Artificial Intelligence

How Can AI Help My Company?

Robert Scipione, Michigan Manufacturing Technology Center
August 13, 2023
Download PDF


The manufacturing industry is collecting data at an unprecedented rate. However, understanding how to analyze this data is crucial to using it to its full potential. Learn the different ways artificial intelligence capitalizes on data to help manufacturers gain a competitive edge.

It appears everyone is talking about Artificial Intelligence (AI). Although the technology is not brand new, it has now developed enough and weaved its way into various life applications, with manufacturing being one.

AI has emerged as a game-changer in the manufacturing industry, revolutionizing traditional processes and unlocking new opportunities for operational efficiency, productivity and innovation. The integration of AI into manufacturing processes has paved the way for advanced automation, predictive analytics and data-driven decision-making, leading to improved outcomes and competitive advantages. Let’s look at ways AI can help manufacturers.

Predictive Maintenance

One of the prominent applications of AI in manufacturing is predictive maintenance. By leveraging machine learning algorithms, AI can analyze data from sensors and equipment to detect patterns and anomalies that indicate potential maintenance issues.

This enables manufacturers to predict when equipment is likely to fail and take proactive measures to prevent costly unplanned downtime. Predictive maintenance can optimize maintenance schedules, extend the lifespan of machinery, and minimize disruptions in the production process, leading to improved productivity and cost savings.

Quality Control

Ensuring product quality is critical in manufacturing, and AI is playing a crucial role in enhancing quality control processes. AI-powered vision systems can quickly and accurately inspect products for defects, inconsistencies and variations, reducing the reliance on human inspection and minimizing the risk of errors.

AI also can analyze data from various sources, such as production records, sensor data and customer feedback, to identify patterns and trends that may impact product quality. This helps manufacturers to take corrective actions in real time and improve overall product quality, leading to increased customer satisfaction and brand reputation.

Read the article in full here.

Sign up today for a free Essential Membership to Automation Alley to keep your finger on the pulse of digital transformation in Michigan and beyond.

Robert Scipione, Michigan Manufacturing Technology Center
Robert Scipione, Michigan Manufacturing Technology Center

Bob Scipione is an Applications Engineer at The Center. In his role, Bob facilitates the transfer of knowledge in Smart Manufacturing Technologies to small and mid-sized manufacturers and assists with their Industry 4.0 implementations and strategies. He brings nine years of experience in manufacturing control system design and software development. Bob has worked as both Installation Engineer and Senior Controls Engineer where he gained experience in robotic systems testing and installation, software engineering and integrating new hardware components to existing software.

Become a Member