Hexagon Enriches Its Digital Twin User Experience with OSIsoft Connection

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By Michael Larner | 1Q 2020 | IN-5751

Hexagon’s HxGN SDx platform enables clients in the oil, gas, and chemicals sectors to develop digital twins. OSIsoft’s PI System looks to help manufacturers manage, curate, and gain insights from the data generated by sensors, devices, and processes in the production line. The HxGN SDx Connector for OSIsoft, which was released in February 2020, enables the firms’ mutual customers to integrate data collected via OSIsoft into HxGN SDx digital twins. HxGN SDx also connects to SAP Plant Maintenance and Leica TruView.

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Partnering to Deliver Digital Twins

NEWS


Hexagon’s HxGN SDx platform enables clients in the oil, gas, and chemicals sectors to develop digital twins. OSIsoft’s PI System looks to help manufacturers manage, curate, and gain insights from the data generated by sensors, devices, and processes in the production line. The HxGN SDx Connector for OSIsoft, which was released in February 2020, enables the firms’ mutual customers to integrate data collected via OSIsoft into HxGN SDx digital twins. HxGN SDx also connects to SAP Plant Maintenance and Leica TruView.

Digital twins’ ability to create a virtual model of a piece of machinery or the whole production line in order to, for example, understand the impact of alterations on performance in real time is a critical tool for plant managers and factory owners. However, to be successful manufacturers need to have all the relevant information readily available.

Hexagon’s release of the SDx Connector for OSIsoft is both evidence of manufacturers’ appetite for digital twins and an acknowledgement of the challenges in creating them.

Blending Historic and Real-Time Data

IMPACT


Data is often buried in different parts of an organization, and within incompatible applications, making the task of improving operational efficiencies more difficult. Applications such as SDx Connector work as a conduit between the applications.

OSIsoft’s PI System produces real-time insights regarding the condition of a piece of machinery as a result of collecting data from sensors, instruments, Distributed Control Systems (DCS), and Supervisory Control and Data Acquisition (SCADA) signals. For example, Italian oil and gas firm Eni S.p.A. uses PI System to collect real-time data concerning the conditions of its oil fields in order to feed simulation models.

The HxGN SDx Connector integrates the real-time data into Hexagon’s information management software, which verifies the data, incorporates it into the clients’ processes, and provides a master data set to create the digital twin from. The benefits of the process mean that by having all the data relate to current operations, engineering processes, and machine maintenance, clients can quickly obtain a single view of their operations. The digital twins provide insights regarding how to improve operational processes or the quality of the final goods. The key benefit of the digital twin is that it is more than a system of record because users can understand the potential impact of changes using real-time data.

Furthermore, investing in digital twins can have wider benefits by acting as a catalyst for change at clients. Data siloes cannot remain as internal teams and external suppliers need to collaborate for a digital twin to be a success.

Digital Twins Are a Key Component of a Digital Factory

RECOMMENDATIONS


Fueled by investments in telecoms bandwidth and cloud infrastructure, manufacturers have increasingly been looking to digital technologies to improve the Overall Equipment Effectiveness (OEE) inside their facilities. Predictive maintenance is an important facet of OEE, and digital twins can support predictive maintenance programs by helping plant managers understand the current and future condition of their machines.

However, manufacturers need to appreciate that a digital twin is not a software application that is bought off the shelf. Manufacturers need to digitize and automate data collection, rather than rely on staff to collect data on paper, and have devised a consistent language when referring to data (Fahrenheit or Celsius, seconds or milliseconds, etc.) and processes. Furthermore, data and process naming conventions need to be adhered to across both the organization and supply chain partners. For example, Hexagon is working alongside Hood Group, JV Driver, and PCL on supporting the Alberta Oil Sands projects.

Management needs to create not only a culture that values the data being generated but also one of collaboration between engineers, data scientists, and production line staff. In other words, the human element regarding the introduction of digital twins is as important to its success as the technology itself.

For Hexagon it will be important to create more connectors so that the company can enable clients to assimilate a broad array of data into their digital twins and enable Hexagon to build its addressable market by promoting the interconnections to the partners’ client base. This process needs to be done quickly, considering companies such as Dassault Systèmes, PTC, and Siemens are offering digital twin solutions as part of their software portfolios and the convenience offered by engaging with a single supplier for multiple applications.

 

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