Predictive Maintenance with Data Science and Machine Learning
The manufacturing industry has always been ever-changing. Every year, the industry faces new challenges and to overcome them, manufacturing companies have been implementing preventive maintenance, getting their machines checked by technicians regularly to make sure equipment keep working well and factories remain up and running.
More than half of the manufacturers are following this necessary, but insufficient method that results in nothing, but increased labor costs. Though machines are regularly checked and serviced by technicians, they can fail at any time. This method is putting manufacturers at risk of unexpected machine failure. Challenges faced by manufacturers are soaring with time,some of which include-
- High maintenance costs
- Unexpected failures
- High repair and overhaul time
- Increased spare parts inventory
- Increased downtime
- Low ‘machinery mean time between failures’
One way to get rid of this is continuous monitoring of machines and equipment. If you know when and how your machines are going to fail, you can create effective maintenance program to take corrective measures even before machines fail. This is called predictive maintenance.
Predictive maintenance helps you monitor your machines, predict quality issues and asset failures even before they occur, so that you can get it fixed quickly. Softweb’s predictive maintenance solutions help manufacturers achieve zero downtime and maximum machine availability, which will minimize warranty claims, optimize inventory and reduce maintenance costs.
If you want to keep your operations up and running with predictive maintenance, get in touch with our experts. We can also set up an on-premise workshop and help you get started quickly.
This video is about Predictive Maintenance with Data Science and Machine Learning - Every year, the industry faces new challenges and to overcome them, manufacturing companies have been implementing preventive maintenance.