AI in manufacturing: Where it’s been and where it’s going
Understanding the history of artificial intelligence (AI) can show where its future may be in manufacturing and what role it will play.
Manufacturing AI insights
- The integration of AI into discrete manufacturing aligns with the concept of Industry 4.0, which is characterized by advancements in technologies like the industrial internet of things (IIoT) and robotics.
- The future of AI in manufacturing will be able to help with machine learning algorithms to reduce downtime, improve efficiency and extend equipment lifecycles.
Artificial intelligence (AI) is everywhere. From Alexa (speech recognition) to Face ID (computer vision) to the chatbot you interacted with to troubleshoot an Internet issue (generative AI), AI is now ingrained in our everyday lives. This is not only true for consumers, but businesses across industries are also embracing AI’s capabilities en masse.
In the context of discrete manufacturing, AI has proven itself an extremely valuable asset at nearly every stage of the production process. Of course, this isn’t news to anyone in the manufacturing space. But what may surprise most (especially younger generations) is that the concept of AI has been around since the 1950s and actually put into practice by the 1970s.
Let’s take a quick look at the evolution of AI in discrete manufacturing to see how we got where we are today.
A brief history of AI in manufacturing
AI, commonly defined as the ability of machines (primarily computers) to simulate human intelligence processing, first showed up in discrete manufacturing facilities with the advent of computer-assisted design (CAD) and computer numerical control (CNC) machines in the 1970s. These technologies helped manufacturers create and modify product designs. Over the years, CAD and CNC machines became more sophisticated, incorporating advanced algorithms and machine learning (ML) to improve accuracy and optimize performance.
By the 1980s and 1990s, manufacturers started using AI applications to capture and share worker knowledge. Rather than relying on clipboards, handwritten notes or word of mouth, factory employees could codify knowledge into software systems, such as computerized maintenance management systems (CMMS) and manufacturing execution systems (MES). These inventions make information-sharing faster and easier while streamlining production through automation, real-time data collection and more.
Today, AI-powered quality control, process optimization, robotics, predictive maintenance and even safety hazard detection are becoming the standard in most discrete manufacturing facilities. Using sensors to detect mechanical issues, such as temperature spikes and abnormal vibrations, AI can not only alert the appropriate personnel to the problem, but it can tell them how, when, and with what tools to fix the problem. Modern-day smart manufacturing solutions like L2L Dispatch, for example, feature these and many more AI-driven capabilities. Moreover, the more shop floor workers interact with AI-enabled technologies, the smarter these technologies become — and the better they get at helping workers perform their jobs.
The future of AI in discrete manufacturing
Manufacturing is in the midst of what experts call Industry 4.0 — a period marked by rapid advancements in technologies like the industrial internet of things (IIoT), robotics and, of course, the integration of AI into nearly every part of discrete manufacturing. In short, machines on the factory floor can now communicate with one another and operate with an impressive degree of autonomy.
However, the most important role of AI in manufacturing is its ability to help people and machines work synergistically. For discrete manufacturing organizations, this is a win-win; technology-enabled people and processes lead to greater efficiency, productivity and safety, among other benefits.
As AI continues to evolve, we can expect to see significant advancements in the following area of discrete manufacturing:
Predictive maintenance: Today, many manufacturers still rely on reactive maintenance approaches that result in costly periods of downtime. With the use of AI and ML algorithms, manufacturers can employ predictive maintenance methods to monitor equipment performance in real time, predicting when maintenance is required before a failure occurs. This can help reduce downtime, improve efficiency, and extend equipment lifecycles. As AI advances, these benefits will be amplified even further.
Quality control: With the evolution and standardization of AI will come faster, more accurate quality control. Instead of manually inspecting machines and products for damage, wear, and other problems, manufacturers can use AI to automatically detect and report defects. AI can also identify patterns in production data as well as from external sources like customer feedback, production schedules, and inventory levels. This helps manufacturing leaders uncover inefficiencies and opportunities for process improvements.
Product development: Another area where AI will have a significant impact includes product design and development. Currently, many manufacturers rely on trial and error to develop new products. But with the use of AI and simulation software, manufacturers can test and refine product designs before they are ever built, reducing development time and costs while improving product performance and user-friendliness.
Worker experience: Despite what many fear, AI is not expected to displace human workers. In fact, its applications in manufacturing will complement and enhance their roles. AI can take over repetitive tasks, such as packaging or documentation, freeing workers to spend time on more complex or creative work. Additionally, AI can help workers complete tasks, such as machine repairs, by suggesting next-best actions. Integrated with IIoT sensors and wearable technology, AI can also improve worker safety. For example, predictive analytics can alert workers to potential safety hazards on the factory floor.
Empowering the workforce with AI
These are only a handful of the changes AI will bring to discrete manufacturers in the near future. With smart factory platforms, a company’s workforce can reap the benefits of more streamlined, less frustrating processes while increasing productivity, efficiency and profits.
– L2L is a CFE Media and Technology content partner.
Original content can be found at L2L.