In the tough automotive market, where efficiency is key, VOSS Automotive leads with fresh thinking. Recognizing the power of data in transforming manufacturing processes, VOSS launched a strong DataOps plan that focuses on easy data access, consistent data formats, and uniform KPI metrics. By enabling near real-time visualization VOSS not only makes sense of their data with context-rich insights, but also establishes a strong data foundation that enables diverse use-cases at scale more efficiently.
Using Litmus Edge, we've improved the integration and automation of our OT infrastructure management and deployment. This advancement helps us move towards unifying and standardizing our data practices throughout our organization.
Sacha Dannewitz, Chief Information Officer, VOSS Automotive
VOSS faced the challenge of managing and utilizing valuable data from a heterogeneous machine park, with data formats ranging from OPC UA to simple text files. Each machine produced a continuous flow of information that was underutilized due to lack of contextual insight and uniformity. Furthermore VOSS, like other companies that had experienced strong growth, was confronted with diverse, historically grown production systems that needed harmonization without having to rip them out and replace them immediately. Having tested different approaches to implement comprehensive digital transformation before, VOSS already knew they would want to combine extensive edge processing with cloud analytics for scalability and cost optimization.
VOSS decided to look for a robust DataOps platform that could seamlessly connect devices, standardize and model data for comprehension, carry out analytics at the edge and connect seamlessly to their cloud infrastructure. They also wanted to ensure the platform could support automated deployment and configuration processes - another key selection criterion, to optimize operational efficiency.
VOSS turned to Litmus to revolutionize not only how they capture, process, and leverage their operational technology data, but also how they manage the data infrastructure layer underneath. The result is a comprehensive Industrial DataOps strategy that encompasses:
Device Connectivity: Seamless connection to old and new production equipment alike for comprehensive data capture.
Context-Rich Data Modeling: Enrichment of machine data with context through
metadata definitions stored in Litmus Edge’ Device Hub. UNS naming conventions ensure standardized topic streaming for consistent data representation.
With Litmus Edge we have been able to add context to manufacturing data right at the source, calculate the desired KPIs at the edge and send them to the cloud – all fully automated within one workflow and one software piece. Thereby, we are replacing four steps with one, resulting in a more efficient, robust and agile data landscape.
Sebastian Rodtmann, Business Analyst Digital Manufacturing, VOSS Automotive
Automated KPI Calculations and Visualization: Extensive automation to calculate and standardize various operational KPIs across facilities, such as machine health, energy consumption, or OEE among many others.
Data Integration: Bi-directional MQTT connections that enable seamless data exchange between OT and IT systems. The outbound connection allows real-time, change-based data transfer minimizing data noise while the inbound connection from systems such as Enterprise Resource Planning (ERP) provides business critical data for additional KPIs and use cases.
Scalability: Establishment of a flexible yet standardized data infrastructure that can be readily extended to encompass additional production facilities.
The adoption of these strategies allowed VOSS to not only streamline their data processes but to also bring a new level of intelligence and efficiency into their manufacturing operations.
The impact of VOSS's automation-driven strategy through Litmus Edge was both immediate and long-term. By adding context to their data, VOSS was able to gain actionable insights that had previously been obscured by the sheer volume and complexity of information. The automation of KPIs brought standardization and efficiency, allowing for a more nuanced understanding of machine performance and energy consumption. Furthermore, the change of value feature ensured that only the most critical and relevant data was communicated, preserving bandwidth and focusing attention where it was needed most.
By focusing on data-driven approaches, VOSS has strengthened its role in manufacturing innovation and adaptability. Litmus Edge, acting as the cornerstone of their Unified Namespace (UNS) implementation, empowers VOSS to continuously transform raw data into operational intelligence, driving long-term success.
