David Holding: The trend towards predictive maintenance and industrial monitoring with Archimed IIoT
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For over a decade, the control of production assets moves on two well known, but fundamentally limited directions. The first – reactionary maintenance, which places importance on the maximum requirements for capacity of the equipment till the moment of shutdown. And the second, a more modern concept, which implements planned preventive repairs (PPR) based on the work hours.
Looking for a balance between these two concepts, modern engineering maintenance is aimed toward predicative diagnosis. How does a software ecosystem move from simple collection of telemetric data to calculating the life cycle of hardware and to what extent can software foresee the amount of expenses needed? To analyze this technological change, we spoke with experts from David Holding - a proven European developer that has been digitizing and automating business processes in our country for three decades.
"The big challenge facing modern software is not simply to visualize current parameters in the form of graphs on the screen. The goal is to create a dynamic model that adapts to the real physical state of the machine and predicts the occurrence of emergency situations before they turn into an actual failure of the machines and mechanisms," comment David Holding. It is in this niche that the Archimed IIoT platform and its predictive module, developed in accordance with the requirements for preventive control, are positioned. The product changes the concept by replacing "blind following" of the calendar with pure mathematical analysis of asset wear in real time.
The engineering logic of Archimed Predictive Maintenance is based on direct integration of industrial controllers (PLC). Instead of relying on information inputted by operators, the software continuously “overhears” the microvibration spectrum, temperature amplitudes, and energy consumption of compressors, pumps and electric motors.
Photo source: David Holding, ©Engineer.BG via Canva.com