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Figure 3: The value analysis process.

evaluated to determine value thresholds of the extended benefits, or "bells and whistles" as they are sometimes called.

To continue the examples above, the coding system would consider additional digits to further detail the parts and allow additional benefits in design, engineering, drafting, process planning, and possibly manufacturing also. More capable and expensive robots would be considered for more complex production tasks. And a larger MRP II system, perhaps for the mainframe, would be considered with significantly expanded capabilities for supporting other functions and departments.

Note that the pilot stage defined above was "broad" rather than "deep" and not the typical incremental approach used in engineering. That is. its functional capability was limited but not its breadth of application. The other way of handling a pilot stage, which can also be useful, is to reverse the process. For example, conduct the classification and coding for only a limited number of the firm's products, say, all turned parts. But the full set of digits would be used for these parts. And in the third example situation above, the firm would implement only one portion of the MRP II system, for example, the routings package. But it would be used on the mainframe and for all products made in the shop.

Either of these methods can help the firm approach factory automation with more understanding and less risk. The essence of value analysis is to separate the cost and the value derived to let managers intuitively ascertain if the value of the benefits obtained is worth their cost. It also provides an incremental approach to the automation process that lets managers control the cost and thus not let the risk to the firm get out of hand.

Portfolio Analysis The scenario for portfolio analysis consists of a number of projects competing for limited capital funding. The task is to choose the best set of projects for implementation. The selection is made by creating a portfolio of projects that either maximizes value to the firm subject to capital investment or risk limitations, or minimizes risk or capital subject to attainment of a certain level of value. The value can be based on any number of factors such as return on investment, reduction in scrap, improvement in quality, and so on.

Three general types of portfolio models exist: non-numeric models, scoring models, and programming models. All three are discussed and illustrated in Meredith and Mantel (1985).

Risk Analysis The usual approach of risk analysis (see, for example, Hertz 1964 or Turban and Meredith 1985) is to simulate the projects under consideration to determine the variables of interest—benefits, costs, yields, capacity, and so on—and describe the outcomes statistically or graphically. Cumulative distribution functions are determined for each variable of interest showing the likelihood of achieving a certain profit, capacity, return on investment, and so on. Various automation projects can thus be simulated beforehand and the results compared. Using the concepts of stochastic dominance as described by Whitmore and Findlay (1978), inferior policies or projects can be eliminated and only the most promising implemented (e.g., see Suresh and Meredith 1985) We illustrate the approach with a simple machine tool investment example below.

There are two potential investment alternatives to replace an existing manufacturing system that is old and overworked. The capital costs, hourly operating costs, and annual maintenance costs are given in Table 1. There are four products (A, B, C, and D) and several minor parts (P) currently being made on this equipment. The typical operation times required for each of the products and parts are given in Table 2 and the anticipated sales volume and price over the next eight years are listed in Tables 3 and 4, respectively. The sales volume estimates have an accuracy of plus or minus 250 units and the price accuracies are as shown.

Given the uncertainties in sales volumes and prices, a simulation risk analysis to determine factors such as net present value (NPV) and machine utilization of each of the alternatives is warranted. In the simulation model (written in SIMSCRIPT 11.5), the sales volume is taken as a uniform random variate between the 250 unit accuracy limits. Prices are determined in the same manner. Following this, machine operating hours, equipment utilization, and then the

Table 1 Equipment Cost Elements

Present Alternatives

Equipment 1 2

Capital cost (salvage value, 5000) 40,000 32,500 Hourly operating cost 1.5 0.2 0.75 Annual maintenance cost 1000 1400 1250

Table 2 Operation Times

Product

Present Equipment

Alternative 1

Alternative 2

Project Management Made Easy

Project Management Made Easy

What you need to know about… Project Management Made Easy! Project management consists of more than just a large building project and can encompass small projects as well. No matter what the size of your project, you need to have some sort of project management. How you manage your project has everything to do with its outcome.

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