Transcript Slide 1

Using & Accessing
Historian Data
Understanding the Proficy
Historian and how to use the
Excel Add-in to view plant data
Stephen Friedenthal
[email protected]
617.916.5101 (w) / 617.901.9193 (m)
Agenda
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System Overview
• Quick introduction to the Proficy Historian
• GreenFuel system architecture
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Excel Interface
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Installation and configuration
Basic queries (to get our feet wet)
A primer on data storage
Data retrieval modes
Advanced analysis and interactive
spreadsheets
Wrap-up & questions
Plus! A cool (?) bonus… a sample Excel report you can use when you’re done!
Introduction to the iHistorian
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Key features
• High-speed collection & retrieval (20k/sec)
• “Understands” time-series data
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Able to provide time-based data aggregation (min,
max, average, etc.)
Data compression (“dead banding”)
• Robust data collection from plant floor
• Event & time-driven calculations on historical
data
• Near real-time access to plant data
• Store/add comments with data
Historian Introduction (cont’d)
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Additional Features
• Easy-to-use
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THE easiest to use, fastest to install and configure, and
lowest maintenance historian available in the world today
(really!)
Information access is easy without requiring any
specialized training, programming or database skills
• Security, auditibility & traceability
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Secure, 21CFR11 compliant application
User & role-based security & 100% auditing 100% of the
time
• Analysis and enterprise connectivity
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A fast, flexible, easy-to-use Client Tools include, Excel, web
portal, Plant Applications™, SDK, and OLE DB
Getting Started
Installing the Excel tool
How to install…
Step 1: Insert the CD or run the network install
2. Go through the usual prompts and select
the Excel add-in, then press Next..
3. Enter the server name and
continue with the setup. Example
below connects to the server called,
“NANO”
How to Configure Excel
To add the iHistorian
Excel “add-in””
1.
Select “Tools”,
from the menu
bar, then “Addins”
2.
Select “Proficy
Historian Add-in”
and press OK
Note: If you don’t see the Proficy Historian listed, search for the file,
iHistorian.xla and then use the Browse button to select it.
Configuring Excel (cont’d)
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After selecting the
add-in, Historian
will be a new menu
item on your
toolbar whenever
you start Excel.
Historian Functions
An overview of some of the
thing you can do with the
historian Excel add-in
A Quick Example – Search Tags
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A tag search lets you quickly find and
display process variables
This is usually the first step to
retrieving data, since the data is
accessed by the tag name
Ex.:
• The tag name for a bio reactor CO2
monitor is GFAZ1.200_AE_245H.F_CV
• This is then used to retrieve data
Performing a tag search
6 Easy Steps
First, select Search
Tags from the addin menu
1. Enter the search
criteria for the
tagname (blank for
all)
2. Select the tags for
the report
3. Select outputs
4. Type or select the
spreadsheet
location
5. Press OK
Historian Excel add-in functions
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Just as with the tag search, the add-in can
be used to:
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Search Tags
Query Current Values
Query Calculated Values
Query Raw Data
Query Alarms & Events (NA for GreenFuel)
Query Calculated Data
Query Filtered Data
Tag Search
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Purpose: To retrieve tag names,
description, units, etc.
Features:
• Search by tag name or description
• Dynamic searching by using a cell
address vs. a string (i.e., cell A2 is used
for the tag mask)
Advanced Tag Search
The text in cell $B$2 is used to
retrieve tag names
Instead of searching each time,
just type a new entry in $B$2
Advanced Tag Search II
After you create a dynamic
search based on tag
name, you can edit the
formula in Excel to add the
tag description as a criteria
Notes:
1. Tag name & description
are a Boolean AND
2. Blank = All
3. Wild card characters:
1. * = ALL chars to right
2. ? = single character
Retrieving Data
But first… we need to learn a
little about data storage
Time-series data storage
conundrum
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Data is not typically
stored at even
intervals, but…
• We may need evenly
spaced reports (e.g.,
hourly avg.)
• We need to know what
the value is “now” even
though new data may not
have been stored for a
long time
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We need a way to know
“what happened” &
when without looking at
MB (or GB!) of data
100
90
80
70
60
50
40
30
20
10
0
9:00
9:05
10:00
Red marks are raw
samples that were stored.
(Note different intervals)
12:30
Historian data retrieval
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The historian “understands” the nature of
the data and:
• When you ask for the “current value” it returns
the last good value (even if it’s hours or days
old)
• When you ask for evenly spaced samples it
interpolates the raw data*
• When you ask for data in between real
samples it gives the best interpolated result
(e.g., if you ask for the maximum it will return
an interpolated maximum)
* Note that Lab data and Trend Sampling do not interpolate or smooth the data
Example: Retrieving current values
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Select Query
Current Values
from add-in menu
Enter the tag
names, or use a
cell reference from
the tag search
Select outputs and
location
Retrieving current values
Historian Calculations
Now for the fun stuff…
Different ways to retrieve data
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Sampling Modes
• Interpolated – Just like it sounds,
historian interpolates between raw
samples and return results based on the
time interval (e.g., every 30 min.) or
number of samples
• Calculated – Historian will perform one
of several aggregate calculations (min.,
max., avg., etc.) on the data and return
results (more on this in a bit)
More ways to retrieve data
• Lab – Strangely named, but Lab
sampling returns “raw” values, evenly
spaced by a user selected interval.
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For each interval it returns either (1) a raw
sample that was stored at that time, or (2)
the last good value that was stored
Very useful when you don’t want any
interpolation or smoothing
Primarily used to trend “raw data”, with
evenly spaced samples to make nice charts
Lab sampling Example
Actual
Time raw data stored
Value
9:00
25.0
9:05
30.0
9:31
15.5
Lab Sampling, 5 Min. Interval
Time
Value
9:00
25.0
9:05
30.0
9:10
30.0
9:15
30.0
9:20
30.0
9:25
30.0
9:30
30.0
9:35
15.5
9:40
15.5
Trend Sampling
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Trend Sampling solves a problem
that few realize is there, but can be
critical:
How do know that you are seeing all
of the extrema of a process?
Not necessarily an issue over short
time periods with short retrieval
intervals, but what about longer time
periods?
Trend sampling Example
Actual
Time raw data stored
Value
9:00
25.0
9:06
125.0
9:10
50.0
9:15
25.0
Lab Sampling, 30 Min. Interval
Time
Value
9:00
25.0
9:30
25.0
Lab Sampling, 5 Min. Interval
Time
Value
9:00
25.0
9:05
25.0
9:10
50.0
9:15
25.0
See the problem??
• With 5 Minute sampling, we
see a smaller peak
• With 30 minute sampling we
don’t see the peak at all!
Trend sampling (cont’d)
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Trend sampling solves the dilemma by returning
a High-Low pair for each time interval
Trend sample divides the interval in half and
returns the high or low value (whichever occurred
first) for the middle time sample
• We never miss a maximum or minimum extrema –
regardless of the sample interval
• Able to get a very good view of the process with only a
small sample of data (e.g., review a year of data with
month-long intervals)
• Note that the time of the min/max is NOT the actual
time of the raw data
Historian calculation modes
Calculatio
n
Description
Average
Returns the interpolated average of the data
collected during the sample period
Minimum
Returns the interpolated minimum value during
sample period
Maximum
Returns the interpolated maximum value during
the sample period
Standard
Deviation
Returns the interpolated standard deviation of the
data during the sample period
Total
Returns the integrated total of a process value
based on a 24 hour sample period (e.g., calculate
the total flow through a flow meter with a given
flow rate) NOTE that this is NOT the same as
Historian calculation modes
Calculatio
n
Description
Count
Returns the number of samples stored during the
sample period
Raw
Average
Returns the arithmetic average of the raw data
stored during the sample period
Raw
Standard
Deviation
Returns the actual, non-interpolated standard
deviation of the data during the sample period
Raw Total
Returns the arithmetic total of the raw data stored
during the sample period
Time of
Minimum
value
Returns the time of the minimum value
Historian calculation modes
Calculatio
n
Description
Time of
Maximum
value
Returns the time of the maximum value
Time
Good
Returns the total time in milliseconds that the data
was of good quality during the sample period.
Useful for calculating pump run times and the like
Example: Calculation Query
Raw Data Queries
When you just want the beef
Raw Data Queries
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Raw data queries let you access the raw,
unfiltered data
Very fast, but some caveats:
• A typo can cause A LOT of data to be
requested
• Excel can’t handle more than 64,000 rows
• Because the source data is stored only on a
change, raw data can be confusing
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You may get no data back based on your start & end
dates
Raw Data Query Options
Options
1. Select start & end dates
(but you must select an
output range large
enough to hold the data)
2. Select a time and ask for
a number of samples
forward or back from that
point (you only need to
select the first cell of the
output range in this
case)
Advanced Topics
But wait… There’s More!
Filtered Data Queries
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Filtered queries let you retrieve data
(lab, interpolated, calculation, or
trend) for one or more tags, based
upon the value of a different tag
For example, retrieve conductivity
based upon pH or temperature
Filtered Data Query Menu
Same as Query Calculated Data menu
Enter the filter tag (e.g., algae
temperature), and the condition
(e.g., <= 90)
Create Tags, Import and Modify
Data
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Administration functions
• Create, modify tag properties
• View on-line archives and storage status
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Data storage functions
• Export data, import new data, modify stored
data*, even add comments to stored data
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Audit functions
• Export and search audit trail, import new audit
messages
*But, don’t worry.. The original value is still retained
Questions