Microsoft Office Tutorials and References
In Depth Information
Service Time Distributions are shown next to the Selection of Arrival Order table.
The table suggests that service times are distributed with 3 discrete outcomes—
20% best case or shortest service time, 60% most likely case, and 20% worse case
or longest service time. For the Oil Change service, the times are 20, 30, and 45
minutes, respectively, for the best, most likely, and worse case. This information
is also the type of subjective information that could be derived from an interview
with Wolfgang. The information gathering could be as simple as asking Wolfie to
make the following determination: “If we define Best Case occurring 20% of the
time, what value of oil change service time is appropriate for this case”. Similarly,
times for worse case and most likely can be determined. These estimates can be
quite accurate for a knowledgeable individual, but great care must be taken in the
process of eliciting these subjective values. The interviewer must make sure that the
interviewee is fully aware of what is meant by each question asked. There are many
excellent structured techniques that provide interviewers a process for arriving at
subjective values.
Finally, the Worker Assumptions relate to the employee policies that Inez will set
for the work force. As stated in Table 8.2, three mechanics, each in a single bay, pro-
vide service and it is assumed that they are available from 9:00 am to 7:00 pm (600
total minutes), with a one hour lunch break, four 15 minute breaks, and a changeover
from one auto to another requiring 10 minutes of set-up time. The first three times
are obviously a matter of workforce policy, but the set-up could be uncertain. This
could include, placing the auto into the bay, selection of appropriate tools, and any
number of other activities associated with the preparation for service of the next
auto available. Set-up might also be dependent on the worker, the type of service, or
other factors. It is possible that more experienced workers might require less set-up
time than less experienced workers. Given the variety for types of automobile ser-
vice, the total daily set-up time could be quite substantial, and this is time that Inez
might want to reduce through special tools and standardization of work.
We have assumed a deterministic time for set-up to simplify our model. Also note
that these numbers can be manually changed by the modeler to perform what-if or
sensitivity analysis . For example, what if we could introduce training or equipment
that might reduce set-up time significantly? We would want to know if the invest-
ment in the time reduction is worth the effort, or analyze competing technological
changes to determine their cost/benefit. Having all these parameters on a single
worksheet, the Brain , is beneficial to the modeler performing the analysis.
8.5.3 Building the Calculation Worksheet
Exhibit 8.18 provides a view of the calculation worksheet which simulates 250 days
of auto arrivals. We will use the 250 days of randomly selected arrivals, along with
their arrival order, to determine what autos the mechanics can service each day and
which services they will provide. The Calculation worksheet will be used to deter-
mine some of the fundamental calculations necessary for the model. As you can see
Search JabSto ::




Custom Search