Manufacturing success has always required the careful collection and analysis of data. Since the dawn of the Industrial Revolution in the late 18th century, shops have been performing increasingly sophisticated analyses of their operations to gain a competitive edge or develop new innovations. Indeed, the manufacturing handbooks and manuals found on workbenches and in front offices around the world can be seen as the final result of centuries of metalcutting experimentation and data collection.
Today, the rise of the Industrial Internet of Things (IIoT) has allowed manufacturers to collect more information than ever before – and reach new levels of process optimization – through real-time machine monitoring. Much of this can be seen as automating what was previously an arduous process in which production engineers collect information and analyze it by hand. But what truly unleashes shops’ productivity is just how much data can be collected and how quickly it can be distributed to help manufacturing professionals make decisions and create more efficient processes.
The latest machine monitoring solutions can collect vast amounts of information, both automatically via sensors and manually through operator data entry. The speeds, feeds, loads and tools of any given operation on any given machine can be recorded and timestamped for historical analysis. The raw data is then aggregated and fed back to the operators for instant feedback on performance for an individual job or shift. This can be particularly useful for operators who manage entire machining cells with the help of automation, allowing them to see notifications in real time, including alerts that draw on historical data to predict maintenance needs.
For a shop’s management, machine monitoring allows for more than just tracking Overall Equipment Effectiveness (OEE), it can make it far easier to maximize the productivity of an entire facility and its workforce. Aggregated data about part throughput and machine uptime can be cross-referenced with operator information to show which machinists perform the best at certain tasks, or which machine cells are best suited for certain types of parts. And for the utmost in quality control, operators can input the causes of workpiece damage to help shops identify when, how and why waste occurs to further increase throughput.
Perhaps the most valuable aspect of machine monitoring, however, is that it can provide clarity in terms of setup and machining times. Even modest machine shops tend to get busy enough that it can be difficult to track how long various tasks take. When these tasks are regularly taking longer than scheduled, it creates bottlenecks and inefficiencies that can be hard to spot in all the noise. With machine monitoring, management can instead see exactly where the disconnect is located, down to the exact machine and the operator in charge of it.
As with all manufacturing technology, modern machine monitoring has already grown by leaps and bounds. Today’s solutions don’t simply aggregate data – they automatically generate reports that digest the data into an easily readable form. Now, rather than spend time writing up reports or entering data into spreadsheets, production engineers and other shop managers can focus their attention on more difficult tasks, adding more value to their production. And with the additional time for process optimization, better machine utilization data and easier methods for identifying hidden bottlenecks, many shops will see their investment in machine monitoring solutions pay for themselves in a matter of weeks.
Author: Patrik Löfström
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