Predictive Maintenance using IoT is a multi-step process that assists maintenance and reliability professionals in monitoring the health of equipment to avoid failures
Predictive Maintenance reduces unplanned downtime and helps in preventing asset failure. It enables remote monitoring of critical industrial assets and proactive asset maintenance
Predictive Maintenance using the Internet of Things (IoT) helps in identifying problems in complex equipments, in turn aiding in the avoidance of unplanned downtime. Remote monitoring using IoT offers many benefits to manufacturing operators resulting in increased efficiency on an operations level, while adding to cost-effectiveness. Predictive Maintenance is thus a one-step solution to multi-pronged problems.
The use of the Internet of Things (IoT) in the manufacturing and industrial sector refers to the use of Wireless Industrial IoT sensors and applications to connect machines and equipment sets. This is used in order to facilitate machine-to-machine communication, which improves overall manufacturing process efficiency.
In the field of IoT, Predictive Maintenance refers to the use of a data-driven approach that analyses the condition of the equipment to predict when it needs to be serviced. It’s a technique that has the potential to significantly improve asset performance and lifespan.
Predictive Maintenance using IoT is a multi-step process that assists maintenance and reliability in monitoring the health of equipment to avoid failures and unplanned downtime. It estimates the time of equipment failure and schedules maintenance activities based on data gathered from sensors and predictive algorithms.
It also identifies the root cause of problems in sophisticated equipment as well as the parts that need to be replaced. Remote Condition Monitoring of equipment is commonly used in Predictive Maintenance to collect real-time performance data, obtaining actionable insights from complex machine condition data analysis and taking corrective actions based on the findings in order to maximise asset uptime.
Industrial IoT Wireless Sensors are placed near a machine to capture various output parameters such as vibration, temperature and sound and converts them into signals. These are then routed through wireless networks to servers located in the cloud or on-premise. In most cases, these signals are routed to the server via gateways.
Machine learning algorithms are then used to convert the received data into meaningful data. It enables service providers to thoroughly filter and analyse data in order to provide insights about the health and performance of the machines. All stakeholders can access this information via a mobile app or a dashboard.
Predictive Maintenance reduces unplanned downtime and helps in preventing asset failure. It enables remote monitoring of critical industrial assets and proactive asset maintenance. Predictive Maintenance using IoT improves machine health and performance, resulting in less downtime, increased production and improved workplace safety.
Predictive Maintenance with IoT provides numerous benefits to manufacturing operators, allowing them to gain a significant competitive edge. These include visibility of manufacturing and production operations, increased operational efficiency, reduced unplanned downtime and cost-effective operation of production facilities.
The Predictive Maintenance system analyses historical and real-time machine performance data using predictive algorithms to detect faults before they occur and prevent subsequent failures. It also allows you to maximise asset uptime while lowering maintenance costs and resources.