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Case Study of EnergyEfficiency Improvement inBayer, Baytown
Pratik Misra, Ph.D.Texas Technology ShowcaseGalveston, TX, Dec 6-7, 2006
BCBS BTS AmericasProcess Technology GroupPage 2
Bayer Group and Bayer Technology Services As a Part ofBayer Group
Methodology –Total Performance Optimization (TPO) SixSigma
Case Study Results
Presentation Outline
BCBS BTS AmericasProcess Technology GroupPage 3
Bayer AGBayer AG
Corporate CenterCorporate Center
Business Units
CropScienceCropScience
MaterialScienceMaterialScience
HealthCareHealthCare Service Units
Industry ServicesIndustry Services
Business ServicesBusiness Services
Technology ServicesTechnology Services
Bayer Group: Organization
Services offeredon the external market –LanXess, BioDiesel ....
Services offeredon the external market –LanXess, BioDiesel ....
Employees worldwide(*) 2,100
Customer segments•HealthCare•Crop Science•Polymers•Chemicals
(*) Status: 2005LanXessLanXess
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Bayer Technology Services: Product Portfolio
Product & ProcessInnovations
Plant Optimizaton Consulting &Services
•Technology Inovation•Process Engineering•Project Support•Pressure Safety Expertise•Materials Engineering
•Engineering DisciplineExperts
•Design Guidelines andPractices
•Site Master Planning /Development
•Energy and Utilities•Mechanical Integrity•Inspection Services•Engineering Computer
Systems
•Process Monitoring andOptimization
•Advanced ProcessControl
•Process AnalyzerTechnology
•Production Scheduling•Logistics•Supply Chain Optimization•Advanced Manufacturing
Solutions•Dataanlysis/Datamining
Engineering &Construction
•Project Management•Scope Development•Basic Engineering•Cost Estimates•Detail Engineering•Procurement Coordination•Construction Management•Commissioning•Qualification•Validation Support•Site Engineering
Extensive services for the entire process and plant life cycle from asingle source with the know how of a global company.
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Bayer Group and Bayer Technology Services As a Part ofBayer Group
Methodology –TPO Six Sigma
Case Study Results
Presentation Outline
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Mission: To Extract the Maximum Value from:
1. Six Sigma and / or Lean Sigma Methods
2. Technical ExpertiseOrder Procurement Manufacturing Distribution Cash
Measurement, modeling and total system’s analysis & optimization
3. Digital InvestmentProcess Management Systems (PI, LIMS, APC etc.)
ERP’s (SAP data and workflows)
Datamining & data analysis softwares
TPO Six Sigma –An Innovative Solution
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Six Sigma- Business Definition
Six Sigma* Improves customers’experience
Improves operational efficiency
Builds a winning & transparent culture better leaders
Two Easy Steps Measure & accept that variation in processes & products is evil
60% of the work is to bring this mindset
Analyze and implement improvements to get rid of evil
40% of the work
Measurable Value 10 - 30% improvement in process speed and efficiency
2 to 4 fold improvement in process capability to satisfy customers
*Winning by Jack Welch, pg. 247, 2005.
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Only 1.5 Sigma Level
MeanLowerLimit
UpperLimit
6 Sigma Level
1.5*σA6 *σB
Quality or Lead time Quality or Lead Time
Process A Process B
MeanLowerLimit
UpperLimit
Sigma Level –A Measure of Process Capability
MeanLowerLimit
UpperLimit
1.5*σA
MeanLowerLimit
UpperLimit
6*σA
BCBS BTS AmericasProcess Technology GroupPage 9
Bayer Group and Bayer Technology Services As a Part ofBayer Group
Methodology –TPO Six Sigma
Case Study Results
Presentation Outline
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Case Study –Define Phase of TPO Six Sigma
April 2003
After changes in a polyurethane raw
material production unit, the unit was not
able to consistently meet special product
specifications at high rates.
May 2003
A six-sigma optimization project was
launched to deliver sustainable process
improvement, following the six sigma
methodology. Project focus was on total
performance optimization including rates,
energy usage and quality.
Base May 2003Rate: 100,000 lb/dSteam: 1.00 lb/lbQuality: Mean -Level
Q1 104 0Q2 1.7 1
Target1Rate: 112,500 lb/dSteam: 0.875 lb/lbQuality: Target -Level
Q1 70 or less 4Q2 1.75 4
Target2Rate: 140,000 lb/dEnergy and Quality: Same as
Target 1
Step 1: Define Phase
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Case Study Measurement Phase
Data Collection
Operating Data (PIMS,LIMS)
Weekly Review w/ Operations
Validate measurements
Visual mining of data
“Quick wins”- Immediate
implementation
150 Process & Performance Variables
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Case Study Measurement Phase
On-Line Performance Monitoring System 24/7 Smart Tracking Tools Bring Transparency and Knowledge to the
Workflow and Prevent Backsliding
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Case Study Measurement Phase
On-Line Performance Monitoring System
All important variables that can affect quality and energy usage are
constantly monitored and if they go out of “good”bounds,
operations is alerted by change in color in monitoring system.
24/7 Smart Tracking Tools Bring Transparency and Knowledge to the
Workflow and Prevent Backsliding
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Case Study Measurement Phase
On-Line Performance Monitoring System
Trends are also created for the important variables.
24/7 Smart Tracking Tools Bring Transparency and Knowledge to the
Workflow and Prevent Backsliding
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-8-7-6-5-4-3-2-1
0123
Prin
2
-9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4
Prin1
Bivariate Fit of Prin2 By Prin1
Case Study Analysis Phase
Data-analysis of “Good”and “Bad”Operating Regions
Green: Highvariation
Red: BadBlack:Good
Cluster Analysis of entire process Multivariate Analysis
Distinct Multivariate Performance
Clusters
Critical Variables, Xi
Key variables that impact quality,
rate and steam.
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Case Study - Improvement Implementation
Organized plant tests
Set-point Changes
Process ControlImprovements
New ratio controls wereimplemented
Steam usages werecascaded
Advanced tools werecreated that help operationsto predict quality goals andreach them in an energyoptimal way
January 04 (After)Improved operating
Conditions w/ less VariabilityMay 03 (Before)
PC 1
PC
2
EA V1EA Steam
EB V2*EC V3
* Important steam optimization variable with no quality impact
Jan. 04May 03
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Specific Energy Usage vs. Rate in two periods before and after Six Sigma Optimization.
Much lower energy usage after optimization. Energy-rate relationship has been fundamentally
shifted as a result of optimization.
Case Study - Measurable Improvements
Steam UsageSpecific Energy Comparison
0.4
0.6
0.8
1
1.2
1.4
1.6
50000 70000 90000 110000 130000 150000 170000
Norm. Prod. Rate
No
rmE
ner
gy
Use Jan -Jun 04
Jun-Nov 02
Power (Jan -Jun 04)
Power (Jun-Nov 02)
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Case Study - Sustainability of Results
Continuous improvement using six sigma methodology has continued in this unit.
The energy and rate gains have increased every year as shown in chart below.Quality has been sustained to meet all customers specifications.
All gains have been achieved without major capital expenditure.
0.000
0.200
0.400
0.600
0.800
1.000
1.200
1.400
2002 2003 2004 2005 2006 YTD
Normalized Average Yearly Production
Normalized Yearly Average Specific Steam
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Target 1:
Achieve Normalized rate 112,500 lb/day with
Normalized energy usage target = 0.875 lb/lb
product
Quality 1 < 100.0; CP of 1.3, Target: 70.0
Quality 2 1.5 to 2.0 with target of 1.75, CPK of
1.3
Target 2:
Achieve 140,00 lb/day with same quality
specification as in phase 1.
2004 Project Score Card - Targets vs. Results
Sign-Off The champion signs off the
sustainable results of theproject.
The team celebrates andstrives for continuousimprovements.
Improvement methodologyimplemented in other units inthe train.
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Comparative Magnitude of Energy Savings
Industrial consumption accounts for 33.25%of energy consumed in US.
Number of industrial manufacturing facilitiesis much lesser than numbers of homes,commercial buildings, and vehicles.
Energy savings in just one industrial plantcan be very big when compared to savings inother sectors.
Energy Information Administration, Annual Energy Review 2004
The energy savings shown in this casestudy and other units in the same productiontrain were equivalent to replacing 3800 regularsedans with hybrid cars in a year.
X3800
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Pratik Misra, Ph.D.(281) 383-6341