Seven Problem Solving Tools[1]
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Transcript of Seven Problem Solving Tools[1]
TQM TOOLS
"As much as 95% of quality related problems in the factory can be "As much as 95% of quality related problems in the factory can be solved with seven fundamental quantitative tools." - Kaoru Ishikawasolved with seven fundamental quantitative tools." - Kaoru Ishikawa
© 2005 Wiley 2
Seven Problem Solving Tools• Cause-and-Effect Diagrams
• Flowcharts
• Checksheet
• Control Charts
• Scatter Diagrams
• Pareto Analysis
• Histograms
The “Seven QC Tools”
5. Pareto Diagrams: separate the vital few from the trivial many causes; provide direction for selecting projects for improvement.
6. Cause-and-Effect Diagrams: represent chain of relationships; often called a fishbone diagram.
7. Scatter Diagrams: graphical component of regression analysis.
Chapter 15 Seven Tools of Quality Management
Cause and Effect Diagram• Also called the Ishikawa Diagram, or Fishbone Diagram.• Problem analysis technique which attempts to identify the root
causes for a problem thereby allowing a group to work towards solving the "real" problems and not just symptoms.
• A line is drawn across the middle of a sheet of paper to a box on the right hand side. In that box, the problem statement is written.
• Major possible categories of cause are distributed along the line. • From these, lines are drawn sloping to the left. • From these lines, contributing issues for each category are
placed.• From these, additional lines can be drawn. the final result is a
tree with all potential causes identified.
Cause-and-Effect DiagramsUsed to identify the cause of a quality problem
Followup: Collect data to verify the cause and develop a plan to eliminate the cause.
Constructing a Fishbone Diagram
• Step 1 - Identify the Problem• Step 2 - Draw “spine” and “bones”
Example: High Inventory Shrinkage at local Drug Store
Shrinkage
Constructing a Fishbone Diagram
• Step 3 - Identify different areas where problems may arise from
Ex. : High Inventory Shrinkage at local Drug Store
Shrinkage
employees
shoplifters
Constructing a Fishbone Diagram
• Step 4 - Identify what these specific causes could be
Ex. : High Inventory Shrinkage at local Drug Store
Shrinkage
shoplifters
Anti-theft tags poorly designedExpensive merchandise out in the open
No security/ surveillance
Constructing a Fishbone Diagram
• Ex. : High Inventory Shrinkage at local Drug Store
Shrinkage
shoplifters
Anti-theft tags poorly designedExpensive merchandise out in the open
No security/ surveillance
employeesattitude
new traineetraining
benefits practices
Constructing a Fishbone Diagram
• Step 5 – Use the finished diagram to brainstorm solutions to the main problems.
Example (1 of 4)
• Step 1 & 2:
Poor Service(“backbone”)
(“head”)
Example (2 of 4)
• Step 3 & 4:
Poor Service
Responsiveness
Reliability
Appearance
Attention
Example (3 of 4)
• Step 5, 6, & 7:
Poor Service
ResponsivenessAppearance
Attention Reliability
time
courtesy
personnelfacility
equipment
One on one service
dependability
accuracy
Example (4 of 4)
• Step 8 & 9:– Use tools to analyze and evaluate causes
• Pareto diagrams, charts, and graphs• Statistical analysis for causes in processes
– Decide and take action• Use fishbone diagram, analysis and evaluations to
find causes that can be fixed• Take action to eliminate and fix problem causes
Cause and Effect Diagram
Product Quality
Order Fulfillment
Service
Distribution System
Order Processing System
Customers are dissatisfied
Fishbone Chart: Airline Customer Service
Cause-and-Effect Chart for Flight Departure Delay (Fishbone Chart)
Equipment Personnel
Procedure
Material
Other
Aircraft late to gateLate arrival
Gate occupied
Mechanical failuresLate pushback tug
WeatherAir traffic
Late food serviceLate fuel
Late baggage to aircraft
Gate agents cannot process passengers quickly enoughToo few agents
Agents undertrainedAgents undermotivated
Agents arrive at gate late
Late cabin cleaners
Late or unavailable cockpit crewsLate or unavailable cabin crews
Poor announcement of departuresWeight an balance sheet late
Delayed checkin procedureConfused seat selection
Passengers bypass checkin counterChecking oversize baggage
Issuance of boarding pass
Acceptance of late passengersCutoff too close to departure time
Desire to protect late passengersDesire to help company’s income
Poor gate locations
DelayedFlightDeparture
Exercise• Create a Fishbone (cause and effect,
Ishikawa) Diagram for the following:
‘ Management at Red MeatIndustries has noticed that the productivity of its workers is well below the standard. After interviewing its employees, it was noticed that a vast majority felt dissatisfied and unhappy with their work. Your boss has asked you and a group of your peers to find the causes of worker dissatisfaction. Include all possible causes to at least the secondary level.’
Exercise• Answers should include the following:• Worker dissatisfaction as the ‘head’ of the diagram• Major causes should include environment, equipment,
and management• Secondary causes for environment• Worker training, worker empowerment, cleanliness,
wages, benefits, etc.• Secondary causes for equipment:• Effectiveness of equipment, age and maintenance
requirements, lack of new technologies, etc.• Secondary causes for Management:• Leadership qualities, Involvement, Attention, Expertise,
human relations, etc.
Flowchart
• Used to document the detailed steps in a process
• Often the first step in Process Reengineering
FlowchartsDon’t Forget to:
• Define symbols before beginning
• Stay consistent
• Check that process is accurate
22
Flowcharts / Flow Diagram
i.e., how a process flows
1 2 3 4
1a
yes
no
Produce GoodProvide Service
Stop Process
Yes
NoAssign.
Causes?Take Sample
Inspect Sample
Find Out WhyCreate
Control Chart
Start
Flowchart e.g. Statistical Process Control Steps
Passenger Arrives
Ticket No Wait for For Flight Appropriate
Flight
Yes
Check Yes Excess Luggage Carry-on
No
IssueBoarding Pass
PassengerBoards Airplane
Acme Pizza Example (Flowchart)
• Answer: Since we know that 2 slices is the most common order we could possibly add a step between Time to close and take customer order. If we brought two slices up to the window during peak hours this would quicken service. There are multiple improvements that can be made on the process. The class can brainstorm on ways of improving this flowchart.
• Note that a decision must be made at each triangle before the next step can begin.
Want some practice?Make a flowchart for:
• Taking a shower• Cooking dinner• Driving a car• Having a party• Creating a Flowchart
Any other processes you can think of?
Check Sheet
Month Lost Departure Mechanical Overbooked Other
Luggage Delay FailureJanuary 1 2 3 3 1February 3 3 0 1 0March 2 5 3 2 3April 5 4 4 0 2
May 4 7 2 3 0June 3 8 1 1 1
July 6 6 3 0 2August 7 9 0 3 0September 4 7 3 0 2October 3 11 2 3 0November 2 10 1 0 0December 4 12 2 0 1
Total 44 84 24 16 12
• A simple checklist that is used to record when something occurs. This is used to identify symptoms and/or potential cases for a problem
ChecksheetTool Used to Collect Data for Analysis
Control Charts
• Control charts are a means of regulating a process. It tracks the output of a process and its conformance to the company’s standards. As long as the process stays within the upper and lower limits then the process is “safe” and normal. Any observations made outside of the limits are irregular and problematic. They need to be immediately researched to improve quality. A process that consistently stays “safe” is a good quality process.
• Deviation from Mean
• Upper and Lower Spec’s
• Range
Control Charts
Control Charts
Upper Limit
Lower Limit
Unacceptable deviation
X
X= meanThe majority of observations have fallen close the average. The one that’s under the lower limit is irregular, it needs to be examined and fixed.
Control Charts
Acme Pizza Management wants to get in on the control chart action
•Average Diameter = 16 inches
•Upper Limit = 17 inches
•Lower Limit = 15 inches
Acme example Control Charts
Upper Limit
17 inches
Lower Limit15 Inches
Small Pie
X16 inches=
Monitoring the pizza process, this example shows how almost every pie is within specifications. The process should be analyzed to discover why the one small pie was produced and corrected to improve quality.
Acme example #50Control Charts
•Pies within specifications were acceptable
•One abnormally small pie is “uncommon”
•Should be examined for quality control
Control Chart• Set confidence intervals for the mean and range of a
process (usual behavior)• LCL = lower control limit, UCL = upper control limit• Is process in control (predictable)?• Does process have conformance quality?
Scatter Diagrams
• A graph that shows how two variables are related to one another
• Data can be used in a regression analysis to establish equation for the relationship
Scatter Diagrams
• depict relationships between paired data
5 10 15 20 25
A
ve. N
o. o
f D
efec
ts 0
1
0
20
3
0
40
|
|
|
|
Linear Relationship
Thousand Lines of Code
Acme Pizza (Scatter Diagram)
Minutes Cooking Defective Pies
10 1
45 8
30 5
75 20
60 14
20 4
25 6
In this simple example, you can find the existing relationship without much difficulty
Scatter Diagrams
0
5
10
15
20
25
0 20 40 60 80
•Easier to see direct relationship
Time Cooking (minutes)
Def
ecti
ve P
izza
sThere is a direct relationship between time spent cooking by employees and defects. As Time cooking increases, so does the amount of defects.
Histogram
• A chart that shows the frequency distribution of observed values of a variable like service time
at a bank drive-up window• Displays whether the distribution is symmetrical
(normal) or skewed
Histogram
• Bar chart showing the number of occurrences of some event often derived from the results of a check sheet.
• It could be a real world event, like late deliveries by month for a year, or it could be the number of time a proposed solution is suggested.
• It allows a quick prioritisation based on frequency.
Histrogram of Lost Luggage
0
0.5
1
1.5
2
2.5
3
3.5
1 2 3 4 5 6 7
Occurrences per Month
Fre
qu
en
cy
Constructing a HistogramFrom a set of data compute
• sum
• mean (x)
• Max
• Min
• Range (max-min)
Constructing a Histogram• Use range to estimate beginning and end
• Calculate the width of each column by dividing the range by the number of columns
Range
# of Columns= Width
Acme Pizza Example• Let’s say the owner wants a distribution of
Acme’s Thursday Night SalesData Set from last Thursday(slices) 0 2 1 2 2 4 1 3 1 2 1 2 2 4 3 4 1 4 3 2 2 3 2 1 2 2 1 2 2 1 4 2 2 1 2 1 2 2 1 2 1
2 1 2 1 2 1 2 1 2 2 2 1 2 1 2 1 1 2 2 2 3 1 4 2 2 3 2 2 2 1 2 3 2 2 4 2 2 4 4 1 2 2 2 3 2 2 1 2 2 4 2 1 2 4 2 1 7 2 1 2 2 3 1 2 1 1 2 1 2 2 2 1 2 2 1 2 1 2 2 2 4 2 4
These numbers represent the customers order at the order window at the pizza store. For example, the first customer didn’t order any pizza, the second ordered 2 slices, the third ordered 1 and so on. It should be noticed that the highest order was 7 slices and the lowest was 0. This is used to find the range which is used to find the column width for the histogram.
Acme Pizza ExampleMean = 2.032258
Max = 7
Min = 0
Range = 7
Question
For 7 columns what would the width be?
Range/Columns=7/7=1 slice
Acme Pizza Example
33
65
812
0 0 10
10
20
30
40
50
60
70
1 2 3 4 5 6 7
Slices of Pizza
# tim
es o
rder
edHistogram
Constructing a HistogramHow is this helpful to Acme?• 2 slices of pizza most common order placed• Distribution of sales useful for forecasting next Thursday’s late night
demand• If you were an Acme manager how could you apply this
information?
• Most common types of orders placed is valuable information. Knowing that the average customer will order 2 slices of pizza can be implemented into Acme’s strategic plan. By taking at least 2 slices up to the window at peak hours, this can improve Acme’s customer service and speed. It makes the line move much faster making the perceived quality higher for the customer.
• Very similar to Histograms
• Vilfredo Pareto (1848-1923) originated the 80/20 Rule, which states that 80% of the problems comes from only 20% of the causes. Pareto Analysis is very similar to Histograms but it incorporates this theory into it. Pareto Analysis adds weight to the most frequently occurring things.
• Use of percentages to show importance
Pareto Analysis
Pareto AnalysisUsed to Prioritize Problems
• Most important problems should be solved first• Prioritize by number of defects or $ cost of defects• Often called the 80-20 Rule: Most quality problems are the
result of only a few causes. Example: 80% of the problems caused by 20% of causes
Pareto Diagrams
• measures the distribution of quality losses
A B C D E
61%
4%5%13%
17%
% E
RR
OR
S
Pareto Chart• A Pareto chart is usually used to identify the principle drivers to a
problem.
• A checksheet is used to count how often a particular item occurs usually as a cause to a problem (e.g. missing account number on check leads to miss-filing).
• The items are then charted by the percentage of the occurrences in decreasing order.
• The resulting chart shows which items had the most influence on the problem. This goes along with the 80-20 rule which states that 80% of the problem are attributable to only 20% of the causes.
Acme Pizza (part 2)• The completed Pareto Analysis results in the following graph:
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7
Slices of Pizza
# tim
es o
rder
ed
2 1 4 3 7 5 6
Managing Quality + Time + Productivity + Capacity = JIT
The objective of JIT is to . . .
•purchase materials
• produce products
•and deliver products
. . . just when they are needed.
The objective of JIT is to . . .
•purchase materials
• produce products
•and deliver products
. . . just when they are needed.
Managing Quality + Time + Productivity + Capacity = JIT
The goal is to manage costs so that the savings associated with JIT exceed the cost of
implementing JIT
The goal is to manage costs so that the savings associated with JIT exceed the cost of
implementing JIT
Cost savings:•Inventory warehouse rent or cost
•Inventory managers and personnel
•Less warranty cost
Cost savings:•Inventory warehouse rent or cost
•Inventory managers and personnel
•Less warranty cost
Implementation costs:•Employee retraining
•Technology improvement
•Exposure to work stoppage risks.
Implementation costs:•Employee retraining
•Technology improvement
•Exposure to work stoppage risks.
Traditional “Push” Manufacturing - Example
Computer Manufacturer
Forecast Sales Order components
Prepare Production Schedule
Begin Production in Anticipation of Sales
Make sales from finished
goods inventory
Store Inventory
JIT “Pull” Manufacturing - Example
Computer Manufacturer
Customer places an order
Create Production Order
Generate component requirements
Production begins as parts arrive
Goods delivered just in time
Components are ordered