3 Ways IIoT Will Impact Your Operations

Visualization of sensor data gives you the ability to target maintenance procedures based on data rather than assumptions. In many legacy production systems, maintenance was “reactive” and occurred only when a problem had already caused downtime and scrap. A machine was installed, run until it stopped working, and then repaired. This cycle was repeated until the machine was eventually scrapped and replaced.

Today most maintenance is “preventive,” but requires technicians to have a preset maintenance schedule or “route,” whether machines need maintenance or not. This heavily manual process is successful in preventing many failures, but there are still downsides. Maintenance technicians spend unnecessary time and often incur travel expenses, performing unneeded maintenance too early. In some cases, this type of maintenance scheduling can even create problems, such as if the technician accidentally assembles something incorrectly, introducing a fault that wasn’t there before.

“Predictive” maintenance is the next evolution in reliability. With this method, IIoT data lets reliability groups make data-driven decisions about what assets to service and when to schedule maintenance.

IIoT systems from Banner Engineering (such as the Vibe-IQ vibration analysis software and hardware) have algorithms running at “the edge” of the factory’s network (i.e. near the source of the data). These algorithms automate the process of identifying machine performance trends.

An asset’s gradual condition decline is identified long before it becomes a problem, and maintenance can be scheduled to bring equipment up to spec. In addition to identifying performance trends, condition monitoring systems can also send alerts to maintenance team phones and desktops if a problem is growing worse over time, or if an instantaneous fault occurs.

Predictive maintenance offers one of the quickest returns on investment for IIoT applications. It allows facilities to prioritize technician time on the things that will make the most impact on the business. It’s extremely simple to add a condition monitoring system to an existing process. And among the various applications for IIoT, predictive maintenance is among the fastest to give facilities a return on their investment by eliminating costly downtime. The elimination of even one occurrence of downtime typically more than covers the cost of sensors and monitoring equipment.

Production managers must schedule people and raw materials, meet production targets, and ensure they’re not holding too much inventory.

IIoT technologies give visibility to the plant floor, letting managers make decisions about productivity and scheduling that are based – not on assumptions -- but nearly real-time data.

Data historians of the past helped organizations track production over time, spotting trends and patterns in production history. By making production data available in an IIoT platform, facilities speed the feedback loop to front-line operators who can make decisions with better context. Instead of looking backward to past weeks or months, IIoT lets you see what you produced in the last hour, every hour.

Production tracking tools, such as Banner’s PPM Kit (Production Performance Monitoring Kit) track production to identify sources of reduced output in production lines. Sensors at each stage of the production process count parts that move by and alert users to extended slow or stopped conditions. By measuring individual line speeds and part counts and comparing them with ideal user-set conditions, these tools give operators insight into their performance and data they can use to identify and remove bottlenecks in production.

IIoT systems let users see data from multiple facilities, so they can identify patterns and make correlations that they couldn’t make, if looking only at a single point. By using the combination of features a robust IIoT platform provides, facilities can improve production with better visibility and accountability across all areas of the business.

IIoT platforms also make data available to analyze and correlate with other business systems like sales data, financial information, and other manufacturing processes. This lets companies begin the journey towards “big data” and makes advanced analytics possible. A good IIoT platform will offer tools for getting immediate value from the data on the first day, while also making that data accessible to other analytics tools to build more complex datasets as your digital transformation evolves and matures.