Six sigma, spc , lean

SixSigma|SPC Techniques |Lean
Metrology & Quality Assurance
Mechanical Engineering
D e p a r t m e n t

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Table of Contents
Six Sigma
History of Six Sigma
6 Sigma Key Concept
Example
Six Sigma Methodologies
Levels of Six Sigma
Other Statistical Analysis Tools
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Six Sigma
The term “Six Sigma” refers to the
notion that if you have six standard
deviations between the mean and the
nearest specification limit, practically
nothing will exceed the limits.
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History of Six Sigma
• Initially developed at Motorola by Bill Smith in 1986
• Used old concepts and combined them
• Way of measuring defects and improving quality
• New methodology for reducing defects below
• 3.4 DPMO (defects per million opportunities
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History of Six Sigma
 Motorola claims over $17 billion in savings that can be attributed
to Six Sigma as of 2006
 Many companies since Motorola have also adapted Six
Sigma
 General Electric
 Bank of America
 Caterpillar
 Honeywell
 3M
 Amazon.com
 Boeing
 Whirlpool
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Six Sigma Key Concepts
• Critical to Quality
Attributes most important to the customer
• Defect
Failing to deliver what the customer wants
• Process Capability
What your process can deliver
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Six Sigma Key Concepts
• Variation
What the customer sees and feels
• Stable Operations
Ensuring consistent, predictable processes to improve
what the customer sees and feels
• Design for Six Sigma
Designing to meet customer needs and process capability
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About the Term Six Sigma
• Standard Deviation
Degree of dispersion from mean value
Where,
 s = standard deviation
 X = data point
 M = average of all data points
 n = population
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Six Sigma= Near Perfection!
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Examples of Six Sigma
GE’s 6σ implementation
• Began in 1995 across entire organization
• Saved $320 million in first 2 years, $1 billion by 1999.
 It is not a secret society, a slogan or a cliché. Six Sigma is a highly
disciplined process that helps us focus on developing and delivering
near-perfect products and services.
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Example of Six Sigma
 Geico: 97% customer satisfaction
 4σ
 USPS: 95% 1st class mail delivered on time
 3σ
 Six Sigma can be applied to any industry,
service, or approval rating
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Six Sigma Methodologies
 Two key methodologies
DMAIC
 Used for improving existing processes
DMADV
 Used for creating new product/process designs
 Used for already optimized processes (with
DMAIC or another method) that still fall short of
expectations
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DMAIC
 DMAIC stands for:
 D Define
 M Measure
 A Analyze
 I Improve
 C Control
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DMAIC : Define
 Define process improvement goals
 Why the 6σ program is in place?
 Define customers needs
 Need vs. requirements to fulfill need
 Create high level process map
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DMAIC : Measure
• Measure current process and collect relevant data
• Develop data collection plan
• Collect data from many sources to
determine types of defects
• Compare to customer surveys
• Determine shortfalls
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DMAIC : Measure
• Determine unit, defect, opportunity
 Unit = Value of process, input, or output
 Defect = Something wrong with a unit
• Too large
• Too small
• Not equal to
 Opportunity = Way to fix the defect
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DMAIC : Measure
• Find the baseline σ
• Defects / Million opportunities = Number
of Defects x 1,000,000
• Number of Units x Number of Opportunities
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DMAIC :Analyze
• Analyze data collected
 Identify gaps between current performance and
goal performance
• Determine root causes of defects
 Sources of variation
• Look for opportunities for improvements
 Prioritize them
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DMAIC :Analyse
• Example: Grocery Store
 Horizontal bar graph showing percentages of defect occurrences
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DMAIC :Analyse
 Process analysis
 Subprocess Mapping
 Start with High Level Process Map from Define phase
 Reduce or eliminate inefficient steps
 Analyze map for non-value added steps
 Categorize non-value added steps
 Root cause analysis
 Determine cause of defects
 Open Brainstorm all explanations of current sigma process
 Narrow Consolidate similar ideas and vote on most likely causes
 Close
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DMAIC : Improve
 Create innovative solutions to fix and prevent problems using
technology and discipline
 Create a solution for each verified root cause
 Select solutions
 Implement solutions either individually or in groups
 Recalculate sigma for each implementation
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DMADV
 DMADV stands for:
 D Define
 M Measure
 A Analyze
 D Design
 V Verify
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DMADV- Design
 Design details
 Optimize design
 Run simulations if necessary
 Prepare for design verification
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DMADV- Verify
 Verify design
 Set up pilot runs
 Implement process
 Train process owners
 Hand over to process owners
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Levels of Six Sigma
Yellow Belt
 Trained in Six Sigma techniques as part of a
corporate-wide initiative
 Have not completed a Six Sigma project
 Not expected to use Six Sigma actively for
quality improvement projects.
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Levels of Six Sigma
Green Belt
 Focuses on 1-2 projects, part time
 Have other job responsibilities
 Direction comes from Black Belt
 Skilled at project management
 Responsible for project progress
 Lead planning teams
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Levels of Six Sigma
Black Belt
 Focuses on 1-3 projects
 Full time
 Has specific projects
 Focus on project execution
 Direction comes from Master Black Belt
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Levels of Six Sigma
Expert
 Used primarily in Aerospace and Defense
Business Sectors
 Work across company boundaries
• Work at many different sites
• Improve services, processes, and products
 Not all companies have this level
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Levels of Six Sigma
• Master Black Belt
 Identified by Champions
 Act as an in-house expert coach for Six Sigma
 Supports many improvement teams, not limited to a certain
number of projects
 Recruits and trains other Black Belts and Green Belts
 Deploy Six Sigma across various functions and departments
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Levels of Six Sigma
• Champion
 Usually senior manager
 Driving force behind organization’s 6σ implementation
 Mentor to other Black Belts
 At some companies, may be known as “Quality Leader”
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Levels of Six Sigma
• Executive Leadership
 CEO and other top management
 Set up vision for Six Sigma
 Choose Champions
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Criticism on Six Sigma
 Article in Fortune that claims "of 58 large companies that have
announced Six Sigma programs, 91 percent have trailed the S&P
500 since.“ and that Six Sigma is effective at what it is intended to
do, but that it is "narrowly designed to fix an existing process" and
does not help in "coming up with new products or disruptive
technologies."
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Criticism on Six Sigma
• Hard to get things done with 6σ
• 6 is an arbitrary number
 Not necessary for some companies, good for others, not acceptable for some
• i.e. medical supplies versus direct mail advertising campaign
• Home Depot attempted to use Six Sigma but led to frustration for
employees and customers – employees required to help 22.8 customers
per hour instead of 13.4
 Basis for choosing 6 for the number of standard deviations is never clearly
explained
 Along with the 1.5σ shift
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StatisticalProcessControl
(SPC)
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Table of Contents
 Definition
 Importance of SPC
 Quality measurement in manufacturing
 Statistical control charts
• Introduction
• Types of variation
• Control charts
 Process capability
• Basic Definition.
• Use of process capability information.
• Standardized formula.
• Relationship to product specification.
• The capability index.
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Definition
 Statistical process control as the application of statistical
method to the measurement and analysis of variation in a
process.
 This techniques applies to both in-process parameter and
end-of-process parameters.
 A process is a collection of activities that converts inputs into
outputs or result.
 More specifically a process is a unique combination of
machine, tools, methods, materials and people that attain an
output in goods, software or services.
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Importance of SPC
•Reduces waste
•Reduction in the time which is required to produce the product.
•Detecting error at inspection.
• Reduces inspection cost.
•Saves cost of material by reducing number of rejects.
• More uniform quality of production.
•Customer satisfaction.
• It provides direction for long term reduction in process variability.
• It is stable process and operates with less variability.
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Quality Measurement in Manufacturing
 Quality measurement is central to the process of quality control:
“what gets measured, gets done.”
 Measurement is basic for all three operational quality process and
for strategic management
• Quality control measurement – provides feedback and early warnings of
problems.
• Operational quality planning measurement – quantifies customer needs
and product and process
capabilities.
• Quality improvement measurements – can motivate people, prioritize
improvement opportunities, and help in diagnosing causes.
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Statistical Control Charts
• A statistical control chart compares process performance data to
computed ‘statistical control limits’ drawn
• as limit lines on the chart.
• Prime objective of control chart is – detecting special causes of
variation in a process by analysing data from both the past and the
future
• Process variations have two kinds of causes
1. Common (random or chance)
2. Special (assignable)
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Types of Variation
• Two kinds of variation occur in all manufacturing processes
1. Common Cause Variation or Random Cause Variation
• consists of the variation inherent in the process as it is designed.
• may include variations in temperature, properties of raw materials, strength of an electrical current
etc.
• Common cause is the only type of variation that exist in the process and process is said to be ‘in
control’ and stable
2. Special Cause Variation or Assignable-cause Variation
 With sufficient investigation, a specific cause, such as abnormal raw material or incorrect set-up
parameters, can be found for special cause variations.
• Special cause variation exist within the process and process is said to be ‘out of control’ and
unstable
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Types of Variation
•SPC control chart is one method of identifying the type of variation present.
 Statistical Process Control (SPC) Charts are essentially:
• Simple graphical tools that enable process performance monitoring.
• Designed to identify which type of variation exists within the process.
• Designed to highlight areas that may require further investigation.
• Easy to construct and interpret.
 2 most popular SPC tools
• Run Chart
• Control Chart
 SPC charts can be applied to both dynamic processes and static processes
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Control Charts
 Show the variation in a measurement during the time period that the process
is observed.
 changes to the process. This information is then used to make quality
improvements.
 A time ordered sequence of data, with a centre line calculated by the mean.
 Used to determine the capability of the process.
 Help to identify special or assignable causes for factors that impede peak
performance.
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Control Charts
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Control Charts
 Control limits define the zone where the observed data for a stable and
consistent process occurs virtually all of the time (99.7%).
 Any fluctuations within these limits come from common causes
inherent to the system, such as choice of equipment, scheduled
maintenance or the precision of the operation that results from the design.
 An outcome beyond the control limits results from a special cause.
 The automatic control limits have been set at 3-sigma limits.
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Control Charts
•The area between each control limit and the
centerline is divided into thirds.
 Zone A - "1-sigma zone“
 Zone B - "2-sigma zone"
 Zone C - " 3-sigma zone “
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Types of Control Charts
•The are two types of charts:
1. Variable Charts
1. R- Chart
2. X- Chart
2. Attributed Charts
1. P- Charts
2. C - Charts
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Variables Charts
 Variable data are measured on a continuous scale
 Ex: time, weight, distance or temperature can be
measured in fractions or decimals
 Applied to data with continuous distribution
Attribute Charts
 Attribute data are counted and cannot have
fractions or decimals.
 Attribute data arise when you are determining
only the presence or absence of something:
success or failure, accept or reject, correct or not
correct.
 Ex: A report can have four or five errors but it
cannot have four and half errors.
 Applied to data following discrete distribution
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R - Charts
 It controls the dispersion of the process
 R is the range or difference between the highest
and lowest values in sample
 It measures gain or loss of uniformity within a
sample which represents the variability in the
response variable over time.
 Ex: Weigh samples of coffee and computes ranges
of samples Plot
X - Charts
 It controls the central tendency of the process
 Shows sample means over time
 Monitors process average
 Example: Weigh samples of coffee and compute
 means of samples; Plot
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P - Charts
 It tracks the proportion or percent of
nonconforming units or percent defective
in each sample over time.
 Ex: Count defective chairs & divided by
total chairs inspected
 Chair is either defective or not defective
C - Charts
 It shows the number of nonconformities
i.e defects in a unit
 Unit may be chair , steel sheet , car etc.
Size of unit must be constant
 Ex: Count defects (scratches .chips etc.)
in chair of a sample of 100 chairs
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Advantages of Statistical Control
 Provides means of detecting error at inspection.
 Leads to more uniform quality of production.
 Improves the relationship with the customer.
 It reduces cost.
 It reduces the number of rejects and saves the cost of material.
 It determines the capability of the manufacturing process
 It provides direction for long term reduction in process variability.
 It is stable process and operates with less variability.
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Process Capability
 Process capability studies distinguish between conformance to
control limits and conformance to
 specification limits (also called tolerance limits)
• if the process mean is in control, then virtually all points will
remain within control limits
• staying within control limits does not necessarily mean that
specification limits are satisfied
• specification limits are usually dictated by customers
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Use of Process Capability Information
 Predicting the extent of variability that process will exhibit.
 Choose most appropriate process to meet the tolerance.
 Planning the inter-relationship of sequential process.
 Assign themachines to work for which they are best suited.
 Testing causing of defect during quality improvement programs.
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Standardized Formula
 The most widely used formula for process capability is
Process Capability = ± 3σ
Where,
σ = Standard deviation of the process
 If the process is centered and follows normal probability within ± 3σ of the
normal specification.
 99.37% product will fall
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Capability Index ( CPK )
Cp index measures potential capability, assuming that the process avg. is
equal to the mid point of the specification limit and the process is
operating in statistical control because the avg. often not at the mid point it
is useful to have capability index that reflects both variation and the
location of the process avg. Such index is the capability index (Cpk) .
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Cpk = [ Upper Specification limit – x ] or
3
[ x - Lower Specification Limit ]
3
Where,
x  process mean
  standard deviation of the processpopulation

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Capability Index ( CPK )
 If actual avg. = mid point of the specification range
Cpk = Cp
 Higher the Cp lower the amount of product outside specification limit.
 A capability index can also be calculated around a target value rather than
actual avg.
 This index called as Taguchi index (Cpm).
 Krishnamoorti & Khatwani (2000) propose capability index for handling
normal and non- normal characteristic.
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Assumption of Statistical Control & Its Effect on Process Capability
 There are five key assumption
 Process Stability:-statistical validity requires a state of statistical control with
no drift or oscillation.
 Normality of the characteristic being measured :-Normality is needed to draw
statistical interference about the population.
 Sufficient Data :-It is necessary to minimize the sampling error for the
capability index.
 Representativeness of samples :- must include random sample.
1. Independence of measurements:- Consecutive measurement cannot be
correlated.
Are not theoretical refinements they are important condition for applying
capability index .
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Table of Contents
 What is lean?
 Why lean?
 Principles of lean
 Goals of lean
 Types of waste
 Lean tools
 Steps to achieve lean systems
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What is Value?
Value - A capability provided to a customer at
the right time at an appropriate price, as defined
by the customer.
 Cost
 Quality
 Delivery
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What is Waste?
Waste is any activity that consumes time,
resources, or space but does not add any value to
the product or service.
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Constraints on Performance Improvement
• Lack of Funds 43%
• Limited Resources 42%
• Lack of Time 40%
• Lack of Qualified Personnel 32%
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5 Principles of Lean
 Define value from the customer perspective
 Identify the value stream
 Make the process flow
 Pull from the customer
 Head toward perfection
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Specify value :
 Specify value from the standpoint of the
end customer by product family.
Identify the value stream :
 Identify all the steps in the value stream for
each product family, eliminating whenever
possible those steps that do not create value.
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Create flow :
 Make the value-creating steps occur in
tight sequence so the product will flow
smoothly toward the customer.
Let the customer pull product through the
value stream:
 Make only what the customer has ordered.
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• Seek perfection :
 As value is specified, value streams are
identified, wasted steps are removed, and
flow and pull are introduced, begin the
process.
 and continue it until a state of perfection
reached in which perfect value is created
waste.
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Four Goals of Lean
Improve quality:
 In order to stay competitive in today’s
marketplace, a company must understand its
customers' wants and needs and design processes
to meet their expectations and requirements.
Eliminate waste:
 Waste is any activity that consumes time,
resources, or space but does not add any value to
the product or service.
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Four Goals of Lean
Reduce time:
 Reducing the time it takes to finish an activity
from start to finish is one of the most effective
ways to eliminate waste and lower costs.
Reduce total costs:
 To minimize cost, a company must produce only
to customer demand. Overproduction
increases a company’s inventory costs due to
storage needs.
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The Seven Forms ofWaste
 overproduction (occurs when production should have stopped)
 Waiting (periods of inactivity)
 Transport (unnecessary movement of materials)
 Extra Processing (rework and reprocessing)
 Inventory (excess inventory not directly required for current orders)
 Motion (extra steps taken by employees due to inefficient layout)
 Defects (do not conform to specifications or expectations)
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Overproduction :
Producing more/sooner than the Internal or External customer needs.
Waiting :
Long periods of inactivity for people, information, machinery or
materials.
Transportation :
Excessive movement of people, information or materials.
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In appropriate processing:
 Using the wrong set of tools, procedures or systems.
Unnecessary Inventory:
 Excessive storage and delay of information or products.
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List of Lean Tools
 waste elimination
 standardized work
 poka yoke
 5s visual workplace
 just in time
 continuous improvement
 material management
 work in process
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POKA-YOKE
 POKA-YOKE- means “Mistake proofing”.
 And it also provides visual or other signals to
indicate characteristic state and referred as
error proofing .
 It is a Japanese word .
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5SVisual Work Place
 POKA-YOKE- means “Mistake proofing”.
 And it also provides visual or other signals to
indicate characteristic state and referred as
error proofing .
 It is a Japanese word .
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Just in Time
 It can lead to huge improvements in quality
and efficiency .
 This method was adopted by Japanese
manufacturing company.
 JIT means making what the market wants,
when it want it.
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Continuous Improvements
 Continuous improvement ,in regards to
quality and performance .
 And it also improves customers satisfaction
through continuous and incremental
approach.
 And there by removing unnecessary activities
and variation .
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Work in Process
 It aims to minimize the work .
 It needs to store the inventory .
 It take time to look above and below work
areas for needed storage .
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Material Management
 It is a branch of logistics and deals with
tangible components of supply chain.
 It can consolidate and efficiently handle core
service .
 The parts and materials used in supply chain
meets the minimum requirements by
performing quality assurance .
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Value Stream Mapping
Lean Thinking diagnostic tool that allows you
to:
 Visualize work
 “See the waste” (barriers to flow)
 Focus on improvements
 Value Stream = steps (value added and non-
value added) that are required to complete a
service from beginning to end
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ValueAdded VS Non-Value
• Value added activities
 The customer is willing to pay money for the
process
 Work that changes the market form, fit or
function
• Non-value added activities
 Should be eliminated, simplified, reduced, or
integrated whenever possible
 Two types of non-value added activities:
 Required for business
 Not required for business
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ValueAdded VS Non-Value
 Continuous focus on increasing value added
activities
 If value added activities are increased by
10% = gain of only 2%!
 Focus on reducing non-value added
activities by 10% = gain of 8% value
added!
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Non-ValueAdded
80%
Value Added

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Design a Simple Manufacturing System
• There is always room for improvement
The core of lean is founded on the concept of continuous product and process
improvement and the elimination of non-value added activities. “The Value adding
activities are simply only those things the customer is willing to pay for, everything else is
waste, and should be eliminated, simplified, reduced, or integrated”. Improving the flow of
material through new ideal system layouts at the customer's required rate would reduce
waste in material movement and inventory.
• Continuously improve
A continuous improvement mindset is essential to reach a company's goals. The term
"continuous improvement" means incremental improvement of products, processes, or services
over time, with the goal of reducing waste to improve workplace functionality, customer
service, or product performance.
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Design a Simple Manufacturing System
A fundamental principle of lean manufacturing is demand-based
flow manufacturing. In this type of production setting, inventory
is only pulled through each production centre when it is needed
to meet a customer’s order.
 The benefits of this goal include
 decreased cycle time
 less inventory
 increased productivity
 increased capital equipment utilization
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ThankYou
ALI RAZA
+92 3338683924
2017ME516@student.uet.edu.pk
2017-ME-516
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Six sigma, spc , lean

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