Beyond Loss Cost: An AHP Framework for Prioritising Focused Improvement Initiatives in Total Productive Maintenance

Wina Indra Lavina; Timotius FCW Sutrisno

doi:10.37034/jems.v9i1.583

Authors

Wina Indra Lavina Universitas Ciputra
Timotius FCW Sutrisno Universitas Ciputra

DOI:

https://doi.org/10.37034/jems.v9i1.583

Keywords:

Total Productive Maintenance, Focused Improvement, Analytic Hierarchy Process, Group Decision-Making, Improvement Prioritisation

Abstract

Focused Improvement (FI) teams in Total Productive Maintenance (TPM) must decide which loss-reduction initiatives to pursue first, yet TPM prescribes no method for this choice, and plants usually rank initiatives by loss cost. This study develops and tests a multi-criteria framework for this decision. An Analytic Hierarchy Process (AHP) hierarchy of four criteria and 16 sub-criteria, derived from the JIPM loss structure and the literature, was weighted by 15 division and department heads of an Indonesian pipe manufacturer, 12 of whom then compared five initiatives from the plant’s 2026 improvement portfolio. Consistency, consensus, alternative aggregations, weight sensitivity, critical weights and a bootstrap over experts were analysed. Business impact received the highest weight (0.448), followed by sustainability (0.285), operational urgency (0.177) and implementation feasibility (0.090); customer impact, long-term benefit and quality outweighed cost reduction. The yield-loss initiative ranked first in 99.9% of bootstrap panels, and a quality initiative with the smallest realised saving rose from last to second place, so the AHP ranking agreed only weakly with the monetary ranking (ρ = 0.40). Loss cost should therefore inform, but not decide, the order of FI initiatives. The study extends AHP in TPM from ranking success factors to ranking FI initiatives and shows that managers value customer impact and risk above loss cost.

References

Fallahiarezoudar, E., Ahmadipourroudposht, M., Bagherian Rafi, M. H., & Ngadiman, N. H. A. (2025). A systematic approach of maintenance 4.0 towards a sustainable manufacturing policy: A case study on an automobile company. Process Integration and Optimization for Sustainability, 9(4), 1229–1251. https://doi.org/10.1007/s41660-025-00505-y

Samadhiya, A., Agrawal, R., & Garza-Reyes, J. A. (2024). Integrating Industry 4.0 and total productive maintenance for global sustainability. The TQM Journal, 36(1), 24–50. https://doi.org/10.1108/TQM-05-2022-0164

Nam, H., Cho, Y., Kim, J., Joo, Y., & Nam, H. (2025). An analytic hierarchy process for the sustainable development of small- and medium-sized enterprises in the manufacturing sector, South Korea. Environment, Development and Sustainability, 27(8), 20153–20180. https://doi.org/10.1007/s10668-024-05860-3

Utama, D. M., & Abirfatin, M. (2023). Sustainable Lean Six-sigma: A new framework for improve sustainable manufacturing performance. Cleaner Engineering and Technology, 17. https://doi.org/10.1016/j.clet.2023.100700

Chohan, I. M., Ahmad, A., Bheel, N., Najeh, T., & Almaliki, A. H. (2025). Sustainability assessment of different pipeline materials in freshwater supply systems. Frontiers in Materials, 12. https://doi.org/10.3389/fmats.2025.1566151

Badan Pusat Statistik. (2026). Ekonomi Indonesia tahun 2025 tumbuh 5,11 persen. Retrieved from https://www.bps.go.id/assets/pressrelease/2026/02/05/2546/ekonomi-indonesia-tahun-2025-tumbuh-5-11-persen.html

Ministry of Industry of the Republic of Indonesia. (2026). Industri pengolahan mendominasi kinerja ekonomi nasional. Retrieved from https://sippa.kemenperin.go.id/news/post/2026/02/20/37/industri-pengolahan-mendominasi-kinerja-ekonomi-nasional

Tirta, E. B. E. (2026). Impor plastik RI tembus Rp 46,3 triliun, siapa negara pemasoknya? CNBC Indonesia. Retrieved from https://www.cnbcindonesia.com/research/20260406115504-128-724138/impor-plastik-ri-tembus-rp-463-triliun-siapa-negara-pemasoknya

Dewi, S., Febrianti, R., & Utama, D. M. (2023). An integrated method for manufacturing sustainability assessment in tire industry: A case study in Indonesian. International Journal of Sustainable Engineering, 16(1), 1–12. https://doi.org/10.1080/19397038.2023.2276936

Rosiani, T. Y., Utama, D. M., Ummudiyah, A. Y., & Amallynda, I. (2024). Sustainable manufacturing assessment using sustainable VSM and AHP involving workload and machine efficiency: A case study in Indonesian paving block production. Circular Economy and Sustainability, 4(3), 2049–2071. https://doi.org/10.1007/s43615-024-00366-6

Rosiani, T. Y., Septian, R. I., & Masudin, I. (2026). Integrating Lean Six Sigma, Delphi, AHP and TOPSIS for waste minimization in sustainable manufacturing: A case of concrete paving block (CPB) production. Circular Economy and Sustainability, 6(3), Article 217. https://doi.org/10.1007/s43615-026-00947-7

Di Luozzo, S., Starnoni, F., & Schiraldi, M. M. (2023). On the relationship between human factor and overall equipment effectiveness (OEE): An analysis through the adoption of analytic hierarchy process and ISO 22400. International Journal of Engineering Business Management, 15. https://doi.org/10.1177/18479790231188548

Japan Institute of Plant Maintenance. (2016). Monodzukuri test learning textbook. JIPM.

Mouhib, Z., Gallab, M., Merzouk, S., Soulhi, A., & Di Nardo, M. (2025). Total productive maintenance and Industry 4.0: A literature-based path toward a proposed standardized framework. Applied System Innovation, 8(4). https://doi.org/10.3390/asi8040098

Bertolini, M., & Castellano, D. (2026). Quality cost deployment (QCD): A lean-inspired methodology for systematic reduction of total quality costs. International Journal of Lean Six Sigma, 17(8), 133–160. https://doi.org/10.1108/IJLSS-09-2025-0252

Hagström, M. H., Bergsjö, D. H., Sathyanarayana, A., & Machado, C. (2023). Quantifying and visualising wastes and losses in automotive production flows (across multiple plants and organisations) for increased accuracy in improvement prioritisations. International Journal of Product Development, 27(3), 245–264. https://doi.org/10.1504/IJPD.2023.133062

Salomon, V. A. P., & Gomes, L. F. A. M. (2024). Consistency improvement in the analytic hierarchy process. Mathematics, 12(6). https://doi.org/10.3390/math12060828

Srđević, B., & Srđević, Z. (2026). Incomplete judgments in AHP: Transition-based approaches, aggregation strategies, and their impact on decision outcomes. Algorithms, 19(1). https://doi.org/10.3390/a19010002

Madzík, P., & Falát, L. (2022). State-of-the-art on analytic hierarchy process in the last 40 years: Literature review based on latent Dirichlet allocation topic modelling. PLOS ONE, 17(5), Article e0268777. https://doi.org/10.1371/journal.pone.0268777

Kumar, J., Prince, N., & Baker, H. K. (2022). Balanced scorecard: A systematic literature review and future research issues. FIIB Business Review, 11(2), 147–161. https://doi.org/10.1177/23197145211049625

Wilson, R., Cudney, E. A., & Marley, R. J. (2024). Current status of Hoshin Kanri. The TQM Journal, 36(2), 460–483. https://doi.org/10.1108/TQM-07-2022-0216

Pakdil, F. (2022). Six Sigma project prioritization and selection methods: A systematic literature review. International Journal of Lean Six Sigma, 13(2), 382–413. https://doi.org/10.1108/IJLSS-01-2021-0001

Nakielski, M., & Ginda, G. (2026). AHP in design for Six Sigma project selection. Sustainability, 18(11). https://doi.org/10.3390/su18115258

Prasojo, R. A., Zainal, M. R., Handani, G. P. C., Hakim, M. F., Wijaya, B. H., Ghoneim, S. S. M., Mahmoud, K., Lehtonen, M., & Darwish, M. M. F. (2025). Enhanced maintenance prioritization strategies for medium voltage distribution substations through precise health index assessment. Sustainable Energy, Grids and Networks, 44. https://doi.org/10.1016/j.segan.2025.101987

Singh, R. K., & Gurtu, A. (2022). Prioritizing success factors for implementing total productive maintenance (TPM). Journal of Quality in Maintenance Engineering, 28(4), 810–830. https://doi.org/10.1108/JQME-09-2020-0098

Toke, L. K., & Kalpande, S. D. (2023). An assessment of key performance indicators and its relationship for implementation of total productive maintenance in manufacturing sector. International Journal on Interactive Design and Manufacturing, 17(4), 1741–1753. https://doi.org/10.1007/s12008-023-01252-5

Slavina, T., & Štefanić, N. (2024). Facing challenges of implementing total productive management and lean tools in manufacturing enterprises. Systems, 12(2), Article 52. https://doi.org/10.3390/systems12020052

Lucantoni, L., Antomarioni, S., Ciarapica, F. E., & Bevilacqua, M. (2025). A data-driven framework for supporting the total productive maintenance strategy. Expert Systems with Applications, 268, Article 126283. https://doi.org/10.1016/j.eswa.2024.126283

Swarnakar, V., Singh, A. R., Antony, J., Tiwari, A. K., & Garza-Reyes, J. A. (2023). Sustainable Lean Six Sigma project selection in manufacturing environments using best-worst method. Total Quality Management & Business Excellence, 34(7–8), 990–1014. https://doi.org/10.1080/14783363.2022.2139675

Kastratović, N., Arsić, D., Komatina, N., Delić, M., & Marinković, D. (2026). Prioritization of process improvement measures in a forging process using an IPF-AHP-based SREM framework. Journal of Manufacturing and Materials Processing, 10(7), Article 250. https://doi.org/10.3390/jmmp10070250

Hermeindito, H., Kristianto, L. S., & Christian, T. F. (2026). Vendor selection system in the system integration company PT. Visiniaga in Surabaya using the analytic hierarchy process (AHP) method. Jurnal Manajemen Teknologi, 25(1), 1–21. https://doi.org/10.12695/jmt.2026.25.1.1

Ecer, F. (2024). A state-of-the-art review of the BWM method and future research agenda. Technological and Economic Development of Economy, 30(4), 1165–1204. https://doi.org/10.3846/tede.2024.20761

Mazurek, J., Perzina, R., Strzałka, D., Kowal, B., Kuraś, P., Petřů Puhrová, B., & Rajs, R. (2024). Is the best–worst method path dependent? Evidence from an empirical study. 4OR, 22(3), 387–409. https://doi.org/10.1007/s10288-023-00553-5

Srđević, B., & Srđević, Z. (2024). Multi-model assessing and visualizing consistency and compatibility of experts in group decision-making. Mathematics, 12(11), https://doi.org/10.3390/math12111699

Lin, C., Kou, G., Peng, Y., & Alsaadi, F. E. (2022). Aggregation of the nearest consistency matrices with the acceptable consensus in AHP-GDM. Annals of Operations Research, 316(1), 179–195. https://doi.org/10.1007/s10479-020-03572-1

Tu, J., & Wu, Z. (2025). Analytic hierarchy process rank reversals: Causes and solutions. Annals of Operations Research, 346(2), 1785–1809. https://doi.org/10.1007/s10479-023-05278-6