October 19-21, 2021
Kentucky International Convention Center in Louisville, KY
Embracing the advancement of condition monitoring technology with superior sensor sensitivity, data intelligence, and software with forward-thinking innovators. We are focused on producing next-generation machine health and condition monitoring solutions. As a result, we are able to provide our clients with the best performing condition monitoring solutions and technology in the industry.
Temperature reading and triaxial vibration in one sensor.
Piezoelectric accelerometer with a wide frequency range and high sensitivity.
Ultrasonic sensor, piezoelectric accelerometer, and temperature sensor in one small form.
Further evidence, as identified by industry captured data, shows that unplanned downtime is responsible for 3 to 5% of lost production. In return, this costs businesses 2 to 5x more than planned downtime.
The ultimate power behind your data. Worldview software combines the best features from across all the conditioning monitoring worlds to provide real-time information on your equipment.
For a more robust approach to machine health, we add to the power of our cutting-edge software with custom data integration — allowing you to take your data to the next level.
We don’t make you fit our mold — we custom-design the solution that works best for you and your environment.
Our expert team will install Uptime’s state-of-the-art wireless monitoring sensors to your industrial machinery or we can provide you with the tools to self-install.
Our flexible architecture allows you to connect wirelessly to the Cloud or via on-premise direct access.
Human capital is a key differentiator in condition monitoring success. We house best-in-class reliability experts and vibration analysts for excellence in diagnostics.
Advanced automated alerts identifying maintenance priorities of equipment that require attention.
We offer custom-designed plugins that integrate with third-party platforms, providing you with seamless connections to the tools you use today and tomorrow.
Some people equate Condition Monitoring to the way we monitor the condition of the human body. We use blood tests, blood pressure, body temperature and other activities to know our condition from a health perspective.
In a similar way, Condition Monitoring can be defined as different methods that are used to measure the status of critical machinery components, particularly with rotating machinery. For example, Condition Monitoring will look at vibrations, temperature, and oil condition to identify any conditions that could indicate a problem. At the same time, this information is used to track irregularities that could eventually lead to operational failure. Condition Monitoring helps to prolong the life of equipment through regular maintenance and preventative repairs. Small issues can be taken care of quickly before they have the opportunity to become bigger, more expensive problems.
Reactive Maintenance is the most costly type of maintenance. Oftentimes, businesses will adopt this approach with the expectation that the costs associated with downtime and repairs will not exceed the cost required to invest in an ongoing maintenance practice. This can be a risky approach, especially when you consider that in 2016, the average cost of downtime across all businesses was $260,000 per hour. That was a 60% jump from 2014. One can only assume that there have also been significant jumps in more recent years. Condition Monitoring can reduce the amount of reactive maintenance that is performed thereby reducing overall operating costs and downtime losses.
Condition Monitoring can provide information so that time based activities can be optimized. Think of preventative maintenance as taking your car in every three months for an oil change. Maintenance is being performed as you do your part to prevent major engine problems, but you may also be missing other signs of emerging problems in between visits.
The only way to understand what the failure modes are and how fast they are progressing is to monitor various parameters on the machine with Condition Monitoring. With this approach, maintenance is only performed when needed and operators have a clear understanding of machine health based on vital indicators.
True predictive maintenance happens when intelligence is captured over long periods of time from your machinery. Data is collected, intel is captured, and over time, AI (Artificial Intelligence) steps into the predictive maintenance process to begin providing alerts and notifications predicting when maintenance should occur to eliminate failure and downtime.
Ultimately Condition Monitoring is able to automate predictive maintenance in a way that relies heavily upon excellence in data capture and analysis. The human asset will play a critical role in developing the pattern of greatness in monitoring analysis for the effective evolution of predictive maintenance.