Modeling and Analyzing Supporting Systems for Smart Manufacturing Systems with Stochastic, Technical and Economic Dependences

Document Type : Original Article

Authors

1 Aerospace Research Institute, Ministry of Science, Research and Technology, Iran

2 Energy Engineering Department, Polytechnic di Milano, Italy

Abstract

Smart manufacturing systems are triggerring the next industrial revolution.They are intended to be collaborative manufacturing systems that respond in real time to meet the system’s changing demands and conditions. Different types of dependencies among system components are introduced to enable this and to improve system performance, including structural, stochastic, technical and economic dependences. Supporting systems are also introduced to this aim, through specified interfaces. In this paper, the role of maintenance policy, spare part inventory and buffer size as supporting systems of smart systems is considered. Load-sharing dependence, adaptive control with feedback and economic dependence are specifically considered, and their effect is studied via Monte Carlo simulation. Results show that smart systems with properly designed supporting systems have undoubtedly increased system complexity and dependencies, but can indeed increase availability and production volume, and system efficiency overall, with total cost reduced.

Keywords

References

1.     Thompson, K., "Smart manufacturing operations planning and control program", Gaithersburg, MD: National Institute of Standards and Technology (NIST),  (2014).
2.     Mobley, R.K., "An introduction to predictive maintenance, Elsevier,  (2002).
3.     Chen, X., Xu, D. and XiAo, L., "Joint optimization of replacement and spare ordering for critical rotary component based on condition signal to date", Eksploatacja i Niezawodność,  Vol. 19, (2017). 76-85. DOI: 10.17531/ein.2017.1.11
4.     Zhu, Q., Peng, H. and van Houtum, G.-J., "A condition-based maintenance policy for multi-component systems with a high maintenance setup cost", Or Spectrum,  Vol. 37, No. 4, (2015), 1007-1035.
5.     Tian, Z. and Liao, H., "Condition based maintenance optimization for multi-component systems using proportional hazards model", Reliability Engineering & System Safety,  Vol. 96, No. 5, (2011), 581-589.
6.     Bian, L. and Gebraeel, N., "Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions", Iie Transactions,  Vol. 46, No. 5, (2014), 470-482.
7.     Keizer, M.C.O., Teunter, R.H. and Veldman, J., "Clustering condition-based maintenance for systems with redundancy and economic dependencies", European Journal of Operational Research,  Vol. 251, No. 2, (2016), 531-540.
8.     Zhang, X. and Zeng, J., "Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems", European Journal of Operational Research,  Vol. 262, No. 2, (2017), 479-498. DOI: 10.1016/j.ejor.2017.03.019
9.     Keizer, M.C.O., Teunter, R.H., Veldman, J. and Babai, M.Z., "Condition-based maintenance for systems with economic dependence and load sharing", International Journal of Production Economics,  Vol. 195, (2018), 319-327.
10.   Cheng, J., "Condition based maintenance optimization for multi-component systems based on neural network health prediction", Concordia University,  (2010),
11.   Van Horenbeek, A., Buré, J., Cattrysse, D., Pintelon, L. and Vansteenwegen, P., "Joint maintenance and inventory optimization systems: A review", International Journal of Production Economics,  Vol. 143, No. 2, (2013), 499-508. DOI:10.1016/j.ijpe.2012.04.001
12.   Lynch, P., Adendorff, K., Yadavalli, V. and Adetunji, O., "Optimal spares and preventive maintenance frequencies for constrained industrial systems", Computers & Industrial Engineering,  Vol. 65, No. 3, (2013), 378-387. Doi:10.1016/j.cie.2013.03.005
13.   Wang, Y., Gu, H., Zhao, J. and Cheng, Z., "Modeling on spare parts inventory control under condition based maintenance strategy", Journal of Shanghai Jiaotong University (Science),  Vol. 21, No. 5, (2016), 600-604.
14.   Lin, X., Basten, R.J., Kranenburg, A. and van Houtum, G.-J., "Condition based spare parts supply", Reliability Engineering & System Safety,  Vol. 168, (2017), 240-248.
15.   Van der Auweraer, S. and Boute, R., "Forecasting spare part demand using service maintenance information", International Journal of Production Economics,  Vol. 213, (2019), 138-149.
16.   Driessen, M., Arts, J., van Houtum, G.-J., Rustenburg, J.W. and Huisman, B., "Maintenance spare parts planning and control: A framework for control and agenda for future research", Production Planning & Control,  Vol. 26, No. 5, (2015), 407-426. DOI: 10.1080/09537287.2014.907586
17.   MacGregor Smith, J. and Cruz, F.R., "The buffer allocation problem for general finite buffer queueing networks", IIE Transactions,  Vol. 37, No. 4, (2005), 343-365.
18.   Lutz, C.M., Davis, K.R. and Sun, M., "Determining buffer location and size in production lines using tabu search", European Journal of Operational Research,  Vol. 106, No. 2-3, (1998), 301-316.
19.   Weiss, S., Schwarz, J.A. and Stolletz, R., "The buffer allocation problem in production lines: Formulations, solution methods, and instances", IISE Transactions,  Vol. 51, No. 5, (2019), 456-485. DOI: 10.1080/24725854.2018.1442031
20.   Gan, S. and Shi, J., "Maintenance optimization for a production system with intermediate buffer and replacement part order considered", Eksploatacja i Niezawodność,  Vol. 16, No. 1, (2014), 140--149.
21.   Sharma, G., Kumar, A. and Jain, M., "Maintenance cost analysis for replacement model with perfect minimal repair", International Journal of Engineering,  Vol. 15, No. 2, (2002), 161-168.
22.   Ghandali, R., Abooie, M. and Nezhad, F., "A pomdp framework to find optimal inspection and maintenance policies via availability and profit maximization for manufacturing systems", International Journal of Engineering,  Vol. 31, No. 12, (2018), 2077-2084.
23.   Ram, M. and SINGH, V., "Modeling and availability analysis of internet data center with various maintenance policies", International Journal of Engineering,  Vol. 27, No. 4, (2014), 599-608.
24.   TC, I., "Petroleum, petrochemical and natural gas industries–collection and exchange of reliability and maintenance data for equipment",  Standard, (2007).
25.          Chang, Q., Ni, J., Bandyopadhyay, P., Biller, S. and Xiao, G., "Maintenance opportunity planning system", Journal of Manufacturing Science and Engineering, Vol. 129, (2007), 661-668.
International Journal of Engineering
Volume 33, Issue 11
TRANSACTIONS B: Applications
November 2020
Pages 2310-2318

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