In the factory of the future, the value chain—made up of suppliers; component manufacturing; press, body, and paint shops; final assembly; and the customer—will be fully integrated, blurring traditional boundaries. (See Exhibit 2.) Throughout the value chain, manufacturing will be facilitated by the comprehensive integration of IT systems and the availability of all required production data. Within a company, this integration will strengthen connections across R&D, production, sales, and other functions. For example, Continental Tire has accelerated product testing by setting up a research and production facility in which all machinery is fully integrated using sensor systems and software. Such integration will also be possible outside a company’s boundaries, creating real-time connections with suppliers and customers. An OEM’s press shop, for example, will be able to adjust the pressing parameters for a specific coil on the basis of data provided by the supplier. Customers will be able to view the production of their vehicle in real time and request last-minute changes. Of automotive respondents, 87% said that integrated value chains will be relevant in 2030. These respondents overwhelmingly recognized the benefits: reducing costs as well as improving production flexibility, quality, and speed.
For each plant shop in this integrated value chain, automotive respondents provided insights into what they considered will be the most important elements in the dimensions of plant structure, plant digitization, and plant processes. (See Exhibit 3.)
Component manufacturing will benefit from greater flexibility and improved working conditions. For example, 80% of automotive respondents cited the relevance of decentralized production steering and, in particular, the automated adjustment of machine parameters in the factory of 2030. Nearly all of these respondents pointed to flexibility improvements currently arising from communication between machines and products. When producing camshafts, ThyssenKrupp assigns each one a Data Matrix code comprising product data. The production machines scan each camshaft’s code and make appropriate adjustments to their parameters prior to executing manufacturing tasks. Additionally, more than 70% of respondents noted that additive manufacturing (commonly known as 3D printing) will be relevant to component manufacturing in 2030. The main applications cited for additive manufacturing today are not only the creation of prototypes but also the printing of tools and spare parts.
The press shop will benefit from improved equipment effectiveness. Of automotive respondents, 93% cited the relevance of predictive maintenance in 2030. In fact, most respondents have implemented, or plan to implement within the next two years, their first applications of predictive maintenance. Schuler has developed robots that not only move parts along the press line but also monitor the condition of components and signal to workers if a replacement is required. Fraunhofer IWU is conducting research to determine how to enable a press to take corrective measures on the basis of information it receives about a raw material’s specific characteristics. Energy efficiency is expected to be relevant in 2030 by 85% of respondents. Škoda Auto will recover energy released during pressing by installing press lines that consume up to 15% less energy, compared with conventional systems.
Automotive companies are using new technologies to promote greater flexibility in the body shop. More than 80% of automotive respondents said that smart robots and production simulations will be relevant in the body shop in 2030. Already, automotive manufacturers are using smart robots that communicate with the car body and adjust their actions in response to the information received, while simulations assist in the planning and configuration of the shop’s layout. For the body shop that builds the Jeep Wrangler, Kuka and Microsoft have developed an intelligent system that not only connects all robots but also monitors their wear and tear. Magna has implemented a simulation program developed by Siemens that facilitates digital planning and replicates body shop processes, such as the interaction of up to six robots.
The paint shop will benefit from technologies that improve energy efficiency and the quality of the paint job. Of automotive respondents, more than three-quarters said that energy efficiency will be relevant in the paint shop of 2030. For example, in its Leipzig factory, Porsche currently uses waste heat from a nearby biomass power plant to provide a carbon-neutral supply of up to 80% of the paint shop’s heat requirements. Nearly three-quarters of automotive respondents noted that big data and analytics will be relevant. Most automotive companies have already started to use big data in the paint shop. The goal is to analyze data to identify the factors that cause variances in paint jobs and thereby improve quality.
Final assembly will benefit the most from a more flexible, multidirectional layout. Increasingly, automotive companies will have to offer a wider variety of car models to meet higher customer expectations and government regulations; a multidirectional layout will enable producing a wider variety while maintaining high production output. More than 90% of automotive respondents expect a modular line setup will be relevant in final assembly in 2030, with the flexible and cost-efficient replacement of line elements seen as especially important. For example, Toyota is introducing smaller and more flexible lines, leading to reduced line investments. Eighty-five percent of respondents cited the relevance of smart robots in final assembly. Companies are hoping for advancements in robotics that would allow these devices to take on tasks requiring high precision. And more than 75% of respondents noted that digital plant logistics will be relevant. This can be used, for example, to automatically replenish workstations with preassembled parts.
With respect to plant processes, lean principles will be important throughout the value chain in 2030. Two-thirds of automotive respondents expect that new technologies will enhance lean management and the continuous improvement of production processes. The use of production simulations, for example, will enable manufacturers to increase “pull” in production, thereby reducing waiting times and the work in progress. Augmented reality (for example, smart glasses) will support operators in executing assembly and maintenance activities by displaying operating procedures. By analyzing production data with advanced big data algorithms, manufacturers will gain a significantly better overview of each production step, allowing them to continuously improve production processes. Only 7% of automotive respondents expect that new technologies will make lean management obsolete.