Sensitivity analysis and design optimization

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Author: Anne Disabato, Tim Hanrahan, Brian Merkle

Steward: David Chen, Fengqi You

Date Presented: February 23, 2014


Introduction

Optimization and sensitivity analysis are key aspects of successful process design. Optimizing a process maximizes project value and plant performance, minimizes project cost, and facilitates the selection of the best components [1].

Design Optimization

Economic optimization is the process of finding the condition that maximizes financial return or, conversely, minimizes expenses. The factors affecting the economic performance of the design include the types of processing technique and equipment used, arrangement, and sequencing of the processing equipment, and the actual physical parameters for the equipment. The operating conditions are also of prime concern.

Optimization of process design follows the general outline below:


  1. Establish optimization criteria: using an objective function that is an economic performance measure.
  2. Define optimization problem: establish various mathematical relations and limitations that describe the aspects of the design
  3. Design a process model with appropriate cost and economic data


Although profitability or cost is generally the basis for optimization, practical and intangible factors usually need to be included as well in the final investment decision. Such factors are often difficult or impossible to quantify, and so decision maker judgment must weigh such factors in the final analysis [3], [4].

Defining the Optimization Problem and Objective Function

Trade-Offs

Parametric Optimization

Sub-optimizations

Optimization of a Single Decision Variable

Search Methods

Unrestricted Search

Three-Point Interval Search

Golden-Section Search

Quasi-Newton Method

Optimization of Two or More Decision Variables

Optimization in Industrial Practice

Optimization in Process Design

Sensitivity Analysis

Parameters to Study

Statistical Methods of Risk Analysis

Contingency Costs