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Logistics

Express drones:
delivered by air

They are now indispensable as flying camera tripods: multirotor drones, delivering fascinating images from a bird’s‑eye view. They are often also deployed on supply flights in inaccessible regions. Audi is now testing another interesting application: the automated transport of parts in factory halls.

The transport infrastructure in a traditional automobile plant that has grown over many years is quite often close to the limits of feasibility; there is usually no more space for additional transport paths. At Audi in Ingolstadt, most of the goods transport in series production takes place on conveyor vehicles moving along the floor; they transport the components to the desired place at the specified times. But the established system has its limits: The rare case of a subsequent order of parts, a so‑called urgent call‑off, can sometimes lead to long replacement times. In this case, the direct route through the air would be fast alternative.

Audi has not yet used the airspace in its factory halls for transport purposes, but that could change soon. For some months now, the logistics experts have been testing the use of transport drones for automated component transport in the factories. In early September 2016, the first drone was in the air for the transport of components in an Audi plant – carrying out test flights on a production‑free day.

The defined test route of the electrically powered unmanned aerial vehicles (UAVs) was mainly in a straight line through the hall of Audi A3/Q2 production. But it also included one change of direction to the right and two to the left. The drones used – with four enclosed rotors for safety reasons – carried out the preprogrammed flight maneuvers without any problems.

Under normal conditions and outdoors with a stable GPS signal, the short flights would not pose a significant technical challenge. But things are a little different in the hall of an automobile plant. Strict safety rules apply here, and the departments involved (Logistics, Assembly, Occupational Safety) place differing requirements on supply through the air.

The first tests and all flight maneuvers were carried out by specially trained pilots via remote control. Orientation was aided by new intelligent sensor technology, which was developed especially for the needs of the automotive industry. The drones’ flight speeds were initially limited to the speed of conventional floor‑vehicles: 2.2 meters per second.

The smart factory is gradually becoming reality at Audi. Further test during normal production should soon bring new findings on the various possibilities offered by drones. Additional scenarios include the transport of urgently required components, applications with camera-based repair and maintenance work, a follow-me function for trucks on the plant site and the high‑speed transport of urgently needed instruments such as a defibrillator for use in first aid.

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Big Data @ Factory Management:
predictive yard management

How can the management of a factory be optimized with the help of data? This question is being examined by an interdisciplinary project team in Audi’s Logistics department at the Neckarsulm plant. In this context, Audi’s logistics experts are using a database that is as large as possible. In addition to data from suppliers and shipping companies as well as information on traffic jams, the focus is also on data from other business units and from the entire production value chain – consisting of press shop, body shop, paint shop and assembly. The task of the logistics experts is to link up all of the available information, to analyze it and to collate it in a so‑called “data lake.”

SAP, Oracle and Microsoft Access databases, plus innumerable Excel spreadsheets: The enormous variety of data at large companies is unimaginable. Hitherto, every department at Audi has had its own specialized approach to what is now being brought together under the heading of “big data.” In order to make Audi fit for digital production, it is important to link up all data bit by bit. The computing power required for this project is enormous: The databases with up to 19 billion lines can only be handled with special software and tools.

But the potential of these databases can only be fully utilized when various sources of data are intelligently connected. The predictive yard management case study of the “Big Data @ Factory Management” project team at Audi shows what is possible with data. The project team is based in Neckarsulm and has been formed for one year to deal with various projects in that time. The team takes a startup approach: Not every promising idea has to lead to success; failures are also allowed.

The initial situation:
the space is filling up

As soon as an Audi is produced, it receives the status “ZP8” and is temporarily stored on a vacant parking space. This takes place according to clear logic: Depending on its ultimate destination, each car is parked for loading in a row on a defined lane. As soon as such a row has been completely filled with new cars, the shipping company receives the order, “Please pick up and deliver!” The shipping company then loads up to seven cars onto a truck and starts the journey to their destination.

The problem:
waiting for the shipping company

The shipping company is only commissioned to pick up the cars when one row on the parking area is completely full of new cars. The process until now has led to waiting times averaging 1.6 working days – and thus to high space requirements at the plants.

The idea:
predicting the pick‑up time

The new cars’ waiting times can be significantly reduced if the shipping companies receive their orders several hours before a row is full. Big data is very helpful here. By connecting vehicle‑specific information from production (How much longer will a certain model be in production?) with the real‑time status information from the shipping zone (How many cars with an identical destination are already in a row?), employees can forecast when the rows will fill up. Based on this data, the cars can be shipped earlier than before.

The future:
pick‑up exact to the minute

So the low loaders for delivering the new cars will already start their journey to the plant when the last car (or cars) of a row are still in production. In the ideal case, the truck will drive up to the row of cars exactly when another new Audi receives the “ZP8” status and takes up the last vacant space in the row.

In the unlikely case that a car is not ready at the predicted time and one space in the row is still vacant, the truck would go on its tour nevertheless. The advantage of permanently saving space due to shorter waiting times clearly outweighs the small risk of a truck not being fully utilized. 

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Forklift trucks and tugger trains: 

through the plant autonomously

Many challenges exist for logistics at Audi. The main focus is on the task of making materials available for production punctually and in the best quality. A maximum of process quality and security is to be achieved while keeping process costs as low as possible. A great opportunity is offered by automated transport systems, which are currently undergoing their first test‑drives at Audi. As of January 2017, they will operate in series production.

Automated transport systems of the latest generation can be applied safely and universally – also in existing structures and processes. Because unlike with conventional automation technology, they can adapt flexibly to changing conditions and can be connected with the Audi production system – a prerequisite for the next step towards smart logistics in the Audi factory of the future.

Autonomous forklift trucks
at the Logistics Center

At present, container transport at the Logistics Center at Audi in Ingolstadt only takes place with normal forklift trucks driven by trained employees. Driving into the high‑rack warehouse, picking up and putting down the transport containers – all of that is controlled from the driver’s seat.

Audi now plans to use autonomously guided forklift trucks within the packing operation for the delivery of small parts. This has several advantages: reduced space requirement, efficient transport processing and a lower risk of accidents at work. These advantages result from the interaction between innovative technologies such as a 3D laser scanner for navigation and several safety sensors. Scanner and sensors together create a 360‑degree safety radius around the forklift truck.

Several tasks have to be performed on the test run at Audi: The autonomous forklift truck has to independently place the containers, so‑called large‑load carriers, into a high rack and take them out again. The second steps are the autonomous delivery of the container to where it is needed and bringing back the surplus contents. The large variety of containers is a big challenge. The forklift truck easily recognizes obstacles on its route and waits until the way is clear; it then continues its transport task. If the autonomous forklift truck recognizes a problem in its routine, it independently warns the workstations involved about the kind of problem it faces and initiates action to solve the problem.

Data sheet: autonomous forklift truck
Type: Automated reach truck type FM-X 12 von STILL
Loading device: Fork
Lift: Five meters
Load: One ton
Navigation: Laser navigation via permanently installed reflectors
Traveling speed: 1.5 meters per second
Safety systems: Safety scanner (two at the front, one at the rear), Audi Safety Spot, acoustic warning signal, visual warning signal, emergency cutoff switch

Driverless floor conveyors
in the Logistics Center

In the future, Audi will produce the cockpit modules of the Audi A4 and Audi A5 models in the new Hall B of the Logistics Center in Ingolstadt. For the first time, driverless conveyors will be used that navigate in their environment and move independently with the help of suitable sensors and control algorithms.

Thanks to their advanced technology, the driverless floor conveyors can be used flexibly in different kinds of halls and on differing routes, because they do not need any artificial landmarks or guidance tracks such as induction loops set into the floor, magnetic grids or visual driving lanes. They use laser scanners to measure conspicuous orientation points in their surroundings, such as walls, pillars or shelves. By comparing with a digitalized map of the surroundings, they determine their position and navigate with high precision on freely programmable routes.

Furthermore, the driverless floor conveyors use laser scanners to monitor their routes ahead and evaluate the safety systems of the trailers they are towing. This avoids potential collisions with persons or objects. In conjunction with additional safety systems such as the Audi Safety Spot, (which projects a graphic warning signal onto the floor when reversing), visual and acoustic signals, direction indicators and emergency cutoff switches, driverless floor conveyors operate safely in the area of general traffic. This means that they do not need to operate in cordoned‑off areas.

Unlike conventional driverless transport systems, driverless floor conveyors have the advantage that they are developed from existing vehicles. Standard equipment such as trailers, existing structures and transport relations can generally be taken over without any major adaptations.

By connecting driverless floor conveyors with a central guidance control and its production system, Audi achieves more effectiveness in traffic control and material handling.

Data sheet: Driverless floor conveyor
Type: Automated tow tractor type EZS 350aXL from Jungheinrich
Loading device: Tow bar
Towing load: 5,000 kilograms
Navigation: Laser scanner, navigation in surroundings without reflectors
Traveling speed: Limited to six kilometers per hour (permitted speed in production at Audi)
Safety systems: Speed‑ and curve dependent laser‑warning monitoring and protective‑field monitoring, side and height monitoring, Audi Safety Spot, visual and acoustic warning signals, emergency cutoff switch

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Logistics app:
playing in perfect time

Making the complexity of a car factory visible and tangible also for non‑specialists, that is achieved by the new app “Audi Logistic Challenge.” This game for smartphones and tablets (iOS and Android) was developed by Audi and presents the subject of logistics in a completely new way. Players need a good overview, quick decisions, problem‑solving abilities and good timing. In short, all the basic requirements of a functioning car plant.

Every Audi can be individually configured by the customer – right down to the smallest equipment detail. This results in an almost unimaginable diversity of variants, and means that the individual steps of production in an automobile plant are a bit different every day. The material flows also differ from day to day. To ensure that these constantly changing requirements remain manageable, Audi exactly defines the sequence of cars in production. At the Neckarsulm plant, that takes place six days in advance. This allows Audi to guarantee that the right parts are available at the various points of production in the right sequence and at the right time.

What sounds like an extract from a textbook for logistics experts and seems perfectly logical in theory is very challenging for the players of “Audi Logistic Challenge.” They have to make sure that all parts are produced, assembled, temporarily stored and painted in the right color. At the same time, they have to keep an eye on the suppliers as well as on the return of empty containers.

The game’s difficulty increases steadily over 40 levels. The players quickly learn technical terminology from the world of logistics, with additional help from a glossary. After a short time, the app users become real logistics professionals and know what terms such as supermarket, string of pearls or quality of supply mean in a logistics context. Even the mysterious abbreviation AKL (automatic warehouse for small‑load containers) or JIS (just in sequence) soon become clear to the players of the “Audi Logistic Challenge.”

Like in a real car factory, also in the app, the lack of important components leads to the assembly lines coming to a standstill. The so‑called job‑stopper parts have to be installed or fitted at a certain time. They include for example the cable sets, which are essential for the functioning of a car’s electronics.

Logistics experts know: Only perfect synchronicity between material flow and vehicle flow allows the punctual production and delivery of a new car. In this respect, the virtual “Audi Logistic Challenge” does not differ from reality. The app will be available in the iOS App Store and the Android Play Store before the end of this year.

Fuel consumption of the models named above:

Fuel consumption of the Audi A3:
Combined fuel consumption in l/100 km: 7.1 – 3.7
Combined CO2 emissions in g/km: 163 – 98

Fuel consumption of the Audi A3 Sportback e tron:
Combined fuel consumption in l/100 km: 1.8 – 1.6
Combined CO2 emissions in g/km: 40 – 36

Fuel consumption of the Audi A4:
Combined fuel consumption in l/100 km: 7.6 – 3.7
Combined CO2 emissions in g/km: 175 – 95

Fuel consumption of the Audi A5:
Combined fuel consumption in l/100 km: 7.6 – 4.1
Combined CO2 emissions in g/km: 175 – 107

Fuel consumption of the Audi Q2:
Combined fuel consumption in l/100 km: 5.7 – 4.1
Combined CO2 emissions in g/km: 134 – 109

Fuel consumption of the Audi R8:
Combined fuel consumption in l/100 km: 12.3 – 11.4
Combined CO2 emissions in g/km: 287 - 272

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