UNDESTANDING

SIX SIGMA:AN VERVIEW

Mr. VINOD NARAYAN PUND

HPGD/JL14/1232

SPECIALIZATION: OPERATIONS MANAGEMENT

PRIN. L. N. WELINGKAR INSTITUTE OF MANAGEMENT DEVELOPMENT & RESEARCH

YEAR OF SUBMISSION: JUNE2016

ACKNOWLEDGEMENT

I take the opportunity ofsubmitting this dissertation to express my deep regards towards those whohave offered their invaluable assistance and guidance in hour of need.

Mr. Nitin Suvarna, Mr Tharanathkuppa Swami and all my colleagues has been inspiring. And without their inspiration,guidance, the project would have remained a dream. I would also like to thank to Mr. Nilesh Tungikar of KPIT TECHNOLOGIES LTD. For his kind support, guidance and help for selecting this project and allowing me to go ahead with this project.

Last but not least, I would like to thanks to all my friends and family members, who had directly or indirectly given their kind co-operation and encouragement. I admit that co-operation and morality are keywords to success.

(VINOD NARAYAN PUND)

CERTIFICATE FROM THE GUIDE

This is to certify that the Project work titled

“UNDERSTANDING SIX SIGMA: AN OVERVIEW”is a confide work carried out by our employee Mr. VINOD NARAYAN PUNDworking as Team Lead,(Admission No.)HPGD/JL14/1232a candidate for the /Post Graduate Diploma in Business Administration.(HPGD-OPERATIONS MANAGEMENT) examination of the Welingkar Institute of Management under my guidance and direction.

SIGNATURE OF GUIDE:

NAME:Mr. Nilesh Tungikar

DESIGNATION:Project Leader

COMPANY:KPIT TECHNOLOGIES LTD

ADDRESS: 35&36 Rajiv Gandhi InfoTech Park, MIDC Phase I,

Hinjewadi, Pune -411057. Maharashtra, India

DATE: 15/06/2016

PLACE: PUNE

PREFACE

I take an opportunity to present this project report on “UNDERSTANDING SIX SIGMA: AN OVERVIEW” and put before the readers some useful information regarding my project.

I have made sincere attempts and taken every care to present this matter in precise and compact form, the language being as simple as possible.

I am sure that the information contained in this volume would be certainly prove useful for better insight in the scope and dimension of this project in its true prospective.

The task of completion of project though being difficult was made quite simple, interesting and successful due to deep involvement and complete dedication of my colleagues.

Undertaking by Candidate

I declare that project work entitled “UNDERSTANDING SIX SIGMA: AN OVERVIEW”

is my own work conducted as part of my syllabus .

I further declare that project work presented has been prepared personally by me and is not sourced from any outside agency.

I understand that, any such malpractice will have very serious consequence and my admission to the program will be cancelled without any refund of fees.

I am also aware that, I may face legal action, if I follow such malpractice.

Source of Data: The study is primarily based on the secondary data collected from journals, industry reports, company websites, news articles and reports.

Signature of Candidate

(Vinod Pund)

INDEX

  1. INTRODUCTION ………………………………………………………………7
  2. KEY ELEMENTS……………………………………………………………….12
  3. WHY SIX SIGMA………………………………………………………………20
  4. ORGANIZATION……………………………………………………………….30
  5. STRATEGIC SIX SIGMA………………………………………………………33
  6. GET STARTED………………………………………………………………….43
  7. METHODOLOGY.………………………………………………………………46
  8. DEFINE PHASE…………………………………………………………………49
  9. MEASURE PHASE……………………………………………………………..53
  10. ANALYZE PHASE……………………………………………………………...56
  11. IMPROVE PHASE………………………………………………………………59
  12. CONTROL PHASE……………………………………………………………..61
  13. DMAIC in Service Organizations………………………………………………..63
  14. TECHNICAL TOOLS…………………………………………………………..67
  15. DEFECT METRICS…………………………………………………………….70
  16. CONCLUSION………………………………………………………………….72
  17. BIBLIOGRAPHY……………………………………………………………….73

1.0Introduction

Six Sigma is one of the most important and popular developments in the quality field. It has saved huge amounts of money and improved the customer experience for a large number of organizations across the world, yet it is applied in an inconsistent and often reductive fashion in many companies. This has led to criticism in the literature and a number of abandoned implementations. This study guide is designed to provide an overview of the key elements, important historical context and current debates in the field of Six Sigma. It aims to give a coherent view of the underlying principles, and how these relate to practical application in a range of organizations as well as to other areas of study.

Six Sigma is a highly disciplined process that helps us focus on developing and delivering near-perfect products and services.

•A Measure: A statistical definition of how far a process deviates from perfection.

•A Target: 3.4 defects per million opportunities.

•A Philosophy: A long term business strategy focused on the reduction of cost through the reduction ofvariability in products and processes.

Accordingly, it is defined in a variety of ways by several authors, but for the purposes of these notes the definition from Pande et al (2000) focused on the more comprehensive philosophy of Six Sigma will be used:

“A comprehensive and flexible system for achieving, sustaining and maximising business success. Six Sigma is uniquely driven by close understanding of customer needs, disciplined use of facts, data, and statistical analysis, and diligent attention to managing, improving, and reinventing business processes.”

Features of Six Sigma:

Six Sigma's aim is to eliminate waste and inefficiency, thereby increasing customer satisfaction by delivering what the customer is expecting.

Six Sigma follows a structured methodology, and has defined roles for the participants.

Six Sigma is a data driven methodology, and requires accurate data collection for the processes being analyzed.

Six Sigma is about putting results on Financial Statements.

Six Sigma is a business-driven, multi-dimensional structured approach for:

  • Improving Processes
  • Lowering Defects
  • Reducing process variability
  • Reducing costs
  • Increasing customer satisfaction
  • Increased profits

The word Sigma is a statistical term that measures how far a given process deviates from perfection.

The central idea behind Six Sigma: If you can measure how many "defects" you have in a process, you can systematically figure out how to eliminate them and get as close to "zero defects" as possible and specifically it means a failure rate of 3.4 parts per million or 99.9997% perfect.

Key Concepts of Six Sigma:

At its core, Six Sigma revolves around a few key concepts.

Critical to Quality: Attributes most important to the customer.

Defect: Failing to deliver what the customer wants.

Process Capability: What your process can deliver.

Variation: What the customer sees and feels.

Stable Operations: Ensuring consistent, predictable processes to improve what the customer sees and feels.

Design for Six Sigma: Designing to meet customer needs and process capability.

Our Customers Feel the Variance, Not the Mean. So Six Sigma focuses first on reducing process variation and then on improving the process capability.

Myths about Six Sigma:

There are several myths and misunderstandings surrounding Six Sigma. Some of them are given below:

  • Six Sigma is only concerned with reducing defects.
  • Six Sigma is a process for production or engineering.
  • Six Sigma cannot be applied to engineering activities.
  • Six Sigma uses difficult-to-understand statistics.
  • Six Sigma is just training.

Benefits of Six Sigma

Six Sigma offers six major benefits that attract companies:

  • Generates sustained success
  • Sets a performance goal for everyone
  • Enhances value to customers
  • Accelerates the rate of improvement
  • Promotes learning and cross-pollination
  • Executes strategic change

Origin of Six Sigma:

Six Sigma originated at Motorola in the early 1980s, in response to achieving 10X reduction in product-failure levels in 5 years.

Engineer Bill Smith invented Six Sigma, but died of a heart attack in the Motorola cafeteria in 1993, never knowing the scope of the craze and controversy he had touched off.

Six Sigma is based on various quality management theories (e.g. Deming's 14 point for management, Juran's 10 steps on achieving quality).

By 2000, many of the world’s top corporations had a six sigma initiative underway and by 2003 over $ 100 billion in combined savings had been tallied.

Six sigma performing companies realized staggering business success:

  • General Electric profited between $7 and $10 billion from Six Sigma in about 5 years.
  • Dupont added $1 billion to its bottom line within two years of initiating its six sigma program and that number increased to about $2.4 billion within 4 years.
  • Honeywell achieved record operating margins and savings of more than $2 billion in direct costs.
  • Motorola the place where Six Sigma began saved $2.2 billion in a four year time frame.

The six sigma approach is not for an unprepared organization. It is intense and rigorous and it entails a thorough inspection of the way everything is done. Six Sigma sets ambitious business objectives and measures performance in a way that forces accountability. It doesn’t allow a management team to become complacent, but rather it exposes waste that otherwise would remain largely invisible.

Six sigma takes a business out of its comfort zone –but for a relatively short time. After the first project gains are made and the money starts flowing to the profit margin, a cultural change takes hold. the early discomfort of changing business processes gives way to success , problem become opportunities for improvement and the organization begins to enthusiastically leverage the methods and tools of six sigma-more pervasively and with a keen eye on value.

All businesses, organizations and individuals have room to improve. No operation is run so tightly that another ounce of inefficiency and waste can’t be squeezed out. By their nature, organizations tend to become messy as they grow. Processes, technology, systems and procedures- the ways of doing business-become cluttered with bottlenecks, resulting into work piling up in one part of the organization while other parts sit idle with nothing to do.

Work is often performed incorrectly, or the outcome is flawed in some way. When this happens, one scraps products and services and have to do the work over again. One has to consume additional resources to correct a problem before it is delivered to the customer or the customer asks later for a “redo” a new product or a more satisfactory service.

Sometimes, flaws and defects are not the problem, but a product or service simply takes too long to produce and deliver. Imagine a problem for a mortgage company, if it processed home loans perfectly, but did so 5 times slower than the competition. That would be a disaster. Six sigma was once a quality-improvement methodology, but now it is a general-purpose approach to minimizing mistake and maximizing value.

2.0KEY ELEMENTS

There are three key elements of Six Sigma Process Improvement:

  • Customers
  • Processes
  • Employees

The Customers

Customers define quality. They expect performance, reliability, competitive prices, on-time delivery, service, clear and correct transaction processing and more. This means it is important to provide what the customers need to gain customer delight.

The Processes

Defining processes as well as defining their metrics and measures is the central aspect of Six Sigma.

In a business, the quality should be looked from the customer’s perspective and so we must look at a defined process from the outside-in.

By understanding the transaction lifecycle from the customer's needs and processes, we can discover what they are seeing and feeling. This gives a chance to identify weak areas with in a process and then we can improve them.

The Employees

A company must involve all its employees in the Six Sigma program. Company must provide opportunities and incentives for employees to focus their talents and ability to satisfy customers.

It is important to Six Sigma that all the team members should have a well-defined role with measurable objectives.

2.1 Basic Statistical Concepts

Large elements of the Six Sigma approach are statistical in nature. This text book does not purport to be a statistical text-book and so will not deal in detail with statistical tools and techniques; for a comprehensive treatment refer to “Essentials of Statistics” also available on Bookboon.com.

2.1.1 Probabilistic Thinking

In many organizations there is a tendency to think deterministically. This basically means an expectation that there will be no variation in outcomes, and that a given input (or inputs) will always generate the same output (or outputs). This flies in the face of our general life experience; we know that, for example, that a particular Olympic runner will not always beat other runners over the same distance and in the same conditions. This does not, however, stop organizations for assuming that, for example, inspection systems will always reject products of poor quality and accept products of good quality.

Thinking probabilistically allows for more effective decision making by allowing us to quantify the probability of success or failure, risk and reliability. Deterministic thinking tends to lead to overly simplistic characterization of situations and inappropriate responses when the simplistic model fails to predict reality effectively.

2.1.2 Probability Distributions

When there are a range of possible outcomes for a given process (for example the dimensions of a manufactured product or time taken to complete a task) we can predict the probability of each outcome and thereby develop a probability distribution which models the long-term outcomes of that process. This adds a layer of sophistication to the ability to make decisions with respect to whether processes can meet design intent, or whether to give a contract to a particular supplier.

There are a number of general distribution shapes which describe situations within certain parameters. Key distributions in the context of Six Sigma are Normal, Binomial, and Poisson.

Probability calculations and distributions are handled in detail in “Essentials of Statistics” also available on Bookboon.com.

2.1.3 Descriptive Statistics

When dealing with distributions and attempting to make appropriate decisions we need to summarize what we are dealing with. This requires us to understand three key things:

•Central Tendency: Where is the distribution centered? This can be important in, for example, seeing if thedistribution of a process is centered on the target for that process.

•Spread: How variable is the distribution? In general we want as much consistency as possible for adistribution.

•Shape: For the same central tendency and spread differing shapes of distribution would lead to differentdecisions.

The appropriate measures for central tendency and spread will vary with the particular measure, and the question being asked.

2.1.4. Hypothesis Testing

A key question in process improvement is ‘has something changed?’. We may ask this question in relation to deterioration of an existing process, or to establish whether an attempt to improve a process has been successful. There are a variety of tests associated with different situations and different underlying distributions, and even some which are independent of distribution. The essential question is whether the results under consideration can be explained by the natural variation within the process before the ‘deterioration’ or ‘improvement’.

A specific form of hypothesis testing relates to correlation, where we are attempting to understand whether the variation in one measure is related to the variation in another – usually as a precursor to establishing causation. For example we might be concerned with whether a change in feed rate in a metal cutting process effects a change in the surface finish of the material.

2.2Variation, the Normal Distribution, DPMO and Sigma Levels

2.2.1 Variation and the Normal Distribution

Variation reduction is the key mechanism for Six Sigma to deliver business benefit. By focusing on product, service or process variation (depending on circumstances) projects create consistency of performance and improved conformance to customer requirements.

Six Sigma focuses on the concept of defects per million opportunities (DPMO). It uses the standard normal distribution as its measurement system. From the standard normal distribution, the mean is µ and the standard deviation is denoted by σ. From figure 2.1, 68.2% of the population lies within ±1.0σ of the mean, 95.45% of the population lies within ±2.0σ of the mean and 99.73% of the population lies within ±3.0σ of the mean

Figure 2.1. Standard normal distribution

When addressing variation it is important to remember the effects of special and common cause variation. The normal distribution and DPMO cannot apply if special causes are dominant within the process.

2.2.2 Defects per Million Opportunities

Six Sigma uses the DPMO level of a process to generate a Sigma level for the process. The idea of a Sigma level is that it compares the variation in process performance to the acceptable levels set by the customer, the higher the Sigma level the better; a Six Sigma performance indicates 3.4 DPMO.

Figure 2.2. A one-sided normal distribution

So for example, from figure 2.2, when σ = 3 there are 1350 DPMO ((1-0.998)*1000000).

According to the standard normal distribution a process a six sigma performance would actually produce a DPMO of 0.002, but Sigma levels are calculated using an inbuilt 1.5 σ shift for the process average.

This is effectively an allowance for the natural propensity of processes to drift and, although debate still rages as to the validity of the exact assumption this is the commonly used approach.

The basic idea is to create a process quality metric which allows comparison of any type of process; Goh (2010) described this as one of the six triumphs of Six Sigma. The DPMO are calculated first and then translated into a Sigma value via a conversion table (see table 2.1 below).

Process / DPMO / Process / DPMO / Process / DPMO / Process / DPMO
Sigma / (shift=1.5 σ) / Sigma / (shift=1.5 σ) / Sigma / (shift=1.5 σ) / Sigma / (shift=1.5 σ)
6.0 / 3.4 / 4.5 / 1,350.0 / 3.0 / 66,810.6 / 1.5 / 501,350.0
5.9 / 5.4 / 4.4 / 1,865.9 / 2.9 / 80,762.1 / 1.4 / 541,693.8
5.8 / 8.5 / 4.3 / 2,555.2 / 2.8 / 96,809.1 / 1.3 / 581,814.9
5.7 / 13.4 / 4.2 / 3,467.0 / 2.7 / 115,083.1 / 1.2 / 621,378.4
5.6 / 20.7 / 4.1 / 4,661.2 / 2.6 / 135,686.8 / 1.1 / 660,082.9
5.5 / 31.7 / 4.0 / 6,209.7 / 2.5 / 158,686.9 / 1.0 / 697,672.1
5.4 / 48.1 / 3.9 / 8,197.6 / 2.4 / 184,108.2 / 0.9 / 733,944.5
5.3 / 72.4 / 3.8 / 10,724.1 / 2.3 / 211,927.7 / 0.8 / 768,760.5
5.2 / 107.8 / 3.7 / 13,903.5 / 2.2 / 242,071.4 / 0.7 / 802,048.1
5.1 / 159.1 / 3.6 / 17,864.5 / 2.1 / 274,412.2 / 0.6 / 833,804.3
5.0 / 232.7 / 3.5 / 22,750.3 / 2.0 / 308,770.2 / 0.5 / 864,094.8
4.9 / 337.0 / 3.4 / 28,717.0 / 1.9 / 344,915.3 / 0.4 / 893,050.4
4.8 / 483.5 / 3.3 / 35,931.1 / 1.8 / 382,572.1 / 0.3 / 920,860.5
4.7 / 687.2 / 3.2 / 44,566.7 / 1.7 / 421,427.5 / 0.2 / 947,764.9
4.6 / 967.7 / 3.1 / 54,801.4 / 1.6 / 461,139.8 / 0.1 / 974,042.6

Table 2.1. Process sigma table