Transcript

TCS Mapping Six Sigma in TCS Mapping Six Sigma in client’s processclient’s process

TCS – An IntroductionTCS – An Introduction

• Largest software IT and management consultancy

• Staff strength of over 70,000

• Revenue of US $ 4.3 bn in 2006-07

• Tata Research Development and Design center

• ISO 9000 certification across 95% of the company in 1995

…………contd contd

• Software Engineering Institute’s ( SEI ) Capability Maturity Model

• About SEEPZ

• About Chennai

Product Engineering PracticeProduct Engineering Practice

• Delivers end-to-end solutions • > 1500 consultants• Over 6000 person-years of experience• High end consulting expertise 1. Automotive 4. Marine Engineering

2. Aerospace 5. Transportation 3. Heavy Engineering

TCS practise Six Sigma for some TCS practise Six Sigma for some client’s processclient’s process

6σ - An Introduction

• Founded by Bill Smith at Motorola in 1986

• Inspired by quality control, TQM and Zero Defects

……..contd..contd

• Registered service mark and trade mark of Motorola Inc.

• Motorola saved US $ 17 bn

• Practiced by BA, Caterpillar, HI, GE 3M, Merry Lynch

• 2 key methodologies – DMAIC & DMADV inspired by Demming’s cycle

…….contd.contd

• TCS adopted 6σ initiatives ( not yet a six sigma company ) in 1998.

• > 350 trained six sigma technology consultants

Why SIX SIGMA ?Why SIX SIGMA ?

• Reduces costs by 50% or more• Reduces waste chain.• Better understanding of customer requirements.• Improves delivery and quality performance.• Provides critical process inputs• Develops robust products and processes• Drives improvements rapidly with internal

resources.

How much is TCS capable for its How much is TCS capable for its implementation?implementation?

• Over 350 experienced Six Sigma consultants• 260 Certified Green Belts, 12 Black Belts and a Master Black

Belt• 400 Six Sigma projects completed.• Quality Standards

– Six-Sigma– SEI-CMM– ISO 9000– Tata Business Excellence Model (Based on Malcolm Baldridge-

Award)• Specialized training programs• Domain experts 

Where will TCS implement six Where will TCS implement six sigma ?sigma ?

Service Offerings• Six Sigma for Organizational Business Process

Improvement• Six Sigma for Product Quality Improvement• Six Sigma Consultancy for Services

– Engineering Services– Architecture & Technology Consulting– E-Security– E-Business– Infrastructure Development and Management

ResultsResults

Six Sigma Projects completed in the areas of

• Cycle Time Reduction

• Defect Prevention

• Productivity Improvement

• Process Refinement

• New Process Definitions

• Design Optimization of Products

Our ObjectiveOur Objective

To study implementation of six sigma process in OEDC (Offshore Engineering

Development Center), Chennai

for General Electric corp.

In 1998 - 1999In 1998 - 1999

• OEDC carried out 4 six sigma projects

• Schedule compliance and product quality compliance

• 4 phases – MAIC (Measure, Analyse, Implement, Control)

• Center Managers, Project Leaders, Quality team and all team members participated.

• Undertaken for 2 GE business teams.

11stst step – Measurement step – Measurement

• Process mapping to reduce variability, time & cost

• Identification of key input and output variables at every step

• Objective – To eliminate non-value-added process steps, bottlenecks and re-work process.

Input variables which affect CTQ such as schedule Input variables which affect CTQ such as schedule compliance & quality compliance were identifiedcompliance & quality compliance were identified

Process Variables : Schedule Compliance• Estimates • Realistic estimates • Input Study • Project Management• Effective project tracking and Monitoring • Fixing up priorities • Resources management • Input Quality • Clarity and completeness• Conformance to standards

Process Variables : Product Quality

Knowledge

ProductStandards

Input Quality Clarity Conformance to Standards

Estimates

Estimated time

Tight schedules

22ndnd step - Analyse step - Analyse

• Cause & effect Diagram - To isolate key problem areas

- To study the variance from the ideal performance

- To identify relationship between variables.

C & E - Mechanical - Schedule Compliance

Components variationsin frames

Initiator specific requirement

H/W problems(network, m/c, links)

Delayed response toclarif/int.del.feedback

Power failure

Use of incompletePDM filesChange

of scope

Estimation Execution(Model)

Insufficient timefor dwg. Studybefore execution

Communicationbetween team members

Errors during execution

Improper assumptionduring execution

UG limitationsVersion problems

New team membersfor specific components

UG H/w Bugs

Attempting to maintainsimto values

D.N. & clarifs. not given to EQA

Dimension(conflicting, insuffi-cient redundant, ambiguous)

Delivery

PDM structure

File /directorypermission

Unawareness of del. Format del.

procedure

Power failure

V C interruption

Unforeseen eventsfrom PDM, execution

Scope change duringdelivery

Forms filing & auth.procedures

Absentism of teammembers

Delayed responseto dwg requests

Ambiguousinputs

Link problems(PE, drop box)

Insufficient supportfacilities(H/W, paper)

PDM files not asper dwgs/stds

Poor quality ofinputs

Commn, of scope

Inadequate studyby execution/QA

Inadequate inputs

Non-availabilityof DPA(scope)

M/cs with insufficient features

(*based)

Frequent changes in GE Database(COPICS,PDM,revisions in dwgs)

Data storage retrieval

Insufficient m/cs

Non uniformityin h/w features(keyboard, mouses)

Insufficient disk space

Compatibility betweenmachines(OS)

Change in shift

New team members

Non uniformityof skills acrossmanpower

Frequent shiftingof manpoweracross pkgs

H/w limitationNon uniformworkload by GE

Priorities(undefined,change)

Manpower absenteeism

Input Study Scheduling & res-ource allocation Execution drafting

Q A

Infrastructure(space h/w)

Decision on splitting of sheet

Drafting updationdue to change in GE Data

base

UG limitations(splitting, views,blends)

Compatibilitybetween Simto

& model

Error on modelat draftingstage

Skill level bet. team members

Non availabilityof GRIPS

Non availabilityof tool onall m/cs

Initiator specific stds.

Ambiguitiesin simtos

Peripheralproblems(plotterprinter, paper)

Aware-ness to stds

DN, clarif.overlooked

Too many QA ChecksMore than

one simtos RepeatedQA

Defect loggingnot clear

Commn. betEQA duringexecution

Involvement of EQA& Execution team

Study ofinputsby QA

Awareness of Stds

Shortage of QAmanpower

inconsistencyacrossQA team

members

Error duringdrafting Chklists

updationinitiatorspecific

Schedule slippage

Link

Cause and Effect Diagram

22ndnd step - Analyse step - Analyse

• Cause & effect Diagram - To isolate key problem areas

- To study the variance from the ideal performance

- To identify relationship between variables.

• Process Failure Mode and Effect Analysis (PFMEA)

- To identify ways in which project can fail

- To estimate risks

- To evaluate current plans

33rdrd step – Improvements step – Improvements

• For the Process improvement, the following were introduced…

- Process controls

- Error Proofing/ Productivity Tools

• Management actions to prevent failure causes

Improvements carried out by TCSImprovements carried out by TCS

MANAGEMENT ACTIONS

– New Facility– New Hardware

PROCESS IMPROVEMENTS

– Procedures– Guidelines– Error Proofing

Tools

– Productivity Tools

PROCESS CONTROLS

– Project Review

Meetings

– Causal Analysis – Internal Audit– Compliance

Monitoring

44thth step - Control step - Control

• To assure six sigma spread would fit within limits of specifications ( Process capability study)

• To draw normal curves for CTQs and make decisions about capability of the process ( Process generated data)

On-time delivery and Product Quality On-time delivery and Product Quality

20100-10-20-30

150

100

50

0

sch.slip

Freq

uenc

y

Histogram of sch.slip, with Normal Curve

3210

500

400

300

200

100

0

C2Fr

eque

ncy

Histogram of C2, with Normal Curve

Normal Curve Charts

On-time delivery and Product QualityOn-time delivery and Product Quality

9080706050403020100

5

0

-5

Observation

Indi

vid

uals

11

1

1

1

X=0.055563.0SL=2.147

-3.0SL=-2.036

876543210M

ovin

g R

ange

1111

11

11 11

R=0.7865

3.0SL=2.570

-3.0SL=0.000

I and MR Chart for sch.slip

Control Charts

Trend charts for schedule Trend charts for schedule compliance and quality compliance compliance and quality compliance

Schedule Compliance

3rd Qtr '98 4th Qtr '98 1st Qtr '99 2nd Qtr'99 3rd Qtr '99

Quality Compliance

3rd Qtr '98 4th Qtr '98 1st Qtr '99 2nd Qtr'99 3rd Qtr '99

the end..

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