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Root Cause AnalysisMethodology & Tools

By Gustavo Diaz, ASQ CSSBB

Root Cause Analysis Teams & Problem Definition

Team Development & Classification Problem Definition

RCA DMAIC

Define

Statement of Opportunity, Problem definition, Brainstorming, Affinity diagrams

Measure

Check sheets, Pareto analysis, Scatter diagrams, Run charts, Tree diagrams, Flow charts, Process mapping

Analyze

Evaluation matrices, FMEA, Pugh Matrix, DOE, Force Field Analysis (Barrier Analysis)

Implement

Gantt Charts, Action Plans (definition of components), Contingency Plans, Monitoring

Sustain

SPC charts, Check sheets, Contingency plans, RACI.

2016 2Copyright 2015-2016. All rights reserved.

Root Cause Analysis - Environment

2016 3

Team

Forming

Storming

NormingPerforming

Adjourning

RCA Methodology

Define

Statement of Opportunity

Problem

Statement

Charter

Measure

Check sheetsPareto Analysi

sScatter Diagra

ms

Tree Diagra

msFlow

chartsProcess maps

Analyze

FMEAPugh

Matrix

Force Field

Analysis

DOE

Execute

Gantt chartsAction Plans

Contingency Plans

Monitoring

Communicati

on

Sustain

SPC RACI

Problem

Effects

Failure Modes

Causes

• Potential Causes

Critical Causes

Copyright 2015-2016. All rights reserved.

Root Cause Analysis – Problem Solving Tools

Steps Tools Notes

Problem Definition

Brainstorming

Buzz Groups

Nominal Groups

Delphi Methods

Focus Groups

Root Cause Analysis: Likelihood of

occurrence vs. severity of Incident.

Problem Statement

Affinity diagrams

Fault trees

Critical to Quality (CTQs)

Kano Model

SWOT analysis

Creation of a Problem charter.

Definition of a “decision criteria” for

alternative solutions selection.

Measure

Check sheets

Pareto analysis

Scatter diagram

Run charts

Tree decomposition diagrams

Flow charts

Process mapping

These techniques will include their

definitions, as well as hands-on on the

techniques, using cases or Client

specifics.

Analyze

Ishikawa diagram

5 Whys

Evaluation matrices

FMEA

Pugh Matrix

DOE

Force Field Analysis (Barrier Analysis)



techniques, using cases or Client specifics.

Execute

Gantt Charts

Action Plans (definition of

components)

Contingency Plans

Monitoring



techniques, using cases or Client specifics.

Sustain Solution

SPC charts

Check sheets

RACI


Root Cause Analysis - Introduction

2016 5

Root-Cause Analysis(RCA)

Problem Definition

Statement of opportunityProblem statementBrainstormingBuzz groupsCTQsAffinity diagrams

Measure

Check sheetsPareto chartsXY diagramsRun charts

Analyze

Ishikawa diagram5 Whys

Delphi methodsNominal groupsTree decompositionFlow chartsProcess mapsFMEAPugh matrix

Execute

Force field analysisGantt chartsAction plans

Sustain

Check sheetsSPCContingency plansRACI



What is a (business) Problem?

A perceived gap between the existing state and a desired state;

or a deviation from a norm, standard, or status quo.

Although many problems turn out to have several solutions

(means to close the gap or correct the deviation), difficulties

arise where such ways are either not obvious or are not

immediately available.

What is Problem-Solving?

Problem solving consists of using generic or ad hoc methods, in an

orderly manner, for finding “best” solutions to problems.

Problem-solving is a mental process that involves discovering,

gathering, and analyzing facts (data) to solve problems.

The ultimate goal of problem-solving is to overcome obstacles and

find a solution that “best” resolves the issue.



Problem Solving Methodologies

There are several problem solving methodologies

1. Problem-Definition Process (Sep-2012, Harvard Business Review)

2. Plan-Do-Check-Act (PDCA Cycle, or Deming Cycle)

3. Soft Systems Methodology (SSM)

4. (Global) 8D Problem Solving Process (Ford Motor Co., 1982)

5. The Cynefin Framework (Davis Snowden, 1999)

6. Appreciative Inquiry (Case Western Reserve, 1980)

7. The Simplex Process (Min Basadur, 1995)

8. The Straw-man Concept

9. Hurson’s Productive Thinking Model (2007)

10.Action Learning Sets (Reginald Revans, 1983)

11.The FOCUS Model (TQM, Healthcare)



Proposed Methodology

1. Based upon the strong believe that customer comes first,

and process are geared to satisfy 100% (6σ) client

expectations and requirements.

2. Based upon Six Sigma DMAIC

Define a Problem

Measure the Problem

Analyze the Problem

Improve / Implement the Solution(s)

Sustain the Solution(s)

3. Based upon a strong team commitment and

culture

4. Strong top-down managerial support


Root Cause Analysis - Environment

2016 9

Team

Forming

Storming

NormingPerforming

Adjourning

RCA Methodology

Define

Problem

Statement

Charter

Measure

Check sheetsPareto AnalysisScatter Diagra

ms

Tree Diagra

msFlow

chartsProcess maps

Analyze

FMEAPugh

Matrix

Force Field

AnalysisDOE

Execute

Gantt chartsAction Plans

Contingency Plans

Monitoring

Communicatio

n

Sustain

SPC RACI

Problem

Effects

Failure Modes

Causes

• Potential Causes

Critical Causes


Root Cause Analysis – The Team

What is a Team?

A group of people with a full set of complementary skills required

to complete a task, job, project, or solve a problem.

Team characteristics

1. operate with a high degree of interdependence,

2. share authority and responsibility for self-management

(empowered teams),

3. are accountable for the collective performance, and

4. work toward a common goal and shared rewards(s).

A team becomes more than just a collection of people when a

strong sense of mutual commitment creates synergy, thus

generating performance greater than the sum of the performance

of its individual members.

The mutual commitment and sense of shared goals

happens throughout a series of stages…



Team Formation Stages

The Forming Storming Norming Performing theory from Dr.

B. Tuckman (1965, 1975), is a proven, helpful explanation of

team development and behavior.

Developmental progression:

FormingStormingNormingPerformingAdjourning


Stage Team BehaviorLeader

Trait

FormingHigh dependence on leader for guidance and direction.

Individual R & R are unclear.

Processes are often ignored. Members test tolerance of system and leader.

Leader

directs

Storming

Team members attempt to establish themselves in relation to other team members and

the leader.

Clarity of purpose increases, but plenty of uncertainties persist.

Cliques and factions form and there may be power struggles.

Leaders

coaches

Norming

Agreement and consensus largely forms among the team.

Roles and responsibilities are clear and accepted. Big decisions are made by group

agreement.

Commitment and unity is strong. General respect for the leader and some of leadership

is more shared by the team.

Leader

facilitates

and enables

Performing

The team has a shared vision and is able to stand on its own feet with no interference

or participation from the leader.

Team has a high degree of autonomy. Able to work towards achieving the goal, and also

to attend to relationship, style and process issues along the way.

Team members look after each other.

Team members might ask for assistance from the leader with personal and

interpersonal development.

Leader

delegates and

oversees

Adjourning

Tuckman's fifth stage is the break-up of the group, hopefully when the task is

completed successfully.

From an organizational perspective, recognition of, and sensitivity to people's

vulnerabilities is helpful, particularly if members of the group have been closely

bonded and feel a sense of insecurity or threat from this change.

Feelings of insecurity would be natural for people with high 'steadiness' attributes and

with strong routine and empathy style.

Leader

consoles and

advises

2016 12



Root Cause Analysis – Problem Definition

2016 13


Problem Definition


Measure


Analyze



Execute


Sustain




What is it?

Root Cause Analysis (RCA) is a problem solving method used for

identifying the root causes of faults or problems.

A critical factor is considered a root cause if removing it from the

problem-fault-sequence, prevents the final undesirable event from

occurring or recurring.

A causal factor is one that affects an event's outcome, but is not a

root cause.

Though removing a causal factor can benefit an outcome, but it

does not prevent its recurrence within certainty.

RCA is applied to identify and correct the

root causes of events.

Focusing corrective actions on root causes

has the goal of entirely preventing

problem recurrence.



Where do we start?

Statement of Opportunity – general description of the

symptoms or the “pain” in the process, or the “pain” caused

by the problem.

Usually starts with the sentence “ There is an opportunity

to…” , written in noun-verb structure, with an active verb

(like eliminate, reduce, minimize, decrease, etc.)

It should include the benefits to the customer, and the risk

taken by the organization by not solving such “pain”.

Supported with some numbers and more detail once data

have been obtained. See Problem Statement next…



Statement of Opportunity – Poor Examples

Poor Statement of Opportunity 1A: Inventory levels are too

high and must be reduced.

Poor Statement of Opportunity 1B: Having too few forklifts

is making inventory levels too high.

Poor Statement of Opportunity 1C: Human resources is

taking too long to fill personnel requests.

Poor Statement of Opportunity 1D: Our admission office

has a problem with the number of insurance claim forms

submitted with errors to the insurance company.



Statement of Opportunity – Better Examples

Good Statement of Opportunity 2A: Inventory levels at the West Metro inventory storage process in Scottsdale are consuming space, taking up asset management time, and creating cash flow issues. These high levels are causing obsolescence affecting customer expiration dates, and causing returns.

Good Statement of Opportunity 2B: Recruiting time for software engineers for the flight systems design department in San Jose is taking long time. This delay is adding costs in overtime, contractor labor, and rework costs; and jeopardizing “go live” deadlines.

Good Statement of Opportunity 2C: Insurance claim forms originating at the Fremont North Memorial emergency department are causing a loss of revenue, excessive rework costs, and delayed payment to the hospital, impacting the cycle time to pay vendors and customers.



Problem Statement – Next step

The problem statement serves several purposes in a root cause analysis. First, it clarifies the current situation by specifically identifying the problem, its severity, location, frequency, financial and customer impact (pain).

It also serves as a great communication tool, helping to get buy-in and support from others. When problem statements are well written, people readily grasp and understand what we are trying to accomplish.

A problem statement should be concise and include the following:

1. A brief description of the problem and the metric used to describe the

problem

2. Where the problem is occurring by process name and location

3. The time frame over which the problem has been occurring

4. The size or magnitude of the problem

5. Customer impact.



Problem Statements – Good Examples

Problem Statement 3A: Inventory levels at the West Metro inventory storage process in Scottsdale are consuming space, taking up asset management time, and creating cash flow issues. Inventory levels are averaging 31.2 days, with a high of 45 days. These levels have exceeded the target of 25 days 95 percent of the time since January 2012. $250,000 could be saved per year if inventories were at the targeted level.

Problem Statement 3B: Insurance claim forms originating at the Fremont North Memorial emergency department are causing a loss of revenue, excessive rework costs, and delayed payment to the hospital. Forty-five percent of the claim forms have errors, with an average of 2.3 defects per form.This problem has existed since claims processing was moved to Kansas City in March 2012. Billings could increase by $3.5 million per month, rework cost could be reduced by 50 percent, and an additional 1.3 percent of revenue could be recovered if errors were occurring less than 5 percent of the time. Achieving this level of performance would increase profits by $395,000 per year.



Techniques to aid with the Problem definition…

Affinity diagrams

Brainstorming

Buzz Groups

Focus Groups

Nominal Groups

Mind Mapping



Tools: Brainstorming

Brainstorming is a problem definition / solving approach designed to help a team clearly define a problem, or generate several creative solutions to a problem.

It was first developed by Alex Osborn, an advertising executive who felt the need for a problem solving technique that, instead of evaluating and criticizing ideas, would focus on developing imaginative and innovative solutions.

Brainstorming combines a relaxed, informal approach to problem solving with lateral thinking. It encourages people to come up with thoughts and ideas that can, at first, seem a bit crazy. Some of these ideas can be crafted into original, creative solutions to a problem, while others can spark even more ideas. This helps to get people unstuck by "jolting" them out of their normal ways of thinking.



Tools: Brainstorming Characteristics

Procedure designed to release a team's creativity in order to generate multiple imaginative solutions to a problem definition or solution.

Separates the idea-generation from the idea-evaluation process by not allowing any criticism to take place while the team is generating ideas.

May be more productive for each member to brainstorm quietly and then share ideas with the team (brain writing technique).

Electronic brainstorming puts each member at a computer terminal and their ideas are projected to a screen so no one knows from whom an idea came.



Tools: Affinity Diagrams

The affinity diagram organizes a large number of ideas into their natural, higher-level, relationships and associations. This method taps a team’s creativity and intuition.

It was created in the 1960s by Japanese anthropologist Jiro Kawakita.

Also called: Affinity chart, K–J method, thematic analysis.

When to Use it?

When you are confronted with many facts or ideas in apparent chaos

or disarray

When issues seem too large and complex to grasp

When group consensus is necessary

After a brainstorming exercise

When analyzing verbal data, such as survey results.

2016Copyright 2014-2015. All rights reserved. 24


Tools: Affinity Diagram Procedure

Record each idea on a separate sticky note or card.The entire team gathers around the notes and participates in the next steps.

It is very important that no one talk during this step. Look for ideas that seem to be related in some way. Place them side by side. Repeat until all notes are grouped.

It is okay to have “loners” that do not seem to fit a group. It’s all right to move a note someone else has already moved.

You can talk now. Team can discuss the shape of the chart, any surprising patterns, and especially reasons for moving controversial notes. When ideas are grouped, select a heading for each group. Place it at the top of the group.

Combine groups into “super-groups” if appropriate.



Tools: Critical to… CTQs

CTQ trees (critical-to-quality trees) are the key measurable

characteristics of a product or process whose performance

standards or specification limits must be met in order to satisfy

the customer requirements.

CTQs are used to decompose broad customer requirements

impacted by a problem, into more easily quantified elements.

CTQ trees are often used as part of RCA methodology to help

prioritize such requirements affected by a problem or a defect.

CTQs represent the product or service characteristics as defined

by the customer/user. They may include upper and lower

specification limits or any other factors.

A CTQ must be an actionable, quantitative business specification.



Tools: Critical to… CTQs


Root Cause Analysis - Measure



Problem Definition


Measure


Analyze



Execute


Sustain


Root Cause Analysis – Measure

Tools: Pareto Analysis

Pareto Analysis is a quantitative technique in decision-making used for the selection of a limited number of tasks that produce significant overall effect. It uses the Pareto Principle (also known as the 80/20 rule) the idea that by doing 20% of the work you can generate 80% of the benefit of doing the entire job.

Pareto Analysis is a simple technique for prioritizing possible changes by identifying the problems that will be resolved by making these changes. By using this approach, you can prioritize the individual changes that will most improve the situation.

How to use the tool?

Step 1: Identify and List the Problem

Step 2: Identify the potential Root Causes of the Problem

Step 2: Score the Causes

Step 5: Add up the Scores for each group of Causes

Step 6: Sort and prioritize

Step 7: Take Action



Tools: Pareto Analysis Example



Tools: Scatter Diagrams (XY graphs)

An XY or scatter plot either shows the relationships among the

numeric values in several data series or plots two groups of

numbers as a single series of XY coordinates. It can show

uneven intervals or clusters of data and is commonly used for

business data.

The scatter plot is a type of mathematical diagram using

Cartesian coordinates to display values for two variables for a

set of data.

A scatter plot can suggest various kinds of correlations

between variables with a certain confidence interval.

Correlations may be positive (rising), negative (falling), or

null (uncorrelated).



Tools: Scatter Diagrams (XY graphs)



Tools: Process Maps

Process Mapping, often referred to as Flowcharting, is a graphic representation showing all the inputs, steps, actions, controls and decisions points of a business process.

“As is”:

Teams often start their process improvement efforts by identifying the “actual” path of a process under study that produces a particular product or service.

“To Be”:

Teams may follow that up with developing the “ideal” path in order to compare it back to the actual in order to identify deviations and then improve them.

Process Maps are great for:

Showing what the current process looks like.

Identifying deviations from the norm.

Showing relationships between steps or departments involved.

Identifying where to collect data and investigate further for

improvement opportunities.

Use as a training aid (shows how the work should be done).

Serving as process documentation and standardization (SOP).



Tools: Process Maps Graphical Tools


Stability

Do I have input variation thatis causing output variation?

• Is the process stable?• What are my inputs?• How do they vary?• What is the predictive equation

Capability

Am I delivering outputs that meet customer expectations?

• How good is the measurement system?• What are the specs?• Are the specs changing?• How are we performing?

Control

Do I know what to do andwhen to do it?

• What is the procedure?• When do I use it?• How do I make decisions?• Are my decisions correct?

Process Outputs

Material

Labor

Information

Tools

Inputs Process Outputs

(Stability)

(Stability)(Capability)

(Control)

(Attributes)


Tools: Process Maps Level -2


Root Cause Analysis - Analyze



Problem Definition


Measure


Analyze

Ishikawa diagram

5 Whys


Execute


Sustain


Root Cause Analysis –Analyze

Tools: Ishikawa Diagram (fish-bone diagram)

Ishikawa diagrams (aka fishbone diagrams, cause-and-effect diagrams) are causal diagrams created by Kaoru Ishikawa (1968) to show the potential causes of a specific event.

Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect.

Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify these sources of variation.

These major categories typically include:

People: Anyone involved with the process.

Methods: How the process is performed and the specific requirements for doing it, such as policies, procedures, rules, regulations and laws.

Machines: Any equipment, computers, tools, etc. required to do the job.

Materials: Raw materials, parts, paper, etc. used to produce the final product.

Measurements: Data generated from the process, used to evaluate its quality.

Environment: The conditions, such as location, time, temperature, and culture in which the process operates.


Root Cause Analysis –Analyze



Root Cause Analysis – Analyze




Tools: 5-Whys?

By asking "Why?" five times, and in succession, one can delve into

a problem deeply enough to understand the ultimate root cause.

By the time you get to the 4th or 5th why, you will likely be

looking some measurable practice or the lack thereof.

This methodology is closely used with the Cause & Effect

(Ishikawa) diagram.

Many times teams will stop once a reason for a problem or a

defect has been identified. This reason may not be the root cause.

The purpose of 5-whys analysis is to get the right people in the

room discussing all of the potential root causes of a given problem

or defect in a process.



Tools: Failure Mode & Effects Analysis

Failure Modes and Effects Analysis (FMEA) is a step-by-step approach for identifying all possible failures in a design, a manufacturing or assembly process, or a product or service.

“Failure modes” mean the ways, or modes, in which something might fail. Failures are any errors or defects, especially ones that affect the customer, and can be potential or actual.

Failures are prioritized according to how serious their consequences are, how frequently they occur and how easily they can be detected. The purpose of the FMEA is to take actions to eliminate or reduce failures, starting with the highest-priority ones.

“Effects analysis” refers to studying the consequences of those failures.

The FMEA also documents current knowledge and actions about the risks of failures, for use in continuous improvement. FMEA may be used during design to prevent failures. Later on, it is used for control, before and during ongoing operation of the process.

The FMEA is used in RCA to locate in a process where the problem causes occur. It may be used during the earliest stages of root causing.




The steps to complete an FMEA are listed below


Step Description

1 Review the process map. List the steps and decisions in

the FMEA template.

2 Brainstorm potential failure modes for each step in the

process, listed in the FMEA.

3 List all potential effects of the failure (from the

customer perspective.

4 Assign Severity rankings

5 Assign Occurrence rankings

6 Assign Detection rankings

7 Calculate the RPN for each line

8 Develop Action Plans

9 Take action, i.e. RACI


Tools: Failure Mode & Effects Analysis Example

A bank performed a process FMEA on their ATM system. The figure shows part of it—the

function “dispense cash” and a few of the failure modes for that function. According to

the RPN, “machine jams” and “heavy computer network traffic” are the first and second

highest risks.




Calculation Risk Priority Number (RPN)

The Risk Priority Number, or RPN, is a numeric assessment of

risk assigned to a process, or steps in a process.

The team assigns each failure mode numeric values that

quantify likelihood of occurrence, likelihood of detection, and

severity of impact.

RPN utilizes three rating scales:

1. Severity (S) - rates the severity of the potential effect of

the failure.

2. Occurrence (O) - rates the likelihood that the failure will

occur.

3. Detection (D)- rates the likelihood that the problem will be

detected before it reaches the end-user/customer.




Risk Priority Number (RPN) Guidelines



Tools: Design of Experiments

Design of experiments (DOE) is a statistical systematic method to determine the relationship between factors affecting a process and the output of that process.

It is used to find cause-and-effect relationships. This information is needed to manage process inputs in order to optimize the output.

A strategically planned and executed experiment may provide a great deal of information about the effect on a response variable due to one or more factors that may interact.

Many experiments involve holding certain factors constant and altering the levels of another variable. This One–Factor–at–a–Time (or OFAT) approach to process knowledge is, however, inefficient when compared with changing factor levels simultaneously to determine interactions.



Tools: Design of Experiments

The most commonly used terms in the DOE methodology include:

controllable and uncontrollable input factors, responses, hypothesis

testing, blocking, replication and interaction.

Hypothesis testing helps determine the significant factors using statistical

methods. There are two possibilities in a hypothesis statement: the null and

the alternative. The null hypothesis is valid if the status quo is true. The

alternative hypothesis is true if the status quo is not valid. Testing is done at

a level of significance, which is based on a probability.

Blocking and replication: Blocking is an experimental technique to avoid any

unwanted variations in the input or experimental process. Practitioners

also replicate experiments, performing the same combination run more than

once, in order to get an estimate for the amount of random error that could

be part of the process.

Interaction: When an experiment has three or more variables,

an interaction is a situation in which the simultaneous influence of two

variables on a third is not additive.


Root Cause Analysis - Execute



Problem Definition


Measure


Analyze



Execute


Sustain


Root Cause Analysis – Execute

Tools: Gantt Charts

A Gantt chart is a horizontal bar chart developed as a production

control tool in 1917 by Henry L. Gantt, an American engineer

and social scientist.

A Gantt chart provides a graphical illustration of a schedule that

helps to plan, coordinate, and track specific tasks in a project.

Gantt charts illustrate the start and finish dates of the terminal

elements and summary elements of a project. Terminal

elements and summary elements comprise the work breakdown

structure of the project.

Modern Gantt charts also show the dependency (i.e.,

precedence network) relationships between activities.



Tools: Gantt Charts



Tools: Action Plans (component definition)

Action planning is a process which will help you to focus your ideas and to decide what steps you need to take to implement the solution(s) to a particular problem that you may have. It is a statement of what you want to achieve over a given period of time.

An action plan is a way to make sure the problem at hand is solved, and organization's strategy is made concrete. It describes the way your team will leverage the corrective actions to solve the problem.

Each action step or change to be sought should include the following information:

1. What actions or changes will occur?

2. Who will carry out these changes?

3. By when they will take place, and for how long?

4. What resources (i.e., money, staff) are needed to carry out these changes?

5. Communication (who should know what?)



Tools: Action Plans (component definition)

3C’s Criteria to measure a good action plan:

Complete? Does it list all the action steps or changes to be

sought in all relevant parts involved in the corrective actions

(e.g., operators, business, managers)?

Clear? Is it apparent who will do what by when?

Current? Does the action plan reflect the current work? Does it

anticipate newly emerging opportunities and barriers?


Root Cause Analysis - Sustain



Problem Definition


Measure


Analyze



Execute


Sustain


Root Cause Analysis – Sustain

Tools: SPC Charts

Control charts are used to monitor quality and process stability in manufacturing and service processes.

Control charts are graphs used to study how a process changes over time. Data are plotted in time order.

A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data.

Depending on the number of process characteristics to be monitored, there are two basic types of control charts.

The first, referred to as a univariate control chart, is a graphical display (chart) of one process characteristic.

The second, referred to as a multivariate control chart, is a graphical display of a statistic that summarizes or represents more than one quality characteristic.



What SPC Charts to use?


Process With Continuous Data

Charts every data observation XmR (I&MR)

Charts a small group of data (between 2-10 observations in one instance/batch/job run)

X-bar & R

Charts a larger group of data (more than 11 observations in one instance/batch/job run)

X-bar & s

Process With Discrete Data (Attributes)

Counts the number of defects, equal sample size c-Chart

Counts the number of defects, variable sample size u-Chart

Charts the proportion of defectives, variable sample size p-Chart

Charts the number of defective units, equal sample size np-Chart


SPC Charts – I&MR Charts

An I & MR, or Individual & Moving Range Chart, is a graphical tool

that displays process variation over time for individual measures

(observations) of the process.

It signals when a process may be going out of control and

shows where to look for sources of variation.

I & MRs are used:

To observe every data point in the process.

Because our data is continuous and our subgroup size is

one.

The Individual (I) Chart plots each measurement (sometimes

called an observation) as a separate data point. Each data point

stands on its own and there is no rational subgrouping and the

subgroup size of 1.



SPC Charts – I&MR Charts


Part # Diameter (mm)

1 5.77

2 4.57

3 5.79

4 6.21

5 5.32

6 4.24

7 4.65

8 5.20

9 5.10

10 6.07

11 5.82

12 4.78

13 5.33

14 5.67

15 4.79

16 4.29

17 6.01

18 5.23

19 5.78

20 4.56

21 4.98

22 5.27

23 5.80

24 5.21

25 5.67

26 4.88

27 5.10

28 5.92

29 5.11

30 4.93

UCL 7.08

CL 5.27

LCL 3.45

2.80

3.80

4.80

5.80

6.80

7.80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Dia

mete

r (m

m)

Date/Time/Period

X Diameter (mm)

UCL 2.23

CL 0.68

0.00

0.50

1.00

1.50

2.00

2.50

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Ran

ge

Date/Time/Period

R Diameter (mm)


SPC Charts – Xbar&R Charts

After processes have been running for a while, and we have

additional collectable data points, we can produce an X-bar & R

to assess process control more accurately.

The X-bar & R groups individual data points into subgroups

(between 2 – 10 data points in one sub-group).

X-bar & R charts are used when you can rationally collect

measurements in groups (or subgroups) of between 2 and 10

observations. Each subgroup represents a "snapshot" of the

process at a given point in time.

If we use an I & MR for so many data points, it may produce a

false alarm at this point.



SPC Charts – Xbar&R Charts


Days 7a-3p 3p-7p 7p-11p 11p-7a

1 -1.50 0.00 0.00 0.00

2 -0.50 -0.50 -0.50 0.00

3 0.00 0.00 0.00 0.00

4 0.00 0.00 0.00 0.00

5 0.00 -1.00 0.00 0.00

6 -0.50 -0.50 0.00 0.00

7 0.00 0.50 0.00 0.00

8 0.00 0.00 0.00 0.00

9 0.50 0.00 0.00 0.00

10 0.00 0.00 0.00 0.00

11 0.00 0.50 0.00 0.00

12 -1.50 0.00 0.00 0.00

13 -3.00 0.00 -1.00 0.00

14 -2.00 -0.50 -1.00 0.00

15 -2.50 -0.50 -0.50 1.00

16 -1.50 0.00 0.00 1.00

17 0.00 -0.50 0.00 1.00

18 0.00 0.00 -0.50 0.00

19 0.00 0.00 -0.50 0.00

20 0.00 -1.00 -1.50 0.00

21 0.00 -0.50 -0.50 0.00

22 -1.00 -0.50 -0.50 -0.50

23 -1.00 -0.50 0.00 0.00

24 0.00 0.00 -0.50 0.00

25 -1.00 -2.00 -1.00 -1.00

26 -0.50 -0.50 -0.50 0.00

27 0.00 0.00 0.00 0.00

28 0.00 0.00 -0.50 0.00

29 -1.00 -0.50 -0.50 0.00

30 0.00 0.00 -0.50 0.50

UCL 0.41

CL -0.28

LCL -0.96

-1.50

-1.00

-0.50

0.00

0.50

1.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Av

era

ge

Date/Time/Period

X 7a-3p - 11p-7a

UCL 2.13

CL 0.93

0.00

1.00

2.00

3.00

4.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Ran

ge

Date/Time/Period

R 7a-3p - 11p-7a


SPC Charts – Xbar&Sigma Charts

An X-bar & s(igma) chart is a special purpose variation of the X-

bar and R chart.

Sigma represents the standard deviation of the individual samples.

The major difference is that the subgroup standard deviation is

plotted when using the Xbar & s chart, while the subgroup range is

plotted when using the Xbar & R chart.

Used with processes that have a subgroup size of eleven (11) or

more, the X-bar & s charts show if the system is stable and

predictable.

Because standard deviation uses each individual reading to

calculate variability, it provides a more effective measure of the

process spread as it happens throughout the time data is

sampled.



SPC Charts – Xbar&Sigma Charts

X-bar & Sigma charts are used when you can rationally collect

measurements in groups (subgroups). Each subgroup represents a

"snapshot" of the process at a given point in time.

The charts X-axis are time-based, meaning the charts show a history

of the process and one must enter in the sequence from which it was

generated.

For subgroup sizes greater than ten (10) observations, always use

X-bar & Sigma charts, as the Range statistic (R = max – min) is a

poor estimator of process sigma for large subgroups.

The subgroup sigma is always a better estimate of subgroup variation

than subgroup range (R). The popularity of the Range chart is only

due to its ease of calculation.



SPC Charts – Attribute Charts

Attribute charts are the simplest of statistical process control charts to build and interpret.

Attribute charts track measure data that either does, or does not possess a specific characteristic or attribute.

Some examples of attribute data would include:

% of orders that had all required information before submission to fulfillment.

% of invoices paid within 90 days.

% of customer service emails receiving a reply within specified limit (e.g. 4 hours).

% of customers that rated their satisfaction with services received on the 'favorable' side of neutral.

% of new employees that leave within the first year of employment.



SPC Charts – Attribute Charts

The most common attribute charts are


Chart Records Subgroup Size

p Fraction defective Varies

np Number of defectives Constant

c Number of defects Constant

u Number of defects per unit Varies

100p Percent defectives Varies


SPC Attribute: p Charts

A p-chart is an attribute control chart used with data collected in

subgroups of varying sizes. Because the subgroup size can vary, it

shows a proportion on nonconforming items rather than the actual

count.

The purpose of a p chart is to evaluate process stability when

counting the fraction defective.

The p chart is used when the sample size varies:

Example: The total number of circuit boards, meals, or bills

delivered varies from one sampling period to the next.

Measures % of nonconforming items

Example: Count # defective chairs & divide by total chairs

inspected.

Chair is either defective or not defective.



SPC Attribute: p Charts


Sample

Number

Nonconforming

Units

Sample

Size

S1 12 100

S2 8 80

S3 6 80

S4 9 100

S5 13 110

S6 12 110

S7 11 100

S8 16 100

S9 10 90

S10 6 90

S11 20 110

S12 15 120

S13 9 120

S14 8 120

S15 6 110

S16 8 80

S17 10 80

S18 7 80

S19 5 90

S20 8 100

S21 5 100

S22 8 100

S23 10 100

S24 6 90

S25 9 90

CL0.097

UCL0.190

LCL 0.0030.00

0.05

0.10

0.15

0.20

0.25

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

No

nco

nfo

rmin

gU

nit

s -

Sam

ple

Siz

e

Date/Time/Period

Non-conformingUnits


Tools: Communication – RACI(S)

A RACI matrix or linear responsibility chart (LRC), describes the participation by various roles in completing tasks or deliverables for a project or corrective action.

Not all roles have a responsibility towards implementing a task, and a given task may not be associated to all roles. Typically a task is associated with at least one role or in some cases multiple roles. This ‘Association’ of the role with a task can be divided into the following four association types:

Responsible

Accountable

Consulted

Informed

There is another association type that is sometimes used in addition to the above four types:

Supports

When using all the five types in the matrix, it is called a RASCI (pronounced ‘race ski’) Matrix.



Tools: Communication – RACI Example


Root Cause Analysis


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