Accelerated ramp-up of assembly systems through self-learning

IFIP Advances in Information and Communication Technology

Volumn 371 AICT, Issue , 2012, Pages 175-182

  Oates, Robert ^a   Scrimieri, Daniele ^a   Ratchev, Svetan ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

Assembly Systems; Ramp up; Self Learning

Indexed keywords

ASSEMBLY SYSTEMS; RAMP-UP; SELF-LEARNING; SYNTHETIC DATA;

ASSEMBLY;

RIVETING;

EID: 84861002221     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-28163-1_21     Document Type: Conference Paper

References (18)

1. Fjällström, S., Säfsten, K., Harlin, U., Stahre, J.: Information enabling production ramp-up. Journal of Manufacturing Technology Management 20(2), 178-196 (2009)
2. Ceglarek, D., Huang, W., Zhou, S., Ding, Y., Kumar, R., Zhou, Y.: Time-based competition in multistage manufacturing: Stream-of-variation analysis (SOVA) methodology-Review. Journal of Flexible Manufacturing Systems 16(1), 11-44 (2004)
3. Haller, M., Peikert, A., Thoma, J.: Cycle time management during production ramp-up. Robotics and Computer-Integrated Manufacturing 19(1-2), 183-188 (2003)
4. Terwiesch, C., Bohn, R.E.: Learning and process improvement during production ramp-up. International Journal of Production Economics 70, 1-19 (2001)
5. Carrillo, J.E., Franza, R.M.: Investing in product development and production capabilities: The crucial linkage between time-to-market and ramp-up time. European Journal of Operational Research 171, 536-556 (2006)
6. Haller, M., Peikert, A., Thoma, J.: Cycle time management during production ramp-up. Robotics and Computer-Integrated Manufacturing 19, 183-188 (2003)
7. de Ron, A.J.: Measure of manufacturing performance in advanced manufacturing systems. International Journal of Production Economics 41, 147-160 (1995)
8. Hon, K.K.B.: Performance and evaluation of manufacturing systems. CIRP Annals - Manufacturing Technology 54, 675-690 (2005)
9. Kaplan, R.S., Norton, D.P.: The balanced scorecard-measures that drive performance. Harvard Business Review 70, 71-79 (1992)
10. Neely, A., Gregory, M., Platts, K.: Performance measurement system design: A literature review and research agenda. International Journal of Operations and Production Management 15, 80-116 (1995)
11. Doltsinis, S., Ratchev, S., Lohse,N.: A Framework for Performance Measurement during Production Ramp-up of Assembly Stations. Submitted to the European Journal of Operational Research
12. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
13. Voulgaris, Z., Magoulas, G.D.: Extensions of the k Nearest Neighbour Methods for Classification Problems. In: Proc. of 26th IASTED International Conference on Artificial Intelligence and Applications, ACTA, pp. 23-28 (2008)
14. Belongie, S., Malik, J., Puzicha, J.: Shape Matching and Object Recognition Using Shape Contexts. IEEE Transactions on Pattern Analysis and Machine Intelligence 24, 509-522 (2001)
15. Kim, S.: Protein β-turn Prediction Using Nearest Neighbour Method. Bioinformatics 20(1), 40-44 (2003)
16. Basri, R., Hassner, T., Zelnik-Manor, L.: Approximate Nearest Subspace Search. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(2), 266-278 (2011)
17. Vapnik, V., Vashist, A.: A new learning paradigm: learning using privileged information. Neural Netw. 22(5-6), 544-557 (2009)
18. Doltsinis, S.C., Lohse, N.: A Model-Free Reinforcement Learning Approach Using Monte Carlo Method in Production Ramp-Up Policy Improvement. Submitted to the 14th IFAC Symposium on Information Control Problems in Manufacturing (2012)