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QUALITY MANAGEMENT

ROOT CAUSE ANALYSIS

CA / PA BASIC TOOLS
Date: Oct 09, 2009
CA/PA BASIC TOOLS Rev 01 10.08.09

For most of us, it's a lot easier to jump to solutions, isn't it?

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Objectives Module 1: Participants will learn how to: • Create and use Pareto chart in the analysis of a problem • Implement steps for carrying out effective RCA • Select and apply tools that support RCA

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Objectives Module 2:

Participants will be able to:
• Define and explain the 8 – D as a Problem Solving Method

• Apply the 8 Disciplines and Concepts

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HOME PAGE

• INTRODUCTION
• MODULE 1 • MODULE 2 • APPLICATION
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INTRODUCTION

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Introduction
Introduction

MODULE 1

MODULE 2

 Definition of Terms
 What it is  Why use it

 RCA Process
 How to use it

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Terms and Definition
Cause (causal factor) - a condition or event that results in an effect Direct Cause - cause that directly resulted in the occurrence Contributing Cause - a cause that contributed to the occurrence, but by itself would not have caused the occurrence Root Cause - cause that, if corrected, would prevent recurrence of a non-conformity and similar occurrences

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RCA Definition Root Cause Analysis - a process designed for use in investigating and categorizing the root causes of

events

A process of tracing a Problem to its Origins

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Root Cause Analysis Process
Step One:
Define the Problem

Step Two: Collect Data Step Three:
Identify Possible Causal Factors

Step Four:
Identify the Root Cause(s)

Step Five:
Recommend and Implement Solutions
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Module 1
Digging for the Root Causes

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Module 1 Table of Contents
MODULE 1 MODULE 2 APPLICATION

 Histograms and Pareto Chart  Cause and Effect Diagram
 What it is  How to use it  Examples

 Summary
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Histograms- What it is

• A chart that graphically display the distribution of a set of data.

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Pareto Chart - What it is
A Pareto chart allows data to be displayed as a bar chart and enables the main contributors to a problem to be highlighted.
It reveals that a small number of NCNs are responsible for the bulk of quality issues, a phenomenon called the „Pareto Principle‟.

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Pareto Chart – How to create it
1. Gather facts about the problem 2. Rank the contributions to the problem in order of frequency.

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Pareto Chart – How to create it
(cont’n)

3. Draw the value as a bar chart. 4. add a line showing the cumulative percentage of errors

5. Review the chart
6. Redefine classifications if necessary.
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Pareto Analysis Example
• Chart 1 : The chart gives summary information and starts the cumulative % count at the top of the first bar:
Pareto of D3 Small Engine Card Faults
100 80

600 500

Percent
ec . Sp
141 139 23 23 22 45 69 11 56 52 8 65 22 4 68 20 3 71 20 3 75 17 3 77 17 3 80 17 3 83 16 3 85 13 2 87 10 2 89 10 2 91 10 2 92 8 1 94 6 1 95 5 1 29 5 95 100

Count

400 300 200 100

60 40 20 0

Defect

e r lan rd pai v al Re c t. atp d Boa mo He Ee d i tg r ed r tec tFitlte fotue h lty tmid r y Re is ni ting 0 . lde m ee c to d Fau r os fo na h n iSo Mg t t ne mp ble ge t Ecs nt Mh Mi tion Joc noton Ci ma en T ou nenot horn ra Pr o nd ds c autio n t n iee Co ina tMis s ed o a S pg pt po s ms W yo t L rty kol am t D po ro Cmtn omeg fCm nk orn lde l er s L Pr e iBeg au n hio mp om mp eJo i ont W C L F T C C C D C Lo So Oth

Count Percent Cum %

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Pareto Analysis Example
• Example 2 : a series of Pareto charts drill down to more detail:
Fault by Main Cause
100 70 60 80

Percent

50

Count

60 40 20

40 30 20 10 0
ent pon Com

1st level Analysis gives “Design” as main cause of failure 2nd level Analysis gives breakdown of “Design”

0
d Buil er Oth

Defect
Count Percent Cum %

ign Des

57 75.0 75.0

13 17.1 92.1

4 5.3 97.4

2 2.6 100.0

Design Faults
100 50 80 40

Percent
dule t Mo nec Con
21 36.8 36.8

Count

60 40 20

30 20 10 0
rs Moto que Tor
10 17.5 54.4

Defect
Count Percent Cum %

le odu on rM r ati uc e alib rt Sta r ans d IC C T AS Cold
8 14.0 68.4 8 14.0 82.5 5 8.8 91.2

0
IOP
3 5.3 96.5

n Imo
2 3.5 100.0

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Pareto Analysis Example
• Example 3 : if the original Pareto is very flat, be prepared to cut the defects in a different way, here, it is 40:60
Pareto Chart for Child11
100 200 80

Percent
788 646 777 780 CC CC CC CC KD KD KD KD 7E - 10 4- 4 116 823 727 6- 7 - 56482 95 564- 8 7 7 66 40 CC CC 4040KD KD er s Oth

Count

60 40 20

100

0

0

Defect
Count Percent Cum %

18 7.6 7.6

13 5.5 13.0

11 4.6 17.6

11 4.6 22.3

11 4.6 26.9

10 4.2 31.1

9 3.8 34.9

9 3.8 38.7

8 3.4 42.0

138 58.0 100.0

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Pareto Analysis Example
How it helps
Pareto Analysis is a useful tool to:

•
• •

identify and prioritize major problem areas based on frequency of occurrence;
separate the „vital few‟ from the „useful many‟ things to do; identify major causes and effects.

The technique is often used in conjunction with Brainstorming and Cause and Effect Analysis.
HINT ! The most frequent is not always the most important! Be aware of the impact of other causes on Customers or goals.
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Pareto Chart and Analysis
A method for showing the distribution of quantitative data and identifying those with the greatest impact.

Process Steps
Pareto
Identify the problem and the potential direct or contributing causes

Summary
Pareto Charts provide a visual representation of the variables which contribute to problems or issues.

Collect data about each of the potential direct or contributing causes

Pareto Charts can be used as a prioritization tool to aid in focusing on the top issues which contribute to specific conditions.
Pareto analysis is an approach which ranks the contributing factors and identifies which are the ones which have the most impact on a problem or issue. Often referred to as an approach for “separating the vital few from the trivial many”, sometimes referred to as the “80-20 rule”
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Construct the Pareto Chart: Causes on Horizontal Axis Frequency of events on Vertical Axis

Identify the Vital Few (those with the highest number of occurrences)

Develop Corrective Action or Improvement Action Plans for those identified as the Vital Few

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CAUSE AND EFFECT

Ishikawa/Fish Bone Diagram
Procedures People

Problem

Equipment
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Materials
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Cause and Effect • Cause and Effect Analysis is a tool for identifying all the possible causes associated with a particular problem Valuable for:
• Focusing on causes not symptoms • Providing a picture of why an effect is happening • Establishing a sound basis for further data gathering and action • Identifying all of the areas that need to be tackled to generate a positive effect
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Cause and Effect Sources of Variation Sources of Variation is categorized as follows
1. People 2. Method 3. Machine 4. Material 5. Environment 6. Measuring System

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How to do it
• 1. Identify the Problem/Issue • 2. Brainstorm 3. Draw fishbone diagram
Place the effect at the head of the “fish” Include the 6 recommended categories shown below
People Method Machine

Problem or Issue

Material

Environment

Measurement System

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How to do it (cont’n) • 4. Align Outputs with Cause Categories

• 5. Allocate Causes
• 6. Analyze for Root Causes • 7. Test for Reality

Tip ! The 6 categories recommended will address almost all scenarios. However, there is no one perfect set of categories. You may need to adapt to suit the issue being analyzed.

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Sources of Variation - People

People • • The activities of the workers. Variations caused by skill, knowledge, competency and attitude

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Sources of Variation - Method

Method • The methods used to produce the products. • Variations caused by inappropriate methods or processes.

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Sources of Variation - Machine

Machine

•
•

The equipment used to produce the products.
Variations caused by temperature, tool wear and vibration.

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Sources of Variation - Material

Material • The "ingredients" of a process. • Variations caused by materials that differ by industry, product and stage of production.

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Sources of Variation - Environment

Environment

• The methods used to control the environment.
• Variations caused by temperature changes, humidity etc.

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Sources of Variation – Measurement System

Measurement System

• The methods and instruments used to evaluate products.
• Variations caused by measuring techniques, or calibration and maintenance of the instruments.

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Cause and Effect Analysis Example

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PROBLEM SOLVING FAILURE

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• •

Jumping to conclusion
Failure to define problem Failure to find the root cause

•
•

Weak problem solving
No execution of corrective action

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PROBLEM SOLVING SUCCESS Problem is clearly defined. Problem is accepted As an opportunity/challenge to improve True root cause is found Implemented an effective and irreversible corrective and preventive action - Problem did not re-occur -

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Cause and Effect Diagram (Ishikawa)

A visual brainstorming tool used to help identify and categorize potential root causes named for Kaoru Ishikawa.

Summary
The development of the cause and effect Fishbone diagram is credited to Kaoru Ishikawa, who pioneered quality management processes in the Kawasaki shipyards. The cause and effect diagram is used to explore potential causes (or inputs) that result in a single undesirable effect (UDE, or output). Causes are categorized under six headings, namely Machinery, Methods, Measurement, Manpower, Materials, and Environment. Potential causes can be arranged according to their level of importance or detail, resulting in a depiction of relationships and hierarchy of events. It is the hierarchy that creates a map that looks somewhat like fish bones, hence the name. The Ishikawa Fishbone Diagram is intended help you brainstorm and search for potential root causes or identify areas where there may be problems by questioning the existence of causes under each of the six categories.

Ishikawa Fishbone Template

Measurement Measurement

Methods Methods

Machinery Machinery

Causes, inputs, or sources of variation

UDE
Materials Materials Environment Environment

Manpower Manpower

A UDE is an UnDesireable Effect

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Action Reflection
Wait! I think I missed $$$ something
It isn’t that they cannot see the solution, It’s that they can’t see the problem.
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Created by:
Sid Calayag – Lead Auditor for Taikisha Phils., Inc Quality Management System

Presented by: Sid Calayag

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DOCUMENT INFO
Description: This is a short orientation for root cause analysis that I presented to TPI staff inorder for them to learn the tools used in quality management