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Optimization Algorithms and Their Applications and Prospects in Manufacturing Engineering.

Juan Song1, Bangfu Wang2, Xiaohong Hao1

  • 1Department of Basic Courses, Suzhou City University, Suzhou 215104, China.

Materials (Basel, Switzerland)
|August 29, 2024
PubMed
Summary
This summary is machine-generated.

Optimization algorithms enhance machining efficiency and quality by refining process parameters. Mature methods like genetic algorithms are crucial for advancing manufacturing technology towards greater efficiency and customization.

Keywords:
engineering applicationsgenetic algorithmsoptimization algorithmsparticle swarm optimizationprocess parametersresponse surface method

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Area of Science:

  • Manufacturing Engineering
  • Computational Intelligence
  • Materials Science

Background:

  • Optimization algorithms are integral to modern manufacturing for improving machining efficiency and quality.
  • Advancements in computing and artificial intelligence are increasing the importance of these algorithms in process parameter optimization.
  • Established methods include the response surface method, genetic algorithm, Taguchi method, and particle swarm optimization algorithm.

Purpose of the Study:

  • To systematically review the application and developmental trends of optimization algorithms in practical engineering production.
  • To classify, define, and assess the current research status of process parameter optimization algorithms in manufacturing.
  • To explore the specific real-world applications of these optimization algorithms.

Main Methods:

  • Literature review and systematic analysis of optimization algorithms in manufacturing.
  • Classification and definition of process parameter optimization algorithms.
  • Exploration of established methods such as response surface, genetic algorithm, Taguchi, and particle swarm optimization.

Main Results:

  • Optimization algorithms are extensively applied to surface roughness, subsurface damage, cutting forces, and mechanical properties in machining.
  • These algorithms are critical for optimizing parameters in both conventional and special machining processes.
  • The review covers domestic and international research on optimization algorithms in engineering manufacturing.

Conclusions:

  • Optimization algorithms are evolving to enhance manufacturing competitiveness, efficiency, sustainability, and customization.
  • Continued development of these algorithms is vital for advancing manufacturing technology.
  • The application of optimization algorithms is key to achieving higher quality and more efficient production outcomes.