AI is impacting the manufacturing industry
The manufacturing industry has recently received a lot more attention in the news. Although globalization has increased the availability of goods all over the world and significantly reduced their cost over the past decades, the impact of globalization is also being felt in regions where manufacturing was previously a mainstay of local economy.
The use of AI brings a wide range of innovations to the manufacturing industry that improve not only the quality and availability of goods, but also the ability to support manufacturing efforts in regions where AI can increase otherwise high labor costs or availability of materials.
AI improves and augments the manufacturing process
For a long time, automation has been used in the product assembly and manufacturing process, especially since the industrial revolution and the waves of Industry 2.0 and 3.0 which added more and more factory lines, computer-driven automation and more precise manufacturing technologies. AI adds aspects of intelligence to this automation formula that make these automated manufacturing processes more precise and adaptable.
Even though most of today’s traditional industrial robots lack the basic intelligence necessary to qualify as AI, AI-based robots are poised to make a substantial impact in manufacturing manufacturing. You can have non-intelligent robots programmed to perform specific tasks and automate them, and these robots are usually kept away from humans because of the damage they could cause if you happen to be in the wrong place at the wrong time.
However, collaborative robots, also called “cobots,” are a different type of robotic beast. These AI-driven robots are used to automate repetitive tasks, such as assembly or welding, or material handling. These collaborative robots are able to work alongside humans and therefore do not need to be caged.
The use of AI-based computer vision solutions is also commonly used to aid quality control and inspection. Computer vision systems are deployed to help detect product defects throughout the manufacturing process. These systems can detect even the smallest imperfections throughout the process, so that defective products can be removed from the production line and repaired or scrapped before reaching the customer’s hands.
AI helps bring the manufacturing industry closer to the idea of the smart factory and the concept of Industry 4.0, in which machines, sensors and systems are interconnected and communicate with each other. These interconnected systems collect real-time data to optimize production processes, improve decision-making and enable predictive maintenance.
Additionally, these fully automated and intelligent systems can operate with minimal human intervention, giving rise to the idea of a “lightless factory” in which manufacturing systems can occur even when the lights are off.
In this vision, manufacturing systems run 24 hours a day and you only need to turn on the lights when you perform quality control. This is even more of a futuristic and fantastical vision, because it’s very difficult to completely take humans out of the manufacturing cycle, but you can see that technology is increasingly making its way to automate these things.
AI helps make manufacturing processes more reliable, efficient, profitable and repeatable, providing factories with more uptime, reducing the cost of goods and reducing problems related to labor shortages and personnel problems. The smart factory cannot be achieved without AI, because it takes intelligence to be smart.
AI enables the manufacturing sector to operate effectively and efficiently
Manufacturing companies are also using AI to keep the production line running by operating equipment and tools. AI analyzes data from sensors built into machines to predict when equipment is likely to fail. This allows maintenance to be carried out only when necessary, thereby reducing equipment downtime and maintenance costs, because in the event of equipment downtime, the production line stops.
AI is able to analyze all equipment data to know in advance when a machine could be headed for failure. In anticipation of a potential future failure, these machines can be taken offline at an opportune time to perform predictive maintenance.
AI also helps maintain manufacturing processes by optimizing supply chain management by forecasting demand, optimizing inventory levels, and improving logistics. Companies are using AI to analyze large amounts of data from suppliers, weather conditions and market trends to improve supply chain efficiency. With the help of AI, organizations are able to more effectively predict demand and optimize inventory levels, as well as improve overall logistics.
Additionally, AI makes manufacturing more efficient by optimizing production schedules through data analysis, including order volumes, machine availability, and workforce capacity. This helps manufacturers maximize efficiency and minimize bottlenecks.
To keep energy-intensive production costs low, AI is even used to monitor and optimize energy consumption in manufacturing facilities. AI systems analyze data from energy meters and production equipment to identify inefficiencies and suggest ways to reduce energy consumption, leading to cost savings and more efficient, more environmentally friendly use of the environment.
Product development and design assistance
AI is increasingly being used in the design process itself. Whether it’s product or packaging design, or overall improving a product’s effectiveness, usability, reliability, or efficiency, AI is increasingly used to accelerate product design and prototyping. AI systems can analyze thousands of different alternatives and options and identify desirable features, taking into account cost, manufacturability, supply availability, energy consumption and other considerations.
These AI systems consider millions of different options with millions of different parameters and considerations, and help manufacturing companies design more efficiently and deliver their products to market more efficiently.
As part of this process, organizations use AI to improve the accuracy of demand forecasts by analyzing historical sales data, market trends, and external factors such as economic indicators. This helps manufacturers better plan their production and inventory, reducing the risk of overproduction or stockouts. These AI-based forecasting systems can help anticipate demand and avoid supply chain or inventory disruptions that cause significant problems across the economy.
In all of these ways, AI is having a significant impact on manufacturing today and will undoubtedly drive advancements in design, development, production and beyond in the manufacturing enterprise of the future.