Abstract

In the garment industry, reducing machine breakdowns is essential because it has a direct impact on production hours, customer orders, and financial losses. In order to reduce downtime and increase operational effectiveness in the garment industry, the DMAIC (Define, Measure, Analysis, Improvement, and Control) approach is the main topic of this research paper. The study starts with a thorough review of the literature, examining various downtime minimization strategies applied in various industrial industries. The importance of downtime reduction in increasing output, reducing costs, and improving overall corporate performance is emphasized. The study emphasizes the value of scheduled, corrective, and preventive maintenance to find and fix any problems before they cause breakdowns. The article offers insights into effective tactics like preventative maintenance, condition-based monitoring, and efficient scheduling, and data-driven approaches using machine learning algorithms and real-time monitoring. The research paper also includes a case study of how the DMAIC methodology was used in the real-world textile industry to drastically minimize downtime. The DMAIC strategy consists of five phases: defining the issue and project goal, assessing the existing situation, investigating the underlying reasons, putting improvement strategies into practise, and setting up controls to maintain the gains. The study prioritises the primary causes of machine failure time, identifies the causes, and suggests remedies such worker training, providing workers with the ability to change needles, putting preventive maintenance in place, and applying standard operating procedures.

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