Improvement Model Based on Standardization and TPM to Reduce Defective Products in a Textile SME

Authors

DOI:

https://doi.org/10.26439/ciii2025.8645

Keywords:

Defect reduction, textile manufacturing, Total Productive Maintenance (TPM), trial testing, work standardization

Abstract

The Peruvian textile industry, a key contributor to the national economy representing approximately 8% of manufacturing GDP, faces a persistent production decline of 4.45% and a defective product rate of 6.6% among small and medium-sized enterprises (SMEs). Despite extensive research on defect reduction through Six Sigma, Total Quality Management (TQM), and Total Productive Maintenance (TPM), gaps remain in scalable and low-cost solutions tailored to resource-constrained SMEs in developing contexts. This study introduces novel variables—ergonomic improvements and iterative operator feedback loops—that have been underexplored in Peruvian textile SMEs. Focusing on a Lima-based SME dedicated to jeans production, a mixed-methods approach was applied to implement process standardization and TPM, reducing the overall defect rate from 10.15% to 6.75%. Unlike prior studies, this research integrates real-time operator input to continuously refine interventions, resulting in a replicable and cost-effective model suitable for SMEs with limited resources. Future research may explore automated fault detection systems to further enhance scalability.

Downloads

Download data is not yet available.

Author Biographies

  • Sebastian P. Caballero-Trujillo, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Sebastian Pedro Caballero-Trujillo holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima, Peru. He currently works as a Business Specialist at Banco de Crédito del Perú. He has experience as an intern in information management and in the Payment Solutions Tribe. His main research interests are risk management, collections, and payment solutions.

  • Renzo J. P. Mestanza-Ames, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Renzo Jean Pierre Mestanza-Ames holds a Bachelor’s degree in Industrial Engineering from Universidad de Lima, Peru. He is currently a professional intern in processes at Universidad de Lima. He has experience in operations, logistics, project management, productivity improvement, and health, safety, and environment. His main research interests are lean manufacturing and logistics.

  • Gino Viacava-Campos, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Gino Viacava-Campos holds a Master’s degree in Operations and Logistics from Universidad Peruana de Ciencias Aplicadas, Peru, and a degree in Industrial Engineering from Universidad de Lima, Peru. He is currently a professor in the Industrial Engineering Program at Universidad de Lima. He has experience in industrial and service companies, focusing on productivity improvement, business model development, and compensation system structuring. He has worked in human resources, operations, and logistics areas of a transnational company, both locally and overseas. As a consultant, he has experience in the construction, manufacturing, services, mining, commercial, finance, and education sectors. He has co-authored papers including “A Production Process Efficiency Improvement Model at a MSME Peruvian Metalworking Company,” published in the Proceedings of the 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). His main research interests are lean manufacturing, master production schedules, logistics, and compensation systems for small and medium sized enterprises.

  • Jorge A. Corzo-Chavez, Carrera de Ingeniería Industrial, Universidad de Lima, Perú

    Jorge Antonio Corzo-Chavez holds a Master’s degree in Business Administration from Universidad ESAN, Peru; a Master’s degree in Marketing Science from ESIC Business & Marketing School, Spain; and a degree in Industrial Engineering from Universidad de Lima, Peru. He is currently a professor in the Industrial Engineering Program at Universidad de Lima and Chief Executive Officer at Conquista Lab. He has advised industrial and service companies on productivity improvement and business model development, and has worked in entrepreneurship, innovation, and commercial roles in the construction, mining, services, and education sectors. He has co-authored papers including “Improvement of Productivity by Applying 5S, Work Standardization, Ergonomic Analysis and Poka Yoke in a Metalworking Company,” published in the Proceedings of the 23rd LACCEI International Multi-Conference for Engineering, Education, and Technology; “Production Model Based on Lean Manufacturing and Systematic Layout Planning to Reduce Waste in a Company in the Poultry Sector: A Case Study,” published in the International Journal of Environmental Pollution and Remediation, volume 12; and “Model for Reducing Mean Absolute Percentage Error through Smoothing and Time Series Forecasting in a Tourism SME: A Case Study,” published in the Journal of Machine Intelligence and Data Science, volume 5. His main research interests are lean manufacturing, logistics, and machine learning for enterprises.

References

[1] A. Bajpai, D. Kannan, J. D. Darbari, and P. C. Jha, “Sustainable supplier selection model with a trade-off between supplier development and supplier switching,” Ann. Oper. Res., vol. 331, pp. 351–392, Dec. 2022, doi: 10.1007/s10479-022-04812-2.

[2] B. S. Alanya, K. E. Dextre, V. H. Nuñez, G. E. Marcelo, J. C. Alvarez, and K. Hatakeyama, “Application of Lean Manufacturing to improve processes and increase productivity in the textile industry of Peru: Case study,” S. Afr. J. Ind. Eng., vol. 35, no. 2, pp. 140–153, Jan. 2024, doi: 10.7166/35-2-2932.

[3] D. Sjarifudin, H. Kurnia, H. H. Purba, and C. Jaqin, “Implementation of six sigma approach for increasing quality formal men’s jackets in the garment industry,” J. Sist. Manaj. Ind., vol. 6, no. 1, pp. 33–44, Jun. 2022, doi: 10.30656/jsmi.v6i1.4359.

[4] C. Ellegaard, U. Normann, and N. Lidegaard, “Intuitive global sourcing – A study of supplier selection decisions by apparel SMEs,” Int. J. Oper. Prod. Manag., vol. 42, no. 2, pp. 151–181, Jan. 2022, doi: 10.1108/IJOPM-03-2021-0205.

[5] F. Hardt, M. Kotyrba, E. Volna, and R. Jarusek, “Innovative approach to preventive maintenance of production equipment based on a modified TPM methodology for Industry 4.0,” Appl. Sci., vol. 11, no. 15, p. 6953, Jul. 2021, doi: 10.3390/app11156953.

[6] R. A. Joy, M. S. Hawlader, M. S. Rahman, M. R. Hossain, S. I. Shamim, and H. Mahmud, “Improving quality, productivity, and cost aspects of a sewing line of apparel industry using TQM approach,” Math. Probl. Eng., vol. 2024, no. 1, pp. 1–13, Feb. 2024, doi: 10.1155/2024/6697213.

[7] S. Kirin and A. H. Šajatović, “Determination of working methods and normal times of technological sewing operation using MTM system,” Tekstilec, vol. 63, no. 3, pp. 203–215, Sep. 2020, doi: 10.14502/Tekstilec2020.63.203-215.

[8] M. Küçük, M. İşler, and M. Güner, “Optimizing the material-product transformation processes in the clothing manufacturing line,” Tekstil ve Konfeksiyon, vol. 32, no. 2, pp. 135–145, Jun. 2022, doi: 10.32710/tekstilvekonfeksiyon.988251.

[9] C. J. Moin, K. R. Hossain, and L. M. Baral, “Investigating root causes of sewing defects using TQM tools for quality improvement in the knit garment industry,” Text. Leather Rev., vol. 6, pp. 417–433, Sep. 2023, doi: 10.31881/TLR.2023.071.

[10] National Institute of Statistics and Informatics (INEI), “Textile industry production statistics,” INEI, Lima, Peru, 2024. [Online]. Available: https://www.inei.gob.pe/media/principales_indicadores/04-informe-tecnico-produccion-febrero-2024.pdf

[11] Risteski S. and V. Srebrenkoska, “Textile waste from confection industries and possibilities for its recycling” Tekstilna Industrija ., Shtip, Macedonia, 2020, vol. 68, no. 4, pp. 77–82. doi: 10.5937/tekstind2004077R

[12] M.-L. Tseng, T.-D. Bui, M. K. Lim, M. Fujii, and U. Mishra, “Assessing data-driven sustainable supply chain management indicators for the textile industry under industrial disruption and ambidexterity,” Int. J. Prod. Econ., vol. 245, p. 108401, Mar. 2022. doi: 10.1016/j.ijpe.2021.108401.

Downloads

Published

2026-06-08

Issue

No. 004 (2025): IV Congreso Internacional de Ingeniería Industrial

Section

Ponencias

License

Copyright (c) 2026 Congreso Internacional de Ingeniería Industrial de la Universidad de Lima

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.