Interrelationships Between Total Productive Maintenance, Jidoka and Economic Sustainability: Empirical Validation of an Integrated Conceptual Model
DOI:
https://doi.org/10.26439/ing.ind2025.n049.8063Keywords:
TPM, jidoka, manufacturing industries, manufacturing processes, lean manufacturing, sustainable development, structural equation modelingAbstract
This study develops and empirically validates an integrated conceptual model that investigates the causal relationships among Total Productive Maintenance (TPM), Jidoka, and economic sustainability (ECSU) within the manufacturing industry. Based on Resource and Capability Theory as well as Systems Theory, the model posits that TPM directly influences both jidoka and ECSU, while jidoka acts as a mediator in the relationship between TPM and ECSU. Utilizing structural equation modeling (SEM-PLS) and data collected from 357 surveys of the maquiladora industry in Ciudad Juárez, Mexico, the analysis confirms that TPM positively affects jidoka (β=,632, p<0,001) and ECSU (β=0,340, p<0,001). Furthermore, jidoka contributes significantly to ECSU (β=0,358, p<0,001) and mediates the effect of TPM on ECSU (β=0,226), resulting in an increased total effect of β=0,566. The researchers conducted graphical analyses that demonstrate nonlinear patterns in relationships. These findings underscore the synergies between TPM and jidoka, which work together to maximize sustainable economic benefits in lean manufacturing environments.
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References
Ahuja, I. P. S., & Khamba, J. S. (2008). Total productive maintenance implementation in a manufacturing organisation. International Journal of Productivity and Quality Management, 3(3), 360–381. https://doi.org/10.1504/IJPQM.2008.017504
Arief, I., Hasan, A., Putri, N. T., & Rahman, H. (2023). Literature reviews of RBV and KBV theories reimagined: A technological approach using text analysis and Power BI visualization. International Journal on Informatics Visualization, 7(4), 2532–2542. https://dx.doi.org/10.62527/joiv.7.4.1940
Balouei Jamkhaneh, H., Khazaei Pool, J., Khaksar, S. M. S., Arabzad, S. M., & Verij Kazemi, R. (2018). Impacts of computerized maintenance management system and relevant supportive organizational factors on total productive maintenance. Benchmarking, 25(7), 2230–2247. https://doi.org/10.1108/BIJ-05-2016-0072
Bekar, E. T. (2023). Efficiency measurement based on novel performance measures in Total Productive Maintenance (TPM) Using a fuzzy integrated COPRAS and DEA method. Frontiers in Manufacturing Technology, 3, article 1072777. https://doi.org/10.3389/fmtec.2023.1072777
Cantini, A., Ahmadi, A., Presciuttini, A., & Portioli-Staudacher, A. (2024). Jidoka advancements and applications for empowering manufacturing and operations: a bibliometric review. In XXIX AIDI Summer School Francesco Turco – Industrial systems engineering. https://www.summerschool-aidi.it/images/papers/session_3_2024/1108_Cantini.pdf
Chaabane, K., Schutz, J Dellagi, S., & Trabelsi, W.. (2021). Analytical evaluation of TPM performance based on an economic criterion. Journal of Quality in Maintenance Engineering, 27(2), 413–429. https://doi.org/10.1108/JQME-08-2019-0085
Cua, K. O., McKone, K. E., & Schroeder, R. G. (2001). Relationships between implementation of TQM, JIT, and TPM and manufacturing performance. Journal of Operations Management, 19(6), 675–694. https://doi.org/10.1016/S0272-6963(01)00066-3
Danguche, I., & Taifa, I. W. R. (2023). Factors Influencing Total Productive Maintenance Implementation for Thermal Generation Plants. Tanzania Journal of Engineering and Technology, 42(1), 97–112 https://journals.udsm.ac.tz/index.php/tjet/article/view/9156
Díaz-Reza, J. R., García-Alcaraz, J. L., Figueroa, L. J. M., Vidal, R. P., & Muro, J. C. S. D. (2022). Relationship between lean manufacturing tools and their sustainable economic benefits. International Journal of Advanced Manufacturing Technology, (123), 1269–1284. https://doi.org/10.1007/s00170-022-10208-0
Gelaw, M. T., Azene, D. K., & Berhan, E. (2024). Assessment of critical success factors, barriers and initiatives of total productive maintenance (TPM) in selected Ethiopian manufacturing industries. Journal of Quality in Maintenance Engineering, 30(1), 51–80. https://doi.org/10.1108/JQME-11-2022-0073
Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least Squares structural equation modeling (PLS-SEM) (2nd ed.). Sage.
Hallioui, A., Herrou, B., Katina, P. F., Santos, R. S., Egbue, O., Jasiulewicz-Kaczmarek, M., Soares, J. M., & Marques, P. C. (2023). A review of Sustainable Total Productive Maintenance (STPM). Sustainability, 15(16), 12362. https://doi.org/10.3390/su151612362
Kock, N. (2021). WarpPLS user manual: Version 7.0. ScriptWarp Systems.
Kock, N. (2023). Contributing to the success of PLS in SEM: An action research perspective. Communications of the Association for Information Systems, 52(1), 730–734. https://aisel.aisnet.org/cais/vol52/iss1/48/
Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS-SEM: The inverse square root and gamma-exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/10.1111/isj.12131
Koteswarapavan, C., & Pattanaik, L. N. (2024). A novel tool-input-process-output (TIPO) framework for upgrading to lean 4.0. International Journal of Production Management and Engineering, 12(1), 65–77. https://doi.org/10.4995/ijpme.2024.19723
Martínez-Loya, V., Díaz-Reza, J. R., García-Alcaraz, J. L., & Tapia-Coronado, J. Y. (2018). SEM: A global technique—Case applied to TPM. In J. L. García-Alcaraz, G. Alor-Hernández, A. A. Maldonado-Macías, & C. Sánchez-Ramírez (Eds.), New perspectives on applied industrial tools and techniques (pp. 3–22). Springer International Publishing.
Mendes, D., Gaspar, P. D., Charrua-Santos, F., & Navas, H. V. G. (2023). Integrating TPM and Industry 4.0 to increase the availability of industrial assets: A case sttudy on a conveyor belt. Processes, 11(7), 1956. https://doi.org/10.3390/pr11071956
Nakajima, S. (1989). TPM development program: Implementing total productive maintenance. Productivity Press.
Oroye, O. A., Sylvester, B. O., & Farayibi, P. K. (2022). Total productive maintenance and companies performance: A case study of fast moving consumer goods companies. Jurnal Sistem dan Manajemen Industri, 6(1), 23–32. https://doi.org/10.30656/jsmi.v6i1.4185
Parsazadeh, N., Ali, R., Rezaei, M., & Tehrani, S. Z. (2018). The construction and validation of a usability evaluation survey for mobile learning environments. Studies in Educational Evaluation, (58), 97–111. https://doi.org/10.1016/j.stueduc.2018.06.002
Pascal, V., Toufik, A., Manuel, A., Florent, D., & Frédéric, K. (2019). Improvement indicators for total productive maintenance policy. Control Engineering Practice, (82), 86–96. https://doi.org/10.1016/j.conengprac.2018.09.019
Pramod, V. R., Devadasan, S. R., & Jagathy Raj, V. P. (2010). Quality improvement in engineering education through the synergy of TPM and QFD. International Journal of Management in Education, 4(1), 1–24. https://doi.org/10.1504/IJMIE.2010.029879
Quiroz-Flores, J. C., & Vega-Alvites, M. L. (2022). Review lean manufacturing model of production management under the preventive maintenance approach to improve efficiency in plastics industry SMES: A case study. South African Journal of Industrial Engineering, 33(2), 143–156. https://doi.org/10.7166/33-2-2711
Rada, E. C., Nicolae, I., Zerbes, M.-V., Tulbure, A., Karaeva, A., Torretta, V., & Giurea, R. (2024). Implementation of a performance management system for environmental sustainability in an industrial organization. Journal of Physics Conference Series, 2857(1), 012030. https://doi.org/10.1088/1742-6596/2857/1/012030
Samadhiya, A., Agrawal, R., Kumar, A., & Garza?Reyes, J. A. (2023). Blockchain technology and circular economy in the environment of total productive maintenance: A natural resource-based view perspective. Journal of Manufacturing Technology Management, 34(2), 293–314. https://doi.org/10.1108/JMTM-08-2022-0299
Shingo, S., & Dillon, A. (1989). A study of the Toyota Production System: From an industrial engineering viewpoint (1st ed.). Routledge. https://doi.org/10.4324/9781315136509
Tamás, P., Tollár, S., Illés, B., Bányai, T., Tóth, Á. B., & Skapinyecz, R. (2020). Decision support simulation method for process improvement of electronic product testing systems. Sustainability, 12(7), 3063. https://doi.org/10.3390/su12073063
Valverde-Curi, H., De-La-Cruz-Angles, A., Cano-Lazarte, M., Alvarez, J. M., & Raymundo-Ibañez, C. (2019). Lean management model for waste reduction in the production area of a food processing and preservation SME. In The 5th International Conference Proceeding on Industrial and Business Engineering. https://doi.org/10.1145/3364335.3364378
Womack, J. P., Jones, D., & Ross, D. (2017). La máquina que cambió el mundo: la historia de la producción lean, el arma secreta de Toyota que revolucionó la industria mundial del automóvil. Profit.
Zhang, X. Z. & Chin, J. F. (2021). Implementing total productive maintenance in a manufacturing small or medium-sized enterprise. Journal of Industrial Engineering and Management, 14(2), 152. https://doi.org/10.3926/jiem.3286
Zhou, Z. R., Xiong, X. Q., Wang, J. X., & Bai, H. T. (2022). Equipment management of customized furnishing manufacturers based on total productive maintenance. Chinese Journal of Wood Science and Technology, 36(3), 20–25. https://dx.doi.org/10.12326/j.2096-9694.2021169
