The evolution of manufacturing to the smart factory, means factories filled with sensors collecting data for optimising performance. These cyber-physical systems mean that rather than relying on a single machine, businesses now have networks of connected machines using the Internet of Things (IoT) and edge data processing.
When Industry 4.0 smart machines talk to each other, they’re generating thousands if not millions of bytes of data. Managing this big data gives producers a holistic view of their operations. When combined with intelligence gained from analysing current and previous performance, it strengthens management’s ability to make faster, better decisions.
Edge data processing
Where to analyse and manage big data is also important to avoid issues such as security and latency. For most SMEs, edge data computing offers more control and immediacy than offsite cloud-based solutions. The reason edge is so important for producers is because of the need for fast decision-making and flexible operations. Combining edge processing with long term data storage in a cloud-based server also gives benefits.
Manufacturing is a very customer-oriented industry where balancing supply and customer demand are critical. A bottleneck due to machinery or inventory problems could disrupt the entire business, resulting in loss of company reputation and revenue.
A blog from Schneider Electric says, “Responding in real-time is so important and this is where the industrial edge data processing is imperative for any business. Having access to this data drives operational efficiency and improves productivity, especially when paired with machine learning. Manufacturers and logistics providers are always looking to improve costs, have better control over processes and improve deliveries.”
This is where latency become critical as a very short reaction time is essential. Businesses need to know when machine components need replacing to get the best final product and avoid waste or downtime. Every minute a machine is down costs the business revenue, especially if it affects a relationship with a customer. Connected machines generate data for analysing in real-time to provide predictive data analytics. A resilient infrastructure is essential for manufacturers, and flexible systems adaptable to change reduce disruption to the whole.
Another concern for manufacturing and logistics companies is security, especially when it comes to data. Attacks on Industrial IoT devices have been going on since 2005, and are increasing with many well-known organisations being hit.
With IoT devices and other connected endpoints within a plant or factory, there are several ways to steal data. Exploiting a vulnerability, for example, in a device connected to the whole network could result in taking down the infrastructure in single location. Malware deployment has also seen success, with the trojans shutting down industrial plant operations. Attackers can tamper with devices if they get physical access, sending the wrong information to the rest of the network or causing a malfunction to affect a production line.
Therefore, having a 360-degree view of infrastructure is critical to protecting data from hackers. Having software that tracks anything from light bulbs and machinery to trucks and inventory allows teams to identify potential threats. With the addition of machine learning, detection of threats can be a lot faster, in real-time.
Moreover, end-point security, especially in IoT devices, is imperative for the industrial edge. While central location servers and the cloud use encryption for protection, some IoT devices have known vulnerabilities. This means that regular patching is necessary, not only to protect company data but that of your customers. It is also necessary to stay compliant with the General Data Protection Regulation (GDPR) in Europe.
Bringing together all these components–a solid infrastructure that offers flexibility and real-time analysis through to secured data and devices–optimises manufacturing plants and their logistics partners. It allows them to provide products and services on a timely basis that meet with their customer’s approval.