Auto-detect production line failures
Manufacturing companies rely heavily on operational readiness. Even a few minutes of downtime can lead to heavy losses. Regular and pre-emptive maintenance can help manufacturers keep their production lines running without a break. While most of the manufacturing sites house a large number of maintenance staff, it is equally important to have a system in place which can auto-detect and predict machine failures. Some of the key challenges faced by manufacturers are:
- The current maintenance paradigm is broken.
- Scheduled maintenance is costly and inefficient and failures can be devastating to the bottom line.
- In large operations, these maintenance costs are no longer sustainable.
At AIndra Labs, we have built a solution to predict and auto-detect production line failures using machine learning and predictive analytics.
Smart Predict is a machine learning based predictive analytics platform which can learn specific historical patterns. The platform’s cognitive engine is designed to address machine prognostics.
The goal of Smart Predict is to change the current way of preventive maintenance to predictive maintenance. The platform can learn from the given data to identify impending failures long before they can occur, and also flag sub-optimal operations before they cause any harm. This will further optimize the machines by increasing the overall lifetime of the assets.
Smart Predict will enable truly predictive capabilities that will deliver millions of Rupees in cost savings and operational efficiency improvements to manufacturing and production factory owners
How it Works.
Historical and IoT data
Predictive Analysis for actionable insights
Improve Business Operations.
Protect assets and keeps them online all the time
Minimizes the maintenance cost by reducing the inspection time, eradicate minor escalations even before the event occurs
Flag upcoming downtimes
Predict machine failures and helps manage back up orders and proactive system maintenance
The results can be visually audited in less than a minute
Reducing the scope of corrupt collusion between workers and vendors significantly
A foolproof and self-adaptive intelligent solution
Runs on DNN based ML platform
Highly scalable and contextualized risk inspection based on visual, contextual and historical data
Predicts machine failure, hence reducing downtime
Cuts down the time consumed in inspecting failures and fixing issues by 30%
Efficient production line and reduced operational costs saves millions of dollars.