Pneumatics maintenance in automation: Combining predictive, preventive strategies
Predictive and preventive maintenance programs are essential to managing equipment lifecycles with the ultimate goal being reduced downtime and protecting people and machinery from accidental equipment breakdowns.
Wear and tear is a fact of life in any manufacturing system. The laws of physics dictate that production equipment—particularly the moving parts—always will have a functional lifecycle, after which the device, component or system will need to be overhauled, remanufactured or completely replaced.
Predictive and preventive maintenance programs are essential to managing equipment lifecycles efficiently and to maximizing the return on investment and total cost of ownership of production equipment. The end goal is minimizing downtime and protecting both people and machinery from accidental equipment breakdowns attributed to poorly maintained equipment.
Use of pneumatic technology
The use of pneumatics, with air-driven cylinders, actuators and valves for process and machine controls, is common in automation systems. These include applications such actuating and controlling diverter gates on material handling and sorting systems; moving devices such as sealers and grippers on packaging machines; and controlling pilot valves in oil and gas refinery equipment.
Pneumatic equipment share some common characteristics: the motion is often fast and highly repetitive (in some cases, the cycle time is milliseconds), and the functions they perform, while simple, are essential to the machine's functionality.
In other words, if the pneumatics fail or begin malfunctioning due to poor maintenance, productivity can suffer and unscheduled machine downtime becomes problematic. Pneumatics manufacturers, working with automation OEMs, have developed enhanced approaches to both predictive and preventive maintenance practices, as well as enhancing the technical features of their pneumatics systems. These enhancements, including new sensors and other digital capabilities, align with the emerging requirements of the Industrial Internet of Things (IIoT) production systems and enable more data-driven approaches to maintenance.
Predictive vs. preventive maintenance
Predictive maintenance is the management approach plant engineers use to track and assess the condition of in-service equipment. Effective use of predictive maintenance determines when maintenance should be performed, and can provide cost savings over routine or time-based preventive maintenance, because tasks are performed only when warranted.
Predictive maintenance is data-driven—delivering the right information at the right time. By knowing which equipment needs maintenance, unplanned downtime is replaced with shorter and fewer planned machine stops, thus increasing plant availability. Other potential advantages include increased equipment lifetime, increased plant safety, fewer accidents with negative impact on the environment and optimized spare parts handling.
Preventive maintenance goes together with predictive maintenance, and is the regular and routine action taken to prevent equipment breakdown. These tasks can include partial or complete overhauls at specified periods; oil changes and lubrication; minor adjustments to device settings; and cleaning of machine components exposed to environmental contamination.
Pneumatics maintenance improvements
Both types of maintenance are advised for pneumatic components. Pneumatics manufacturers constantly are investing in new designs and improved materials to increase the reliability and operational lifespan of their products. This includes better valve sealing techniques, replacing metal components with polymer for better wear profiles and improvements to airflow paths, making devices run smoother and more efficiently.
Working with OEMs, pneumatics manufacturers have identified the key areas of failure and are developing new approaches to sensors in actuators, valves and cylinders that provide more complete data about changes in device performance over time—key indicators that pneumatic device components may be wearing out.
These qualitative improvements have significantly extended product lifecycles. For example, valve systems that were once rated for 100 million cycles can now deliver up to 140 million cycles of error-free operation. Extended lifecycles make predictive maintenance more important for pneumatics; because the products are engineered to operate longer, tracking their performance and intervening to service and repair a malfunctioning device is essential to reaching the projected operating life.
As an example, some pneumatic cylinders contain shock absorbers that use hydraulic fluid. Over time these can lose their effectiveness due to fluid leakage. When a machine is first commissioned, the baseline optimum cycle time for that cylinder is established (for example, at 135 milliseconds). Based on testing by the pneumatics manufacturer a lifecycle value also is determined (called a B10 value).
Predictive maintenance is used to monitor that cylinder's performance with actual sensor data coming from condition monitoring devices. If these sensors report that the cylinder is accelerating at the end of stroke (between dampening the load to when the load stops), that could indicate a loss in hydraulic dampening fluid that may indicate the shock absorber should be replaced.
Following a standard preventive maintenance program however, that cylinder might not be scheduled for repair or replacement until it reaches the end of its projected lifecycle. Even though the actuator isn't completely malfunctioning, the cylinder's performance is starting to degrade and could eventually cause an unscheduled machine shutdown or poor quality production.
Preventive maintenance is necessary to ensure the components that do wear out are cleaned, repaired and/or replaced using standardized, predictable schedules that minimize the impact on overall productivity and equipment effectiveness.
Cylinders and valves have seals and other interior surfaces that can wear over time or become dirt-clogged, especially in rugged environments such as sawmills, where the air contains high particulate levels. Pneumatics manufacturers work with OEMs to recommend maintenance intervals based on operating conditions, combined with established B10 lifecycle values for specific components.
Depending on the device and the operating environment, preventive maintenance might include modifying when key components are replaced. For example, in a steel plant or sawmill, with increased airborne contaminants, a preventative maintenance plan may include more frequent replacement of solenoid control valves to make sure that the valve is not ingesting particles that impede valve performance.
That means having the right supply of spare parts available so there is no delay when a machine is taken offline for maintenance and repair. Good preventive maintenance practices also include planning maintenance of multiple machine systems—not just pneumatics—to minimize overall downtime.
Integrating predictive maintenance into this process can significantly increase the efficiency of preventive maintenance. Now that many pneumatic devices incorporate sensors that measure the functional cycle, condition monitoring can be implemented-where event timing and correlation and threshold monitoring can be used to accurately track the performance of each device.
If a cylinder is rated to operate at 135 milliseconds per cycle and it keeps that cycle, then the machine operator can be confident in continued good operating performance. If the cycle time begins to slip below a certain threshold, condition monitoring can accurately predict the likelihood of failure, and when. If the device is already scheduled for preventive maintenance, no intervention is required. However, if it is not included for service at the next maintenance interval, or if there is no replacement on-hand, plant engineering and maintenance staff can adapt their plan based on the predictive maintenance alert.
This integration of predictive (data-driven) management with preventive (scheduled, standardized) maintenance also can help plant management control spare parts inventory planning and costs. In the past, having a full inventory of system-critical replacement part in inventory "just in case" was the best way to minimize downtime. With the intelligence now integrated into pneumatics components to enable early detection and prediction of possible issues well ahead of time, orders can be placed and replacement parts swiftly delivered to enable repair or replacement.
Ready for IIoT
As pneumatics become more intelligent, they are generating additional data points across the production systems in which they are installed: information such as diagnostics, usage statistics and lifetime data. This enhanced intelligence is consistent with the vision for highly autonomous production systems which is the foundation for many IIoT concepts.
However, device data is only valuable when used to manage production systems to achieve greater productivity, control energy consumption and maximize uptime. In addition, if all the pneumatic components (along with other intelligent machine drives, devices and subsystems) are generating megabytes of performance data, there's a potential to overwhelm the machine control bus and complicate automation command and control performance.
To address this scenario, pneumatics manufacturers have developed a gateway that aggregates and organizes pneumatic performance data and can deliver it through separate pathways to plant management. This gateway can be independent of the process control architecture to deliver alerts and both system-level and device-level performance data.
Ultimately, pneumatics suppliers envision a highly autonomous maintenance process. When the data indicates a device is approaching failure or reaching the end of its lifecycle, a replacement is automatically ordered and delivered to the plant just in time for it to be used during a scheduled maintenance cycle.
The most effective approach to pneumatic maintenance (or maintenance of any automation system or component) is to combine the data-driven insight that predictive maintenance provides about device performance with preventive maintenance's efficiency in scheduling of downtime and service.
Preventive maintenance can be made more efficient by incorporating the outputs of predictive maintenance processes and tools to prioritize which pneumatic devices need to be serviced, and when, as well as controlling the cost of spare parts inventory. Most importantly, combining predictive and preventive maintenance can minimize pneumatic component failures that may risk harming people or machinery, keeping manufacturing systems operating with maximum uptime.
Mark Densley is head of product management for controls for Aventics Corporation.
See additional stories from the Plant Engineering May 2017 cover story below.
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