Digital Technology Trends Driving the Auto Industry

Industry 4.0 is about applying smart practices and technology in manufacturing. It represents a significant shift in outlook and operations, particularly for the automotive industry. It builds on intelligent connected cloud technologies that allow diverse components and systems to work together. This creates a manufacturing framework that delivers consistently refined and scalable process improvements.

Smart automotive plants use robotics, industrial IoT sensors and machines, together with analytics, to gain a competitive advantage. However, there is an increasing requirement for low-latency and compute-intense decisions to be made near the points of operation. For this reason, there is a growing use of private and hybrid 4G/5G networks to support edge computing and AI on the plant floor.

Why 5G?

The use of private wireless networks using 5G technology supports the concept of small-footprint, low-latency robots and cobots that can be easily reconfigured without any expensive wiring to work safely near workers in assembly cells.

Low-latency messages, crucial to real-time decision making, allow a robot to communicate with a centralized operator framework about the required operations, providing manufacturers with greater visibility over an entire process.

5G networks also offer strong cybersecurity measures, protecting sensitive manufacturing data. 5G’s reliable and fast connectivity also is essential for integrating AI and edge computing into manufacturing operations.

Digital Twins Take Hold

As the growth of real-time data collection progresses throughout OEMs' manufacturing plants and along the supply chain, this will feed and create a rich continuum of data from the cloud to the machine edge. This requires a data tiering strategy that classifies, actions, and stores data and will be the feedstock for the emerging use of digital twin software.

A digital twin is a virtual representation of a physical object. This can be a machine at the lowest level, but it can scale to represent a real-time digital counterpart of an entire production facility, and the products produced. This tool has enormous potential for simulating new configurations and predicting the impact of changes in processes in the plant.

Real-time data collection is important for the auto industry because it allows for better tracking and tracing across the connected supply chain. This ensures that components, software variations, and updates are monitored throughout the lifetime of a vehicle and its digital twin, enhancing efficiency and reducing the risk of errors.

Shifting Gears

The Wards Intelligence Survey Q1 2021, which surveyed 262 automotive professionals in the North American automotive industry, provides valuable insights into the industry's approach to smart manufacturing and electric vehicle (EV) production. The survey found that 72% of organizations have some plans for smart manufacturing, and a further 45% anticipate investing more in this area.

However, the status quo of some of these processes may change if EV demand and production processes radically shift. Concerns related to sustainability and carbon footprint are already making OEMs pay attention to the sourcing and packaging of battery raw materials and components. This, combined with shipping costs, is forcing a review of the benefits of smaller local manufacturing and supply ecosystems.

The need to differentiate offerings against multiple players and adapt to local market requirements could also drive the use of additive manufacturing, or 3D printing, allowing increased variation later in production on a more build-to-order basis but with local delivery. 

^{The Journal From Rockwell Automation and Our PartnerNetwork™ is published by Endeavor Business Media.}