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MICROCREDENTIAL

Statistical Process Control

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$1,990.00

START DATE

 Enquire now

MODE

 Mixed (online and in-person)

DURATION

 8 wks

COMMITMENT

 Avg 5 hrs/wk

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Gain foundational knowledge of statistical process control and harness this crucial set of tools, techniques and approaches for quality management and continuous improvement in industrial enterprise.

About this microcredential

Statistical Process Control (SPC) is vital for ensuring quality control, particularly in high-stakes industries where product failure can have significant repercussions, such as defence forces. With the Australian government's emphasis on bolstering local defence capabilities for example, suppliers are required to adhere to stringent quality certifications. SPC training equips manufacturers with crucial ISO 9001 and AS9100 certifications, which are essential for participation in defence supply chains. 

This microcredential provides you with comprehensive training in managing quality, cost, and schedule in advanced manufacturing, aligning with rigorous industry standards. It will enable you to explore specific elements of statistical process control with particular focus on appropriate selection of control charts, sampling size, techniques and process capability. You will be guided through industry-relevant examples, case studies and project activities, providing you with the necessary skills to meet industry standards and drive success effectively.

Key benefits of this microcredential

This microcredential has been designed to equip you with:

  • Skills to interpret and appropriately apply common SPC tools
  • Knowledge of applicable data collection, analysis and interpretation
  • Abilities to develop targeted SPC investigation and response strategies.

This microcredential aligns with the 2-credit point subject,  Statistical Process Control (42143) in a number of postgraduate offerings. For the full list of courses, see "Microcredential subject alignment" below in the "Additional course information" section.

This microcredential may qualify for recognition of prior learning at this and other institutions.

Digital badge and certificate digital badge example for UTS Open short courses

A digital badge and certificate will be awarded upon successful completion of the relevant assessment requirements and attainment of learning outcomes of the microcredential.  

Learn more about UTS Open digital badges.

Who should do this microcredential?

This microcredential is targeted at business representatives across different sectors including engineering, manufacturing, maintenance and production who are seeking to introduce data driven quality tools, particularly with lean manufacturing into their operations to enhance efficiency and productivity. This includes, but is not limited to:

  • Operation executives
  • Engineers
  • Operation managers
  • Maintenance managers
  • Anyone responsible for quality and efficiency in the production line.

Price

Full price: $1,990 (GST-free)*

*Price subject to change. Please check price at time of purchase.

Enrolment conditions

Course purchase is subject to UTS Open Terms and Conditions. 

COVID-19 response 

UTS complies with latest Government health advice. Delivery of all courses complies with the UTS response to COVID-19.

Additional course information

Course outline

The following content will be covered in this microcredential:

Module 1: Introduction to statistical process control

  • Introduction to statistical process control as cornerstone for quality planning in industrial organisations
  • Definition of quality including quality requirements and cost

Module 2: Process variability

  • Understanding and decision making around process variability
  • Process capability and key statistics
  • Interpreting capability indices

Module 3: Process control

  • Key elements to design a control system
  • Control charts and control limits

Module 4: Statistical process control and charts

  • Mean and range charts, charts for individuals
  • Median, mid-range and multi-varied charts
  • Moving mean, moving range and exponentially weighted moving average (EWMA) charts

Module 5: Statistical Process Control and Charts for Standard Deviation

  • Statistical process control and charts for standard deviation
  • Process control by attributes (np charts and p-charts, c-charts, u-charts)
  • The use of control chart and process capability data.  

Course learning objectives

Upon successful completion of this microcredential, participants should be able to: 

  • Interpret and appropriately apply common Statistical Process Control (SPC) tools
  • Demonstrate applicable data collection, analysis and interpretation
  • Develop targeted SPC investigation and response strategies.  

Assessment

Participants will be required to successfully interpret the current state of a target production system and to develop a Statistical Process Control (SPC) investigation with appropriate communication response strategies. This investigation will need to demonstrate data collection, analysis and interpretation skills developed throughout the course, which are then applied to the context of the chosen production system. 

Requirements

Mandatory

  • To complete this online course, you will need a personal computer with adequate internet access and sufficient software and bandwidth to support web conferencing. You will also require an operating system with a web browser compatible with Canvas, Zoom and Microsoft Teams.

Microcredential subject alignment

This microcredential aligns with the 2-credit point subject, Statistical Process Control (42143) in the following postgraduate offerings:

Contact us

For any questions on enrolment or payment, please contact UTS Open Support at  support@open.uts.edu.au  

For any questions about course content, delivery, or progression, please contact the The Faculty of Engineering and IT at FEITshortcourses@uts.edu.au

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Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.

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