Total Cost Targets

Increasing the chosen value of process energy consumption also increases all temperature differences available for heat recovery and hence decreases the necessary heat exchanger surface area (see Fig. 6.6). The network area can be distributed over the targeted number of units or shells to obtain a capital cost using Eq. (7.21). This capital cost can be annualized as detailed in App. A. The annualized capital cost can be traded off against the annual utility cost as shown in Fig. 6.6. The total cost shows a minimum at the optimal energy consumption. 

Now scan a range of values of Ar ,in and calculate the targets for energy, number of units, and network area and combine these into a total cost. The results are given in Table 7.4. 

Once a design is known for the first two layers of the onion (i.e., reactors and separators only), the overall total cost of this design for all four layers of the onion (i.e., reactors, separators, heat exchanger network, and utilities) is simply the total cost of all reactors and separators (evaluated explicitly) plus the total cost target for heat exchanger network and utilities. 

Having to readjust the capital/energy tradeoff after every process change would be a real problem if it were not for the existence of the total cost targeting procedures discussed in Chap. 7. 

Targets for number of shells, capital cost, and total cost also can be set. Thus remaining problem analysis can be used on these design parameters also. 

In any case, like frequency analysis, examining the uncertainties and sensitivities of the results to changes in boundary conditions and assumptions provides greater perspective. The level of effort required for a consequence analysis will be a function of the number of different accident scenarios being analyzed the number of effects the accident sequence produces and the detail with which the release, dispersion, and effects on the targets of interest is estimated. The cost of the consequence analysis can typically be 25% to 50% of the total cost of a large QRA. 

The tender with the lowest total costs (sum of investment, energy and maintenance costs) is the best and the supplier guarantees energy, and maintenance costs for, say, a three-year period. If the target costs are exceeded, the supplier pays a penalty if the operating costs are lowered, the supplier and the customer share the bonus. 

Energy intensity. Energy intensity is an obvious target for green product design. This is the easiest dimension to identify commercial benefits. Lower energy intensity can clearly either save manufacturing costs, or total cost of ownership for the user. 

The in situ bioremediation application at this site included injection of a liquid microbial solution into the subsurface through monitoring and injection wells. This solution includes microbes (Pseudomonas, Bacillus, and Corynebacterium), oxygen, emulsifier, surfactant, and nutrients. Five injections were conducted. Over 11.3 m3 (3000 gallons) was injected from February 1999 to September 2000 into approximately 40 wells and 15 Geoprobe injection points. As of September 2000, MTBE levels decreased by 96% (3310-146 pg/L), while benzene decreased by 83% (2571— 435 pg/L), toluene by 66% (24,330-8300 pg/L), and naphthalene by 84% (5377-853 pg/L) xylene levels increased and were above preoperational level as of September 2000. The system will continue to be operated until all target levels have been met. The total cost for the cleanup of this site is USD63,500.34... 

Heat Exchanger Networks III - Capital and Total Cost Targets... 

Once a design is known for the reaction and separation systems, the overall total cost is the total cost of all reactors and separators (evaluated explicitly) plus the total cost target for heat exchanger network. 

Another perspective for production simulation is automatic capacity utilization optimization of multi-product systems. As discussed, this task may be very difficult because of the many different variables and boundary conditions. In an environment integrating optimization and simulation, the optimizer systematically varies the important decision variables in an external loop while the simulation model carries out production planning with the specified variables in the internal loop (see Gunther and Yang [3]). The target function, for example total costs or lead times, can be selected as required. The result of optimization is a detailed proposal for the sequence of the placed orders. 

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