Migrate Your maintenance from Preventive to Predictive
Ever since the rapid evolution of technology, it has opened a lot of new opportunities for invention and innovation of technological things like mechanical systems and AI technology. However, the risk of mechanical machine systems and operations malfunctioning has also gone up. Solutions made to set up preventive measures are operated the moment a system goes haywire. These are called preventive maintenance solutions.
Preventive maintenance solutions usually operate when a system is malfunctioning. It acts as the on-call repairman of the system. In addition to this, these solutions are driven by routine checks. They inspect the whole system, one aspect after another, and locate the problem after the holistic inspection is completed.
Moreover, because of these preventive maintenance solutions, machine and system operators create a schedule for the regular maintenance of the systems. This is to prevent a system from malfunctioning.
There are two types of preventive maintenance solutions: time-based and usage-based.
Time-based preventive maintenance solutions are done regularly; hence, the time as the preventive maintenance’s base. This kind of solution is routinely done to ensure the success of a system’s operating system.
Usage-based preventive maintenance solutions, on the other hand, are done in a scheduled time. This scheduled time is determined when a system has surpassed a specific limit that was created as a trigger for a system to undergo maintenance.
Those kinds of solutions do not work efficiently in many cases and result in losses in production and services. Additionally, preventive maintenance solutions are not suited for usage when the failures of a system are random and do not associate themselves with maintenance errors. Those kinds of solutions are only made for system failures that can be fixed with the maintenance and system calibration.
In contrast to this, there are solutions wherein a system is automatically monitored regularly. These solutions are called predictive maintenance solutions.
PdM solutions operate routinely when a machine or system is operating. It acts as the supervisor of the system. Another feature that predictive maintenance solutions have is that they examine and analyze patterns in which certain malfunctions and errors can come out from. These examinations are then counted as data that will be used for future possibilities of malfunctions. The data taken from these examinations are then used to alert the errors in a machine or system.
Our company provides predictive maintenance and system optimization solutions by analyzing machine raw data. We also build accurate models and algorithms that anticipate machine behavior. Moreover, our integrated systems will alert our clients on abnormal situations present in their systems. This is to ensure that the existing system problems will not escalate and turn into serious disruptions of the mechanical machine systems.
Our company also grounds itself on two services in which predictive maintenance is utilized when in contact with any kind of mechanical system. Those three services include the following:
Diagsense provides predictive maintenance and system optimization solutions by analyzing raw machine data. The data gathered will then be used to observe behavioral patterns in machine systems in which these observed patterns can then be utilized to not allow further problems in a system.
The models and algorithms we have developed over the years feature system alerts. Those events will then be processed and then will notify the user of machine system errors. Moreover, the algorithm is very accurate and it’s able to detect small defects much before they become a serious disruption in a mechanical system. It will also inform the user of potential abnormalities within the machine system.
Diagsense keeps the continuity of the machine life.