Intended learning outcomes: Present in detail a ball bearing as an example product. Describe the algorithm for estimation of the cost of a product (shown for three cost types). Explain the data flow of the cost-estimation algorithm.
Cost estimation for cost of goods manufactured is based on the master data. We can illustrate this using an example product, a ball bearing, according to Figure 16.2.1.1.
Fig. 16.2.1.1 A ball bearing as an example product.
The ball bearing (Item ID 83569) consists of two components, a ring (item ID 83593, a semifinished product manufactured in-house) and Uniflon (item ID 83607, a purchased raw material). The bill of material for the product thus has two positions. It is produced in two operations: cut Uniflon (position 250 at work center ID 907501, “manual production”) and press together (position 270 at work center ID 908301, “special pressing”). The routing sheet for the product thus contains two operations. In the case under consideration, there are other components, or operations. For the sake of simplicity, however, only these two components (respectively, these two operations) are listed here.
To obtain the costs per unit produced, we must either add together the costs for the entire batch and divide them by the batch size, or divide the setup load of each operation by the batch size.
To estimate the costs, we must then calculate the costs for each of the cost types in Section 16.1.4. For the sake of simplicity, the algorithm in Figure 16.2.1.2 uses only three cost types as illustrations.
Fig. 16.2.1.2 Algorithm for estimating the cost of a product (shown for three cost types).
Figure 16.2.1.3 shows the data flow of the cost-estimating algorithm described above.
Fig. 16.2.1.3 Algorithm for estimating the cost of a product.
The three steps outlined above are shown in the gray section. The spreadsheet section shows the item (first table with three objects) and work center (fourth table with two objects) business objects. The bill of material business object (second table) is divided into detailed logistics objects, specifically into bill-of-material positions corresponding to the components. The operations are shown for the routing sheet business object (third table). See also the detailed description of the object and entity classes in Sections 17.2.1 to 17.2.8, in particular the Figures 17.2.1.1 and 17.2.8.1. The arrows in Figure 16.2.1.3 indicate the sources and usage of the data in the individual calculations.
Course section 16.2: Subsections and their intended learning outcomes
16.2 Cost Estimation
Intended learning outcomes: Present an algorithm for cost estimation of goods manufactured. Produce a representation of the cost accumulation and an overview of the comprehensive calculation for a product line.
16.2.1 An Algorithm for Cost Estimation of Goods Manufactured
Intended learning outcomes: Present in detail a ball bearing as an example product. Describe the algorithm for estimation of the cost of a product (shown for three cost types). Explain the data flow of the cost-estimation algorithm.
16.2.2 Representation of the Cost Accumulation and Comprehensive Calculation for a Product Line
Intended learning outcomes: Explain a graphical representation of the cost accumulation for a product. Disclose how to proceed if the entire line of products has to be recalculated.
