Continuous Data – Equipment Error

Continuous Data – Equipment Error

In case we have continuous data, we have separate tests to check for Equipment Error/Variation and Operator Error/Variation.

Equipment Error

To check for the Error in the measurement contributed by the Equipment, we conduct “Test Retest”.

                In Test-Retest we check the Equipment for its Accuracy and Precision.

Accuracy

The concept of Accuracy says that the Data Points are close to the Target.

To check Accuracy, we calculate the BIAS of the Equipment (i.e. the difference/distance of the Mean from the Target/True Value).

BIAS = TARGET – AVERAGE

Ideally, the BIAS in the Measurement System (Equipment) should be ZERO/Close to ZERO.

Accuracy

Understanding Accuracy or precision is not easy when everything is theory. Advance Innovation understands this and that’s why the Six Sigma training in Delhi is full of examples. To make the understanding clear of Accuracy we have quoted an example below.

Example: In a Filling Plant of300 ml. Pepsi Bottles, the Quality Engineer wants to check if the machine filling Pepsi in bottles is accurate or not, for that, he takes 20 bottles as Sample and manually measures the volume of Pepsi in each bottle. The data is as below:

Bottle No.	Quantity (ml)
1	310
2	305
3	298
4	299
5	295
6	307
7	308
8	305
9	299
10	298
11	309
12	300
13	308
14	306
15	305
16	297
17	299
18	298
19	305
20	309

Using the data, he calculates the Average volume of Pepsi per bottle that he founds to be 303 ml.

The Target volume per bottle was 300 ml.

Now, BIAS = Target – Average

BIAS = 300 – 303

BIAS = -3 ml

As, we can see, the measurement system/equipment is Biased, due to this biasness, the organization is losing 3 ml. Pepsi per bottle, here, the organization will need to decide whether they can live with it or not.

Precision

The concept of Precision says that the Data Points are close to Each other.

To check Precision, we calculate the Standard Deviation of the measurement result and compare it with the Equipment tolerance (which is already present with the equipment, provided by the manufacturer).

In precision, we check if the Thumb Rule is validated or not.

RULE:     

“If Standard Deviation< (1/10)^th of the equipment tolerance, then the equipment is said to be Precise.”

Example: Lets say, in the above example, the QC also calculates the Std Dev. Of the measurement result, which he founds to be 4.83 ml.

The Tolerance of the Equipment was +/- 2 ml. which makes the Tolerance as 4 ml.

(Tolerance = Upper Limit – Lower Limit)

So, (1/10)th of the Tolerance will be .4 ml.

Hence, the Std. Dev. (4.83 ml.) is more than 1/10^th of the tolerance and thus we can conclude that the Measurement System/Equipment is Not Precise.

Precision

NOTE: An Ideal Data is the data that’s both Accurate as well as Precise, so we try to ensure that the data points are close to the target and the variation between the data points is minimum.