Plant-Wide Diagnosis: Cause-and-Effect Analysis Using Process Connectivity and Directionality Information

Production plants used in modern process industry must produce products that meet stringent environmental, quality and profitability constraints. In such integrated plants, non-linearity and strong process dynamic interactions among process units complicate root-cause diagnosis of plant-wide disturbances because disturbances may propagate to units at some distance away from the primary source of the upset. Similarly, implemented advanced process control strategies, backup and recovery systems, use of recycle streams and heat integration may hamper detection and diagnostic efforts. It is important to track down the root-cause of a plant-wide disturbance because once corrective action is taken at the source, secondary propagated effects can be quickly eliminated with minimum effort and reduced down time with the resultant positive impact on process efficiency, productivity and profitability. In order to diagnose the root-cause of disturbances that manifest plant-wide, it is crucial to incorporate and utilize knowledge about the overall process topology or interrelated physical structure of the plant, such as is contained in Piping and Instrumentation Diagrams (P&IDs). Traditionally, process control engineers have intuitively referred to the physical structure of the plant by visual inspection and manual tracing of fault propagation paths within the process structures, such as the process drawings on printed P&IDs, in order to make logical conclusions based on the results from data-driven analysis. This manual approach, however, is prone to various sources of errors and can quickly become complicated in real processes. The aim of this thesis, therefore, is to establish innovative techniques for the electronic capture and manipulation of process schematic information from large plants such as refineries in order to provide an automated means of diagnosing plant-wide performance problems. This report also describes the design and implementation of a computer application program that integrates: (i) process connectivity and directionality information from intelligent P&IDs (ii) results from data-driven cause-and-effect analysis of process measurements and (iii) process know-how to aid process control engineers and plant operators gain process insight. This work explored process intelligent P&IDs, created with AVEVA® P&ID, a Computer Aided Design (CAD) tool, and exported as an ISO 15926 compliant platform and vendor independent text-based XML description of the plant. The XML output was processed by a software tool developed in Microsoft® .NET environment in this research project to computationally generate connectivity matrix that shows plant items and their connections. The connectivity matrix produced can be exported to Excel® spreadsheet application as a basis for other application and has served as precursor to other research work. The final version of the developed software tool links statistical results of cause-and-effect analysis of process data with the connectivity matrix to simplify and gain insights into the cause and effect analysis using the connectivity information. Process knowhow and understanding is incorporated to generate logical conclusions. The thesis presents a case study in an atmospheric crude heating unit as an illustrative example to drive home key concepts and also describes an industrial case study involving refinery operations. In the industrial case study, in addition to confirming the root-cause candidate, the developed software tool was set the task to determine the physical sequence of fault propagation path within the plant. This was then compared with the hypothesis about disturbance propagation sequence generated by pure data-driven method. The results show a high degree of overlap which helps to validate statistical data-driven technique and easily identify any spurious results from the data-driven multivariable analysis. This significantly increase control engineers confidence in data-driven method being used for root-cause diagnosis. The thesis concludes with a discussion of the approach and presents ideas for further development of the methods

Automatic generation of Bond Graph models of process plants

This paper presents an application for the automatic generation of Bond Graph models. The basis for this automated creation is a modified plant model in the XML-format according to the IEC PAS 62424 (CAEX). The application developed in the programming language C, extracts and converts the information which is, then, stored in a model file meeting the requirements and structure of the modelling/simulation-language Dymola. Bond Graphs are used as the modelling technique since they do not distinguish between different energy domains and, therefore, combine several advantages against other modelling techniques. The developed application can be used for multiple purposes such as simulations, visualizations and other specific tasks that might emerge during the planning and operation process of plants and other engineering systems. © 2008 IEEE

Infrastruktur für den Online-Zugriff auf prozesstechnische Apparate ohne dedizierte Kommunikationsanschaltung

Der Betrieb von prozesstechnischen Produktionsanlagen wird stetig von verschiedenen Aufgaben begleitet, zum Beispiel der Steuerung und Optimierung der Produktion und der Aufrechterhaltung der Verfügbarkeit. Alle Gewerke, die sich mit dem Zustand der Anlage und des darin ablaufenden Prozesses beschäftigen, sind auf Daten angewiesen, die in der Anlage erfasst werden. Ein Großteil dieser Daten werden für die automatische Steuerungs-, Regelungs- und Sicherheitstechnik erfasst und darin in Echtzeit verarbeitet. Apparate und anderes Equipment sind zumeist nicht mit für deren Zustandsüberwachung dedizierter Messtechnik ausgestattet. Um Qualitätsmerkmale, Anlagenzustände oder Wartungsbedarfe erkennen zu können, müssen andere in der Anlage vorhandene Daten kombiniert und in Berechnungsmodellen kondensiert werden. Diese Methodik teilt sich in unterschiedliche Schritte auf: Datenakquise, Entwurf von Auswertemodellen, Modellintegration und Auswertung von Ergebnissen mit Ableitung von Aufgaben. Die vorliegende Arbeit ordnet sich in die Softwareaspekte dieser Methodik ein. Dabei versucht sie, die zentrale Frage „Wie könnte eine Infrastruktur auf Basis von verbreiteten Standardtechnologien aussehen, welche alle Schritte des Engineeringprozesses für freie Apparatemodelle automatisieren kann?“ anhand eines Vorschlags für eine Infrastruktur zu beantworten. Es wird eine Möglichkeit dargelegt, im Betrieb ohne Änderungen am bestehenden System kontinuierlich Daten für die Weiterverwendung in Apparatemodellen auszulesen. Der Entwurf und die Implementierung von Auswertemodellen wurde mit Hilfe eines entwickelten Werkzeugs unterstützt und dadurch die Struktur der Apparatemodelle vorgegeben, um eine einheitliche Modellintegration zu ermöglichen. Die Durchführung der Modellintegration erfolgte über die automatische Auswertung von Planungsdaten. Eine auf offenen Technologien basierende Ausführungsplattform für die Bewertungsmodelle wurde implementiert. Die Auswertung von Berechnungsergebnissen wurde über die Integration der Modelle in verbreitete, für Feldgeräte vorgesehene Standardwerkzeuge ermöglicht. Diese Infrastruktur ermöglicht es den verschiedenen Gewerken des Anlagenbetreibers, generische Bewertungsmodelle auf die Apparateinstanzen in der Anlage anzuwenden, und mit deren Berechnungsergebnissen ihre Aufgaben einfacher oder besser bearbeiten zu können. Nach einer Analyse der technischen Rahmenbedingungen wurde ein Konzept zur Modellintegration entwickelt und dessen Automatisierbarkeit diskutiert. Dieses Konzept wurde prototypisch umgesetzt. Es wurden Softwarekomponenten für den Betrieb sowie Softwarewerkzeuge für die Unterstützung sowohl der Erstellung als auch der Integration von Apparatemodellen entwickelt. Anhand dieser wurde Umsetzbarkeit des Konzepts überprüftOperating process plants goes along with different tasks, e. g. control and optimization of the production and maintaining availability of the plant. There are several subsections of operations who deal with the state of the plant and the processes it runs. They are all dependent on information which is gathered throughout the plant. Most of this data is acquired for the automatic control, regulation, and safety gear and is processed in real-time. Apparatuses and other equipment are usually not equipped with measurement devices which are dedicated to monitor their state. For being able to recognize specific quality attributes, states of the plant, or maintenance needs, the existing measurements have to be combined and condensed by calculations. This methodology can be split into the following steps: data acquisition, design of evaluation models, integration of these models, and assessment of findings including inferring actions. This thesis addresses software aspects of this methodology. It tries to answer the key question „How to build an infrastructure, which shall be based on common standard technologies, in which all steps to engineer equipment models may be automated?“ by proposing a concrete infrastructure. A technique has been designed to continuously acquire data for further processing in equipment models without any changes to existing systems. The process of design and implementation of equipment models has been supported by a purpose-built tool. This tool puts out the designed models in a uniform structure to allow uniform model integration. This integration has been automated using the plant’s engineering data. An execution platform has been developed based on open technologies. Infrastructure and model structure have been designed to easily integrate calculation results into standard tools for being able to use them in common work environments. It enables the different subsections of operations in a plant to apply generic equipment assessment models on concrete equipment instances. Using the output of the models, they shall be enabled to perform their task in an easier or better manner. The technical requirements and prerequisites have been analyzed. Using the resulting conclusions, a concept to integrate models has been developed and the options to automate it have been discussed. This concept has been implemented prototypically. This implementation includes a runtime component and two tools to support development of models and their instantiation. It has been used to prove the feasibility of the concept