Artificial intelligence is infiltrating numerous sectors, from healthcare to e-commerce and everything in between. We’ve seen how AI is powering self-driving cars and trucks and letting businesses introduce automation that helps improve profits. Artificial intelligence is making a real impact on the automotive industry, especially from the manufacturing perspective. The technology has the potential to save the industry millions and is the subject of this blog post.
Specifically, we examine the benefits AI brings to the manufacturing industry and hone in on the following topics:
- Collaborative robots
- Predictive Maintenance
- AR and VR
Collaborative Robots and Adaptive Manufacturing
Robots have existed in manufacturing plants for quite a few decades now which has helped satiate ever-increasing consumer demand. By automating specific processes and workflows throughout the manufacturing process, suppliers can ship products quicker than ever. Occasionally, the introduction of such technology has resulted in the loss of jobs but often, this type of technology complements existing human capability, improves productivity and therefore profit.
Augmenting existing robotics and mechanical technology with layers of artificial intelligence is the next evolution in the manufacturing lifecycle and will pave the way for even more costs savings whilst, at the same time, augmenting human capability even further.
It’s hard to ignore that we’re in the middle of another industrial revolution, powered by artificial intelligence and automation. Like other industrial revolutions, understandably, the human workforce may feel threatened as its disrupted. But for those that retrain and can adapt, there will be substantial opportunities for both businesses and employees alike.Augmenting existing robotics and mechanical technology with layers of artificial intelligence is the next evolution in the manufacturing lifecycle Click To Tweet
Locus Robotics and DHL
Back in 2017, Locus Robotics (an order fulfillment robotics company) formed a partnership with DHL. The partnership saw Locus Robotics supply DHL with robots that worked alongside humans to help them locate and select products for shipment!
The introduction of the technology resulted in a decrease in product selection time, it also removed the probability of human error which consequently resulted in cost savings for DHL. Deploying solutions like this – at scale, has the potential to save manufacturers and e-commerce operations millions globally!
Baxter and Adaptive Manufacturing
Generally, robots in manufacturing plants must be programmed with a specific set of (what can be repetitive) instructions for them to complete the task at hand. These steps are followed to the letter. If a workflow changes, the robots must be taken offline, reprogrammed and then added back into the production line. All of this naturally impacts productivity and can result in lost income and so on.
Back in 2012, Rethink Robotics, a technology and robotics firm, created a robot solution called ‘Baxter’. Powered by a proprietary software solution, as well as vision and sensory cameras, Baxter can adapt to real-time events during the manufacturing process!
Blending advancements with robot technology and artificial intelligence like this brings real flexibility to the overall manufacturing process. It lets robots “learn” from human routines with minimal, if any downtime, all of which improve productivity and ultimately the bottom line.
Component Optimization with Predictive Maintenance
Generally, manufacturing equipment is maintained on a schedule (often manually), regardless of the condition of each component. This can occasionally result in wasted man hours for components that are operational, and that don’t need to be replaced, or in the worst-case scenario, components that need to be repaired can be missed out due to human error.
Imagine for a minute, you’re a courier that spends a lot of time on the road and your van could notify you when a component in your car was about to become faulty. Not when you’re on the road, but prior to any potential breakdown from occurring, imagine it was able to give you notice before you made your next set of deliveries.
A company called Predii are building technology to help create technology that will help make these things like this a reality. The firm have built a solution that can ingest multiple streams of binary data that include, but are not limited to position, speed, components temperature and so on.
These readings are then logged and complex AI algorithms are used to identify if readings are out-with “regular operating ranges”. Any readings that aren’t within regular operational ranges can be raised as alerts in driver’s dashboard for example.
Technology like this could also be integrated with manufactures workflow procedures to drive efficiencies that help identify when robotic components are about to fail. Coupled with IoT (Internet of Things) devices, manufacturers could receive notifications to help them better plan component production, thereby ensuring stock levels are sufficient and downtime is kept to a minimum when components need to be replaced. In scenarios like this, predictive maintenance, powered by AI, can help manufacturers better plan their maintenance roster and minimize any downtime, thereby helping them save valuable dollars.
The German car giant BMW are no stranger to introducing innovative technologies to streamline and improve their operational procedures. The giant generates torrents of data through its design, production, logistics and distribution network. To coordinate work, reduce costs and optimize its processes, work is split between 31 manufacturing facilities over 15 countries.
The firm have a system that automates the entire data flow, whilst at the same time, enhances decision making through each phase of the journey from the point where vehicles and components are manufactured until the point they’re sold and shipped.
BMW have also deployed predictive maintenance across its production lines so components can be replaced prior to them failing and bringing production lines to a halt. If stock levels are too high or too low, the system can also signal this to the relevant individuals and corrective action can be taken.
The manufacturing workflow often involves the constructions of multiple components in a predictable number of steps. The best manufacturing operations optimize this process and regardless of whether phones, televisions or even cars are being produced, prescribed instructions need to be documented and distributed with the teams that are responsible for the production of these goods.Blending advancements with robot technology and artificial intelligence brings real flexibility to the overall manufacturing process Click To Tweet
Occasionally, manufacturing instructions can hard to interprets or even out of date, a company called Vital Enterprise are helping to provide solitons to such challenges. The Californian firm have created augmented VR software for manufacturing plants that runs on smart glasses which provides employees with a voice-controlled, hands-free device. The device lets users view all assembly instructions and technical drawings for each component that must be built and saves time as human workers have all the information they need to hand – all through an intuitive display in the smart glasses. No more having to walk back over to workstations and look through instructions and so on. Users can also view associated information, drawings and videos from the previous person who completed prior tasks.
According to a recent report by DZone, the market for predictive maintenance is anticipated to grow from over $2 billion in 2017 to $10.9 billion by 2020. With, what looks like to be the mass adoption o this technology in the next few years, manufacturers will be able to optimize the workflows on their manufacturing processes and workflows and continue to save valuable dollars!
In this blog post, we’ve looked at how artificial intelligence has the potential to save manufacturers millions of dollars globally. We’ve looked at how the introduction of collaborative robots, powered by artificial intelligence and augment the human workforces existing capabilities and improve productivity.
We’ve also explored predictive maintenance solutions and how AI algorithms can be leveraged to forecast, with reasonable accuracy, when a component is due to become faulty, thereby optimizing the maintenance lifecycle aspect components.
Hopefully, by reading this blog post you’ve got a few ideas of your own as to how AI can be applied in the manufacturing industry!