Crosser
Canvas Category Software : Operational Technology : IIoT
Crosser designs and develops Streaming Analytics, Automation and Integration software for any Edge, On-premise or Cloud. The Crosser Platform enables real-time processing of streaming or batch data for Industrial IoT, Data Transformation, Analytics, Automation and Integration. The solution is built to fight complexity with simplicity through the Crosser Flow Studio, the visual design tool that enables teams to innovate faster than ever without developers. The software is ideally suited for Enterprise customers of various industries and applications, including Edge Analytics, Industrial Connectivity, Industry 4.0, Streaming Analytics, Hybrid Integration and Intelligent Workflows.
Assembly Line
Data-driven Maintenance Work Order Management with Crosser and AVEVA
The customer faced a significant challenge with its existing automated work order management system. This system relied on monitoring maintenance metrics using PLCs alongside predefined trigger points. AVEVA System Platform was responsible for initiating SAP to trigger specific work orders aligned with predefined work plans. However, this approach demanded manual adjustments to PLCs and the AVEVA System Platform each time a new device was introduced or new parameters were required.
Moreover, when a SAP work order was completed and counters needed to be reset to zero, manual connections to the PLCs were necessary, introducing operational risks and requiring substantial manual effort with each new device or reset. The existing approach not only carried operational risks with each change but also imposed significant manual labor for every new device and reset process.
IFS Cloud for Manufacturing: Unlocking the Power of AI for Intelligent Automation
The IFS Cloud for Manufacturing uses AI technologies to drive Manufacturing Execution Systems (MES) and Manufacturing Scheduling & Optimization, ultimately enhancing the efficiency and agility of manufacturing operations.
Nokia expands industrial edge applications to accelerate enterprises’ transition to Industry 4.0
Nokia launched four third-party applications for MX Industrial Edge (MXIE), which help enterprises connect, collect and analyze data from operational technology (OT) assets on a robust and secure on-premises edge. Asset-heavy industries can accelerate their digital transformation and benefit most from Nokia’s OT edge ecosystem-neutral approach, which taps into innovation from many top digitalization enablers. The new applications also leverage the GPU capability recently announced on Nokia MXIE, a powerful on-premises OT edge solution that helps process data closest to the source in real time while retaining data sovereignty.
Additions to the Nokia Industrial Application Catalog include Atos Computer Vision - Quality Inspector, Crosser, Litmus Edge, and Palo Alto Networks Next-Gen Firewall
How Edge Analytics Can Help Manufacturers Overcome Obstacles Associated with More Equipment Data
Big data is transforming a variety of sectors, ushering them into the era of Industry 4.0. However, having access to raw data and knowing what to do with it are at completely different ends of the digitalization spectrum. To help manufacturers understand, and overcome, some of the challenges associated with smart manufacturing, Martin Thunman, CEO and co-founder of leading low-code platform for streaming analytics, automation and integration for industrial IoT, Crosser shares his insight.
Towards Artificial Intelligence in Warehouse Automation
GEBHARDT Fördertechnik was founded in 1952 as a mechanical engineering company and has a long-standing experience in developing and manufacturing of system solutions for intralogistics. With this broad range of knowledge GEBHARDT can deliver everything out of one hand: from planning, design, implementation and continuous support up to an optimally integrated solution for warehouse management.
When a shuttle is in motion, vibrations can occur due to used parts at the shuttle or at the high rack. These vibrations are recorded with sensors CMS01 – Gebhardt own development - and then correlated with the driving parameters which come from control units. The different sources are merged with Crosser modules on the Edge and are the basis for calculating the health status of a shuttle. In addition, the data act as input for inhouse developed predictive maintenance models. This approach minimizes the risk of failure and reduces maintenance costs.
GEBHARDT’S architecture is based on the idea of processing data directly at the edge, transferring only relevant data to the back-office system or the respective cloud solution. This saves money and allows fast processing. The data is read and processed directly at the sensors. Processing steps include time series harmonization, data enrichment or data quality improvements. The automatic learning of the system takes place in a specific step of the process chain. It was important for GEBHARDT to use standard components which can be configured easily. The software components for the implementation, execution and maintenance of the processing steps are carried out with the help of the tools from Crosser: Crosser Edge Node™ and Crosser Cloud™.