Software that senses what we need, supply chains that “think” in real time, and robots that respond to changes in their environment. The essence of the AI paradigm shift is the transformation of all business processes within an organisation. It is changing all the rules of how companies operate
There’s no doubt that the manufacturing sector is leading the way in the application of artificial intelligence technology. From significant cuts in unplanned downtime to better-designed products, manufacturers are applying AI-powered analytics to data to improve efficiency, product quality, and the safety of employees.
Today, humans and robots collaborate to produce breakthroughs, thanks to the “marriage” of advanced manufacturing techniques with information technology, and data and analytics.
Let’s have a look at key revolutions AI brings to the manufacturing industry:
Computer vision is used to optimise production lines and digitise processes and workers. In manufacturing, the application of ‘machine vision’, which automates image analysis and directs the robot workforce on the shop floor, is a growth area. On the production line, the most prominent use cases are for inspecting parts and products, controlling processes and equipment, and flagging ‘events’ and inconsistencies.
The trick is to take what would seem like the next logical step—sending those images to a person to make judgments and corrections—and hand that over to the machine as well.
Artificial intelligence is also changing the way we design products. One method is to enter a detailed brief defined by designers and engineers as input into an AI algorithm or “generative design software”. The brief can include data describing restrictions and various parameters such as material types, available production methods, budget limitations and time constraints.
The algorithm explores every possible configuration, before homing in on a set of the best solutions. The proposed solutions can then be tested using machine learning, offering additional insight as to which designs work best. The process can be repeated until an optimal design solution is reached.
Although digital twins have been around for several decades, it’s only been since the rapid rise of IoT that they’ve become more widely considered as a tool of the future. At its simplest, a digital twin is a virtual replica of a physical product, process, or system allowing it to be understood, analysed, manipulated, or optimised. Digital twins act as a bridge between the physical and digital worlds by using sensors to collect real-time data about a physical item.
Digital twins are getting attention because they also integrate things like artificial intelligence and machine learning to bring data, algorithms, and context together, enabling organisations to test new ideas, uncover problems before they happen, get new answers to new questions, and monitor items remotely.
In manufacturing, ongoing maintenance of production line machinery and equipment have a crucial impact on the bottom line of any asset-reliant production operation. Studies show that unplanned downtime costs manufacturers an estimated US$50 billion annually and that asset failure is the cause of 42 per cent of this unplanned downtime.
Predictive maintenance—as opposed to preventive maintenance—eliminates the guesswork as the machines report their conditions on an up-to-the-minute basis. It also saves businesses valuable time and resources, including labour costs, while guaranteeing optimal manufacturing performance. As with digital twins, sensors and advanced analytics embedded in manufacturing equipment make it possible. They enable predictive maintenance by responding to alerts and resolving machine issues.
You’re still on time, but the clock is ticking…
Missing the AI wave in manufacturing could mean getting stranded. If you’re stuck to the traditional way and don’t digitalise manufacturing processes, your costs are going to rise, your products are going to be late to the market, and your ability to provide distinctive value-add to customers will decline.
Yet it’s not too late to adopt the changes already taking place in the manufacturing sector, and run your business like a digital leader.
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by Ing. Joseph Micallef, Chief Operations Officer / Partner at BEAT Limited.