Upon successful completion of this course, students will be able to:
1.Apply the concepts of quality improvement and the DMAIC process within diverse organizational contexts
2.Construct the different types of control charts for process quality improvement
3.Implement the control charts for variables and attributes.
4.Analyze the process and measurement system capability.
5.Develop exponentially weighted moving average and Control Charts for monitoring variability.
Assessment CLOs
Assignment (20) 2,3,4,5
Case Analysis 1 (10) 1,2
Group case analysis 2 (20) 3,4,5
Class Presentation (10) 3,4,5
Final Examination (40) 1,2,3,4,5
Questions:
Assignment Problem 1: (CLO2, 5 Marks)
A packing organization monitoring the performance of a packing machine, each container should weigh 35 lb, during Measure phase, project team performed the process
capability study and observed the following data with 12 sets of container weights of sample size 4. Construct the R and 𝑥̅chart of process quality improvement and identify
the process variability.
[The table is mentioned in the assignment sheet]
Assignment Problem 2: (CLO3, 5 Marks)
When examining time-series data, what we want to occur is the most appropriate action or non-action. However, the conclusion of what action or non-action to take can
be a function of how the data are examined. This point will be illustrated using the data in Table, which provides the number of daily non-conformances that occur from
the number of daily transactions that occur; i.e., 10,000. These data could describe the number of daily non-conformances from an insurance company operating in UAE.
Implement the p and c control charts for variables and attributes and identify the process non-conformances.
[The table is mentioned in the assignment sheet]
Assignment Problem 3: (CLO4, 5 Marks)
In an experiment conducted to understand the effects of percentage moisture and percentage clay on the compatibility of sand, a quality characteristic, the following results
were obtained. Analyze the process and measurement system capability by calculating the effect of each factor and their interaction.
Moisture
3% 6%
Clay 1% 48,44 56,50
3% 42,46 52,49
Note:
a) Clay is Factor A and Moisture is Factor B
b) There are two data points in each quadrant, each is separated by a comma.
Assignment Problem 4: (CLO5, 5 Marks)
A company is trying to identify the average spend by the customer in its discount store. A single sample is selected every hour and average spend is noted. The process
of calculation is automatic through the application developed. Develop exponentially weighted moving average control chart for monitoring spend variability, with
a) 𝜆=0.3 and L=3
b) 𝜆=0.2 and L=2.7
c) 𝜆=0.3 and L=4
d) 𝜆=0.2 and L=2
e) 𝜆=0.2 and L=3
Calculate 𝜇଴
(Mean) and 𝜎 (Standard Deviation).
[The table is mentioned in the assignment sheet]
Statistical Quality Control Assignment Rubrics
Course Learning Outcomes Excellent Students Marks Faculty Comments
Assignment Problem 1: (CLO2, 5 Marks)
A packing organization monitoring the performance of a
packing machine, each container should weigh 35 lb., during
Measure phase, project team performed the process
capability study and observed the following data with 12 sets
of container weights of sample size 4. Construct the R and
𝑥̅chart of process quality improvement and identify the
process variability.
[The table is mentioned in the assignment sheet]
Student will be able to (SWAT) construct the following for a
specific scenario: Centre Line (CL), Upper Control Line (UCL),
and Lower Control Line (LCL) to accurately compute the data
from the constants table (2 marks); R and XBar chart based on
statistical formulas (2 marks); and provide the process
variability (1 Mark)
Assignment Problem 2: (CLO3, 5 Marks)
When examining time-series data, what we want to occur is
the most appropriate action or non-action. However, the
conclusion of what action or non-action to take can be a
function of how the data are examined. This point will be
illustrated using the data in Table, which provides the number
of daily non-conformances that occur from the number of
daily transactions that occur; i.e., 10,000. These data could
describe the number of daily non-conformances from an
insurance company operating in UAE. Implement the p and
c control charts for variables and attributes and identify the
process non-conformances.
[The table is mentioned in the assignment sheet]
Student will be able to (SWAT) implement the p and c chart to
identify the defaults for the given scenario: Centre Line (CL),
Upper Control Line (UCL), and Lower Control Line (LCL)
(2 marks); p and c chart based on statistical formulas
(2 marks); and provide the process variability (1 Mark)
Assignment Problem 3: (CLO4, 5 Marks)
In an experiment conducted to understand the effects of
percentage moisture and percentage clay on the
compatibility of sand, a quality characteristic, the following
results were obtained. Analyze the process and
measurement system capability by calculating the effect of
each factor and their interaction.
Student will be able to (SWAT) to analyze the design of
experiment (DoE) for the given two factors (effects of
percentage moisture and percentage clay) (2 Marks) to
compute the main and combined factors (2 Marks) and process
the analysis based on minimization (1 Mark)
Moisture
3% 6%
Clay 1% 48,44 56,50
3% 42,46 52,49
Note:
a) Clay is Factor A and Moisture is Factor B
b) There are two data points in each quadrant, each is
separated by a comma.
Assignment Problem 4: (CLO5, 5 Marks)
A company is trying to identify the average spend by the
customer in its discount store. A single sample is selected
every hour and average spend is noted. The process of
calculation is automatic through the application developed.
Develop exponentially weighted moving average control
chart for monitoring spend variability, with
a) 𝜆=0.3 and L=3
b) 𝜆=0.2 and L=2.7
c) 𝜆=0.3 and L=4
d) 𝜆=0.2 and L=2
e) 𝜆=0.2 and L=3
Calculate 𝜇଴
(Mean) and 𝜎 (Standard Deviation).
[The table is mentioned in the assignment sheet]
Student will be able to (SWAT) develop the exponential
weighted moving average chart for the given scenario by
computing the EWMA average for each row (2 Marks), identify
the control limits for upper control limit (UCL), and lower control
limit (LCL) (2 Marks) and provide the process variability (1
Mark)