Work Measurement

This module can be used for the three major areas of work measurement - time study, computation of sample size for time study and work sampling

Time Study

A sample screen that includes the data appears next. Our process consists of three elements and we have taken 5 observations of each.

Data

Performance rating. For each element its performance rating must be given. The normal time will be computed as the average time multiplied by the performance rating.

Observations. The time observed for each element must be entered. In some cases, observations will be bad (outliers). In order to exclude them from computations enter a 0 as in the case of observation 2 for element 2.

Allowance factor. The overall allowance factor is given. This allowance factor adjusts the final time for the sum of all three normal times.

Solution

The solution screen for our example appears below.

Average. The average for each element is computed. Notice that the average for elements 1 and 3 are taken over 5 values but that the average for element 2 is taken over 4 values since observation 2 was given as 0 and this is not included in the averaging process.

Standard deviation. The standard deviation for each element is computed although it is not used for any further computations in this submodel .

Normal time. The normal time is computed by multiplying the average of the observations by the performance rating for that element.

Normal processing time. The normal processing time is the sum of the normal times.

Standard time. The standard time is computed in one of two ways depending on the textbook. Some authors use

standard time = normal processing time * (1 + allowance factor)

while others use

standard time = normal processing time /(1 - allowance factor)

If you are using a Prentice-Hall textbook then the appropriate formula should be in use. If not, please check Help, User information to be certain that the software is listed as using the correct textbook.

Example 2 - Computing the sample size

We present the data for our second example below.

The input is similar to the time study above but the goal is different. We want to find the minimum sample size to be 99.45% confident of our results. The input for this submodel is as follows.

Accuracy level. Within what percentage do we want our results to hold? For example, for element 2 we want to be 95.45% confident that our results are within 1% of the true time.

Observations. This is the same as above. The time observed for each element must be entered. In some cases, observations will be bad (outliers). In order to exclude them from computations enter a 0 as in the case of observation 2 for element 2.

Confidence. Six options about the confidence level are presented in the drop down box above the data.

The output appears below. The sample sizes for the three elements are 20, 297 and 3 respectively. Generally this means that we use the largest and have 297 observations of each element.

Example 3 - Work Sampling

An example of both the input and output for work sampling appears below.

Proportion. This is the estimated proportion of time being spent in the task.

Accuracy level. This is similar to the accuracy level above. Within what percentage do we want our results to hold? For example, we want to be 99.73% confident that our results are within 5% of the true proportion.

Confidence. Six options about the confidence level are presented in the drop down box above the data

The result is simply the sample size. In this case we must sample 756 time units.