Conditions for the Application of a Genetic Algorithm in Scheduling Production Orders in an Industry 4.0 Environment

• Autorzy: Piotr Janke , Mirosław Matusek , Adam Sojda , Wojciech Zoleński , Krzysztof Wodarski , Marek Krannich
• Języki publikacji: EN

Abstrakty

EN

Purpose: The article is based on the premises of the R&D project "Research and Development Work on the Development and Application of a Genetic Algorithm for the Optimization of Production Management." The primary goal was to determine the conditions for the application of genetic algorithms in the scheduling of production orders in the Industry 4.0 environment. Design/methodology/approach: The objectives are achieved through a comprehensive analysis of current challenges in production management, particularly in the context of Industry 4.0. The main method used is a theoretical examination of the potential applications of genetic algorithms (GAs) in optimizing production scheduling. The approach is interdisciplinary, combining insights from artificial intelligence, operations management, and industrial engineering. The paper explores both the theoretical framework and practical aspects of GAs in the production environment. Findings: The paper finds that genetic algorithms can significantly enhance production scheduling in the dynamic and complex environment of Industry 4.0. GAs offer solutions for optimizing production processes, maintenance prediction, and supply chain management. It was also found that while the practical applications of GAs are still developing, they hold great potential for addressing the multifaceted challenges of modern production systems. Research limitations/implications: The research is primarily theoretical, suggesting a need for empirical studies to validate the proposed applications of genetic algorithms in real-world industrial settings. Future research should focus on case studies and simulations to demonstrate the effectiveness of GAs in production scheduling. Practical implications: This research highlights the potential of genetic algorithms to revolutionize production scheduling in Industry 4.0, leading to increased efficiency, reduced costs, and enhanced production flexibility. Businesses could implement GAs to optimize various aspects of production, leading to significant economic benefits. Social implications: The implementation of genetic algorithms in production can influence society by potentially leading to more sustainable production practices, efficient use of resources, and reduced environmental impact. It could also set new industry standards in production management, influencing public attitudes towards technological innovation in manufacturing. Originality/value: The originality of the paper lies in its comprehensive analysis of the application of genetic algorithms in the context of Industry 4.0, a relatively new and unexplored area. The paper's value is in providing a theoretical foundation for future empirical research and practical implementation, and it is addressed to academics, industry professionals, and policymakers in the field of production management.(original abstract)

Słowa kluczowe

EN

Genetic algorithms; Industry 4.0; Optimalization; Schedule; Production management

PL

Algorytmy genetyczne; Przemysł 4.0; Optymalizacja; Harmonogram; Zarządzanie produkcją

• Czasopismo: Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
• Rocznik: 2023
• Numer: z. 189 Współczesne zarządzanie = Contemporary management
• Strony: 223--237

Twórcy

autor

Piotr Janke

• Silesian University of Technology, Poland

autor

Mirosław Matusek

• Silesian University of Technology, Poland

autor

Adam Sojda

• Silesian University of Technology

autor

Wojciech Zoleński

• Silesian University of Technology, Poland

autor

Krzysztof Wodarski

• Silesian University of Technology

autor

Marek Krannich

• Silesian University of Technology, Poland

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Identyfikatory

DOI

10.29119/1641-3466.2023.189.15