Intelux Electronics Private Ltd : Intelux Electronics Private Ltd Presentation- Root Cause Analysis : Presentation- Root Cause Analysis By
Mr. Sandip Tambe
Intelux Electronics Pvt. Ltd Scope : 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 Slide 4: “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 ? : 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)
Action to eliminate a detected non conformity Defect and 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 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 : ISO 9001 Requirement Internal Audit – 8.2.2
Roles of Auditor & Auditee
Correction &Corrective Action
Records of Results of Audit Corrective Action – 8.5.2
Identification of Non conformity
Identification of cause
Elimination of cause
Plan and implementation of corrective action
Review of effectiveness
Maintain record Nonconformity Report : 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 : Examples of NCs & CAs Scenario:
Production- Lens Department W-4
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
Reference to internal
Requirement's), if Necessary
Sign Corrective Action Proposed: : 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 : 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: : 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: : Tools & Techniques: Brain Storming
Graphs & Charts
Flow Charts (process Map)
Cause & Effect Diagram
Scatter Diagram Brain Storming : 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 - : 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 : : 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
Group members simply give ideas as they come to mind
Create more relaxed atmosphere
Thumb rule: 5-15 minutes works well Data Collection : Data Collection “The Skill with which a company collects & uses data can make the difference between success & failure”
-Maasaki Imai Data Collection : 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. How to measure the data ? : Plan for the Data Collection How to measure the data ? Establish
method Ensure Data
Stability Collect Data
Consistency Clarity Purpose
of data collection
data to collect Write & pilot operational definitions
Develop & pilot data
collection forms &
Establish a sampling Test & Validate
measurement systems Train data collectors
Pilot process & make
Monitor data accuracy &
consistency Data collection is the 1st step to Understanding the Variation the
Customer Feels Slide 24: 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. Slide 25: 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 & 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 : 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 : 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. Slide 31: 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. Line Graph - Example : Line Graph - Example Bar Graph - Example : Bar Graph - Example Pie Chart - Example : Pie Chart - Example Monthwise SRV Rej : Monthwise SRV Rej Process Mapping : 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 Process flow diagram that visualizes how work is done. : Step1 Start Step 2A Step 2B Step2C Step3 Rework End Good NO Yes Process flow diagram that visualizes how work is done. Process mapping Steps : 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 - : 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.
Drawing revision process.
- what might the start point be?
- what might the end point be? Process Map - Analysis : Process Map - Analysis Identify :
Value added and non value added steps
Input and output for key process steps
Specific types of wastes in each step Process Mapping :analysis : Process Mapping :analysis Look at each process for
Sources of delay
Errors being fixed instead of being prevented
Look at each decision for
Are the decision needed for this point Process Mapping :analysis : 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? : 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 : 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
The most frequent or most costly events are not always the most important
Two fatal accidents deserve more attention than 100 cut fingers. Steps to Build a Pareto Chart : 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 Scored : Players Scored What is cause : 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. Slide 50: 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 : Fishbone Diagram Arial Font Size 24 Slide 52: 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. Why, Why , Why : People Poor & declining
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 : 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 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 : 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 : Histogram – Skewed Distribution A skewed distribution, with one tail longer than the other. Slide 59: 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.