STATISTICAL PROCESS CONTROL STATISTICAL QUALITY CONTROL QUALITY CONTROL

1. SPC,SQC & QC TOOLS
MOHAMETH HISAM M R
A31001916018

2. Relationship between SPC,SQC &
QC

3. Statistical Process Control
Statistical process control (SPC) involves inspecting a random
sample of the output from a process and deciding whether the
process is producing products with characteristics that fall within a
predetermined range. SPC answers the question of whether the
process is functioning properly or not.

4. Application
• Control of Variation
• Continuous Improvement
• Predictability of Processes
• Elimination of Waste
• Product Inspection

5. The Seven Old Tools
1. Control chart
2. Run chart
3. Pareto chart
4. Flow chart
5. Cause and effect diagram
6. Histogram
7. Scatter diagram

6. Control chart is a graph 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.
Control Chart
Data Category Chart Type Statistical Qty
Variable Data X-bar & R Mean & Range
X-tilde & R Median & Range
X-Rs Individual Values
Attributes Data P- Chart Percent of defectives
nP- Chart Number of defectives
C- Chart Number of defects
U- Chart Number of defects per unit

7. Run Chart
A run chart is a line
graph of data plotted over
time. By collecting and
charting data over time, you
can find trends or patterns in
the process. Because they do
not use control limits, run
charts cannot tell you if a
process is stable.

8. Pareto chart
Pareto Chart is a type of chart that contains both bars and a line
graph, where individual values are represented in descending order
by bars, and the cumulative total is represented by the line.

9. Flow Chart
A flowchart is a type of diagram
that represents an algorithm,
workflow or process, showing the
steps as boxes of various kinds,
and their order by connecting them
with arrows. This diagrammatic
representation illustrates a solution
model to a given problem.
Flowcharts are used in analyzing,
designing, documenting or
managing a process or program in
various fields

10. Cause and Effect Diagram (Fishbone Analysis)
Cause and Effect diagram is a diagram which visually displays the
many causes for a problem or effect. It helps to find the root cause of
a problem.

11. Histogram
A histogram is a graphical representation of the distribution of
numerical data. It is an estimate of the probability distribution of a
continuous variable. It consisting of rectangles whose area is
proportional to the frequency of a variable and whose width is equal
to the class interval.

12. Scatter Diagram
Scatter Diagram is a graph in which the values of two variables
are plotted along two axes, the pattern of the resulting points revealing
any correlation present.

13. The Seven New Tools
1. Affinity diagram
2. Relational diagram
3. Tree diagram
4. Matrix diagram
5. Program decision process chart
6. Arrow diagram
7. Prioritization Matrix

14. Affinity Diagram
An Affinity Diagram is a tool that gathers large amounts of
language data (ideas,opinions, issues) and organizes them into
groupings based on their natural relationships . The Affinity process
is often used to group ideas generated by Brainstorming.

15. Relationship Diagram
An entity-relationship diagram (ERD) is a graphical
representation of an information system that shows the relationship
between people, objects, places, concepts or events within that
system. An ERD is a data modeling technique that can help define
business processes.

16. Tree Diagram
Tree diagram a way of representing the hierarchical nature of a
structure in a graphical form. It helps to list the various criteria
based on their importance.

17. Matrix diagram
A Matrix Diagram (MD)
is a tool that allows a
team to identify the
presence and strengths of
relationships between
two or more lists of
items. It provides a
compact way of
representing many-to-
many relationships of
varying strengths.

18. The process decision program chart (PDPC) systematically
identifies what might go wrong in a plan under development.
Countermeasures are developed to prevent or offset those
problems. By using PDPC, you can either revise the plan to avoid
the problems or be ready with the best response when a problem
occurs.
Program decision process chart

19. Arrow diagram
Arrow diagramming method (ADM) is a network diagramming
technique in which activities are represented by arrows. ADM is also
known as the activity-on-arrow (AOA) method. The arrow diagram
shows the required order of tasks in a project or process, the best
schedule for the entire project, and potential scheduling and resource
problems and their solutions. The arrow diagram lets you calculate
the “critical path” of the project.

20. A prioritization matrix is a
simple tool that provides a
way to sort a diverse set of
items into an order of
importance. It also
identifies their relative
importance by deriving a
numerical value for the
priority of each item.
Prioritization Matrix

21. Statistical Quality Control
Statistical quality control refers to the use
of statistical methods in the monitoring and maintaining of
the quality of products and services.
Sampling technique is the most widely used SQC tool

22. Sampling
Sampling is concerned with the selection of a subset of
individuals from within a statistical population to estimate
characteristics of the whole population. Each observation measures
one or more properties (such as weight, location, colour) of
observable bodies distinguished as independent objects or
individuals.

23. Probability Sampling
Probability sampling is a sample in which every unit in the
population has a chance (greater than zero) of being selected in the
sample, and this probability can be accurately determined.
1. Simple random sampling
2. Systematic sampling
3. Stratified sampling
4. Cluster sampling

24. Simple random sampling
In a simple random
sample (SRS) of a given
size, all such subsets of the
frame are given an equal
probability. Furthermore,
any given pair of elements
has the same chance of
selection as any other such
pair (and similarly for
triples, and so on). This
minimises bias and
simplifies analysis of
results.

25. Systematic sampling
Systematic sampling (also known as interval sampling) relies
on arranging the study population according to some ordering
scheme and then selecting elements at regular intervals through that
ordered list. Systematic sampling involves a random start and then
proceeds with the selection of every kth element from then onwards.

26. Stratified sampling
When the population is heterogeneous, t
he use of simple random sample may not
produce representative sample. Some of
the bigger strata may get over representat
ion while some of the small ones may
Entirely be eliminated. Look at the
variables that are likely to affect the
results, and stratify the population in
such a way that each stratum becomes
homogeneous group within itself. Then
draw the required sample by using the
table of random numbers. Hence in
stratified random sampling a sub- sample
is drawn utilizing simple random
sampling within each stratum.

27. Cluster sampling
The purpose of cluster sampling is
to sample economically while retaining the
characteristics of a
probability sample. Groups or chunks
of elements that, ideally, would have heter
ogeneity among the
members within each group are chosen for
study in cluster sampling. This is
in contrast to choosing
some elements from the population as
in simple random sampling, or stratifying a
nd then choosing
members from the strata, or
choosing every nth case in
the population in systematic sampling.

28. Non-probability sampling is any sampling method where some
elements of the population have no chance of selection or where the
probability of selection can't be accurately determined. It involves the
selection of elements based on assumptions regarding the population
of interest, which forms the criteria for selection. Hence, because the
selection of elements is non-random.
Non-probability sampling
1. Quota sampling
2. Convenience sampling
3. Purposive sampling
4. Self-selection sampling
5. Snowball sampling

29. Quota sampling, the population is first segmented into
mutually exclusive sub-groups, just as in stratified sampling. Then
judgement is used to select the subjects or units from each segment
based on a specified proportion.
Quota sampling
In quota sampling the selection of the sample is non-
random. For example, interviewers might be tempted to interview
those who look most helpful. The problem is that these samples
may be biased because not everyone gets a chance of selection.
This random element is its greatest weakness and quota versus
probability has been a matter of controversy for several years.

30. Convenience sampling
Convenience sampling is a type of non-probability
sampling which involves the sample being drawn from that part of
the population which is close to hand. That is, a population is
selected because it is readily available and convenient.
For example, if the interviewer were to conduct such a
survey at a shopping centre early in the morning on a given day,
the people that he/she could interview would be limited to those
given there at that given time, which would not represent the
views of other members of society in such an area, if the survey
were to be conducted at different times of day and several times
per week.

31. Purposive sampling is a sampling technique in which
researcher relies on his or her own judgment when choosing
members of population to participate in the study.
Purposive sampling
TV reporters stopping certain individuals on the street in
order to ask their opinions about certain political changes
constitutes the most popular example of this sampling method.
However, it is important to specify that the TV reporter has to
apply certain judgment when deciding who to stop on the street
to ask questions; otherwise it would be the case of random
sampling technique.

32. Self-selection sampling is appropriate when we want
to allow units or cases, whether individuals or organisations,
to choose to take part in research on their own accord. The key
component is that research subjects (or
organisations)volunteer to take part in the research rather than
being approached by the researcher directly.
Self-selection sampling

33. Snowball sampling
Snowball sampling (or chain sampling, chain-referral sampling, referral
sampling) is a non-probability sampling technique where existing study subjects
recruit future subjects from among their acquaintances. Thus the sample group is
said to grow like a rolling snowball. As the sample builds up, enough data are
gathered to be useful for research. This sampling technique is often used in
hidden populations which are difficult for researchers to access
For example, people who have many friends are more likely to be
recruited into the sample.

34. Quality control
Quality control (QC) is a procedure or set of procedures
intended to ensure that a manufactured product or performed
service adheres to a defined set of quality criteria or meets the
requirements of the client or customer.
The various techniques used in QC are
1. PDCA Cycle
2. 5S
3. Kaizen

35. PDCA Cycle
PDCA (plan–do–
check–act or plan–do–
check–adjust) is
an iterative four-step
management method used
in business for the control
and continual improvement
of processes and products.
It is also known as
the Deming circle/cycle/wh
eel

36. 5S is the name of a workplace organization method that uses a list of
five Japanese words: seiri, seiton, seiso, seiketsu, and shitsuke. They all start
with the letter "S". The list describes how to organize a work space for efficiency
and effectiveness by identifying and storing the items used, maintaining the area
and items, and sustaining the new order. The decision-making process usually
comes from a dialogue about standardization, which builds understanding among
employees of how they should do the work.
5S

37. Kaizen is a lean manufacturing tool that improves quality,
productivity, safety, and workplace culture. Kaizen focuses on
applying small, daily changes that result in major improvements
over time.
Kaizen