Διαχείριση αποθηκών με τεχνητή νοημοσύνη : βελτιστοποίηση της αποδοτικότητας και της ακρίβειας
AI-enhanced warehouse management : optimizing efficiency and accuracy
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Keywords
AI ; Warehouse efficiency ; Warehouse optimizationAbstract
The present study delves into the incorporation of Artificial Intelligence (AI) in warehouse management, with a specific emphasis on inventory management and order processing. The first section of the paper outlines the difficulties that typical warehouse operations now face, including inefficiencies, mistakes, and expensive labor. By streamlining processes and enhancing accuracy, AI is identified as a major factor in resolving these issues through a thorough literature study.
The potential of AI-powered automation technologies, predictive analytics, and machine learning (ML) algorithms to improve warehouse performance is investigated. Certain AI technologies are highlighted because of their ability to improve operational performance, reduce picking errors, and increase cost-effectiveness. Examples of these technologies include computer vision, autonomous mobile robots (AMRs), and robotic arms.
The paper notes how AI affects workforce dynamics and decision-making and examines the consequences of AI adoption for warehouse management methods. The study does admit certain limits, though, namely the reliance on high-quality data and the possibility of biases in AI models.
In conclusion, even if artificial intelligence (AI) has a great deal of promise to improve warehouse operations, its full potential must be realized through careful deployment and continuous assessment. The results add to the body of information in academic discourse regarding AI's contribution to operational efficiency as well as practical warehouse management understanding.