International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 02 | Feb 2024
p-ISSN: 2395-0072
www.irjet.net
HUMAN-AI INTERACTION IN MANUFACTURING Sai Anvesh Durvasula Parabole.ai USA ----------------------------------------------------------------------***-------------------------------------------------------------------ABSTRACT The integration of artificial intelligence (AI), machine learning, and robotics for Industry 4.0 promises to revolutionize manufacturing productivity, but poses integration and skills development challenges. Collaborative human-AI systems that combine the strengths of human judgment with intelligent algorithms have been shown to increase quality control accuracy and output compared to either working independently. For instance, cobot assistants enhanced operator defect detection up to 10% over manual inspection alone at BMW plants. However, barriers exist; 43% cite integrating AI given legacy IT infrastructures as a primary obstacle, and 50 million industrial jobs likely require new technical training in the next decade for more hybrid roles. By establishing clear communication protocols that promote situational awareness, human workers can build appropriate reliance with mobile robotic partners and autonomous decision systems designed for interpretable transparency. Multi-stakeholder leadership is essential for governing this ongoing evolution of human-machine interaction across factory floors. If concerted reskilling investments coordinated between public and private sectors are made in the wake of new process automation waves, positive labor productivity effects could more than offset role redundancies. With analysts projecting 58 million potential net employment gains realizable by applying responsible implementation frameworks for trustworthy AI systems matched to suitable operator abilities, collective prosperity through expanded individual capacities appears achievable if collaborative work design innovations remain centered on mutual augmentation.
Keywords: Hybrid Systems, Explainable AI, Industrial IoT, Distributed Cognition, Machine learning, Human-Robot Collaboration.
I.
INTRODUCTION
Well-known manufacturing organizations, such as Tesla's Gigafactory 1, serve as prime examples of the ongoing Industry 4.0 revolutions that are taking place throughout production facilities by integrating thousands of industrial autonomous robotics and sophisticated machine learning software. [1]-[3]. Figure 1 is an overview of the Tesla Gigafactory 1 manufacturing floor, featuring advanced automation like industrial robots. This highlights the Industry 4.0 transition taking place in manufacturing facilities.
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