Efficient production and manufacturing depends on the harmonious contributions of multiple parties and machines. All must work together to ensure that production schedules are met and the quality of end products meets client demands. Despite operating within an industry where machine disruptions and delays significantly affect the bottom line, many companies continue to employ reactive strategies when managing production road blocks. It’s time to implement predictive maintenance strategies in the manufacturing process to save both time and money.
The goal of all predictive maintenance systems is the early detection of potential machine failures. Early detection allows maintenance teams to plan for repairs or change outs to minimize downtime. At the heart of any good predictive maintenance program are the vibration and ultrasound tools. Vibration will detect machine issues like unbalance, misalignment, looseness, etc. early enough that they can be corrected to prevent bearing failure. Once the bearing starts to fail, ultrasound will identify those faults first, and if uncorrected, will appear in the vibration spectrum as well. Trended to monitor machine health, these technologies work in unison to help in understanding what actions can be taken to correct the problem early while also predicting how much time is available to implement the necessary maintenance.
Technicians observe mechanical trends and data until an alert or alarm is received indicating a measurement has exceeded ISO acceptable vibration levels. At this point, trained analysts, online analysis tools, or remote third-party professionals can begin to analyze the collected data to identify and mitigate the problem before the machine fails and production downtime occurs. Once a problem has been identified problem, the data can be analyzed for a comparative analysis of like-machines to ensure the same fault is not present elsewhere. A complete Failure Mode and Effects Analysis (FMEA) should be performed to determine root cause and eliminate or prevent this fault from occurring in the future.
While detection and analysis are significant parts of the predictive process, correction is where real benefits and solutions are achieved, but determining when to intervene can be difficult. Here are some questions to ask before moving forward:
- Can or should production be interrupted to perform the repairs?
- What is the cost of repair and downtime if we run the machine to failure?
- When is our next maintenance outage and how long will it last?
After answering these questions and documenting the fault, it’s important to begin planning, accounting for the time it takes to acquire the proper parts and tools, and schedule certified technicians and millwrights to complete the task.
If implemented correctly, detecting, analyzing and correcting machine problems early can reduce maintenance costs by as much as 50% and increase uptime by as much as 30%. With predictive maintenance solutions becoming less expensive, simpler to use and ubiquitous, now is the time to employ predictive maintenance in your operations. Contact the knowledge professionals at GTI Predictive Technology to learn more and get started.
About GTI Predictive Technology
At GTI Predictive Technology, it is our mission to provide the best predictive tools on a single iPad platform and 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.