Smart factories are about to get even smarter Business News

Space computing represents the next logical step in the digital transformation for manufacturers who want to take site optimization to a whole new level.

Smart factories are about to get even smarter. With the adoption of space computing – the digitization of spatial relationships between machines, people, and objects to identify their precise location and movement in 3D space – industrial companies have the opportunity to bring the site optimization to a whole new level.

To understand the magnitude of this opportunity, let’s first take a step back. Over the past decade, manufacturers have been able to achieve new levels of efficiency through Industrial Internet of Things (IIoT) programs. These have equipped the factory machines with intelligent sensors capable of reporting their status and use and receiving instructions from a distance.

These connected operations made it possible to better understand the operation of the installations. In turn, companies have been able to make significant strides in maximizing revenue, reducing costs, and improving quality – but the current benefits only extend so far, as the IIoT is lacking. still important spatial information.

In short, traditional IIoT suffers from blind spots when it comes to the physical execution of processes in a 3D environment. When something goes wrong, a worker often needs to be dispatched to diagnose the bottleneck – whether it’s an equipment malfunction, a coworker taking longer than usual to complete. a stain or a stray pallet at one end of the production line. It relies on that worker’s ability to infer the nature of the problem and resolve it, a process that can be random, error-prone, and extremely slow.

Eyes on the ground

Over the next decade, space computing promises to tackle these blind spots, providing smart factories and other industrial workplaces with more precise, non-human “non-human eyes on the ground”.

The term “space computing” was defined by Simon Greenwold, an MIT Media Lab alumnus in 2003, but it is only in recent years that new technologies have made his futuristic vision possible. These include artificial intelligence (AI) and machine learning; camera sensors and computer vision technologies to track environments; IIoT to monitor and control products and assets; and augmented reality (AR) to provide the human user interface.

Cameras with enhanced electronic resolution in space and AI in particular open up entirely new applications. New camera technologies don’t just capture two dimensions; they also measure distances between machines, people and objects. When you can link 3D images from multiple cameras and analyze the results, it is quite possible to create much more complete real-time simulations of reality. The result is a ‘digital twin’ of an entire factory, which can be monitored and controlled by interdisciplinary working groups, collaborating globally and remotely, as if they were all gathered in the factory.

While this vision seems extremely unlikely, it is important to recognize that space computing is already at work today. If you’ve ever eagerly followed the arrival of the next subway train on a passenger information screen or avidly followed the route of your food delivery from a local restaurant to your doorstep, you’ve seen it at work. Space computing is already present in the highly automated warehouses of e-commerce giants, where it is used to orchestrate the rapid collection of specific goods from miles of shelving by automated guided vehicles (AGVs) in the most efficient manner. possible to meet customer expectations for the next day of delivery.

But the potential use cases for space computing are much broader, especially in other industrial contexts. In short, when a manufacturing company can better monitor the interactions and movements of every machine, person and object involved in a process, it will have the information it needs to resolve the inefficiencies it identifies over time, the movement and use of space.

Human empowerment

This is good news for the bosses and their teams. Today, many managers rely on manual time and motion studies to optimize employee work – but according to one study by global management consulting firm Kearney, 43 percent say they are not confident in the results of those results. Using spatial computational analysis for continuous process improvement can more accurately and easily identify worker and production bottlenecks than previous methods. Spatial “heat maps”, for example, will give new clues to the time spent by a worker in a particular location at a particular stage of a workflow and the routes around the plant that are used most frequently. .

For workers, meanwhile, space computing connects them as consumers and suppliers to the digital ecosystem around them. It can, for example, locate for them where an error has occurred in the workshop and identify the best way to reach the hot spot.

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