Duration

2 days

Course Description

A Workshop that focused on the Implementation of Effective and Efficient application of Statistical process control to improve productivity and quality of production process. A clear and detailed implementation plan will be set up to ensure the proper implementation and the value of SPC application. Continuous Improvement element in SPC application is fully emphasized in this training. This training also fulfils the SPC implementation requirement under the IATF16949:2016 quality system

General overview of Process variation by various definition such as engineering, Dr. Shewhart and Dr Deming.
Process Variation – Sources and definition
Application of Statistics in Process Control.
Definition of various process states – Ideal, Threshold, Brink of Chaos and Chaos state.
Data analysis and behavior for Statistical Control Process. – Definition and application.
Benefit of using control charts to control process performance and stability.
Exercise: Definition of data behavior using statistical methods, Normal probability plots for data from production and analysis.
Measurement of Location and Dispersion. Calculation and Interpretation. Normal Distribution theory.
Simple explanation on Mean and Standard Deviation.
Formula for Mean and Standard Deviation and their implications.
Presentation of data using Histogram, Box & Stem plot, Normal Probability Plot etc.
Definition and meaning of normal distribution application in process control.
Meaning of capable process using +/- 3 sigma process variation definition.
Meaning of out of control and reasons for triggering countermeasures.
Exercise: Simple calculation of mean and standard deviation from selected process data and their associated interpretation.
Truth of process control.
Definition of Process Input and Process Output.

Mapping the process Input and Linkage to output.

Tools to study the relationship between Process Input and Output.
Workshop: Develop your process mapping from a selected process.
Determine the right product characteristics to control process.
How to select the appropriate product characteristics to control process performance?
Factors affecting the selection.
Workshop: Develop list of process or product output characteristics and input parameters to be controlled in your selected process.
Appropriate Approach to set up an effective control charts with practical application.
Determine data normality
Process characterization studies
Computation & Reports of Ppk & Cpk.
Develop the first control chart
Continuous monitoring the process using control chart.
Shewhart's Control charts -- basic understanding and reasons.
X-bar R chart definition and application.
X-MR chart definition and application.
Reasons for using X-bar R and X-MR charts. When to use X-bar R and X-MR charts
Exercise: Plotting of X-bar R and X-MR charts using sample data.
Control charts for attribute data (counts)
Definition and application of Np, p and c charts.
Reasons for using the above charts.
Exercise: Plotting of Np, p and c charts based on sample data provided.
Analysis of control charts with reference to abnormal patterns.
What are abnormal patterns as defined by IATF16949:2016 requirements?
669 or 777 rules application
Why we need to act upon abnormal patterns?
Possible reasons for abnormal patterns based on process 4Ms.
Corrective and Preventive actions for abnormal patterns documentation.
Exercise: Identify abnormal patterns from your actual process data charts and sample charts provided.
Continuous improvement through control charts application
Computation and definition of process capability indices Cp, Cpk, Pp and Ppk.
Implication of process capability indices in relation to failure rate and ppm.
Exercise: Computation of Cp, Cpk based on sample data and control charts given.
Implementation requirement according to IATF16949:2016.
Basic rules for TS16949 requirements regarding SPC application.
Implementation plan for Effective SPC application in your factory.
Flow chart for SPC chart selection and implementation.
Management review process for SPC implementation.
Matrix for SPC implementation
Roles and responsibilities of different categories of employees.
Exercise: Develop your own SPC implementation plan.
Questions and Answers.

LEARNING GOALS

To Establish the basic understanding of Control charts so that to set up a proper control chart implementation system.
To set up an effective process control for quality assurance.
To apply SPC to ensure proactive process control and triggering process abnormality in early state.
To analyze the SPC data with the correct approach and method.
To understand the benefits of SPC application in production process.
To fully aware of criticality and importance of process control in product quality assurance.

METHODOLOGY

This course will be conducted in the form of lecture and group discussion in an informal manner. Participants will be involved in exercises and real life practices through out the course. Participants need to do some exercises which will be extracted from their daily line practices.

OBJECTIVES

After Attending the training, participants should be able to :

Understand and classified types of variation in practical situation.
Realize the benefit of using SPC in process performance monitoring.
Analyze process data in statistical approach
Applied statistical process control charts in monitoring production process.
Stratified process variation to it's sources and address them with appropriate corrective actions.
Setting various type of process control charts (for both variable and attribute data) for the appropriate application
Evaluating process capability using control charts.
Setting up an effective SPC implementation procedures and systems for your company

Programme scope, delivery arrangements and suitability are confirmed during enquiry.

SPC (Statistical Process Control) Implementation Procedures