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1
Measuring and Forecasting Production Metrics Using The Barringer Process
Reliability Methodology
Presented To:
SMRP Reliability Analytics SIG
SMRP 2012 Annual Conference
Orlando, Florida
Presented by: Michael Eisenbise
Annual Production Data – Plotted in “Rain Cloud Chart
Daily
Ou
tpu
t W
idg
ets
/Day
Day of Year
All production rates below a “target” production rate identified by most record keeping systems -Normally equipment failures or TAR related
Annual Production Data – Plotted in “Rain Cloud Chart
Day of Year
“Bandwidth” of lower and upper daily production rate when unit was “under control”
Daily
Ou
tpu
t W
idg
ets
/Day
Annual Production Data – Plotted in “Rain Cloud Chart”
Day of Year
What is daily average production that can be counted on in the future?
Daily
Ou
tpu
t W
idg
ets
/Day
Daily Average Production Rate Shown on BPR
Daily production rate shown where production line crosses “Eta” or dotted line
Annual Production Data – Plotted in “Rain Cloud Chart”
Day of Year
What percentage of time was unit operated within this bandwidth?
Daily
Ou
tpu
t W
idg
ets
/Day
Bandwidth Shown on BPR
Point at which raw data is not located on production line is percent of time unit operated within bandwidth – Shown as reliability %. Our competitors at 80% on this process
What are our losses due to “crash and burn issues”?
Losses are area under “raw data” and “production line”. In this case 1,839 Widgets/Year
Losses due to the way we operate and manage this unit?
Losses are area under “production line” and “nameplate line”. In this case 720 Widgets/Year
Data points are mechanical failures or TAR related. In this examples losses are 41 units/year or amount normally captured in a your failure database. Most losses do not fall in this area of curve.
Very few total losses are due to mechanical failures