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CONVEYORS & SORTATION

The CSS perspective: Smart conveyance and predictive maintenance

Experts from the conveyor and sortation industry share how new technologies built into today’s sophisticated systems help identify maintenance issues before breakdowns can happen.

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Roundtable Participants:

Brandon Willard



Brandon Willard, Strategic Growth Leader MH&L, Banner Engineering
Ty Keller


Ty Keller, Director of Engineering, FMH Conveyors
Doug Schuchart


Doug Schuchart, Global Intralogistics Manager, Beckhoff Automation


Like many technologies, conveyors and sortation systems become more sophisticated with every iteration. Sensors are now built into them to monitor performance so that they can operate more efficiently and economically, while predicting maintenance needs well in advance to allow the work to be done when it’s most convenient.

Group Editorial Director David Maloney recently met with three experts who are all members of MHI’s Conveyor and Sortation Solutions Group (CSS), an industry organization that brings equipment and systems suppliers together with end-users to collaborate and address common challenges and opportunities. What follows are some excerpts from their discussion on how these newer technologies are impacting operations. 

Q: One term used to describe some of the intelligence built into today’s conveyors and sorters is smart conveyance. How would you define that for our readers?

Doug Schuchart – Beckhoff: When I think of the term smart conveyance, I think of it referring to multicarrier transport systems that use linear or planar motor technology. Linear track systems have the coils of a motor in a track. In this technology, you’re energizing those coils to move magnetic carriers around in a material handling system.

Planar motor technology is actually very similar, but those coils are in a base of flat tiles, and then the magnetic mover is levitating and has 6 degrees of motion that can move with virtual tracks around the base.

And then there are motorized driven roller conveyors, or MDR, that have motors within a roller to drive the conveying surface. What makes these technologies smart is that we’re able to pull a lot of data through those systems back to the central controller.

Ty Keller – FMH Conveyors: There are several types of equipment that complement the components Doug mentioned, that I would consider part of a smart conveyance system: equipment used for scanning, labeling, measuring, machine learning, or performing any number of actions to collect data for the central controller to turn into inputs for the smart conveyor. Then the smart conveyor takes the product where it needs to go.

Q: Do the same technologies associated with smart conveyance also apply to sortation systems?

Doug Schuchart – Beckhoff: Yes, these technologies can also apply to sortation. For example, what makes planar motor technologies really compelling is that they can replace multiple pieces of equipment in a fulfillment operation. So when we’re looking at material handling for conveyance, sortation, or accumulation—all of those can be handled with planar motor technology.

All of these technologies that we’re talking about are generally controlled with a fieldbus that can capture data from the system and then send the data to the centralized control system to be analyzed. The data can also be sent to the cloud to do further analysis and then make some decisions. And maybe you’re applying some artificial intelligence (AI) to the system for predictive maintenance or better optimization of paths, for instance. All of those would be ways to make the system smarter.

Q: Speaking of maintenance, can you give some examples of how these technologies can help prevent downtime?

Ty Keller – FMH Conveyors: It allows the user to monitor the usage of equipment, to know the exact number of hours in operation and the environment that the conveyor is working in. It can also read things like vibration, temperature, and pressure to help predict when the equipment is going to have issues. If we’re maintaining it appropriately, the equipment will last longer.

This information can also be used to determine preventative maintenance contracts with outside third parties. With the right technology, those contracts can be based on when it is best to perform preventative maintenance instead of a regular maintenance schedule. That’s obviously a more attractive return on investment for the end-user.

Brandon Willard – Banner: There are really four types of maintenance in my mind. There’s reactive maintenance, which is something is broken and we have to go and fix it—the motor is down and that critical conveyance is creating an issue for us.

There’s preventative maintenance, which is scheduled, regularly performed maintenance to reduce failures and is a great step up from just reactive maintenance.

The next step is predictive maintenance, which is using sensors and software to be able to predict failure. It is collecting data to be able to understand when a failure is about to take place so that you can act before it creates downtime and expense.

And then there is one beyond it, which is prescriptive maintenance. This is taking that data and using machine learning to be able to predict failures and identify solutions. If you can take that data that you get from predictive maintenance and use it to service the equipment optimally, then you’re able to extend the life of this type of conveyance. That’s where the value lies.

Q: Can you provide an example of how that might work using smart conveying systems and creating a prescriptive maintenance program?

Brandon Willard – Banner: We could look at vibration data, temperature data, pressure data, and how much electrical current is being drawn. We first want to baseline what that machinery looks like when it’s operating functionally. Then when we see a sharp curve compared to the baseline, we know when a product is about to fail. Sensors on bearings may detect vibration in multiple directions, while other sensors show increases in temperature resulting from rubbing or tearing on a belt or something else that is going wrong. Those vibrations or higher temperatures usually start to spike pretty quickly.

Then applying machine learning, the systems can give a warning threshold. For example, the belt may be rubbing on one side. All we need to do is re-center the belt. Nothing really has to be replaced, but the alerts allow you to check before the belt tears all the way and you’re not able to re-center it. Different warning levels and alerts allow you to protect your assets more efficiently.

Doug Schuchart – Beckhoff: I think we’re talking about a lot of different benefits, such as a reduction of manpower in the facility. We’re also talking about improving reliability and quality of a system. All of those things provide different advantages collectively. We talk to customers about that whole ROI and why you would want to invest in a more automated smart system as opposed to some traditional systems that don’t have that technology.

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