~ The need for predictive maintenance ~
“If it’s not broken, don’t fix it” is a catchy phrase, but it’s not a good rule. Unplanned downtime and poor asset quality cost production and process industry approximately $ 20 to $ 60 billion each year. Unfortunately, such a reluctance to adopt new technologies, partly due to initial costs, hinders progress in operations. Here’s Neil Balinger, EMEA’s head automation parts supplier EU Automation explains why maintenance technologies can increase plant profitability through increased uptime.
Although they may be inevitable, equipment damage must not cause serious disruptions, eat away at profits or cause manufacturers to overspend their budgets. Today’s production facilities are much more complex than ever, consisting of data networks, integrated hardware and many automated systems. As a result, most manufacturers do not have enough maintenance methods. In fact, a report from Infraspeak points out that 93% of companies believe that their maintenance processes are not very effective.
Predictive maintenance is a way to anticipate every possible hardware failure scenario by identifying when maintenance is needed and alerting maintenance staff when needed, as well as providing preventative solutions.
Anyone who works within the production ecosystem will understand that damage and damage happen day after day. The purpose of predictive maintenance is not only to prevent or reduce these damages, but to help manufacturing companies achieve high efficiency standards and deliver quality products in the process. The predictive maintenance program can reduce unexpected damage by up to 90 percent, virtually eliminating damage.
In order to carry out effective forecasting production, the plant manager must collect as much data as possible. This is crucial in the implementation of any preventive maintenance strategy, as the more data available for analysis, the more accurate the damage estimates will be.
The starting point would be the use of intelligent sensors. Intelligent sensors, combined with machine learning algorithms, help detect anomalies in industrial machines. For example, intelligent sensors collecting data in industrial IoT environments can monitor temperature by identifying worn components, such as faulty electrical circuits.
Similarly, specialized intelligent sensors can perform vibration analysis of a specific component, identifying any cases of non-compliance, bent shafts or other engine problems. Based on these data, manufacturers can perform an analysis of critical assets to establish failure regimes. Here the focus is on the frequency of failures, the severity of the machine damage and the difficulty in identifying the fault.
By connecting condition monitoring devices to the CMMS, plant managers can set up alerts to inform maintenance personnel of any equipment malfunctions or anomalies. This provides an opportunity to plan scheduled maintenance when parts need to be replaced, eliminating the possibility of serious damage.
For example, sensor technology can be integrated with several different low-liquid energy products, from connectors, hoses and pipes to pumps, motors, actuators and filters. Here, some of the diagnostic data generated by the check valves can be vital in troubleshooting power problems.
The latest machines usually come with a variety of real-time data collection options, but legacy equipment can also be upgraded with inexpensive additional sensors. Estimated maintenance can be a vital asset when dealing with obsolete assets that require careful planning to obtain obsolete spare parts. Here are the expert consultants automation parts supplierslike EU Automation, it can help with the supply of parts and help power plant operators on their journey with predictable support.
Although some damage to equipment is inevitable, it must not cause unplanned downtime and poor asset quality, which costs billions of manufacturing and process industries each year. Instead, a complete and effective forecast maintenance plan will help prevent and significantly reduce downtime, while increasing plant profits through increased uptime.