Modelling production ramp-up of engineering products

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Volumn 225, Issue 6, 2011, Pages 959-971

  Ball, P D ^a   Roberts, S ^a   Natalicchio, A ^a   Scorzafave, C ^a  

^a CRANFIELD UNIVERSITY   (United Kingdom)

Author keywords

Engineering products; Learning curves; New product introduction; Production ramp up modelling

Indexed keywords

ENGINEERED PRODUCTS; LEARNING CURVES; MODELLING TOOLS; NEW PRODUCT; NEW PRODUCT INTRODUCTIONS; PLANNING AND EXECUTION; SPECIFIC COMPONENT;

EID: 80051899612     PISSN: 09544054     EISSN: 20412975     Source Type: Journal    
DOI: 10.1177/09544054JEM2071     Document Type: Review

References (54)

1. Haller, M., Peikert, A., and Thoma, J. Cycle time management during production ramp-up. Robot. CIM-Int. Manuf., 2003, 19(1-2), 183-188.
2. Terwiesch, C., Bohn, R. E., and Chea, K. S. International product transfer and production ramp-up: a case study from the data storage industry. R&D Management, 2001, 31(4), 435-451. (Pubitemid 33706935)
3. Casamento, J. W. A model for predicting and managing a production ramp-up of a new product. MSc Thesis in Management and Mechanical Engineering, Massachusetts Institute of Technology, 1992.
4. Terwiesch, C. and Bohn, R. E. Learning and process improvement during production ramp-up. Int. J. Prod. Econ., 2001, 70(1), 1-19. (Pubitemid 32160564)
5. Almgren, H. Pilot production and manufacturing start-up: the case of Volvo S80. Int. J. Prod. Res., 2000, 38(17), 4577-4588. (Pubitemid 35401926)
6. Clawson, R. T. Controlling the manufacturing startup. Harvard Bus. Rev., 1985, 63(3), 6-20.
7. Abernathy, W. J. and Baloff, N. A methodology for planning new product start-ups. Decision Sci., 1973, 4(1), 1-20.
8. Lenfle, S. and Midler, C. The launch of innovative product-related services: lessons from automotive telematics. Res. Policy, 2009, 38(1), 156-169.
9. Du, S., Xi, L., Ni, J., Ershun, P., and Liu, C. R. Product lifecycle-oriented quality and productivity improvement based on stream of variation methodology. Comput. Ind., 2008, 59(2-3), 180-192.
10. Sturm, R., Dorner, J., Reddig, K., and Seidelmann, J. Simulation-based evaluation of the ramp-up behavior of waferfabs. In Advanced Semiconductor Manufacturing Conference and Workshop, IEEEI/ SEMI, 31 March-1 April 2003, pp. 111-117.
11. Fjallström, S., Safsten, K., Harlin, U., and Stahre, J. Information enabling production ramp-up. J. Manuf. Technol. Manage., 2009, 20(2), 178-196.
12. Pruett, M. and Thomas, H. Experience-based learning in innovation and production. R&D Manage., 2008, 38(2), 141-153.
13. Agaga, T., Brzusczak, V., Oduneye, N., Broxup, B., and Palomino Fernandez, D. Ramp-up, MSc Group Project Report, Cranfield University, Cranfield, 2008.
14. Hüntelmann, J., Reinsch, S., and Märtens, A. Logistic- and cost-oriented cross-company rampup planning. In Digital enterprise technology perspectives and future challenges (Eds P. F. Cunha and P. G. Maropoulos), 2007, pp. 115-122 (Springer).
15. Meredith, J. Theory building through conceptual methods. Int. J. Oper. Prod. Manage., 1993, 13(5), 3-11.
16. Cooper, R. G. How companies are reinventing their idea-to-launch methodologies. Res. Technol. Manage., 2009, 52(2), 47-57.
17. Chatzimichali, A. P. and Tourassis, V. D. Towards a learning curve theory for batch production, 2008 (Democritus University of Thrace, Xanthi, Greece).
18. Schuh, G., Desoi, J.-C., and Tücks, G. Holistic approach for production ramp-up in automotive industry. In Advances in integrated design and manufacturing in mechanical engineering (Eds A. Bramley, D. Brissaud and C. McMahon), 2005, pp. 255-268 (Springer, Bath, UK).
19. Koss, J. P. Production line start up. Beverage World, 1996, 115(1627), 84-85.
20. Mountney, S. L., Gao, J. X., and Wiseall, S. A knowledge system to support manufacturing knowledge during preliminary design. Int. J. Prod. Res., 2007, 45(7), 1521-1537.
21. Pegels, C. C. Start up or learning curves: some new approaches. Decision Sci., 1976, 7(4), 705-713.
22. Alchian, A. A. Reliability of progress curves in airframe production, 1950 (RM-260-1, The RAND Corporation, Santa Monica, CA).
23. Adler, P. S. and Clark, K. B. Behind the learning curve: a sketch of the learning process. Manage. Sci., 1991, 37(3), 267-281.
24. Womer, N. K. Estimating learning curves from aggregate monthly data. Manage. Sci., 1984, 30(8), 982-992.
25. Balasubramaniam, S., Sarwar, A. K., and Walker, D. M. H. Yield learning in integrated circuit package assembly. Components, Packaging Manuf. Technol., 1997, 20(2), 133-141.
26. Benkard, C. L. Learning and forgetting: the dynamics of aircraft production. Am. Econ. Rev., 2000, 90(4), 1034-1054.
27. Jamasb, T. Technical change theory and learning curves: patterns of progress in electricity generation technologies. Energy J., 2007, 28(3), 51-71. (Pubitemid 47073922)
28. Yelle, L. E. The learning curve: historical review and comprehensive study. Decision Sci., 1979, 10(2), 302-328.
29. Argote, L. and Epple, D. Learning curves in manufacturing. Science, 1990, 247(4945), 920-924.
30. Liao, W. M. Effects of learning on resource allocation decisions. Decision Sci., 1979, 10(1), 116-125.
31. Biskup, D. A state-of-the-art review on scheduling with learning effects. Eur. J. Oper. Res., 2008, 188(2), 315-329.
32. Wang, Q. and Stockton, D. J. Cost model development using artificial neural networks. Aircr. Eng. Aerosp. Technol., 2001, 73(6), 536-541. (Pubitemid 35355351)
33. Kantor, P. B. and Zangwill, W. I. Theoretical foundation for a learning rate budget. Manage. Sci., 1991, 37(3), 315-330.
34. Chen, G. and McLennan, D. D. A study of learning curve impact on three identical small spacecraft. In Proceedings of the 2004 IEEE Aerospace Conference, Big Sky, MT, USA, 6-13 March 2004, vol. 6, pp. 3970- 3976.
35. Curran, R., Kundu, A., Raghunathan, S., Eakin, D., and McFadden, R. Influence of manufacturing tolerance on aircraft direct operating cost (DOC). J. Mater. Process. Techn., 2003, 138(1-3), 208-213.
36. Myers, J. The importance of recurring and nonrecurring costs. Contract Manage., 2007, 3, 36-39.
37. Curran, R., Raghunathan, S., and Price, M. Review of aerospace engineering cost modelling: the genetic causal approach. Prog. Aerosp. Sci., 2004, 40(8), 487-534. (Pubitemid 40394061)
38. Butterfield, J., Curran, R., Watson, G., Craig, C., Raghunathan, S., Collins, R., Edgar, T., Higgins, C., Burke, R., Kelly, P., and Gibson, C. Use of digital manufacturing to improve operator learning in aerospace assembly. In Proceedings of the 7th AIAA Aviation Technology, Integration and Operations Conference (ATIO) 2nd C, vol. 7865, Belfast, Northern Ireland, 18-20 September 2007.
39. Hax, A. C. and Majluf, N. S. Competitive cost dynamics: the experience curve. Interfaces, 1982, 12(5), 50-61.
40. Lanza, G. and Ude, J. A concept for the configuration of value added networks based on quality capabilities ramp-up. In Digital enterprise technology perspectives and future challenges (Eds P. F. Cunha and P. G. Maropoulos), 2007, pp. 393-400 (Springer).
41. Sharma, K. R., Yuan, Z., de Haas, D., Hamilton, G., Corrie, S., and Keller, J. Dynamics and dynamic modelling of H2S production in sewer systems. Water Res., 2008, 42(10-11), 2527-2538.
42. Baykoç, O. F. and Erol, S. Simulation modelling and analysis of a JIT production system. Int. J. Prod. Econ., 1998, 55(2), 203-212. (Pubitemid 128401611)
43. Ceglarek, D., Huang, W., Zhou, S., Ding, Y., Kumar, R., and Zhou, Y. Time-based competition in multistage manufacturing: stream-of-variation analysis (SOVA). Int. J. Flexible Manuf. Syst., 2004, 16(1), 11-44.
44. Barhak, J., Djurdjanovic, D., Spicer, P., and Katz, R. Integration of reconfigurable inspection with stream of variations methodology. Int. J. Machine Tools Manuf., 2005, 45(4-5), 407-419. (Pubitemid 40142534)
45. Winkler, H., Heins, M., and Nyhuis, P. A controlling system based on cause-effect relationships for the ramp-up of production systems. Prod. Eng. Res. Dev., 2007, 1, 103-111.
46. Fleischer, J., Lanza, G., and Ender, T. A dynamic business-process based production ramp-up simulation model. Prod. Eng., 2006, 13(2), 197-200.
47. Mejean, A. and Hope, C. Modelling the costs of nonconventional oil: a case study of Canadian bitumen. Energy Pol., 2008, 36(11), 4205-4216.
48. Kellogg, R. and Phan, S. An analogy-based method for estimating the costs of space-based instruments. In Proceedings of the IEEE Aerospace Conference, Big Sky, MT, USA 8-15 March 2003, vol. 8, pp. 3843-3847.
49. Rosenberg, L., Hihn, L., Roust, K., and Warfield, K. Parametric cost modeling of space missions using the Develop New Projects (DNP) implementation process. In Proceedings of the INCOSE Symposium, Brighton, UK, 1999.
50. Roy, R., Kelvesjo, S., Forsberg, S., and Rush, C. Quantitative and qualitative cost estimating for engineering design. J. Eng. Design, 2001, 12(2), 147-162.
51. Rehman, S. Knowledge-based cost modelling for innovative design. PhD Thesis, Cranfield University, Cranfield, 2000.
52. NASA. Cost estimating handbook, 2002 (NASA HQ, Washington, DC).
53. Hogan, M. Development of an integrated cost model for single living acquisition. MSc Thesis, Cranfield University, Cranfield, 2005.
54. Balci, O. Verification, validation, and testing. In Handbook of simulation-principles, methodology, advances, applications, and practice (Ed. J. Banks), 1998, pp. 335-393 (John Wiley & Sons, New York).