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Operational excellence in total productive maintenance: statistical reliability as support for planned maintenance pillar

Felipe Terra Mohad (Universidade Federal do Rio Grande, Rio Grande, Brazil)
Leonardo de Carvalho Gomes (Universidade Federal do Rio Grande, Rio Grande, Brazil)
Guilherme da Luz Tortorella (Universidad Austral, Buenos Aires, Argentina)
Fernando Henrique Lermen (Universidade Estadual do Paraná, Paranaguá, Brazil)

International Journal of Quality & Reliability Management

ISSN: 0265-671X

Article publication date: 18 September 2024

150

Abstract

Purpose

Total productive maintenance consists of strategies and procedures that aim to guarantee the entire functioning of machines in a production process so that production is not interrupted and no loss of quality in the final product occurs. Planned maintenance is one of the eight pillars of total productive maintenance, a set of tools considered essential to ensure equipment reliability and availability, reduce unplanned stoppage and increase productivity. This study aims to analyze the influence of statistical reliability on the performance of such a pillar.

Design/methodology/approach

In this study, we utilized a multi-method approach to rigorously examine the impact of statistical reliability on the planned maintenance pillar within total productive maintenance. Our methodology combined a detailed statistical analysis of maintenance data with advanced reliability modeling, specifically employing Weibull distribution to analyze failure patterns. Additionally, we integrated qualitative insights gathered through semi-structured interviews with the maintenance team, enhancing the depth of our analysis. The case study, conducted in a fertilizer granulation plant, focused on a critical failure in the granulator pillow block bearing, providing a comprehensive perspective on the practical application of statistical reliability within total productive maintenance; and not presupposing statistical reliability is the solution over more effective methods for the case.

Findings

Our findings reveal that the integration of statistical reliability within the planned maintenance pillar significantly enhances predictive maintenance capabilities, leading to more accurate forecasts of equipment failure modes. The Weibull analysis of the granulator pillow block bearing indicated a mean time between failures of 191.3 days, providing support for optimizing maintenance schedules. Moreover, the qualitative insights from the maintenance team highlighted the operational benefits of our approach, such as improved resource allocation and the need for specialized training. These results demonstrate the practical impact of statistical reliability in preventing unplanned downtimes and informing strategic decisions in maintenance planning, thereby emphasizing the importance of your work in the field.

Originality/value

In terms of the originality and practicality of this study, we emphasize the significant findings that underscore the positive influence of using statistical reliability in conjunction with the planned maintenance pillar. This approach can be instrumental in designing and enhancing component preventive maintenance plans. Furthermore, it can effectively manage equipment failure modes and monitor their useful life, providing valuable insights for professionals in total productive maintenance.

Keywords

Acknowledgements

The authors would like to thank the CAPES Foundation (Coordination for the Improvement of Higher Education Personnel).

Citation

Mohad, F.T., Gomes, L.d.C., Tortorella, G.d.L. and Lermen, F.H. (2024), "Operational excellence in total productive maintenance: statistical reliability as support for planned maintenance pillar", International Journal of Quality & Reliability Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJQRM-09-2023-0290

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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