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A literature review of incoherence and inconsistencies in use of data in maintenance operations of the critical equipment in the weaving section of the textile manufacturing processes
  • Bett Kipchumba
Bett Kipchumba
Moi University

Corresponding Author:bbett90@gmail.com

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Abstract

This research paper presents a comprehensive literature review of the incoherence and inconsistencies in the use of data in maintenance operations of critical equipment in the weaving section of textile manufacturing processes. The paper begins with an introduction that highlights the shift in maintenance strategies from cost-focused approaches to reliability, downtime, safety, and machine availability. The optimization of maintenance schedules and minimization of downtime have become crucial challenges for industries. Proactive strategies such as predictive and preventive maintenance have played a significant role in maximizing machine availability. The outline of the paper includes a discussion of common maintenance issues in textile manufacturing processes, with a specific focus on weaving machines. Various maintenance strategies, including preventive maintenance, predictive maintenance, run-to-failure maintenance, and condition-based maintenance, are explored. The importance of obtaining accurate data for maintenance planning is emphasized, including failure data. The methods reviewed include failure mode and effect analysis (FMEA), fishbone diagram, and reliability and response modeling techniques such as mean time between failures (MTBF), regression analysis, the Weibull distribution, and failure rate vs. time plots. Furthermore, the paper delves into the implementation and validation of an optimized maintenance strategy. The process of implementing maintenance optimization and ensuring the effectiveness of the chosen strategy are discussed in detail. Finally, the research identifies gaps in existing literature and points to areas that require further investigation to enhance maintenance operations in the weaving section of textile manufacturing processes.