Operations Management: SQC Discussion Questions & Answers

This assignment provides detailed answers to discussion questions related to statistical quality control (SQC) in operations management. It covers the three main categories of SQC: descriptive statistics, acceptance sampling, and statistical process control (SPC), explaining their differences and how they can be used together. The assignment also discusses the key differences between common and assignable causes of variation, providing examples. Furthermore, it describes quality control charts, their components (upper and lower control limits), and how to interpret them. Finally, the assignment explains the differences between x-bar and R-charts and their combined use in detecting variations in the mean and variability of a process. Desklib offers a wide array of solved assignments and past papers to aid students in their studies.

Running head: OPERATIONS MANAGEMENT
Operations Management
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1OPERATIONS MANAGEMENT
Table of Contents
Answer to Question 1......................................................................................................................2
Answer to Question 3......................................................................................................................2
Answer to Question 4......................................................................................................................2
Answer to Question 5......................................................................................................................3
References........................................................................................................................................4

2OPERATIONS MANAGEMENT
Answer to Question 1
The three main types of the Statistical quality tools are identified in form of “descriptive
statistics, acceptance sampling and statistical process control (SPC)”. Descriptive statistics is
able to include the measures such as “mean and range” for describing quality characteristics.
Acceptance sampling considers random samples for deciding the viability of a batch or lot. SPC
uses sample to verify the functionality of a process. Descriptive statistics tools can tell about the
quality characteristics, however not able to specify whether it is good or bad. Acceptance
sampling provides the rationale for the same decision which is applicable to a batch or lot. SPC
is able to track the process over time for ensuring proper functionality. The effective use of these
tools together is identified with frequently updating SPC to depict the quality problems from
beforehand. On completion of batch produced, the acceptance sampling is able to depict the
viability of selling to the customer (Goetsch and Davis 2014).
Answer to Question 3
The common causes of variations are represented from random reasons which cannot be
traced. Assignable causes on the other may be identified and eliminated before implementation
of the final procedure. Example of common causes of variations is depicted with soft drink bottle
available in grocery store. No two bottles are filled to the same level, there is always slight
variation. The example of common causes of variations in Assignable case is derived from poor
quality of raw materials. In such cases if the variation persists, it will create quality issues in
future (Nikitin and Dolan 2017).
Answer to Question 4
The samples of a product are plotted on control chart over time. The interpretation of the
chart can evaluate whether the variation is normal or abnormal. It is important to use the chart as
most products and service shows certain degree of variation. Control Chart is a diagram having a
centre line along with a lower and upper control limit (UCL and LCL). In general, the UCL is
equal to the sample mean along with three standard deviations. In case an observation is above
the UCL or below UCL, the process is depicted to be not in control. The chart plotted as per
normal distribution, considers 99.7% of the total plots will be within the three standard

3OPERATIONS MANAGEMENT
deviations of mean. In case the process is outside the range of three standard deviations then it is
considered to be out of control (Bayat, Westgard and Westgard 2017).
Answer to Question 5
The x-bar chart detects the variations in the mean, whereas R-chart can detect the
variability of the process. They are used together when a particular data set is variable in nature.
This signifies that the data can be collected using decimal point such as 12.35 ounces. Some of
the most common examples of the variables include “temperature, weight and height”.
The importance of x-bar chart and R-chart is discerned with the accurate representation
of data. At times the results need to be concluded as per output of both the charts. For instance, if
both the variations are out of control then it is not possible to interpret the process results.
However, if R-chart is in control then we may be able to interpret the x-chart (Hazen et al. 2014).

4OPERATIONS MANAGEMENT
References
Goetsch, D.L. and Davis, S.B., 2014. Quality management for organizational excellence. Upper
Saddle River, NJ: pearson.
Nikitin, A. and Dolan, S., 2017, June. Comparison of the Statistical Performance of Different
Pulsed Neutron Well Logging Tools for Oil Saturation Monitoring. In SPWLA 58th Annual
Logging Symposium. Society of Petrophysicists and Well-Log Analysts.
Bayat, H., Westgard, S.A. and Westgard, J.O., 2017. Planning Risk-Based Statistical Quality
Control Strategies: Graphical Tools to Support the New Clinical and Laboratory Standards
Institute C24-Ed4 Guidance. The Journal of Applied Laboratory Medicine: An AACC
Publication, 2(2), pp.211-221.
Hazen, B.T., Boone, C.A., Ezell, J.D. and Jones-Farmer, L.A., 2014. Data quality for data
science, predictive analytics, and big data in supply chain management: An introduction to the
problem and suggestions for research and applications. International Journal of Production
Economics, 154, pp.72-80.