skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Optimizing the availability of a buffered industrial process

Abstract

A computer-implemented process determines optimum configuration parameters for a buffered industrial process. A population size is initialized by randomly selecting a first set of design and operation values associated with subsystems and buffers of the buffered industrial process to form a set of operating parameters for each member of the population. An availability discrete event simulation (ADES) is performed on each member of the population to determine the product-based availability of each member. A new population is formed having members with a second set of design and operation values related to the first set of design and operation values through a genetic algorithm and the product-based availability determined by the ADES. Subsequent population members are then determined by iterating the genetic algorithm with product-based availability determined by ADES to form improved design and operation values from which the configuration parameters are selected for the buffered industrial process.

Inventors:
; ; ;
Publication Date:
Research Org.:
The Regents of the University Of California, Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1174998
Patent Number(s):
6,782,295
Application Number:
09/848,817
Assignee:
University Of California, The Regents Of
DOE Contract Number:  
W-7405-ENG-36
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Martz, Jr., Harry F., Hamada, Michael S., Koehler, Arthur J., and Berg, Eric C. Optimizing the availability of a buffered industrial process. United States: N. p., 2004. Web.
Martz, Jr., Harry F., Hamada, Michael S., Koehler, Arthur J., & Berg, Eric C. Optimizing the availability of a buffered industrial process. United States.
Martz, Jr., Harry F., Hamada, Michael S., Koehler, Arthur J., and Berg, Eric C. Tue . "Optimizing the availability of a buffered industrial process". United States. https://www.osti.gov/servlets/purl/1174998.
@article{osti_1174998,
title = {Optimizing the availability of a buffered industrial process},
author = {Martz, Jr., Harry F. and Hamada, Michael S. and Koehler, Arthur J. and Berg, Eric C.},
abstractNote = {A computer-implemented process determines optimum configuration parameters for a buffered industrial process. A population size is initialized by randomly selecting a first set of design and operation values associated with subsystems and buffers of the buffered industrial process to form a set of operating parameters for each member of the population. An availability discrete event simulation (ADES) is performed on each member of the population to determine the product-based availability of each member. A new population is formed having members with a second set of design and operation values related to the first set of design and operation values through a genetic algorithm and the product-based availability determined by the ADES. Subsequent population members are then determined by iterating the genetic algorithm with product-based availability determined by ADES to form improved design and operation values from which the configuration parameters are selected for the buffered industrial process.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2004},
month = {8}
}

Patent:

Save / Share:

Works referenced in this record:

Optimal multistage modernization of power system subject to reliability and capacity requirements
journal, June 1999


Structure optimization of power system with bridge topology
journal, June 1998


Reliability optimization of series-parallel systems using a genetic algorithm
journal, June 1996

  • Coit, D. W.; Smith, A. E.
  • IEEE Transactions on Reliability, Vol. 45, Issue 2
  • DOI: 10.1109/24.510811

Successful modeling of a semiconductor R&D facility
conference, January 1990

  • Tullis, B.; Mehrotra, V.; Zuanich, D.
  • IEEE/SEMI International Symposium on Semiconductor Manufacturing Science
  • DOI: 10.1109/ISMSS.1990.66131

Simulation of a semiconductor manufacturing line
journal, October 1990


Application of genetic algorithm for reliability allocation in nuclear power plants
journal, September 1999


Considering risk profiles in design optimization for series-parallel systems
conference, January 1997


Genetic algorithms in optimization of system reliability
journal, June 1995

  • Painton, L.; Campbell, J.
  • IEEE Transactions on Reliability, Vol. 44, Issue 2
  • DOI: 10.1109/24.387368

Application of discrete event simulation in production scheduling
conference, January 1998

  • Vaidyanathan, B. S.; Miller, D. M.; Park, Y. H.
  • IEEE Winter Simulation Conference, 1998 Winter Simulation Conference. Proceedings (Cat. No.98CH36274)
  • DOI: 10.1109/WSC.1998.745800

Genetics based redudancy optimization
journal, April 1997


Optimal design of system reliability using interval programming and genetic algorithms
journal, October 1996


Genetic-algorithm-based reliability optimization for computer network expansion
journal, March 1995

  • Kumar, A.; Pathak, R. M.; Gupta, Y. P.
  • IEEE Transactions on Reliability, Vol. 44, Issue 1
  • DOI: 10.1109/24.376523

Joint redundancy and maintenance optimization for multistate series–parallel systems
journal, April 1999