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Design of the CNC Router Structure for Machining Wood Materials Using Reliability-Based Design Optimization Method

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Recent Advances in Manufacturing Engineering and Processes (ICMEP 2021)

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Abstract

Reliability-based design optimization (RBDO) plays an important role in optimal design because this optimal design method is achieved taking into account uncertainty and is very reliable. This paper applies the RBDO approach to analyze and design the CNC router structure for machining wood materials. With the desired reliability R*, the inverse reliability analysis method is utilized to transform the RBDO problem into a deterministic optimization problem. Monte Carlo simulation (MCS) is utilized to analyze the reliability of the machine structure after optimal design in accordance with the stiffness and strength criteria. The reliability analysis results, according to the MCS method, are compared with the desired reliability R* of the body structure. The obtained findings highlighted that body structure after optimized design according to the RDBO method is satisfactory.

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References

  • Beck, A.T., de Santana Gomes, W.J.: A comparison of deterministic, reliability-based and risk-based structural optimization under uncertainty. Probabilistic Eng. Mech. 28, 18–29 (2012)

    Article  Google Scholar 

  • Van Thuy, T., Nguyen, H.L.: Investigation on influence of cutting parameters on spindle vibration of CNC wood milling machine. MATEC Web Conf. 213, 01007 (2018)

    Article  Google Scholar 

  • Chiralaksanakul, A., Mahadevan, S.: First-order approximation methods in reliability-based design optimization (2005)

    Google Scholar 

  • Royset, J., Kiureghian, A.D., Polak, E.: Reliability-based optimal design of series structural systems. J. Eng. Mech. 127, 607–614 (2001)

    Google Scholar 

  • Youn, B.D., Choi, K.K.: An investigation of nonlinearity of reliability-based design optimization approaches. J. Mech. Des. 126, 403–411 (2004a)

    Article  Google Scholar 

  • Tu, J., Choi, K.K., Park, Y.H.: Design potential method for robust system parameter design. AIAA J. 39, 667–677 (2001)

    Article  Google Scholar 

  • Youn, B.D., Choi, K.K., Park, Y.H.: Hybrid analysis method for reliability-based design optimization. J. Mech. Des. 125, 221–232 (2003)

    Article  Google Scholar 

  • Tu, J., Choi, K.K., Park, Y.H.: A new study on reliability-based design optimization (1999)

    Google Scholar 

  • Cheng, Q., Zhao, H., Zhao, Y., Sun, B., Gu, P.: Machining accuracy reliability analysis of multi-axis machine tool based on Monte Carlo simulation. J. Intell. Manuf. 29, 191–209 (2018)

    Article  Google Scholar 

  • Youn, B.D., Choi, K.K.: A new response surface methodology for reliability-based design optimization. Comput. Struct. 82, 241–256 (2004b)

    Article  Google Scholar 

  • Enevoldsen, I., Sørensen, J.D.: Reliability-based optimization in structural engineering. Struct. Saf. 15, 169–196 (1994)

    Article  Google Scholar 

  • Padmanabhan, D., Agarwal, H., Renaud, J.E., Batill, S.M.: A study using Monte Carlo simulation for failure probability calculation in reliability-based optimization. Optim. Eng. 7, 297–316 (2006)

    Article  MATH  Google Scholar 

  • Loc, N.H., Van Thuy, T., Trung, P.Q.: Reliability-based analysis of machine structures using second-order reliability method. J. Adv. Mech. Des. Syst. Manuf., 13, JAMDSM0063-JAMDSM0063 (2019)

    Google Scholar 

  • Nguyen, H.L.: Reliability based Design and Analysis of Mechanical Systems, National University publisher HCMC, Viet Nam (2015)

    Google Scholar 

  • Wang, G., Ma, Z.: Hybrid particle swarm optimization for first-order reliability method. Comput. Geotech. 81, 49–58 (2017)

    Article  Google Scholar 

  • Nguyen, H.L., Tran, V.T.: Applying FCCCD response surface method in studying the cutting power of wood materials. Solid State Phenom. 329, 25–31 (2022)

    Article  Google Scholar 

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Acknowledgements

We acknowledge Ho Chi Minh City University of Technology (HCMUT), VNU-HCM for supporting this study.

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Correspondence to Huu Loc Nguyen .

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Nguyen, H.L., Tran, V.T. (2023). Design of the CNC Router Structure for Machining Wood Materials Using Reliability-Based Design Optimization Method. In: Agarwal, R.K. (eds) Recent Advances in Manufacturing Engineering and Processes. ICMEP 2021. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-19-6841-9_3

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  • DOI: https://doi.org/10.1007/978-981-19-6841-9_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-6840-2

  • Online ISBN: 978-981-19-6841-9

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