Siemens recently developed a digital asset portal designed to accommodate its customer’s demanding integrated asset information requirements. The portal integrates the COMOS asset management solution with real-time operational data of XHQ Operations Intelligence software and 3D visual context from COMOS Walkinside, with analytics from Siemens’ MindSphere cloud platform. The mobile- and web-based application provides a single environment for all these tools and the wide range of engineering, operational, asset, and other data they can access. This includes traditional sources and IIoT-enabled (sensor) data.
Digitalization of engineering and asset information can provide significant efficiency gains in engineering, maintenance planning and execution, troubleshooting and incident management. Potential benefits include:
- Improved engineering efficiency
- Increased quality time available for engineering and decreased time spent on data and IT tasks
- Shorter time to operational readiness
- Reduced downtime and avoided equipment damage
- Improved operational and asset performance
Challenges in Project and Asset Performance Management
Asset information is generated during both the engineering & construction and the operations & maintenance phases. Once the asset is operational, engineers, operators, and maintenance technicians all work on the same asset; ideally using the same consistent and up-to-date asset information to perform engineering design changes and plant improvements; operations and maintenance for day-to-day activities; and long-term asset management. This is challenging to achieve, particularly when projects and maintenance are done in collaboration with third parties.
In many plants, asset information is spread over a multitude of software applications, databases, and paper files. As a result, the asset information available is often inaccurate, out-of-date, inconsistent and/or poorly synchronized. This “information erosion” creates challenges and inefficiencies, further burdening an often already overstretched workforce. For example, when engineering or maintenance troubleshoot an operational issue or need to start a modification project, before doing any actual work they must first spend time determining the actual configuration, status, and performance of the equipment, availability of spare parts, etc. Further time is lost ordering missing parts or equipment. In other cases, excess spare parts inventories tie up working capital without delivering any benefit. All this increases project duration, mean times to repair, and both operational and capital expenditures. It could also lead to the wrong decisions being made in case of emergency that could cause major damage.
Digitalization involves making smart digital representations of physical information and objects. It has been quite a while since industry moved from paper mail to email, and from pneumatic and analog electronic networks and control to digital controls and fieldbus. However, paperless manufacturing approaches are still maturing.
In a seminal article, Dr. Thomas Tauchnitz, then head of process control engineering at a large European pharmaceutical company, addressed the project and asset performance challenge. He stressed that engineering and asset information must always be consistent and up-to-date. He defined three conditions to fulfill the requirements for a common engineering tool and database:
- All information is generated and maintained at only one location
- Existing knowledge is reused where possible, and
- The software tools stay interfaced while the plant is operating
This digital information (also called digital models or digital twins) about a process or piece of equipment can include engineering information, drawings, technical specifications, serial numbers, maintenance records, etc. Together the information describes the asset. Ideally, this digital asset lifecycle information is accurate, accessible, up-to-date, and provides visibility into previous changes and maintenance activities. Specific digital representations can mimic part of the properties of the physical objects. These are referred to as simulation models. They can be process simulation models, equipment simulation models, simulated controllers, or combinations thereof.
In brownfield installations, and when the asset information is scattered over multiple sources, it can be a challenge to build a consistent, up-to-date digital representation of the asset. Engineering drawings are often converted to “dumb” PDFs, which lack adequate detail and links among object attributes. This suggests that there are degrees of quality and “smartness” to digitalization. Ideally, asset information should be transformed into records structured according to an enterprise-wide asset information model that enables linking among object attributes and with workflows and rules.
Having digital engineering information and asset documentation across the asset lifecycle is a great step on the road of digitalization, however further progress is possible.
An Asset Portal Integrating Operations, Maintenance, and Engineering
The processes discussed above involve many different software tools, each with specific benefits. Additional potential benefits could be realized if they were all integrated seamlessly. Siemens created the single, integrated asset web portal solution, dubbed MindTwin, to provide users with seamless:
- Visualization of real-time asset performance information as XHQ Operations Intelligence solution typically provides
- Complemented with IoT sensor information channeled through MindSphere, plus
- Asset information and process flow diagrams originating from the COMOS engineering tool and asset information database, together with
- 3D contextual information from COMOS Walkinside
From any starting point, the user can investigate performance using these information sources to establish correlations and causal relationships. For example, the user can drill down from an equipment reference in XHQ to design information in COMOS and visualize the context of the location in the plant using COMOS Walkinside.
Siemens’ COMOS object-oriented database, in conjunction with engineering maintenance libraries and collaborative workflow modeling, enable Dr. Tauchnitz’s vision. COMOS enables different engineering disciplines to be integrated with operations and maintenance functions during all stages of the installation’s lifecycle.
For maintenance and operations activities such as dealing with performance issues, or when planning or executing maintenance, COMOS provides additional information on how the plant and the equipment was designed and maintained. This information is also available on mobile devices. Interfaces between COMOS and PCS 7 and other process control systems simplify the synchronization of control system configurations with the COMOS repository.
COMOS retrieves information from different sources. The tool can scan drawings intelligently and use instrumentation and equipment lists to link diagrams with data objects describing the physical objects. An engineer in the field can see on his or her mobile device if the information of a field equipment is available and up-to-date, and add information on the spot, if necessary. These functionalities can reduce the effort required to populate the database to a significant degree.
To understand the context of plant equipment or plan maintenance or inspection routes, it is critical to know the plant topology. COMOS Walkinside provides this context. This solution uses either the existing detailed 3D plant model (making it manageable on standard computing hardware); a 3D model based on digital photographs (as provided by Bentley’s ContextCapture); or, if available, authored models. Either way, it requires very little effort to create the 3D model for COMOS Walkinside. The software also provides immersive operator training and 3D design reviews. In this application, it runs in a web environment, and future releases will also support this capability.
For operations, a time-series database with graphical trending is installed in virtually all process plants. This provides a view of real-time and historical data. Manufacturing analytics or operational intelligence software, such as Siemens XHQ Operations Intelligence (XHQ), extract information from these historians and provide a high-level overview of real-time plant performance in concise graphical dashboards. Drill-down capabilities provide visualization of detailed plant performance. XHQ provides context to operational data by accessing a large array of other data sources, including process historians, MES, ERP, and LIMS. XHQ is currently available on premise and will soon also be available as a software-as-a-service (SaaS) solution on the MindSphere cloud platform.
Industrial IoT (IIoT) complements operations technology (OT), for example by transferring sensor information via a secured, unidirectional gateway to the cloud for performance monitoring or maintenance scheduling. IIoT can lower the cost of such applications compared to traditional OT, however adequate measures must be taken to help ensure industrial cybersecurity and plant safety.
Without an integrated workflow, IIoT could create new information silos. The Siemens MindSphere cloud platform enables this integrated workflow. It allows sensor data from production equipment to be visualized from new, IIoT-enabled equipment or from existing assets retrofitted with sensors connected via a gateway, such as the Siemens MindConnect Nano. It also provides analytics routines for predictive and prescriptive analytics using available process and equipment data. The strength of the solution is that operational data from XHQ, including sensor data via MindSphere, can be combined to perform analyses.
In brownfield installations, it’s important to be able to reduce the time and effort required to populate the asset information database. It’s equally important for plant engineering, operations, and maintenance personnel to be able to quickly and easily access accurate and up-to-date, in-context asset and operational information to troubleshoot issues, perform analyses, and improve performance. Common, integrated tools could reduce the time that engineers and others must spend searching for information, while also reducing data entry time and effort. These time gains can be transformed into quality time for design, operational improvement, or asset excellence, and would favor improved quality of decisions. In emergencies and during incidents, time savings could lead to faster and more appropriate decisions and measures, leading to reduced or avoided damage and lost production.
Outlook and Conclusion
As we learned, the asset portal integrating Siemens’ COMOS, XHQ and MindSphere, offers the potential for significant benefits compared to separate software components and opens new possibilities for the future. ARC recommends that users take a close look at the solution, provide feedback to Siemens, and adjust their strategic automation and application roadmaps.
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Keywords: Integrated Operations, Digitalization, IIoT, Analytics, Plant Engineering, Asset Management, Data Loading, Brownfield, Mobile Operations, ARC Advisory Group.