What is Predictive Maintenance?
While the concept of Predictive Maintenance (PdM) has been around for a while, the recent advancements in IoT, Cloud, Machine Learning technologies are making PdM more accessible to industries across in a cost effective way.
In the last couple of years, the principles of Industry 4.0 and Predictive Maintenance (PdM) have gained widespread acceptance at an executive level with a shift moving towards implementations. Many industrial organizations have assigned responsibilities and budget for evaluating technologies and piloting new solutions.
What is Predictive Maintenance?
Predictive maintenance (PdM) is the application of Industry 4.0 technologies that uses data from various sources like sensors, scada PLCs, historic maintenance data, cleansed and applied to analytical models through machine learning to predict when equipment failure may occur and prevent the failure by performing the required maintenance proactively.
The buzz around PdM has many maintenance professionals setting their sights on O&M activities in order to identify and proactively address industrial equipment problems.
The business objective yields benefits to increase production by:
1. Improving equipment uptime
2. Improving Efficiency
3. Lower operational costs
In a Reactive Maintenance strategy, the industrial plant will react with a corrective action to resolve a breakdown. As a result, when a failure incident occurs, production must be stopped during unscheduled repair time.
In Prognostic, Predictive Maintenance suite, Machine embedded sensor data is acquired via IoT gateway system. Predictive Models are then then applied at machine edge computing through a scalable architecture, Which is trained to identify failure patterns and alert as its identified. Any potential repairs can be scheduled in advance through an automated workorder scheduling or event trigger. During this the period prior to scheduled shutdown, tools and parts can be ordered and repairs scheduled.
In addition, Predictive Maintenance includes the use of automation, robotics and drones to reduce physical inspection and automate repetitive O&M tasks.
There are many significant benefits to implementing a good edge based predictive maintenance solution. However as with all good successful implementation, execution against the right Predictive Maintenance strategy will be key for successful business benefit.
Establishing a well-run preventive maintenance strategy cultivates the skills, processes and top-to-bottom buy-in that can help a facility overcome these challenges. At the end of the day, you’ll be glad you learned how to walk with preventive maintenance before you ran with predictive maintenance .
In the last couple of years, the principles of Industry 4.0 and Predictive Maintenance (PdM) have gained widespread acceptance at an executive level with a shift moving towards implementations. Many industrial organizations have assigned responsibilities and budget for evaluating technologies and piloting new solutions.
What is Predictive Maintenance?
Predictive maintenance (PdM) is the application of Industry 4.0 technologies that uses data from various sources like sensors, scada PLCs, historic maintenance data, cleansed and applied to analytical models through machine learning to predict when equipment failure may occur and prevent the failure by performing the required maintenance proactively.
The buzz around PdM has many maintenance professionals setting their sights on O&M activities in order to identify and proactively address industrial equipment problems.
The business objective yields benefits to increase production by:
1. Improving equipment uptime
2. Improving Efficiency
3. Lower operational costs
In a Reactive Maintenance strategy, the industrial plant will react with a corrective action to resolve a breakdown. As a result, when a failure incident occurs, production must be stopped during unscheduled repair time.
In Prognostic, Predictive Maintenance suite, Machine embedded sensor data is acquired via IoT gateway system. Predictive Models are then then applied at machine edge computing through a scalable architecture, Which is trained to identify failure patterns and alert as its identified. Any potential repairs can be scheduled in advance through an automated workorder scheduling or event trigger. During this the period prior to scheduled shutdown, tools and parts can be ordered and repairs scheduled.
In addition, Predictive Maintenance includes the use of automation, robotics and drones to reduce physical inspection and automate repetitive O&M tasks.
There are many significant benefits to implementing a good edge based predictive maintenance solution. However as with all good successful implementation, execution against the right Predictive Maintenance strategy will be key for successful business benefit.
Establishing a well-run preventive maintenance strategy cultivates the skills, processes and top-to-bottom buy-in that can help a facility overcome these challenges. At the end of the day, you’ll be glad you learned how to walk with preventive maintenance before you ran with predictive maintenance .
