Enabling predictive maintenance with machine self-diagnostics
09 September 2016
Predictive maintenance has become an important enabler for optimising machine availability. Omron’s Barry Graham looks at the self-diagnostics strategies that machine builders can integrate into their designs to help their customers boost overall equipment effectiveness (OEE), and how this can set users on the path to an Industry 4.0.
The last decade has seen a significant change in the way machinery is maintained, moving from reactive maintenance to a strategy of preventative maintenance. From an end-user’s perspective, a key driver behind this change has been the growing acceptance of OEE as a measure for a company’s productivity. Eliminating downtime is an important step in maximising OEE; and if you can solve a potential problem before it leads to unscheduled downtime, then you are on the way to increasing machine availability.
Shift towards self-monitoring
Preventative maintenance is all about looking at the things that might fail, and addressing those aspects in good time. Typically, that will mean replacing key components before they get to the end of their predicted lifespan.
Certainly this minimises unscheduled downtime and the high cost of production line stoppages, but it does mean potentially carrying out work that doesn’t necessarily need doing, or replacing components that could yet have years of useful life. So increasingly we are seeing a goal of moving from preventative maintenance to predictive maintenance, where the machine itself monitors its own components and operations, and gives more accurate and useful information relating to production trends and component problems.
The question for machine builders is how best to implement the self-diagnostics facilities that will assure higher availability and therefore improved OEE, giving them a competitive advantage. Some functions are easy to implement: variable speed drives, for example, have long offered the ability to monitor the current to the motor, with a gradual increase in required current indicative of developing problems within the mechanical power train. Then there are temperature sensors, vibration monitors and other add-on condition monitoring products that can all be used as part of a predictive maintenance strategy. But what about the more sophisticated monitoring functions that could really help end users to take machine availability to the next level?
While the requisite information to deliver enhanced self-diagnostics is certainly available within modern automation equipment, accessing that data and turning it into meaningful, useful information has traditionally been something of a coding and programming challenge. Because of this, often it is something that is left to the end of the machine development process, adding time and cost.
Suppose, though, it was quick and simple to build in this self-diagnostics capability as an integral aspect of the machine design. The result would be machines that offered genuine added value for customers. Further, by being an integral part of the design process, and therefore not adding time and cost, it could free up additional engineering time to add further value to the machine, perhaps with more sophisticated features and functions.
Self-contained function blocks
The key, then, lies in making the enabling tools more accessible, so that engineering teams spend less time writing software from the ground up, potentially having to start from scratch for each new project. It is exactly this requirement that Omron has addressed with a new library of function blocks with a focus on self-diagnostics. These pre-written, pre-configured and pre-tested function blocks speed up the programming of advanced functions such as self-diagnostics. Proven and robust, they offer the ability for machine builders to implement such features as they go along. Further, by being modular and reusable, the function blocks can be dropped into a design as needed, and then simply embellished to meet the needs of the specific application.
The function blocks make it simple to monitor the condition of devices such as pneumatic cylinders, sensors and servo drives/motors that can cause intermittent machine stoppages. Offering the ability to detect the deterioration of operation over time, or providing reasons by error messages from devices, it eliminates sudden machine stoppages and improves operating efficiency.
For example, a function block could be implemented to monitor an actuator’s operating time. If a positioning task is not completed during a specified period of time after the ‘go’ signal from the machine controller, a warning could be flagged up of an impending problem.
As another example, the ability to monitor servo torque profiles – knowing what the ideal should be and triggering alarms as these values drift out of tolerance – again gives maintenance staff ample time to investigate emerging problems before they become real issues. Omron has developed function blocks for exactly this, and set up is a simple teach routine, with the controller taking care of everything else from that point on.
All of these examples give end users the ability to implement a wide range of strategies to deal with problems and optimise availability. It might be a case of fixing a problem immediately before a catastrophic failure brings the line to a halt. In this case, the status of devices before and after the occurrence of an error can be stored on a memory card or to a connected SQL database. This allows the user to identify any underlying cause of the error after the equipment is restarted. Or it might mean simply running the machine a little slower, so as to keep production going until the next schedule maintenance period – maintaining quality albeit at a lower output rate.
Importantly, the function blocks enable machine builders to program not just high or low alarms, but also variable bands and thresholds with different levels of warnings, giving operators greater intelligence to make genuine production-relevant maintenance decisions.
Further, the same self-diagnostics function blocks that provide this necessary ‘in-the-moment’ information can also store and display historical information, with trend graphs that can be indicative of systems drifting out of tolerance, giving end users opportunities not just for predictive maintenance but also for continuous improvement.
The road to 4.0 utopia
When we compare this with the paradigm of Industry 4.0, where machines will have intelligence to make their own production-based decisions, we can see that the levels of self-diagnostics enabled by the likes of Omron’s function blocks are an important step along the path. And because all of this functionality is available within Omron’s standard portfolio of automation products, it represents a future-proofed investment – both for the machine builders themselves and for their customers.
With accessible enabling tools such as these, machine builders have it within their grasp to develop machines with significantly increased capabilities, but without incurring significant programming effort. It means, at last, that sophisticated functionality such as advanced self-diagnostics can be implemented as standard as part of the machine design process, helping to deliver a real competitive advantage.
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