Page 589 - Sensors and Control Systems in Manufacturing

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Cha p te r
Ele v e n

Because of the close interaction between internal cost accounting
and external financial reports, careful attention should be given to the
accounting systems and the supporting cost-accounting records.
11.4 Mathematical Methods for Planning and Control
The cost records described in the preceding sections provide the data
for more advanced mathematical methods of analyzing and planning
business operations. This section outlines briefly some that can be
used by many manufacturers:
• Dealing with uncertainty (probability)
• Capital budgeting analysis
• Inventory analysis (economical order quantities)
• Linear programming
• Project management
• Queuing
• Simulation

11.4.1 Dealing with Uncertainty
Business management always involves uncertainty. The manager is
never entirely sure what will happen in the future. This uncertainty is
of special concern in preparing budgets, establishing standard costs,
and analyzing budget variances, as well as other decision situations.
Uncertainty means that the actual events a manager must try to
predict or evaluate may take on any value within a reasonable range
of estimated values.
The most important concept in dealing with uncertainty is prob-
ability. Two kinds of probability exist and are discussed in the follow-
ing sections.
11.4.2 Objective Probability
Objective probability is a measure of the relative frequency of occurrence
of some past event. It can be illustrated by the example in Table 11.4.
Assume that a manager observes production, counts the number
of units produced, and tabulates the count according to the number
of direct-labor hours used for each unit. This has been accomplished
in columns (1) and (2) of Table 11.4. Column (3) indicates the expected
probability for each time classification—that is, the odds that each
unit will require the number of direct-labor hours. It is computed by
dividing the number of observations for each classification by the
total number of observations. For example, of the 1000 units whose
production was observed, 400 required 2.5 direct-labor hours per
unit. Thus, 2.5 direct-labor hours were needed for 4 out of 10 or 0.40
of the units (400 divided by 1000).