Core competencies
- Digitalization in production
- OT Security
- Data consistency
- Transparency on the shop floor
- Connectivity and collaboration in the supply chain
- Data Security
3 Steps towards the future
Step #1 Connecting and collecting real-time data
Connecting devices, sensors, and Internet of Things (IoT) technology will continuously collect and transmit data from various points in the production process. This results in faster action processes and improved efficiency.
In addition, advanced analytics and machine learning algorithms are integrated into various stages of production to optimize efficiency. It becomes a constant process to minimize patterns and errors and improve overall performance. Rapid adjustments to production parameters are enabled, downtime is minimized, and productivity is optimized. In addition, concepts such as artificial intelligence will provide further opportunities and significantly support the production of the future in the pursuit of perfection. With NeXonic, we are already a leader in digital production control and analysis. We will need to continuously evolve to meet growing demands.
Step #2 Aggregate multiple data sources to identify and optimize correlations between different areas
Aggregation using Business Intelligence will make supply chains highly integrated and collaborative. Companies can then benefit from in-depth insights to optimize their processes, minimize risks and make informed strategic decisions. BI will consequently play a crucial role in increasing the competitiveness and success of companies in a data-driven world. In the manufacturing of the future, BI will be an integral part.
Step #3 Data Security
The increasing interconnectedness of manufacturing will also reveal some challenges in terms of cybersecurity. The convergence of physical and digital systems will create not only numerous opportunities for companies, but also vulnerabilities and risks that can be exploited by cyber attackers. Cyberattacks on industrial systems could then also result in serious consequences, such as production downtime, economic losses and the exposure of sensitive data. Therefore, it is important for us not only to ensure the improvement and optimization of processes, but also their protection in order to operate sustainably in the long term.
KPIs
15%reduction in downtime
80%faster quality detection
30%increase in productivity
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