Global benchmarking for a terminal automation solution
A method of automated remote terminal benchmarking includes providing a computing system including a processor having an associated memory which implements a benchmarking algorithm. The benchmarking algorithm implements receiving raw data associated with a plurality of Key Performance Indicator (KPIs) including real-time data from different bulk liquid terminals spanning sites across a plurality of continents, and calculating a global target benchmark value or global target benchmark range for at least a first of the plurality of KPIs from the raw data. Responsive to a user' request at a selected first of the different bulk liquid terminal (first terminal), a benchmark report is generated which benchmarks a KPI performance of the first terminal including for the first KPI by a comparison to the global target benchmark value or global target benchmark range.
1. A method of automated remote terminal benchmarking, comprising:
providing a computing system including a processor having an associated memory which implements a benchmarking algorithm, said benchmarking algorithm:
receiving raw data associated with a plurality of Key Performance Indicators (KPIs) including real-time data from different bulk liquid storage terminals spanning sites across a plurality of continents;
calculating a global target benchmark value or global target benchmark range for at least a first of said plurality of KPIs (first KPI) from said raw data;
generating a benchmark report which benchmarks a KPI performance of a first terminal of said bulk liquid storage terminals including for said first KPI by a comparison to said global target benchmark value or to said global target benchmark range, and
wherein said benchmarking algorithm further implements a training simulator for said user that simulates actual terminal operations, real conditions, and abnormal conditions including alarm conditions.
2. The method of claim 1 , wherein said computing system is remotely located relative to said first terminal.
3. The method of claim 2 , wherein said computing system is cloud located.
4. The method of claim 1 , wherein said bulk liquid storage terminals comprise a petroleum-based terminal.
5. The method of claim 1 , wherein said bulk liquid storage terminals are involved in modes of transport selected from surface, rail, marine and pipeline.
6. The method of claim 1 , wherein said global target benchmark value or global target benchmark range are based on a best in class performance and a worst in class performance of said bulk liquid storage terminals.
7. A continuous automated remote global benchmarking system for terminals, comprising:
a computing system including a processor having an associated memory which implements a benchmarking algorithm, said benchmarking algorithm:
receiving raw data associated with a plurality of Key Performance Indicator (KPIs) from different bulk liquid storage terminals spanning across a plurality of continents;
real-time calculating a global target benchmark value or global target benchmark range for at least a first of said plurality of KPIs (first KPI) from said raw data;
generating a benchmark report which benchmarks a KPI performance of a first terminal of said bulk liquid storage terminals including for said first KPI by a comparison to said global target benchmark value or to said global target benchmark range, and
wherein said benchmarking algorithm further implements a training simulator for said user that simulates actual terminal operations, real conditions and abnormal conditions including alarm conditions.
8. The system of claim 7 , said global target benchmark value or global target benchmark range are based on a best in class performance and a worst in class performance of said bulk liquid storage terminals.