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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


                         600                                                                                                                                                           100

                         500                                                                                                                                                           80

                         400




                                                                                                                                                                             Percent
                                                                                                                                                                                       60
          Count




                         300
                                                                                                                                                                                       40
                         200
                                                                                                                                                                                       20
                         100                                                .
                                                                      pec                    lan
                                                                                                e
                                                                                                                                      pai
                                                                                                                                         r
                                                                   .S                     atp             d Boa
                                                                                                                 rd
                                                                                                                                   Re        v al
                                                               ec t
                                                                 d                     He
                                                                                      r ed                                     tec         mo
                                               lty        tFitlte
                                                            E
                                                                                  t ge              fotue h
                                                                                                      i tg
                                                                                                                          ni  tmid r y Re                             r
                              0          d Fau         ee
                                                      mp
                                                        .                       non
                                                                               iShild            is
                                                                                               Mhr                    Ecsos fo na               ble
                                                                                                                                                    m
                                                                                                                                                             t ne
                                                                                                                                                                 c to                  0
                                      ge t           Mg
                                                 noton                      Joc
                                                                          T ou              nt t                      Mi                                 horn           tion
                                    ma n
                                   apone           Ci
                                              tMis s                  pt  n t
                                                                         ed o           onenot                    nd ds c autio
                                                                                                                  iee
                                                                                                                   ra                       Pr o          Co         ina
                                 tD          o g
                                             p
                                          Cmtn                     orn
                                                                  fCm
                                                                      ms
                                                                       t             mp gs                  iBeg
                                                                                                                yo
                                                                                                                WL
                                                                                                                     Pr e               kol          rty
                                                                                                                                                  lde l
                                                                                                                                                        S        am           er s
                               mp om      Wr
                                           mp                   eJo i            Co Le                       nk
                                                                                                              n                      hio      So   au        ont
                              C C        C                    D                                            L
                                                                                                           Lo                       T             F        C               Oth
                     Defect
                      Count             141 139         69      52     22     20     20      17     17     17      16     13     10     10      10       8      6      5     29
                     Percent              23     22     11       8       4      3      3       3      3      3      3       2      2      2       2      1      1      1       5
                     Cum %                23     45     56      65     68     71     75      77     80     83      85     87     89     91      92     94     95      95 100



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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                                                                                                                                                      1st level Analysis
                                                                                                                                                                            gives “Design”
                    60                                                                                                  80

                    50




                                                                                                              Percent
                                                                                                                        60
       Count




                    40                                                                                                                                                      as main cause of
                    30                                                                                                  40

                    20                                                                                                                                                      failure
                                                                                                                        20
                    10

                         0
                                 ign          pon
                                                 ent
                                                                                                     er
                                                                                                                        0
                                                                                                                                                          2nd level Analysis gives
                             Des           Com                            d

                                                                                                                                                          breakdown of “Design”
                                                                      Buil                        Oth
               Defect
                Count          57                13                     4                         2
               Percent       75.0              17.1                   5.3                       2.6
               Cum %         75.0              92.1                  97.4                     100.0




                                                                                                          Design Faults


                                                                                                                                                                            100
                                                       50
                                                                                                                                                                            80
                                                       40




                                                                                                                                                                  Percent
                                                                                                                                                                            60
                                       Count




                                                       30
                                                                                                                                                                            40
                                                       20

                                                       10                                                                                                                   20

                                                                                                                             le
                                                           0              dule               rs                           odu                 on                            0
                                                                                                                        rM               r ati
                                                                      t Mo               Moto               rt      uc e             alib
                                                                  nec                que                 Sta r ans d             IC C                         n
                                                               Con               Tor                Cold     T                 AS                   IOP    Imo
                                                Defect
                                                  Count                21               10               8                 8              5           3       2
                                                 Percent             36.8             17.5            14.0              14.0            8.8         5.3     3.5
                                                 Cum %               36.8             54.4            68.4              82.5           91.2        96.5   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
                                                                                                                                         60
       Count




                      100                                                                                                                40


                                                                                                                                         20


                           0                                                              - 10                    7E                     0
                                                                                                              4- 4
                                                                                       116            823 727
                                   788     646     777     780       782     795 564- 8           6- 7 - 564-
                                                                                                66 40
                                 CC      CC      CC      CC        CC      CC 40-           40-                            er s
                               KD      KD      KD      KD        KD      KD                                             Oth
                Defect
                  Count           18      13        11    11         11        10          9         9         8         138
                 Percent         7.6     5.5      4.6     4.6       4.6       4.2       3.8       3.8        3.4        58.0
                 Cum %           7.6    13.0     17.6    22.3      26.9      31.1      34.9      38.7       42.0       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                   Process Steps
          quantitative data and identifying those                                   Pareto

          with the greatest impact.
                                                                      Identify the problem and the potential

           Summary
                                                                          direct or contributing causes




           Pareto Charts provide a visual representation of
           the variables which contribute to problems or             Collect data about each of the potential
                                                                          direct or contributing causes
           issues.

           Pareto Charts can be used as a prioritization tool
           to aid in focusing on the top issues which
                                                                          Construct the Pareto Chart:
                                                                          Causes on Horizontal Axis

           contribute to specific conditions.
                                                                      Frequency of events on Vertical Axis




           Pareto analysis is an approach which ranks the
           contributing factors and identifies which are the          Identify the Vital Few (those with the
                                                                        highest number of occurrences)
           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                    Develop Corrective Action or
           many”, sometimes referred to as the “80-20 rule”           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                    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



             •       Jumping to conclusion
             •       Failure to define problem
             •       Failure to find the root cause
             •       Weak problem solving
             •       No execution of corrective action




                                                                CA/PA BASIC TOOLS Rev 0 09.01.09

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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.

                                                                   Ishikawa Fishbone Template
                        Summary
     The development of the cause and effect
     Fishbone diagram is credited to Kaoru
     Ishikawa, who pioneered quality management
     processes in the Kawasaki shipyards.                  Measurement
                                                           Measurement       Methods
                                                                             Methods         Machinery
                                                                                             Machinery

     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                                                                           UDE
     headings, namely Machinery, Methods,                  Causes, inputs,
                                                           or sources
     Measurement, Manpower, Materials, and                 of variation
     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          Manpower
                                                              Manpower        Materials
                                                                              Materials       Environment
                                                                                              Environment
     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                   A UDE is an UnDesireable Effect
     be problems by questioning the existence of
     causes under each of the six categories.


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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
                         Quality Management System
               Presented by: Sid Calayag




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Crash Course Rca Training Rev 01

  • 1. QUALITY MANAGEMENT ROOT CAUSE ANALYSIS CA / PA BASIC TOOLS Date: Oct 09, 2009 CA/PA BASIC TOOLS Rev 01 10.08.09
  • 2. For most of us, it's a lot easier to jump to solutions, isn't it? 2 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 3. 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 3 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 4. 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 4 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 5. HOME PAGE • INTRODUCTION • MODULE 1 • MODULE 2 • APPLICATION 5 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 6. INTRODUCTION 6 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 7. Introduction Introduction MODULE 1 MODULE 2  Definition of Terms  What it is  Why use it  RCA Process  How to use it 7 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 8. 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 8 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 9. 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 9 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 10. 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 10 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 11. Module 1 Digging for the Root Causes 11 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 12. 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 12 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 13. Histograms- What it is • A chart that graphically display the distribution of a set of data. 13 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 14. 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‟. 14 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 15. Pareto Chart – How to create it 1. Gather facts about the problem 2. Rank the contributions to the problem in order of frequency. 15 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 16. 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. 16 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 17. 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 600 100 500 80 400 Percent 60 Count 300 40 200 20 100 . pec lan e pai r .S atp d Boa rd Re v al ec t d He r ed tec mo lty tFitlte E t ge fotue h i tg ni tmid r y Re r 0 d Fau ee mp . non iShild is Mhr Ecsos fo na ble m t ne c to 0 ge t Mg noton Joc T ou nt t Mi horn tion ma n apone Ci tMis s pt n t ed o onenot nd ds c autio iee ra Pr o Co ina tD o g p Cmtn orn fCm ms t mp gs iBeg yo WL Pr e kol rty lde l S am er s mp om Wr mp eJo i Co Le nk n hio So au ont C C C D L Lo T F C Oth Defect Count 141 139 69 52 22 20 20 17 17 17 16 13 10 10 10 8 6 5 29 Percent 23 22 11 8 4 3 3 3 3 3 3 2 2 2 2 1 1 1 5 Cum % 23 45 56 65 68 71 75 77 80 83 85 87 89 91 92 94 95 95 100 17 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 18. Pareto Analysis Example • Example 2 : a series of Pareto charts drill down to more detail: Fault by Main Cause 100 70 1st level Analysis gives “Design” 60 80 50 Percent 60 Count 40 as main cause of 30 40 20 failure 20 10 0 ign pon ent er 0 2nd level Analysis gives Des Com d breakdown of “Design” Buil Oth Defect Count 57 13 4 2 Percent 75.0 17.1 5.3 2.6 Cum % 75.0 92.1 97.4 100.0 Design Faults 100 50 80 40 Percent 60 Count 30 40 20 10 20 le 0 dule rs odu on 0 rM r ati t Mo Moto rt uc e alib nec que Sta r ans d IC C n Con Tor Cold T AS IOP Imo Defect Count 21 10 8 8 5 3 2 Percent 36.8 17.5 14.0 14.0 8.8 5.3 3.5 Cum % 36.8 54.4 68.4 82.5 91.2 96.5 100.0 18 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 19. 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 60 Count 100 40 20 0 - 10 7E 0 4- 4 116 823 727 788 646 777 780 782 795 564- 8 6- 7 - 564- 66 40 CC CC CC CC CC CC 40- 40- er s KD KD KD KD KD KD Oth Defect Count 18 13 11 11 11 10 9 9 8 138 Percent 7.6 5.5 4.6 4.6 4.6 4.2 3.8 3.8 3.4 58.0 Cum % 7.6 13.0 17.6 22.3 26.9 31.1 34.9 38.7 42.0 100.0 19 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 20. 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. 20 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 21. Pareto Chart and Analysis A method for showing the distribution of Process Steps quantitative data and identifying those Pareto with the greatest impact. Identify the problem and the potential Summary direct or contributing causes Pareto Charts provide a visual representation of the variables which contribute to problems or Collect data about each of the potential direct or contributing causes issues. Pareto Charts can be used as a prioritization tool to aid in focusing on the top issues which Construct the Pareto Chart: Causes on Horizontal Axis contribute to specific conditions. Frequency of events on Vertical Axis Pareto analysis is an approach which ranks the contributing factors and identifies which are the Identify the Vital Few (those with the highest number of occurrences) 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 Develop Corrective Action or many”, sometimes referred to as the “80-20 rule” Improvement Action Plans for those identified as the Vital Few 21 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 22. CAUSE AND EFFECT Ishikawa/Fish Bone Diagram Procedures People Problem Equipment Materials 22 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 23. 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 23 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 24. 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 24 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 25. 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 25 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 26. 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. 26 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 27. Sources of Variation - People People • The activities of the workers. • Variations caused by skill, knowledge, competency and attitude 27 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 28. Sources of Variation - Method Method • The methods used to produce the products. • Variations caused by inappropriate methods or processes. 28 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 29. Sources of Variation - Machine Machine • The equipment used to produce the products. • Variations caused by temperature, tool wear and vibration. 29 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 30. Sources of Variation - Material Material • The "ingredients" of a process. • Variations caused by materials that differ by industry, product and stage of production. 30 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 31. Sources of Variation - Environment Environment • The methods used to control the environment. • Variations caused by temperature changes, humidity etc. 31 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 32. 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. 32 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 33. Cause and Effect Analysis Example 33 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 34. PROBLEM SOLVING FAILURE • Jumping to conclusion • Failure to define problem • Failure to find the root cause • Weak problem solving • No execution of corrective action CA/PA BASIC TOOLS Rev 0 09.01.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 35. 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 35 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 36. Cause and Effect Diagram (Ishikawa) A visual brainstorming tool used to help identify and categorize potential root causes named for Kaoru Ishikawa. Ishikawa Fishbone Template Summary The development of the cause and effect Fishbone diagram is credited to Kaoru Ishikawa, who pioneered quality management processes in the Kawasaki shipyards. Measurement Measurement Methods Methods Machinery Machinery 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 UDE headings, namely Machinery, Methods, Causes, inputs, or sources Measurement, Manpower, Materials, and of variation 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 Manpower Manpower Materials Materials Environment Environment 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 A UDE is an UnDesireable Effect be problems by questioning the existence of causes under each of the six categories. 36 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 37. 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. 37 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE
  • 38. Created by: Sid Calayag – Lead Auditor Quality Management System Presented by: Sid Calayag 38 CA/PA BASIC TOOLS Rev 01 10.08.09 TA I K I S H A P H I L I P P I N E S , I N C OPEN CHALLENGE QUICK RESPONSE

Editor's Notes

  1. The presentation is organized in such a way that we can move from one part (module) of the presentation to another. Also included are two ice breakers during or after the scheduled coffee break. Application form each module is also included although in such a way that it can be part of each or both module, although the advance application will require module 2 to better understand its application.
  2. Root Cause Analysis - structured and thorough review of problem designed to identify and verify what is causing the symptomsa process for understanding and solving a problem. Useful process for understanding and solving a problem. Root Cause AnalysisTracing a Problem to Its OriginsIn medicine, it's easy to understand the difference between treating symptoms and curing a medical condition. Sure, when you're in pain because you've broken your wrist, you WANT to have your symptoms treated – now! However, taking painkillers won't heal your wrist, and true healing is needed before the symptoms can disappear for good.But when you have a problem at work, how do you approach it? Do you jump in and start treating the symptoms? Or do you stop to consider whether there's actually a deeper problem that needs your attention?If you only fix the symptoms – what you see on the surface – the problem will almost certainly happen again. which will lead you to fix it, again, and again, and again. If, instead, you look deeper to figure out why the problem is occurring, you can fix the underlying systems and processes that cause the problem. Root Cause Analysis (RCA) is a popular and often-used technique that helps people answer the question of why the problem occurred in the first place. Root Cause Analysis seeks to identify the origin of a problem. It uses a specific set of steps, with associated tools, to find the primary cause of the problem, so that you can:Determine what happened.Determine why it happened.Figure out what to do to reduce the likelihood that it will happen again. RCA assumes that systems and events are interrelated. An action in one area triggers an action in another, and another, and so on. By tracing back these actions, you can discover where the problem started and how it grew into the symptom you're now facing.You'll usually find three basic types of causes:Physical causes - Tangible, material items failed in some way (for example, a car's brakes stopped working). Human causes - People did something wrong. or did not doing something that was needed. Human causes typically lead to physical causes (for example, no one filled the brake fluid, which led to the brakes failing).Organizational causes - A system, process, or policy that people use to make decisions or do their work is faulty (for example, no one person was responsible for vehicle maintenance, and everyone assumed someone else had filled the brake fluid). Root Cause Analysis looks at all three types of causes. It involves investigating the patterns of negative effects, finding hidden flaws in the system, and discovering specific actions that contributed to the problem. This often means that RCA reveals more than one root cause.You can apply Root Cause Analysis to almost any situation. Determining how far to go in your investigation requires good judgment and common sense. Theoretically, you could continue to trace root causes back to the Stone Age, but the effort would serve no useful purpose. Be careful to understand when you've found a significant cause that can, in fact, be changed.
  3. The Root Cause Analysis ProcessRoot Cause Analysis has five identifiable steps.Step One: Define the ProblemWhat do you see happening? What are the specific symptoms? Step Two: Collect DataWhat proof do you have that the problem exists?How long has the problem existed?What is the impact of the problem? You need to analyze a situation fully before you can move on to look at factors that contributed to the problem. To maximize the effectiveness of your Root Cause Analysis, get together everyone – experts and front line staff – who understands the situation. People who are most familiar with the problem can help lead you to a better understanding of the issues.A helpful tool at this stage is CATWOE. With this process, you look at the same situation from different perspectives: the Customers, the people (Actors) who implement the solutions, the Transformation process that's affected, the World view, the process Owner, and Environmental constraints. Step Three: Identify Possible Causal FactorsWhat sequence of events leads to the problem? What conditions allow the problem to occur?What other problems surround the occurrence of the central problem? During this stage, identify as many causal factors as possible. Too often, people identify one or two factors and then stop, but that's not sufficient. With RCA, you don't want to simply treat the most obvious causes - you want to dig deeper.Use these tools to help identify causal factors:Appreciation - Use the facts and ask "So what?" to determine all the possible consequences of a fact.5 Whys - Ask "Why?" until you get to the root of the problem. Drill Down - Break down a problem into small, detailed parts to better understand the big picture. Cause and Effect Diagrams - Create a chart of all of the possible causal factors, to see where the trouble may have begun. Step Four: Identify the Root Cause(s)Why does the causal factor exist?What is the real reason the problem occurred? Use the same tools you used to identify the causal factors (in Step Three) to look at the roots of each factor. These tools are designed to encourage you to dig deeper at each level of cause and effect. Step Five: Recommend and Implement SolutionsWhat can you do to prevent the problem from happening again?How will the solution be implemented?Who will be responsible for it?What are the risks of implementing the solution? Analyze your cause-and-effect process, and identify the changes needed for various systems. It's also important that you plan ahead to predict the effects of your solution. This way, you can spot potential failures before they happen.One way of doing this is to use Failure Mode and Effects Analysis (FMEA). This tool builds on the idea of risk analysis to identify points where a solution could fail. FMEA is also a great system to implement across your organization; the more systems and processes that use FMEA at the start, the less likely you are to have problems that need Root Cause Analysis in the future.Impact Analysis is another useful tool here. This helps you explore possible positive and negative consequences of a change on different parts of a system or organization.Another great strategy to adopt is Kaizen, or continuous improvement. This is the idea that continual small changes create better systems overall. Kaizen also emphasizes that the people closest to a process should identify places for improvement. Again, with kaizen alive and well in your company, the root causes of problems can be identified and resolved quickly and effectively. Key PointsRoot Cause Analysis is a useful process for understanding and solving a problem. Figure out what negative events are occurring. Then, look at the complex systems around those problems, and identify key points of failure. Finally, determine solutions to address those key points, or root causes. You can use many tools to support your Root Cause Analysis process. Cause and Effect Diagrams and 5 Whys are integral to the process itself, while FMEA and Kaizen help minimize the need for Root Cause Analysis in the future. As an analytical tool, Root Cause Analysis is an essential way to perform a comprehensive, system-wide review of significant problems as well as the events and factors leading to them.Why Do Root Cause Analysis?“Just fix it, there is too much to do.”“We don’t have time to think, we need results now.”Reality - fix symptoms without regard to actual causesRoot Cause Analysis - structured and thorough review of problem designed to identify and verify what is causing the symptoms
  4. Pareto Analysis is used to record and analyse data relating to a problem in such a way as to highlight the most significant areas, inputs or issues. Pareto Analysis often reveals that a small number of failures are responsible for the bulk of quality costs, a phenomenon called the ‘Pareto Principle.’This pattern is also called the ‘80/20 rule’ and shows itself in many ways. For example: 80% of sales are generated by 20% of customers. 80% of Quality costs are caused by 20% of the problems. 20% of stock lines will account for 80% of the value of the stock.A Pareto diagram allows data to be displayed as a bar chart and enables the main contributors to a problem to be highlighted.As a basic Quality Improvement tool, Pareto Analysis can: define categories of defects which cause a particular output (product, service, unit) to be defective; count the frequency of occurrence of each defect; display graphically as a bar chart, sorted in descending order, by frequency of defect; use a second y axis to show the cumulative % of defects .Vilfredo Pareto was an economist who is credited with establishing what is now widely known as the Pareto Principle or 80/20 rule. When he discovered the principle, it established that 80% of the land in Italy was owned by 20% of the population. Later, he discovered that the pareto principle was valid in other parts of his life, such as gardening: 80% of his garden peas were produced by 20% of the peapods.Some Sample 80/20 Rule Applications· 80% of process defects arise from 20% of the process issues.· 20% of your sales force produces 80% of your company revenues.· 80% of delays in schedule arise from 20% of the possible causes of the delays.· 80% of customer complaints arise from 20% of your products or services.(The above examples are rough estimates.)
  5. 1. Gather facts about the problem, using Check Sheets or Brainstorming, depending on the availability of information.2. Rank the contributions to the problem in order of frequency.3. Draw the value (errors, facts, etc) as a bar chart.4. It can also be helpful to add a line showing the cumulative percentage of errors as each category is added. This helps to identify the categories contributing to 80% of the problem. 5. Review the chart – if an 80/20 combination is not obvious, you may need to redefine your classifications and go back to Stage 1 or 2. Examples When possible, use Minitab’s version, as an industry standard, rather than creating one in Excel - refer to Example 1 in this section Use a series of Pareto charts to drill down to more detail - Example 2 Recognise the 80: 20 principle but if the original Pareto is very flat be prepared to cut the defects in a different way, say 40:60 - Example 3 Minitab gives an extra dimension to Pareto Analysis - Example 4
  6. 1. Gather facts about the problem, using Check Sheets or Brainstorming, depending on the availability of information.2. Rank the contributions to the problem in order of frequency.3. Draw the value (errors, facts, etc) as a bar chart.4. It can also be helpful to add a line showing the cumulative percentage of errors as each category is added. This helps to identify the categories contributing to 80% of the problem. 5. Review the chart – if an 80/20 combination is not obvious, you may need to redefine your classifications and go back to Stage 1 or 2. Examples When possible, use Minitab’s version, as an industry standard, rather than creating one in Excel - refer to Example 1 in this section Use a series of Pareto charts to drill down to more detail - Example 2 Recognise the 80: 20 principle but if the original Pareto is very flat be prepared to cut the defects in a different way, say 40:60 - Example 3 Minitab gives an extra dimension to Pareto Analysis - Example 4
  7. Construct the Pareto chart – Example 1Use a series of Pareto charts to drill down to more detail – Example 2 Recognise the 80: 20 principle but if the original Pareto is very flat be prepared to cut the defects in a different way, say 40:60 - Example 3 Create more Pareto by cutting across another variables- Example 4
  8. At first glance, this looks unhelpful. But of 238 data points, most were counts of 1 or 2. A full Pareto would be very flat.Therefore after the first cumulative 42% of defects (100) , the balance of defects (138) are blocked together as “others”.This enables us to see that a “top 9” of defects can be analysed - most are “S-clip” problems (links between ICs and PCB
  9. Examples of Unacceptable Root Cause- Operator Error- It was broken (equipment, gauge, tooling)The process didn’t do what it was supposed to doDidn’t know what to doIt only happened onceFrequent use of “not able to determine/unresolved”
  10. valuable tool for: Focusing on causes not symptoms capturing the collective knowledge and experience of a group Providing a picture of why an effect is happening Establishing a sound basis for further data gathering and action Cause and Effect Analysis can also be used to identify all of the areas that need to be tackled to generate a positive effect.
  11. 1. Identify the Problem/IssueSelect a particular problem, issue or effect. Make sure the problem is specific, tightly defined and relatively small in scope and that everyone participating understands exactly what is being analyzed. Write the problem definition at the top of the flip chart or whiteboard.2. Brainstorm Conduct a Brainstorm of all the possible causes of the effect, i.e., problem.Have a mixed team from different parts of the process (e.g., assemblers and testers).Get a “fresh pair of eyes” - from someone who is not too close to the process.Have a facilitator - an impartial referee.Everyone is an equal contributor (“leave stripes at the door”).Fast and furious - go for quantity rather than quality (of ideas) at first.Involve everyone, or question why he/she is here.Timing - set an upper limit and best time/day of the week.Offer an incentive (free lunch?).Know when to stop.Recognize that this is a snapshot of how the group thinks today.Re-visit the problem again.Refer also to the Process Mapping tool.Consider (how) should you involve your customer?Write each idea on a Post-It® to make it easy to transfer them onto the fishbone diagram later. Be careful not to muddle causes and solutions at this stage. It is important to brainstorm before identifying cause categories otherwise you can constrain the range of ideas. However, if ideas are slow in coming use questions such as, ‘what about?’, to prompt thoughts.3. Draw fishbone diagram Place the effect at the head of the “fish” Include the 6 recommended categories shown below
  12. 4. Align Outputs with Cause CategoriesReview your brainstorm outputs and align with the recommended major cause categories, e.g., the People, Method, Machine, Material, Environment and Measurement System. Note:These may not fit every situation and different major categories might well be appropriate in some instances, however, the total should not exceed six. Other categories may include Communications, Policies, Customer/Supplier Issues etc.5. Allocate CausesTransfer the potential causes from the brainstorm to the diagram, placing each cause under the appropriate category.If causes seem to fit more than one category then it is acceptable to duplicate them. However, if this happens repeatedly it may be a clue that the categories are wrong and you should go back to step 4.Related causes are plotted as ‘twigs’ on the branches. Branches and twigs can be further developed by asking questions such as ‘what?’, ‘why?’ ‘how?’, ‘where?’ This avoids using broad statements that may in themselves be effects. Beware, however, of digging in and getting into bigger issues that are completely beyond the influence of the team.6. Analyze for Root CausesConsider which are the most likely root causes of the effect. This can be done in several ways:Through open discussion among participants, sharing views and experiences. This can be speeded up by using Consensus Decision Making.By looking for repeated causes or number of causes related to a particular category.By data gathering using Check Sheets, Process Maps, or customer surveys to test relative strengths through Pareto Analysis.Once a relatively small number of main causes have been agreed upon, Paired Comparisons, can be used to narrow down further.Some groups find it helpful to consider only those causes they can influence.7. Test for RealityTest the most likely causes by, e.g., data gathering and observation if this has not already been done.The diagram can be posted on a wall and added to / modified as further ideas are generated either by the team or by others who can review the teams' work.Cause and Effect Analysis can be combined with Process Mapping.A fishbone may be developed for each discrete activity within the process that is generating the output / effect so that causes are linked to particular steps in the process
  13. Types of Questions that may be Asked Does the person have adequate supervision and support? Does the person know what he is expected to do in his job? How much experience does the person have? Does the person have the proper motivation to do his best work? Is the person satisfied or dissatisfied with his job?Is the person more- or less-productive at certain times of the day? Do physical conditions such as light or temperature affect their work? Does the person have the tools/equipment needed to do the job? Who does the person contact when problems arise? Is the work load reasonable?
  14. Types of Questions that may be Asked How is the method used defined? Is the method regularly reviewed for adequacy? Is the method used affected by external factors? Have other methods been considered? How does the operator know if the method is operating effectively?Is statistical analysis used to verify the effectiveness of the method? What adjustments must the operator make during the process? Have any changes been made recently in the process?
  15. Types of Questions that may be Asked How old is the equipment or machinery? Is it maintained regularly? Is the machine affected by heat or vibration or other physical factors? How does the operator know if the machine is operating correctly?Is statistical analysis used to verify the capability of the machine? What adjustments must the operator make during the process? Have any changes been made recently in the process?
  16. Types of Questions that may be Asked How is the material produced? How is the material verified? How old is the material? How is quality judged prior to your operation? What is the level of quality?How is the material packaged? Can temperature, light or humidity affect the material quality? Who is the material supplier? Has there been a change in suppliers?
  17. Types of Questions that may be Asked How are conditions monitored? How are conditions controlled? How is the control measuring equipment calibrated? Are there changes in conditions at different times of the day? How does change impact the processes being used? How does change impact the materials being used?
  18. Types of Questions that may be Asked How frequently are products inspected? How is the measuring equipment calibrated? Are all products measured using the same tools or equipment? How are inspection results recorded? Do inspectors follow the same procedures? Do inspectors know how to use the test equipment?
  19. A Cause and Effect diagram (also known as a Fishbone or Ishikawa diagram) graphically illustrates the results of the analysis and is constructed in steps. Cause and Effect Analysis is usually carried out by a group who all have experience and knowledge of the cause to be analyzed. Cause-and-Effect diagrams graphically display potential causes of a problem The layout shows Cause-and-Effect relationships between the potential causesAllow team members to specify where ideas fit into the diagramClarify the meaning of each idea using the group to refine the ideas. For example:Is also Called, “Fishbone" or "Ishikawa" diagram is named after its creator, Kaoru Ishikawa.Is used to systematically list all the different potential causes for a specific problem (or effect). Is often used to help identify the reasons why a process goes wrong.A Cause and Effect diagram graphically illustrates the results of the analysis and is constructed in steps. Cause and Effect Analysis is usually carried out by a group who all have experience and knowledge of the cause to be analyzed. Cause-and-Effect diagrams graphically display potential causes of a problem The layout shows Cause-and-Effect relationships between the potential causesThe Cause and Effect diagram is one of several charts used during Brainstorming to organizing ideas into common themes. This format helps with the process of distinguishing between alternatives, identifying common threads, and keeping the ideas flowing. This method also allows the team to easily divide up the ideas for further work.Organize the topic, team and write down the general categories on the chart. Brainstorm the ideas about the potential causes using good brainstorming practices (no bad ideas, everyone gets a voice). Illustrates how several potential causes may lead to the same effect. Generally takes on the shape of a fishbone.   Potential causes are organized under common headings such as Materials, Machinery, Methods, Environment, Process & Measurement It is common for people working on improvement efforts to jump to conclusions without studying the causes, target one possible cause while ignoring others, and take actions aimed at surface symptomsCause-and-effect diagrams are designed to:Stimulating thinking during a brainstorm of potential causesProviding a structure to understand the relationships between many possible causes of a problemGiving people a framework for planning what data to collectServing as a visual display of causes that have been studiedHelping team members communicate within the team and with the rest of the organization
  20. PROBLEM SOLVING FAILURE- JUMPING TO CONCLUSIONS,NO FACT FINDING- SHOTGUN ROOT CAUSE - FAILURE TO DEFINE THE PROBLEM- FAILURE TO FIND THE ROOT CAUSEWEAK PROBLEM SOLVING SKILL-NO EXECUTION OF CORRECTIVE ACTIONSACTION IS ONLY FOR THE SHOW NO COMMITMENT/OWNERSHIPTIME FACTOR- COST CONSTRAINTS
  21. PROBLEM SOLVING SUCCESSProblem is clearly defined.Problem is acceptedAs an opportunity/challenge to improve- True root cause is found- Implemented an effective and irreversible corrective and preventive action- Problem did not re-occur
  22. PROBLEM SOLVING SUCCESSProblem is clearly defined.Problem is acceptedAs an opportunity/challenge to improve- True root cause is found- Implemented an effective and irreversible corrective and preventive action- Problem did not re-occur