Using

1
Using Accessing Historian Data

• Understanding the Proficy Historian and how to
  use the Excel Add-in to view plant data

Stephen Friedenthal sfriedenthal_at_evsystems.net
617.916.5101 (w) / 617.901.9193 (m)
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Agenda

• System Overview
• Quick introduction to the Proficy Historian
• GreenFuel system architecture
• Excel Interface
• 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 youre done!
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Introduction to the iHistorian

• Key features
• High-speed collection retrieval (20k/sec)
• Understands time-series data
• 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

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Historian Introduction (contd)

• Additional Features
• Easy-to-use
• 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
• Secure, 21CFR11 compliant application
• User role-based security 100 auditing 100
  of the time
• Analysis and enterprise connectivity
• A fast, flexible, easy-to-use Client Tools
  include, Excel, web portal, Plant Applications,
  SDK, and OLE DB

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Why not use a Relational Database?

• RDBs are designed for transactional and
  business-oriented data
• Not designed to store, retrieve and keep on-line
  the tremendous volumes of data generated from a
  plant or production facility
• They are very good at answering
• What are my monthly sales by product and region?
• What are the costs associated with a batch
• Very poor at addressing basic time-series data
  
• What was the hourly average/min/max for a tag
  regardless of how often it was stored?
• Storing data only when a relevant change occurs
• How does the current batch compare against past
  performance?
• Keeping years of data on-line readily available
  without impacting performance

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Getting Started

• Installing the Excel tool

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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
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How to Configure Excel

• To add the iHistorian Excel add-in
• Select Tools, from the menu bar, then Add-ins
  
• Select Proficy Historian Add-in and press OK

Note If you dont see the Proficy Historian
listed, search for the file, iHistorian.xla and
then use the Browse button to select it.
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Configuring Excel (contd)

• After selecting the add-in, Historian will be a
  new menu item on your toolbar whenever you start
  Excel.

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Historian Functions

• An overview of some of the thing you can do with
  the historian Excel add-in

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A Quick Example Search Tags

• 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

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Performing a tag search

• 6 Easy Steps
• First, select Search Tags from the add-in menu
• Enter the search criteria for the tagname (blank
  for all)
• Select the tags for the report
• Select outputs
• Type or select the spreadsheet location
• Press OK

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Historian Excel add-in functions

• Just as with the tag search, the add-in can be
  used to
• Search Tags
• Query Current Values
• Query Calculated Values
• Query Raw Data
• Query Alarms Events (NA for GreenFuel)
• Query Calculated Data
• Query Filtered Data

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Tag Search

• 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)

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Advanced Tag Search
The text in cell B2 is used to retrieve tag
names Instead of searching each time, just type a
new entry in B2
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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
• Tag name description are a Boolean AND
• Blank All
• Wild card characters
• ALL chars to right
• ? single character

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Retrieving Data

• But first we need to learn a little about data
  storage

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Time-series data storage conundrum

• 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
• We need a way to know what happened when
  without looking at MB (or GB!) of data

Red marks are raw samples that were stored.
(Note different intervals)
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Historian data retrieval

• The historian understands the nature of the
  data and
• When you ask for the current value it returns
  the last good value (even if its 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
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Example Retrieving current values

• 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

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Retrieving current values
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Historian Calculations

• Now for the fun stuff

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Different ways to retrieve data

• 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)

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More ways to retrieve data

• Lab Strangely named, but Lab sampling returns
  raw values, evenly spaced by a user selected
  interval.
• 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 dont want any interpolation
  or smoothing
• Primarily used to trend raw data, with evenly
  spaced samples to make nice charts

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Lab sampling Example
Lab Sampling, 5 Min. Interval
Actual raw data stored
Time Value
900 25.0
905 30.0
931 15.5
Time Value
900 25.0
905 30.0
910 30.0
915 30.0
920 30.0
925 30.0
930 30.0
935 15.5
940 15.5
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Trend Sampling

• Trend Sampling solves a problem that few realize
  is there, but can be criticalHow 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?

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Trend sampling Example
Lab Sampling, 5 Min. Interval
Actual raw data stored
Time Value
900 25.0
906 125.0
910 50.0
915 25.0
Time Value
900 25.0
905 25.0
910 50.0
915 25.0

• See the problem??
• With 5 Minute sampling, we see a smaller peak
• With 30 minute sampling we dont see the peak
  at all!

Lab Sampling, 30 Min. Interval
Time Value
900 25.0
930 25.0
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Trend sampling (contd)

• 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

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Historian calculation modes
Calculation 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 adding up the raw values
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Historian calculation modes
Calculation 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
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Historian calculation modes
Calculation 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
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Example Calculation Query
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Raw Data Queries

• When you just want the beef

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Raw Data Queries

• 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 cant handle more than 64,000 rows
• Because the source data is stored only on a
  change, raw data can be confusing
• You may get no data back based on your start
  end dates

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Raw Data Query Options

• Options
• Select start end dates (but you must select an
  output range large enough to hold the data)
• 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)

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Advanced Topics

• But wait Theres More!

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Filtered Data Queries

• 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

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Filtered Data Query Menu
Same as Query Calculated Data menu
Enter the filter tag (e.g., algae temperature),
and the condition (e.g., lt 90)
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Create Tags, Import and Modify Data

• Administration functions
• Create, modify tag properties
• View on-line archives and storage status
• Data storage functions
• Export data, import new data, modify stored
  data, even add comments to stored data
• Audit functions
• Export and search audit trail, import new audit
  messages

But, dont worry.. The original value is still
retained
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Questions