PSI - Issue 33

Nassima Naboulsi et al. / Procedia Structural Integrity 33 (2021) 989–995 Nassima Naboulsi et al. / Structural Integrity Procedia 00 (2019) 000–000

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Fig. 7 illustrates the simulation of the response curve for a temperature set point of 170°C after adjusting the parameters Kp, Ki, Kd of the graphical corrector. As shown in Table 3 the heating system had a response time or rise time of 2.72 minutes, which the temperature stabilizes and reaches the set point value after 4.13 minutes and with a minimum overshoot of 1.95%. For these results, the system must reach the maximum temperature and must stabilize as quickly as possible to produce reliable and conformable filament in the shortest possible time.

Table 3. Control parameters of the heating system of the extruder (PID Controller). PID Parameters PID controller Rise Time 2,72 Settling Time 4,13 Overshoot 1,95

4. Conclusion This paper aims to adjust the temperature of the extruder heating collars. For this purpose, during the studied heating period, first we identified the dynamics of the system in the form of a transfer function, then we regulated the parameters of the PID temperature controller using SIMULINK software to have a better thermal comfort condition in the extruder. The simulation results verified the remarkable accuracy of the proposed method to control the heating system. The goal of this study is to ensure the integrity and conformity of the filaments in order to have experimental samples to study the behavior and damage of the insulating part of high voltage electrical cables. References Zhong, S., & Pearce, J. M. (2018). Tightening the loop on the circular economy: Coupled distributed recycling and manufacturing with recyclebot and RepRap 3-D printing. Resources, Conservation and Recycling, 128(September 2017), 48–58. https://doi.org/10.1016/j.resconrec.2017.09.023 Mwema, F. M., & Akinlabi, E. T. (2020). Basics of Fused Deposition Modelling (FDM). SpringerBriefs in Applied Sciences and Technology, 1– 15. https://doi.org/10.1007/978-3-030-48259-6_1 Carneiro, O. S., Silva, A. F., & Gomes, R. (2015). Fused deposition modeling with polypropylene. Materials and Design, 83, 768–776. https://doi.org/10.1016/j.matdes.2015.06.053 Nassar, M. A., Elfarahaty, M., Ibrahim, S., & Hassan, Y. (2019). Design of 3D filament extruder for Fused Deposition Modeling (FDM) additive manufacturing. International Design Journal, 9(4), 55–62. Nithya Priya, S., Naveen Kumar, S., Prem Kumar, S., & Pradeep, K. K. (2021). Design and fabrication of filament extruder with spooler. Materials Today: Proceedings, xxxx, 20–22. https://doi.org/10.1016/j.matpr.2021.03.103 Ang, K. H., Chong, G., & Li, Y. (2005). PID control system analysis, design, and technology. IEEE Transactions on Control Systems Technology, 13(4), 559–576. https://doi.org/10.1109/TCST.2005.847331 Ribeiro, J. M. S., Santos, M. F., Carmo, M. J., & Silva, M. F. (2017). Comparison of PID controller tuning methods: Analytical/classical techniques versus optimization algorithms. 2017 18th International Carpathian Control Conference, ICCC 2017, 533–538. https://doi.org/10.1109/CarpathianCC.2017.7970458 Septiani, N. I., Bayusari, I., Caroline, C., Haiyunnisa, T., & Suprapto, B. Y. (2017). Optimization of PID control parameters with genetic algorithm plus fuzzy logic in stirred tank heater temperature control process. ICECOS 2017 - Proceeding of 2017 International Conference on Electrical Engineering and Computer Science: Sustaining the Cultural Heritage Toward the Smart Environment for Better Future, 61–66. https://doi.org/10.1109/ICECOS.2017.8167167 Dehghani, A., & Khodadadi, H. (2017). Designing a neuro-fuzzy PID controller based on smith predictor for heating system. International Conference on Control, Automation and Systems, 2017-Octob(Iccas), 15–20. https://doi.org/10.23919/ICCAS.2017.8204416 Oo, H. L., Ye, K. Z., & Linn, Y. H. (2018). Modeling and Controlling of Temperature in 3D Printer ( FDM ). 1738–1742.