oil and gas, energy transition, digital transformation

Realizing the AIoT Vision: When Artificial Intelligence Meets the Internet of Things

A Walk Through the Aspen AIoT Hub

5月 24, 2021

Frederic Bastien, VP of Product Management and R&D for AIoT Solutions delivered an insightful presentation at the recent AspenTech OPTIMIZE 2021 conference. He started off by introducing the overarching Aspen Digital Reference Architecture for Asset Optimization Portfolio and delved deeper to explain how the Aspen Artificial Intelligence of Things (AIoT) HubTM provides the Industrial AI Infrastructure for this vision.

 

Aspen AIoT Hub is the Industrial AI Infrastructure

He explained how the Aspen AIoT Hub underpins the Industrial AI strategy for all other AspenTech solutions by supporting the portfolio’s cloud-enabled Industrial AI apps, integrated solution roadmap and cloud convergence strategy. The premise behind this offering is that not every industrial organization has an army of data scientists. Which is why AspenTech has brought to market this fit-for-purpose, cloud-ready, built-for-industry infrastructure to embed AI into various domain-specific industrial applications - that empowers domain experts as well as data scientists to unlock the business value in industrial data. He articulates how Industrial AI is very different from the generic AI solutions offered by various horizontal cloud vendors – while being well-suited to delivering measurable business outcomes in the industrial sector. It is this purposeful blend of data science and AI/ML, advanced analytics together with the domain expertise, which includes first-principles engineering as well as the underlying physics, chemistry and math parameters packaged into domain-specific, software-at-scale applications that deliver real-world value.

 

 

A Walk Through the Components of the Aspen AIoT Hub 

Fred then went deeper into the different architectural components of the Aspen AIoT Hub full-stack solution on which AspenTech is building its next-gen of Industrial AI applications, and which enables customers and partners to collaborate to build their own AI-enabled, data-rich applications using a wide range of capabilities.

First off, on the data historian side (Aspen InfoPlus.21®), AspenTech has delivered a new evolution called Aspen MES Collaborative™ which enables users to set up their cloud-ready, enterprise-level historian that works hand-in-hand with plant and site historian products. By deploying the Aspen MES Collaborative, not only greater capacity, performance, and scalability are achieved, but also smaller sites benefit; and furthermore, the inherent high-availability capabilities can eliminate the ripple effect of data loss and other data management issues. 

Second, Frederic spoke about the compelling enhancement to Aspen Cloud ConnectTM. In V12 and V12.1 AspenTech introduced a number of capabilities from the security and performance standpoints, with the gRPC connectivity to IP.21 as well as several source and destination plug-ins. In V12.1, AspenTech has added new capabilities and functionality that support the integration of data across other third party historians, including OSIsoft PI. Some plants working with IP.21 and others with the PI system are now able to connect to historians seamlessly and bring all the tags, timeseries and the contextual data into the destination servers with the help of Aspen Cloud Connect. In addition, Aspen Cloud Connect is now the integral part of Asset Performance Management (APM) and provides new connectors to Aspen Mtell®. If customers need to do advanced analytics, it is not enough to just have a set of tags with labels. They need to know the context around it, what asset it belongs to, and what is happening around that set of tags and labels. Contextual data can be pulled across Aspen products such as Aspen Manufacturing Master Data Manager (mMDM) and Aspen Production Record Manager (APRM) or from third party sources, and can be brought into the Aspen cloud-based historian or the Aspen Cloud storage of the Aspen AIoT Hub, driving the integration and mobility of industrial data across the plant as well as the enterprise. 

 

 

Third, moving to Aspen Enterprise Insights™, Frederic mentioned that this is the solution for digital workflows enabling enterprise governance – facilitating the path from data to decisions. Within the interface of Aspen Enterprise Insights, users can click-through without coding and create new apps and workflows to fit their business processes. A ready-to-use template of a solution can be deployed in different organizations without recreating anything. If users are building a set of pipelines, workflows, or communities to manage capital projects, they can replicate a solution with just a click-of-a-button within Aspen Enterprise Insights. AspenTech also introduced version management of those workflows so that users can modify workflows over time and keep track of different versions. Aspen Enterprise Insights also unveiled a new use case for the Pharmaceutical industry, in particular, where there is a big need for audit trails and compliance. 

All the benefits mentioned above are available both in the Software-as-a-Service (SaaS) deployment model, where Aspen Enterprise Insights is entirely running on the Aspen cloud infrastructure, and in the hybrid cloud deployment, where the application is managed by AspenTech but the data remains on-premise on a server or on a VPC on Azure or AWS. This highlights one of the most important benefits of Aspen Enterprise Insights, which is greater flexibility while delivering accelerated time-to-insights.