AspenTech Acquires Industrial Internet of Things Cloud-based Software and Edge Connectivity Assets of RtTech Software Inc.
IIoT Cloud and Edge Technology Will Expand AspenTech APM Solutions;
Represents Another Step in the Execution of Company’s Asset Optimization Strategy
The acquisition strengthens AspenTech’s asset optimization strategy by providing sophisticated cloud and edge processing technology that captures and aggregates critical data from assets throughout the plant and across the enterprise. This holistic view of every plant’s connected assets will extend the modeling and machine learning abilities of aspenONE® software to continually deliver accurate and actionable insights that optimize asset, plant and enterprise performance throughout the entire lifecycle.
RtTech’s Cipher software delivers on the IIoT promise of affordable, high performance connectivity for old, new, local and remote assets, without having to rip out and replace existing IT/OT (information technology/operational technology) infrastructures or business systems.
With Cipher, customers can eliminate the challenge of having to build and maintain their own IIoT infrastructure to connect their assets to the enterprise. Using the latest IIoT technology, Cipher works with almost any commercially available edge device. It supports a wide range of industry-standard communication and security protocols, enabling thousands of remote and local assets and devices (wired or wireless) to be connected to Cipher’s cloud-based data store for advanced analytics and asset optimization across the enterprise.
Cipher is a cloud-native application with multitenant capabilities
leveraging a modern architecture design, based on Microsoft’s Azure
- Cipher Portal: Used on-premise and in the Cloud to create a rich, aggregated data store of asset information for advanced analytics and asset optimization.
- Cipher Connect: Used “at the edge” to
collect, cleanse and analyze data from sensors and other data sources.
Cipher Connect supports a wide range of communication protocols
including MQTT, OPC UA, OPC DA, Modbus, BACnet, Ethernet IP,
Allen Bradleyand MT Connect for connecting almost any asset or device. Data collected by Cipher Connect can be written to a Cipher Portal on-premise or in a public or private cloud for advanced analysis and asset optimization. Data can also be written to enterprise systems such as historians, APM, EAM (enterprise asset management) and ERP (enterprise resource planning) for use in business analysis and applications.
In addition, the founder of RtTech,
Financial terms of the transaction were not disclosed.
“The acquisition of RtTech Software technology delivers another essential piece in support of our asset optimization strategy. RtTech provides best-in-class cloud-based software and IIoT connectivity, delivering capabilities that allow for data cleansing and local analytics at the edge. Combining RtTech’s capabilities with AspenTech APM software will offer our customers comprehensive solutions for Industrial IoT, Analytics and Machine Learning, with both on-premise and cloud-based deployment options.”
“We look forward to being a key part of AspenTech’s Asset Optimization strategy, leveraging our best-in-class Industrial IoT and cloud-based technologies. AspenTech will also provide us with the go-to-market capabilities to bring Cipher to a broader range of customers.”
AspenTech is a leading software supplier for optimizing asset performance. Our products thrive in complex, industrial environments where it is critical to optimize the asset design, operation and maintenance lifecycle. AspenTech uniquely combines decades of process modeling expertise with big data machine-learning. Our purpose-built software platform automates knowledge work and builds sustainable competitive advantage by delivering high returns over the entire asset lifecycle. As a result, companies in capital-intensive industries can maximize uptime and push the limits of performance, running their assets faster, safer, longer and greener. Visit AspenTech.com to find out more.