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23 Days 8 Hrs
TIMEZONES
UK
SECTOR
Core Tools, Automotive
DELIVERY OPTIONS
In Person- Online
In PersonINTRODUCTION TO THIS COURSE
Statistical Process Control, (SPC), is a method for gaining an understanding of the types of variation within a process and hence guide actions to either control or reduce this variation. It is used in many industrial sectors such as automotive, aerospace, renewable energy and mobile power generation.
INDIVIDUALS
TRAINED
COUNTRIES ACROSS
5 CONTINENTS
SPECIALIST CONSULTANTS
AND TRAINERS
CONSULTANCY
PROGRAMMES DELIVERED
Description
SPC is module three of the Core Tools Certification. This module can be completed as a standalone course or part of the full Core Tools Certification Training. The full Core Tools Certification is achieved by completing all 5 modules of Core Tools Certification Training (APQP, Control Plan, FMEA, SPC, MSA and PPAP) and upon successful completion of the exam. Modules can either be taken as consecutive days (which can be booked here) or individually.
More information about the contents of each module and SMMT Quality Management’s upcoming module dates can be found here:
Advanced Product Quality Planning (APQP) and Control Plan Training
Failure Mode and Effects Analysis (FMEA) Training
Measurement Systems Analysis (MSA) Training
Production Part Approval Process (PPAP) Training
Please note: The statistical techniques used during the Measurement Systems Analysis course are covered in detail in our 1-day Statistical Process Control (SPC) programme. Therefore, we strongly recommend that you attend our SPC course before attending an MSA course unless you are already familiar with the statistical tools used.
Who should attend?
This course is designed for Management Representatives, Implementation Teams, Internal Auditors and others who are involved in the auditing or implementation of Statistical Process Control (SPC).
Familiarity with basic statistical concepts would be beneficial but not necessary.
Course Outline
- Overview of SPC
- Concepts of process variation
- Understanding Common and Special cause variation
- Charting for Variable data
- Charting for Attribute data
- Control limits
- Capability calculation
Benefits and Learning Objectives
SPC can be used to understand the types of variation present within manufacturing process. By understanding the types of variation present actions can be taken either to eliminate the variation or reduce its impact. If the variation is excessive the process can be stopped to avoid making nonconforming product.
It is often mandated by automotive, aerospace and other engineering primary manufacturers as a specific requirement to support the management of critical product or process characteristics. Companies that apply SPC successfully, see improved product quality, on time delivery performance and reduction in the cost of non-quality.
Delegates will become competent in implementing, undertaking and auditing Statistical Process Control concepts including variable and attribute studies.
SPC can be used to understand the types of variation present within manufacturing process. By understanding the types of variation present actions can be taken either to eliminate the variation or reduce its impact. If the variation is excessive the process can be stopped to avoid making nonconforming product.
It is often mandated by automotive, aerospace and other engineering primary manufacturers as a specific requirement to support the management of critical product or process characteristics. Companies that apply SPC successfully, see improved product quality, on time delivery performance and reduction in the cost of non-quality.
Delegates will become competent in implementing, undertaking and auditing Statistical Process Control concepts including variable and attribute studies.
Certification
Upon completion of the course you will receive an SMMT Quality Management certificate of attendance.
COURSE AVAILABILITY
Browse upcoming course dates and locations below. Courses are available online and at selected UK locations, with flexible options to suit your schedule.
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