Reducing human effort in engineering drawing validation.

Oil & Gas facilities are extremely huge and have complex industrial structures that are documented using thousands of printed sheets. During the last years, it has been a tendency to migrate these paper sheets towards a digital environment, with the final end of regenerating the original computer-aided design (CAD) projects which are useful to visualise and analyse these facilities through diverse computer applications. Usually, this was done manually by re-sketching each page using CAD applications. Nevertheless, some applications have appeared which generate the CAD document automatically given the paper sheets. In this last case, the final document is always verified by an engineer due to the need of being a zero-error process. Since the need of an engineer is absolutely accepted, we present a new method to reduce the required engineer working time. This is done by highlighting the digitised components in the CAD document that the automatic method could have incorrectly identified. Thus, the engineer is required only to look at these components. The experimental section shows our method achieves a reduction of approximately 40% of the human effort keeping a zero-error process

Optical character recognition on engineering drawings to achieve automation in production quality control

Introduction: Digitization is a crucial step towards achieving automation in production quality control for mechanical products. Engineering drawings are essential carriers of information for production, but their complexity poses a challenge for computer vision. To enable automated quality control, seamless data transfer between analog drawings and CAD/CAM software is necessary.Methods: This paper focuses on autonomous text detection and recognition in engineering drawings. The methodology is divided into five stages. First, image processing techniques are used to classify and identify key elements in the drawing. The output is divided into three elements: information blocks and tables, feature control frames, and the rest of the image. For each element, an OCR pipeline is proposed. The last stage is output generation of the information in table format.Results: The proposed tool, called eDOCr, achieved a precision and recall of 90% in detection, an F1-score of 94% in recognition, and a character error rate of 8%. The tool enables seamless integration between engineering drawings and quality control.Discussion: Most OCR algorithms have limitations when applied to mechanical drawings due to their inherent complexity, including measurements, orientation, tolerances, and special symbols such as geometric dimensioning and tolerancing (GD&T). The eDOCr tool overcomes these limitations and provides a solution for automated quality control.Conclusion: The eDOCr tool provides an effective solution for automated text detection and recognition in engineering drawings. The tool's success demonstrates that automated quality control for mechanical products can be achieved through digitization. The tool is shared with the research community through Github

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

Field Evaluations of Low-Frequency SAFT-UT on Cast Stainless Steel and Dissimilar Metal Weld Components

This report documents work performed at the Pacific Northwest National Laboratory (PNNL) in Richland, Washington, and at the Electric Power Research Institute's (EPRI) Nondestructive Examination (NDE) Center in Charlotte, North Carolina, on evalutating a low frequency ultrasonic inspection technique used for examination of cast stainless steel (CSS) and dissimilar metal (DMW) reactor piping components. The technique uses a zone-focused, multi-incident angle, low frequency (250-450 kHz) inspection protocol coupled with the synthetic aperture focusing technique (SAFT). The primary focus of this work is to provide information to the United States Nuclear Regulatory Commission on the utility, effectiveness and reliability of ultrasonic testing (UT) inspection techniques as related to the inservice ultrasonic inspection of coarse grained primary piping components in pressurized water reactors (PWRs)

Understanding urban rainfall-runoff responses using physical and numerical modelling approaches

This thesis provides a novel investigation into rainfall-runoff processes occurring within a unique two-tiered depth-driven overland flow physical modelling environment, as well as within a numerical model context where parameterisation and DEM/building resolution influences have been investigated using an innovative de-coupled methodology. Two approaches to simulating urban rainfall-runoff responses were used. Firstly, a novel, 9 m2 physical modelling environment consisting of a: (i) a low-cost rainfall simulator component able to simulate consistent, uniformly distributed rainfall events of varying duration and intensity, and; (ii) a modular plot surface layer was used. Secondly, a numerical hydroinundation model (FloodMap2D-HydroInundation) was used to simulate a short-duration, high intensity surface water flood event (28th June 2012, Loughborough University campus). The physical model showed sensitivities to a number of meteorological and terrestrial factors. Results demonstrated intuitive model sensitivity to increasing the intensity and duration of rainfall, resulting in higher peak discharges and larger outflow volumes at the model outflow unit, as well as increases in the water depth within the physical model plot surface. Increases in percentage permeability were also shown to alter outflow flood hydrograph shape, volume, magnitude and timing due to storages within the physical model plot. Thus, a reduction in the overall volume of water received at the outflow hydrograph and a decrease in the peak of the flood event was observed with an increase in permeability coverage. Increases in the density of buildings resulted in a more rapid receding limb of the hydrograph and a steeper rising limb, suggesting a more rapid hydrological response. This indicates that buildings can have a channelling influence on surface water flows as well as a blockage effect. The layout and distribution of permeable elements was also shown to affect the rainfall-runoff response recorded at the model outflow, with downstream concentrated permeability resulting in statistically different hydrograph outflow data, but the layout of buildings was not seen to result in significant changes to the outflow flood hydrographs; outflow hydrographs appeared to only be influenced by the actual quantity and density of buildings, rather than their spatial distribution and placement within the catchment. Parameterisation of hydraulic (roughness) and hydrological (drainage rate, infiltration and evapotranspiration) model variables, and the influence of mesh resolution of elevation and building elements on surface water inundation outputs, both at the global and local level, were studied. Further, the viability of crowdsourced approaches to provide external model validation data in conjunction with dGPS water depth data was assessed. Parameterisation demonstrated that drainage rate changes within the expected range of parameter values resulted in considerable losses from the numerical model domain at global and local scales. Further, the model was also shown to be moderately sensitive to hydraulic conductivity and roughness parameterisation at both scales of analysis. Conversely, the parameterisation of evapotranspiration demonstrated that the model was largely insensitive to any changes of evapotranspiration rates at the global and local scales. Detailed analyses at the hotspot level were critical to calibrate and validate the numerical model, as well as allowing small-scale variations to be understood using at-a-point hydrograph assessments. A localised analysis was shown to be especially important to identify the effects of resolution changes in the DEM and buildings which were shown to be spatially dependent on the density, presence, size and geometry of buildings within the study site. The resolution of the topographic elements of a DEM were also shown to be crucial in altering the flood characteristics at the global and localised hotspot levels. A novel de-coupled investigation of the elevation and building components of the DEM in a strategic matrix of scenarios was used to understand the independent influence of building and topographic mesh resolution effects on surface water flood outputs. Notably, the inclusion of buildings on a DEM surface was shown to have a considerable influence on the distribution of flood waters through time (regardless of resolution), with the exclusion of buildings from the DEM grid being shown to produce less accurate results than altering the overall resolution of the horizontal DEM grid cells. This suggests that future surface water flood studies should focus on the inclusion and representation of buildings and structural features present on the DEM surface as these have a crucial role in modifying rainfall-runoff responses. Focus on building representation was shown to be more vital than concentrating on advances in the horizontal resolution of the grid cells which make up a DEM, as a DEM resolution of 2 m was shown to be sufficiently detailed to conduct the urban surface water flood modelling undertaken, supporting previous inundation research

Systems Engineering: Availability and Reliability

Current trends in Industry 4.0 are largely related to issues of reliability and availability. As a result of these trends and the complexity of engineering systems, research and development in this area needs to focus on new solutions in the integration of intelligent machines or systems, with an emphasis on changes in production processes aimed at increasing production efficiency or equipment reliability. The emergence of innovative technologies and new business models based on innovation, cooperation networks, and the enhancement of endogenous resources is assumed to be a strong contribution to the development of competitive economies all around the world. Innovation and engineering, focused on sustainability, reliability, and availability of resources, have a key role in this context. The scope of this Special Issue is closely associated to that of the ICIE’2020 conference. This conference and journal’s Special Issue is to present current innovations and engineering achievements of top world scientists and industrial practitioners in the thematic areas related to reliability and risk assessment, innovations in maintenance strategies, production process scheduling, management and maintenance or systems analysis, simulation, design and modelling

NASA SBIR abstracts of 1991 phase 1 projects

The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included

Antimisting kerosene atomization and flammability

Various parameters found to affect the flammability of antimisting kerosene (Jet A + polymer additive) are investigated. Digital image processing was integrated into a technique for measurement of fuel spray characteristics. This technique was developed to avoid many of the error sources inherent to other spray assessment techniques and was applied to the study of engine fuel nozzle atomization performance with Jet A and antimisting fuel. Aircraft accident fuel spill and ignition dynamics were modeled in a steady state simulator allowing flammability to be measured as a function of airspeed, fuel flow rate, fuel jet Reynolds number and polymer concentration. The digital imaging technique was employed to measure spray characteristics in this simulation and these results were related to flammability test results. Scaling relationships were investigated through correlation of experimental results with characteristic dimensions spanning more than two orders of magnitude

Cumulative index to NASA Tech Briefs, 1963-1967

Cumulative index to NASA survey on technology utilization of aerospace research outpu