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

Integration of 3D Feedback Control Systems for Fabrication of Engineered Assemblies for Industrial Construction Projects

A framework and methods are presented in this thesis to support integration of 3D feedback control systems to improve dimensional conformance during fabrication of engineered assemblies such as process piping, structural steel, vessels, tanks, and associated instrumentation for industrial construction projects. Fabrication includes processes such as cutting, bending, fitting, welding, and connecting. Companies specializing in these processes are known as fabricators, fabrication shops or fab shops. Typically, fab shops do not use 3D feedback control systems in their measurement and quality control processes. Instead, most measurements are done using manual tools such as tape measures, callipers, bubble levels, straight edges, squares, and templates. Inefficiency and errors ensue, costing the industry tens of billions of dollars per year globally. Improvement is impeded by a complex fabrication industry system dependent on deeply embedded existing processes, inflexible supply chains, and siloed information environments. The goal of this thesis is to address these impediments by developing and validating a new implementation framework including several specific methods. To accomplish this goal, several research objectives must be met: 1. Determine if 3D dimensional control methods are possible for fab shops that do not have access to 3D models corresponding to shop drawings, thus serving as a step toward deploying more integrated, sophisticated and higher performing control systems. 2. Discover ways to solve incompatibility between requested information from fabrication workers and the output information delivered by state-of-the-art 3D inspection systems. 3. Conduct a credible cost-benefit analysis to understand the benefits required to justify the implementation costs, such as training, process change management, and capital expenditures for 3D data acquisition units for fab shops. 4. Investigate ways to compare quality and accuracy of dimensional control data sourced from modern point cloud processing methods, conventional surveying methods, and hand tools. Methodologies used in this research include: (1) an initial literature review to understand the knowledge gaps coupled with informal interviews of practitioners from industrial research partners, which was revisited throughout the development of the dissertation, (2) development of a conceptual framework for 3D fabrication control based on 3D imaging, (3) development and validation of algorithms to address key impediments to implementation of the framework, (4) experiments in the fab shop environment to validate elements of the framework, and (5) analysis to develop conclusions, identify weaknesses in the research, understand its contributions, and make recommendations. By developing and testing the preceding framework, it was discovered that three stages of evolution are necessary for implementation. These stages are: 1. Utilization of 3D digital templates to enable simple scan-vs-3D-model workflows for shops without access to 3D design models. 2. Development of a new language and framework for dimensional control through current ways of thinking and communication of quality control information. 3. Redefining quality control processes based on state-of-the-art tools and technologies, including automated dimensional control systems. With respect to the first stage, and to address the lack of access to 3D models, a framework for developing 3D digital template models was developed for inspecting received parts. The framework was used for developing a library of 600 3D models of piping parts. The library was leveraged to deploy a 3D quality control system that was then tested in an industrial-scale case study. The results of the case study were used to develop a discrete event simulation model. The simulation results from the model and subsequent cost-benefit analysis show that investment in integrating the scan-vs-3D-model quality control systems can have significant cost savings and provide a payback period of less than two years. With respect to the second stage and to bridge the gap between what 3D inspection systems can offer and what is expected by the fabrication workers, the concept of Termination Points was further defined and a framework for measuring and classifying them was developed. The framework was used to developed applications and tools based on the provided set of definitions. Those applications and tools were further analyzed, and the results are reported in each chapter. It is concluded that the methods developed based on the framework can have sufficient accuracy and can add significant value for fabrication quality control