Increase Factory Capacity Utilization with Predictive Machine Maintenance Tools

Garment factories can gain 10%-15% of its productive capacity with predictive machine maintenance tools.
In the apparel manufacturing industry, costs associated with machine downtime contribute as the largest source for loss of production time.

As per the published reports from various research, unplanned machine downtimes can cost manufacturing companies thousands of dollars every hour.

Machine related downtimes result in a loss of between 5%-20% productive capacity to an average factory. However, more than 75% of the factories are not able to accurately predict their downtime costs and related reasons.

How you can gain the productive capacity

With the advent of Manufacturing-AI-IoT integration, tech solutions like STITCH are bringing in revolutionary changes in the apparel manufacturing industry where predictive maintenance is replacing scheduled maintenance based on time and usage resulting in significant reductions in unplanned downtime and saving millions of dollars to the manufacturers.

STITCH Predictive Maintenance system utilizes trending and historical data of the sewing machines' performance to forecast and detect issues using AI machine learning models to quantify the machinery performance trends.

In simpler words, the need for periodic services of machines is eradicated. Machine mechanics can monitor different types of machine data like failure frequencies, reasons of sudden breakdowns, MTTR, MTBF and spare parts related breakdowns in order to understand the behaviours of the machines. They can forecast breakdown trends. Machine learning models predict when a specific machine might be nearing failure.

Advanced tools such as automatic and real-time assigning and monitoring of maintenance requests and their status, real-time machines status visibility in the entire factory can be improved over the sewing machine maintenance procedure. Event-based automatic mobile alerts bring a huge cultural change in making every shop floor people accountable.

Accessibility of e-manual and seamless access to the manufacturer’s online maintenance instruction videos, images, and other associate resources empowers technicians immensely in bringing up the machines in no time.

Other advanced features, like the skill matrix of the technicians, help in assigning the right maintenance work orders to the skilled technicians based on inbuilt maintenance performance skill history. Maintenance of spare parts and the ability to update stocks on the fly with auto minimum quantity stock alerts is another proactive smart feature.

Analytics with key performance indicators like comparative and automatic analysis by machines types, vendors, maintenance cost or other entity along the months of the current year and past years and other maintenance information makes the maintenance team more proactive with its maintenance services.

This article is submitted by Stitch MES team. STITCH MES is a game-changer cloud-based integrated system for sewing factories that monitors productivity across a factory’s global operations. Centralizing real-time data captured from the entire manufacturing process provides both instantaneous feedback and deep analytics to troubleshoot and adapt on the fly for the factory people minimizing cost and downtime. This ability to quickly respond to concerns before they escalate ensures quality and efficiency and on-time delivery.

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