The FLETEC learning system is driven by an Algorithm that contains approximately 20 years of industry experience. Utilizing different business criteria, statistical methods, and intelligent benchmarking the Algorithm selects a small quantity of relevant repair situations.
Such data is made available on the FLETEC Assessment Platform allowing human experts an efficient assessment of the repair situations. The Algorithm learns from the assessment results and improves the selection process of further assessments.
With a growing quantity of assessments / increasing training data each customer is generating its own data, FLETEC allows a smooth application of machine learning technologies to further enhance the Algorithm performance.
The results of the technical assessment of the Algorithm-selected repair situations are put into a general context identifying operational improvement areas and behavior patterns. FLETEC makes such information available performing a report and enriches live operational repair data to enable process automation (see Transparency & Automation).
The FLETEC principle offers a new efficient approach to reduce individual control of repair situations without losing cost control abilities.