Machine Learning Approach for Risk-Based Inspection Screening Assessment

Risk-based inspection (RBI) screening assessment is used to identify equipment that makes a significant contribution to the system's total risk of failure (RoF), so that the RBI detailed assessment can focus on analyzing higher-risk equipment. Due to its qualitative nature and high dependency on sound engineering judgment, screening assessment is vulnerable to human biases and errors, and thus subject to output variability and threatens the integrity of the assets. This paper attempts to tackle these challenges by utilizing a machine learning approach to conduct screening assessment. A case study using a dataset of RBI assessment for oil and gas production and processing units is provided, to illustrate the development of an intelligent system, based on a machine learning model for performing RBI screening assessment. The best performing model achieves accuracy and precision of 92.33% and 84.58%, respectively. A comparative analysis between the performance of the intelligent system and the conventional assessment is performed to examine the benefits of applying the machine learning approach in the RBI screening assessment. The result shows that the application of the machine learning approach potentially improves the quality of the conventional RBI screening assessment output by reducing output variability and increasing accuracy and precision.acceptedVersio

Welding procedure qualification record (WPQR) for welds fabricated at proximity

Maintaining the minimum allowable distance between proximity welds has always been considered a subject of debate among design engineers, welding engineers/inspectors and fabricators/engineering contractors. The scattered nature of guidelines available in welding codes and standards for maintaining the minimum allowable distance poses a significant challenge in the welding procedure and inspection criteria development process. This is especially critical for complex welded joints on submerged sections of offshore structures, in compact layouts/branched connections of topside piping components, and on topside structural joints (depending on the complexity). This manuscript presents the findings of an experimental study that was performed by fabricating two girth welds at proximity on an S355 steel tubular section with diameter of 219.1 mm and thickness of 8.18 mm. Proximity girth welds were fabricated on S355 tubular sections at three different distances between their weld toes, 5, 10, and 15 mm, respectively, using two different welding procedures. Welding procedure qualification record (WPQR) was performed, and all prescribed mechanical tests were recorded as per NORSOK M-101, a structural steel fabrication code. Although all results from the mechanical test met the minimum specified values as defend in the NORSOK code, the research findings revealed a noticeable difference in Charpy and hardness values for proximity region between adjacent welds. Considerable changes in final microstructure morphology were observed between proximity welds due to varying thermal cycles. These observations can form the basis for the future welding procedure qualification of critical welded joints, especially for proximity welds on critical welded joints of offshore structures and welds fabricated during replacement/repair procedures in compact piping layouts.Welding procedure qualification record (WPQR) for welds fabricated at proximitypublishedVersio

Digitalization of Distribution Transformer Failure Probability Using Weibull Approach towards Digital Transformation of Power Distribution Systems

Digitalization of the failure-probability modeling of crucial components in power-distribution systems is important for improving risk and reliability analysis for system-maintenance and asset-management practices. This paper aims to implement a Python programming-based Weibull approach for digitalization of distribution-transformer (DT) failures, considering a regional section of DTs in Sri Lanka as a case study. A comprehensive analysis for DT-failure data for six years has been utilized to derive a Weibull distribution analysis for DTs. The interpretation of the resulting beta and alpha parameters of the Weibull analysis for different categories of DTs in the selected region is also presented. The resulting data can be uploaded to computerized maintenance-management systems (CMMS), to adopt conclusions or resolutions reached by the asset and maintenance managers. Ultimately, failure-probability modeling is beneficial for decision-making processes for higher management aiming for the digital transformation of power-distribution systems.publishedVersio

Experimental and numerical investigation of residual stresses in proximity girth welds

International fabrication codes and standards provide minimum distance criteria for proximity welds, although rigorous justification is lacking. These distances are either based on practical experience or mutual agreement and are often left to the engineering judgment of contractors, inspection engineers, etc., especially in cases of repair welds fabricated in proximity to existing welds. Previous studies have shown high tensile residual stresses and altered mechanical and microstructural properties between proximity welds. This article focuses on numerical and experimental quantification of residual stresses in the proximity region by X-ray diffraction (XRD) and finite element method (FEM) thermo-mechanical models. Specimens were machine welded, then repair welded at distances of 5–15 mm. A fair agreement in results was achieved between FEM and XRD. The most detrimental effect was observed at the weld root toe for the repair weld at 5 mm proximity, likely due to the high constraint and multiaxial stress state. These findings enable practitioners to propose technical justification and corrective actions while specifying minimum distance criteria for proximity welds.publishedVersio

The effect of laser surface melting on the retained austenite and wear properties of AISI D2 tool steel

In this study the effect of laser surface melting (LSM) on the amount of retained austenite, hardness and wear resistance of AISI D2 steel was investigated utilizing hardness test, X-ray diffraction (XRD), pin on disk wear test and scanning electron microscopy (SEM). In order to evaluate wear resistance, pin on disk tests at two different loads were carried out on surface treated samples including as received annealed and a quenched and tempered specimen. Surface treatment has been carried out in three different conditions; LSM, LSM with pre-heating at 300 °C and LSM with pre-cooling in liquid nitrogen which resulted in 64, 42% and 90% of retained austenite respectively, revealing that higher cooling rate led to a higher amount of retained austenite. The results showed that in spite of the presence of austenite as major phase in re-melted surface, the hardness reached to the values of up to 600 HV10 which is approximately two times of the as received steel having a lot of carbides dispersed in the ferrite matrix. In addition, at lower load, conventionally heat treated sample exhibited better wear resistance, whereas at higher load, the wear rate of laser melted specimen was the least as a result of the transformation of retained austenite into martensite. At lower load the dominant wear mechanism was abrasion while Adhesion was identified as the main wear mechanism at higher load.acceptedVersio

Development of a Procedure for Risk-Based Qualification of Additively Manufactured ‎Components: Adopting to Oil and Gas Industrial Applications

Recent advances in additive manufacturing (AM) technology provide the potential for on-demand and rapid production of spare parts during urgent repair times. Recently, big oil and gas companies have shown early progress in using additive technology in manufacturing specific heat exchangers, downhole cleanout tool nozzles, offshore risers, gas turbine nozzles, and subsea chemical stick injection tools. Despite the mentioned progress, the current adoption level of additive technology for the offshore oil and gas industry is very limited. Non-destructive and destructive evaluation methods of additively manufactured metallic components have been studied extensively. However, the technique selection procedure and scope of the required test methods have not been studied sufficiently. This paper discusses various elements related to the qualification of additively manufactured components for application in the oil and gas industry. A risk-based qualification method for identifying the scopes of required non-destructive and destructive tests and the resulting qualification procedure for additively manufactured spare components in offshore oil and gas applications is suggested.Development of a Procedure for Risk-Based Qualification of Additively Manufactured ‎Components: Adopting to Oil and Gas Industrial ApplicationspublishedVersio

Digitization Methods of Grinding Pins for Technological Process Planning

The paper presents different techniques for digitizing grinding pins and discusses the use of digitalized pins and the results of measurements in technological process planning (TPP), focusing on the challenges of the digital era. It describes the potential of different measuring devices, taking into account the digitization of a real tool shape into virtual 2D and 3D models. The following methods for measuring grinding pins are presented in the study: contact and non-contact coordinate measurements – performed on coordinate measuring machines (CMM); optical measurements on microscopes (i.e. focus-variation technique); optical measurements using tool presetters; optical measurements with measuring arm; laser micrometer measurements; and laser triangulation sensor measurements. Moreover, the use of testers which are applied in contour measurements is analyzed. On the basis of the presented methods, taking into account their possibilities and limitations, we discuss how the obtained digital data can be used in the planning of technological processes.publishedVersio

Thin-Walled Cylindrical Shell Storage Tank under Blast Impacts: Finite Element Analysis

Thin-walled cylindrical shell storage tanks are pressure vessels in which the walls of the vessel have a thickness that is much smaller than the overall size of the vessel. These types of structures have global applications in various industries, including oil refineries and petrochemical plants. However, these storage tanks are vulnerable to fire and explosions. Therefore, a parametric study using numerical simulation was carried out, considering the internal liquid level, wall thickness, material yield strength, constraint conditions, and blast intensity, with a diameter of 100 m and height of 22.5 m under different blast loads using the finite element analysis method. The thickness of the tank wall is varied as 10 mm, 20 mm, 30 mm, and 40 mm, while the fill level of internal fluid is varied as 25, 50, 75, and 100%. The blast simulation was conducted using LS-DYNA software. The numerical results are then compared with analytical results. The effects of blast intensity, standoff distance, wall thickness, and fill level of internal fluid on the structural behaviour of the storage tank were investigated and discussed.publishedVersio

Finite Element Analysis of Steel Plates with Rectangular Openings Subjected to Axial Stress

Steel plates with openings are among the important ship structural components used in the ship’s hull to withstand the hydrostatic forces of the ocean, which cause sagging and hogging moments at the ship’s bottom. The existence of openings on plates can cause structural rupture, stress concentration and a decrease in ultimate strength. This research is aimed at investigating the influence of selected parameters on the ultimate capacity of steel plates with rectangular holes subjected to axial stress, using ANSYS finite element analysis (FEA) under its non-linear static structural programme. The main parameters investigated in this paper are the plate thickness, opening aspect ratio, number of openings, position of openings, and the boundary condition of the plate. The influence of these parameters on the stress of plates and their deformation was evaluated. The comparison of the numerical simulation with the well-established analytical method using the Navier solution and Roark’s Formulas showed a good agreement.Finite Element Analysis of Steel Plates with Rectangular Openings Subjected to Axial StresspublishedVersio

Machine Learning Approach for Risk-Based Inspection Screening Assessment

Risk-based inspection (RBI) screening assessment is used to identify equipment that makes a significant contribution to the system's total risk of failure (RoF), so that the RBI detailed assessment can focus on analyzing higher-risk equipment. Due to its qualitative nature and high dependency on sound engineering judgment, screening assessment is vulnerable to human biases and errors, and thus subject to output variability and threatens the integrity of the assets. This paper attempts to tackle these challenges by utilizing a machine learning approach to conduct screening assessment. A case study using a dataset of RBI assessment for oil and gas production and processing units is provided, to illustrate the development of an intelligent system, based on a machine learning model for performing RBI screening assessment. The best performing model achieves accuracy and precision of 92.33% and 84.58%, respectively. A comparative analysis between the performance of the intelligent system and the conventional assessment is performed to examine the benefits of applying the machine learning approach in the RBI screening assessment. The result shows that the application of the machine learning approach potentially improves the quality of the conventional RBI screening assessment output by reducing output variability and increasing accuracy and precision