Maintaining Momentum

Technology is enhancing boxmakers’ approach to equipment maintenance, improved efficiency, and real-time data analysis

In the words of Jeff DeVries, president of dryer and ink management equipment manufacturer XericWeb Drying Systems (XDS), “If you can keep your equipment running effectively and efficiently, you’ll ship boxes that cost you less to make, and you’ll meet on-time order schedules. It’s not rocket science. It’s just paying attention to the details.”

Managing those details, though, can be challenging as equipment advances, employees come and go, and customer expectations rise. As a result, DeVries says, “my general experience is that the majority of our customers operate from the perspective of ‘We’ll fix it when it’s broken,’ rather than focusing on preventing breakage in the first place. I don’t believe that’s due to negligence. It’s just that in many cases boxmakers are running lean, and there are fewer and fewer resources—people and time—for preventive maintenance on equipment that seems to be running fine. That’s where I think we machinery people can help, providing tools to optimize their available time and get the best performance out of their equipment.”

From Manuals to Microchips

In the past, recommended maintenance schedules typically were presented in printed equipment manuals. At XDS, that included a recommended planned maintenance (PM) schedule and a blank chart customers could fill in to track what was being done and when. In reality, these tools were rarely used. “If I visited a customer five years later, that chart would likely be empty,” DeVries notes.

This situation is common. The need for more effective maintenance solutions has given rise to a number of problem-solving technologies, many of which are based
on a collection of general business applications known as Industry 4.0 and Industry 5.0.

“Industry 4.0/5.0 seeks to optimize the manufacturing process through the integration of digital technology, including artificial intelligence,” DeVries explains. “So we began looking at how we could use Industry 5.0 tools—greater digital connectivity, improved analytics, machine learning, and artificial intelligence (AI) applications—to help our customers improve their overall operation as well as improve the maintenance of the equipment that leads to better operation.”

One immediate advantage has been the ability to tailor maintenance to actual machine needs rather than an arbitrary schedule. It’s a process DeVries calls “actively managed maintenance.”

“Historically, our PM guidelines said things like, ‘Every two weeks you clean this. Every six weeks you do this.’ The guidelines were the same for every use case, whether you used the equipment a lot or very little,” he says. “Now, we’re building tools into our control software that look at how the equipment is being used, allowing our customers to focus on when things need to be done based on actual usage.”

The digital nature of these tools means large amounts of data are being captured that allow for detailed analysis, comprehensive reporting, and informed decision-making. “We’re able to create reports that automatically can be distributed to the right people and stress what needs to be done on the basis of urgency,” DeVries says. “We can tell you how long certain maintenance will take so you can better schedule it into the workday and even provide videos that can walk someone step-by-step through the process. We log the actions when they have been done and can distribute reports on the process, including the parts used and recommendations for future parts stocking. We’re also able to associate costs with this kind of maintenance; we can specifically point out to a customer that by doing this $150 worth of maintenance they saved themselves $2,000 in repair costs. These tools are helping people make smart decisions in situations where they simply don’t have the time, the staff, or the skill set to be able to do that effectively.”

Teamwork Makes Machines Work

At Royal Containers, Continuous Improvement Manager Mohamed Azzouz is constantly on the lookout for opportunities to enhance or improve efficiencies, safety, and overall work conditions in the plant. “The work varies from improving a process to physical improvement at a machine center to get better at what we do,” he says. “Even small improvements can make a huge impact on our process over time.”

When evaluating potential adjustments to current equipment, his discovery process often begins with an investigation that analyzes the production process, measures overall equipment effectiveness, and then determines the extent to which that particular machine could be improved. Then, he may organize what are known as kaizen events, small-group gatherings where employees spend a focused week or two working as a team to explore ways to improve a well-defined and limited-scope project. “The scope is limited by design to make sure we don’t get too ambitious and try to improve everything at once,” Azzouz says. “If you try to do everything at once, you end up not achieving any of your objectives.”

Some changes can be implemented immediately after the event. “For something that requires a longer process, we come up with a list of recommendations to our maintenance team, or if we need to get a new piece of equipment or upgrade existing equipment, then we have to submit a proposal and justify the expense. We try to use existing resources and critical thinking to get around inefficiencies and challenges. Nine times out of 10 we’re able to make a significant impact without spending money,” Azzouz says.

One particular lesson Azzouz has learned after overseeing many improvements is that while each new piece of equipment or each improved process may deliver efficiencies of its own, any changes you introduce likely will affect workflow and potentially create a bottleneck somewhere else. Each piece of equipment plays a part in your overall production and needs to be managed in relationship to the entire plant. “We need to focus on global efficiencies,” he says.

The pursuit of global efficiencies is leading some manufacturers to seek similarly holistic technological solutions.

So Long, Silos

At DeLine Box & Display, Jeff Putt, managing director of digital services, notes that the company has been using various separate platforms to address the company’s equipment and personnel needs. “Because we don’t yet use sensors on our machines, maintenance is based on scheduling rather than what might be happening within the equipment,” he says.

For that, DeLine relies on a cloud-based platform called Fiix, which manages service records, inventories, and purchase orders. “It’s a tool that lets us know what we should consider replacing and changing. It isn’t predictive maintenance; it’s preventative,” he points out.

In addition, employee training relies on the web-based Dozuki application. Salespeople are using a bespoke workflow automation program that manages project information, including sales, design, and customer-service functions. The company is developing a new customer relationship management application, which will provide sales analytics to help the sales team make the most of their interactions with customers and prospects.

“All of these are tools great,” Putt says, “but they don’t talk to each other. That minimizes our ability to get true insights out of all this data we’re gathering. Ideally, we want to be able to take that data, analyze and clean it, and develop a dashboard that collates it into a real-time management system. We need to move away from these separate silos, connect our disparate processes together into a more integrated data-warehouse environment so they can be useful in real time. But I think we’ve got at least three or four years ahead of us to develop a useful system.”

It’s a process with inherent challenges. “Whenever you start sharing data between applications, across company departments, with a variety of different suppliers and their equipment, the concern is that someone’s going to hack in and take the whole network down,” acknowledges DeVries. “That leads to reluctance to share information. We’re trying to help customers—and, through them, other manufacturers—see how technology can add value and provide a return on investment for our customers so they can benchmark their practices and see for themselves that these kinds of tools are worth investing in.”

For boxmakers, the advantages of cooperative data exchange are numerous. “Once you have connectivity across the system, you can have a dashboard, a window into real-time events. You can see what’s happening, what needs to happen, and what’s liable to happen,” Putt says. “You can also utilize tools like generative AI and machine learning to give you insights that are deeper than what’s on the surface. Ultimately, you’re going to be able to access data in a timely way so you can utilize it in a timely way. No more waiting until the end of the month to get any real data from your enterprise resource planning [software]. Once the month is closed, it’s too late to do anything about it; all you can do is look in the rearview mirror.”

AI = Real Opportunities

AI based on machine-learning applications is destined to play a significant role in data-driven decision-making.

“Data analysis is where AI software can really benefit a box plant,” Azzouz says. “We’re all collecting all kinds of data from the jobs we run. The challenge is the analysis. You can train an AI model to do that for you, instead of you having to go line by line trying to figure out how efficiently you’re running your production. Once you know what to target for improvement, then you can confirm through direct observations. AI is a game changer for both continuous improvement and operations.”

Gokul Gopakumar, vice president of technology and business development at SUN Automation Group, says, “I think AI will affect every department and be a part of every operating function within a box plant. Currently, it’s going to be most effective where an infrastructure is already in place to support it, and that typically means around scheduling, planning, and supply chain logistics as well as predictive equipment maintenance. These are areas where we have seen a lot of investment and a lot of success in other industries, which translates effectively to boxmakers.”

The extent to which AI can help improve a boxmaker’s efficiency is going to depend, in part, on the boxmaker’s size. “Bigger operations will have more operational intricacies, more places where efficiency improvements can bring bigger rewards,” Gopakumar points out. As a result, “it may not be cost-effective yet for really small operations.”

Gopakumar believes boxmakers should keep two key factors in mind as they explore the benefits of AI. First, he says, “box plants have to reconsider the talent they hire. There is great value in bringing in people who have specific software skill sets,” tailored to making the most of what AI has to offer. Second, understand that AI requires an investment, whether a plant chooses to manage everything on their own—investing in development resources, new computer hardware, and so on—or to use existing suppliers to provide some of the AI infrastructure and the required data connections.

“AI is about augmenting and improving people’s ability to be effective and efficient,” Gopakumar sums up. “When it’s implemented well, it empowers more people to do things effectively, provided they have the acumen to learn how to work with it.”

Never-Ending Journey

For better or worse, the learning process and the accompanying pursuit of maximum machine performance and efficiency will never end.

“Continuous improvement is just that: continuous, ongoing,” Azzouz says. “We will never reach a level where everything is running as smoothly as possible and everyone is completely satisfied because the world is constantly changing. No matter how efficient our current processes are, they will change as we add new equipment, develop new products, and respond to new customer requests and market demands. Nothing stays static. And if nothing stays static, you will always have work to do.”

Robert Bittner is a Michigan-based freelance journalist and a frequent BoxScore contributor.