Large-scale Layout Optimization for Chemical Plant

Generative design algorithm for automated multi-layer facility layout optimization

Project Overview

This project developed an automated facility layout optimization system using generative design algorithms for industrial plant construction. The system optimizes the placement of equipment in multi-layer process plants, addressing the Facility Layout Problem (FLP) which has significant economic impact on industrial facility construction costs and operational efficiency.

My Role

Algorithm Developer

  • Designed and implemented core optimization algorithms for multi-layer facility layout
  • Developed generative design methodology considering process efficiency and safety constraints
  • Created automated layout generation system that surpasses traditional experience-based approaches

Problem Statement

Automated facility layout optimization using generative design algorithms

Facility layout design in industrial plants has traditionally relied on the experience and intuition of field experts. However, this approach has critical limitations:

  • Manual design cannot satisfy all constraints simultaneously: Complex interdependencies between equipment, safety regulations, and process requirements make it nearly impossible to achieve true optimization through experience alone
  • High economic stakes: Poor layouts lead to increased construction costs, reduced operational efficiency, and higher maintenance requirements
  • Complexity of multi-layer plants: Modern process plants involve vertical stacking of equipment across multiple floors, exponentially increasing design complexity
  • Emergency response considerations: Layout directly impacts ability to handle emergency situations safely and efficiently

Technical Approach

Optimization Objectives

  1. Minimize plant footprint area: Reduce land use and construction costs
  2. Minimize total pipe length: Reduce material costs and pressure losses
  3. Satisfy safety and operational constraints: Maintain required clearances, access paths, and process flow requirements

Algorithm Innovation

Unlike previous facility layout optimization studies, this project developed a novel algorithm specifically designed for multi-layer process plant configurations. The algorithm:

  • Generates optimized layouts automatically considering vertical (multi-floor) arrangement possibilities
  • Balances competing objectives of space utilization and piping efficiency
  • Incorporates real-world constraints from industrial plant design standards
  • Produces layouts that meet or exceed expert-designed configurations

Case Study: SRIP Plant, Oman

The algorithm was validated using actual design data from the Sur Refinery Improvement Project (SRIP) in Oman, demonstrating practical applicability to real-world large-scale industrial facilities.

Impact

This project demonstrated that computer-aided optimization can produce facility layouts superior to those created solely through human expertise. The automated approach:

  • Explores a vastly larger design space than manual methods
  • Guarantees constraint satisfaction
  • Provides quantifiable optimization metrics
  • Reduces design time and costs
  • Enables rapid iteration and what-if analysis

The methodology developed can be applied to various types of industrial facilities including refineries, chemical plants, and manufacturing facilities.

Project Duration: May 2021 - October 2022 (18 months) Client: DLE&C Organization: Smart Design Lab, KAIST

Reference: 학술논문 링크