Statistical Process Control (statistics for industry)

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This program is technically co-sponsored by IEEE SPS Malaysia Chapter.

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Dear Ladies and Gentlemen,

A one-day short course on “Statistical Process Control (statistics for industry)” is being organised by Center for Intelligent Signal and Imaging Research (CISIR)”.

 

The course brochure is attached herewith. Also, please refer to a short description of the course as follows:

“This short course introduces the principles and tools behind statistical process control (SPC) and monitoring. Monitoring and controlling the process ensures that it operates to, produce items that conform to specifications with minimum amount of waste. The tools of SPC can be applied to any process such as manufacturing, or any service related business, for which conformance can be measured. This short course will introduce the principles of SPC which include statistical thinking, understanding of variation and tools that are used to measure, identify, monitor and control variation.”

 

In addition, the course objectives include:

  1. To introduce the principles of SPC which include statistical thinking and the understanding of variability; both natural and abnormal.
  2. To introduce statistical tools that can measure natural variation and identify abnormal variation.
  3. To introduce and develop control charts as a tool for process monitoring and control.
  4. To introduce and develop capability and performance indices to measure the ability of the process to operate with specification limits.

 

The course has been organized according to the following schedule:

Day: 15th December 2016

Time: 9:00am to 4:30pm

Venue: Seminar Room 6, UTP

 

Course Instructors:

1) AP Dr Vijanth Sagayan Asirvadam,

2) AP Dr Sarat Chandra Dass,

3) Dr Mohana Sundaram Muthuvalu,

 

For course registration, please refer to the method as mentioned in the course brochure (attached herewith).

 

We have limited numbers of slots, and the participation fee is RM 100/- to RM 250/- per participant.

Thank you

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