AI-Driven Predictive Maintenance: How Printing Technology Became Smarter Than Ever

Imagine if your car could predict exactly when a part is about to fail—not just based on mileage but on real-time driving conditions, engine performance, and environmental factors. That sounds very convenient; uncertainty about when to change the oil or replace a belt is essentially gone because your vehicle would be capable of pinpointing the exact moment it needs replacing. In this scenario, there would be no need to rely on routine vehicle checkups, scheduled servicing, and parts replacements before they wear out.That is an example of the shift from preventive maintenance (PM)—where a set schedule is followed to reduce the risk of failure—to predictive maintenance (PdM)—where real-time data from your device’s sensors diagnose themselves by anticipating failures before they happen.

Now, imagine how much you’d save if your printers could do this.

Welcome to the world of PdM: a game-changer in the printing industry where AI, IoT, and machine learning are revolutionizing how organizations maintain their equipment for peak efficiency and cost-effectiveness. Amazing, isn’t it?

IoT Organizes PdM, But What Enhances It?

Predictive maintenance wouldn’t be as effective without the fundamental technology: the Internet of Things (IoT).

Many modern copiers are multifunction printers (MFPs), which can connect to the Internet and to which other devices can connect to. Using the Internet, IoT bridges these devices upon connection and allows the exchange of important information.

For a concrete example, in a situation where your printer’s ink is running low, tiny sensors would store this data and display it on your phone or other connected devices using the IoT. This immediate transmission of vital information means that your printer can warn you early on before it needs maintenance.

IoT allows for communication across a network of devices, but what enhances the data being interpreted across all fronts? What automates this process, all the while improving the self-diagnosing capabilities of MFPs? The answer is actually fairly simple: artificial intelligence (AI).

The Role of AI in PdM

AI has been transforming printer maintenance in various ways, from data analyses, where AI algorithms sift through massive amounts of data from printer sensors, to independent decision-making where AI makes informed decisions about when maintenance is needed and what parts need replacement. For printers, AI usually takes the form of machine learning, in which its algorithm is trained on historical data on printer performance to recognize patterns and their indicators.

Machine learning models improve over time as they are exposed to more data. Recently, as the AI industry continues to grow at a fast rate, there have been several key advancements that make predictive maintenance even more effective.

One such example is Deep Learning, a method where machine learning uses layered artificial neural networks that are inspired by the human brain to analyze a lot of complex data. This makes anomaly detection for printers much easier because deep learning models are trained on vast amounts of sensor data from printers being used. All that data is then synthesized and harnessed to identify potential issues before they occur.

Another key advancement is Natural Language Processing, where, fascinatingly, AI systems understand and interpret human language. This helps analyze printer maintenance logs to identify recurring issues, common failure points, and areas of improvement. All of this information enables service providers to address various printer requirements.

How Major Brands Adopt These Updated Predictive Maintenance Solutions

Of course, considering the evolving landscape of technology, leading printer brands have begun adopting these latest advancements. Here are some major brands that deliver better maintenance solutions:

1. Canon
   Recently, Canon’s imageWARE Enterprise Management Console (iW EMC) has significantly enhanced its AI-powered toner management, allowing for further data-driven decision-making. Not only can iW EMC reboot machines remotely as it always did, but it now incorporates machine learning models trained by the encompassing data from thousands of Canon devices.
   
   As a result, Canon printers can deliver:
   
   • faster printing
   • better troubleshooting
   • more effective predictive maintenance
   This is because accurate toner predictions lead to fewer unexpected print interruptions due to empty cartridges, and better machine learning models would lead to more accurate detection of any problems.
   
   
2. Kyocera
   Kyocera uses the Kyocera Fleet Services (KFS), a comprehensive printer management platform that maximizes print resources through a centralized location. This platform has advanced analytics dashboards providing printer usage visualizations and corresponding environmental impacts.
   
   With its platform, KFS:
   
   • enables faster printing
   • manages multiple machines
   • performs toner management for predictive maintenance
   Not only does KFS enable printer management in multiple sites; it also promotes cost-effectiveness by reducing the need for multiple maintenance check-ups. Although this feature has been present even before, Kyocera upgraded it and now provides detailed diagnostics and remote firmware updates that can help resolve proactive issues.
   
   
3. Xerox
   Xerox printers feature the ConnectKey Technology, which, in the past, was mostly about automating print-related processes through cloud-based operations that allow users to create electronic documents. Recently, however, the company took its AI-driven diagnostics to the next level.
   
   Now, it can automatically resolve paper jams and reduce print quality defects. Alongside toner alerts, this means that Xerox copiers can now:
   
   • use effective troubleshooting technology
   • automatic problem-solving abilities
   • perform proper predictive maintenance
   Xerox is a great option if you’re looking for self-solving printers with efficient AI-driven diagnostics to minimize user intervention.
   
   
4. Konica Minolta
   Last but not least, Konica Minolta offers a predictive service called bizhub vCare, which enables simple component monitoring, automatic meter reads, and cloud-based operations. Now, with predictive maintenance, this service also monitors each component extensively, such as drums, developer units, and even the fusing units.
   
   Konica Minolta takes predictive maintenance to the next level by analyzing stored data (about the papers being used) and environmental factors (such as temperature and humidity) to estimate the lifespan of these components. As a result, Konica Minolta printers now:
   
   • encourage smart spending
   • minimize downtime
   • increase printer lifespan
   Hence, with its emphasis on durability, Konica Minolta remains a key player in the print technology market.

What Comes Next?

We’ve discussed how print companies are taking steps forward to evolve their copiers and deliver more significant continuous-user benefits. The question now is: how will you access this?

If you want to incorporate predictive maintenance into your printers, look no further than SumnerOne. Our team of friendly print specialists will guide you in upgrading your printers through tailored solutions designed specifically for your needs.

Who needs printer check-ups when the printers themselves can do it? (And when you need help, you may easily submit a service request or order supplies on our website.)

Ready to enjoy the benefits of predictive maintenance? Contact us now and tell us about your print requirements!