Statistical Process Control By Deepak Patidar What is

Statistical Process Control By Deepak Patidar

What is Statistics? ? It is a science of drawing inference by collecting samples, analyzing and predicting or taking decision on entire population

When do we need Statistics? ?

Need for Statistics ? ?

Why Statistics ? ?

Why do we need Statistics ? ?

Sampling

Measures Of Location

Measures Of Central Tendency

Measures Of Variability (Spread)

Philosophy of SPC

Goal Post Mentality

Taguchi Loss Function Curve

Measure of Quality

Product V/s Process Control

Common Cause V/S Special Cause

Local Action & Action on System

What is SPC? ?

Definition Of SPC

3 Important Elements Of Basic Statistics

Understanding Process Behavior

Process Control

How can we practically check stability of process?

Control Charts

What Is Control Chart?

Basic Chart Elements

Control chart formula

Basic Chart Elements

Control Chart Mechanics

Fundamental Control Chart

Preparatory Steps

X-Bar & R Chart Steps

Control Chart Principle

Control Chart Analysis

Special Cause Criteria

Individual and Moving Range Chart (X-MR)

X-MR Chart Steps

X-MR Chart

Phases Of SPC Study

Control Limit & Specification Limit

2 Common Mistakes

Calculating Capability

Concept of Cp & Cpk

Calculating Capability

Concept Of Cpk

Understanding Cp & Cpk

Exercise

Process Capability V/s Performance

Machine Capability

Machine Capability Study

Formula

Typical Mistakes In SPC

Typical Misconceptions - SPC

Desired level of Cpk

Cp V/s Pp, Cpk V/s Ppk Process Capability Process Performance Cpk is an index (a simple number) which measures how close a process is running to its specification limits, Process Performance Index basically tries to verify if the sample that you have generated from the process is capable to meet Customer CTQs (requirements). It helps in predicting the process It only shows the variation exists in the batch from which the samples were drawn Short Term Study Log Term Study It shows how the process will behave in future It shows how the process was in past Sigma in R-bar/d 2 Sigma is RMS It measures Within sub group variation only It measures within and between sub group variation Calculated only when the process is stable Can be calculated from short production run Variation is only due to common causes Variation is due to both special and common casues