AI in manufacturing is helping companies design, build, and operate digital twins of their industrial sites with more efficiency and sustainably.
Artificial Intelligence (AI) adoption in manufacturing is multifaceted offering solutions for efficiency, quality control, predictive maintenance, and waste reduction. Its ability to unveil complexities in supply chains and enhance worker safety represents a significant shift in how manufacturing operates, aligning technological progress with human and environmental well-being. This innovation is part of a wider trend in manufacturing, where AI is increasingly integral, from design to delivery.
The integration of AI in manufacturing raises questions about its impact on the workforce. Some companies are exploring AI’s role in ensuring worker safety around machinery, using machine learning and computer vision to monitor factory environments for potential hazards. Wearable AI technologies, like exoskeletons, are being deployed in warehouses to protect workers performing physically demanding tasks.
Safety and efficiency
AI’s prowess in processing vast data sets is crucial in anticipating and managing disruptions. Manufacturing delays can be costly, and AI’s real-time process monitoring and predictive capabilities are vital for maintaining productivity, especially during peak demand times like holidays or sales events.
AI undergoes hours of machine monitoring to develop algorithms that precisely detect various malfunctions. It also provides comprehensive insights into equipment health, enabling proactive maintenance scheduling, and reducing the need for emergency repairs. Advanced sensors, infused with AI, are trained to detect sounds signaling potential breakdowns. These devices, educated on extensive audio data, can identify issues like wear on conveyor belts or bearings.
AI’s impact extends to waste reduction. By ensuring optimal machine functioning, AI can lower energy consumption. Another AI application, computer vision, is employed in factories worldwide for quality control. This technology enables machines to identify defects in products, a task particularly crucial for intricate items like computer chip wafers or circuit boards, where human oversight might miss minor but significant errors.
AI is not a mere tool for modernizing factories just to enhance worker efficiency but also for groundbreaking uses like capacity sharing among manufacturers, enhanced supply chain transparency, optimized logistics, and customer satisfaction. AI technology is being used to develop predictive tools to trace ingredients like palm oil, often listed under various names, to prompt consumer awareness and sustainability.
Skill Development with AI Training
AI-driven training programs are revolutionizing how workers develop skills. These personalized learning experiences focus on efficiency, enabling workers to acquire new capabilities faster and more effectively. By incorporating Virtual Reality (VR) and Augmented Reality (AR) into training, employees gain practical experience in a safe, risk-free environment. This approach not only enhances skill acquisition but also prepares workers for a variety of scenarios without the associated real-world risks.
Enhancing Workplace Ergonomics through Robotics
The integration of robotics and automation in the workplace is significantly reducing the physical demands on employees. By automating repetitive and physically strenuous tasks, there is a notable decrease in the risk of work-related injuries. This shift is pivotal in improving overall workplace ergonomics, ensuring a safer and more comfortable environment for workers.
Data-Driven Insights for Improved Production
AI analytics are playing a crucial role in enhancing the understanding of production processes. By leveraging data-driven insights, businesses can make more informed decisions that positively impact worker conditions and boost productivity. This approach fosters a more efficient and worker-friendly production environment.
Automating Quality Control for Worker Relief
Automated systems are now integral in maintaining high-quality standards in production. These systems relieve workers from the continuous monitoring of product quality, ensuring consistent excellence without adding to the workload.
AI for Workforce Flexibility
AI technology supports more flexible staffing models. It adeptly adapts to changing demand patterns, ensuring that staff are not overburdened during peak periods. This flexibility is essential in maintaining a balanced and responsive workforce, capable of efficiently handling fluctuating demands without compromising employee well-being.
Jan Iverson is Head of Studio at FS Studio and an award-winning product leader with over 20-years of extensive experience in digital media and marketing, with a specialization in the design and development of AR, VR and 3D activations: mobile apps, games, LBE, sales tools, digital twins; with XR cross-platform content development, and a track record of success in leading award-winning digital creative teams. Virtually Human is her bi-weekly series.