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New modules for Orion eAPI - reliability at asset management

Grant number: 15/22689-6
Support Opportunities:Research Grants - Innovative Research in Small Business - PIPE
Start date: March 01, 2017
End date: May 31, 2020
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
Principal Investigator:Claudio Caiani Spanó
Grantee:Claudio Caiani Spanó
Company:ReliaSoft Brasil Ltda
City: São Paulo
Associated researchers: Bruno Cesar Soriani ; Cleber Caiani Spanó ; Eduardo Gonçalves Melero
Associated scholarship(s):18/23776-8 - New modules to Orion and API: reliability and asset management, BP.TT

Abstract

The operational efficiency on the production lines of mining, energy and oil and gas industries is strongly related to asset management practices. Normally these industries contribute sharply to their countries GDP and use their assets intensively. In the other hand, recent surveys show that asset management decisions are strongly based on the experience and felling of the professionals and general information gathered by vendors. Reinforcing that scenario, Daniel Levitin, professor of psychology and behavioral neuroscience at McGill University states that nowadays the enormous volume of data and information available for everyone is greater than the processing capacity of the human brain. Appraising this information, we can understand the difficulty experienced by the professionals dealing with asset management trying to comprehend the expressive volume of data related to the manufacturing assets. Therefore, many decisions are not completely efficient, even more, they are based only in experience and feeling. On the current management models adopted by industries, fast decisions are requested; and obviously, the required data cannot be well processed. The Orion eAPI was developed to organize and process manufacturing asset data and depict valuable information to support decisions. The proposed project aims to develop new mathematics routines to increase the number and type of analyses performed by the system. It is planned to implement routines to calculate the asset reliability using the cumulative damage technique, automatization of the assessment of spare part quantities required to support operations among others. These new routines will benefit the users due to the reduction of time expended with calculus and the improvement of the quality of the decisions related to asset management; and will differentiate the system from the concurrency. (AU)

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