This course is specifically developed to provide participants in the food industry the basic statistical techniques for process control and improvement. Participants will gain knowledge of the basic fundamentals of process improvement, concept of variation, statistical process control and other simple but powerful statistical techniques.
This course should be attended by managers and engineers from process, research and development, quality and production. Managers, engineers and personnel from IT, maintenance and purchasing will also find this course relevant to their job function.
Duration – 2 days
Software – Minitab
- In-depth understanding of the concepts underlying SPC.
- Examine necessary steps in implementing SPC methods in your company.
- Ability to determine the capability of products and processes.
- Knowledge of process characterisation, control and improvement flow.
Statistical Process Control (SPC)
Fundamentals of Process Improvement
- Concept of Loss
- Definitions of Statistics, Process, Control
- Two approaches to Variation
- Stable versus Unstable Process/Common versus Special Causes
- Four States of a Process
Deriving Information from Data
- Measures of Location: Mean and Median
- Measures of Dispersion: Range and Standard Deviation
- Normal Distribution
- Behavior of Sample Means
Introduction to Control Charts
- Concept Underlying Control Charts
- Basic Variables Control charts; Xbar-R, Xbar-S, I-MR
- Chart Critique and Interpretation
- Characteristics of an Effective Control Chart
Using Attribute Data Effectively
- Control Charts for Binomial and Poisson Count
- Characteristics of Attribute Data
- Definitions of Capability Indices (Cp, Cpk, Pp, Ppk) for Variables Data
- Uses and Abuses of Capability Indices
- Capability of Attribute Data
- SPC Implementation Guidance