Chemical Processing System Design with Time-Dependent Reliability

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Solution Overview

Problem

Current chemical processing system design methods do not adequately consider the temporal variations in reliability and availability of equipment, leading to suboptimal economic performance due to fixed failure rate assumptions and lack of maintenance optimization.

Innovation Solution

A method that defines a system model with parameters expressing availability and reliability as functions of time, incorporating preventive maintenance to determine an optimal arrangement of apparatus, which includes analyzing the system model to find a preferred arrangement that minimizes capital investment and operational costs while maximizing system performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If fixed failure rate assumptions are used in design, then design simplicity is maintained, but reliability accuracy deteriorates

Engineering Contradiction:
Improvedesign simplicityVSAvoidreliability accuracy
Core Design Contradiction:
Device complexityVSReliability

Solution Approach 1:

The patent applies dynamics by transitioning from static fixed failure rate assumptions to dynamic time-dependent failure rate models. The superstructure optimization framework incorporates time-varying reliability parameters that evolve throughout the plant lifecycle, allowing the design to adapt to changing reliability conditions without requiring complex manual recalculations.

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent changes key parameters from constant values to time-dependent functions. Failure rates, availability, and maintenance costs are transformed into parameters that vary with time and operational state, enabling more accurate reliability assessment while maintaining computational tractability through the optimization framework.

Inventive Principle:
Principle #35Parameter changes

2Device complexity

If maintenance optimization is excluded from design, then design process is simplified, but operational performance deteriorates

Engineering Contradiction:
Improvedesign process complexityVSAvoidoperational performance
Core Design Contradiction:
Device complexityVSProductivity

Solution Approach 1:

The patent applies preliminary action by incorporating maintenance optimization considerations during the conceptual design phase rather than addressing them later. The superstructure optimization simultaneously determines equipment configuration and maintenance strategies, ensuring that maintenance requirements are built into the design from the outset, leading to improved operational performance.

Inventive Principle:
Principle #10Preliminary action

3Device complexity

If temporal variations in reliability are not considered, then design computation is simplified, but economic performance deteriorates

Engineering Contradiction:
Improvedesign computation complexityVSAvoideconomic performance
Core Design Contradiction:
Device complexityVSReliability

Solution Approach 1:

The patent implements feedback mechanisms where time-dependent reliability parameters continuously inform the optimization process. The superstructure optimization framework uses evolving reliability data to adjust design decisions and maintenance strategies throughout the plant lifecycle, creating a closed-loop system that improves economic performance by responding to actual reliability conditions.

Inventive Principle:
Principle #23Feedback

Data Source

PatentEP2117698B1Chemical processing system
Publication Date: 2013.12.18 UNIV OF MANCHESTER
  • EP2117698B1 patent drawingFigure 1~2
  • EP2117698B1 patent drawingFigure 3~4
  • EP2117698B1 patent drawingFigure 5~7

AI summary

A method of optimising apparatus utilised within a processing system includes defining a system model indicative of a predetermined range of apparatus options within a processing system, constraints indicative of feasible interconnections between each apparatus, and parameters indicative of performance criteria associated with each apparatus. The system model is analysed with respect to predetermined criteria to determine a preferred arrangement of apparatus within the processing system. A parameter relating to at least one apparatus is indicative of the availability and/or the reliability of the apparatus expressed as a function of time.