: Benefits and Limitations.” Journal of Manufacturing Science and Engineering 137 (4): 040901.
   Web of Science ®Google Scholar
• Wang, X., S. K. Ong, and A. Y. C. Nee. 2017. “A Comprehensive Survey of Ubiquitous Manufacturing Research.” International Journal of Production Research 1: 1–25. doi: 10.1080/00207543.2017.1401239
   Web of Science ®Google Scholar
• Wang, L., M. Törngren, and M. Onori. 2015. “Current Status and Advancement of Cyber-Physical Systems in Manufacturing.” Journal of Manufacturing Systems 37 (Part 2): 517–527. doi: 10.1016/j.jmsy.2015.04.008
   Web of Science ®Google Scholar
• Wang, X. V., and L. Wang. 2014. “From Cloud Manufacturing to Cloud Remanufacturing: A Cloud-Based Approach for WEEE Recovery.” Manufacturing Letters 2 (4): 91–95. doi: 10.1016/j.mfglet.2014.06.002
   Google Scholar
• Wang, L., and X. V. Wang. 2018a. “Latest Advancement in Cloud Technologies.” In Cloud-Based Cyber-Physical Systems in Manufacturing, 3–31. Cham: Springer.
   Google Scholar
• Wang, L., and X. V. Wang. 2018b. “Latest Advancement in CPS and IoT Applications.” In Cloud-Based Cyber-Physical Systems in Manufacturing, 33–61. Cham: Springer.
   Google Scholar
• Wang, L., and X. V. Wang. 2018c. “Cloud-Enabled Distributed Process Planning.” In Cloud-Based Cyber-Physical Systems in Manufacturing, 105–123. Cham: Springer.
   Google Scholar
• Wang, L., X. V. Wang, L. Gao, and J. Váncza. 2014. “A Cloud-Based Approach for WEEE Remanufacturing.” CIRP Annals 63 (1): 409–412. doi: 10.1016/j.cirp.2014.03.114
   Web of Science ®Google Scholar
• Xu, X. 2012. “From Cloud Computing to Cloud Manufacturing.” Robotics and Computer-Integrated Manufacturing 28 (1): 75–86. doi: 10.1016/j.rcim.2011.07.002
   Web of Science ®Google Scholar
• Xu, X. 2017. “Machine Tool 4.0 for the new era of Manufacturing.” The International Journal of Advanced Manufacturing Technology 92 (5-8): 1893–1900. doi:10.1007/s00170-017-0300-7.
   Web of Science ®Google Scholar