What type of Inspection procedures are in use

Where in the process should inspection take place

How are variations in the process detected before they become defects

Every feature/part is inspected Disadvantages are: Very time consuming and expensive. repetitive nature can lead to inspectors losing

concentration resulting in human error e.g. Wrong measurements being made, failure to identify defects etc.

Normally only employed when: Failure of a component will result in significant risk of

injury/death Where fully automated inspection can be employed quickly

and cost effectively and their is little chance of error.

Close inspection of a randomly selected sample of materials or components from a batch.

Can be based on Variables: where a specific value/s can be measured and

recorded and can vary within prescribed tolerances e.g. Length, diameter, height etc.

Attributes: which are acceptable or unacceptable e.g. Colour, surface finish, size etc.(size is inspected by gauging with Go No-Go as apposed to specific using direct measuring equipment.

Decision whether to accept or reject the whole batch is based on mathematical statistical procedure using the results of this inspection.

This method is less time consuming however it does have certain risks for both the supplier and the consumer

The most simple form of sampling is taking a sample(n) from a batch and accepting or rejecting the batch depending on defects found.

If defects found are equal or less than agreed limit batch is accepted, if number exceeds agreed limit batch is rejected.

This can be shown graphically by plotting its Operating Characteristic (OC) curve

In an ideal situation this graph would have a straight line as shown opposite where all batches with 5% defects or less (Acceptance Quality Level) AQL are accepted and all with a higher level are rejected

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25

% b

atch

es a

ccep

ted

% Defective in the batch

Ideal OC curve for AQL = 5%

Ideal operating characteristics Loop curve

In practice this is never encountered as all processes have some degree of variability

The graph opposite shows a more typical OC curve where;

PAPD is the Process Average Percentage Defective, this usually coincides with the AQL, it is the percentage of defects produced when a process is considered to be operating at an acceptable level

LTPD is the Lot Tolerance Percentage Defective, this is the percentage of defects the customer would find unacceptable also know as consumer risk

AQL is based on type of defects e.g. Critical (failure results in persons at risk) Major (failure could seriously effect the

function of item) Minor (not likely to effect the function of

the product) Vendors can use this to rate suppliers

Typical Operating Characteristic Curve

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11Pr

obab

ility

of b

atch

es b

eing

acc

epte

d% Defectives in a batch

PAPD 3%

Producers risk (100% - 90% = 10%

AQL 3%

Consumers risk ( 15% )

LTPD 9%

Ideally inspection should take place at critical points in the production process to avoid further costly processes being carried out on already defective parts

Such points could be: Prior to setting up and performing costly machining

processes when a vital part is too small or large Prior to a point of no return where rectification is impossible

e.g. assembly of sealed parts Before costly operations such as plating are carried out Before painting which could mask defects Prior to a process where failure of a part could result in

costly damage to machinery

Consider a sample of 36 location pins selected randomly from a batch of 200.

The nominal diameter is 10mm , each pin is measured and the size and frequency is recorded on a histogram.

The frequency is plotted vertically and the size horizontally

The width of each bar is classified as the class interval

0

1

2

3

4

5

6

7

8

9

10

9.96 9.97 9.98 9.99 10 10.01 10.02 10.03 10.04Fr

eque

ncy

Diameter in mm

68%

95%

99.73%

Control charts are based on the principle of variability of a process following a normal distribution curve.

There are a number of methods of producing control charts based on this variability or dispersion such as range, mean deviation and standard deviation.

Each has its own advantages but Standard deviation is the most satisfactory for control charts

Standard deviation is the distance from the mid-point on a distribution curve where it starts to change direction and move horizontally as in chart opposite.

Wheel Diameter Frequency

115 mm 3

116 mm 7

117 mm 12

118 mm 20

119 mm 15

120 mm 8

121 mm 2

During production Sample batches are measured and the mean size is plotted on the graph this should remain between the UWL and LWL preferably around the normal size.

If they cross these lines then you need to consider making adjustment before they reach the UAL or LAL

If they cross the UAL or LAL the process is out of control and will start to make defective parts

In the chart opposite (bottom) the green line shows a gradual drift in size in a positive direction indicating tool wear over a period of time. The black line shows a gradual increase followed by a sharp increase going outside the UAL which shows a problem has occurred, possibly a broken tool