Z Score,T Score, Percential Rank and Box Plot Graph
C chart class material
1. Work Study -Basic procedure involved in Method
Study and Work Measurement-Statistical Quality
Control :C CHART:
Mr.Bestha Chakrapani M.pharm (Ph.D)
Associate Professor
Department of Pharmaceutical sciences
Balaji college of Pharmacy
Anantapuramu
UNIT–II
8. BASIC PRINCIPLES OF CONTROL CHARTS
The control chart is a graphical display of a
quality characteristic that has been measured
or computed from a sample versus the sample
number or time.
The charts contains a central line,a upper
control limit and a lower control limit.
.
9. TYPES OF CONTROL CHARTS
CONTROL
CHARTS
VARIABLE
X_bar,R
X_bar,S
SHEWHART
INDIVIDUA
L
P-CHART
np-CHART
ATTRIBUTE
U-CHART
C-CHART
10. HEALTHCARE & CONTROL CHART
Control chart
Aid in process understanding
Assess process stability
Identify changes indicating improvement or
deteoriation in quality
Used in
Hospital process improvement projects
Accrediting bodies and governmental
agencies
Public health surveillance
11. CONTROL CHART FOR
NONCONFORMITIES(DEFECT)
The nonconfirming item is a unit of
product that doesnt satisfy the
specifications for that product.
Distinction between a defect and
defective is clear
Defect:-Any instance of the item’s
lack of conformity to specification.
Defective:-Item that fails to fulfil one
or more of the given specifications
12. WHAT IS C-CHART?
Originally proposed by WalterA.
Shewhart.
It is a control chart for
nonconformities.
Developed for total number of
nonconformities in a unit.
Underlying distribution-Poisson
distribution.
Two cases- 1.Standard given.
2.Standard not given.
13. C-CHART:STANDARD GIVEN
UCL =c+3√c.
Central line= c
LCL=c-3√c.
NOTE:
where c is the parameter of Poisson
distribution.
If LCL comes negative, take it as 0.
14. C-CHART:STANDARD NOT GIVEN
Let ci be the c value for the sample taken
from the ith subgroup(i=1(1)n).Then the
appropriate estimate of c will be
c’=∑ ci /n.
UCL= c’+3√c’.
CENTRAL LINE= c’.
LCL= c’-3√c’.
15. NOTE:
c’ is the estimated value of the poisson
parameter. c’ may be estimated as the
observed average number of
nonconformities in a preliminary sample of
inspection units.
When no standard is given, the control
limits in equation should be regarded as trial
control limits.
16. 26 Samples -516 total nonconformities
c’=516/26=19.85
UCL=c’+3√c’=19.85+3√19.85=33.22
Centre Line=c’=19.85
LCL=c’-3√c’=19.85-3√19.85=6.48
EXAMPLE…
17. After removing the two out of control points , The
estimate of c is now computed as c’=472/24=19.67
Revised control limits:-
UCL=c’+3√c’=19.67+3√19.67=32.97
Centre Line=c’=19.67
LCL=c’-3√c’= 19.67-3√19.67=6.36
18.
19. USE OF C-CHART IN HEALTH CARE
Attribute data involves-
-counts(no.of falls per day).
--proportions(proportion of patients receiving right antibiotics).
-rate(the number of falls per 1000 patient-days).
For counts we use c-chart.
20. CONCLUSION
Defect or nonconformity data are always
more informative than fraction
nonconforming,
Widely used in transactional and service
business applications of statistical process
control.
The limitation of c chart is that it takes
samples of constant size where in reality it
might not be so.In case of variable sample
size we use the u charts that gives us the
no.of defects per unit i.e u=c/n.