As well as being one of the core components of the Six Sigma approach, Statistical Process Control (SPC) is also a key element of ISO/TS16949, where it is required to be used within the Product Realisation process.
Many problems encountered with Statistical Process Control (SPC) and Design of Experiments (DOE) are caused by problems with measurement systems where the process of obtaining measurements and data may have variation and produce defects.
SPC is an optimisation philosophy concerned with continuous process improvement, using a collection of (statistical) tools for data and process analysis making inferences about process behaviour. SPC is a key component of Total Quality initiatives and ultimately SPC seeks to maximise profit by improving product quality, improving productivity, streamlining process, reducing wastage and reducing variation
- The existence and measurement of variation
- Concepts
- Variation
- Data tables, histograms and run charts
- Normal Distribution
- Accuracy and Precision
- Measures of variation (mean, mode, median, range, standard deviation and variance)
- Understanding and Managing Variation
- Common and special causes
- Taking appropriate action on common and special causes
- Process improvement methodology
- Reacting to special causes
- Statistical Control, what it is and the advantages of processes being in control vs tampering with the process
- Role of Control Charts
- Role, uses and definition of control charts
- Types of Control Charts
- X-Range Charts
- Use of Charts
- Preparation and use of control charts
- Examples
- Measures of variation (mean, mode, median, range, standard deviation and variance)
- Attributes Charts
- c, p, np and u charts (overview)
- Examples
- Capability Analysis
- Process capability
- Performing a process capability study
Additional Core Tools relating to the Automotive industry include: Advanced Product Quality Planning (APQP) and Production Part Approval Process (PPAP); Failure Mode & Effects Analysis (FMEA); Measurement Systems Analysis (MSA)
- Personnel involved in manufacturing, quality, inspection, design/process engineering.
- Those who are required to develop and interpret control charts.
- Generate, utilise and interpret a variety of Control Charts (Xbar/R, S & Attribute).
- Perform a capability study and determine process capability indices (Cp, Cpk, Pp and Ppk).
- Interpret the results in the context of the process variation and product acceptance criteria.