Digital process tracking in real time
In almost all task areas of the chemical and pharmaceutical industry, there is a requirement for strict documentation. Pixel Robotics' digital process tracking can provide relief both here and in many other industrial sectors, especially logistics. Since its founding in 2017, the Munich-based startup has been offering its customers an innovative solution to recognize and document objects and work processes using artificial intelligence (AI) cameras. In doing so, applications such as real-time location & recognition or robots can use real-time recognition as the basis for completely new applications.
"Through our AI object recognition and tracking, we enable the digitization of all processes as well as personnel and material movements. And this in real time," affirms Dr. Christoph Plapp, co-founder and shareholder. "We then mirror the collected data into a so-called digital twin. Already today, we have about 30,000 professional users worldwide on our cloud platform w2mo.logivations.com."
In an interview with 5-HT, Christoph explains what exactly the Digital Twin is, what new applications it enables, and how 5-HT's support can drive future innovation in the chemical and pharmaceutical industries.
Observing work areas using AI cameras
"The AI cameras we place in work areas are each equipped with a machine learning computer. We can train their neural networks in such a way that they recognize the observed objects and processes in a decentralized manner, i.e. on edge. The compiled information subsequently serves as a basis with which we can do a variety of things," Christoph explains, describing part of Pixel Robotics' business model.
“All manufacturing companies and service providers whose logistics processes have a certain scope can profit”, Christoph affirms. Here, the rule of thumb is: "If more than 20 employees are involved in logistics, it makes economic sense to use it." This is because Pixel Robotics can facilitate, accelerate and make safer all processes in these industries, thereby reducing the workload.
The Digital Twin: a 3D map
Christoph explains the exact technology behind the Digital Twin by referring to a scene in logistics: "The classic activity in such an environment consists primarily of forklifts, employees, goods movements and storage locations. In contrast to conventional monitoring systems, our detection units, like humans, can accurately recognize relevant objects and their position in 3D space.
Using this knowledge, an accurate understanding of the movements and states of objects can now be produced in 3D," Christoph vividly describes.
This allows the camera, to return to the initial example, to recognize exactly where in a building a forklift or an employee is standing, for example.
Tracking, process documentation and storage - new applications through the connection of the digital twin with reality
Depending on the specific case, this enables several new applications. One of these is the tracking of objects and products: "Statistically, about 1/3 of the working time in logistics is used for the manual identification of products, i.e. by means of barcodes and scanners. Our technology can make this work easier, because since our AI cameras constantly track what was moved exactly when and where and how, products no longer have to be continuously identified. Thus, this enormous amount of work is eliminated," says Christoph.
On the other hand, processes can be documented, which means, for example, that it is possible to automatically count how many products an employee has loaded onto a forklift. Finally, Christoph explains that control systems can be set up in this way: "Here, our innovative, highly reliable autonomous driverless transport robots (AMRs) are in cooperation with the AI cameras. So they only need to see the immediate close-up area, because the AI cameras provide the overall view," he explains.
Above all, this makes it easier for the vehicles to navigate, because the overall view they are given means they know what is happening everywhere at all times. "For example, also what's around the next corner," Christoph adds.
If requested, the videos and tracks can be saved, which can be used for quality control, for example. This aspect is particularly relevant for the chemical and pharmaceutical industries.
Special applications in the chemical and pharmaceutical industry
As mentioned at the beginning, there is a strict documentation requirement in the chemical and pharmaceutical industry. "Our tracking can significantly simplify chemical work in this area because processes, such as in which order an employee does something or in what way something was added where, are visually recorded and, in case of doubt, saved as a track and a video. If an incident should occur, it can be analyzed afterwards at which point in the process a mistake was made," says Christoph. For this purpose, the tracks (stored positions of all objects) can first be automatically evaluated. If "anomalies" are detected, the videos can also be checked quickly and specifically.
In addition, tracking has other advantages: "Due to the introduction of the uniform national identification key for drugs, medical devices, and other common pharmacy products, known as the Pharmacy Central Number (PZN) for short, products have to be recorded again and again in the course of a process," Christoph lists as another example. "Our AI cameras can capture all barcodes at once, which is why we have already been able to provide our customers with considerable savings in this context. At the same time, this ensures consistency. Our customer Pharmlog reports here, among other things, savings in the process of over 30%", he adds.
Pixel Robotics: both software and hardware company
Essentially, Pixel Robotics derives its profits from the ready-to-use provision of recognition units and autonomous mobile robots, together with the associated software. "In addition, we often provide various services, such as one-to-one consulting. Although it was not explicitly planned at the beginning, we manufacture much of the hardware we use ourselves. This is the precondition for us to be able to really assure our customers of an end-to-end, operational solution," Christoph explains. The cost-effectiveness comes from the fact that identification activities are avoided and process documentation and transports are automated.
Many reasons to be proud
"The development of this technology, i.e. an overall integration that allows an end-to-end application to be built along with it, was certainly one of the biggest challenges, which is why we are particularly proud of this," says Christoph. "There is no other tool that is so widely used and proven around the world to create Digital Twins of logistics processes in warehouses and production," he adds.
In addition, Pixel Robotics has been able to grow into a team of more than a hundred since its founding four years ago without investors. In line with this, Christoph's advice to founders is: "There is nothing like customers, because as a rule nothing leads past them in the long term. Also, there are differences selling an idea to an investor, versus selling it to a customer. Sometimes investors think product ideas are 'cool' but they don't sell to customers."
Where Pixel Robotics sees itself in the future, thanks to the support of 5-HT:
Currently, the topic of expansion is on the agenda of the young startup: "Because we want to transfer our technology to more customers and applications, we are currently planning a roll-out. In addition, our team is currently working on automating processes as far as possible. Here's an example: Assuming a customer produces goods and wants to load them on pallets at the end of the process, then we can, in the future, automate this process right up to the loading of the truck," explains Christoph, at the same time describing another aspect that sets Pixel Robotics apart from the market competition.
From 5-HT, Christoph hopes to find wide contacts with companies. "We are particularly interested in concrete cases, of course, not just theory or applications in the lab," Christoph concludes.
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