Adaptive Production Programming Method Supported by a Performance Measurement and Continuous Improvement System
Abstract
This paper proposes a production scheduling method that adapts to the scenario production of each industry. Named as MAP-Prod this method should incorporate characteristics of reactive and proactive approaches. Thus, the cycle of adaptation is characterized by improvement actions found through the gathering information and analysis of indicators in a performance measurement system. These actions are accompanied by a continuous improvement system to diagnose their effectiveness. A simulation is then performed with real data from an industry in order to verify the results that can be obtained with the method.
Keywords:
Adaptive Method, Measurement System, Production Scheduling
References
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Aytug, H., Lawley, M. A., McKay, K., Mohan, S., and Uzsoy, R. (2005). Executing production schedules in the face of uncertainties: A review and some future directions. European Journal Of Operational Research, pages 86–110.
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Bidot, J., Vidal, T., Laborie, P., and Beck, J. C. (2009). A theoretic and practical framework for scheduling in a stochastic environment. Journal of Scheduling, 10.
Billaut, J. C., Moukrim, A., and Sanlaville, E. (2010). Introduction to Flexibility and Robustness in Scheduling. ISTE.
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Mehta, S. and Uzsoy, R. (1998). Predictable scheduling of a job shop subject to breakdowns. IEEE Transactions on Robotics and Automation, 14:365–378.
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Ouelhadj, D. and Petrovic, S. (2009). Survey of dynamic scheduling in manufacturing systems. Journal of Scheduling, 12/4:417–431.
Savolainen, T. (1999). Cycles of continuous improvement: realizing competitive advantages through quality. International Journal of Operations & Production Management, 19(11).
Aytug, H., Lawley, M. A., McKay, K., Mohan, S., and Uzsoy, R. (2005). Executing production schedules in the face of uncertainties: A review and some future directions. European Journal Of Operational Research, pages 86–110.
Bessant, J., Caffyn, S., Gilbert, J., R., H., and Webb, S. (1994). Rediscovering continous improvement. Technovation, 14.
Bidot, J., Vidal, T., Laborie, P., and Beck, J. C. (2009). A theoretic and practical framework for scheduling in a stochastic environment. Journal of Scheduling, 10.
Billaut, J. C., Moukrim, A., and Sanlaville, E. (2010). Introduction to Flexibility and Robustness in Scheduling. ISTE.
Gerolamo, M. C. Proposta de sistematização para o processo de gestão de melhorias e mudanças de desempenho. Master’s thesis, Sao Carlos.
Herroelen, W. and Leus, R. (2005). Project scheduling under uncertainty: Survey and research potentials. European Journal Of Operational Research, pages 289–306.
Lambrechts, O., Demeulemeester, E., and Herroelen, W. (2008). Proactive and reactive strategies for resource-constrained project scheduling with uncertain resource availabilities. Journal of Scheduling, 11.
Liu, W., Chua, T. J., Lam, J., Wang, F. Y., Cai, T. X., and Yin, X. F. (2002). Aps, erpand mes systems integration for semiconductor backend assembly. 7th International Conference on Control, Automation, Robotic and Vision (ICARCV 2002), pages 1403–1408.
Mehta, S. and Uzsoy, R. (1998). Predictable scheduling of a job shop subject to breakdowns. IEEE Transactions on Robotics and Automation, 14:365–378.
Merli, G. (1993). EuroChallenge: TQM Approach to Capturing Global Markets. IFS.
Ouelhadj, D. and Petrovic, S. (2009). Survey of dynamic scheduling in manufacturing systems. Journal of Scheduling, 12/4:417–431.
Savolainen, T. (1999). Cycles of continuous improvement: realizing competitive advantages through quality. International Journal of Operations & Production Management, 19(11).
Published
2012-05-16
How to Cite
BELAN, Helder Carlo; PALMA, Jandira Guenka.
Adaptive Production Programming Method Supported by a Performance Measurement and Continuous Improvement System. In: BRAZILIAN SYMPOSIUM ON INFORMATION SYSTEMS (SBSI), 8. , 2012, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2012
.
p. 157-168.
DOI: https://doi.org/10.5753/sbsi.2012.14402.
