Two Brazilian friends, Igor Marinelli (23) and Gabriel Lameirinha (22), created a startup and developed a sensor that warns the industry when a machine can crash, have problems or break.
They work in the following way: the sensors are glued to the industrial machinery, they detect the vibration and the temperature of the equipment, with this, they can detect and anticipate a series of anomalies for a professional to correct. With the sensors connected to the internet, the data is sent to a platform, which with the help of artificial intelligence, analyzes the data and notifies when the machine gives signals that it needs maintenance.
The idea for the equipment came from inside Igor’s house. With a father as a maintenance manager, Igor always had the idea to do something to improve the life of the maintenance manager in the industry.
The startup already has 70 sensors placed in 12 industries and the idea is to provide the technology and the privilege of maintenance of large industries for small and medium industries, which represent 90% of the establishments. These sensors can help these enterprises in their predictive maintenance.
The importance of predictive maintenance
The predictive maintenance consists of periodic monitoring of equipment and machines using data collected in inspection routines and condition investigation, which can be visual, vibrations analysis, ultrasound, noise analysis, etc. It can be used to predict the useful life of machines and their components to define forms to optimize this period.
Good predictive maintenance can increase the durability of machines and equipment, eliminate the need for disassembly for inspection, determine in advance whether a tool, component or machine needs to be repaired, decrease the amount of emergency corrective actions, mitigate damages, increase productivity and, at the same time, reduce maintenance costs.
By Kássia Carvalho