New Features in ZOOMS 2.2.3 (which has shipped, btw)

Yep, ZOOMS 2.2.3 is shipped. There are multiple upgrades, including several under the hood, but the user-features are as follows:

Autocomplete Detects Text Within Words

We are fast learning from customers that despite S88, people naturally like having the equipment hierarchy in the unit name. It's natural and logical. As such, we've modified our autocomplete to search after delimiters such as the period (.) and the underscore (_). You can see below that the user typed "10" and yet items that have "10" after a legal delimiter show up.

TimeExpressions

Inputting time is a pain in the buttocks. ZOOMS already recognizes the PI time expressions (*, t, y) as well as (60s, 1m, 1h, 2d, 3w, 4y...) time intervals. But our users like not having to type the forward slashes (/) and colons (:) that come with inputting time like "11/23 23:00."

ZOOMS now recognizes several more oddball time formats that don't come standard. You can see below that "1123 2300 to 1130" resolved to: 11/23/2014 23:00:00 to 11/30/2014 0:00:00.

Downloading Raw and Evenly Spaced Data

The ability to download raw data has existed since 2.2.2. Raw data is the actual data captured in the data archive. Unfortunately, the captured data may not happen at the same timestamp and if you need to correlate values with other parameters. So for version 2.2.3, we have the ability to download evenly-spaced data in user-specified increments. Click that "timed CSV" button and you're going to get interpolated data values every 15 minutes:

Trend data visualization and data downloads remain a core offering.  Stay tuned for more release announcements.


Request a ZOOMS demo

Process Data for the Rest of Us

I first started using OSIsoft's PI in 1999 when I got hired as a fermentation engineer at the world's largest cell culture plant (at the time, 144,000-liters).

I remember the first week vividly.  Me - not knowing anything about how read cell culture trends - watching my boss run his cursor over PI trends, nodding his head and then running off to meetings telling the operations staff what's happening in the bioreactors.

Over the years, I've put my eyeballs on thousands of cell culture runs and became an expert on the matter.  Yet, no matter how many trainings gave to tech(nician)s, supe(rvisor)s, and managers to increase the population of process experts at the company, I got the sense that ultimately it was still my team's (i.e. manufacturing sciences') job to know what's happening to the cell culture runs in-progress.

OR, maybe not...

The VP of the plant had the PI administrator write a script to open up PI ProcessBook and snapshot current trends as a images and put it on a website (remember, this was back in 1999).  Clearly management recognized the value of these trends, but was just too much activation energy to get PI data to "The People."

So when I left my awesome company (and awesome job), I set out to do one thing:



And by PI, I mean "process data."

Google had already pioneered the one text-box, one click format for accessing website data.   So why is it that cGMP citizens can find information on the internet faster than they can find critical process data from within the enterprise?

This is why I bothered creating ZOOMS and this is why I think that there's a place for ZOOMS in the competitive space of trend visualization on the web.

It actually wasn't until the Jared Spool lecture at this year's OSIsoft PI User's Conference that I learned how to better enunciate this creation.  


A quick recap:

The bottom of the escalator is where you are if you know nothing about an app (new users live here).  The top of the escalator is if you know everything about the app (developers live here).

Current knowledge is where the user is today; and target knowledge is where a user needs to be to know enough about the application to perform his duties.

Mr. Spool tells us that intuitive design happens when the knowledge gap (the difference between target knowledge and current knowledge) is zero.

A key observation is that the more powerful and feature-rich the tool, the higher up the target knowledge is...and the harder the knowledge gap is to close.

The success of Google (which is to be replicated with ZOOMS in the process trend visualization context) is a modest number of features in order to lower the target knowledge... and thus diminish this knowledge gap and achieve intuitive design.

There are plenty of feature rich PI trend visualization tools for process experts.  ZOOMS is process trends for the rest of us; in other words: PI for the "non-user."

At the end of the day, it's People, Process, and Technology... in that order.  You can buy awesome technology, but if only a small minority of your people use it, you're neither capitalizing on their potential, nor your process.

ZOOMS v2.2 shipped!

by Oliver Yu

Wow, what an exciting week.

ZOOMS version 2.2 is shipped! The Top 3 features in this release are:

• Wildcard tag search
• Digital States now rendered; Step=1 recognized
• Full-text search on units

Wildcard Tag Search

Wildcard tag search was a feature that was added back to ZOOMS. This feature originally left behind because the idea behind ZOOMS is that users want to search metadata, not tags. As it turns out, there's a delay between when the tags get added to the data archive and when the ZOOMS metadata gets updated, and in between that time, these tags aren't findable on ZOOMS. Well, we listened to our customers and it's back in there.


ZOOMS detects if there is a wildcard in the query; if there is, ZOOMS will do a tag search and show the results asynchronously.  This way, the slowness of the data archive does not impact the speed of the page load.

Digital States and Stepped Tags

Up until now, ZOOMS interpolated all values - which is great for a majority of numerical tags that come in at high frequency. But what about the tags that don't change in value... or are monotonic in nature (like setpoints or OFF/ON)? Well, the glitch in ZOOMS prior to this release is that they'd be plotted as interpolated and didn't make much sense.


 This glitch is fixed.  In the above image, the magenta tag is stepped.

Full-Text Search on Units

This was another great suggestion from one of our best customers. Prior versions of ZOOMS could identify the name of the unit; and therefore suggest it as a user typed it and combine it with parameters to produce a trend. The problem is users often know about the unit by its description or where it is in the equipment hierarchy... not necessarily by name. With this upgrade, any word that appears in the description or hierarchy of the unit gets recognized by ZOOMS and will show up in the SERP.

In the image below, you can see that the user is interested in the 12,000-liter bioreactors in the plant and has typed in his colloquial search term, "12kL."

ZOOMS will return the units T440 through T447 as that "12kL" string appears in the descriptor (but not the name).



Incidentally, in the above query, user could have searched on "ZYM", "CCP1", or "Fermentation" and gotten results.  Now, the user has to know even less about the equipment to get a search result.

Previously added features:

• Ability to magnify the x-axis
• Ability to scale the y-axis
• What is semantic search for process data?

How to Scale X-Axis for ZOOMS Trends

by Oliver Yu

In the last post, we talked about scaling the Y-Axis of ZOOMS trends.  What about the X-Axis?

Well, the X-axis (or as pedantic mathematicians would call it, "abscissa") for ZOOMS is always the time-axis.  As with any chart, there is an "x-min" for the minimum value of x as well as an "x-max."

In the world of time-series data, there are more colloquial names:

• x-min is starttime
• x-max is endtime

Unfortunately, there are also hundreds of ways of representing time:

• 04-Jul-1776
• 12/8/1941
• 

Type Time Range into Search Box

And typing in the starttime and endtime is one way to set the time range:

ZOOMS is able to interpret a lot of date inputs, but not all of them.

Use the Trend Buttons

What happens when you've got a trend and you want to go from there?
There are 3 buttons at the bottom of each trend.

1. Back Arrow is an arrow pointing to the left that will take the trend one time-range into the past.
2. Forward Arrow is an arrow pointing to the right that will take the trend one time-range into the future.
3. Refresh/Revert will restore the time-range to the original as-loaded trend.

Highlight Area On Trend

You can magnify a time range by highlighting it with the mouse: clicking and holding down the mouse button at one edge of the time range and dragging the mouse to the other edge of the time range:
When you release the mouse button, the trend will zoom to the selected time range.

Summary

In summary, there are at least 3 ways to scale the X-Axis of a ZOOMS trend:

1. Type in the time range in the search box.
2. Use the "back" and "forward" buttons
3. Highlight an area on a trend

See Also:

• How to Scale Y-Axis of a ZOOMS Trend
• Controlling Who Can View Process Data with ZOOMS
• OSIsoft PI Search Engine: ZOOMS

How to Scale Y-Axis for ZOOMS Trends

by Oliver Yu

There are several improvements with ZOOMS 2.1 and the first difference you'll notice is the trend controls... the buttons at the bottom of each trend that "control" what happens to the trend.

For this post, we'll be focusing on the Y-axis scaling buttons, which are 5 o'clock position when looking at the trend from straight on.  There are 3 buttons:

• multi
• channel
• single

Multi

By default, every trend is plotted as "multi," which is an abbreviation for multiple Y-axis.  Each trace on the trend gets its own Y-axis scale where the bottom is the minimum value and the top is the maximum value:

While you get a fuller sense of each trace - since each trace spans the entire range of the graph, there is no sense of what the traces are like in absolute value.

Single

The left-most button is "single," which refers to plotting all the traces on a single Y-axis. Using this method, you can get a strong sense for how the traces relate to each other.
Compared to the multiple Y-axis, we can now tell that the orange sinusoid is oscillates in a lower range than either of the red or magenta traces.

Channel

The channel Y-axis scaling divides up the trend in N horizontal slices and plots each trace in its own channel.  Using this method, you can hover your cursor over the entire trend and get a feel for what the values actually are.


There are plenty of awesome web-trending applications that give you more precise control over the actual scaling of the Y-axis, and we think they serve the tactical employees (e.g. operators and engineers) well.

The Zymergi implementation of Y-axis scaling is geared towards the time-crunched strategic users like managers and directors.

See also:

• Securing ZOOMS
• Introducing ZOOMS
• What is Metadata Search for Time-Series Data? 

Securing the Process Data Historian Search Engine: ZOOMS

by Oliver Yu

When I worked at an FDA-regulated commercial biologics manufacturing facility, access to data was limited to authorized individuals; 21 CFR Part 11 (10d) specifically calls for this control so that the authenticity, integrity, and, when appropriate, the confidentiality of electronic records are assured.

Needless to say, those who operate under cGMP regulations are worried about compliance with Part 11 have concerns with software that is trying to democratize the data.

Fair enough.


It turns out that you can have cake and eat it too.  That is, you can have an easy-to-use, web-based interface for your trend data AND you can limit the access to authorized individuals.

Within Internet Information Services (IIS), the web-server on which ZOOMS runs, the default setting is to enable Anonymous Login and to disable everything else.

The way to secure ZOOMS is go to click on the website under which ZOOMS is installed and select the Authentication Feature:

When you double-click on IIS Authentication, you get a setting for how you want this web-server to be secured.  There are 4 options to enable/disable.  The way to ensure unauthorized access is not granted is to set Anonymous Authentication Status to Disabled.

And if you happen to be running Windows Active Directory and you want to use that as the method to control access, set Windows Authentication Status to Enabled.



Assuming that you're in an environment with Active Directory, you can use Active Directory credentials to control access to ZOOMS.

Now when I attempt to access ZOOMS, here's what I get:

(I'm on a Mac using Safari to access a Windows IIS server running ZOOMS)

And only when I input valid Windows credentials am I granted access to ZOOMS.  At this point, access to ZOOMS has been limited from everyone with network access to everyone with a valid domain account.

If you want further restrictions, you simply need to set up ASP.NET URL Authorization where you specify the exact role that you want to allow access.

If you want to create an Active Directory group for just your users, you can do so.  If you want to grant access to an existing Active Directory group, you can do so.

The key here is to Allow first, Deny last.

The point in all this is that you don't have to sacrifice the freedom of your information for the sake of security.

For more questions, contact Zymergi Technical Support at 650-646-4996.

See also:

• ZOOMS: Semantic Search Engine for Time-Series Data
• ZOOMS = Metadata Search

Semantic Search Engine for Time-Series Data

It's the year 2014 and there are several updates to the Zymergi Object-Oriented Metadata Search (i.e. a semantic search engine for time-series data).

The first update is that we've moved to HTML5.  This means that we're dropping support for for IE8 or less.  We're proven on the latest versions major web-browsers: Google Chrome, Mozilla Firefox and Apple Safari.

Here's a screenshot of what the search page looks like.  There's no equivalent of "Google Instant" but given the metadata inputted by the administrator into ZOOMS, the software is able to guess what words you are meaning to type:

The second update is that ZOOMS uses a CSS Framework called, "Bootstrap."  Bootstrap was developed by Twitter and they gave it out for free.  The deal with CSS Frameworks is that someone has already done a lot of the heavy web-page styling.  You just need to customize it a bit to fit your look.

The other thing about Bootstrap is that it is "responsive," meaning the webpage will "respond" differently depending on the size of your screen.  Responsive web design (RWD) refers to whether or not a website is optimized for mobile devices.

No, we aren't wading into the time-series-data on mobile devices.  We actually believe that Transpara has a great product in Visual KPI.   We actually don't expect customers to be using ZOOMS on a phone or tablet on a regular basis, but we acknowledge that it can't be helped; in those cases, you can get your trend data with ZOOMS.  Besides, it came for free, so why not add this value?

The last update is that the entire product has been refactored.  The changes are all under the hood, but we've applied the MVC design pattern to separate the functions for a faster, more technically supportable system.

Below, you see a search engine results page (i.e. SERP) for the search terms inputted above.  ZOOMS tells you exactly which typed words has which meaning:

• Reactor1 was identified as a unit.
• Temperature was identified as a parameter.
• Volume was identified as a parameter.

ZOOMS is figuring out what the typed words mean and combining it into a search result.  In this case, someone looking for the reactor temperature and volume may be interested in a trend with each of these two traces plotted.

It is by far the fastest way for an untrained individual to get/view time-series data in a process environment.

We'll be disclosing shortly, but in addition to existing features, there are exciting updates in the coming months… like the ability to run without connecting to other data historians (yep, there's going to be an internal one).

Want a test drive?

The Zymergi Mission

Zymergi sees a world where there is greater wealth than today: a world where individuals have more time to spend on what they want (rather than what they must to do).

Look around the house. Chances are, there's a clothes washer/dryer. The washer is a reactor/centrifuge combination; the dryer is a tumbler... chemical processing units. Now, you don't have to waste time at the river with a washboard washing your clothes.

Oh, there's a fridge and freezer? That's refrigeration process with replete with compressor, expansion valve and working fluid and now you can store foods longer and not have to salt your foods or waste time on extra trips to the grocery store.

Gotta a car, too? That's the chemical processing unit where you convert hydrocarbon to CO2 + water, heat to work to get from point A to B. Now you can get to that job 40 miles away in 40 minutes instead of 8 hours.

The time you get back is possible because of these chemical processes. And these chemical processes are executed by these machines (i.e. "units"). And when you look beyond the symbols of wealth (which happen to be fancier units like yachts and airplanes and sports cars), you realize that the wealthy have limitless time for leisure, while the poor do not. No truer words were spoken when they invented the phrase, "Time is money."

Zymergi thinks the path to creating more wealth for us, our customers, and their customers is to help people who run chemical processes better "see" what their units are doing and get more out of them. The easier it is to "get data," the more time our customers get to "understand the process." And the more process understanding, the greater ability to change the course of the process for greater profitability.

The world where machines do more work means a world where humans have more leisure. Automation is the answer.

Even the world of Star Trek, where does this time...

...to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before

come from?

They (the crew) are enabled by the Starship Enterprise. The starship is simply a plant that manufactures light-years. What runs the enterprise? A "computer" that is simply the starship's SCADA. Again: automation systems.

In virtually every scenario of the future we want to live in, automation... units... chemical processes are there enabling humans to have more time... more leisure.   This future of greater time and wealth is the Zymergi Vision.

The Zymergi Mission: the relentless pursuit of excellence in systems integration and automation software is the straight-line that you can draw from our reality today to our vision of tomorrow.

  

ZOOMS 2 - Fastest Way to View Trends

So in addition to biologics manufacturing commentary, it turns out that Zymergi is actually a for-profit business that provides software, consulting and technical support.

For 2014, we're pretty much booked on the technical support side, but I wanted to take some time to talk about our software products.

Our flagship product is ZOOMS, which is an acronym for Zymergi Object-Oriented Metadata Search.  And in 2014 - thanks to Edward Snowden, more people know what metadata is than in 2008 when we started ZOOMS (v1.0)

So why are we interested in searching metadata? Well, let's take a step back. When working the front lines of campaign monitoring and process support, we noticed that viewing trend data (i.e. tag values plotted against time) was the principal component of process understanding. The more trends a person reviewed, the more process knowledge they gained and the more they understood normal from abnormal.

And in all that time, very few people actually learn to speak "Automationese."

"Hey, did you see that weird thing going on with T100.GLOBAL.CLX.AI05.PV?"
- No one ever

In the automation world, everything is a tag. In the Manufacturing Sciences world, everything is about a measurable parameter within the process. So when you listen to the process scientists and engineers talk, it's always about some parameter (e.g. "Optical Density") in some unit (e.g. "Tank 100"). That right there is the metadata of a tag.

The tag takes care of the Y-axis on the trend. What about the X-axis?

The X-axis deals with time-windows: start times and end times and the metadata around the time-windows are called, "batches." Specifically using S88 terminology, people involved with campaign support are interested in Unit Procedures, a.k.a. "unitbatches."

I'll leave the formal definition of "unit procedure" up to the automation gurus, but to a Manufacturing Sciences data engineer, a unit procedure is a process that happens on a piece of process equipment.

So say you're making rituximab in production bioreactor T100 using the version 1.1 process and batch R2D201 ran from 20-Dec-2013 to 28-Dec-2013... that there is a unit procedure:

batchid	unit	product	procedure	start time	end time
R2D201	T100	rituximab	production culture version 1.1	20-Dec-13	28-Dec-13

The metadata around this time-window (i.e 12/20/2013 to 12/28/2013) are as follows:

• R2D201
• T100
• rituximab
• production culture version 1.1

So it stands to reason that if an internet user who knows nothing about a subject can type keywords into Google and get the most relevant results on that subject; that in 2014, a process citizen who doesn't know too much about the process ought to be able to type some keywords into a webpage and get some process trends.

And now they can: Introducing ZOOMS 2:



Learn More

ZST is 67% faster.

For those of you who don't know, the ZST (Zymergi SQL Tool) is a Windows-app that gets your database information and puts it in any format you want.  Typically, customers want to convert their relational data to HTML5 so that they can view (and act on ) it with a desktop or mobile-device browser.



Well, there's good news.  ZST is now 67% faster.  Now, this increased speed may not matter in an enterprise environment where apps are feature-rich, but slow.  But for our customers with external-facing websites, more speed = more revenue.

So why would the enterprise customer want ZST?

Well, the first thing is that this is commercial off-the-shelf (COTS) software.  Secondly, you're essentially adding search and browsing capabilities to your existing relational data.  And ultimately, you're looking to institutionalize tribal knowledge.

• Boosting speed of ZST
• ZST Support Page

Data Visualization - Learn By Looking

by Oliver Yu

So the least rigorous form of statistical analysis is simply looking at the data. I've written about this before where you can tell quite a bit about a phenomenon just by looking at the data (no p-values, no alphas... just looking at the data)

Here was that example distribution of test scores:

When you look at the data and there are irregularities or non-smoothness, you're looking at some human intervention... some manual action that does not comport with the natural order.

Have a look at this visualization. It's apparently the average monthly premiums for insurance plans under the Affordable Care Act for each county. Dark blue are plans that cost $250/mo. Dark red are plans that cost $1,250/mo... so the more red, the more costly.


What's most interesting to me is that you can see the shapes of Virginia, Wyoming, South Dakota and New Jersey pretty well on this map according to the price of ACA insurance premiums. Some guy living in Montana is paying $500/month; cross an imaginary line into Wyoming and now it's $1,000.

When you see something like this, you can infer that a non-natural phenomenon holds the true explanation (e.g. state law). There's a step-function here and step-functions aren't found that often in nature.

Now have a look at New England: here, there's a gradient... the farther northeast you go, the more costly the insurance. Likewise in Wisconsin... the closer you get to Minnesota, the more expensive the premium. Gradual changes or smoothness is what we can expect for nature. And a lot of information can be inferred by just looking.

Thuperbowl1!!!! (Excel vs. PI continuous vs stepped)

I was actually pulling for the Niners yesterday primarily because I've lived in the SF Bay Area since 1999; but on balance, I didn't really care about the game: the Pixburgh Stillers weren't playing.

That and because the NFL actively supported SOPA, the bill that aims at restricting our internet freedom:

That said, here's a look how scatter plot of score vs game duration.


Source data:  Milwaukee-Wisconsin Journal Sentinel

The awesome thing about Excel is that you get to change the Y-axis increments (I made it 7 since that's how many points are in a touchdown)... as well you can configure the X-axis increments (I made it 15 since that's how many minutes are in a quarter).

It's a nice graph and all, but not terribly reflective of what actually happened.  You can see from the start of the game, there's a ramp from 0 to 7 for the Baltimore Ravens.  That's not what actually happened.  At 4:23 into the first quarter, the score was still 0.  At 4:24, the Ravens' score was 7.

Let's look at what this graph looks like in PI ProcessBook with correctly configured tags:

Here, is an accurate depiction of what the scores were at the time they happened:  the score goes up in increments forming what looks like "steps". 

When you have infrequent data, the most accurate visual representation of the data is to set the step point attribute equal to one (step=1).  For cell culture and fermentation, you do this for any offline measurement such as:

• viable cell count
• viability
• offline pH
• Osmo
• Glucose, Lactate, Ammonium, Sodium

If you have it configured any other way, it may look funky... like that first plot in Excel.

#GoogleMaps for #iPhone at 40,000 feet.

by Oliver Yu

So I'm flying back from a client site yesterday and I'm on one of these Southwest airplanes with WiFi.

It was a 1 hour 20 minute flight and probably less than an hour for web surfing time, so I figured the cost wasn't worth it.

But I connected to the WiFi anyway and Southwest lets you go to their mobile website, track their flights.

Well, earlier in the day, I read that GoogleMaps for iOS6 made its debut and had downloaded it.

So I figure I'd kill five minutes checking it out.  So I'm at 40,000 feet, and it slowly dawns on me that I can zoom in, zoom out and pan to wherever I want in the world.  So I tried to see if GoogleMaps could find my location... and it did.

The GoogleMaps App must be getting data across the Southwest WiFi.  And since Southwest blocks port 80 (i.e. so you cannot surf the internet without paying them their 5 bucks), GoogleMaps must be working off some other port.

Here's me somewhere over a field in California's central valley:



Here's me a few seconds later:



And I'm clear in another field a few seconds after that.



This GoogleMaps visualization was so cool because I could see what the land actually looked like below (in Satellite mode).  I could fly as high or as low as I wanted to (zoom level).

For the remaining 20 minutes of the flight, I was no longer a weary software consultant in seat 17E...  I was Superman blazing across the Central Valley fields.

Too bad we had to put away our electronic devices in preparation for landing, otherwise I'd have watched it the whole way.

Great job, Google Maps... Well done.

Related articles:

• Why Google Maps for iOS6 is Better Than The Old Google Maps.
• GoogleMaps for iOS6 is Number 1 Download  - CNBC

PI ProcessBook - Best Biopharma Practices 3

by Oliver Yu

ProcessBook can open 2 types of files:

1. .PIW are ProcessBooks
2. .PDI are Displays

And frankly, I can't think of a good reason to have .PIW files anymore.

ProcessBook (.piw) files are mostly navigational.  You create this glorified outline of essentially text links:




And that's it.  Your users are looking at an outline.  Big whoops.

In its heyday, I bet this knocked the socks off a ton of people.  But we have the internet.  Even the desktop browser seems old compared to these snazzy phones and tablets.

The world has grown up in a damn hurry and for PI ProcessBook to compete, you basically have to go with PI displays.

My recommendation is to create remarkable PI displays for more than just engineers and operators.  Here's that same PIW file made into a PI display:

So instead of a static text-linked outline, make a display where you can see the entire area.  In the above figure, there are only 5 units in use.  Now, users aren't wasting their time clicking into the display for a unit that has nothing going on.

And this is important when you want to engage infrequent-PI users.  Not everyone has a job where looking at the process is a daily task.

Moreover, these area overview displays are a low buck, high bang activity...especially for management.  Managers like to see the things they're paying for... the easiest way to show off their investment in PI is to create remarkable displays that they can relate to.

The more you market their investments to them, the more they're willing to plow cash back into your projects.

It's a win for your users.  It's a win for your management.  And it's a win for you.

Previous best practices:

1. Standardize On Colors For Key Parameters.
2. Use White/transparent Background For Presentation-Ready Displays.

PI ProcessBook - Best Biopharm Practices 2

by Oliver Yu

The thing about visualizing process trends is that at some point, you're going to have to make a decision with it.  And when you make a decision with it in the cGMP environment, you're going to need someone to review the decision.  Perhaps this decision is big enough that you're going to need to document it.

Or perhaps, this decision needs a little CYA and you're going to have to present it to the plant management.  Whatever the case, there comes a time when you're going to have to take what you're seeing out of PI ProcessBook and put it in a Microsoft Word document or Powerpoint slide.

This is where the core philosophy of my ex-boss "Jesse B." comes in handy.  Jess is a big believer in one-stop or "few-stop" shopping for data.  You go to one or two places for data and spend the rest of your time analyzing.  OSIsoft PI server is the ideal stop for plant information.

The corollary to "One-Stop Shopping" is "No Additional Editing."  This means having the PI display formatted correctly where "correctly" means no additional work has to be done.

Face it, when you're facing a big decision and you've spent all your bandwidth on analyzing the data, the last thing you want to do is mouse around trying to get the background color right, or putting lipstick on the proverbial PI display pig.

Here are a few things to help you out:

• Use a white or transparent background for your PI ProcessBook displays.
  All Word documents and most Powerpoint slides have white backgrounds
• Use dark colors for primary tags
  The tags that need the most attention should have dark to contrast against the white background
• Use lighter colors for noisier tags
  Noisy tags like jacket temperature or controller output will do well with lighter colors

Have a look at this display and you can tell immediately that this can be copied and pasted directly into a memo with no additional editing:

You're shaving 5 to 10 minutes off every presentation you make.  Over the course of a week, we're easily talking an hour or two of your life you're never going to have to spend on making your memo look pretty.

PI ProcessBook - Best Biopharm Practices 1

by Oliver Yu

There's this guy I knew who dropped out of the Air Force Academy. He was telling me that I'd never last (probably true). For example, he was saying that the amount of conformity was insane. Everyone had to fold their bed the same way. Their underwear in the same drawer, shampoo in the same drawer. Had to pack their bags the same way.

And the reason, I'd imagine, is in the heat of combat, you need some ammo from your buddy, that you know where he's packed it and can get to it without asking. And the sooner you enforce this discipline, the better off you are.

The same goes for PI ProcessBook displays. The great thing about ProcessBook display is that once you know how to create stuff, people go crazy and create a bunch of displays using the default colors. There are some folks who will change their own colors, but overall, it's a jungle out there.

The bad part of this is that displays are usually shared. The way people actually use ProcessBook is by pulling it up to show someone.

Maybe you're a Manufacturing Sciences plant support guy and you need to show an operator what's going on and why he needs to switch to controlling off the other probe.

Maybe you're showing your boss why you think this batch of media is contaminated.

Maybe you're presenting data to the VP of the plant a real-time status update and you needed a screenshot for your Powerpoint presentation.

Whatever the case, the moment you show someone your ProcessBook display, they're spending the next 5 to 10 seconds reading the labels to figure out what is going on. Meanwhile, you've started explaining what's going on, dragging that cursor left and right.

The way to fix that is standardizing on your colors:


For cell culture displays, I've proposed:

• pH and related trends - red
• dO2, Air, O2 Sparge - blue
• Temperature (Vessel/Jacket) - green
  Red and blue represent hot and cold, so a neutral color like green makes sense.
• Agitation - black
• Volume - orange
  The color of media is orange
• Pressure - grey

If you have a vibrant PI user community at your organization, standardizing on parameter-color is going to be a tough sell.  But if you can pull it off, it will be a great stride towards organizational efficiency.

OSI PI ProcessBook Glossary

by Oliver Yu

There's a ton of confusion regarding PI ProcessBook terminology. This short post will help clear it up.

PI ProcessBook

A OSIsoft-written Windows application that renders trends with PI data

Because this is the software people use to view PI data, users often confuse this with PI itself.

ProcessBook

A file-type (.piw) that can be read by PI ProcessBook application. Helps organize displays

A ProcessBook is one of two types of files that can be opened by PI ProcessBook (the application) used to organize displays and help users navigate the plethora of files on the file server.

Display (aka "PI Display)

A file-type (.pdi) that can be read by PI ProcessBook application. Typically, users open pre-configured displays to view data

PI display is where the magic happens.

Symbol

An object on a display that graphically represents PI data

Trend

A symbol that plots tag data versus time

The trend where PI data gets plotted. Users interact with the Trend symbol the most to visualize what's happening with the process.

Trace

A curve on the trend of plotted PI point data. The above trend has 3 traces.

If you understand the world in Microsoft Excel terms, here's the analogy:

Excel	PI ProcessBook
Workbook	ProcessBook
Worksheet	Displays
Chart	Trend
Series	Trace

If you open up VBA (Alt-F11) and explore the guts of PI ProcessBook, you'll see that the objects behind PI ProcessBook are named this way.

Further reading:

• PI ProcessBook is trend visualization tool
• PI ProcessBook for Mass Balance
• Biopharma ProcessBook Consulting