Toiling away in every imaginable industry in every corner of the globe, the intelligent, sensor-equipped Lexmark devices that customers ask us to manage are continuously generating the data we need to make our products stronger, better and more reliable.
This powerful application of big data analytics expedites problem resolution, reduces unnecessary service calls, and maximises uptime. For R&D, it also drives deeper understanding of product operation and improves future product design.
Sensors and algorithms: What we Learn
Job sizes
Though many Lexmark product tests were built on the assumption that customers’ average job size was three pages, sensor data indicated that managed print services users were actually running more one-page jobs. Based on this data — and the technical implications of single-page output on device performance and wear — we can better understand how Lexmark devices get used, and design and test products to meet real customer needs.
Device usage patterns
Without data, manufacturers can only estimate how frequently customers actually print. With managed print services data, we can now see a distribution of how many pages per time period customers actually use their printers, and determine averages. This assists in developing appropriate testing protocols and ultimately designing devices to fit real-world scenarios.
Sensor sensibility
One customer’s device reported a high number of paper-jam errors, leading the field service team to investigate. They discovered it wasn’t really paper jams, just an empty paper tray. The “paper out” message wasn’t showing up due to a bent sensor, driving a change in product testing to include running trays empty and confirming that the proper “load tray” message appears.
Grasping the gap
The product development process includes monitoring the gap between pages, an indicator of wear and other inherent variability in the paper path. Being able to monitor whether the gap between the pages is narrowing or widening over time allows Lexmark engineers to control paper-feed motor speed via software in order to maintain a consistent throughput rate for the device, for predictable performance throughout its lifetime.
Toner mystery, solved
When some users reported running out of toner without warning, it initially appeared that toner cartridge sensors were failing to detect low toner levels. However, other system sensor data allowed Lexmark engineers to trace the cause of unexpected run-out back to failing system cards or defective cables, thus clearing the suspect toner cartridges of any actual problems.
Torque tech
Sensor data reflecting fuser motor torque can provide early clues about fuser wear and the likelihood of upcoming failure, prompting support personnel to perform preemptive component replacement. Combining such torque data with a known increase in paper jam errors can even point to defective imaging units, again allowing replacement before complete failure occurs.
It's not magic. It’s based on Lexmark's expertise and experience with artificial intelligence, machine learning and big data analytics.
The key is our ability to capture and interpret millions of data points collected from sensors on Lexmark-managed devices around the world. Taking action to keep our customers’ fleets at peak performance is a big advantage of Lexmark Analytics, but it’s not the only one. Ultimately, the point of listening to our devices out there — and making sense of the data they collect — is to gain insights that drive product improvement in here, helping us make products that work better and last longer…extending your investment.
That’s intentional engineering, only from Lexmark.
