Artificial intelligence (AI) is already taking the world by storm, with almost every industry across the globe destined to be impacted in some way. Within manufacturing, AI is already being deployed for certain use cases and will continue to scale in 2025.
So far, we have seen the rise of the fourth industrial revolution (Industry 4.0), which has not only introduced significant opportunities for manufacturers but also helped with optimising processes through automation and robotics, reduced costs and streamlined operations. However, it is vital that these advanced technologies are deployed where there is a strong use case and a clear benefit.
Combined with human-centric and data-driven decision-making, advanced manufacturing technologies can help improve productivity, eco-efficiency, agility, supply chain resilience and speed to market as well as customer centricity. Success will boost adoption of these advanced technologies to reap more benefits.
As AI and machine learning (ML) technologies continue to evolve, it is crucial that organisations identify the right use cases for applying AI as a way to introduce greater efficiencies into existing processes, while also determining challenges on the factory floor that could be improved. Just one example of this is autonomous robots which are used to improve the speed and efficiency of routine operations, particularly in warehousing and manufacturing spaces. They work side-by-side with humans for added efficiency, and reduce the risk of employee injury in dangerous environments.
Advanced manufacturing technologies are quickly becoming essential tools for optimising the manufacturing process. For example, manufacturers can deploy AI and ML for predictive maintenance, which detects and alerts manufacturers to potential failures in their equipment so that they can be resolved with minimal downtime. AI and ML algorithms also support quality control and can provide insights into process optimisation to make the manufacturing process faster and more efficient.
The challenges
Products that require visual inspection are traditionally inspected by humans on the manufacturing line. Yet, as product demands and timeline speeds have increased, it becomes more difficult for the human eye to detect anomalies. In electronics manufacturing for example, printed circuit boards (PCBs) can be highly complex with hundreds, or even thousands of parts that are difficult for the human eye to see.
For greater accuracy at speed, AI is used to accurately validate components and their placement during high speed PCBA production, improving production quality and avoiding problems later in the product testing phase.
AI/ML-based defect detection systems will continue to use deep neural networks to detect defects that cannot be seen by conventional visual systems or human inspectors. This streamlines inspection processes, resulting in greater efficiency performance while optimising factory floor space by making room for other lines and solutions through the elimination of legacy inspection stations.
Transforming production
AI and ML technologies will continue to change the manufacturing industry, but will only realise their full potential if manufacturers embrace their adoption, and see the rewards.
While doing so demands a substantial investment of time, effort, and resources, as well as upskilling workers, the window of opportunity to integrate AI into production processes is closing fast—those who have not started risk being left behind.
Of course, there are still challenges ahead, from data readiness—where the quality of an AI/ML model is only as good as the training data—to quantifying the return on investment of AI/ML implementations, which can be tricky.
Organisations need to identify the right use cases for the business, find relevant data, process it, and then develop, fine-tune, and eventually deploy models. These steps all take time, but they are vital to reaping the greatest benefits.
Manufacturers today are successfully using AI and ML in certain areas of their manufacturing processes, and while hurdles remain, advanced technologies are at the forefront of Industry 4.0 and have the power to transform production and operations on every level.
Murad Kurwa
Murad Kurwa, VP, of Advanced Manufacturing Engineering at Flex.
