Recent trends show that more and more manufacturers are looking to expand in the US or move capacity back from overseas. To do this, companies will have to look for new, smarter ways to improve performance, increase machine reliability, maximize workforce effectiveness, and increase uptime. Informed decisions must be made at every level – production, maintenance, purchasing, engineering and IT.
Thanks to the advent of predictive maintenance applications and the ubiquity of IIoT-enabled devices, most manufacturers are turning to predictive insight to figure out what will happen next. However, having data isn’t always the same thing as having the right data, and in order to truly move a maintenance program from reactive to predictive, it’s critical to understand the value of reliable data, how to track it, and how to use it.
Identify Your Goals
Decide if your goal is to increase output or decrease equipment wear. Then, determine which machines you need to collect data on to meet those goals. Depending on the importance of the machine, you might want to collect data more often. High-speed, critical devices should be monitored continuously. The data required can vary depending on the type of machine. Temperature, ultrasound, and vibration data, or a combination of any of these inputs, can provide valuable insights.
Devise a Data Collection Workflow
Figure out how data will be collected and how often. Online solutions provide the most consistent measurements as they can be automatically fed into your data collection program. Manually collected data is collected less frequently and is time-consuming. Save time and money by ensuring your staff is only collecting data that is relevant to the machines you are monitoring and the goals you’ve established. The data must be provided automatically from control systems that can consistently feed machine health data in real-time, or near real-time, to effectively monitor machine health.
Master the Industrial Internet of Things (IIoT)
IIoT devices are the primary conduit for all of this data, which is why some estimates predict the IIoT industry could contribute as much as $14.2 trillion to the global economy by 2030. However, manufacturers have also identified a skill shortage of data scientists as an inhibitor to harnessing the full potential of machine analytics. Currently, 50% of manufacturing professionals report that their plant staff fail to recognize the full potential of IIoT predictive maintenance. With the costs of technical tools such as smartphones, laptops, and tablet computers dropping every day, there’s never been a better time to get your staff trained. The combination of a well-implemented predictive maintenance software package and high-quality, consistent data can help any predictive maintenance program achieve its goals.
Are you and others in your organization getting the data you need to make informed decisions? Contact the professionals at GTI Predictive today to find ways to add high-quality, consistent machine health data to your predictive maintenance program.
About GTI Predictive Technology
At GTI Predictive Technology, it is our mission to provide the best predictive tools on a single iPad platform with services to monitor nearly any asset. We strive to bring our customers the portability, connectivity, and affordability offered by the latest available technologies. Our product family combines wireless portable and online vibration data collection and analysis, balancing, shaft alignment, thermography, and ultrasound into an affordable and completely scalable solution on one simple to use platform. GTI’s predictive technology apps feature many additions that have come directly from customers. Click here to learn more.