InterviewPartnersPress

On the way to autonomous production with the Digital Twin

By December 17. 2018 No Comments

Intelligent factories that control themselves, anticipate malfunctions and react flexibly to production changes are the goal of Industry 4.0. To make production more flexible, it is not enough to equip machines and plants with sensors. The signal streams from the shopfloor must also be interpreted correctly in terms of production logic. The prerequisite for this is the use of a Digital Twins, which connects the digital planning world with the real manufacturing world.

Digital Twins not only enable planned production plants to be secured at an earlier stage and virtual commissioning to take place, but also, in conjunction with data from the shopfloor, enable them to be monitored during ongoing operation and allow for faster conversions in the event of production changes. They represent a digital image of the plant, which behaves like the real plant thanks to virtualized control. Via an IoT platform, the digital twin can be fed with the operating data of the real plant in order to simulate and optimize its behavior. An essential requirement of this Factory Twin is the ability to process huge amounts of sensor data in real time and to relate them to the manufacturing logic. It is only in this context that the data can be used for plant monitoring, process control and flexible adaptation to production requirements.

 

Figure 1: The Digital Twin can help to network the shopfloor and production logistics. All images: © ASCon Systems GmbH
Figure 2: How the digital twin can be used for plant optimization depends on the sensor technology.

 

Matthias Stach, Managing Director of ASCon Systems GmbH, which develops a real-time Digital Twin solution, explains why bridging the gap between digital planning and the real world of manufacturing is so important: “Without feedback of the data from the shopfloor, the planning status no longer fits in very quickly with what happens in production. Only if we succeed in establishing the link to the digital twin during the planning phase can we adapt the planning models during ongoing operation. Today there are technologies available for digitally mapping the operation of PLCs or controls that were not available to us five years ago”.

The implementation of a digital Factory Twins requires a close interaction of sensor, manufacturing and planning experts. For this reason, ASCon Systems cooperates with iNDTact GmbH in Würzburg, a system house specializing in sensor technology, and SG Engineering GmbH in Rothenburg odT, which develops production systems for automotive and special-purpose machine manufacturing. ASCon Systems contributes the ASCon Digital Twin to the cooperation, which Gartner believes has the potential to disruptively transform the market for Industry 4.0 applications. The American market researchers have therefore named the young company one of the “Cool Vendors 2018”.

Systems only partially digitalized

Companies in the automotive and other manufacturing industries face the challenge of bringing their products to market faster, as Stach says. “Above all, they have to speed up production start-up, otherwise they will be overtaken by newcomers who don’t have to worry about how to pay for their expensive equipment. A second challenge is making production more flexible: converting a production line for two vehicle models to a third one requires enormous effort today because the IT behind it is highly proprietary and the control logic is hard programmed into the system. In the case of Brownfiled systems, the additional problem is that the information is not sufficient for intelligent control. “In a sense, the eyes and ears are missing, and that’s where we quickly get to the sensors,” says Stach.

The complete digitalisation of the systems, including for example the electrical system, the control software or the PLC, is an essential prerequisite for setting up a digital twin, with which the functionality of a system can be reliably simulated in the planning phase and adapted in subsequent operation with less effort. Stefan Glanz, Managing Director of SG Engineering, confirms that this is still a long way off in reality.

Usually the mechanical design and simulation is commissioned first, but this is a purely kinematic simulation of the processes. Whether this can later be implemented and switched in terms of control technology is only known when the electrics and PLC come on board. “This means that we have to change the system concept again and again at 70 percent maturity,” says Glanz. “The Digital Twin is not only an enormous relief for us, it also saves the customer a lot of time during commissioning”.

 

Figure 3: The digital shadow as a preliminary stage of the digital twin.

 

The difficulty faced by system planners today is that customers provide them with a lot of information too late for the digitalisation of the systems and that the planning process is incomplete, error-prone and inefficient due to many media or system breaks. The solutions available today for CAD and digital factory planning are not continuous enough, criticizes Stach: “We want to link the digital plant models with the digitalization of all signal streams and all plant data, including the controller and PLC, so that the planners at customers, system suppliers, engineering service providers, etc. can access all data at any time via a simple interface.”

Simulation under real conditions

The digital twin of the ASCon system provides planners with all relevant data in a kind of library from which they can simply remove certain elements or function blocks and connect them with each other. The library contains not only modules for the equipment, but also, for example, for the sensors/actuators with the associated control logic, as far as they are relevant for value creation. This has the advantage, among other things, that changes to these modules are immediately effective in all plants in which they are installed. “The trick is to set up the semantic network in such a way that all data relevant to the functionality of a plant are mapped,” emphasizes Stach. This is the prerequisite for being able to simulate them under real conditions. “Putting the systems virtually into operation is not a completely new idea, but it failed at the first attempt because offline programming on the PC never worked as expected,” adds Glanz. The reason for this is that the mode of operation of the electronics could never be precisely simulated. They were always only approximations: “Only with the new generation of software for virtual commissioning is it possible to simulate the mode of operation down to the level of a fieldbus in real time. Real-time plays a very important role here. It allows hardware and software to be simulated under realistic conditions. This easily saves the user two months in the start-up phase, because he can work without all the test runs and adjustments”. In practice today it is the automation engineers who get the systems up and running and keep them running with a lot of manual effort. At the interfaces between the system, controller, PLC and IT systems, they ensure that the system does exactly what it is supposed to do. “The manual effort is so great because relevant control information is entered on a cell computer or even programmed directly on the system,” explains Stach. “Our goal is to make this information more accessible by taking programming to a higher level and making the control software easier to configure.”

New ideas for “intelligent” systems

SG Engineering expects new ideas for “intelligent” systems from the cooperation with iNDTact and ASCon. Glanz uses an example to illustrate why this intelligence has to be taken into account as early as the planning stage: “For example, you can install a sensor system in a welding device that uses the evaluation of the acoustic signals to check whether all the welding points for the connection between the base assembly and the side part are set correctly. Today, vehicles are ejected for this purpose in order to randomly check the weld spots. A sensor could eliminate the need for ejection and holding areas.” Clemens Launer, Managing Director of iNDTact GmbH, explains how the inspection of the welding spots works in principle: “When a welding spot is set, a structure-borne sound is generated which is a mixture of the natural vibration of the material and process noise. The parameters derived from this, such as signal shape, level and frequency components, are a kind of fingerprint of the process”. In order to check the quality of the weld spots in the running process, such “fingerprints” are stored in the Digital Twin so that each weld spot can be checked for deviations in real time. The iNDTact sensor systems measure vibrations and loads in combination with structure-borne noise (e.g. due to acoustic emissions) and thus record all important quantities that allow conclusions to be made about the condition of machines or processes. They register, for example, when material begins to break, record the movement of an object and the load it has been subjected to, detect leaks in vacuum foils, measure the distribution of forces and detect the wear of a ball bearing before it breaks, so that a spare part can be requested in good time.

Sensor signals alone are not enough

“Our sensor systems are capable of extracting specific information from the signals, but it is the combination with solutions such as those from ASCon Systems that enables them to be used effectively,” says Launer, who is no big friend of Big Data. The decisive factor is not so much the amount of data as its relevance. That’s why you need software that filters out irrelevant signals. Pre-filtering is important, among other things, because data transmission on the shopfloor reaches its limits. “While computers are now faster than the human brain when it comes to data processing, we are not yet ready for transmission,” adds Launer. “That’s why we constantly have to ask ourselves how much data a system can pass on to the next node. The first meter from the sensor unit to the gateway and from there to the servers is particularly critical. This is usually where the largest amounts of data accumulate.” The hype surrounding Industry 4.0 has led many companies to the misconception that it is sufficient to install sensors everywhere and then use artificial intelligence and/or big data analytics to turn the sensor data into something useful. After the first disillusionment, it has now become clear that context and manufacturing logic have to be known in order to extract added value from the data. “Our software brings exactly this context together with the functionality of the equipment. But we need close cooperation with plant planning and sensor technology in order to make the added value fully usable for our customers,” says Stach, summarizing the goal of the cooperation with iNDTact and SG Engineering.

 

Michael Wendenburg
on behalf of ASCon Systems GmbH
70176 Stuttgart, Germany
Phone: +49 711 2585890

info@ascon-systems.de