Statistical Quality Control

A review of data handling (types of data, variation, randomness, sampling, frequency distributions, histograms, time series, summary statistics, etc.) is intended to bring all students up to an acceptable level of interaction with data analysis.

• Concept of probability. Probability rules. Probability distributions - hypergeometric, binomial, geometric, Poisson, exponential, normal. Probability plots. Confidence intervals. Concept of expectation. Central limit theorem.
• Acceptance sampling. Single sampling plans: Acceptable Quality Level, Producer's Risk, Limiting Quality, Consumer's Risk, Operating Characteristic, Rectifying Inspection, Average Outgoing Quality, Average Outgoing Quality Limit, Average Total Inspection. Double sampling plans: Operating Characteristic, Average Sample Number.
• Control charts: X bar and range charts for variables, p charts and c charts for attributes, discussion of CUSUM control charts and time weighted charts. Decision rules are introduced and examined. Opportunities are given to decide, use, and select a suitable type of chart, and to construct and use the chart. Average Run Length.
• Capability indices (Cp index and Cpk index): their calculation, interpretation, and limitations.
• Design of experiments (hypothesis testing): t tests, chi squared test.
• Metrology: Identify the importance of measurement, relationship between standards and measurement in a quality process, identification of quality characteristics of a product or service, effect of instrument characteristics on measurement results, GR&R studies.
• Six Sigma approaches will be discussed, with examples.

This module will develop a range of graduate attributes, including numeracy skills, problem formulation, problem-solving skills, and the ability to present a clear argument. 

This module has been reviewed and updated, taking cognisance of the University’s Curriculum Framework principles.  Examples of this are found within the module such as active and engaging tutorial activity with contemporary industry examples of modular content, module assessment which reflects industry activities, learning synergies across modules and levels of study and recorded lecture content supporting students to organise their own study time.

At the end of this module the student will be able to:

• select, describe and critically use the main concepts and practices of statistics as the science of collecting analyzing and presenting data.
• create and implement suitable acceptance sampling schemes for given guarantees and evaluate the benefits gained from Single and Double sampling.
• select and employ the common tools found in statistical quality control and demonstrate a critical awareness in their use and limitations.
• examine, discuss and debate the importance of metrology and standards in quality issues.
• select and justify strategies for quality improvement and participate in the debate of benefits etc. of chosen strategies.

  This is an SCQF Level 11 module, and upon successful completion, participants will be awarded 20 credits.

 

Delivery 

This module will last for 12 weeks, planned for Tuesdays 9am to 12pm.  

 

Course presenter

This module will be delivered by Dr Farhad Anvari.

 

Funding

This course may be available on a fully funded basis to some delegates.  Further details, including regarding eligibility, are available under Funding Support.

If you have any questions, please contact us at cpd@uws.ac.uk.

 

NOTE: This is a university module and upon approval of your application, you will be invited to register and then supported to complete enrolment. To enrol on the university system, the first step involves security set-up using the Microsoft Authenticator app; you will need to ensure that you have a compatible smartphone.

Further information is available at the Student Information Portal.

To access this module via the CPD route, individuals should be ordinarily resident in Scotland.  If you do not meet this criteria, please enquire here.