DMAIC Methodolgy

Six Sigma – DMAIC Methodology(A case study)

A Seminar Report on

Presented by,Bharath M – 1MS09IM401

Contents :

Overview of Six Sigma 

Introduction – DMAIC Methodology Define Measure Analyze Improve Control 

Case Study • Ispat Industries Limited

What is SIGMA ?

Sigma is the Greek letter representing astatistical unit of measurement that definesthe standard deviation of a population. Itmeasures the variability or spread of thedata.

6 Sigma is also a measure of variability. It is a name given to indicatehow much of the data falls within the customers requirements. Thehigher the process sigma, the more of the process outputs, productsand services, meet customers requirements – or, the fewer the defects.

Six Sigma focuses on the Reduction of Variation that generates defects for customers.

Defect Reduction due to Variation is Achieved by Eliminating Root Causes of Variation that … Reduce the amount of variation in the process output and/or Move the mean performance of the process output.

Reducing The Process Output Variation

Moving The Mean

Six Sigma Tools: The DMAIC Process

Six Sigma’s DMAIC toolkit is without question the most effective process improvement framework known in industry today, and teams that learn and apply this methodology will achieve unprecedented success.

What is DMAIC?

DMAIC is the five-step approach that makes up the Six Sigma tool kit, and its sole objective is to drive costly variation from manufacturing and business processes.  The five steps in DMAIC are Define, Measure, Analyze, Improve, and Control. As the backbone of the Six Sigma methodology, DMAIC delivers sustained defect-free performance and highly competitive quality costs over the long run.

DMAIC Overview

DMAIC Phase Problem Solving Roadmap

Define What are the various opportunities

Which opportunity we will work on

Who will work on the realization of opportunity

By When the problem will be eliminated

Measure What is the Project Y

What is the specification on Y

What are the issues with Measurements on Y

Analyze What is the existing baseline on Y

How much we want to improve

What are the possible Xs impacting Y

Improve What are the probable Xs impacting Y

Where we should set these Xs

Control How the results will be sustained in the long run

Case Study :

“ Improvement In Liquid Metal Yield ”Ispat Industries Limited, Dolvi, Navi Mumbai

D M A I C• Project Title : Improvement in liquid metal Yield

• Business Champion : B.K.Singh

• Project Champion : Alok Chandra

• Black Belt : B.K.Devangan

• Project Launch date : 25/04/2008

• Target Closure date : 30/09/2008

• Estimated financial Gains : Rs. 111.62 Rs. Crore (Yearly)

85.6

86.486.3

86.1

86.9

85.3

83

84

85

86

87

88

Oct'07 Nov'07 Dec'07 Jan'08 Feb'08 March'08

Month wise trend of LM Yield

CTQ Drill down

HSM Contribution

Raw Material OverheadsDirect Cost

Yield CostConversion Cost

• Business CTQ : Increase in productivity• Customer : Business• Customer CTQ : Increase in LM Production• Internal CTQ : Increase in LM Yield at EAF

Problem Statement Average Yield for the period of Oct’07 to March’08 is 86.1% . Yield loss is the main contributor in direct cost at EAF. Our objective is to reduce Yield loss by analyzing critical parameter or any other Innovation in process.

Project Selection Criteria

Project Time Schedule

DMAIC Phase Target Completion date Actual Completion date

Define 30/04/2008 30/04/2008

Measure 15/05/2008 15/05/2008

Analyze 31/07/2008 31/07/2008

Improve 31/08/2008 31/08/2008

Control 30/09/2008 30/09/2008

Team Charter

S.N. Team member name

Emp. Code

Dept Name Role in the dept Responsibility in 6 sigma project

1 J P sahay 7747 SMS Oprn Shift in-charge

SMS Oprn

Feedback on process and implementation of countermeasure

2 R N Yadav 7568 SMS Oprn Shift in-charge

SMS Oprn

Feedback on process and implementation of countermeasure

3 Bharath M 11413 SMS Oprn SMS Oprn (Tech. cell)

Analysis and implementation of countermeasure

4 Swathi Siddabathula

11336 Technology & Innovation

Technical analysisData collection and analysis

Operational Definition

In the process of steel making ,the total liquid metal extracted from the raw material is called as Yield. So yield is basically output divided by inputIn any process.

At Steel Melt Shop

Yield (%) = [LM produced (Ton) / Total Charge (ton)]*100

Project Scope

Longitudinal:

Start – Electric Arc Furnace End – Electric Arc Furnace

Lateral:

Liquid metal yield in Shell–1,2,3 & 4

Financial benefit calculations

Business Target LM Yield – 87.88 % with the following charge-mix :

Hot Metal - 50.8% Prime DRI – 31.38%Cold briquette – 2.98%Scrap – 14.85%

Baseline LM Yield is 86.1% with 51.4 % Hot Metal & 10.04% ScrapNew baseline is 86.4% LM yield with the charge mix as per ABP.

Saving – 1.48 % Yield improvement – 111.62 Rs. crore/annum [with 3.18 mtpa LM prodn]

SIPOC

Blast Furnace

SIPScrap Yard

Hot MetalDRI

Scrap

ChargingBlowingArcing

Tapping

Liquid Metal

LFCaster

MillSlag Yard

Suppliers Inputs Processes Output Customer

Measurement System Design

Unit of measurement : %

Data Type : Continuous type

Data collected for base lining : June-08

Source of data : EAF heat report

Process Map Process Map

Graphical Summary

8887868584

Median

Mean

86.286.186.085.985.885.7

Anderson-Darling Normality Test

Variance 0.782Skewness -0.024032Kurtosis 0.804470N 81

Minimum 83.430

A-Squared

1st Quartile 85.205Median 86.0703rd Quartile 86.315Maximum 88.100

95% Confidence I nterval for Mean

85.755

1.80

86.146

95% Confidence I nterval for Median

86.010 86.160

95% Confidence I nterval for StDev

0.766 1.046

P-Value < 0.005

Mean 85.950StDev 0.884

95% Confidence Intervals

Summary for Yield

Process Capability

8887868584

LSL TargetProcess Data

Sample N 81StDev(Within) 0.32458StDev(Overall) 0.88696

LSL 85.21000Target 87.88000USL *Sample Mean 85.95049

Potential (Within) Capability

CCpk 2.74

Overall Capability

Pp *PPL 0.28PPU *Ppk

Cp

0.28Cpm 0.42

*CPL 0.76CPU *Cpk 0.76

Observed PerformancePPM < LSL 246913.58PPM > USL *PPM Total 246913.58

Exp. Within PerformancePPM < LSL 11262.44PPM > USL *PPM Total 11262.44

Exp. Overall PerformancePPM < LSL 201895.58PPM > USL *PPM Total 201895.58

WithinOverall

Process Capability of Yield

Defects – LM Yield less than 85.21%

Process Improvement Target

Business Target LM Yield – 87.88 % with the following charge-mix :

Hot Metal - 50.8% Prime DRI – 31.38% Cold briquette – 2.98% Scrap – 14.85%

Identification of sources of variation in Y thru brain storming

Factors affecting LM yield :

1. % Hot Metal 2. % Prime DRI3. % Scrap4. % Coal base DRI5. % HBI6. HM quality7. DRI quality8. Process Type9. Coke cons.10. Oxygen in Arcing

Analyze : % Yield Vs Process type

Process type

Yie

ld

90.0

88.5

87.0

85.5

84.0

85.698985.778

86.9343

86.0683

86.9496

Boxplot of Yield vs Process type

Analyze : % Yield Vs Process type

One-way ANOVA: Yield versus Process type

Source DF SS MS F PProcess type 4 649.87 162.47 32.70 0.000Error 3314 16466.19 4.97Total 3318 17116.06

S = 2.229 R-Sq = 3.80% R-Sq(adj) = 3.68%

Individual 95% CIs For Mean Based on Pooled StDevLevel N Mean StDev -----+---------+---------+---------+----100% Hot Metal 23 86.950 3.066 (--------------*--------------)Arc-Cojet proces 126 86.068 1.244 (-----*------)Arc-Con-Arc 549 86.934 1.866 (--*--)Conarc with scra 2088 85.778 2.207 (-*)Conarc without s 533 85.699 2.740 (--*--) -----+---------+---------+---------+---- 85.80 86.40 87.00 87.60

Analyze : %Hot Metal Vs Yield

HM Category

Yie

ld

3. More than 55% HM2. 45 to 55% HM1. Less than 45% HM

90.0

88.5

87.0

85.5

84.0

82.5

86.7183

85.8407

84.7214

Boxplot of Yield vs HM Category

Analyze : %Hot Metal Vs YieldOne-way ANOVA: Yield versus HM Category

Source DF SS MS F PHM Category 2 1221.69 610.85 106.84 0.000Error 3424 19575.53 5.72Total 3426 20797.23

S = 2.391 R-Sq = 5.87% R-Sq(adj) = 5.82%

Level N Mean StDev1. Less than 45% 430 84.721 2.7772. 45 to 55% HM 2068 85.841 2.2843. More than 55% 929 86.718 2.431

Individual 95% CIs For Mean Based on Pooled StDevLevel --+---------+---------+---------+-------1. Less than 45% (---*---)2. 45 to 55% HM (-*)3. More than 55% (-*--) --+---------+---------+---------+------- 84.60 85.20 85.80 86.40

Impact of arcing oxygen on LM yield

Remarks :

Test heat taken to restrict the oxygen injection in Arcing phase upto 200 t of total charge ,which lead to improvement in LM yield by 0.4%.