Shelves that label themselves, cooperation invirtual spaces, and high-performance computers that make autonomous decisions:In the Supply Chain department at Audi, this is no longer a future vision - asis demonstrated by selected examples at different production sites.
The company tested digital shelf labeling at theAudi plant in Győr, Hungary, for the first time last year. This new technologyis equipped with what are known as e-ink displays, which are also used ine-book readers, and offers significant added value. When names, numbers, or thearrangement of the parts in the shelf change, the logistics specialists nolonger need to update the labeling by hand. Information can also be displayedat short notice quickly, for example if a part is out of stock and is to bereplaced with a different part. Another advantage is that the digital displaysalways stay clean, do not generate any waste paper, and consume only verylittle electric energy, even in continuous operation. The German/Hungarianproject team is currently enhancing the technology. One of the goals is toimplement fully automatic updates. Series production in the near future isconceivable, including at other Audi sites. With digital shelf labeling, Audiis taking another step toward paperless order picking. When gathering parts,Audi employees already usually work with tablets and hand-held scanners today.
Digital helpers like these are just one exampleof the use of smart technology in the automotive manufacturer’s Logisticsdivision. “We are making targeted use of the advantages of digitalization atour production sites worldwide” says Dieter Braun, Head of Supply Chain. Thedriverless transport systems that have been in use at the Audi plants for manyyears are another example. They transport parts to the workstationsautomatically, for example in the electric motor production in Győr, where thereis no assembly line. They use laser scanners to orient themselves in theproduction hall and find the optimum route. This highly flexible procedure ismade possible by algorithms and machine learning, controlled by a smart ITsystem in the control station. This enables IT to keep track of all systems,all driverless transport vehicles, and the product, even without a fixedassembly line sequence.
At Pre-Series Logistics in Ingolstadt, Audi iscurrently the first automotive manufacturer to try out a new driverlesstransport system, which follows people around. The “Effibot” uses laser sensorsto detect the employee’s legs and follows them automatically at low speed. Allit takes is a touch of a button – the system requires neither complicatedadjustments nor a special infrastructure. It also offers an autonomous drivingfunction that allows the “Effibot” to head for previously defined destinationsindependently. The employees welcome the pilot project: They have an assistantthat helps them with their work and they no longer need to push order pickingtrolleys by hand.
Another smart solution brings Audi employeesworldwide together: They use virtual reality (VR) to work together group-wideand across locations in virtual spaces. In Packaging Logistics, for example,employees have been training with VR for several years. The training isdesigned like a video game and can be adapted to suit other activities as well– no programming skills are required. The company is also counting on VRtechnology in the production: As part of a pilot project, the logisticsplanners in Neckarsulm are currently testing how special containers can beplanned and tested entirely in a virtual space and without any physicalprototypes. These containers are used for particularly sensitive parts such aselectrics, headlights, or the windshield. They are custom-made for this taskand their planning takes a corresponding amount of effort. Developing thespecial containers with VR is less expensive and is also better for theenvironment.
The Smart Decisions team at Audi addresses evenmore complex planning processes. The experts “translate” a wide range of issuesinto mathematical models, and a high-performance computer uses these as a basisto find solutions for logistics-related problems, for example the externalstorage forecast. As part of the delivery process, certain models may have tobe put into interim storage for a short time. But which of the storage areas issuitable? Numerous factors play a part in answering this question: For example,the distance between the respective parking lot, the plant and the deliverydestination, the cost for transportation between these stations, or thecapacity of the parking lots. The mathematical model created by the SmartDecisions team allows these vehicles to be distributed optimally among thestorage areas. The prototype is finished and further development is underway –as is the case with numerous promising digital projects in Audi Logistics.