MPXM2102AS datasheet(20/670 Pages) MOTOROLA

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Motorola Sensor Device Data

www.motorola.com/semiconductors

Figure 2. Impact of Assignable Causes on

Process Predictable

Figure 3. Difference Between Process

Control and Process Capability

Process “under control” – all assignable causes are

removed and future distribution is predictable.

PREDICTION

TIME

SIZE

TIME

PREDICTION

SIZE

TIME

Out of control

(assignable causes present)

In control assignable

causes eliminated

SIZE

TIME

In control but not capable

(variation from random variability

excessive)

Lower

Specification Limit

Upper

Specification Limit

In control and capable

(variation from random

variability reduced)

At Motorola, for critical parameters, the process capability

is acceptable with a Cpk = 1.33. The desired process

capability is a Cpk = 2 and the ideal is a Cpk = 5. Cpk, by

definition, shows where the current production process fits

with relationship to the specification limits. Off center

distributions or excessive process variability will result in less

than optimum conditions

SPC IMPLEMENTATION AND USE

DMTG uses many parameters that show conformance to

specification. Some parameters are sensitive to process

variations while others remain constant for a given product

line. Often, specific parameters are influenced when

changes to other parameters occur. It is both impractical and

unnecessary to monitor all parameters using SPC methods.

Only critical parameters that are sensitive to process

variability are chosen for SPC monitoring. The process steps

affecting these critical parameters must be identified also. It

is equally important to find a measurement in these process

steps that correlates with product performance. This is

called a critical process parameter.

Once the critical process parameters are selected, a

sample plan must be determined. The samples used for

measurement are organized into RATIONAL SUBGROUPS

of approximately 2 to 5 pieces. The subgroup size should be

such that variation among the samples within the subgroup

remain small. All samples must come from the same source

e.g., the same mold press operator, etc.. Subgroup data

should be collected at appropriate time intervals to detect

variations in the process. As the process begins to show

improved stability, the interval may be increased. The data

collected must be carefully documented and maintained for

later correlation. Examples of common documentation

entries would include operator, machine, time, settings,

product type, etc.

Once the plan is established, data collection may begin.

The data collected will generate X and R values that are

plotted with respect to time.

X refers to the mean of the

values within a given subgroup, while R is the range or

greatest value minus least value. When approximately 20 or

more X and R values have been generated, the average of

these values is computed as follows:

= (

2 +3 + ...)/K

R = (R1 + R2 + R3 + ...)/K

where K = the number of subgroups measured.

The values of X and R

are used to create the process

control chart. Control charts are the primary SPC tool used

to signal a problem. Shown in Figure 4, process control

charts show X and R values with respect to time and

concerning reference to upper and lower control limit values.

Control limits are computed as follows:

R upper control limit

+ UCL

R +

D4 R

R lower control limit

+ LCL

R +

D3 R

X upper control limit

+ UCL

X + X )

A2 R

X lower control limit

+ LCL

X + X *

A2 R

Freescale Semiconductor, Inc.

For More Information On This Product,

Go to: www.freescale.com

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