Summary
Computers used in IIoT- enabled systems must be treated as critical equipment that require a higher level of maintenance strategy than non-critical devices.
Predictive Maintenance of Computers is Critical to IIoT-Enabled Systems
Businesses are striving to achieve intelligence at the edge of their industrial networks by deploying computers that can collect, process and analyze data in unmanned or remote sites. The consequences are dire when these computers have a performance issue or run out of memory, therefore preventing them from performing their role efficiently, if at all. Industrial processes come to a halt, leading to huge financial losses. If an industrial process malfunctions because of a failure to detect and fix computer issues on time, it could also lead to accidents that result in employee injuries. For these reasons, computers used in IIoT- enabled systems must be treated as critical equipment that require a higher level of maintenance strategy than non-critical devices.
Traditionally, manufacturers have maintained their assets using manual processes that are time-consuming and resource-intensive. The IIoT brings with it a paradigm shift with respect to the operation and maintenance of industrial equipment. Now, instead of waiting for equipment to fail before fixing it, or scheduling time-based maintenance that sometimes leads to unnecessary maintenance of equipment and downtime, companies are adopting predictive maintenance strategies to stay ahead of the game. These same practices should be applied to industrial computers.
Predictive maintenance tools for a computer can keep track of any variance from expected behavior for key parts, such as CPU usage, CPU temperature, memory usage, and disk usage. Predictive analytics empowers users to explore potential root causes and apply appropriate remedies. By identifying issues early on and allowing repairs to be scheduled in an orderly fashion, predictive maintenance provides lead time to purchase parts for the necessary repairs and reduces the need for maintaining an inventory of key parts. Hard drives, processors and other damaged parts are replaced before failures occur, and since maintenance work is only performed when needed, production capacity is likely to increase as well.
The goal of any predictive maintenance program is to enable proactive access to data for each piece of critical equipment, enabling the monitoring of its realtime health status, analyzing historical trends, and planning maintenance downtime based on the data.
Predictive maintenance tools for industrial computers monitor its health in order to make repairs well in advance to maximize system uptime. The tools will feature a well-designed dashboard that helps operators keep an eye on key indicators such as CPU loading and memory usage, plus an alarm function to trigger audio or visual alarms and SNMP traps when parameters go over predetermined thresholds.
Additional tool capabilities that aid in predictive maintenance are:
- Easy-to-use remote monitoring functions
- A ready-to-use tool that runs on a Windows or Linux OS
- RESTful APIs that give access to key-part parameters.
Predictive maintenance in action
Below we illustrate the importance of predictive maintenance for rail, marine, and power segments using remote-site scenarios.
Railroads: In a metro transit system, computers are widely deployed in onboard control and video recording systems. Because space is limited on refurbished traincars, computing systems are often installed in places that are hard to reach and even more difficult to maintain such as cabinets, compartments under passenger’s seats, or on the ceiling. Having ready access to a computer’s current condition …….
Source: https://www.automation.com/en-us/articles/august-2022/predictive-maintenance-computers-iiot-systems