Home / Current Issue / Paper 1708638
Systematic Review of Non-Destructive Testing Methods for Predictive Failure Analysis in Mechanical Systems
Subject area: Science,Engineering and Technology · Area of research: Mechanical Engineering
Abstract
Predictive failure analysis in mechanical systems is a crucial aspect of modern engineering maintenance and reliability management. Non-Destructive Testing (NDT) methods have emerged as essential tools for detecting material defects, structural anomalies, and potential failures without compromising the integrity of components. This systematic review evaluates the efficacy, limitations, and application domains of various NDT techniques?including ultrasonic testing (UT), magnetic particle testing (MT), radiographic testing (RT), eddy current testing (ECT), acoustic emission (AE), thermographic testing (TT), and visual inspection (VI)?in predictive failure analysis. The study follows the PRISMA methodology, employing a comprehensive literature search from databases such as Scopus, Web of Science, and IEEE Xplore from 2013 to 2020. A total of 79 peer-reviewed articles were selected based on relevance, citation quality, and methodological rigor. The findings highlight that ultrasonic testing and acoustic emission methods are highly effective in early crack detection and fatigue monitoring, especially in aerospace and pressure vessel applications. Radiographic and thermographic techniques excel in detecting internal voids and delamination in composite materials. Magnetic particle and eddy current testing are particularly suitable for surface and near-surface flaws in ferromagnetic and conductive materials, respectively. Visual inspection remains widely used due to its simplicity, though it often lacks the precision of other methods. Integrated approaches that combine multiple NDT techniques with artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being adopted to enhance diagnostic accuracy and predictive capabilities. Despite their effectiveness, challenges such as operator dependency, high equipment costs, and limitations in defect quantification remain prevalent. The review recommends a hybrid framework that leverages sensor fusion, digital twins, and real-time data analytics for robust predictive maintenance. Furthermore, the review calls for the standardization of data interpretation protocols and the adoption of automated systems to minimize human error. This systematic review contributes to the growing body of knowledge aimed at improving mechanical system reliability, minimizing downtime, and optimizing lifecycle costs. It provides a foundation for further research into adaptive, intelligent NDT systems for Industry 4.0 environments, where continuous monitoring and predictive analytics are essential.
Keywords
Non-Destructive Testing, Predictive Failure Analysis, Mechanical Systems, PRISMA Review, Ultrasonic Testing, Acoustic Emission, Thermographic Testing, AI-Driven NDT
References
[1] Abdelkhalek, S. and Zayed, T. (2021). Performance assessment model of non-destructive technologies in inspecting concrete bridge decks. Structure and Infrastructure Engineering, 19(2), 216-237. https://doi.org/10.1080/15732479.2021.1937234
[2] Ameel, T. A., Papautsky, I., Warrington, R. O., Wegeng, R. S., & Drost, M. K. (2000). Miniaturization technologies for advanced energy conversion and transfer systems. Journal of Propulsion and Power, 16(4), 577-582.
[3] Asif, M., Khan, M. A., Khan, S. Z., Choudhry, R. S., & Khan, K. A. (2018). Identification of an effective nondestructive technique for bond defect determination in laminate composites—A technical review. Journal of Composite Materials, 52(26), 3589-3599.
[4] Barricelli, B., Casiraghi, E., & Fogli, D. (2019). A survey on digital twin: definitions, characteristics, applications, and design implications. Ieee Access, 7, 167653-167671. https://doi.org/10.1109/access.2019.2953499
[5] Bertocci, F., Grandoni, A., & Djuric-Rissner, T. (2019). Scanning acoustic microscopy (sam): a robust method for defect detection during the manufacturing process of ultrasound probes for medical imaging. Sensors, 19(22), 4868. https://doi.org/10.3390/s19224868
[6] Bertovic, M. (2015). Human factors in non-destructive testing (NDT): risks and challenges of mechanised NDT. Technische Universitaet Berlin (Germany).
[7] Bodnar, J., Nicolas, J., Candoré, J., & Detalle, V. (2012). Non-destructive testing by infrared thermography under random excitation and arma analysis. International Journal of Thermophysics, 33(10-11), 2011-2015. https://doi.org/10.1007/s10765-012-1265-2
[8] Bolborea, B., Dan, S., Matei, C., Gruin, A., Baeră, C., & Perianu, I. (2021). Estimating the concrete compressive strength by using the concrete ultrasonic pulse velocity and moduli of elasticity. Advanced Materials Research, 1164, 77-86. https://doi.org/10.4028/www.scientific.net/amr.1164.77
[9] Brown, M., Wright, D., M’Saoubi, R., McGourlay, J., Wallis, M., Mantle, A., ... & Ghadbeigi, H. (2018). Destructive and non-destructive testing methods for characterization and detection of machining-induced white layer: A review paper. CIRP Journal of Manufacturing Science and Technology, 23, 39-53.
[10] Cai, S. Q., Chen, Y. C., & Bhunia, A. (2016). Design, development and tests of a compact thermofluid system. Applied Thermal Engineering, 102, 1320-1327.
[11] Chaki, S. and Krawczak, P. (2022). Non-destructive health monitoring of structural polymer composites: trends and perspectives in the digital era. Materials, 15(21), 7838. https://doi.org/10.3390/ma15217838
[12] Civera, M. and Surace, C. (2022). Non-destructive techniques for the condition and structural health monitoring of wind turbines: a literature review of the last 20 years. Sensors, 22(4), 1627. https://doi.org/10.3390/s22041627
[13] Demčenko, A., Visser, H., & Akkerman, R. (2016). Ultrasonic measurements of undamaged concrete layer thickness in a deteriorated concrete structure. NDT & E International, 77, 63-72. https://doi.org/10.1016/j.ndteint.2015.09.005
[14] Dixit, T., & Ghosh, I. (2015). Review of micro-and mini-channel heat sinks and heat exchangers for single phase fluids. Renewable and Sustainable Energy Reviews, 41, 1298-1311.
[15] Dong, C., Li, L., Yan, J., Zhang, Z., Pan, H., & Çatbaş, F. (2021). Pixel-level fatigue crack segmentation in large-scale images of steel structures using an encoder–decoder network. Sensors, 21(12), 4135. https://doi.org/10.3390/s21124135
[16] Drobiec, Ł., Jasiński, R., & Mazur, W. (2019). Accuracy of eddy-current and radar methods used to reinforcement detection.. https://doi.org/10.20944/preprints201901.0014.v2
[17] Duchene, P., Chaki, S., Ayadi, A., & Krawczak, P. (2018). A review of non-destructive techniques used for mechanical damage assessment in polymer composites. Journal of materials science, 53(11), 7915-7938.
[18] Fan, Y., & Luo, L. (2008). Recent applications of advances in microchannel heat exchangers and multi-scale design optimization. Heat Transfer Engineering, 29(5), 461-474.
[19] Gholizadeh, S. (2016). A review of non-destructive testing methods of composite materials. Procedia structural integrity, 1, 50-57.
[20] Gisario, A., Kazarian, M., Martina, F., & Mehrpouya, M. (2019). Metal additive manufacturing in the commercial aviation industry: A review. Journal of Manufacturing Systems, 53, 124-149.
[21] Grzyb, K., Drobiec, Ł., Blazy, J., & Zając, J. (2022). The use of ndt diagnostic methods and calculations in assessing the masonry tower crowned with the steel dome. Materials, 15(20), 7196. https://doi.org/10.3390/ma15207196
[22] Haertel, J. H., Engelbrecht, K., Lazarov, B. S., & Sigmund, O. (2018). Topology optimization of a pseudo 3D thermofluid heat sink model. International Journal of Heat and Mass Transfer, 121, 1073-1088.
[23] Helal, J., Sofi, M., & Mendis, P. (2015). Non-destructive testing of concrete: a review of methods. Electronic Journal of Structural Engineering, 14(1), 97-105. https://doi.org/10.56748/ejse.141931
[24] Hendricks, T. J. (2008, January). Microtechnology: A Key to System Miniaturization in Advanced Energy Recovery and Conversion Systems. In Energy Sustainability (Vol. 43208, pp. 153-163).
[25] Hon, K. K. B. (2005). Performance and evaluation of manufacturing systems. CIRP annals, 54(2), 139-154.
[26] Jalili, M., Mousavi, S., & Pirayeshfar, A. (2014). Flexural free vibration as a non-destructive test for evaluation of viscoelastic properties of polymeric composites in bending direction. Iranian Polymer Journal, 23(5), 327-333. https://doi.org/10.1007/s13726-014-0227-x
[27] Japar, W. M. A. A., Sidik, N. A. C., Saidur, R., Asako, Y., & Nurul Akmal Yusof, S. (2020). A review of passive methods in microchannel heat sink application through advanced geometric structure and nanofluids: Current advancements and challenges. Nanotechnology Reviews, 9(1), 1192-1216.
[28] Jeong, D., Baek, M., Lim, T., Kim, Y., Kim, S., Lee, Y., … & Lee, I. (2022). Digital twin: technology evolution stages and implementation layers with technology elements. Ieee Access, 10, 52609-52620. https://doi.org/10.1109/access.2022.3174220
[29] Joshi, Y., & Wei, X. (2005). Keynote Lecture: Micro and Meso Scale Compact Heat Exchangers in Electronics Thermal Management–Review.
[30] Jung, S., Park, J., Kang, T., & Ahn, K. (2019). Design optimization for a microfluidic crossflow filtration system incorporating a micromixer. Micromachines, 10(12), 836. https://doi.org/10.3390/mi10120836
[31] Kapteyn, M., Knežević, D., Huynh, D., Tran, M., & Willcox, K. (2020). Data‐driven physics‐based digital twins via a library of component‐based reduced‐order models. International Journal for Numerical Methods in Engineering, 123(13), 2986-3003. https://doi.org/10.1002/nme.6423
[32] Katunin, A. (2017). A concept of thermographic method for non-destructive testing of polymeric composite structures using self-heating effect. Sensors, 18(1), 74. https://doi.org/10.3390/s18010074
[33] Katunin, A. and Dragan, K. (2022). Qualitative to quantitative non-destructive evaluation: a concept for d-sight inspections of aircraft structures. Applied Mechanics and Materials, 909, 69-74. https://doi.org/10.4028/p-d8r1x7
[34] Katunin, A., Wronkowicz, A., & Dragan, K. (2020). Impact damage evaluation in composite structures based on fusion of results of ultrasonic testing and x-ray computed tomography. Sensors, 20(7), 1867. https://doi.org/10.3390/s20071867
[35] Khaira, A., Dwivedi, R., & Jain, S. (2020). Structural health monitoring (shm) of machine using a combination of non-destructive testing for heavy manufacturing industry. E3s Web of Conferences, 184, 01059. https://doi.org/10.1051/e3sconf/202018401059
[36] Khashan, S. and Furlani, E. (2011). Effects of particle–fluid coupling on particle transport and capture in a magnetophoretic microsystem. Microfluidics and Nanofluidics, 12(1-4), 565-580. https://doi.org/10.1007/s10404-011-0898-y
[37] Kloss, C., Goniva, C., Hager, A., Amberger, S., & Pirker, S. (2012). Models, algorithms and validation for opensource dem and cfd-dem. Progress in Computational Fluid Dynamics an International Journal, 12(2/3), 140. https://doi.org/10.1504/pcfd.2012.047457
[38] Koli, D. K., Agnihotri, G., & Purohit, R. (2015). Advanced aluminium matrix composites: the critical need of automotive and aerospace engineering fields. Materials Today: Proceedings, 2(4-5), 3032-3041.
[39] Kumar, S., & Mahto, D. G. (2013). Recent trends in industrial and other engineering applications of non destructive testing: a review. International Journal of Scientific & Engineering Research, 4(9).
[40] Kuśmierczak, S. and Majzner, T. (2017). Comprehensive approach to evaluation of degradation in chosen parts of energy equipment.. https://doi.org/10.22616/erdev2017.16.n134
[41] Laloya, E., Lucia, O., Sarnago, H., & Burdio, J. M. (2015). Heat management in power converters: From state of the art to future ultrahigh efficiency systems. IEEE transactions on Power Electronics, 31(11), 7896-7908.
[42] Lauritzen, P. N., Reichard, J., Ahmed, S., & Safa, M. (2019). Review of non-destructive testing methods for physical condition monitoring in the port industry. Journal of Construction Engineering, 2(2), 103-111.
[43] Li, B., Dobosz, K., Zhang, H., Schiffman, J., Saranteas, K., & Henson, M. (2019). Predicting the performance of pressure filtration processes by coupling computational fluid dynamics and discrete element methods. Chemical Engineering Science, 208, 115162. https://doi.org/10.1016/j.ces.2019.115162
[44] Li, P., Li, Y., Seem, J. E., Qiao, H., Li, X., & Winkler, J. (2014). Recent advances in dynamic modeling of HVAC equipment. Part 2: Modelica-based modeling. HVAC&R Research, 20(1), 150-161.
[45] Li, S., Zhang, H., Cheng, J., Li, X., Cai, W., Li, Z., & Li, F. (2019). A state-of-the-art overview on the developing trend of heat transfer enhancement by single-phase flow at micro scale. International Journal of Heat and Mass Transfer, 143, 118476.
[46] Lin, J. and Li, H. (2010). Applications of network integrated system with eddy current and ultrasonic testing. International Journal of Applied Electromagnetics and Mechanics, 33(3-4), 1309-1315. https://doi.org/10.3233/jae-2010-1255
[47] Liu, H., Wang, D., Leng, X., Zheng, D., Chen, F., Wong, K., … & Leung, T. (2020). State-of-the-art computational models of circle of willis with physiological applications: a review. Ieee Access, 8, 156261-156273. https://doi.org/10.1109/access.2020.3007737
[48] Liu, J., Zhao, T., Liu, K., Sun, B., & Bai, C. (2021). Optimization of structure parameters in a coal pyrolysis filtration system based on cfd and quadratic regression orthogonal combination and a genetic algorithm. Engineering Applications of Computational Fluid Mechanics, 15(1), 815-829. https://doi.org/10.1080/19942060.2021.1918258
[49] Ma, Q., Tian, G., Zeng, Y., Li, R., Song, H., Wang, Z., … & Zeng, K. (2021). Pipeline in-line inspection method, instrumentation and data management. Sensors, 21(11), 3862. https://doi.org/10.3390/s21113862
[50] Melesse, T., Pasquale, V., & Riemma, S. (2021). Digital twin models in industrial operations: state‐of‐the‐art and future research directions. Iet Collaborative Intelligent Manufacturing, 3(1), 37-47. https://doi.org/10.1049/cim2.12010
[51] Miracle, D. B. (2005). Metal matrix composites–from science to technological significance. Composites science and technology, 65(15-16), 2526-2540.
[52] Moir, I., & Seabridge, A. (2011). Aircraft Systems: Mechanical, electrical, and avionics subsystems integration. John Wiley & Sons.
[53] Moll, J., Kathol, J., Fritzen, C., Moix-Bonet, M., Rennoch, M., Koerdt, M., … & Bach, M. (2018). Open guided waves: online platform for ultrasonic guided wave measurements. Structural Health Monitoring, 18(5-6), 1903-1914. https://doi.org/10.1177/1475921718817169
[54] Muhammad, N. M. A., & Sidik, N. A. C. (2018). Utilization of Nanofluids in Minichannel for Heat Transfer and Fluid Flow Augmentation: A Concise Research Design. Journal of Advanced Research Design, 50(1), 18-29.
[55] Nahm, S., Kim, J., Park, J., Yu, K., Kim, D., Kim, A., … & Kim, D. (2004). Degradation evaluation of 2.25cr-1mo steel using electrical resistivity. Key Engineering Materials, 270-273, 1212-1217. https://doi.org/10.4028/www.scientific.net/kem.270-273.1212
[56] Najmon, J. C., Raeisi, S., & Tovar, A. (2019). Review of additive manufacturing technologies and applications in the aerospace industry. Additive manufacturing for the aerospace industry, 7-31.
[57] Ngo, T., Wang, Y., & Chiang, D. (2021). Applying artificial intelligence to improve on-site non-destructive concrete compressive strength tests. Crystals, 11(10), 1157. https://doi.org/10.3390/cryst11101157
[58] Noor, A. K., Venneri, S. L., Paul, D. B., & Hopkins, M. A. (2000). Structures technology for future aerospace systems. Computers & Structures, 74(5), 507-519.
[59] Odedeyi, P. B., Abou-El-Hossein, K., Oyekunle, F., & Adeleke, A. K. (2020). Effects of machining parameters on Tool wear progression in End milling of AISI 316. Progress in Canadian Mechanical Engineering, 3
[60] Ohadi, M. M., & Buckley, S. G. (2000). High temperature heat exchangers and microscale combustion systems: applications to thermal system miniaturization. In Thermal Sciences 2000. Proceedings of the International Thermal Science Seminar. Volume 1. Begel House Inc..
[61] Olisa, S., Khan, M., & Starr, A. (2021). Review of current guided wave ultrasonic testing (gwut) limitations and future directions. Sensors, 21(3), 811. https://doi.org/10.3390/s21030811
[62] Olisakwe, H. C., Tuleun, L. T., & Eloka-Eboka, A. C. (2011). Comparative study of Thevetia peruviana and Jatropha curcas seed oils as feedstock for Grease production. International Journal of Engineering Research and Applications, 1(3).
[63] Omar, T., & Nehdi, M. L. (2016). Mat-713: evaluation of ndt techniques for concrete bridge decks using fuzzy analytical hierarchy process.
[64] Omari, A., John, J., & Kichonge, B. (2020). Simulation and optimization of municipal solid waste combustion: a case study of a fixed bed incinerator. Journal of Engineering Research and Reports, 5-19. https://doi.org/10.9734/jerr/2020/v11i317060
[65] Ph Papaelias, M., Roberts, C., & Davis, C. L. (2008). A review on non-destructive evaluation of rails: State-of-the-art and future development. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and rapid transit, 222(4), 367-384.
[66] Pham, D., Sun, X., Tan, V., Chen, B., & Tay, T. (2011). Progressive failure analysis of scaled double-notched carbon/epoxy composite laminates. International Journal of Damage Mechanics, 21(8), 1154-1185. https://doi.org/10.1177/1056789511430415
[67] Piascik, B., Vickers, J., Lowry, D., Scotti, S., Stewart, J., & Calomino, A. (2012). Materials, structures, mechanical systems, and manufacturing roadmap. NASA TA, 12-2.
[68] Pirinu, A. and Panella, F. (2021). Fatigue damage monitoring of cfrp elements by thermographic procedure under bending loads. Key Engineering Materials, 873, 47-52. https://doi.org/10.4028/www.scientific.net/kem.873.47
[69] Pitarresi, G., Scalici, T., & Catalanotti, G. (2019). Infrared thermography assisted evaluation of static and fatigue mode ii fracture toughness in frp composites. Composite Structures, 226, 111220. https://doi.org/10.1016/j.compstruct.2019.111220
[70] Poole, A., Sutcliffe, M., Pierce, S., & Gachagan, A. (2022). Autonomous, digital-twin free path planning and deployment for robotic ndt: introducing lpas: locate, plan, approach, scan using low cost vision sensors. Applied Sciences, 12(10), 5288. https://doi.org/10.3390/app12105288
[71] Qian, F. and Yu, X. (2012). Numerical simulation to study the effect of the particle deposition morphology on the filtration efficiency of the fibrous media. Advanced Materials Research, 518-523, 1767-1770. https://doi.org/10.4028/www.scientific.net/amr.518-523.1767
[72] Qing, X., Kumar, A., Zhang, C., Gonzalez, I., Guo, G., & Chang, F. (2005). A hybrid piezoelectric/fiber optic diagnostic system for structural health monitoring. Smart Materials and Structures, 14(3), S98-S103. https://doi.org/10.1088/0964-1726/14/3/012
[73] Rao, R. V., Saroj, A., Ocloń, P., & Taler, J. (2020). Design optimization of heat exchangers with advanced optimization techniques: a review. Archives of computational methods in engineering, 27, 517-548.
[74] Riggio, M., Macchioni, N., & Riminesi, C. (2016). Structural health assessment of historical timber structures combining non-destructive techniques: the roof of giotto's bell tower in florence. Structural Control and Health Monitoring, 24(7), e1935. https://doi.org/10.1002/stc.1935
[75] Saha, S. K., Tiwari, M., Sundén, B., & Wu, Z. (2016). Advances in heat transfer enhancement (Vol. 4). Springer International Publishing.
[76] Shan, Z., Qin, S., Liu, Q., & Liu, F. (2012). Key manufacturing technology & equipment for energy saving and emissions reduction in mechanical equipment industry. International Journal of Precision Engineering and Manufacturing, 13, 1095-1100.
[77] Shrifan, N., Akbar, M., & Isa, N. (2019). Prospect of using artificial intelligence for microwave nondestructive testing technique: a review. Ieee Access, 7, 110628-110650. https://doi.org/10.1109/access.2019.2934143
[78] Siang, T., Akbar, M., Jawad, G., Yee, T., & Sazali, M. (2021). A past, present, and prospective review on microwave nondestructive evaluation of composite coatings. Coatings, 11(8), 913. https://doi.org/10.3390/coatings11080913
[79] Singh, J., Montesinos-Castellanos, A., & Nigam, K. D. P. (2019). Process intensification for compact and micro heat exchangers through innovative technologies: A review. Industrial & Engineering Chemistry Research, 58(31), 13819-13847.
[80] Šmelko, M., Draganová, K., Lipovský, P., Semrád, K., Blišťanová, M., & Kašper, P. (2020). Non-Destructive testing of aircraft structures using microwire-based tensile stress sensor. Applied Sciences, 10(22), 8218.
[81] Stafford, J., Grimes, R., & Newport, D. (2012). Development of compact thermal–fluid models at the electronic equipment level.
[82] Talouti, S., Benzerga, D., & Abdelkader, H. (2022). Numerical investigations of damage behaviour at the weld/base metal interface. International Journal of Engineering, 35(12), 2337-2343. https://doi.org/10.5829/ije.2022.35.12c.09
[83] Tang, G., Han, Y., Lau, B. L., Zhang, X., & Rhee, D. M. W. (2016). Development of a compact and efficient liquid cooling system with silicon microcooler for high-power microelectronic devices. IEEE Transactions on Components, Packaging and Manufacturing Technology, 6(5), 729-739.
[84] Tay, T., Liu, G., Tan, V., Sun, X., & Pham, D. (2008). Progressive failure analysis of composites. Journal of Composite Materials, 42(18), 1921-1966. https://doi.org/10.1177/0021998308093912
[85] Towsyfyan, H., Biguri, A., Boardman, R., & Blumensath, T. (2020). Successes and challenges in non-destructive testing of aircraft composite structures. Chinese Journal of Aeronautics, 33(3), 771-791.
[86] Umar, T., Yousaf, M., Akbar, M., Abbas, N., Hussain, Z., & Ansari, W. (2022). An experimental study on non-destructive evaluation of the mechanical characteristics of a sustainable concrete incorporating industrial waste. Materials, 15(20), 7346. https://doi.org/10.3390/ma15207346
[87] Volk, A., Ghia, U., & Stoltz, C. (2017). Effect of grid type and refinement method on cfd-dem solution trend with grid size. Powder Technology, 311, 137-146. https://doi.org/10.1016/j.powtec.2017.01.088
[88] Wang, B., Zhong, S., Lee, T. L., Fancey, K. S., & Mi, J. (2020). Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review. Advances in mechanical engineering, 12(4), 1687814020913761.
[89] Wang, B., Zhong, S., Lee, T. L., Fancey, K. S., & Mi, J. (2020). Non-destructive testing and evaluation of composite materials/structures: A state-of-the-art review. Advances in mechanical engineering, 12(4), 1687814020913761.
[90] Wang, B., Zhong, S., Lee, T., Fancey, K., & Mi, J. (2020). Non-destructive testing and evaluation of composite materials/structures: a state-of-the-art review. Advances in Mechanical Engineering, 12(4), 168781402091376. https://doi.org/10.1177/1687814020913761
[91] Williams, J. C., & Starke Jr, E. A. (2003). Progress in structural materials for aerospace systems. Acta materialia, 51(19), 5775-5799.
[92] Wronkowicz, A. (2018). A brief review on ndt&e methods for structural aircraft components. Fatigue of Aircraft Structures, 2018(10), 73-81. https://doi.org/10.2478/fas-2018-0007
[93] Wu, R., Zhang, H., Yang, R., Chen, W., & Chen, G. (2021). Nondestructive testing for corrosion evaluation of metal under coating. Journal of Sensors, 2021(1). https://doi.org/10.1155/2021/6640406
[94] Wu, S., Lin, Y., Hwang, K., Cheng, T., & Tung, K. (2018). High-efficiency hollow fiber arrangement design to enhance filtration performance by cfd simulation. Chemical Engineering and Processing - Process Intensification, 125, 87-96. https://doi.org/10.1016/j.cep.2018.01.003
[95] Xu, Y., Song, X., Sun, Z., Lu, G., Li, P., & Yu, J. (2015). Simulation and evaluation of the performance and feasibility of two‐stage industrial hydrocyclones for caso4 removal in potassium chloride production. The Canadian Journal of Chemical Engineering, 93(4), 736-746. https://doi.org/10.1002/cjce.22163
[96] Zeng, T., Wang, H., Yang, M., & Alexandersen, J. (2020). Topology optimization of heat sinks for instantaneous chip cooling using a transient pseudo-3D thermofluid model. International Journal of Heat and Mass Transfer, 154, 119681.
[97] Zhou, M., Alexandersen, J., Sigmund, O., & W. Pedersen, C. B. (2016). Industrial application of topology optimization for combined conductive and convective heat transfer problems. Structural and Multidisciplinary Optimization, 54, 1045-1060.
How to cite this paper
@article{1708638,
author = {Enoch Oluwadunmininu Ogunnowo, Musa Adekunle Adewoyin, Joyce Efekpogua Fiemotongha, Thompson Odion Igunma, Adeniyi K. Adeleke},
title = {Systematic Review of Non-Destructive Testing Methods for Predictive Failure Analysis in Mechanical Systems},
journal = {Iconic Research And Engineering Journals},
year = {2020},
volume = {4},
number = {4},
pages = {207-222},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708638.pdf},
abstract = {Predictive failure analysis in mechanical systems is a crucial aspect of modern engineering maintenance and reliability management. Non-Destructive Testing (NDT) methods have emerged as essential tools for detecting material defects, structural anomalies, and potential failures without compromising the integrity of components. This systematic review evaluates the efficacy, limitations, and application domains of various NDT techniques?including ultrasonic testing (UT), magnetic particle testing (MT), radiographic testing (RT), eddy current testing (ECT), acoustic emission (AE), thermographic testing (TT), and visual inspection (VI)?in predictive failure analysis. The study follows the PRISMA methodology, employing a comprehensive literature search from databases such as Scopus, Web of Science, and IEEE Xplore from 2013 to 2020. A total of 79 peer-reviewed articles were selected based on relevance, citation quality, and methodological rigor. The findings highlight that ultrasonic testing and acoustic emission methods are highly effective in early crack detection and fatigue monitoring, especially in aerospace and pressure vessel applications. Radiographic and thermographic techniques excel in detecting internal voids and delamination in composite materials. Magnetic particle and eddy current testing are particularly suitable for surface and near-surface flaws in ferromagnetic and conductive materials, respectively. Visual inspection remains widely used due to its simplicity, though it often lacks the precision of other methods. Integrated approaches that combine multiple NDT techniques with artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being adopted to enhance diagnostic accuracy and predictive capabilities. Despite their effectiveness, challenges such as operator dependency, high equipment costs, and limitations in defect quantification remain prevalent. The review recommends a hybrid framework that leverages sensor fusion, digital twins, and real-time data analytics for robust predictive maintenance. Furthermore, the review calls for the standardization of data interpretation protocols and the adoption of automated systems to minimize human error. This systematic review contributes to the growing body of knowledge aimed at improving mechanical system reliability, minimizing downtime, and optimizing lifecycle costs. It provides a foundation for further research into adaptive, intelligent NDT systems for Industry 4.0 environments, where continuous monitoring and predictive analytics are essential.},
keywords = {Non-Destructive Testing, Predictive Failure Analysis, Mechanical Systems, PRISMA Review, Ultrasonic Testing, Acoustic Emission, Thermographic Testing, AI-Driven NDT},
month = {October},
}