Abstract
Nowadays, automated guided vehicles (AGVs) play a key role in manufacturing systems because of improving system efficiency and lowering the cost of production. To increase the efficiency and stability of AGVs, it is crucial to consider maintenance planning for them. To the best of our knowledge, there are rarely found studies related to maintenance planning and AGVs’ design and control. Accordingly, in this paper, a new integrated nonlinear mathematical model is developed for optimizing the AGV design (including AGV fleet sizing and AGV assignment to workshops) and preventive maintenance policy. The proposed model aims to determine the preventive maintenance cycles, the optimal number of employed AGVs in manufacturing, and the optimal assignment of AGVs to manufacturing workshops so that the total cost is minimized. To solve this model, a genetic algorithm (GA) is developed, and its performance is compared with the global solver of LINGO software on 15 test problems, some of which are large dimensions. To tune the GA parameters, a Taguchi method is used. Moreover, a sensitivity analysis is performed to represent the validity of the model and solution approach. The results have demonstrated the effectiveness of GA in terms of computational time and solution quality.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Enquiries about data availability should be directed to the authors.
References
Abderrahim M, Bekrar A, Trentesaux D, Aissani N, Bouamrane K (2020) Manufacturing 4.0 operations scheduling with AGV battery management constraints. Energies 13(18):2–19. https://doi.org/10.3390/en13184948
Angeloudis P, Bell MGH (2010) An uncertainty-aware AGV assignment algorithm for automated container terminals. Transp Res Part E Logist Transp Rev 46(3):354–366. https://doi.org/10.1016/j.tre.2009.09.001
Bae J, Chung W (2017) A heuristic for a heterogeneous automated guided vehicle routing problem. Int J Precis Eng Manuf 18(6):795–801. https://doi.org/10.1007/s12541-017-0095-3
Balaji H, Shaikh S, Jadhav S (2022) A review of design and control of automated guided vehicle systems. J Mech Civ Eng 171(1):29–35 (ISSN: 2278-1684)
Chang K, Chang A, Kuo C (2014) A simulation-based framework for multi-objective vehicle fl eet sizing of automated material handling systems: an empirical study. J Simul 8(4):271–280. https://doi.org/10.1057/jos.2014.6
Chawla VK, Chanda AK, Angra S (2018) Automatic guided vehicles fleet size optimization for flexible manufacturing system by grey wolf optimization algorithm. Manag Sci Lett 8(2):79–90. https://doi.org/10.5267/j.msl.2017.12.005
Chen JC, Chen TL, Teng YC (2020) A simulation and control framework for AGV based transport systems. Simul Model Pra and Theo 13(18):2–19. https://doi.org/10.3390/en13184948
Cheong HW, Lee H (2018) Concept design of AGV (automated guided vehicle) based on image detection and positioning. Procedia Comput Sci 139:104–107. https://doi.org/10.1016/j.procs.2018.10.224
Choobineh FF, Asef-Vaziri A, Huang X (2012) Fleet sizing of automated guided vehicles: a linear programming approach based on closed queuing networks. Int J Prod Res 50(12):3222–3235. https://doi.org/10.1080/00207543.2011.562560
De Ryck M, Versteyhe M, Shariatmadar K (2020a) Resource management in decentralized industrial Automated Guided Vehicle systems. J Manuf Syst 54:204–214. https://doi.org/10.1016/j.jmsy.2019.11.003
De Ryck M, Versteyhe M, Debrouwere F (2020b) Automated guided vehicle systems, state-of-the-art control algorithms and techniques. J Manuf Syst 54:152–173. https://doi.org/10.1016/j.jmsy.2019.12.002
Dehnavi-Arani S, Saidi-Mehrabad M, Ghezavati V (2019) An integrated model of cell formation and scheduling problem in a cellular manufacturing system considering automated guided vehicles’ movements. Int J Oper Res 34(4):542–561. https://doi.org/10.1504/IJOR.2019.099108
Dehnavi-Arani S, Sadegheih A, Zare Mehrjerdi Y, Honarvar M (2020) A new bi-objective integrated dynamic cell formation and AGVs’ dwell point location problem on the inter-cell unidirectional single loop. Soft Comput 24(21):16021–16042. https://doi.org/10.1007/s00500-020-04921-9
Fazlollahtabar H, Naini SGJ (2013) Adapted Markovian model to control reliability assessment in multiple AGV manufacturing system. Sci Iran 20(6):2224–2237
Fazlollahtabar H, Saidi-Mehrabad M (2013) Optimising a multi-objective reliability assessment in multiple AGV manufacturing system. Int J Serv Oper Manag 16(3):352–372. https://doi.org/10.1504/IJSOM.2013.056768
Fernandes J, Reis J, Melão N, Teixeira L, Amorim M (2021) The role of industry 4.0 and bpmn in the arise of condition-based and predictive maintenance: a case study in the automotive industry. Appl Sci. https://doi.org/10.3390/app11083438
Fransen KJC, van Eekelen JAWM, Pogromsky A, Boon MAA, Adan IJBF (2020) A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems. Comput Oper Res 123:105046. https://doi.org/10.1016/j.cor.2020.105046
Fu J, Zhang J, Ding G, Qin S, Jiang H (2021) Determination of vehicle requirements of AGV system based on discrete event simulation and response surface methodology. Proc Inst Mech Eng Part B: J Eng Manuf 235(9):1425–1436
Gu G, Hong Z, Luo D (2020) A data-driven intelligent algorithm for dynamic path design of automated-guided vehicle systems. IEEE Explore 8:202312–202353. https://doi.org/10.1109/IMCEC46724.2019.8983941
Hafidz M, System AMA (2011) Combinatorial auction method for decentralized task assignment of multiple- loading capacity AGV based on intelligent agent architecture, pp 207–211. https://doi.org/10.1109/IBICA.2011.56
Hafidz M, Member S, Yahaya SH (2013) Intelligent combinatorial auctions of decentralized task assignment for AGV with multiple loading capacity, pp 371–379. https://doi.org/10.1002/tee.21868
Hu H, Jia X, Liu K, Sun B (2021) Self-adaptive traffic control model with behavior trees and reinforcement learning for AGV in Industry 4.0. IEEE Trans Ind Informat. https://doi.org/10.1109/TII.2021.3059676
Huang S, Brown C, Hu G (2017) Shop floor AGV assignment optimization with uncertain request arrival. In: 67th annu. confer. expo inst. ind. eng., pp 1115–1120
Koo PH, Jang J, Suh J (2004) Estimation of part waiting time and fleet sizing in AGV systems. Int J Flex Manuf Syst 16(3):211–228. https://doi.org/10.1007/s10696-005-1008-9
Kriegel J, Rissbacher C, Reckwitz L, Tuttle- L, Kriegel J (2021) The requirements and applications of autonomous mobile robotics (AMR) in hospitals from the perspective of nursing officers hospitals from the perspective of nursing o ffi cers. Int J Healthc Manag. https://doi.org/10.1080/20479700.2020.1870353
Le-Anh T, De Koster MBM (2006) Design and methodology of automated guided vehicle—a review. Eur J Oper Res 171(1):1–23. https://doi.org/10.1016/j.ejor.2005.01.036
Lim JK, Lim JM, Yoshimoto K, Kim KH, Takahashi T (2003) Designing guide-path networks for automated guided vehicle system by using the Q-learning technique. Comput Ind Eng 44(1):1–17. https://doi.org/10.1016/S0360-8352(02)00128-6
Lin PT, Liao CA, Liang SH (2021) Probabilistic indoor positioning and navigation (PIPN) of autonomous ground vehicle (AGV) based on wireless measurements. IEEE Access. https://doi.org/10.1109/ACCESS.2021.3057415
Liu CI, Ioannou PA (2002) A Petri net based approach for AGV dispatch scheduling and fleet size determination, vol 15, no 1. IFAC
Lopez J, Zalama E, Gomez J (2022) Meta-model based simulation optimization for automated guided vehicle system under different charging mechanisms. Simul Model Pract Theory 116(1):1–10. https://doi.org/10.1016/j.simpat.2021.102430
Lu KV, Moreira AP (2016) Integrated tasks assignment and routing for the estimation of the optimal number of AGVS, pp 719–736. https://doi.org/10.1007/s00170-015-7343-4
Mahaleh MBB, Mirroshandel SA (2018) Harmony search path detection for vision based automated guided vehicle. Rob Auton Syst 107:156–166. https://doi.org/10.1016/j.robot.2018.06.008
Mihai S, Davis W, Hung DV, Trestian R, Karamanoglu M, Barn B, Prasad RV, Venkataraman H, Nguyen HX (2021) A digital twin framework for predictive maintenance in industry 4.0
Mohamad NR, Fauadi MH, Noor AZ (2018) Optimization of material transportation assignment for automated guided vehicle (AGV) system. Int J Eng Technol 7(320):334. https://doi.org/10.14419/ijet.v7i3.20.19269
Muller T (1983) Automated guided vehicles, IFS (Publications), University of California, USA
Nishi T, Akiyama S, Higashi T, Kumagai K (2020) Cell-based local search heuristics for guide path design of automated guided vehicle systems with dynamic multicommodity flow. IEEE Trans Autom Sci Eng 17(2):966–980. https://doi.org/10.1109/TASE.2019.2952920
Oyekanlu EA et al (2020) A review of recent advances in automated guided vehicle technologies: integration challenges and research areas for 5G-based smart manufacturing applications. IEEE Access 8:202312–202353. https://doi.org/10.1109/access.2020.3035729
Pjevcevic D, Nikolic M, Vidic N, Vukadinovic K (2017) Data envelopment analysis of AGV fleet sizing at a port container terminal. Int J Prod Res 55(14):4021–4034. https://doi.org/10.1080/00207543.2016.1241445
Qiuyun T, Hongyan S, Hengwei G, Ping W (2021) Improved particle swarm optimization algorithm for AGV path planning. IEEE Access 9:33522–33531. https://doi.org/10.1109/ACCESS.2021.3061288
Sabattini L, Digani V, Secchi C, Fantuzzi C (2017) Optimized simultaneous conflict-free task assignment and path planning for multi-AGV systems. IEEE Int Confer Intell Robot Syst 2017:1083–1088. https://doi.org/10.1109/IROS.2017.8202278
Saidi-Mehrabad M, Dehnavi-Arani S, Evazabadian F, Mahmoodian V (2015) An ant colony algorithm (ACA) for solving the new integrated model of job shop scheduling and conflict-free routing of AGVs. Comput Ind Eng 86:2–13. https://doi.org/10.1016/j.cie.2015.01.003
Shneor R, Edan Y, Paz E, Naor N, Berman S (2006) Fuzzy dispatching of automated guided vehicles. In: 2006 IIE annu. conf. exhib., no. Koff 1987
Suparjon S (2022) Evaluation of layout design, operation and maintenance of multi automated systems guided vehicles (AGV): a review. J Mech Eng Tech Appl 3(1):1–7 (ISSN: 2722-3213)
Tavana M, Fazlollahtabar H, Hassanzadeh R (2014) A bi-objective stochastic programming model for optimising automated material handling systems with reliability considerations, pp 37–41. https://doi.org/10.1080/00207543.2014.887232
Tran LV, Huynh BH, Akhtar H (2019) Ant colony optimization algorithm for Maintenance, Repair and Overhaul scheduling optimization in the context of Industrie 4,0. Appl Sci. https://doi.org/10.3390/app9224815
Vale A, Ventura R, Lopes P, Ribeiro I (2017) Assessment of navigation technologies for automated guided vehicle in nuclear fusion facilities. Rob Auton Syst 97:153–170. https://doi.org/10.1016/j.robot.2017.08.006
Valmiki P, Simha Reddy A, Panchakarla G, Kumar K, Purohit R, Suhane A (2018) A study on simulation methods for AGV fleet size stimation in a flexible manufacturing system. Mater Today Proc 5(2):3994–3999. https://doi.org/10.1016/j.matpr.2017.11.658
Vis IF (2006) Survey of research in the design and control of automated guided vehicle systems. Eur J Oper Res 170(3):677–709. https://doi.org/10.1016/j.ejor.2004.09.020
Wang F, Zhang Y, Su Z (2019) A novel scheduling method for automated guided vehicles in workshop environments. Int J Adv Robot Syst 16(3):1–13. https://doi.org/10.1177/1729881419844152
Wang H et al (2021) A novel multi-objective optimization algorithm for the integrated scheduling of flexible job shops considering preventive maintenance activities and transportation processes. Soft Comput 25(4):2863–2889
Weyns D, Boucké N, Holvoet T (2006) Gradient field-based task assignment in an AGV transportation system. In: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems, pp 842–849
Yalaoui A, Chaabi K, Yalaoui F, Yalaoui A, Chaabi K, Yalaoui F (2014) production systems Integrated production planning and preventive maintenance in deteriorating production systems. Inf Sci (NY). https://doi.org/10.1016/j.ins.2014.03.097
Yan R, Jackson LM, Dunnett SJ (2017) Automated guided vehicle mission reliability modelling using a combined fault tree and Petri net approach. Int J Adv Manuf Technol 92(5–8):1825–1837. https://doi.org/10.1007/s00170-017-0175-7
Yan R, Dunnett SJ, Jackson LM (2018a) Novel methodology for optimising the design, operation and maintenance of a multi-AGV system. Reliab Eng Syst Saf 178:130–139. https://doi.org/10.1016/j.ress.2018.06.003
Yan RD, Dunnett SJ, Jackson LM (2018b) Optimising the maintenance strategy for a multi-AGV system using genetic algorithms. In: Saf. reliab.—safe soc. a chang. world—proc. 28th int. eur. saf. reliab. conf. ESREL, pp 547–554. https://doi.org/10.1201/9781351174664-67
Yifei T, Junruo C, Meihong L, Xianxi L, Yali F (2010) An estimate and simulation approach to determining the automated guided vehicle fleet size in FMS. In: Proc.—2010 3rd IEEE int. conf. comput. sci. inf. technol. ICCSIT 2010, vol 9, pp 432–435. https://doi.org/10.1109/ICCSIT.2010.5565147
Yu NN, Li TK, Wang BL, Yuan SP, Wang Y (2021) Reliability oriented multi-AGVs online scheduling and path planning problem of automated sorting warehouse system. IOP Confer Ser Mater Sci Eng. https://doi.org/10.1088/1757-899X/1043/2/022035
Funding
The authors did not receive support from any organization for the submitted work.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Saeed Dehnavi-Arani and Aliakbar Hasani.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Ethical approval
The authors confirm all the ethical approvals and adhere to them.
Informed consent
This article is not related to human issues, and therefore, this case is not required.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Dehnavi-Arani, S., Hasani, A. An integrated automated guided vehicle design problem and preventive maintenance planning. Soft Comput 27, 15873–15892 (2023). https://doi.org/10.1007/s00500-023-08838-x
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-023-08838-x