Programmable Automation Technologies. Daniel Kandray
of production is manufacturing lead-time. Manufacturing lead-time is the total time it takes to convert raw material into a finished product. Thus, it is the summation of the time of each individual manufacturing process that the product passes through. Note, however, that a product is not processed continually. There is also non-operation time associated with each operation. Examples of non-operation times include those for moving and queuing of parts between operations, waiting for materials, waiting for tools, and so on. These must be accounted for in the calculation of manufacturing lead-time. Additionally, the time to set up the process, where appropriate, must also be considered. Accordingly, the equation for the manufacturing lead-time of a process manufacturing system consisting of operations (indexed by i) is
tmlt = sumi(tsu + Qtc + tnop)i,
where
| t mlt | = | manufacturing lead-time for batch |
| t su | = | setup time for a process |
| Q | = | number of parts in batch |
| t c | = | operational cycle time of a process |
| t nop | = | non-operation time of a process |
Note that this equation can be used for other types of manufacturing systems as well. However, some of the terms may be insignificant. Consider a quantity manufacturing system. The setup time and non-operation time may become very small compared to the batch size. Additionally, in the flow-line system the setup and non-operation time are essentially nonexistent.
Example 2.11
A part is routed through 4 machines in lot sizes of 500 parts/batch. Average non-operation time is 6 hr. Setup and operational cycle times are shown in the table below. Calculate the manufacturing lead-time for the part.
Solution
The governing equation is
tmlt = sumi(tsu + Qtc + tnop)i.
Calculate the manufacturing lead-time for each operation:
| t mlt1 | = | 1 hr/batch + (500 parts/batch)(3 min/part)(1 hr/60 min) + 6 hr/batch = 32 hr/batch |
| t mlt2 | = | 6 hr/batch + (500 parts/batch)(8 min/part)(1 hr/60 min + 6 hr/batch = 78.67 hr/batch |
| t mlt3 | = | 1.5 hr/batch + (500 parts)(4 min/part)(1 hr/60 min + 6 hr/batch = 40.83 hr/batch |
| t mlt4 | = | (4 hr/batch + 500 parts)(3 min/part)(1 hr/60 min) + 6 hr/batch = 35 hr/batch |
Summing operation lead-times gives
tmlt = tmlt1 + tmlt2 + tmlt3 + tmlt4 = 32 + 78.67 + 40.83 + 35 = 186.5 hr/batch.
It is relatively easy to visualize how improvements in productivity result in corresponding improvements in these measures. Therefore, such measures can also be used in making the case for automation.
2.4 Process Inputs and Manufacturing Costs
The previous section demonstrated how one would quantify the output of a process with a measure (production rate) that can be used in productivity calculations. In this section, methods of quantifying the input to the process are developed. As shown in Section 2.2, input into the productivity calculation (PI) is amount of money required for the process step under consideration, which is input into the process over the same time frame as that of the output measurement. Both measurements are in units of $/hr.
Inputs to a process are typically broken down into categories consisting of capital, energy, labor, and material. These categories are termed partial productivity measures. Consideration of a breakdown of the costs to manufacture a product is shown in Figure 2-2.
Figure 2-2 Manufacturing process expenses
Figure 2-2 is a pie chart showing the relative percentage of expenses that make up the final selling price of a representative product. Note that the manufacturing cost is only 40%. Figure 2-3 is a pie chart of the relative percentage of expenses that make up total manufacturing cost for this product. Notice how the categories in Figure 2-3 relate to the partial productivity measures. Direct labor coincides with labor, capital equipment costs with capital; indirect labor is often absorbed into the capital equipment or direct labor costs; materials and supplies category would represent both material and energy. When an automation project is undertaken, its goal is to decrease one or more of the expenses shown in the figure. Thus, these expenses need to be accurately reflected in the productivity calculations. One accomplishes this by expressing the partial productivity measures in $/hr.
Figure 2-3 Manufacturing cost percentages
When one evaluates an existing process, labor rate, energy cost, and raw material costs are typically readily available from the manufacturing firm’s accounting office. Additionally, the capital costs of the existing equipment would be available as well. These rates will include allocated overhead costs. However, capital costs of an alternative—new automated equipment—process must be estimated.
Estimation of capital costs of a proposed automation can be done through simple calculations that take into account the time value of money in conjunction with allocated factory overhead. When a manufacturing firm invests in a capital expenditure, it expects the investment will yield a return. Most firms have a standard rate of return. This figure, expressed as a percentage, should be readily available from a firm’s upper management. With the rate in hand, the automation engineer can begin to make estimated capital cost calculations.
The goal of the capital cost calculations is to represent the cost of the proposed automation in terms that can be used in the productivity calculations. Thus, cost needs to be expressed in terms of $/hr. The calculation breaks the initial cost of the equipment into an annual cost, then spreads that annual cost over the hours the machine is estimated to run in a year; finally, it adds in factory overhead expenses. The estimated hourly capital cost of the automation can be calculated with the following equation:
Cc = Ca(1 + rfoh),
where