STATISTICAL PROCESS CONTROL (SPC) :

Hello friends, Today, we are talking about SPC.

Topics that we are covering today:

INTRODUCTION
BASIC TERMS OF STATISTICAL PROCESS CONTROL
VARIABILITY: TYPES OF CAUSES
QUALITY MEASURES : TYPES OF DATA THAT USE IN SPC TERM
CONTROL CHART

So friends lets start without wasting time.

INTRODUCTION:

SPC means Statistical process control. It means that we control and monitor our process based on data.
From the data, we find out what are the trends of our process and how many variations in the process or where is going our process. It is monitored and if any defect is being generating in it then identify their causes and try to improve the process.

Definition:

Statistical process control (SPC) is a scientific visual method which is used to monitoring and controlling the manufacturing processes by eliminating variations of special causes to improve the quality.

BASIC TERMS OF SPC:

1. Statistical process control:

In this, we monitor the production process to detect and prevent poor quality.

2. Sample:

A single item which is taken from a lot of items for inspection to know that the lot is acceptable or not.

Control chart:

Process is within statistical control limits.

VARIABILITY:

There are two causes of variation in any process.
1. Random causes
2. Non Random causes

1. Random causes:

It includes common causes.

Common causes are inherent in process and generally are not controllable by process operator. For example: variation in raw material, Variation in ambient temperature and humidity.
It can be eliminated only through improvements in the tools or system.

2. Non Random causes:

It includes special causes.

It clearly identified what the cause of defect generation.
It can be modified through operator or help of management team action.
For example: tool wear, gross changes in raw materials, and broken equipment. Sometimes, it is also called assignable causes.

QUALITY MEASURES:

There are 2 types of data :

1. Attribute

2. Variable

1. Attribute:

This type of product characteristics that can be evaluated with a discrete response.

E.g. Yes - No, Good - Bad etc.

2. Variable:

This type of product characteristics that can be measures.

E.g. Weight - Length

CONTROL CHART:

The control chart is a graph in which the control limits are defined. Control limits are the upper limit and lower limit.

Process control chart

The process control chart is shown in pic.

In this, number of samples are showing which is from 1 to 10. The lower control limit and upper control limit are shown which is the lower specification and upper specification and a centerline is the mean or also called as a target line. The process must be at the target line or around it.

In this, all the points are around the target line but the second last point is outside the upper control limit. Where the point has gone beyond the upper limit, this means that there will be generate defects in the process.

Similarly, we are able to monitor the data with the help of control chart. We can also detect & control the defects in the process.

Below points are shown that process is under control:

A process is in control if:

The points of reading of the sample will not be outside the control limit.
Most points will be near the target or average line.
There should be equal number of points in the above and below the center line.
The number of points should be appear randomly distributed.

TYPES OF CONTROL CHART:

1. Attribute control chart

p chart
np chart
c and u chart

2. Variable control chart

Range (R- chart)
Mean (x- bar chart)

1. Attribute control chart:

Attributes control charts are used for discrete or count the data. There are several scenarios where the classification of measurements in only one category has quality characteristics of interest. Those variable that are defined as