To assist. Not replace.
How AI is bringing the latest innovations and enhancements to the production line (and beyond)
Manufacturing as a sector has always been quick to embrace change. From the Spinning Jenny, through Ford’s assembly line, to 3D printing, the quest for ever more efficient production processes has always pushed the industry to adopt change.
Artificial Intelligence has the potential to make the next seismic shift in production capability, so it’s no surprise that many major manufacturers are already adopting the technology in some shape or form. But AI’s capabilities don’t stop at the production line. They stretch across warehousing, supplier relations, and throughout the back office.
The image that AI in manufacturing conjures up is often of a production line devoid of human workers, with autonomous robots operating in their place. This is not Quantum’s goal: we believe that the success of any AI application is in its ability to work with, for, and alongside human workers, enabling them to do their jobs more safely, more efficiently, and in doing so adding more value to the business as a whole. By implementing our intelligent DPA, workforce time and effort is reduced on the mundane tasks, and allows them to spend more time on the valuable tasks.
For this to happen, we first explore a division of labour between mundane, repetitive or potentially dangerous jobs, perfect for machines, and higher value, bespoke tasks that need human oversight. With AI, ‘virtual workers’ in the form of physical robots or intelligent programme ‘bots’ are able to take responsibility for their workloads, learn and improve on their roles and instil a dynamic of ‘continuous improvement’ that often has positive impacts on human colleagues’ performance too.
AI can automate many of the asset-management tasks connected with complex production lines, co-ordinating scheduled maintenance to minimise disruption, extend asset lifecycles, and maintain optimum efficiency.
All manufacturers strive to keep their facility and critical production equipment operational. AI/ML contributes significantly to modernizing maintenance management, moving it from a responsive or regular maintenance posture towards a predictive or prescriptive one.
This popularity is driven by the fact that manufacturing data is a good fit for AI/machine learning. Manufacturing is full of analytical data, which is easier for machines to analyse. Hundreds of variables impact the production process and while these are very hard to analyse for humans, machine learning models can easily predict the impact of individual variables in such complex situations. In other industries involving language or emotions, machines are still operating at below human capabilities, slowing down their adoption.
With intellectual property and time-to-market becoming real areas of competition for many manufacturing businesses, it’s important that appropriate measures are taken against possible security breaches. But with high costs associated with physical security in particular, and the potential safety concerns for human security guards operating at night, this maintaining security can be a real challenge.
AI has proven itself again here to be a powerful ally to its human colleagues. By integrating with existing systems – CCTV, door passes, ANPR, it is able to build a detailed picture of ‘normal’ operations and recognize and escalate any behaviours or activities that seem incongruous. Meanwhile, AI can take this behavioural analysis to a granular level, building up a ‘Digital DNA’ for each user and application on your network that can then enable informed management of SSO, PAM, and more.
Manufacturing is more than just putting parts together. It’s coming up with ideas, testing principles, and perfecting the engineering, as well as the final assembly.
– James Dyson, Founder of Dyson
Enables fast and decentralized learnings to be gathered from IoT sensors on machines and wearables on staff to; improve production quality and yield, detect early signs of failure, and track health and safety.
Industrial robots, also referred to as manufacturing robots, automate repetitive tasks, prevent or reduce human error to a negligible rate, and shift human workers’ focus to more productive areas of the operation.
The extreme price volatility of raw materials has always been a challenge for manufacturers. Businesses have to adapt to the unstable price of raw materials to remain competitive in the market.
While humans are forced to work in shifts, robots are capable of working for 24/7 in the production line. With AI and robotics, businesses can scale rapidly to meet global demand.
A step towards AI means less human resource have to carry out dangerous and overly laborious work. As robots replace humans and perform normal and risky activities, the number of workplace accidents will decrease.
Although, bringing AI into the manufacturing industry would necessitate a huge capital investment, the ROI is significantly high. As intelligent machines start taking care of day-to-day-activities, businesses can enjoy considerably lower operating cost.
As AI takes over the manufacturing plant, and automates boring and ordinary human tasks, workers will get to focus on complex and innovative tasks. While AI takes care of unskilled labour, humans can focus on driving innovation and routing their business to advanced levels.
AI assembly lines are data-driven, interconnected, and autonomous, based on a set of parameters and algorithms that constantly update production guidelines to deliver the best possible end-products.