The corrugated industry has long been at the mercy of the maintenance of the machines that make it hum. When operating at full capacity, corrugated manufacturers are extremely lucrative and powerful, thanks to the speed and efficiency of the machines. And with the popularity and continuous growth of the e-commerce vertical driving the need for corrugated output, the ability to keep pace with the market is extremely important to manufacturers keeping their clients happy and their orders rolling in. But when there are breakdowns or other unforeseen maintenance issues, money is lost and profit margins (and client relationships, potentially) are compromised by the minute. There are general manuals about when routine maintenance should take place and esoteric knowledge that belongs to experienced operators and technicians, many of whom are rapidly approaching retirement age. Even with this insight and experience, largely the day-to-day has always been a series of calculated risks and hoping for the best. But Predictive Analytics is changing everything.
Thanks to Helios, the Corrugated Industry’s Machine Learning and Industrial Internet of Things (IIOT) Platform, we have achieved unprecedented levels of predictive analytics that will make unexpected downtime a thing of the past. Helios, which retrofits seamlessly and agnostically to existing corrugated machines, is providing predictive analytics that can supercharge any corrugated operation. Here are four ways that predictive analytics will change corrugated forever:
- Improve Uptime by Predicting Issues Before They Happen
By analyzing thousands of data points per second, Helios is able to see patterns in machine behavior and performance that are otherwise undetectable to even the most experienced maintenance professionals. These behaviors, which may take the form of idiosyncrasies, vibrations, noises or shudders, are monitored and analyzed by machine learning to create patterns and draw conclusions about potential downtime with high accuracy and very short lead time. The Helios platform is able to accurately predict 3 out of 4 instances of impending downtime within 30 minutes of an incident, and it gets smarter, faster, and more accurate every day as it takes in more data. This information has a number of crucial applications for corrugated operations, including preemptive adjustments to avoid issues, scheduling maintenance around non-peak hours, and prioritizing and triaging maintenance work based on urgency. - Parts Ordering
Sourcing and replacing parts can be extremely expensive, especially when rush delivery is required. This matter is exacerbated by supply chain issues and other restrictions in the aftermath of COVID-19. The cost of the part and its shipping is only the beginning though–if there is an unexpected breakdown, the downtime associated with waiting for the part to be delivered is costing the operation money through lost productivity. But thanks to the predictive analytics available through the Helios platform, parts ordering can be done for you by using predictive analytics. Currently, Helios provides a burndown chart listing the various parts, ranking them according to urgency and timetable for replacement. This means that parts can be ordered weeks or even months in advance of the replacement need, in anticipation of breakdowns. And future capabilities will even allow Helios to place orders automatically for parts in need of replacement based on these predictive analytics. - Optimize Training and Stem the Tide of the Silver Tsunami: One of the biggest challenges facing corrugated, like other manufacturing industries, is that many of the people with the know-how regarding intricate corrugated machine maintenance and oversight are nearing retirement age. There is a lack of the critical influx of the next generation of employees necessary to replace these people as they retire. And even when there are new people phased in, there are certain bits of insight regarding maintenance and performance that come only with experience. With a lack of documentation and turnover processes in place, these new technicians are being set up for failure. However, with the incorporation of Helios, the intelligence lies within the machine learning software and its predictive analytics that can identify, diagnose, and remedy problems. This insight means a shorter or even non-existent learning curve and no knowledge gap for people replacing retiring corrugated machine specialists. This ultimately means that the insights and information through the predictive analytics platform of Helios are able to be delivered to operators and technicians so that they can perform with the power and insight of someone with far more years of experience.
- Unprecedented Levels of Transparency and Insight into Machine Performance: There are many factors that impact the levels of performance of a corrugated machine and its optimal output. But in a traditional machine, with so many moving parts, it is tough to know if a machine is producing up to capacity, or if money is being left on the table due to suboptimal machine performance. Furthermore, short of looking at the machine itself, it is impossible to know what might be impacting productivity. But when machines are equipped with Helios, technicians have access to real-time statistics about production volume. This information, when coupled with machine performance data and predictive analytics, can lead to insight into how effective these machines are performing. Helios will also be incorporating Overall Equipment Effectiveness (OEE) data, showing how many boxes are being produced by the machines, relative to the optimal capacity, which can help indicate where and how improved performance and more profit can be eeked out of the machines. Through the Helios platform, the data that is harvested is accessible virtually from anywhere, offering insight to your stakeholders and decision-makers anywhere around the globe.
Learning more about how Helios can optimize your corrugated organization’s uptime and maximize your profits.
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