7 QC(Quality Control) Tools

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Quality Control (QC) Tools
Brief presentation
Location: DIVGI TORQTRANSFER SYSTEMS PVT LTD, SIRSI

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As much as 95% of quality related problems in the
factory can be solved with seven fundamental
quantitative tools.”(Kaoru Ishikawa)
Why Quality Control?

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Quality Control, or QC for short, is a process by which entities review the quality
of all factors involved in production. We need quality tools for
 problem solving,
 continual improvement and
 process measurement.
IATF:16949 defines quality control as “A part of quality management focused on
fulfilling customer-specific quality requirements”.

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This approach places an emphasis on three aspects;
 Elements such as control, job management, defined and well managed
processes, performance and integrity criteria, and identification of
records.
 Competence, such as knowledge, skill, experience, and qualifications.
 Soft elements, such as personnel, integrity, confidence, organizational
culture, motivation, team spirit, and quality relationship.

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7 Quality Control (QC) Tools:
 Check sheet
 Flow Chart
 Histogram
 Cause and Effect Diagram(Fish-Bone)
 Pareto Chart
 Scatter Diagram
 Control Chart

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CHECK SHEET
 Made popular by Kaoru Ishikawa
 Check sheet is a simplest way to assess common problems.
 The Check Sheet is a document that is used for collecting data in real time and
the location where the data is generated. The document is typically a blank
form that is designed for the quick, easy, and efficient recording of the desired
information.
 Data can be quantitative(numeric) or qualitative(non-numeric).
1. Check Sheet

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When to use it?
 collecting data from a production process.
 To distinguish between fact and opinion.
 When data can be observed and collected repeatedly by same person and at
location.
 When collecting data on the frequency or problems, defects, defect location
and causes etc.
1. Check Sheet

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Check Sheet Procedure:
 There is a standard format for an ISO/IATF certified company.
 Created all spaces on the form.
 Date, Shift, Component name, part number, batch, process number and name,
Entities to record and serial number. These are the standard sections in a
check sheet.
1. Check Sheet

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Example of Check sheet:
1. Check Sheet

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Benefits of Check Sheet:
 It is a simplest and effective way to display data.
 It is a good first step in understanding the nature of problem.
1. Check Sheet

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Flow Chart:
 Draw a flowchart for whatever you do, until you do, you do not know,
what you are doing, you just have a job. ( Dr. Edward Deming)
 diagram commonly used in Process Engineering to indicate the general flow of
plant processes and equipment.
 displays the relationship between major equipment of the plant facility and
does not show minor details and designation
 Process Flow Diagram (PFD), Flow Sheet are other names for Flow Chart
2. Flow Chart

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When to use a Flow Chart ? :
 To study process for improvement
 To develop understanding of how a process is done
 To communicate to other how is process is done
 To document a process
 When better communication needed between people involved with the same
process.
 When planning a project
2. Flow Chart

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Flow Chart basic procedure :
 Discuss and decide on the boundaries of your process : where and when does
the process start? Where and when does it end? Discuss and decide on the
level of detail to be included in the diagram
 Identify the activities that take place. Write each on the note.
 Arrange the activities in proper sequences.
 When all activities are included and everyone agrees on correctness of
sequence, draw arrow to show the flow of the process.
 Review the flowchart with others involved in the process(workers, supervisors,
suppliers, customers)
2. Flow Chart

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Example of Flow Chart:
Better description of process
Hitting snooze button 3 times
Makes the end process delay by
5 minutes each time
2. Flow Chart

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Benefits of Flow Chart:
 Identify process that need improvement
 Depicts customer-supplier relationship
 Determine major and minor inputs in process
 Promotes process understanding
 Create visual map of the process.
2. Flow Chart

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Histogram:
 Graphical representation of the distribution of numerical data
 Pictorial nature of histogram enables us to see patterns that are difficult to see
in check sheet/ table of numbers
 It shows the form of distribution by establishing the frequency of data within
range.
 Tells about patterns of variation
3. Histogram

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When to use a Histogram:
 When the data are large and numerical.
 To compare measurement to specification.
 To communicate information to the team.
 To look where the central tendency of a process is.
 When analysing whether a process can meet customer’s requirement.
 To determine whether the outputs of two or more process are different.
3. Histogram

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Histogram Procedure: (1/2)
 Arrange the collected data column wise in table form.
 Find and mark maximum and minimum value in each group. And in whole set
 Calculate the Range. (Range = max – min)
 Determine the numbers of class intervals for frequency e.g. <500 = 5 to 7,
500 to 1000 = 6 to 10, >1000 = 7 to 12
 Determine intervals(bucket) and boundaries. (Interval= range /class interval)
 Determine the frequencies of each class interval with tallies / Excel
3. Histogram

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Histogram Procedure: (2/2)
 Mark and label frequency at vertical scale
 Mark and label measurement value at the horizontal scale
 Draw the columns according to frequencies
 Label the histogram
3. Histogram

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Histogram example:
3. Histogram

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Histogram example:
3. Histogram

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Histogram example:
3. Histogram

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Histogram Analysis: (1/2)
1) Normal: common pattern (bell-shaped) known as normal distribution(ND)
2) Skewed: asymmetrical because a limit prevents outcome on one side.
3) Double-picked or bimodal: looks like back of two-humped camel
4) Plateau: called multimodal distribution. Several processes with ND
combined
5) Comb: the bars are alternatively tall and short.
6) Truncated or heart-cut: looks like ND with tails cut off
3. Histogram

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Histogram Analysis: (2/2)
7) Dog food: its missing something – results near the average.
8) Edge peak: Normal distribution except that it has large peak at one tail.
3. Histogram

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Benefits of Histogram:
 Simple to use, visualise, and interpret.
 Process monitoring and centering.
 To know whether process produces within specification.
 To know whether process is stable and predictable.
 Application to all variable data.
3. Histogram

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Cause and Effect Diagram:
 Also known as Ishikawa Diagram, Fishbone diagram, herringbone diagram.
 Shows relationship between a problem and its possible causes
 Explore potential causes and help identify root causes.
 Where and why the process isn’t working
 Used for product design, quality defect prevention
 Each cause for imperfection is a source of variation.
4. Cause and Effect Diagram

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When to use Cause and Effect Diagram:
1) When identifying possible causes for a problem.
2) To analyse existing problems.
3) For problem-solving.
4) To sort out interactions among factors for a cause.

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Why to use Cause and Effect Diagram?
1) Group participation and knowledge sharing.
2) To determine root cause of a problem.
3) Increases knowledge of a process and its factors.
4) Identifies area for further data collection
5) For process improvement.

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Cause and Effect Diagram procedure:
1) Identify and define a problem statement (effect)
2) Identify major categories of causes of problem. General ones are 6Ms
1. Man(personnel) 4. Material
2. Machine 5. Measurement
3. Method 6. Mother Nature (Environment)
3) Write categories as branches for the effect.
4) Brainstorm all the possible causes of problem and write details
5) Write sub-branches, continue to ask “why?” to find deeper level of cause

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Cause and Effect Diagram Example:

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Benefits of Cause and Effect Diagram:
1) Making a diagram is educational in itself.
2) Indicates possible causes of variation
3) Focus is on ”causes” rather than “symptoms”.
4) Improve team performance and effectiveness.
5) Improve process knowledge.
6) Set as a standard for future similar effects.

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Pareto Chart:
 Named after Vilfredo Pareto, is a type of chart contains bars & line graph.
 States that, for many event, roughly 80% of the trouble comes from 20% of
the problems
 Individual values are in descending order by bars, cumulative total is
represented by the line.
 Values of statistical variable are placed in order of relative frequency, reveals
which factors have the greatest impact and where attention is likely to yield the
greatest benefit.
5. Pareto Chart/Analysis

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When to use Pareto Chart ? :
1) When analysing data about frequency of problems or causes in a process.
2) When there are many problems or causes and you want to focus on the most
significant.
3) When analysing broad causes by looking at their specific components.
4) When communicating with others about your data.
5) Allow better use of limited resources.

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Pareto Chart procedure : (1/2)
1) Decide what categories to use to group items.
2) Decide what measurement is appropriate, common measurement are
frequency, quantity, cost and time.
3) Decide the the period of time this chart will cover; one work cycle, full day,
month ?
4) Collect the data, recording the category each time
5) Subtotal the measurement for each category and plot bars in descending
order.
6) Calculate the percentage and plot cumulative total % along with it.

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Pareto Chart procedure : (2/2)
7) Focus on the area which falls under 80% of cumulative percentage
8) Note: There are many tools which we can get pareto results by just inputting
the data.

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Pareto Chart Example : (2/2)

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Benefits of Pareto Chart Example :
 Identifies “major” problems
 Improves team performance and effectiveness
 Before and after tracking of a problem in chart
 Helps for continual improvement
 Cost reduction and customer satisfaction

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Benefits of Pareto Chart Example :
 Identifies “major” problems
 Improves team performance and effectiveness
 Before and after tracking of a problem in chart
 Helps for continual improvement
 Cost reduction and customer satisfaction

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Scatter Diagram:
 Is a visual and statistical testing tool. Called as Scatter Plot or X-Y graph
 Used to investigate the possible relationship between two variables that relate
to the same event. To arrive at quantitative conclusion.
 Makes it easy to spot trends and correlations.
 If variables are correlated, the points fall among a line or curve.
 The better the correlation, tighter the points near the line.
6. Scatter Diagram

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When to use Scatter Diagram ? :
 When we have paired numerical data.
 When dependent variable may have multiple values for each value of
independent variable.
 In problem-solving to establish a root cause.
 To confirm a hypothesis
 When testing for autocorrelation before constructing a control chart
6. Scatter Diagram

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Scatter Diagram procedure :
1) Collect pairs of data; independent and dependent variable.
2) Independent variable on the horizontal axis and dependent on vertical axis
3) For each pair of data, put a dot where X-axis intersects Y-axis’ value.
4) Look at the pattern of points to see if a relationship is obvious.
5) If the data clearly form a line or curve, then the variables are correlated. Then,
can be proceeded to correlation analysis
6. Scatter Diagram

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Scatter Diagram Analysis :
Patterns of correlation
6. Scatter Diagram

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Scatter Diagram Analysis :
The local cold drink shop track of how much cold drink bottle they sell versus the noon
temperature of that day. Data for the last 10 days.
6. Scatter Diagram
We can also draw a “line of best fit”
on scatter diagram

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Control Chart:
 Is a special type graph used to detect the special causes in the process over
time.
 Used for monitoring, improving quality and measure consistency of a process
or machine.
 Has a central line for average, upper line for Upper Control Limit(UCL), lower
line for lower control limit(LCL).
 These lines are determined from historical data of process or machine.
 By comparing current data to these line, you can draw result easily about
whether the variation is in control or out of control.
7. Control Chart

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When to use Control Chart ? :
1) When identifying variation at its source.
2) When predicting the expected range of outcomes from a process.
3) When visual displaying for process output.
4) When determining whether a process is stable.
5) To monitor, control and improve.
7. Control Chart

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Types of Control Chart :
7. Control Chart

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7. Control Chart

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1. For variables : for the characteristics that can be measured (X-R Chart)
2. For attributes : for the characteristics that can be judges as pass or fail, defective or ok, go are no-go etc.
· R chart – in this chart, the sample range are plotted in order to control the variability of a variable.
· S chart – in this chart, the sample standard deviations are plotted in order to control the variability of
variable.
· C chart – in this chart, plot the number of defectives (per day, per batch or per machine)
· U chart – in this chart, plot the number of defectives divided by the numbers of units inspected
(numbers of batches)
· Np chart – in this chart, plot the number of the defectives as in the C chart. However, the control
limit in this chart are not based on the distribution rare events, but rather on the binomial distribution.
· P chart – in this chart, plot the percent of defectives as in the U chart, However, the control limit in this chart are not
based on the distribution rare events, but rather on the binomial distribution.
7. Control Chart

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Control Chart procedure:
1) Choose the correct control chart for your data.
2) Determine the appropriate time period for collecting and plotting data.
3) Collect data, draw chart and analyse
4) Look for “in-control” or “out-of-control” condition
5) For “out-of-control” signal, mark it on the chart and investigate the cause.
6) Document how you investigated, what you learned, the cause and it was
corrected.
7. Control Chart

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Control Chart example:
7. Control Chart

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Benefits of Control Chart:
 Easy and simple to study and maintain.
 It is an effective tool to control the process statistically
 It provides information about capability.
 Tool which help to reduce variation.
 Helps to detect changes in the process over a period of time and take corrective
action
7. Control Chart

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PRODUCT LEADERSHIP
LIKE NO OTHER
Thank You

7 QC(Quality Control) Tools

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