Increase data quality sustainably

Simplified teach-in when programming a robot via instructions in the physical action space.

© PTC

With the advent of IIoT, the use of machining centers on the factory floor has been optimized on the basis of MES concepts. As part of the introduction of the Manufacturing Execution System (MES, also known as process-oriented detailed production planning), the monitoring of individual production cells was centralized, several machines were monitored in parallel and their cycles were coordinated. Now the increasingly demanding activities of the workers need to be synchronized more precisely with the machine sequences. Spatial computing makes it possible to visualize process instructions with a clear spatial reference and thus make them easier to understand. For example, when programming industrial robots. Until now, these have been laboriously programmed via 2D interfaces (teach-in).
Understanding this complicated programming environment requires lengthy training. Spatial computing, however, significantly reduces the level of abstraction of the teach-in. Instructions can be intuitively linked to the physical action space of the robot via an interface. For example, by giving the robot a direction with an arm movement or placing waypoints with a smartphone.

Intuitive interfaces merge the digital and real worlds.

© PTC

If several machines and robots then have to be linked together, the advantage of spatial computing becomes even more obvious: in a factory where large numbers of sensors are in operation, it is still necessary to inspect vast quantities of time series in drop-down menus on the desktop - it is a real challenge to maintain an overview due to the different data structures. Spatial computing can show where an error has occurred on the store floor and an AR application can show the employee how to get there. This can significantly increase overall productivity and considerably reduce the frustration of individual workers due to unnecessary queries.

The digital twin is getting smarter

Necessary work steps are reported and error messages are displayed immediately.

© PTC

In addition to the machines, cameras can be used to track and evaluate the movements of materials, tools and workers. Whereas the actual routes taken by employees or goods were previously largely unknown, the entire production process, including assembly work, can now be precisely documented. This allows initiatives to be developed that make use of this knowledge. Spatial computing is thus further developing the digital twin of the factory. In future, not only will the processes in the machine be mapped in real time, but the digital twin of the worker can also be created: It will be possible to precisely record where a person is currently located, what they are doing and what skills they have. If, for example, it is known that a person can only lift 10 kg without harming their health, but is trying to lift twice that weight, the system automatically detects the conflict, warns the person concerned and requests assistance. This enables employers to better fulfill their duty of supervision.

Another remarkable aspect of spatial computing is its analytical capabilities: Via so-called spatial heat maps, companies gain insights into where workers are most frequently located during the workflow, where unexpected machine downtime occurs and which work routes are most frequented.

Spatially improved high-resolution cameras and machine learning have given rise to a completely new field of application. New camera technologies not only capture a 2D image, but also distance information. The most advanced method is based on the time-of-flight method: The time it takes for a beam of light to travel from the camera to the object and back again as a result of reflection is measured. The 3D images from several cameras can be linked together to create comprehensive real-time simulations of reality. AR applications can be projected onto these scenes.

Record processes over a longer period of time

Valentin Heun is Vice President Innovation Engineering, Reality Lab at PTC.

© PTC

The right to privacy is a major issue, currently once again brought into the spotlight by the GDPR. Since spatial computing also records people's movements, the protection of intimacy must be taken into account. The key issue here is which data is collected and how it is processed.

Currently, new processes are simulated in advance and then their duration is measured at the implementation site using a stopwatch. It has long been common practice to record the relevant data, for example in accordance with the specifications of the REFA Federal Association. On this basis, quantities are defined that are to be achieved per hour. The danger with this method, however, is that the measured times may unintentionally contain special effects: If a worker knows that they are being observed and their time is being logged, they are likely to exert themselves more and work faster. This does not take into account the fact that they may become tired and perform differently depending on their state of mind during the day. This is because only a short section under ideal conditions is mapped and converted into a target. If, on the other hand, longer stages are recorded with the help of spatial computing, a more realistic image is obtained. Spatial computing makes it possible to collect data much more precisely and thus better align the workplace and performance specifications with the worker's capabilities. Depending on guidelines and internal specifications, only de-personalized movement patterns are stored, but not video recordings in the sense of personal data.

A new era in the industry

Interlinked camera systems can be used to control entire production sites remotely. Interdisciplinary working groups can collaborate globally on the basis of the digital twin as if they were sitting together in one room - they can see themselves and move around in each other's virtual observation room.

PTC is investing in this technology, knowing full well that it is far from exhausted. For example, the company is making the Vuforia Spatial Toolbox available to the open source community so that they can develop their own programs and learn from each other. In addition to partners from industry, the system provider works closely with universities such as the Massachusetts Institute of Technology (MIT).

While spatial computing is already very successful in the e-commerce environment, further research and development is required for its effective use in industrial production. For example, PTC is intensifying its work on the Vuforia Spatial Toolbox in a lively exchange of knowledge with other protagonists in this field.