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Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures

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Abstract

The accurate due-date reliability evaluation of demand satisfaction is vital for due-time performance prediction of production systems. This paper proposes an improved multi-state reliability evaluation approach for production systems with finite buffers subject to time-dependent failures (TDFs), operation-dependent failures (ODFs). Instead of TDF machine model or ODF machine model, a modified machine reliability model considering both TDFs and ODFs is presented as a basis. And then an equivalent workstation reliability model is proposed by steady probability analysis of finite buffers. A united reliability calculating framework is constructed for the multi-state production system based on universal generating function. A case study of a piston production line is conducted to prove the feasibility and effectiveness of the proposed methodology.

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References

  • Altumi, A. A., Philipose, A. M., & Taboun, S. M. (2001). Reliability optimisation of flexible manufacturing systems with spare tooling. The International Journal of Advanced Manufacturing Technology., 17, 69–77.

    Article  Google Scholar 

  • Boiteau, M., Dutuit, Y., Rauzy, A., & Signoret, J. P. (2006). The AltaRica data-flow language in use: Modeling of production availability of a multi-state system. Reliability Engineering & System Safety., 91, 747–755.

    Article  Google Scholar 

  • Bouslah, B., Gharbi, A., & Pellerin, R. (2018). Joint production, quality and maintenance control of a two-machine line subject to operation-dependent and quality-dependent failures. International Journal of Production Economics., 195, 210–226.

    Article  Google Scholar 

  • Buzacott, J. A., & Zhang, R. Q. (2004). Inventory management with asset-based financing. Management Science., 50, 1274–1292.

    Article  Google Scholar 

  • Chang, P.-C. (2017). Reliability with finite buffer size for a multistate manufacturing system with parallel production lines. Journal of the Chinese Institute of Engineers., 40, 275–283.

    Article  Google Scholar 

  • Chen, Z., Chen, Z., Zhou, D., Xia, T., & Pan, E. (2021). Reliability evaluation for multi-state manufacturing systems with quality-reliability dependency. Computers & Industrial Engineering., 154, 107166.

    Article  Google Scholar 

  • Chen, Y., Jin, J., & Shi, J. (2004). Integration of dimensional quality and locator reliability in design and evaluation of multi-station body-in-white assembly processes. IIE Transactions., 36, 827–839.

    Article  Google Scholar 

  • Dallery, Y., & Gershwin, S. B. (1992). Manufacturing flow line systems: A review of models and analytical results. Queueing Systems., 12, 3–94.

    Article  Google Scholar 

  • Das, K., Lashkari, R. S., & Sengupta, S. (2007). Reliability consideration in the design and analysis of cellular manufacturing systems. International Journal of Production Economics., 105, 243–262.

    Article  Google Scholar 

  • Demir, L., Tunali, S., & Eliiyi, D. T. (2014). The state of the art on buffer allocation problem: A comprehensive survey. Journal of Intelligent Manufacturing., 25, 371–392.

    Article  Google Scholar 

  • Ding, Y., Hu, Y., & Li, D. (2021). Redundancy optimization for multi-performance multi-state series-parallel systems considering reliability requirements. Reliability Engineering & System Safety., 215, 107873.

    Article  Google Scholar 

  • Duffie, N., Bendul, J., & Knollmann, M. (2017). An analytical approach to improving due-date and lead-time dynamics in production systems. Journal of Manufacturing Systems., 45, 273–285.

    Article  Google Scholar 

  • Enginarlar, E., Li, J., Meerkov, S. M., & Zhang, R. Q. (2002). Buffer capacity for accommodating machine downtime in serial production lines. International Journal of Production Research., 40, 601–624.

    Article  Google Scholar 

  • Fiondella, L., Lin, Y. K., & Chang, P. C. (2015). System performance and reliability modeling of a stochastic-flow production network: A confidence-based approach. IEEE Transactions on System Man Cybernetics-Systems., 45, 1437–1447.

    Article  Google Scholar 

  • Fiondella, L., & Xing, L. D. (2015). Discrete and continuous reliability models for systems with identically distributed correlated components. Reliability Engineering & System Safety., 133, 1–10.

    Article  Google Scholar 

  • Görkemli, L., & Kapan, U. S. (2010). Fuzzy Bayesian reliability and availability analysis of production systems. Computers & Industrial Engineering., 59, 690–696.

    Article  Google Scholar 

  • Hosseini, S., Barker, K., & Ramirez-Marquez, J. E. (2016). A review of definitions and measures of system resilience. Reliability Engineering & System Safety., 145, 47–61.

    Article  Google Scholar 

  • Jafary, B., & Fiondella, L. (2016). A universal generating function-based multi-state system performance model subject to correlated failures. Reliability Engineering & System Safety., 152, 16–27.

    Article  Google Scholar 

  • Jiang, Z. B., & He, J. M. (2003). Stochastic object-oriented petri nets (SOPNs) and its application in modeling of manufacturing system reliability. Chinese Journal of Mechanical Engineering., 16, 272–276.

    Article  Google Scholar 

  • Levitin, G. (2004). A universal generating function approach for the analysis of multi-state systems with dependent elements. Reliability Engineering & System Safety., 84, 285–292.

    Article  Google Scholar 

  • Levitin, G., Jia, H., Ding, Y., Song, Y., & Dai, Y. (2017). Reliability of multi-state systems with free access to repairable standby elements. Reliability Engineering & System Safety., 167, 192–197.

    Article  Google Scholar 

  • Levitin, G., & Xing, L. (2010). Reliability and performance of multi-state systems with propagated failures having selective effect. Reliability Engineering & System Safety., 95, 655–661.

    Article  Google Scholar 

  • Levitin, G., Xing, L., & Dai, Y. (2018). Optimizing Dynamic Performance of Multistate Systems With Heterogeneous 1-Out-of-N Warm Standby Components. IEEE Transactions on Systems, Man, and Cybernetics: Systems., 48, 920–929.

    Article  Google Scholar 

  • Li, J., Blumenfeld, D. E., & Alden, J. M. (2006). Comparisons of two-machine line models in throughput analysis. International Journal of Production Research., 44, 1375–1398.

    Article  Google Scholar 

  • Li, J., Blumenfeld, D. E., Huang, N., & Alden, J. M. (2009). Throughput analysis of production systems: recent advances and future topics. International Journal of Production Research, 47(14), 3823–3851. https://doi.org/10.1080/00207540701829752

    Article  Google Scholar 

  • Li, Y. F., Huang, H. Z., Mi, J. H., Peng, W. W., & Han, X. M. (2022). Reliability analysis of multi-state systems with common cause failures based on Bayesian network and fuzzy probability. Annals of Operations Research., 311, 195–209.

    Article  MathSciNet  Google Scholar 

  • Li, J., & Meerkov, S. M. (2003). Due-Time Performance of Production Systems with Markovian Machines. In S. B. Gershwin, Y. Dallery, C. T. Papadopoulos, & J. M. Smith (Eds.), Analysis and Modeling of Manufacturing Systems (pp. 221–253). Springer, US.

    Chapter  Google Scholar 

  • Li, J., Meerkov, S. M., & Zhang, L. (2010). Production systems engineering: Problems, solutions, and applications. Annual Reviews in Control., 34, 73–88.

    Article  Google Scholar 

  • Lin, Y. K., & Chang, P. C. (2013). Reliability-based performance indicator for a manufacturing network with multiple production lines in parallel. Journal of Manufacturing Systems., 32, 147–153.

    Article  Google Scholar 

  • Lin, Y.-K., & Chang, P.-C. (2015). Demand satisfaction and decision-making for a PCB manufacturing system with production lines in parallel. International Journal of Production Research., 53, 3193–3206.

    Article  Google Scholar 

  • Lin, Y. K., Chang, P. C., & Chen, J. C. (2012). Reliability evaluation for a waste-reduction parallel-line manufacturing system. Journal of Cleaner Production., 35, 93–101.

    Article  Google Scholar 

  • Lin, Y. K., Chang, P. C., Yeng, L. C. L., & Shih, P. S. (2017). Reliability evaluation for an intermittent production system with stochastic number of normal machines. Journal of Manufacturing Systems., 45, 222–235.

    Article  Google Scholar 

  • Matta, A., & Simone, F. (2016). Analysis of two-machine lines with finite buffer, operation-dependent and time-dependent failure modes. International Journal of Production Research., 54, 1850–1862.

    Article  Google Scholar 

  • Mourani, I., Hennequin, S., & Xie, X. (2007). Failure models and throughput rate of transfer lines. International Journal of Production Research., 45, 1835–1859.

    Article  Google Scholar 

  • Nourelfath, M., Ait-kadi, D., & Isaac Soro, W. (2003). Availability modeling and optimization of reconfigurable manufacturing systems. Journal of Quality in Maintenance Engineering., 9, 284–302.

    Article  Google Scholar 

  • Nourelfath, M., Fitouhi, M. C., & Machani, M. (2010). An integrated model for production and preventive maintenance planning in multi-state systems. IEEE Transactions on Reliability., 59, 496–506.

    Article  Google Scholar 

  • Ozdogru, U., & Altiok, T. (2015). Continuous material flow systems: Analysis of marine ports handling bulk materials. Annals of Operations Research., 231, 79–104.

    Article  MathSciNet  Google Scholar 

  • Savsar, M., & Aldaihani, M. (2008). Modeling of machine failures in a flexible manufacturing cell with two machines served by a robot. Reliability Engineering & System Safety., 93, 1551–1562.

    Article  Google Scholar 

  • Shanthikumar, J. G., Ding, S. W., & Zhang, M. T. (2007). Queueing theory for semiconductor manufacturing systems: A survey and open problems. IEEE Transactions on Automation Science Engineering., 4, 513–522.

    Article  Google Scholar 

  • Sun, J. W., Xi, L. F., Du, S. C., & Ju, B. (2008). Reliability modeling and analysis of serial-parallel hybrid multi-operational manufacturing system considering dimensional quality, tool degradation and system configuration. International Journal of Production Economics., 114, 149–164.

    Article  Google Scholar 

  • Tan, B., & Gershwin, S. B. (2011). Modelling and analysis of Markovian continuous flow systems with a finite buffer. Annals of Operations Research., 182, 5–30.

    Article  MathSciNet  Google Scholar 

  • Tang, Y., & Zhou, M. (2006). A Queuing network-based method for reconfiguration of back-end semiconductor manufacturing systems with unreliable equipment. International Journal of Intelligent Control and Systems., 11, 106–113.

    Google Scholar 

  • Tina Song, W., & Lin, P. (2018). System reliability of stochastic networks with multiple reworks. Reliability Engineering & System Safety., 169, 258–268.

    Article  Google Scholar 

  • Tolio, T. A. M., & Ratti, A. (2018). Performance evaluation of two-machine lines with generalized thresholds. International Journal of Production Research., 56, 926–949.

    Article  Google Scholar 

  • Tsarouhas, P. (2018). Reliability, availability and maintainability (RAM) analysis for wine packaging production line. International Journal of Quality & Reliability Management., 35, 821–842.

    Article  Google Scholar 

  • Tsarouhas, P. (2019). Statistical analysis of failure data for estimating reliability, availability and maintainability of an automated croissant production line. Journal of Quality in Maintenance Engineering., 25(3), 452–475.

    Article  Google Scholar 

  • Wang, C., Li, J., (2007). Approximate analysis of re-entrant lines with Bernoulli reliability models. In: 2007 IEEE International Conference on Automation Science and Engineering, (pp. 398–403).

  • Wiendahl, H.-P. (1995). Load-Oriented Manufacturing Control. Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-57743-7

    Book  Google Scholar 

  • Xie, X., Mourani, I., & Hennequin, S. (2004). Performance evaluation of production lines subject to time and operation dependent failures using Petri nets. In: 2004 8th International Conference on Control, Automation, Robotics and Vision, Vols 1–3. New York: IEEE; 2004. (pp. 2123–2128).

  • Yodo, N., Wang, P. F., & Rafi, M. (2018). Enabling Resilience of Complex Engineered Systems Using Control Theory. IEEE Transactions on Reliability., 67, 53–65.

    Article  Google Scholar 

  • Yong, C., & Jionghua, J. (2005). Quality-reliability chain modeling for system-reliability analysis of complex manufacturing processes. IEEE Transactions on Reliability., 54, 475–488.

    Article  Google Scholar 

  • Youssef, A. M. A., & ElMaraghy, H. A. (2007). Optimal configuration selection for Reconfigurable Manufacturing Systems. International Journal of Flexible Manufacturing Systems., 19, 67–106.

    Article  Google Scholar 

  • Youssef, A. M. A., & Elmaraghy, H. A. (2008). Availability consideration in the optimal selection of multiple-aspect RMS configurations. International Journal of Production Research., 46, 5849–5882.

    Article  Google Scholar 

  • Youssef, A. M. A., Mohib, A., & ElMaraghy, H. A. (2006). Availability assessment of multi-state manufacturing systems using universal generating function. CIRP Annals., 55, 445–448.

    Article  Google Scholar 

  • Zhang, W. J., & van Luttervelt, C. A. (2011). Toward a resilient manufacturing system. CIRP Annals., 60, 469–472.

    Article  Google Scholar 

  • Zhang, D., Zhang, Y. J., Yu, M. R., & Chen, Y. (2014). Reliability defects identification of serial production systems: application to a piston production line. Arabian Journal for Science and Engineering., 39, 9113–9125.

    Article  Google Scholar 

  • Zhou, X., & Lu, B. (2018). Preventive maintenance scheduling for serial multi-station manufacturing systems with interaction between station reliability and product quality. Computers & Industrial Engineering., 122, 283–291.

    Article  Google Scholar 

  • Zio, E. (2009). Reliability engineering: Old problems and new challenges. Reliability Engineering & System Safety., 94, 125–141.

    Article  Google Scholar 

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Acknowledgements

This project is supported by the National Natural Science Foundation of China (Grant No.U20A6004,72271067), The International Science and Technology Cooperation Program of Guangdong Province (Grant No.2022A0505050047). Guangzhou Basic and Applied Basic Research Program (SL2023A04J01597), Natural Science Basic Research Program of Shaanxi province (Program No. 2021JQ-263).

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Zhang, D., Luo, Y. & Liu, Q. Reliability evaluation of production systems with finite buffers subject to time-dependent and operation-dependent failures. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-05891-z

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