Industrial Analytics Transforms CP Kelco to Embrace the Future · 1. AF analytics to calculate fermentor phases into a PI tag for each tank (key component) 2. TrendMiner validated

#OSIsoftUC #PIWorld ©2018 OSIsoft, LLC


Industrial Analytics Transforms CP Kelco

to Embrace the Future Norman W. Ridgley

Sr. Manager Operational Excellence

For CP Kelco, a Huber Company



• Headquarter in Atlanta, Georgia

• Global leader in the manufacturing of specialty hydrocolloids with offices and manufacturing sites across the global

• 2,200 employees worldwide

• Have six global manufacturing sites

• Products are derived from raw materials found in nature



• All products are batch fermentation based

• Produced from bacteria found in nature • Examples:

• Xanthan Gum is derived from bacteria found on cabbages leaves

• Gellan gum is from the Lily pad varieties found on ponds/lakes

• Main uses include food, personal and oral care, beverage, pharmaceutical, industrial applications, and oilfield

• Examples

• Salad dressing is thick in the bottle for suspension, but flows when poured

• Long term suspension for specialty drinks

Biogums: Xanthan Gum, Gellan Gum, and Diutan



• Continuous batch process

• Pectin • Extracted from citrus peels (orange, lemon, etc.) or sugar beet pulp

• Gelling, thickening, and stabilizing in a variety of food applications • Example: Jam and jellies

• Carrageen • Extracted from red seaweed

• Gelling, thickening, and stabilizing for food, household and personal care industrials

• Example: Marinating of meat and poultry

Food Gums: Pectin and Carrageen



Common to These Six Sites -OSIsoft PI System-

Großenbrode, Germany Pectin

Limeira, Brazil Pectin

Lille Skensved, Denmark Pectin, Carrageenan & Refined LBG

Okmulgee, Oklahoma, USA Xanthan Gum, Gellan Gum

Matão, Brazil Citrus Peel Processing

San Diego, California, USA Xantham Gum, Gellan Gum



This Is Where We Started Not Getting Full Value from Our Data



• Theme was “Visualizing Your Data”

• All six PI using plant sites sent representatives • Included representatives from our corporate IT and OSIsoft

• The week was broken into four major parts • Where we are (baseline)

• What is possible

• What do we want to become

• Action plan to get there

• End of the week we had a five year plan and a process data users group

April 2017 Process Data Users Conference At Company Headquarters



• Use OSIsoft Asset Frame (AF) to facilitate process analysis through analytics, events, and notifications

• Create data relationships at the process and batch level

• Identify tools for visualizing, trending, and analysis

• Analyze based on exceptions to drive Simplicity

• Promote organic growth across sites sharing successes

• In addition • Train Process Engineers to maximize utilization of data

• Define Big Data Analytic Tools for further insights into the data

How We Plan To Capture Value



Base PI System

- AF & Notifications

Configuration - Training - Standards - Data Merge

Stage 1 - KPI Tracking - Deviations - E-Mail Alerts

Stage 2 - Batch Tracking - CBM - Analysis - OEE Equip

Stage 3 - Big Data - AI & Process Control

5- Year Process Data Progression Focus

18 months



• Okmulgee: Test integration of OSIsoft PI AF system, plant SQL databases, and data analytics tools

• Develop batch tracking using AF

• Microsoft’s Power BI for big data visualization

• TrendMiner for process data analytics to support the AF build and analysis of raw PI data

• Skensved: Develop AF events for batch tracking within a pectin and carrageen processing plants

Pilot Sites: Okmulgee and Skensved



• Built in 1977 as an all Xanthan Gum fermentation plant

• Site has had two major expansions

• Today produces numerous deviations of Xanthan Gum and other commercial gum types

• There are approximately 170 employees

• Using OSI PI System since 1998

The Okmulgee Site

Okmulgee, Oklahoma, USA Xanthan Gum, Gellan Gum



Fermentation Has Two Major Processes

Unit Op 2

Unit Op 1

Unit Op X….

Today’s Topic

Unit Operations



1. AF analytics to calculate fermentor phases into a PI tag for each tank (key component)

2. TrendMiner validated AF calculation of phases

3. Review potential KPIs using TrendMiner

4. Key KPIs are tracked by AF events for each batch

5. AF analytics capture statistics at the end of each batch into PI tags

6. Batch summary data captured in AF event including those created using AF analytics (step 5 above)

7. Power BI used PIOLEDB to extract event data and merge with plant SQL databases for “big data” analysis

Okmulgee Strategy & Action Plan



Tracking Individual Tank Performance

• PI Event Data • SAP Data • Local Data

Power BI Data Model • Shape data • Create relationships

• Create visuals • Analyze • Compare batch trends using TrendMiner



Configuration Step

1. Power BI was used to identify best performing batches (yield, quality, kg/hr rate, etc.)

2. In TrendMiner created overlays of the best 3-4 batches for a tank

3. Converted to a finger print in TrendMiner as show on the right

• Creates acceptable range of operation by PI tag

TrendMiner Finger Print Creation

TrendMiner Finger Print for Batch Deviation – Set Up



Analysis Step

1. Using Power BI visuals again, picked low performing batches needing further analysis

2. In TrendMiner used search filter to trend low performing batch

3. Compared low performing batch to the finger print created early

4. In this case it was a startup issue causing the control logic to deviate on the low performing batches

5. Installed event and notification monitoring

TrendMiner Finger Print Creation

TrendMiner Finger Print for Batch Deviation – Analysis



• Used layers in TrendMiner to compare batch runs

• Discovered deviations in the batch process control that only lasted for a few minutes

• Consistent across all batches

• After review was able to see issue with batch process control logic

• Logic will be updated to remove deviations

Using Layers in TrendMiner to Compare Batches TrendMiner Overlay Example

Batch Clock Relative



• Failure alarm issue with the fermentor tanks

• Failure descriptions from the control system was limited

• Using TrendMiner and AF batch markers to summarize valve operations and download the data to Excel

• Using pivots exposed high frequency of specific valve failures or tank

• Data is being used for reliability improvements

Productivity Improvement



• Created event severity levels based on key process variables

• Used TrendMiner to validate AF calculations and stats

• Collected associated process data within the events to better understand root cause

• Supporting process variables of the event

• Now starting to use it for some batch operation monitoring with “start triggers” marking the different operational statuses

Linking Tag Deviations To Batch Productivity and Quality



Reducing Deviation Improved Okmulgee OEE Using OSIsoft AF/EF, TrendMiner, and Microsoft’s Power BI the site was able to identify and either reduce or eliminate process deviations. Reduction in deviations supported the overall process improvement objective of over $1MM annual savings.



• Was a key support tool in identify deviations within our process

• Validate if the deviation was repeating and the degree of impact

• If yes then we spent resources to develop an AF model for reporting into Power BI

• Used TrendMiner to validate the AF models were working properly

• Finger printing and overlays were key to determine operational deviations in the batch control system

• Used to support capital engineering projects to confirm operational issues

• Resulted in a project to upgrade during shutdown of this year

Summary


RESULTS CHALLENGE SOLUTION

COMPANY and GOAL

22 #OSIsoftUC #PIWorld ©2018 OSIsoft, LLC

Industrial Analytics Transforms CP Kelco to Embrace the Future We wanted to advance our use of process data across sites by leveraging OSIsoft AF and creation of a visualize analysis tools. Our pilot at the Okmulgee site tested the benefits of using AF, TrendMiner, and Microsoft’s Power BI to construct data models for visualization of process data.

To advance the use of plant data to improve throughput, quality and operating cost.

In April 2017 Process data conference was held at company headquarters

Pilot program at Okmulgee used AF, Power BI, and TrendMiner in an effort to improve OEE.

• Agreed to expand site data infrastructure

using OSIsoft AF and standardize on

configuration

• Growth was to be organic using

engineers at each plant site

• Agreed to pilot TrendMiner and

Microsoft’s Power BI

• All six plant sites were using the same

basic data infrastructure based on

OSIsoft data historian and Process Book

for the past +15 yrs

• How to advance data analysis using new

tools and merge with other data sources.

The Big Data challenge

• Okmulgee site OEE numbers have

improved as process deviations were

reduced. Potential $1MM per year

savings



• Enhance integration with TrendMiner and Power BI

• Expand the number of TrendMiner Users

• Begin to branch out AF/EF to remaining processes

• Track batches in the recovery process within each unit operations

• Use TrendMiner to develop key KPIs and limits with each unit op

• Configure AF event deviations

• Expand AF into Utilities area • TrendMiner developing KPIs and operating alerts

• Develop AF tracking of major KPIs and events

Next Steps



• Norman W. Ridgley

• [email protected]

• Sr. Manager, Operational Excellence

• CPKelco, a Huber Company

Industrial Analytics Transforms CP Kelco to Face the Future

Norm’s

Trust in god, everyone else has to have data

If you torture the numbers enough you can get them to say anything

Share - Knowing it all still means nothing if tribe knows nothing



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Documents

Industrial Analytics Transforms CP Kelco to Embrace the Future · 1. AF analytics to calculate fermentor phases into a PI tag for each tank (key component) 2. TrendMiner validated