Integrated maintenance, inventory and quality engineering decisions for multi-product systems

• Autorzy: Salmasnia Ali , Hafezian Rahil , Maleki Mohammad Reza

Identyfikatory

DOI

10.2478/emj-2022-0033

• Języki publikacji: EN

Abstrakty

EN

It is essential for manufacturers to consider the interrelation among quality, inventory, and maintenance decisions to detect imperfect quality products, keep the production system in good operating condition, and manage quality and inventory costs. Hence, this paper aims to develop an integrated model of inventory planning, quality engineering, and maintenance scheduling in which the expected total cost per time unit is minimised by determining the sample size, sampling interval, control limit coefficient, along with production cycle time. In this regard, an imperfect multi-product manufacturing system is considered, in which the inventory shortage in satisfying the demand for each product type and the idle time during the production cycle are not allowed. It is assumed that the process starts in an in-control condition where most produced units are conforming. However, due to the occurrence of an assignable cause (AC), the process mean moves to an out-of-control condition in which a significant fraction of non-conforming units is produced. The efficiency of the proposed mathematical model is evaluated by a numerical example, and then the sensitivity of the proposed model to important inputs is analysed. Finally, a comparative study based on the Taguchi design approach is given to confirm the capability of the proposed model to achieve remarkable cost savings.

Słowa kluczowe

EN

multiproduct system; production planning; maintenance scheduling; control chart; inventory planning; imperfect production system

PL

system wieloproduktowy; planowanie produkcji; planowanie konserwacji; wykres kontrolny; planowanie inwentaryzacji; niedoskonały system produkcji

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Engineering Management in Production and Services
• Rocznik: 2022
• Tom: Vol. 14, no. 4
• Strony: 94--113
• Opis fizyczny: Bibliogr. 50 poz., tab., wykr.

Twórcy

autor

Salmasnia Ali

• University of Qom, Iran

• https://orcid.org/0000-0001-9263-2520

autor

Hafezian Rahil

• University of Qom, Iran

autor

Maleki Mohammad Reza

• Industrial Engineering Group, Golpayegan College of Engineering, Isfahan University of Technology, Golpayegan, Iran.

• https://orcid.org/0000-0002-6005-3046

Bibliografia

• Amiri, A., Bashiri, M., Maleki, M. R., & Moghaddam, A. S. (2014). Multi-objective Markov-based economicstatistical design of EWMA control chart using NSGA- II and MOGA algorithms. International Journal of Multicriteria Decision Making, 4(4), 332-347.
• Baker, K. R. (1970). Note – On Madigan’s Approach to the Deterministic Multi-Product Production and Inventory Problem. Management Science, 16(9), 636-638.
• Ben-Daya, M., & Makhdoum, M. (1998). Integrated production and quality model under various preventive maintenance policies. Journal of the operational Research Society, 49(8), 840-853.
• Bisgaard, S., Hunter, W. G., Pallesen, L. (1984). Economic selection of quality manufactured product. Technometrics, 26(1), 9-18.
• Bomberger, E. E. (1966). A dynamic programming approach to a lot size scheduling problem. Management Science, 12(11), 778-784.
• Cassady, C. R., Bowden, R. O., Liew, L., & Pohl, E. A. (2000). Combining preventive maintenance and statistical process control: a preliminary investigation. IIE Transactions, 32(6), 471-478.
• Chen, W. S., Yu, F. J., Guh, R. S., & Lin, Y. H. (2011). Economic design of x-bar control charts under preventive maintenance and Taguchi loss functions. Journal of Applied Research, 3(2), 103-109.
• Cho, D. I., & Parlar, M. (1991). A survey of maintenance models for multi-unit systems. European Journal of Operational Research, 51(1), 1-23.
• Ershadi, M. J., Ershadi, M. M., Haghighi Naeini, S., & Niaki, S. T. A. (2021). An economic-statistical design of simple linear profiles with multiple assignable causes using a combination of MOPSO and RSM. Soft Computing, 25(16), 11087-11100.
• Fakher, H. B., Nourelfath, M., & Gendreau, M. (2018). Integrating production, maintenance and quality: A multi-period multi-product profit-maximization model. Reliability Engineering & System Safety, 170, 191-201.
• Gouiaa-Mtibaa, A., Dellagi, S., Achour, Z., & Erray, W. (2018). Integrated maintenance-quality policy with rework process under improved imperfect preventive maintenance. Reliability Engineering & System Safety, 173, 1-11.
• Hodgson, T. J. (1970). Addendum to Stankard and Gupta’s note on lot size scheduling. Management Science, 16(7), 514-517.
• Hu, J., Wang, Y., Pang, Y., & Liu, Y. (2022). Optimal maintenance scheduling under uncertainties using Linear Programming-enhanced Reinforcement Learning. Engineering Applications of Artificial Intelligence, 109, 104655.
• Kamel, G., Aly, M. F., Mohib, A., & Afefy, I. H. (2020). Optimization of a multilevel integrated preventive maintenance scheduling mathematical model using genetic algorithm. International Journal of Management Science and Engineering Management, 15(4), 247-257.
• Kuo, Y. (2006). Optimal adaptive control policy for joint machine maintenance and product quality control. European Journal of Operational Research, 171(2), 586-597.
• Lee, P. H., Torn, C. C., & Liao, L. F. (2012). An economic design of combined double sampling and variable sampling interval control chart. International Journal of Production Economics, 138(1), 102-106.
• Linderman, K., McKone-Sweet, K. E., & Anderson, J. C. (2005). An integrated systems approach to process control and maintenance. European Journal of Operational Research, 164(2), 324-340.
• Liu, G., Long, X., Tong, S., Zhang, R., & Chen, S. (2019). Optimum Consecutive Preventive Maintenance Scheduling Model Considering Reliability. Journal of Shanghai Jiaotong University (Science), 24(4), 490- 495.
• Liu, L., Yu, M., Ma, Y., & Tu, Y. (2013). Economic and economic-statistical designs of a control chart for two-unit series systems with condition-based maintenance. European Journal of Operational Research, 226(3), 491-499.
• Liu, X., Wang, W., & Peng, R. (2015). An integrated production, inventory and preventive maintenance model for a multi-product production system. Reliability Engineering & System Safety, 137, 76-86.
• Lorenzen, T. J., & Vance, L. C. (1986). The economic design of control charts: a unified approach. Technometrics, 28(1), 3-10.
• Madigan, J. G. (1968). Scheduling a multi-product single machine system for an infinite planning period. Management Science, 14(11), 713-719.
• Makis, V., & Fung, J. (1998). An EMQ model with inspections and random machine failures. Journal of the Operational Research Society, 49(1), 66-76.
• Mehrafrooz, Z., & Noorossana, R. (2011). An integrated model based on statistical process control and maintenance. Computers & Industrial Engineering, 61(4), 1245-1255.
• Moghaddam, K. S., & Usher, J. S. (2011). Sensitivity analysis and comparison of algorithms in preventive maintenance and replacement scheduling optimization models. Computers & Industrial Engineering, 61(1), 64-75.
• Nenes, G., Tasias, K. A., & Celano, G. (2015). A general model for the economic-statistical design of adaptive control charts for processes subject to multiple assignable causes. International Journal of Production Research, 53(7), 2146-2164.
• Nourelfath, M., Nahas, N., & Ben-Daya, M. (2016). Integrated preventive maintenance and production decisions for imperfect processes. Reliability Engineering & System Safety, 148, 21-31.
• Pal, B., Sana, S. S., & Chaudhuri, K. (2014). A multi-echelon production-inventory system with supply disruption. Journal of Manufacturing Systems, 33(2), 262-276.
• Pan, E., Jin, Y., Wang, S., & Cang, T. (2012). An integrated EPQ model based on a control chart for an imperfect production process. International Journal of Production Research, 50(23), 6999-7011.
• Rahim, M. A., & Ben-Daya, M. (1998). A generalized economic model for joint determination of production run, inspection schedule and control chart design. International Journal of Production Research, 36(1), 277-289.
• Rogers, J. (1958). A computational approach to the economic lot scheduling problem. Management science, 4(3), 264-291.
• Rosenblatt, M. J., & Lee, H. L. (1986). Economic production cycles with imperfect production processes. IIE transactions, 18(1), 48-55.
• Roshanbin, N., Ershadi, M. J., & Niaki, S. T. A. (2022). Multi-objective economic-statistical design of simple linear profiles using a combination of NSGA-II, RSM, and TOPSIS. Communications in Statistics- Simulation and Computation, 51(4), 1704-1720.
• Saeedi Mehrabad, M., Jabarzadeh, A., & Alimian, M. (2017). An integrated production and preventive maintenance planning model with imperfect maintenance in multi-state system. Journal of Industrial and Systems Engineering, 10(4), 28-42.
• Salmasnia, A., Abdzadeh, B., & Namdar, M. (2017). A joint design of production run length, maintenance policy and control chart with multiple assignable causes. Journal of Manufacturing Systems, 42, 44-56.
• Salmasnia, A., Namdar, M., & Noroozi, M. (2018a). Robust design of a VP-NCS chart for joint monitoring mean and variability in series systems under maintenance policy. Computers & Industrial Engineering, 124, 220- 236.
• Salmasnia, A., Kaveie, M., & Namdar, M. (2018b). An integrated production and maintenance planning model under VP-T2 Hotelling chart. Computers & Industrial Engineering, 118, 89-103.
• Salmasnia, A., Rahimi, A., & Abdzadeh, B. (2019a). An integration of NSGA-II and DEA for economic–statistical design of T2-Hotelling control chart with double warning lines. Neural Computing and Applications, 31(2), 1173-1194.
• Salmasnia, A., Soltany, F., noroozi, M., Abdzadeh, B. (2019b). An economic-statistical model for production and maintenance planning under adaptive non-central chi-square control chart. Journal of Industrial and Systems Engineering, 12(Special issue on Statistical Processes and Statistical Modeling), 35- 65.
• Salmasnia, A., Namdar, M., & Abdzadeh, B. (2020a). An integrated quality and maintenance model for two-unit series systems. Communications in Statistics-Simulation and Computation, 49(4), 886-917.
• Salmasnia, A., Hajihosseini, Z., Namdar, M., & Mamashli, F. (2020b). A joint determination of production cycle length, maintenance policy, and control chart parameters considering time value of money under stochastic shift size. Scientia Iranica, 27(1), 427-447.
• Salmasnia, A., Abdzadeh, B., & Maleki, M. R. (2022). An economic-statistical production quantity model under quality-maintenance policy for imperfect manufacturing systems with interaction effect among assignable causes. Scientia Iranica. In Press, doi: 10.24200/SCI.2022.58548.5783
• Stankard, M. F., & Gupta, S. K. (1969). A note on Bomberger’s approach to lot size scheduling: Heuristic proposed. Management Science, 449-452.
• Tagaras, G. (1988). An integrated cost model for the joint optimization of process control and maintenance. Journal of the Operational Research Society, 39(8), 757-766.
• Taleizadeh, A. A., Cárdenas-Barrón, L. E., & Mohammadi, B. (2014). A deterministic multi product single machine EPQ model with backordering, scraped products, rework and interruption in manufacturing process. International Journal of Production Economics, 150, 9-27.
• Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139(3), 469-489.
• Xiang, Y. (2013). Joint optimization of control chart and preventive maintenance policies: A discrete-time Markov chain approach. European Journal of Operational Research, 229(2), 382-390.
• Yin, H., Zhang, G., Zhu, H., Deng, Y., & He, F. (2015). An integrated model of statistical process control and maintenance based on the delayed monitoring. Reliability Engineering & System Safety, 133, 323-333.
• Zhou, W. H., & Zhu, G. L. (2008). Economic design of integrated model of control chart and maintenance management. Mathematical and computer Modelling, 47(11-12), 1389-1395.
• Zhou, X., Zhu, M., & Yu, W. (2021). Maintenance scheduling for flexible multistage manufacturing systems with uncertain demands. International Journal of Production Research, 59(19), 5831-5843.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).