Aug. 14, 2024

This paid piece is sponsored by Eide Bailly LLP.

By Ryan T. Doyle, CPA, partner

 A version of this insight first appeared on EideBailly.com.

Artificial intelligence in manufacturing isn’t a futuristic concept — it’s a reality that businesses increasingly are leveraging to enhance efficiency, reduce costs and gain a competitive edge. According to research from the Manufacturing Leadership Council, 96 percent of manufacturers plan to increase AI investments in operations by 2030. 

AI in manufacturing

AI in manufacturing has evolved to address a wide range of applications, including:

• Production line scheduling: AI optimizes the scheduling of production lines, ensuring efficient use of resources.
• Administrative task automation: Repetitive administrative tasks are automated, reducing human labor and human error.
• Predictive maintenance: AI analyzes data to predict when machinery requires maintenance, minimizing downtime and repair costs.
• Quality control: Real-time computer vision and machine learning detect defects, ensuring products meet high-quality standards.
• Personalized manufacturing: AI-driven customization allows manufacturers to produce highly customized products efficiently, catering to individual customer needs.

Power of AI technologies

Modern AI technologies have reached unprecedented levels of sophistication. They can learn from experience and make more complex decisions thanks to advances in computing power, large-scale data integration and more. These AI advancements have significantly transformed manufacturing by reducing costs, increasing efficiency and improving quality and productivity.

• Cost reduction: AI-driven predictive maintenance helps prevent costly machinery breakdowns, lowering maintenance and repair expenses. Companies can realize substantial cost reductions in operational and maintenance expenses, often resulting in a more efficient cost structure.
• Improved quality and productivity: AI technologies can enhance product quality and production efficiency through real-time quality control, predictive maintenance and process optimization. By automating quality inspections and monitoring, manufacturers can significantly reduce defects and rework. This not only leads to higher-quality products but also boosts productivity as resources are utilized more effectively.
• Enhanced decision-making and efficiency: AI provides valuable insights and data-driven recommendations that enable manufacturers to make informed decisions. This includes optimizing production schedules, managing inventory levels and responding to changing market demands more effectively. AI-driven analytics and insights lead to better decision-making, improved operational efficiency and increased competitiveness. 

Future of AI in manufacturing

AI, from a manufacturing standpoint, is about leveraging non-human controlled interactions. This encompasses various technologies like electro-mechanical systems, electrical relays, control boards and analytical calculation models. Interpretive language or learning models, or generative AI, represent the more familiar face of AI. When implemented effectively, these complex programming giants can add substantial value.

While there is a growing fear that generative AI will replace jobs, the majority of manufacturing leaders do not believe this is the case. In fact, one-third expect their workforce head count to increase because of AI.

As AI continues to evolve, its applications in manufacturing are poised to expand, offering even more benefits to companies worldwide.

Contact Eide Bailly to learn more about AI in manufacturing.