Case Study of Energy Efficiency Improvement in Bayer, Baytown · Case Study of Energy Efficiency Improvement in Bayer, Baytown Pratik Misra, Ph.D. Texas Technology Showcase Galveston,

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


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


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.



Methodology –TPO Six Sigma

Case Study Results



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


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.


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



Methodology –TPO Six Sigma

Case Study Results



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


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



On-Line Performance Monitoring System 24/7 Smart Tracking Tools Bring Transparency and Knowledge to the

Workflow and Prevent Backsliding



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




On-Line Performance Monitoring System

Trends are also created for the important variables.

24/7 Smart Tracking Tools Bring Transparency and Knowledge to the



-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.


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


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)


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


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.


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


Pratik Misra, Ph.D.(281) 383-6341

[email protected]

Documents

Case Study of Energy Efficiency Improvement in Bayer, Baytown · Case Study of Energy Efficiency Improvement in Bayer, Baytown Pratik Misra, Ph.D. Texas Technology Showcase Galveston,