Industry 4.0 in the automobile industry

Industry 4.0 in the automotive sector is simply the hot topic of the moment in the automobile industry. Ultimately, networking machines and processes in an intelligent manner will provide value added for the entire automobile value creation chain in future – whether this is in production, sales or after sales. Logistics plays an important role in this process. It supports vehicle manufacturers and OEMs as they face challenges and makes a contribution to the ongoing development of the sector because it offers tailor-made solutions. According to Mercedes Benz,¹ smart logistics “not only covers the customer’s vehicle configuration and order, but also determining the need for parts and procurement and even the production and delivery of the vehicles. Expressed in visionary terms, ‘a vehicle that has been ordered looks for its production site and machine itself.’” – However, what progress have automobile manufacturers made in terms of this vision at the moment and what potential is available from networking in the view of the logistics specialist?

Companies often handle many processes manually at the moment – whether this involves phoning the freight forwarder to enquire where the goods are or walking through the warehouse for stocktaking purposes. Then there is the fact that many machines and warehouse systems are operated for relatively long periods of time because of the high level of initial investments. Although all of this is sufficient for smooth coordination between the individual production steps, it makes it difficult to achieve the kind of comprehensivenetworking that would be necessary for the use of Industry 4.0 in the automotive industry. Especially, if it is necessary to integrate different suppliers and the interfaces do not make this possible because of interruptions in various media. The quality of the master data is also often insufficient to create the necessary transparency along the supply chain. Forecasting the actual need for the individual products and their geographical location is often confounded by the fact that spare parts are still often managed on manual lists. As a result, OEMs purchase spare parts if a breakdown occurs, parts are hard to identify along the supply chain and data management between the supplier and the manufacturer does not work properly because of a lack of any connection with the machines in service.

“We’re fully aware of the flow of materials, the output from each individual workstation and the state of the machines. By documenting the process stages using PLC interfaces, but also deliberately using smart image and video monitoring of the processes, we know the parameters that have been used for each process stage and have ultimately been used for the end product. We can always make this data available to our customers, if required,” says Florian Karlstedt. If a car breaks down as a result of a faulty process, the logistics specialist can trace the cause of the problem in this way. Were the screws tightened properly and what torque measurements were used? The OEM is able to trace the problem easily if a claim for compensation is made and this normally prevents a general recall. If no proper digitalisation is available, all the vehicles that were manufactured at that time would have to be checked. By collecting data, the OEM can exclude this or retrospectively restrict the measures to the vehicles involved.

However, the Covid-19 crisis has triggered a change in thinking: faced with fragile supply chains, which have been disrupted on a long-term basis, many OEMs are seeking to be more resilient and more independent with regard to the situation in the market place. The measures being adopted here include extending local warehouse capacity or sourcing decisions in favour of European suppliers in order to transfer the value creation process for critical elements back to the local region. Having a transparent flow of information within the broadly dispersed network of suppliers will achieve genuine value added for the OEMs in future too.

OEMs should systematically start tackling the issue of collecting data for Industry 4.0 in the automotive industry in order to be able to make full use of the potential created by networking: this includes gradually digitalising the old data stocks and machine pools and viewing the topic of digitalisation as an essential requirement from the outset when making new investments. One field, which has often been neglected in the past, opens up real possibilities: collecting and analysingbig data, that is to say, very large, complex and short-lived quantities of data. This data comes from a wide variety of sources, for example, logistics systems and assembly facilities, and is initially gathered in unfiltered form. If data is compared for issues such as activities and existing resources, productivity and processed quantities, the company then knows how the data is changing on a daily basis and to what degree these changes can be predicted.

Big data can be used for particular areas, which then contribute to the entire process of Industry 4.0 in the automotive sector. One example is predictive maintenance. By monitoring the electricity consumption of individual components such as motors, it is easy to identify any discrepancies, resistance levels that are too high or voltage peaks. The manufacturer can therefore inform its maintenance employees about the problem even before the part breaks down. Measurable difficulties in assembly work discovered through using big data can also create improved quality management. Regular statistical process monitoring also benefits from the patterns that emerge from analysing the data: managers then recognise, for example, that a process may still be delivering acceptable products, but is gradually becoming unstable and will therefore tend to cause problems in the long term.

In order to be able to use the benefits of Industry 4.0 in the automotive industry, however, data is not the only thing that is required, but the ability to make this data useful. Logistics specialists support OEMs here by providing appropriate solutions in the field of information management. They include software for electronically exchanging data between different systems. The Production Traceability System (PTS) used by the logistics specialist, Rhenus, for example, processes incoming orders and assigns them to a workstation. The target figures associated with this are compared to the process parameters. As a result, it becomes clear whether working stages have taken place within the prescribed tolerances. If this is not the case, PTS blocks the part. The employees then have to rework the part or replace it. The Warehouse Management System (WMS) finally acts as the control framework around the entire flow of materials.

If we think ahead to strategically using data from production and logistics, parts will make their way through the factory automatically in an ideal automobile production environment – the key term here is “smart factory”. The OEM then knows at any time which parts are in stock, are in production, have been blocked or are in transit. And it knows which parts have actually been delivered by the supplier. Or what is the reason for the striking difference in the output of the early and late shifts? On this basis, it is possible to expose weak points or inefficiencies in the process. Bottlenecks come to light even before they actually occur on the production line. In principle, it is possible to pre-emptively reduce quality fluctuations and the breakdown of units or even prevent them entirely.

This would also make it possible to increase service quality for customers with a comprehensive introduction of Industry 4.0 in the automotive industry. If vehicles are ordered with special equipment, the sales department can exactly define the time of delivery. Here is one example: there are still ten special components in stock at the factory in Hamburg. As all ten of them have already been earmarked for use, one more would need to be obtained for this order. However, there are still some unused parts in stock at the factory in Munich. The customer receives information that the part would be available at this or that factory in a certain number of weeks from now. Put the other way round, the customer obtains transparent information about the delivery time because of the special equipment that it has ordered and can then consider separately whether it is prepared to accept this additional waiting time because of the individual equipment option. This transparency and flexibility guarantee competitiveness and future viability for the manufacturers in the long term and therefore safeguard their position as a digital pioneer in the market.