Cost Model

Figure 7.9 The Xp parameter avoids steep slopes on the Fp curves, whereas minimum Fp does not. (Reprinted from Ahmad, Linnhoff, and Smith, Cost Optimum Heat Exchanger Networks II. Targets and Design for Detailed Capital Cost Models, Computers Chem, Engg., 7 751, 1990 with permission from Elsevier Science, Ltd.)...

The combination of the cost model and the optimization method will then give an augmented model from which the allocation of the component tolerances are optimized for competitive results. Optimization methods have also been extended to include procedures that select the most cost-effective manufacturing process for each component tolerance in the assembly stack (Chase and Parkinson, 1991). 

Research looking into tolerance allocation in assembly stacks is by no means new. A current theme is towards an optimization approach using complex routines and/ or cost models (Lin et al., 1997 Jeang, 1995). Advanced methods are also available, such as Monte Carlo Simulation and Method of Moment. ) (Chase and Parkinson, 1991 Wu et al., 1988). The approach presented here is based on empirical process capability measures using simple tolerance models, cost analogies and optimization... 

Dong, Z. 1997 Tolerance Synthesis by Manufacturing Cost Modeling and Design Optimization. In Zhang, H. (ed.). Advanced Tolerancing Techniques. NY Wiley Interscience. 

To evaluate the economics of this process, a cost model has been developed to estimate the separation costs for a specific racemate [68, 69]. For this purpose, the sensitivity of the separation costs for several key process parameters have been established as compared to a base-case separation in which a purity of 99 % is required at an enantioselectivity of 1.15. The maximum solubility of the drug is set... 

C. Taguchi Loss Functions as Continuous Quality Cost Models.401... 

In Section IV we considered a categorical performance metric y. Although that represents a common practice, especially when y defines the quality of a product or process operation, there are many instances where system performance is measured by a continuous variable. Even when y is quality-related, it is becoming increasingly clear that explicit continuous quality cost models should be adopted and replace evaluations of performance based on categorical variables. 

This Section addresses cases with a continuous performance metric, y. We identify the corresponding problem statements and results, which are compared with conventional formulations and solutions. Then Taguchi loss functions are introduced as quality cost models that allow one to express a quality-related y on a continuous basis. Next we present the learning methodology used to solve the alternative problem statements and uncover a set of final solutions. The section ends with an application case study. 

Both situations with categorical and continuous, real-valued performance metrics will be considered and analyzed. Since Taguchi loss functions provide quality cost models that allow the different objectives to be expressed on a commensurate basis, for continuous performance variables only minor modifications in the problem definition of the approach presented in Section V are needed. On the other hand, if categorical variables are chosen to characterize the system s multiple performance metrics, important modifications and additional components have to be incorporated into the basic learning methodology described in Section IV. 

Ahmad S, Linnhoff B and Smith R (1990) Cost Optimum Heat Exchanger Networks II Targets and Design for Detailed Capital Cost Models, Comp Chem Eng, 7 751. 

The nature of the optimization problem can mm out to be linear or nonlinear depending on the mass transfer model chosen14. If a model based on a fixed outlet concentration is chosen, the model turns out to be a linear model (assuming linear cost models are adopted). If the outlet concentration is allowed to vary, as in Figure 26.35a and Figure 26.35b, then the optimization turns out to be a nonlinear optimization with all the problems of local optima associated with such problems. The optimization is in fact not so difficult in practice as regards the nonlinearity, because it is possible to provide a good initialization to the nonlinear model. If the outlet concentrations from each operation are initially assumed to go to their maximum outlet concentrations, then this can then be solved by a linear optimization. This usually... 

The user is allowed to define a cost model for controlling the behavior of the optimizers. Rules can be derived from costs, times, resource utilization or lead times. Also parts of the quant network can be deleted again if they are identified as not optimal by applying user defined evaluation procedures. 

The objective is to maximize the profit which is calculated by a cost model of sales revenues, production costs, storage costs, and penalties for lateness and for finishing line start-ups and shut-downs. The cost model adds some equality and inequality constraints with associated real valued variables for the sales, deficits, and the storage, but it does not further restrict the feasibility of the production decisions. 

All remaining decisions can be made after the observation of the outcome of uncertain parameters, either in the detailed scheduler or by decisions of the aggregated problem which are taken later. Thus, these decisions are considered as second-stage decisions. Consequently, the vector of second-stage decisions ya consists of all production decisions of the periods i > h and all continuous variables of the cost model for all periods. 

One of the main aspects of the SNP planning process is the cost-based plan determination. The following cost types are used to build a cost model which represents the business scenario of value-based planning ... 

The definition of the cost model is of crucial importance for controlling the behavior of the S N P optimizer. One of the central questions is whether to maximize service level, which usually means using high penalties for non and late delivery, or to maximize profits, which requires the use of realistic sale prices. In the case study scenario, the nondelivery cost levels reflect real sale prices sufficiently close to enable a profit maximization logic. 

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