37
June
2016
HYDROCARBON
ENGINEERING
T
he production of superior fuels requires strict attention to quality control.
Regardless of the geographical location, refineries need tight control of
manufacturing processes in order to turn out quality fuels while
optimising costs and adhering to local regulations. Whether a refinery is
dealing with Environmental Protection Agency (EPA) Tier III regulations or aiming for
process optimisation, statistical analysis of process data is an ideal way to hit the
production and grade targets each time.
The recent expansion of the Clean Air Act (CAA) has sparked a new wave of
interest in performance-based methodologies. Fuel refineries have been following
changes in the CAA for decades and adapting in order to stay compliant. The recent
implementation of strict test method requirements has some refineries scrambling
to find solutions for analytics-centric process control.
EPA Tier III basics for fuel refineries
Tier III of the CAA was introduced by the EPA in 2014 and has been rolled out in
segments since. A set of regulations known as the Performance-Based Analytical Test
Method Approach (PBATMA) has been introduced as part of the Tier III Vehicle
Emission and Fuel Standards Programme. The aim of the PBATMA is to set minimum
performance criteria for a test method, including verifying that analytical equipment
and procedures meet published standards and that they adhere to specific statistical
quality control (SQC) criteria. These regulations target, and have wide ranging
implications for, global oil companies and vehicle manufacturers alike.
John Maurer, Northwest Analytics, USA,
explains why the use of statistical analysis
for data processing is an integral element of
quality control in superior fuel production.
