Predictive maintenance is a proactive method that employs condition monitoring technologies to track asset health and identify potential defects in real-time. It assists in predicting when maintenance is required to minimize equipment downtime and associated expenses.
Any industry’s primary concern is to reduce breakdowns and increase production. Choosing the correct maintenance approach might help you avoid frequent equipment failures and monetary loss. Preventive maintenance is planned maintenance that includes cleaning, lubrication, repairs, and replacements at predefined intervals to reduce the probability of equipment failure and unexpected downtime.
“The Current Trend: Prediction Is Better Than Prevention!”
In predictive maintenance, IoT sensors are utilized to monitor the condition of the equipment. These sensors capture data such as temperature, vibration, ultrasound, current, voltage, etc. The data collected, both historical and real-time, is used to predict equipment failure early on.
The Internet of Things (IoT) converts data acquired from sensors into digital form & facilitates data exchange between various devices. Machine Learning is applied to identify the faults and predict equipment failure.
Identification of critical assets: Identify the assets that are critical to the operations of the business. The failure of these assets regularly has a negative influence on production and leads to significant financial losses. Online monitoring can be employed for continuous remote monitoring of critical assets whereas offline monitoring can be employed for periodic monitoring of assets with a lower priority. The SANDS ARGUS vibration sensor comes in two versions: Online & Offline.
Determine the type of maintenance: After we’ve identified our key assets, we need to figure out what kind of maintenance we’ll do. Vibration Analysis, Electrical Analysis, Thermography, Ultrasound Analysis are some of the methods used in predictive maintenance. SANDS ARGUS is a portable tri-axial vibration sensor that measures vibration in three directions simultaneously.
Decide the threshold limits: We must next define threshold limits after identifying the type of maintenance. If we want to monitor asset vibration, for example, we must first establish a vibration limit. We can undertake maintenance to prevent asset failure when the asset vibration exceeds the preset limit. When the asset vibration exceeds the threshold limit, the AHMS Cloud Software alerts the user through SMS or email.
Installation of IoT sensors: The IoT sensors will then be installed on the equipment that needs to be monitored. IoT sensors include Vibration Sensors, Electrical Signature Analyzers, Thermal Cameras, and Ultrasonic flaw detectors. ARGUS can be mounted on the equipment with the use of a magnet, adhesive, and stud.
Data Collection and Analysis: Once the sensors are installed, the data is collected and stored in a smartphone, tablet, or personal computer. The collected data will be analyzed to identify the faults which cause equipment failure. For offline data collection, the ARGUS app is used to collect data through Bluetooth, and for online data collection, the data from the sensor is transferred to AHMS Cloud Software through WiFi.
Plan & Perform Maintenance: The next step is to plan and execute the maintenance task. Early detection and correction of faults improves equipment reliability and reduces downtime. Finally, double-check the accuracy of the predictions and offer suggestions for improvement.
Predictive Maintenance is the process of continuously monitoring the condition of an asset in order to detect and correct faults before the asset fails. Preventive Maintenance, on the other hand, is scheduled maintenance that occurs at predetermined intervals and involves the replacement of parts that are still in excellent working order.
Predictive Maintenance employs cutting-edge technology such as the Internet of Things (IoT) and Machine Learning to predict and prevent equipment failure. Preventive Maintenance is a traditional maintenance plan based on the concept that parts will deteriorate over time and need to be replaced to avoid equipment failure and maintain productivity.
In comparison to Preventive Maintenance, Predictive Maintenance has a lower maintenance cost and lower production loss. Industrial Predictive Maintenance cuts down on equipment downtime.
Signals & Systems (India) Private Limited commonly known as SANDS is primarily a technology company manufacturing niche products using embedded technology for the Generation, Transmission & Distribution segments of the Power Industry. On the Services front, we specialize in Energy Management Solutions to manage energy consumption efficiently to avoid penalties. We also undertake testing of Energy meters at the site on behalf of the utilities as part of the regulatory guidelines.
Our core guiding principle has been ‘Make Global Standard Products in India” ever since the inception of the company. We’ve received several accolades and recognition for the innovative products that we’ve designed and manufactured in India. Most of our products have been the first of their kind in the country. We have over a decade, entered into the Industrial segment with solutions for IoT-based Predictive Maintenance such as Vibration-Based Machine Condition Monitoring, Current Signature Analysis, & Energy Management. To know more about us and other details, please visit www.sandsindia.com or write to email@example.com