Intelux Electronics Private Ltd

Presentation- Root Cause Analysis

By

Mr. Sandip Tambe

Quality Assurance

Intelux Electronics Pvt. Ltd

Scope

• To Understand ISO 9001 requirements on cause non conformities, cause identification, correction & corrective action.

• To Apply these requirements in generating non conformities, planning & implementing corrective actions.

• To Review non conformities, correction,causes & corrective action reporting for correctness.

• Improve effectiveness of QMS by effective implementation of corrective actions

“Every Problem is an opportunity”

“Every defect is treasure ,if the company can uncover its cause and work to prevent it across the corporation”

- Kilchiro Toyoda, founder of Toyota

.

• ISO 900 Requirements Vis-à-vis

Root Cause Analysis

What is a Nonconformance ?

ISO 9000:2000, 3.6.2“Non – Fulfillment of a Requirement”

• Objective evidence exists showing that:

• Type of NC - • A requirement not been addressed (intent)• Practice differs from the defined system(implementation)• The practice is not effective (effectiveness)

• Correction: Action to eliminate a detected non conformity

Defect and Non conformity

• Defect –

Non fulfillment of requirement related to an intended or specified use

Product quality characteristics

• Non conformity :

Non fulfillment of requirement

Business or production process

Corrective x Preventive action

• Corrective Action –• Action to eliminate

cause of detected non conformity or other undesirable situation

• Preventive Action –• Action to eliminate the

cause of a potential non conformity

ISO 9001 Requirement

• Internal Audit – 8.2.2• Documented Procedure

• Audit Planning

• Roles of Auditor & Auditee

• Correction &Corrective Action

• Records of Results of Audit

• Corrective Action – 8.5.2• Documented Procedure• Identification of Non conformity• Identification of cause• Elimination of cause• Plan and implementation of

corrective action• Review of effectiveness• Maintain record

Nonconformity Report

No set rules; however all have these two parts:

• The requirement ( What was supposed to do ) • The evidence ( What actually is )• • Different organizations have different formats

• Use the format chosen by your client or firm.

• Non conformance must be, Factual, Precise, Objective, Traceable, Concise

Examples of NCs & CAs

• Scenario:• Production- Lens Department W-4• Morning Shift.• 4 out of 18 operators seen not wearing nylon caps. Caps

were available at the entrance area.• WI4-01, Clause 6, requires that all personnel entering W-

4 must wear nylon caps. Instruction clearly displayed at the entrance.

.

• Area • Problem• Attribution• Grading• Reference to internal • Requirement's), if

Necessary• Sign

IRCA Quality Audit Incident No…………... NONCONFORMITY REPORT

Company Under Audit XYZ plc. Note Number………

Area Under Review. ISO9001 Class No………...

Production- Lens.Div.W-4…………………..6.4.

Category: Major/Minor

Deficiency: During the morning shift 4 out of 18 operators were not wearing nylon caps.W14-01, cl, 6, requires that all staff entering W-4 must wear nylon caps.The Slandered requires that the organization must determine & manage the work environment needed to achieve product conformity.

Auditor :Yogita

Corrective Action Proposed:

• The 4 concerned operators will be given a verbal warning to follow system.

• Will the proposed action prevent recurrence of the non conformity?

• New operator - training

Quality Tools for Root Cause Analysis

What is Root cause Analysis?

• A process designed for use in investigating & categorizing the root cause of events with safety, health, environmental, quality, reliability & production impacts.

• Simply stated RCA is a tool designed to help identify not only what & how an event occurred, but also why it happened.

• Should we apply in depth root cause analysis for each identified non conformity or problem ?

Major steps in RCA:• Step1 – Problem identification

• Steip2 – Data collection

• Step3 – Causal factor charting

• Step4 –Root Cause Identification

• Step5 – Corrective action Recommendations & Implementation

Tools & Techniques:

• Brain Storming• Data Collection• Graphs & Charts• Flow Charts (process Map)• Pareto Analysis• Histogram• Cause & Effect Diagram• Scatter Diagram

Brain Storming

• Brain Storming is used to establish common method for a team to creatively & Efficiently generate high volume of ideas on any topic

• Brainstorming encourages of all the team members without the dominance of anyone team member

• Allows team members to build on each others creativity while staying focus on the joint mission

.

• Definition – Brain Storming is a team approach to generate creative in a short time brain storming plays an important role to build a cause & Effect diagram.

• Why Brain Storming? • To identify the problem

• To identify critical causes• To find the Solution

• To Prevent the problem

Types of Brainstorming -

• Free Wheeling: Spontaneous flow of ideas by all team members

• Round Robin: Team members take turns suggesting ideas

• Card Method: Team members write ideas on cards with no discussion

Brain storming :

Structured• Every person in a group must give an idea as their turn• Forces even shy people to participate.• Create a certain amount of press

Unstructured• Group members simply give ideas as they come to mind • Create more relaxed atmosphere• Risks domination.• Thumb rule: 5-15 minutes works well

Data Collection

• “The Skill with which a company collects & uses data can make the difference between success & failure”

-Maasaki Imai

Data Collection

• Step1 : What is data?

• Data is information about a topic

• It is derived from objects, situations or phenomenon in the form of measurements.

• It is used to classify, describe, improve or control objects, situations or phenomenon.

Plan for the Data Collection

How to measure the data ?

Establish Data

Collection Goals

Develop operational Definitions

& procedures/ measurement

method

Ensure Data consistency &

Stability

Collect Data & Monitor

Consistency

•Clarity Purpose of data collection

•Identify what data to collect

•Write & pilot operational definitions

•Develop & pilot data collection forms & Procedures

•Establish a sampling

• Test & Validate measurement systems

•Train data collectors

•Pilot process & make Adjustments

•Collect data

•Monitor data accuracy & consistency

•Data collection is the 1st step to Understanding the Variation the Customer Feels

Types of Data:• Data type is an important considerations because it can

impact not only hoe you define your measures but also how you collect data & what you can learn from it.

• Discrete Data (Attribute data)

• Discrete data is information that can be categorized into a classification. It is based on counts.

• Finite no. Of values which can not be subdivided meaningfully.

• Binary (Yes/No, Defect/No Defect)

• Ordered categories( 1-5)• E.g. No. of incomplete

applications– No. of Green Belts

Trained

Continuous Data (Variable Data)

• Continuous data is information that can be measured on a continuous & Scale.

• Can have almost any number value which can be measuring subdivided into finer & finer increments

• Can be broken down into increments

• Infinite no. of possible values E.g.Cycle time (measured in days, hour, minutes, etc.)

Weight (measured in tons,pounds,etc.)

Pros & Cons – Discrete Data

Pros:• Factors can be defined only as

discrete data,

e.g. –Location (State, City, Street), Customer type new or repeat, business VS home)

• Intangible factors can often be converted into measurable discreet characteristics, E.g. Effectiveness of ad (good, bad, not sure)

• It is faster & easier to capture discrete data

• Cons:• Requires to make more

observations to get valid information. Need to count more items to get accurate data. some statisticians note that continuous data can be accurate with a sample of just 200 items no matter how high the volume of the process. So discrete data can be more expensive

• Discrete data can bury important information

• You can do many more potentially useful Analysis with continuous data versus discrete

Key Concepts- Defects Based Measurement

• Unit- an items being processed, or the final product or service being delivered to the customer- a car, a hotel statement etc. Defect- a failure tom meet a customer requirement or performance standard – a leaky cranky case, a lost reservation

• Defective- any unit that contains one or more defects. Hence a car with any defects is just defective as a car with 15 defects

• Opportunity – a chance to go right or wrong- Most product or services have multiple customer requirements, there can be several chances or opportunities to have a defect

.Graph

Purpose:

• Graphs & Charts are pictorial representation of the data, making it easy to spot trends, ratios & comparisons among different groups of data.

.

• The more common types of graphs & charts are line graphs ,Bar charts & pie charts.

• To present the numerical Data in an easy to plot visual form.

Graph

• To present the numerical Data in an easy to plot visual form.

• Line graphs used to depict change or variation over time

• Bar charts are used for comparing quantities between persons, regions, time intervals etc.

• Pie Charts are used to show % or proportions of different components of a specific items.

• Select the type of chart or graph most suitable for the type of data.

• Decide the units & scale of items to be shown on X-axis & Y-axis.

• Fill the information on the graph sheet.• Join the required points to complete line or bars.• Colour or shade the lines or bars to distinguish between

different groups or classes.• Provide appropriate title.

Response Time

96

1

9297

96 94

100

9595

100 95

0

20

40

60

80

100

Week 43 Week 44 Week 45 Week 46 Week 47

% C

om

plit

ion

Line Graph - Example

Bar Graph - Example

INWARD VOLUME - Oct. 2009

020406080

100120

Week 42 Week 43 Week 44 Week 45 WeeK 46 Week 47

Type

JSRV/SRV VOLUME

Week 42 Week 43 Week 44 Week 45 WeeK 46 Week 47

SRV 48 75 46 76 82 63

JSRV 86 60 79 75 112 68

Total 134 135 125 151 194 131

Pie Chart - Example

26%

13%

41%

3%0%17%

WP

WI

JUMP

DRY

MISSING

OTHER

Monthwise SRV RejMonth No. of Items

Month Inspected Rejected

Jan-09 414 7

Feb-09 39 17

Mar-09 572 23

Apr-09 387 27

May-09 562 32

Jun-09 499 26

Jul-09 822 31

Aug-09 438 31

Monthwise SRV Rej

0

200

400

600

800

1000

Jan-09

Feb-09

Mar-09

Apr-09

May-09

Jun-09

Jul-09 Aug-09

Month

Inspected

Rejected

Process Mapping

• Process mapping is technique used for marking work visible

• Process map shows who is doing what ,with whom ,when and for how long

• It also shows decision that are made , sequence of events and time delays, if any in the process

Step1Start

Step 2A Step 2B Step2C

Step3

ReworkEndGood

NO Yes

Process flow diagram that visualizes how work is done.

Symbol Meaning

Start or End of Process

Activity or Process

Decision or Inspection point

Connector

Direction of flow

Process mapping Steps

• 1.Fix process start & end points• 2.Brainstorms list of process steps.• 3.Do first walk-through & interview• 4.List key process steps on sticky notes• 5.Discuss, review & modify• 6.Do second walk-through & interview• 7.Add inspection, rework, repair and scrap steps

on sticky notes• 8.Agree on “as is” process map.

Processes Mapping -

• Start And End Point -• Review problem statement• Describe the process causing the problem• Discuss measurable start & end points• Agree & record• Problem statement :• Customer waits to long for modified drawings.• Process:• Drawing revision process.• Ask:• - what might the start point be?• Ask:• - what might the end point be?

Process Map - Analysis

Identify : Process deliverablesProcess outputValue added and non value added stepsIntermediate measuresInput and output for key process stepsSpecific types of wastes in each step

Process Mapping :analysis

A. Look at each process for

Bottle necks Sources of delay Errors being fixed instead of being prevented Role ambiguity Duplications Unnecessary steps Cycle time

B. Look at each decision for Authority ambiguity Are the decision needed for this point

Process Mapping :analysis

C. Look at each Rework loop for

Possibly doing it in less time Possibility of eliminating step Trying to prevent

D. Using Customer Point of View Identify value added vs non value added steps

What Is A Pareto Diagram?

• A diagram that shows 20% of the input(Xs) Of the problems with dependent process outputs(Ys)

KEEP IN MIND-

Pareto analysis is powerful tool when we use objective data & facts & not opinions.

Pareto Analysis

• Vilfredo pareto was an Italian engineer in the 19th century who studied the number of people in various income classes & declared…

• - 20% of the people own 80% of the country’s wealth.• - 80% of the people own 20% of the country’s wealth.• - Get the biggest problem first • - Solve the vital Few• Remember…• The most frequent or most costly events are not always the most

important• e.g.• Two fatal accidents deserve more attention than 100 cut fingers.

Steps to Build a Pareto Chart

• 1. Arrange data in the descending order

• 2. Collect Data• 3. Calculate the cumulative in the next

column• 4. Calculate cumulative % in the next

column• 5. Draw a graph with scales on both

axis• 6. Draw bar chart based on data• 7.Using cumulative data, draw

cumulative curve• 8.Identify the VITAL FEW

• Exercise -

Players Runs

Laxman 281

Dravid 180

Ganguli 48

SS Das 39

S Ramesh 30

Zaheer Khan 23

Sachin 10

Mongia 4

Players ScoredPlayers Runs Cum %

Laxman 281 281 45

Dravid 180 461 73

Ganguli 48 509 81

SS Das 39 548 87

S Ramesh 30 578 92

Zaheer Khan 23 601 96

Sachin 10 611 98

Harbhajan 8 619 99

Mongia 4 623 100

0

20

40

60

80

100

120

Laxm

an

Dravid

Gangu

li

SS Das

S Ram

esh

Zaheer

Kha

n

Sachin

Harbha

jan

Mon

gia

% r

un

%

What is cause

• CAUSE = Reason or Factor contributing to the EFFECT CAUSE is happens.

• In 1953,Kaoru Ishikawa, Professor of the University of Tokyo, used the cause & effect diagram for the first time.

• A cause & effect diagram is also called a fish bone diagram since it looks like the skeleton of a fish.

• If there are no clues to indicate the cause, Write a cause & effect diagram.

• List down the possible & probable causes by brain storming.• Group them under 5M & E category• Then by observation eliminate causes which do not

contribute to the problem.

Cause Effect

Material Machine Environment

Measurement Man Method

Fishbone Diagram

• Arial Font Size 24

• Cause & Effect Diagramming is brainstorming!• It is very important to ask “WHY” over &over again. Good

cause & Effect Diagramming is question & answer.• Teams create cause & effect diagrams to get at the

difficult to discover causes.

People

Poor & declining participation I improvement

programs

People resist change

1.1They fear making mistakes

(1.1.1)They are criticized for mistakes

(1.1.2) They are penalized for mistakes

(1.1.3)To err is human to forgive is not company policy

1.2 They fear job loss

Why, Why , Why

Histogram

• It is graphic summary of variation in set of data

• Enables us to see patterns that are difficult to see in simple table of numbers

Histogram – Normal Distribution

Histogram – Normal Distribution

A skewed distribution, with one tail longer than the other.

A truncated curve, with the peak at or near the

edge while trailing gently off to the other side, often means that part of the distribution has been removed through screening, 100% inspection, or review. These efforts are usually costly and make good candidates for improvement

efforts.

Histogram – double peaked

A double-peaked curve often means that the data actually reflects two distinct processes with different centers. You will need to distinguish between the two processes to get a clear view of what is really happening in either individual process.

Histogram – Skewed Distribution

A skewed distribution, with one tail longer than the other.

A truncated curve, with the peak at or near the edge while trailing gently off to the other side, often means that part of the distribution has been removed through screening, 100% inspection, or review. These efforts are usually costly and make good candidates for improvement efforts.

Amplifier gain data

8.1 10 8.8 9.7 7.8 9.9 12 8.01 9.3 9

8.2 8.9 10.1 9.4 9.2 7.9 9.5 10.9 7.8 8.3

9.1 8.4 9.6 11.1 7.9 8.5 8.7 7.8 10.5 8.5

11.5 8 7.9 8.3 8.7 10 9.4 9 9.2 10.7

9.3 9.7 8.7 8.2 8.9 8.6 9.5 9.4 8.8 8.3

8.4 9.1 10.1 7.8 8.1 8.8 8 9.2 8.4 7.8

7.9 8.5 9.2 8.7 10.2 7.9 9.8 8.3 9 9.6

9.9 11 8.6 9.4 8.8 8.2 11 9.7 9.1 8

8.7 9.8 8.5 8.9 9.1 8.1 8.1 9.5 8.7 9.3

8.1 10 9.6 8.3 8 9.8 9 8.9 8.1 9.7

8.5 8.2 9 10.2 9.5 8.3 8.9 9.1 10.3 8.4

8.6 9.2 8.5 9.6 9 11 8.6 10 8.8 8.6

Range = High -low

Range =11.7-7.8=3.9db

Result of Amplifier Gain testing

05

1015202530

7.75

- 8.

25

8.25

- 8.

75

8.75

- 9.

25

9.25

- 9.

75

9.75

- 10

.25

10.2

5 - 10.

75

10.7

5 -11.2

5

11.2

5 - 11.

75

11.7

5 - 12.

25

Gain in dB

Nu

mb

er