Optimization of processes on the base of artificial intelligence in industry

Rixsiboyev Nozimbek Abdurasul oʻgʻli

Marketing · 2025-yil

Annotatsiya

This article examines the optimization of production processes using artificial intelligence (AI) technologies in industrial manufacturing. The study utilizes theoretical analysis, a comparative study of international practices, and methods for evaluating the effectiveness of AI -based optimization methods, such as machine learning, deep learning, reinforcement learning, and genetic algorithms. The results demonstrate that AI -based optimization systems can adjust production parameters in real time, efficient ly utilize resources, reduce energy consumption, and stabilize product quality. Using international experience as examples, the article analyzes AI - based optimization methods from leading industrial companies, such as BMW, BASF, Intel, and Bosch, and prese nts their results. The key stages of implementing AI in industrial process optimization, along with technical requirements and expected economic benefits, are substantiated.

Maqola ma’lumotlari
MualliflarRixsiboyev Nozimbek Abdurasul oʻgʻli
JurnalMarketing
NashriyotТошкент давлат иқтисодиёт университети
ISSN3060-4621
Nashr sanasi2025-06-30
Son6
TilIngliz
Ilmiy sohaIqtisodiyot
DOI10.67668/mj/2025iss6/402
Indeksga qo‘shilgan2026-10-18

DOI: 10.67668/mj/2025iss6/402 · Maqolaning asl sahifasi

Kalit so‘zlar

Artificial intelligence, process optimization, manufacturing, machine learning, reinforcement learning, genetic algorithms, digital twins, real -time optimization, parameter tuning, energy efficiency, Industry 4.0, smart manufacturing, process control, adap tive control, Искусственный интеллект, оптимизация процессов, производство, машинное обучение, обучение с подкреплением, генетические алгоритмы, цифровые двойники, оптимизация в реальном времени, настройка 279 параметров, энергоэффективность, Индустрия 4.0, интеллектуальное производство, управление процессами, адаптивное управление, Sunʼiy intellekt, jarayonlarni optimallashtirish, ishlab chiqarish, mashinali oʻrganish, kuchaytiruvchi oʻrganish, genetik algoritmlar, raqamli egizaklar, real vaqt optimizatsiyasi, parametrlarni sozlash, energiya samaradorligi, Sanoat 4.0, aqlli ishlab ch iqarish, jarayon nazorati, adaptiv boshqaruv

Ilmiy soha

Iqtisodiyot

Iqtibos keltirish

APARixsiboyev Nozimbek Abdurasul oʻgʻli (2025). OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY. Marketing, (6). https://doi.org/10.67668/mj/2025iss6/402
GOST (OAK)Rixsiboyev Nozimbek Abdurasul oʻgʻli OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY // Marketing. – 2025. – № 6. – DOI: 10.67668/mj/2025iss6/402.
MLARixsiboyev Nozimbek Abdurasul oʻgʻli. “OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY.” Marketing, (6), 2025. https://doi.org/10.67668/mj/2025iss6/402
ChicagoRixsiboyev Nozimbek Abdurasul oʻgʻli. “OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY.” Marketing, (6) (2025). https://doi.org/10.67668/mj/2025iss6/402
HarvardRixsiboyev Nozimbek Abdurasul oʻgʻli (2025) ‘OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY’, Marketing, (6). https://doi.org/10.67668/mj/2025iss6/402
BibTeX
@article{rixsiboyevnozimbekabdurasulogli2025,
  title = {OPTIMIZATION OF PROCESSES ON THE BASE OF ARTIFICIAL INTELLIGENCE IN INDUSTRY},
  author = {Rixsiboyev Nozimbek Abdurasul oʻgʻli},
  journal = {Marketing},
  year = {2025},
  number = {6},
  doi = {10.67668/mj/2025iss6/402},
  url = {https://doi.org/10.67668/mj/2025iss6/402}
}

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