Process Monitoring in the Automotive Industry

The great advantage about the today’s IIoT oriented systems is the big range of solutions we are offered, and we are just seeing the top of the iceberg. Today’s market offers multiple options, even Open Source software ones which allows to easily gather real-time data and show it in dynamic fully customizable dashboards. This provides a huge advantage to the companies since they are not limited to one single solution from one manufacturer, but they have the whole range available, being possible even to integrate several DAQ systems with one centralized tool.

The advantage of these systems lies also on their flexibilty. Networked systems must remain flexible in order to be able to react to changes quickly. As a result of the openness of the today’s monitoring systems, production systems can be scaled and expanded more easily. Networks can be set up individually and flexibly with a few mouse clicks. Sensor Endpoints can be added to the network or easily displaced from one point to another with few to no impact for the manufacturer, and also no impact to the centralized monitoring platform. Through industrial communication standards, the information will be collected by strategic placed “Coordinators” within the factory, and transmitted to the monitoring platform.

The centralized platform manages the data and the actions to be carried out. It integrates networks beyond hierarchy levels, from the sensor in production through to the smartphone at business level. Production data can be transferred to the ERP system directly or saved in the cloud.

One key point when we talk about automotive industry is Quality. Nowadays everybody talks about quality and sells quality to their customers or to the final consumer. Actually, quality and costs are very interrelated, and therefore car manufacturers struggle to achieve their better results in both aspects. One of the advantages of the monitoring is it contribution to both factors, helping the manufacturer to identify the right spot where to drive an action before something goes wrong, which indirectly impacts in the final cost of the product (less quality incidents helps to a better line or machine performance – OEE – therefore better cost rates). It also helps in quality audits and traceability topics, being the manufacturer able to get all the machine / process important historical data with just few mouse clicks.

Challenges of process monitoring in the Automotive Plants

Maintenance is also one of the most challenging fields and with lot of improvement potential that we can have within the automotive industry. Maintenance costs are very high and it is very important to try to minimize them, and also to avoid machine crashes which impacts the whole manufacturing chain. The emerging market for Predictive Maintenance shows increasing growth as maintenance strategies move from what has been known as Condition-based Maintenance to Analytics- and IoT-enabled Predictive Maintenance. The transition toward Predictive Maintenance is mostly driven by new IoT monitoring platforms, low-cost secure cloud storage as well as analytics vendors that offer dynamic data models play. Predictive maintenance, a 1,5M$ market in 2016 is expected to grow to 11M$ by 2022.

Likewise, automotive security plays a big role within this equation. As a result of ever-more networked systems and the integration of different devices, it is necessary to make production IT more transparent to the outside. This consequently also lead to more security loopholes and points of attack being opened. Integrated security technologies and concepts such as Security by Design can support you to build-up secure production operations.