TOWARDS DIGITAL TWIN-DRIVEN PERFORMANCE EVALUATION METHODOLOGY OF FMS

Grzegorz BOCEWICZ; Robert WÓJCIK; Paweł SITEK; Zbigniew BANASZAK

doi:10.35784/acs-2022-17

Open full text

pdf

Published: Sep 30, 2022

DOI: https://doi.org/10.35784/acs-2022-17

DOI

https://doi.org/10.35784/acs-2022-17

Authors

Grzegorz BOCEWICZ

grzegorz.bocewicz@tu.koszalin.pl

Faculty of Electronics and Computer Science, Koszalin University of Technology

Robert WÓJCIK

robert.wojcik@pwr.edu.pl

Faculty of Information and Communication Technology, Wrocław University of Science and Technology,

Paweł SITEK

sitek@tu.kielce.pl

Department of Information Systems, Kielce University of Technology, Kielce

Zbigniew BANASZAK

zbigniew.banaszak@tu.koszalin.pl

Faculty of Electronics and Computer Science, Koszalin University of Technology

Abstract

The paper presents a method of automated modelling and performance evaluation of concurrent production flows carried out in Flexible Manufacturing Systems. The method allows for quick assessment of various variants of such systems, considering their structure and the organization of production flow of possible ways of their implementation. Its essence is the conditions imposed on the designed model, limiting the space of possible variants of the production flow only to deadlock-free variants. The practical usefulness of the model implemented in the proposed method illustrates the example, which describes the simultaneous assessment of alternative variants of the flexible machining module's structure and the planned multi-assortment production. The ability of the method to focus on feasible solutions offers attractive perspectives for guiding the Digital Twin-like scenario in situations caused by the need to change the production flow.

Keywords:

FMS, Petri Nets, Performance evaluation

References

Alexopoulos, K., Anagiannis, I., Nikolakis, N., & Chryssolouris, G. (2022). A quantitative approach to resilience in manufacturing systems. International Journal of Production Research, 60(13), 4342–4360. DOI: https://doi.org/10.1080/00207543.2021.2018519

Bakar, B. A., Henry, R. M., & Ali, M. (1991). An alternative approach in batch process control implementation using hierarchical Petri nets, World Scientific. Proc. of the International Conference on Computer Integrated Manufacturing (pp. 171–174).

Banaszak, Z. (1992). Synchronisation of robots in flexible assembly systems. Archiwum Budowy Maszyn, 39(1–2), 117–133.

Banaszak, Z., Skolud, B., & Zaremba, M. B. (2003). Computer-aided prototyping of production flows for virtual enterprise. Journal of Intelligent Manufacturing, 14, 83–106. DOI: https://doi.org/10.1023/A:1022291313614

Bocewicz, G., Wójcik, R., Witczak, M., & Banaszak, Z. (2022). Petri Net Approach to Automated Modelling and Performance Evaluation for Robotic Assembly Systems. 2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) (pp. 306–311). IEEE. https://doi.org/10.1109/MMAR55195.2022.9874291 DOI: https://doi.org/10.1109/MMAR55195.2022.9874291

Bujari, A., Calvio, A., Foschini, L., Sabbioni, A., & Corradi, A. (2021). A Digital Twin Decision Support System for the Urban Facility Management Process. Sensors, 21(24), 8460. https://doi.org/10.3390/s21248460 DOI: https://doi.org/10.3390/s21248460

Claes, D., & Tuyls, K. (2018). Multi robot collision avoidance in a shared workspace. Autonomous Robots, 42, 1749–1770. https://doi.org/10.1007/s10514-018-9726-5 DOI: https://doi.org/10.1007/s10514-018-9726-5

Coito, T., Faria, P., Martins, M. S. E., Firme, B., Vieira, S. M., Figueiredo, J., & Sousa, J. M. C. (2022). Digital Twin of a Flexible Manufacturing System for Solutions Preparation. Automation, 3(1), 153–175. https://doi.org/10.3390/automation3010008 DOI: https://doi.org/10.3390/automation3010008

David, J., Lobov, A., & Lanz, M. (2018). Leveraging Digital Twins for Assisted Learning of Flexible Manufacturing Systems. 2018 IEEE 16th International Conference on Industrial Informatics (INDIN) (pp. 529-535). IEEE. https://doi.org/10.1109/INDIN.2018.8472083 DOI: https://doi.org/10.1109/INDIN.2018.8472083

Hatono, I., Katoh, N., Yamagata, K., & Tamura, H. (1989). Modelling of FMS under uncertainty using stochastic Petri Nets. Proc. of the 3rd International Workshop on Petri nets and performance models (pp. 122–130).

He, Z., Zhang, R., Ran, N., & Gu, C. (2022). Path Planning of Multi-Type Robot Systems with Time Windows Based on Timed Colored Petri Nets. Applied Science, 12(14), 6878. https://doi.org/10.3390/app12146878 DOI: https://doi.org/10.3390/app12146878

Heiner, M. (1992). Petri net based software validation (prospects and limits), Technical report No. TR-92-022. International Computer Science Institute.

Janardhanan, M. N., Li, Z., Bocewicz, G., Banaszak, Z., & Nielsen, P. (2019). Metaheuristic Algorithms for balancing robotic assembly lines with sequence-dependent robot setup times. Applied Mathematical Modelling, 65, 256–270. DOI: https://doi.org/10.1016/j.apm.2018.08.016

Jensen, K. (1987). Computer tools for construction, modification and analysis of Petri nets. Lecture Notes on Computer Science (No. 255). Springer Verlag. DOI: https://doi.org/10.1007/3-540-17906-2_20

Jonsson, P. (2000). An empirical taxonomy of advanced manufacturing technology. International Journal of Operations & Production Management, 20(12), 1446–1474. DOI: https://doi.org/10.1108/01443570010353103

Laemmle, A., & Gust, S. (2019). Automatic layout generation of robotic production cells in a 3D manufacturing simulation environment. Procedia CIRP, 84, 316–321. DOI: https://doi.org/10.1016/j.procir.2019.04.207

Makris, S., Michalos, G., & Chryssolouris, G. (2012). Virtual Commissioning of an Assembly Cell with Cooperating Robots. Advances in Decision Sciences, 2012, 428060. https://doi.org/10.1155/2012/428060 DOI: https://doi.org/10.1155/2012/428060

Manu, G., Kumar, V. M., Nagesh, H., Jagadeesh, D., & Gowtham, M. B. (2018). Flexible Manufacturing Systems (FMS): A Review. International Journal of Mechanical and Production Engineering Research and Development, 8(2), 323–336. DOI: https://doi.org/10.24247/ijmperdapr201836

Neto, A. A., Carrijoa B. S., Brock, J. G. R, Deschamps, F., & Lima, E. P. (2021). Digital twin-driven decision support system for opportunistic preventive maintenance scheduling in manufacturing. Procedia Manufacturing, 55, 439–446. DOI: https://doi.org/10.1016/j.promfg.2021.10.060

Nielsen, L. D., Sung, I., & Nielsen, P. (2019). Convex Decomposition for a Coverage Path Planning for Autonomous Vehicles: Interior Extension of Edges. Sensors, 19(19), 4165. https://doi.org/10.3390/s19194165 DOI: https://doi.org/10.3390/s19194165

Nielsen, P., Michna, Z., & Do, N. A. D. (2014). An Empirical Investigation of Lead Time Distributions. Advances in Production Management Systems. Innovative and Knowledge-Based Production Management in a Global-Local World. APMS 2014. IFIP Advances in Information and Communication Technology (vol. 438). Springer. https://doi.org/10.1007/978-3-662-44739-0_53 DOI: https://doi.org/10.1007/978-3-662-44739-0_53

Patalas-Maliszewska, J., & Kłos, S. (2019). An Approach to Supporting the Selection of Maintenance Experts in the Context of Industry 4.0. Applied Sciences, 9(9), 1848. https://doi.org/10.3390/app9091848 DOI: https://doi.org/10.3390/app9091848

Rachamadugu, R., & Stecke, K. E. (1994). Classification and review of FMS scheduling procedures. Production Planning & Control, 5(1), 2–20. https://doi.org/10.1080/09537289408919468 DOI: https://doi.org/10.1080/09537289408919468

Recalde, L., Silva, M., Ezpeleta, J., & Teruel, E. (2022). Petri Nets and Manufacturing Systems: An ExamplesDriven Tour. ACPN 2003. Lecture Notes in Computer Science (vol. 3098). Springer. https://doi.org/10.1007/978-3-540-27755-2_21 DOI: https://doi.org/10.1007/978-3-540-27755-2_21

Reisig, W. (1982). Petri nets. Springer Verlag. Reutenauer, Ch. (1988). The mathematics of Petri nets. Englewood Cliffs.

Silva, E. B., Costa, M. G., Silva, M. F., & Pereira, F. H. (2012). Evaluation of Production Sequencing Rules in Job Shop and Flow Shop Environment through Computer Simulation. ICIEOM 2012 (no. 257).

Sliwa, M., & Patalas-Maliszewska, J. (2016). A Strategic Knowledge Map for the Research and Development Department in a Manufacturing Company. Foundations of Management, 8(1), 151–166. DOI: https://doi.org/10.1515/fman-2016-0012

Stączek, P., Pizoń, J., Danilczuk, W., & Gola, A. (2021). A digital twin approach for the improvement of an autonomous mobile robots (AMR's) operating environment – a case study. Sensors, 21(23), 7830. https://doi.org/10.3390/s21237830 DOI: https://doi.org/10.3390/s21237830

Świć, A., & Gola, A. (2013). Economic Analysis of Casing Parts Production in a Flexible Manufacturing System. Actual Problems of Economics, 141(3), 526–533.

Vaisi, B. (2022). A review of optimization models and applications in robotic manufacturing systems: Industry 4.0 and beyond. Decision Analytics Journal, 2, 100031. https://doi.org/10.1016/j.dajour.2022.100031 DOI: https://doi.org/10.1016/j.dajour.2022.100031

Van der Aalst, W. M. (1992). Timed coloured Petri nets and their application to logistics. Technische Universiteit Eindhoven. DOI: https://doi.org/10.1007/3-540-56863-8_61

Viswandham, N., & Narahari, Y. (1992). Performance modelling of automated manufacturing systems. Prentice-Hall.

Yang, B., & Hu, H. (2022). Maximally Permissive Deadlock and Livelock Avoidance for Automated Manufacturing Systems via Critical Distance. In IEEE Transactions on Automation Science and Engineering. IEEE. https://doi.org/10.1109/TASE.2021.3138169 DOI: https://doi.org/10.1109/TASE.2021.3138169

Zanchettin, A. M. (2021). Robust scheduling and dispatching rules for high-mix collaborative manufacturing systems. Flexible Services and Manufacturing Journal, 34, 293–316. https://doi.org/10.1007/s10696-021-09406-x DOI: https://doi.org/10.1007/s10696-021-09406-x

Zhang, F., Bai, J., & Yang, D. (2022). Digital twin data-driven proactive job-shop scheduling strategy towards asymmetric manufacturing execution decision. Scientific Reports, 12, 1546. https://doi.org/10.1038/s41598-022-05304-w DOI: https://doi.org/10.1038/s41598-022-05304-w

Zhou, K. Q., & Zain, A. M. (2016). Fuzzy Petri nets, and industrial applications: a review. Artificial Intelligence Review, 45(4), 405–446. https://doi.org/10.1007/s10462-015-9451-9 DOI: https://doi.org/10.1007/s10462-015-9451-9

BOCEWICZ, G., WÓJCIK, R., SITEK, P., & BANASZAK, Z. (2022). TOWARDS DIGITAL TWIN-DRIVEN PERFORMANCE EVALUATION METHODOLOGY OF FMS. Applied Computer Science, 18(3), 5–18. https://doi.org/10.35784/acs-2022-17

Article Sidebar

Main Article Content

DOI

Authors

Abstract

Keywords:

References

Article Details

License