In recent years, pharmaceutical packaging machines have become more intelligent, and in some ways, more “human.” They use more decentralized, intelligent “sensing” to protect the machine from expensive breakdowns. They diagnose errors and react without requiring commands to pass through the controller.

Intelligent servo drives now use electronics with built-in predictive maintenance monitors. They track machine performance and maintenance thresholds (the “nerves”) to provide drive-based automated diagnostic and motion control functions and protect the machine throughout its entire life cycle (the “reflexes”).

For pharmaceutical and healthcare packaging operations, predictive maintenance can prove highly valuable. The industry demands high levels of machine reliability, availability, throughput, and packaging precision. Machines that package pharmaceuticals, surgical instruments, and medical devices (pacemakers, earphones, and so on) are typically optimized for 24/7 operation. Because the products are expensive, extremely accurate, low-waste, high-throughput packaging is standard practice. When machines need frequent adjustment and repairs, they waste time and money.

Immediate Protection for Drives and Axes
A wide range of pharmaceutical packaging machines can benefit from predictive maintenance. This includes vial-filling machines for liquid injectable medications, capsule filling machines, blister packaging for solid medicines and trays, carton and case-packing machines for surgical kits and medical devices, and other products.

Drive-based predictive maintenance works best by streamlining the information exchange between the packaging machine controller and the drive actuators and sensors. That is why optimizing data exchange between the drive and the controller is a high priority item during the development of a predictive maintenance system.

This example of an intellegent drive monitors itself as well as feedback signals from the motor it drives. The parameters include torque, speed, acceleration, and several others.

Drive-based predictive maintenance can monitor mechanical characteristics such as backlash, belt stiffness, tension, load variation, and other conditions that are critical to the packaging machine’s operation. The intelligent drive monitors itself and the feedback it gets from the motor it is driving: Motor torque, speed, acceleration, and other parameters can be tracked. If these characteristics fall outside of the tolerance bands for that axis, the drive recognizes that something is wrong and takes the appropriate action in much the same way our reflexes “automate” our response if we bang our knee or touch a hot stove.

To keep the data exchange between the drive and its control to a minimum, the performance thresholds are pre-set in the drive, and fixed, corresponding target values are transmitted to the controller. For example, in a liquid filling machine, 10 vials are being moved down a single conveyor and need to be positioned under 10 nozzles for filling. The machine lowers the nozzles into the containers, fills them, then lifts them out and re-positions the nozzles for the next set of 10 vials. This highly repetitive “walking beam” motion sequence – down to fill, over to the right, up, back to the left, and down – has extremely tight tolerances for accuracy and throughput.

If a belt on the conveyor or a gearbox on the filler axis slips, then machine synchronization is lost, and it could crash or fill the vial improperly and waste the product. Since this slippage affects motor performance and the drive detects the variations in the pre-set values, the deviations can then be used for monitoring or analyzing the axis.

The predictive maintenance function in this drive detects abnormal variations, such as a slipping belt, to ensure that the machine remains in synchronization.

Preventing fatal errors before they kill
Not all reactions of a machine or a human being can be left to the slow response of the brain: the signal must go through a so-called reflex circuit. It is exactly the same in automation. The detection of a fatal error in the drive must lead to the proper reaction at the drive. For the electric drive itself, this is the current state of technology. With predictive maintenance, this protection is extended further to the connected axis mechanics, where additional reflexes have been included to protect the mechanical system or the entire axis.

For example, after a vial is filled and capped, a pick-and-place machine inserts the vial into a container along with a pamphlet containing prescribing information for the physician. If it jams during carton loading, the pamphlet insertion moves out of synch with the vial insertion: the vial or carton could be damaged and force the carton-filling machine to shut down.

Drive-based predictive maintenance can prevent these slips from growing into significant problems. It monitors the backlash between the servomotor and the axis mechanics the motor moves. The performance of the motor directly relates to the performance of the mechanics the motor moves. The drive monitors how the motor responds to the amount of play in the gears or the belt; if it falls outside the tolerances set for that axis, the drive intelligence can do one of several things:

• Generate a warning message to the controller or operator,

• Modify the drive current to compensate for the change in the mechanics, or

• Initiate a safe shutdown, to prevent machine and product damage before the situation gets critical.

Reflexes like breathing mean the preservation of life for humans. Similarly, a servomotor will not turn or fulfill its intended function if drives did not have something like reflexes. Intelligent drives, such as the Rexroth IndraDrive can stabilize a disturbance or noise of all types using the control loops in the drive. Quick and direct real-time access to all drive parameters makes faster reflexes possible.

Sometimes, a reaction in the drive can be triggered by multiple unhealthy or risky conditions. These can include an extreme condition signal (setting an input or initiating a command) such as a reverse movement after a collision, or the targeted initialization of an analysis function in the drive to detect the detailed axis status.

Similar to the human nervous system, complex information is prepared in the drive and translated into a simple diagnostic for the controller. This replaces sending all the complex information to the controller and taxing cycle times to have the PLC do the diagnosis. It is a more efficient controls’ architecture, since the communication required between the control and the axes is automatically reduced.

Bottle-filling sequences require tight timing and displacement tolerances, which can be monitored, analyzed, and flagged by the drive automatically before expensive errors can crop up.

Prediction depends on extended diagnostics
Wear-related machine breakdowns make themselves known ahead of time, and extended diagnostics makes preventive measures possible. With IndraDrive, Rexroth has structured preventive maintenance into three key diagnostic functions:

1) Maintenance Planner: Tracks time-specific maintenance intervals defined in the drive, to issue a warning, remind about upcoming maintenance activities, or execute a self-analysis.

2) Monitoring Function: provides expanded diagnostics, runs during operation and enables constant monitoring of the total axis status including the attached mechanics. It can also indicate a needed system analysis.

3) Analysis Function: Expanded mechanical analysis and comparison with “zero-hour-record” — the performance tolerances set in the machine at startup. In a separate test run, while using expanded analysis methods, a correlation between the error location and cause can often be determined.

In our carton-filling example, a motor connects to a belt, which drives a pusher to load the vial and pamphlet into the package. The toothed belt runs on a toothed gear driven by a servomotor. If excess wear and tear, high accelerations, or poor lubrication causes a tooth to jump on the belt, the vial and pamphlet will not be fully inserted in the package: It could jam.

Using extended diagnostics on this machine:

• The Maintenance Planner has a preset schedule that calls for belt tension adjustment every 100 hours,

• The Monitor Function is set to monitor belt stiffness, and based on motor feedback, it detects a loosening belt, and

• The Analysis Function compares that axes performance to the zero-hour record in the drive; if it falls outside the tolerance band for that motor, the situation calls for maintenance intervention to protect the machine and production.

Diagnostic messages can be displayed on the drive display, PC, control, or handheld units. To keep the communication requirement as low as possible while continuing to transmit the established standard communication mechanisms, the information related to signal processing is handled in the drive and therefore highly compressed.

“Zero-Hour” baseline is crucial
People who are concerned about maintaining good health usually get a yearly checkup, not because anything is wrong, but by having an annual baseline of their health, if an illness or chronic condition begins to develop, it can be checked against their original condition.

The same principle is true for machine health. Drive-based predictive maintenance must be built on capturing and loading into the drives the optimal performance of each axis at it’s healthiest: “zero hour” when the machine is completed commissioning, but before it’s released for production. Some tool builders and manufacturers hesitate to invest the time and effort to accomplish this, but it is investment that protects machine performance and practically guarantees to extend the machine’s operating life.

This investment is especially valuable for synchronized multi-axis lines. For example, in a robotic pick-and-place application, 12 robots place needles in a tray over a single conveyor (a row of six robots on both sides of a conveyor). Each robot is assigned an operating zone. If one robot slips a gear tooth, an out-of-position situation could develop.

Unless the drive has the “zero hour” tolerance band for that axis, it cannot recognize that the gear tooth slip could jeopardize the entire line. If the drive is monitoring the backlash, it detects when the tight coupling between the motor shaft and the gearbox shaft is malfunctioning. The drive’s reflex is whatever you define: initiate an error message to the machine controller, or perform a safe shutdown to prevent damage to products or other parts of the machine.

With Rexroth IndraDrive drives and motors, for example, your machine’s “nervous system” is reflexive and responsive. Predictive maintenance lets you monitor everything including motor speed, position, acceleration, torque, temperature, current, voltage, and frequency; everything that governs the healthy operation of every axis. Based on the parameters you set, intelligence in the drive keeps you fully aware of the health of each axis, predicts if that health is degrading, and lets you apply the right medicine before the damage grows severe. Predictive maintenance: It’s the ounce of prevention that’s worth much more than a pound of cure.

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Bosch Rexroth Corp.
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