the best enterprise app for
Did you know that:
The large plants lose 323 production hours a year or 27 hours a month to machine failure - that’s more than a day’s production. The average cost of unplanned downtime in lost revenue, financial penalties, idle staff time, and restarting lines is $532K according to senseye.
Problem: Industrial equipment breaks.
SaaS for prediction of electrical motors failures to help enterprises reduce their cost in repair and maintenance with Industrial AI service
During the tests accuracy of the models – 93% and above in specific cases
Initial focus on global compound feed industry. 28,414 feed mills are in the world; 6,232 in the USA; 6,948 in Europe.
There are 8,800 grain elevators in the USA; 28,000 in the world.
Additional industries where sound analytics for electrical motors might be applied:
a-Gnostics is Industry 4.0 subsidiary of custom software development outsourcing company, SoftElegance, that was founded in Troy, NY in 1993, and specialized in providing reliable services for implementation of SaaS systems, sophisticated business solutions, engineering applications, and business processes automation software for the U.S. and the E.U. companies, ranging from dynamic small and medium to Fortune 500.
In October 2016, we've conducted the presentation 'Spark — Universal Computation Engine for Processing Oil Industry Data' at Spark Summit Brussels. The next day after the presentation we've decided that October 28 will be a-Gnostics Birthday.
Di-agnostics is the product of a-Gnostics, it is Industrial AI sound analytics SaaS for prediction of failures in heat engines and electrical motors, to help enterprises simplify their work and reduce maintenance costs. We are working on it since late 2021.