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Assessment of the current state of the near-surface part of the geological environment and understanding of its layered structure play an important role in various scientific and applied fields. The presented work is devoted to the application of phasometric modifications of geoelectric control methods to solve the problem of the detailed complex study of the underground layers of the environment in the process of drilling operations with the use of special equipment. These studies are based on the analysis of variations in phase parameters and characteristics of an artificially excited multiphase electric field to assess poorly distinguishable details and changes in the layered structure of the medium. The proposed method has increased accuracy, sensitivity and noise proofness of measurements, which allows for extracting detailed information about the heterogeneity, composition and stratification of underground geological formations not only in the zone where the drill makes contact with the medium, but also in the entire control zone. This paper considers practical mathematical models of phase images for basic scenarios of drill penetration between the layers of the near-surface part of the geological medium with different characteristics, obtained by means of approximation apparatus based on continuous piecewise linear functions, and also suggests the use of modern machine learning methods for intelligent analysis of its structure. Studying the phase shifts in electrical signals during drilling highlights their value for understanding the dynamics of soil response to the process. The observed signal changes during the drilling cycle reveal in detail the heterogeneity in soil structure and its response to changes caused by drilling. The stability of phase shifts at the last stages of the process indicates a quasi-equilibrium state. The results make a significant contribution to geotechnical science by offering an improved approach to monitoring a layered structure without the need for deep drilling. [ABSTRACT FROM AUTHOR]

The exterior layer of the fuselage skin structure is made of Glass-Reinforced Fiber Metal Laminates (GLARE-FMLs). Hole quality is impacted by various force components during the drilling process. The process variables of drilling are optimized to obtain quality holes by controlling such force components. Because of the very limited works on optimizing the significant input process variables in getting quality drilled holes on FML plates, the present investigation is aimed to analyze the impact of varying the significant drilling process variables referred from the literature study and the wt.% of Layered Double Hydroxide (LDH) mixed with the epoxy, on the force components generated during the drilling process. The FML plates proposed in the study have been drilled based on the test plan prepared by Taguchi's DOE. Grey Relational Analysis has been used for discovering the best combination of process variables leading to good quality holes. Further, grey-fuzzy modeling technique has been employed to check the results of GRA. From the results, it is identified that 1000 rpm spindle speed, 20 mm/min feed rate and 4 wt.% inclusion of LDH to the epoxy resin combination within the considered range of input process variables were found to be the best input parameter combinations resulting in comparatively better output responses. Artificial Neural Network (ANN) model has been generated to bridge the input variables with the outputs measured. The fitness of the generated ANN model has been checked and reported. The effect of varying the process variables on obtaining the quality drilled holes has been revealed using Main Effect Plots (MEPs). [ABSTRACT FROM AUTHOR]

Drilling operation has a direct impact on the quality of the production. Insufficiently controlling the cutting force during the drilling process leads to the risk of early drill failure. Typically, the selection of the drilling parameters is determined based on machining-data handbook where the experience and skill of the operator are required. This paper presents an optimal framework to control the cutting force of the drilling process. A mathematical model that captures complex drilling dynamics between cutting force and feed rate based on system identification is used. Then, a Proportional-Integral-Derivative (PID) controller is proposed to control the cutting force. Taking advantage of up-to-date swam-based optimization technique, an Enhance Bat Algorithm (EBA) approach is used to tune the design variables of the PID controller based on the Integral Absolute Error (IAE) criterion. The results are compared with another two swam optimization, the Particle Swarm Optimization (PSO) and the Whale Optimization Algorithm (WOA). The comparison reveals that EBA can give better results in terms of improving time domain specifications and reducing error performance indices. [ABSTRACT FROM AUTHOR]

Summary: During horizontal drilling operations, real‐time prediction of drilling pressure during the drilling process can help the drilling team cope with the complex and changing working environment downhole, adjust the parameters of the drilling rig promptly, make correct decisions, reduce the probability of drilling accidents, and avoid affecting the duration and cost of the project. This study provides a method for real‐time prediction of the drilling pressure of horizontal drilling rigs. A deep learning model based on a convolutional Transformer is trained for accurate real‐time prediction by extracting real‐time operating data of the horizontal drilling rig from the data acquisition system. The method proposed in this study can be a useful tool to improve the performance of horizontal drilling rigs and can assist the drilling team in operating horizontal drilling rigs. The results of the case study show that: (1) the proposed convolutional Transformer model provides reliable real‐time prediction with an MAE of 0.304 MPa and an RMSE of 0.508 MPa; (2) the proposed method can quickly and accurately predict the trend of drilling pressure change in the next period based on the current change of drilling pressure, and grasp the dynamics of drilling pressure of horizontal drilling rigs in advance. Further research could focus on assisted decision‐making and intelligent optimization to provide solutions for preventing drilling accidents and improving horizontal rig performance based on the prediction. [ABSTRACT FROM AUTHOR]

The effectiveness of horizontal well drilling in improving the gas recovery efficiency of hydrate production makes it a promising technology for commercial exploitation. However, during horizontal well drilling in hydrate reservoirs, it is crucial to control hydrate dissociation to ensure the reservoir stability and drilling safety. In this work, a two-dimensional model using polar coordinates was built to study the influences of hydrate reservoir characteristics and drilling fluid salinity on gas production. The simulation applies to the hydrate reservoir of the second natural gas hydrate (NGH) production test in the Shenhu area of the South China Sea. The characteristics of hydrate dissociation and secondary formation and the drilling invasion behavior in the NGH layer and the mixing layer (free gas + hydrate) during horizontal well drilling were analyzed and compared. The simulation results indicated that the pressure and temperature transmission rates in the mixing layer (free gas + hydrate) are higher than those in the NGH layer. The invasion amount of drilling fluid in the mixing layer is 18.8 times more than that in the NGH layer. Under the high invasion of the drilling fluid, the hydrate dissociation amount in the mixing layer is similar to that of the NGH layer even though the initial hydrate saturation of the NGH layer was 2.65 times that of the mixing layer. The area of the hydrate dissociation in the mixing layer is much larger than that in the NGH layer, which may lead to the increase in risk of wellbore instability. The secondary hydrate formation is only observed in the NGH layer, which inhibits the drilling fluid invasion. The salinity of the drilling fluid has a more significant impact on the hydrate dissociation near the wellbore in the mixing layer compared to the NGH layer. With the increase in salinity from 3.05 wt% to 20 wt%, the hydrate dissociation range in the mixing layer increases from 0.16 m to 0.23 m, while the hydrate dissociation range in the NGH layer does not significantly change. [ABSTRACT FROM AUTHOR]

The crucial role of information technology (IT) in operating and managing industrial systems is widely recognized, and Iraq's IT capabilities hold great promise for its industrial and other economic sectors. The demand for IT services has risen considerably, particularly for oil and gas companies, which face the challenge of boosting capital asset returns while ensuring safety and sustainability. They need to manage rising demands as well as competition for access to oil reserves while driving improved asset reliability, productivity, and performance. This application show how information technology is used in the petroleum industry. It specifically examines information technology applications in the upstream, midstream, and downstream important segments of the petroleum industry during the drilling process. The increased price volatility's noteworthy effect on the profitability of the energy industry is just one of the current supply chain management challenges. Better supply chain management aids in lowering operational costs, a challenge that many businesses are under demand to address right away. The study's theoretical and practical value is in exposing the characteristics and issues with the infrastructure supporting the Iraqi oil industry and in creating a control algorithm for the evolution of its Regular visual inspections of pipelines, offshore oil rigs, and other infrastructure may be carried out swiftly and safely thanks to technology. Light devices that enable temperature checks using infrared scanning are available in modern applications. Hazards like poisonous substances can be identified by other sensors from a safe distance. Enhancing oil and gas safety with artificial intelligence technologies protects the environment and ensures worker safety

Assessment of the current state of the near-surface part of the geological environment and understanding of its layered structure play an important role in various scientific and applied fields. The presented work is devoted to the application of phasometric modifications of geoelectric control methods to solve the problem of the detailed complex study of the underground layers of the environment in the process of drilling operations with the use of special equipment. These studies are based on the analysis of variations in phase parameters and characteristics of an artificially excited multiphase electric field to assess poorly distinguishable details and changes in the layered structure of the medium. The proposed method has increased accuracy, sensitivity and noise proofness of measurements, which allows for extracting detailed information about the heterogeneity, composition and stratification of underground geological formations not only in the zone where the drill makes contact with the medium, but also in the entire control zone. This paper considers practical mathematical models of phase images for basic scenarios of drill penetration between the layers of the near-surface part of the geological medium with different characteristics, obtained by means of approximation apparatus based on continuous piecewise linear functions, and also suggests the use of modern machine learning methods for intelligent analysis of its structure. Studying the phase shifts in electrical signals during drilling highlights their value for understanding the dynamics of soil response to the process. The observed signal changes during the drilling cycle reveal in detail the heterogeneity in soil structure and its response to changes caused by drilling. The stability of phase shifts at the last stages of the process indicates a quasi-equilibrium state. The results make a significant contribution to geotechnical science by offering an improved approach to monitoring a layered structure without the need for deep drilling.

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Most of the parts of furniture made of medium density fiberboards (MDF) require at least one hole to be assembled. The drilling technological parameters influence the quality of holes. Factors such as tip angle of the drill bit, feed rate, type and diameter of the drill bit, and spindle rotational speed could affect the drilling process. Therefore, the right choosing of drilling parameters is a mandatory condition to improve the drilling efficiency that is expressed through tool durability, cost, and quality of the drilling. Thus, in this work, we are proposed an approach that consists in combining two modelling techniques, which were successfully applied in various fields, namely artificial neural network (ANN) and response surface methodology (RSM), to analyze and optimize the drilling process of MDF boards. Four artificial neural network models with a reasonable accuracy were developed to predict the analyzed responses, namely delamination factor at inlet, delamination factor at outlet, thrust force, and drilling torque. These models were used to complete the experimental design that was requested by the RSM. The optimum values of the selected factors and their influence on the drilling process of the MDF boards were revealed. A part of optimum combinations among analyzed factors could be used both during the drilling of the MDF boards and prelaminated wood particleboards. [ABSTRACT FROM AUTHOR]

Many problems such as delamination, cracking, fiber tearing, ovality, and surface roughness are encountered in the drilling of glass-fiber-reinforced composite (GFRP) materials. In this study, the percentage of multi-walled carbon nano tube (MWCNT), cutting tool type, feed rate, and cutting speed were selected as control factors during the drilling of MWCNT-reinforced GFRP nanocomposites. The quality characteristics of the drilling process were determined as surface roughness, delamination, torque, and thrust force. The experiments were carried out in accordance with the Taguchi L27 orthogonal array. The lowest values obtained because of the experiments were Ra = 4.95 µm, Dm = 1.099, T = 14.78 N, and F = 44.24 N, respectively. However, since each of these outputs were obtained from different experimental trials, different multi-criteria decision-making (MCDM) methods were used to optimize all outputs at the same time. First, the criteria were weighted using the fuzzy AHP method, and then the outputs were optimized using multi-criteria decision-making methods (i.e., GRA, WASPAS and VIKOR). Very close optimal ranking was obtained in all three methods. The best results were obtained for Ra = 4.86 µm, Dm = 1.13, T = 55.57 N, and F = 48.00 N. In the next step, the performance values obtained from each MCDM method were re-optimized using the Taguchi S/N ratio method. By comparing between these models, a single optimal condition for drilling is proposed. Accordingly, A2B3C1D1 (Ra = 4.86 µm, Dm = 1.10, T = 17.47 N and F = 48.33 N) for FAHP-GRA and FAHP-WASPAS and A2B3C2D2 (Ra = 5.02 µm, Dm = 1.09, T = 37.19 N and F = 45.01 N) for FAHP-VIKOR were determined as the best performing experiments. Finally, validation tests were conducted to compare the performance of the experiments. As a result, the FAHP-GRA and FAHP-WASPAS optimization with Taguchi S/N gave an unweighted improvement of 82.9% and a weighted improvement of 10.04% compared to the results of the experiment with MCDM. Compared to the results of the experiments with MCDM, S/N FAHP-VIKOR provided an unweighted improvement of 52.75% and a weighted improvement of 8.19%. According to the results obtained, for this study, FAHP-GRA and FAHP-WASPAS are more effective optimization methods than FAHP-VIKOR. [ABSTRACT FROM AUTHOR]

The different flexibility and diversity requirements for respective manufacturing units have made modern cutting tool management much more crucial and complicated, as a greater variety of tools and more frequent tool changes are required to enhance production efficiency and avoid unplanned manufacturing downtime. Developing in-process anomalous change detection methods has been identified as an essential challenge. Machine learning techniques have been widely applied in tool condition monitoring and anomalous change detection. As anomaly data is rare in manufacturing processes, supervised machine learning approaches (such as regression and classification) are not applied to the anomalous change detection problem. Rather, self-supervised machine learning (a representative type of unsupervised machine learning) is applied. This study describes a variational autoencoder (VAE) neural network and proposes a VAE-based method for tool condition monitoring and change detection in a drilling process using the temperature near a drill edge. The proposed VAE evaluates the drill tool condition based on the reconstruction error between the input temperature and its estimate per a drill unit process through the trained network. Computational simulations demonstrate that the proposed VAE network model can avoid overfitting to the anomaly data and that its expressive power is greater than that of the conventional autoencoder model. [ABSTRACT FROM AUTHOR]

This paper aims to optimize the quality characteristics of the drilling process in glass fiber-reinforced polymer (GFRP) composites. It focuses on optimizing the drilling parameters with drill point angles concerning delamination damage and energy consumption, simultaneously. The effects of drilling process parameters on machinability were analyzed by evaluating the machinability characteristics. The cutting power was modeled through drilling parameters (speed and feed), drill point angle, and laminate thickness. The response surface analysis and artificial neural networks enhanced by the particle swarm optimization algorithm were applied for modeling and evaluating the effect of process parameters on the machinability of the drilling process. The most influential parameters on machinability properties and delamination were determined by analysis of variance (ANOVA). A multi-response optimization was performed to optimize drilling process parameters for sustainable drilling quality characteristics. The obtained models were applied to predict drilling process characteristics, and exhibited an excellent harmony with the experiment results. The optimal drilling process factors were the highest spindle speed and the lowest feed, with a drill point angle of 118° for the laminate of 4.75 mm thickness. [ABSTRACT FROM AUTHOR]

Glass fiber reinforced polymer (GFRP) composites are becoming more attractive in modern engineering fields due to their outstanding mechanical/physical properties. However, a thorough understanding of their drilling machinability is seriously lacking in the research community. The present work aims to address the drilling behavior of woven GFRP composites under varying cutting speeds and feed rates. Machining studies were conducted using two different diamond-coated special tools involving a double point angle drill and a dagger drill. The drilling machinability of GFRPs was comprehensively analyzed in terms of cutting forces, machining temperatures, drilling-induced damages, dimensional accuracy, and hole wall morphologies. Theoretical analyses and experimental characterizations of delamination damage were conducted for both special drills. A special attempt was made to clarify the impact of different drill shapes on the damage formation and extension of cut GFRP materials. The results obtained can supplement the expertise of composites machining and guide the damage-free drilling of GFRP laminates for academia and industry.

In drilling processes, faulty downhole conditions often lead to drilling performance degradation and even serious accidents, such as the blowout, and well collapse. To improve the drilling efficiency and enhance the process safety, a new downhole condition identification method is proposed for geological drilling processes based on quantitative trends and expert rules. A knowledge base that associates the quantitative trends and downhole conditions is established based on variational trends extracted from the historical data and rules summarized from the drilling operation manual. When the new data arrive for online monitoring, the variational trends are extracted, and then, the downhole condition is identified by comparing such trends with each rule in the knowledge base. The effectiveness and practicality of the proposed method are demonstrated by industrial case studies with real drilling process data. [ABSTRACT FROM AUTHOR]

The early warning of drilling faults is of paramount importance to prevent or reduce environmental and property damages. In view of the complex drillstring kinematic characteristics and changeable formation environment, this paper proposes a new fault early warning method for the drillstring system based on a multi-model fusion and self-updating strategy. The major contributions are twofold: (1) A hybrid drillstring early warning method is proposed to identify faulty conditions based on the fusion of multi-dimensional prediction models of the drillstring system; (2) An event-triggered model self-updating strategy is proposed to mitigate the prediction performance degradation caused by formation uncertainties. The effectiveness and practicability of the proposed method are demonstrated by industrial case studies, and the results indicate that the proposed method outperforms other approaches. • A hybrid drillstring early warning method is proposed based on multi-model fusion. • An event triggered model updating strategy is proposed for formation uncertainties. [ABSTRACT FROM AUTHOR]

Due to their inexpensive cost and superior qualities compared to conventional metals, Glass Fibre Reinforced Plastic (GFRP) composites are frequently used in engineering applications. Despite the development of numerous non-traditional drilling methods, traditional mechanical drilling methods based on CNC machines are still utilized as the primary applications for composites due to their financial advantages. Damage in the composite materials during the drilling process due to delamination often happens. The delamination has directly related to the drilling force. A dynamic model of the drilling force is a function of the feed rate. Due to the unpredictable nature of the composite material's physical and chemical properties, it may be challenging to realize the dynamics of the drilling process in this material. In this paper, the mathematical model of the drilling process is obtained experimentally based on system identification. Then, to address the problem of controlling the drilling force of composite materials, this paper proposes a Model Reference Adaptive Control (MRAC) based on the Enhanced Flower Pollination Algorithm (EFPA) to handle the uncertainties and time-varying dynamics of the drilling process. The performance of the proposed controller is evaluated based on the Integral Time of Absolute Error (ITAE) index. The simulation results show that the proposed controller is effective in avoiding drilling-induced delamination in composite under different operation conditions. [ABSTRACT FROM AUTHOR]

Due to the variability in the physical and chemical properties of the composite material, understanding the dynamics of the drilling process in this material can be challenging. One of the most significant issues that can result from size and shape abnormalities in the hole during the drilling process is delamination. These errors could be unacceptable and lower the product's quality. In order to regulate the drilling process of Glass Fiber Reinforced Plastic (GFRP) composite, this work proposes an optimal Proportional-Integral-Derivative (PID) controller based on Enhanced Flower Pollination Algorithm (EFPA). Based on the Integral Time of Absolute Error (ITAE) index, the proposed tuning approach is compared with the traditional Flower Pollination Algorithm (FPA) and Particle Swarm Optimization (PSO). In terms of time response specifications and error performance index. Simulation results using MATLAB demonstrate the superiority of the proposed EFPA over conventional FPA and PSO for improving the tuning of the PID for controlling the drilling process. [ABSTRACT FROM AUTHOR]

The effectiveness of horizontal well drilling in improving the gas recovery efficiency of hydrate production makes it a promising technology for commercial exploitation. However, during horizontal well drilling in hydrate reservoirs, it is crucial to control hydrate dissociation to ensure the reservoir stability and drilling safety. In this work, a two-dimensional model using polar coordinates was built to study the influences of hydrate reservoir characteristics and drilling fluid salinity on gas production. The simulation applies to the hydrate reservoir of the second natural gas hydrate (NGH) production test in the Shenhu area of the South China Sea. The characteristics of hydrate dissociation and secondary formation and the drilling invasion behavior in the NGH layer and the mixing layer (free gas + hydrate) during horizontal well drilling were analyzed and compared. The simulation results indicated that the pressure and temperature transmission rates in the mixing layer (free gas + hydrate) are higher than those in the NGH layer. The invasion amount of drilling fluid in the mixing layer is 18.8 times more than that in the NGH layer. Under the high invasion of the drilling fluid, the hydrate dissociation amount in the mixing layer is similar to that of the NGH layer even though the initial hydrate saturation of the NGH layer was 2.65 times that of the mixing layer. The area of the hydrate dissociation in the mixing layer is much larger than that in the NGH layer, which may lead to the increase in risk of wellbore instability. The secondary hydrate formation is only observed in the NGH layer, which inhibits the drilling fluid invasion. The salinity of the drilling fluid has a more significant impact on the hydrate dissociation near the wellbore in the mixing layer compared to the NGH layer. With the increase in salinity from 3.05 wt% to 20 wt%, the hydrate dissociation range in the mixing layer increases from 0.16 m to 0.23 m, while the hydrate dissociation range in the NGH layer does not significantly change.

In multi-hole drilling, optimization of the drill-path sequencing can lead to a significant reduction in machining time and eventually improves productivity in industries. Hence, the researchers have explored this domain and the similarity between the structure of the multi-hole drilling process and the traveling salesman problem. Wherein the prime intent is to seek the shortest possible path to minimize the traveling distance. Further, the researchers have used mainly three types of distance functions to model the travel distance of drill tools i.e., Euclidean, rectilinear, and Chebyshev distances. This paper aims to study these distance function models and compares their performances and effect on the drill-path sequences using test problems from the literature. The Simulated Annealing algorithm is utilized for the optimization of the drill-path sequences. It also discusses the abilities and shortcomings of these distance functions. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polymer (CFRP) is a lightweight composite material with high mechanical properties, which has been applied in many fields. Especially in the aerospace field, it is a preferable material to make different shape thin wall sheet parts, which needs to be assembled and connected with other parts through riveting or bolt. Therefore, a large number of holes need to be drilled on the CFRP. However, as CFRP is an inhomogeneity and anisotropy laminate, defects such as delamination, burrs, tear, and excessive roughness are easy to occur in the process of drilling holes. These defects will greatly reduce the service life of structural parts or even directly make them scrap. In this review, the generation mechanism and influencing factors of drilling defects of CFRP are explored. The relevant achievements of experimental optimization, algorithm optimization and finite element method optimization about traditional drilling process are summarized. The research progress of new drilling processes is introduced. The shortcomings of existing research and the future development direction are analyzed. This review will help researchers optimizing the CFRP drilling process, reduce the defects in the drilling process, improve the quality of drilling holes, and provide reference for drilling process of other composite materials. [ABSTRACT FROM AUTHOR]

Drilling is often employed when using carbon fiber–reinforced polymers (CRFPs) to fabricate machine parts. However, CFRP drilling is compromised by uncut fibers and delamination of the final layers of fiber sheets, reducing the quality and strength of the product, increasing fatigue around drilled holes, and rendering product assembly difficult. We used a mathematical model to analyze drilling behaviors at the critical cutting angles 0 < φ ≤ Υ 0 +π/2 and Υ 0 +π/2 < φ. We used the Euler–Bernoulli beam theory to derive the maximum lengths of uncut fibers; these were determined by reference to half of the maximum deflection of a simply supported beam. Critical cutting angles were calculated by evaluating the hogging and sagging of a cantilever beam after fracture of a maximally deflected single fiber. These analyses were used to validate the experimental data obtained under various machining conditions, employing two tools to drill three different types of multidirectional CFRP sheets. Predictions were derived using an analytical Dexel model that employs self-generating 3D software. During simulation, the drilling tools were moved using NC-code kinematics, or manually, in the X, Y, and Z directions. The model errors for the experimental results were 2–12% in terms of the maximum uncut fiber length. The critical uncut fiber cutting windows of the predictions and experiments indicate approximately 90–95% agreement. [ABSTRACT FROM AUTHOR]

Camellia Sinensis/Ananas Comosus/GFRP/Epoxy Polymer composites are widely accepted to be a better material for indoor sound damping. It has a series of challenges, like force cuts on the drilling of these composites. The focus is to drill on hybrid laminates by changing the cutting conditions like the speed and feed and the selection of optimum machining process parameters. Nine experimental cycles have been performed, and five various attributes were analyzed, for example, torque, tangential force, thrust force, and also the factor of delamination (Enter & Exit). This study shows a sequential parameter selection for the drilling machining process. Using Multi-attribute optimization, order preference and optimum drilling machining process parameters are selected by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). From the TOPSIS analysis, the best suitable optimum drilling conditions for hybrid laminates are chosen as 600 rpm and 0.02 m/min for cutting speed and feed rate, respectively.

Abstract In this paper, a connection between vibration amplitude and tool wear when drilling of IS3048 steel utilizing different dimensioned tools is dissected through tests. Discriminant features, which are sensitive to drill wear and breakage, were developed. These were discovered to be somewhat impervious toward sensor location and cutting conditions. In the process, the vibration amplitude features a checking highlight dependent on ascertaining both the tools and their performance over vibrations, which was discovered to be somewhat powerful for on-line identification of drill tool breakage in both frequency and time domains. These vibrational amplitude signal features are directly affected, related to the tool geometry, which give higher chances of tool selection criteria during the drilling process. The experiments were carried out using solid carbide tool with change in tool geometry under dry conditions where the vibration amplitude for both is evaluated. The results revealed that cutting tool vibrational amplitude and tool wear were relatively dependent showing the tool selection of suitable tool geometry.

The drilling process is an important step in petrochemical industries, but the drilling process is risky and costly. In order to improve the safety and cost the impact of faults in the drilling process, this paper proposes intelligent moving window based sparse principal component analysis (MWSPCA) integrating case-based reasoning (CBR) (MWSPCA-CBR) in the fault diagnosis of the drilling process in the petrochemical industry. Through introducing sparsity into the PCA model, the Lasso constraint function of the MWSPCA method is used to optimize the sparse principals. The corresponding T2 and Q statistics calculated by the selected sparse principals decide whether the faults have occurred, and the occurrence time of the anomaly is quickly located based on the MWSPCA method. Then the CBR method is used to analyze the anomaly data to identify the possible fault types, and provide the relational handling methods for real-time monitoring experts. Finally, the MWSPCA method is verified based on the intelligent diagnosis of the Tennessee Eastman (TE) process, reducing false negatives and false positives and improving the accuracy rate and the diagnosis speed. Furthermore, the proposed method is applied to analyze the data of the drilling process. The experimental results demonstrate that the proposed method can effectively diagnosis faults in the drilling process and reduce risks and costs in the petrochemical industry. [Display omitted] • An improved moving window sparse principal component analysis-based case based reasoning is proposed. • The moving window sparse principal component method is verified based on the diagnosis of the Tennessee Eastman process. • The intelligent fault diagnosis framework of the drilling process is obtained. • The proposed method can effectively diagnosis faults in the drilling process. • The proposed method can reduce risks and costs of petro chemical engineering. [ABSTRACT FROM AUTHOR]

For minimally invasive drilling processes, the temperature development in the drilling ground is of crucial importance for patient safety. To monitor the temperature during drilling, a drill prototype was developed by BREDEMANN ET AL. which can record the drill temperature in parallel to the process and in real time. The measurement principle of the thermistor (temperature sensor) integrated in the drill could be validated. [1] The prototype must be refined for use in the operating room, as the drill does not yet meet all the medical requirements that need to be fulfilled. In further development, the recorded temperature data in particular must be processed and communicated to the surgeon in order to provide added value for the surgical procedure.

Water jet-guided laser (WJGL) processing of ceramic matrix composites offers smooth cutting surfaces and minimizes defects such as delamination, burrs, and recast layers. However, the processing ability of WJGL is limited by the stability of the water jet. Splashing is a critical factor that affects water jet stability. This study investigates the splashing morphology and its impact mechanism during WJGL processing of continuous carbon fiber reinforced silicon carbide (C f /SiC) composites. High-speed cameras were used to capture splashing morphologies and laser transmission states during drilling and grooving. The results indicate that the splashing morphology was significantly affected by the water jet speed and the micro-hole/groove depth, resulting in behaviors such as water accumulation, droplets falling, rebound droplets, splash impact, water film, and mist, which distorted or even broke the water jet. The laser escaped in the distorted water jet, leading to a reduction in material removal rate. The splashing at the water jet speed of 160 m/s resulted in a 61.1 % reduction in material removal rate during drilling compared to 40 m/s. In addition, a method of placing a porous water-absorbing material on the workpiece surface was proposed, which effectively improved the material removal rate. This paper presents a theoretical basis for comprehending and addressing splashing in WJGL processing. [Display omitted] • Water splashing significantly reduced drilling efficiency compared to grooving. • Splashing morphologies were captured in detail with high-speed cameras. • The mechanism of splashing interfering with the water jet was revealed. • The distorted water jet led to laser escape and reduced processing efficiency. • The placement of porous water-absorbing material can effectively suppress splashing. [ABSTRACT FROM AUTHOR]

Carbon fiber reinforced polymer (CFRP) laminates are featured by superior mechanical properties and excellent structural functions, which have been a promising alternative to conventional alloys and steels in diverse industrial fields. Mechanical drilling is a compulsory operation to shape fibrous composites to desired workpiece quality and target dimensional accuracy. Progressive tool wear is an extremely crucial issue when drilling CFRPs as it may result in undesired machining consequences such as increased force generation, elevated temperatures, and deteriorated surface quality. Despite great endeavors already made to address the wear issues, a complete review of the wear phenomena for CFRP drilling is still significantly lacking. The present paper aims to report the key research advances in tool wear aspects when drilling CFRPs. The wear phenomena, wear modes, and tool failure mechanisms are carefully reviewed. The effects of wear progression on various drilling outputs of CFRP laminates, such as drilling forces, cutting temperatures, and surface quality attributes, are discussed. A particular focus is placed on the quantification and assessment of tool wear during drilling CFRPs. Some research prospects for both academia and industry are outlined. The paper intends to offer a comprehensive understanding of wear mechanisms controlling the drilling of CFRP laminates.

Smart materials properties are altered using external stimuli such as temperature, pressure and magnetic field. Magnetorheological Elastomer (MRE) is a type of smart composite material consisting of a polymer matrix embedded with ferromagnetic particles. In the presence of an external magnetic field, its mechanical properties, such as stiffness, change due to the interaction between the magnetic particles, which have applications in vibration isolation. Unwanted vibration in machines can cause severe damage and machine breakdown. In this work, a semi-active vibration isolator using MRE is proposed for a potential application in a drilling system to isolate the torsional vibration. The MRE was fabricated with a 35% mass fraction (MF) consisted of silicon rubber and iron particles. It was fitted with aluminium couplers and attached to the shaft (drill string) to study its efficiency in vibration isolation under a magnetic field. Two tests were conducted on the drilling prototype setup used in this work; the first test was a hammer impact test. The torsional transfer function TTF analysis showed that the system's natural frequency has shifted from 13.9 Hz to 17.5 Hz by the influence of increasing magnetic field around the MRE. The results showed that the continuous rotational vibration amplitude of the prototype is attenuated by more than 40%. [ABSTRACT FROM AUTHOR]

The process of drilling in natural gas hydrate reservoirs in sea areas involves problems such as hydrate decomposition and wellbore instability. To study the response behaviors of a reservoir during the drilling process, a two-dimensional numerical model of drilling fluid invading a hydrate reservoir in a cylindrical coordinate system was established to simulate the processes of heat and mass transfer, gas–liquid two-phase flow, and hydrate formation and decomposition in the hydrate reservoir during the drilling process. Based on the hydrate reservoir at station W17, Shenhu area of the South China Sea, the physical property response of the hydrate reservoir under different drilling fluid temperatures and salinity values was studied. The simulation results showed that during the drilling process, the temperature and pressure of the reservoir respond rapidly in a large area, further promoting the hydrate decomposition in the reservoir around the wellbore and leading to secondary hydrate formation. Moreover, a high hydrate saturation zone appears near the decomposed hydrate area in the layer without free gas, which corresponds to the low water saturation and high salinity zone. The hydrate decomposition area in the layer with free gas is larger than that without free gas. The increase in the drilling fluid temperature significantly enhances the hydrate decomposition in both layers of the reservoir. The hydrate decomposition near the wellbore under the high drilling fluid temperature will cause a sharp increase in the pressure in the reservoir, leading to the flow of pore fluid into the wellbore. The increase in drilling fluid salinity has little effect on the range of the hydrate decomposition in the reservoir but significantly increases the salinity of the pore water in the layer with free gas. As the drilling fluid temperature increases, the possibility of the gas invasion from the reservoir into the wellbore will be greatly increased at the early stage. [ABSTRACT FROM AUTHOR]

Losses of drilling mud and other fluids is the one of the major types of drilling troubles. Annual time losses for their elimination by oil and gas companies are huge. The factors, influencing the mud losses and regulating the direction of the further works, can be divided into two groups: geological and technological. Conducted studies on the use of an insulating composition based on chromium acetate made it possible to identify: the use of the insulation composition on the chrome acetate base allows considerable reduction of time required to eliminate disastrous circulation loss without installation of cement plugs; avoiding BHA replacement; avoiding drilling-in after bullheading and overlapping of lost-circulation layer; low cost, possibility of fast preparation, as it does not entail the delivery of additional chemicals, which also contributes to reduction of time required to eliminate disastrous circulation loss; the use with every type of drilling mud. Basing on the positive experience of the use of this composition in the neighboring regions and considering its economic side, the technique can be used in regions of the Udmurt Republic.

Holding pressure is an important factor affecting the rate of penetration (ROP) in horizontal wells. The holding pressure problem is directly and effectively solved by using the vibrating drag-reduction tools. In this paper, the finite element method is used to model the drilling process in a horizontal well with and without rotary percussion. The established model is based on a rotary percussion tool driven by PDM. Based on the simulation results, the authors compared and analyzed the impact of rotary percussion on the weight-on-bit (WOB), torque, acceleration and ROP in drilling process. The results show that the rotary percussion tool can effectively solve the problem of the holding pressure, increase the overall level and the fluctuation range of WOB, and improve ROP in the drilling process. It also increases the torque-on-bit and axial acceleration parameters. The analysis results can provide theoretical guidance for the parameter design and type selection of tools under different working conditions. [ABSTRACT FROM AUTHOR]

The goal of reducing oil consumption for lubrication of machining processes can be achieved by means of minimum quantity lubrication (MQL). In minimum quantity lubrication, the cutting fluid is a mixture of air and oil where only a small amount of the latter is added to the mixture. However, this reduced oil consumption must not be detrimental to the effectiveness of the machining process. In order to analyze the performance of minimum quantity lubrication, the two-phase fluid dynamics of the MQL dispersion fluid has to be investigated. In the present work, this two-phase flow for internal lubrication of a drilling process was studied by means of numerical modeling and simulation based on an Eulerian–Lagrangian–Eulerian (ELE) model. The Eulerian–Lagrangian–Eulerian model can properly describe the transition between the aerosol and wall liquid film two-phase flow. Attention was focused on the flow in the internal channels of a twist drill. A parametric study was carried out in order to disclose the effects of three different relevant parameters, namely the oil droplet diameter and the mass flow rate at the channel inlet and the drill bit rotational speed, on the MQL cutting fluid flow quality inside the drill bit channel and at the channel outlet. [ABSTRACT FROM AUTHOR]

Accurate prediction of the rate of penetration (ROP) is a difficult issue in the drilling process, especially under complex formation conditions. Many methods, such as mechanism and machine learning, were introduced to investigate it. However, most of them are offline prediction methods which may not be capable of capturing the online trend of ROP. In this paper, a novel dynamic model for ROP prediction is proposed considering the process characteristics, which consists of three stages. In the first stage, the correlations between ROP and eight drilling parameters are analyzed, and the rotational speed, weight on bit, depth are selected as the model inputs. In the second stage, the drilling data are pre-processed by using the filtering and re-sampling techniques. In the last stage, the moving window strategy, extreme learning machine, and 10-fold cross validation are used to establish the ROP model. Our main idea of online prediction of ROP lies in this last stage. Specifically, two steps (modeling and prediction) are executed alternately in the moving drilling depth windows so as to predict the ROP more accurately. Finally, the proposed ROP prediction model is applied to the drilling well ZK3 in Xiangyang area, Central China. The prediction accuracy is improved by at least 7% compared with seven well-known ROP prediction methods, two online and five offline, which validates the effectiveness of the proposed method. It is believed that the proposed model provides a basis for intelligent optimization control in drilling process. • A novel intelligent dynamic model is proposed for the online prediction of drilling ROP. • The influence of the length of moving window and distance between two windows are investigated thoroughly. • The proposed model can learn autonomously in the drilling process and has a fast computation speed. • The proposed method has a higher prediction accuracy than two online and five offline well-known conventional methods. [ABSTRACT FROM AUTHOR]

Despite the growth of composites and other lightweight materials, aluminium alloys remain an attractive choice of the aerospace industry due to their mature manufacturing processes, good resistance to fatigue crack growth and superior damage tolerance. In the aerospace industry, the drilling process is the most challenging among all the other machining process as millions of holes are required for producing riveted and bolted joints in the assembly operation of the aircraft's structures. The major challenges which arise from the drilling of these alloys are characterized by the poor hole quality which might initiate cracks within the airframe structure and reduces their reliability. This results in the rejection of parts at the assembly stage which directly impacts the manufacturing cost. Hence, appropriate selection of tool geometry, tool material and coatings, optimal cutting speed and feed rate, as well as drilling machines, is required to meet the requirement of machined parts. This motivates both academia and industries to further research on the application of drilling operations in the aircraft industry. This review aims to document details on drilling forces, drilling parameters, drill tool geometry, drill materials and coatings, chips formation, analysis of tool wear and hole metrics such as the hole size and circularity error, surface roughness, and burrs formation during the drilling of different aluminium alloys used in the aerospace industry. The focus will be mainly on Al2024 and Al7075 alloys since they are most commonly used and reported in the open literature.

An integrated approach has been applied to predict and optimize multi-performance-characteristics, being optimum thrust force (FTh), torque (M), hole entry delamination (FDen) and hole exit delamination (FDex), in the drilling process of carbon fiber reinforced polymer (CFRP). The drilling operation was performed by using a full factorial design of experiments with two different drill geometry (DG), three diverse levels of spindle speed (n), and feeding speed (Vf). The quality characteristics of FTh, M, FDen, and FDex were smaller the better. Back propagation neural network (BPNN) was first performed to model the drilling process and to predict the optimum drilling responses. Particle swarm optimization (PSO) was executed to attain the best combination of drilling parameters levels that would give optimum performance. The influences of drill geometry, speeds of spindle, and feeding speed on the responses were examined by using the response graphs. In addition, the scanning electron microscope (SEM) photos of the drilled hole are also provided to show the difference of the hole quality before and after optimization. The outcome of the confirmation experiment disclosed that the integration of BPNN and PSO managed to substantially predicted and enhanced the multi-performance characteristics accurately.

The aim of this paper is to investigate and optimize surface quality and geometrical characteristics in drilling process of AISI H13 steel, because they are critical items for precision manufacturing. After conducting the experiments, two regression models are developed to extensively evaluate the effect of drilling parameters on process outputs. After that, evolutionary multi-objective optimization algorithm is employed to find the optimal drilling conditions. Non-dominated Sorting Genetic Algorithm (NSGA-ІІ) is developed and regression functions are taken into account as objective functions of algorithm to simultaneously optimize the surface roughness and deviation of circularity. The optimization results are successfully in agreement with experimental findings and finally the set of optimal drilling conditions is reported that can be selected by process engineer according to the priority and application. It is shown that, an increase in Cutting speed and liquid coolant intensity decreases the surface quality, while higher depth of cut, tool diameter and reed rate improve it. It is also found that tool diameter and depth of cut are the most effective input parameters on deviation of circularity. Finally, it can be concluded that, the implemented approach in this research provides an efficient method for other manufacturing processes to increase the performance and reduction of production costs.

Camellia Sinensis/Ananas Comosus/GFRP/Epoxy Polymer composites are widely accepted to be a better material for indoor sound damping. It has a series of challenges, like force cuts on the drilling of these composites. The focus is to drill on hybrid laminates by changing the cutting conditions like the speed and feed and the selection of optimum machining process parameters. Nine experimental cycles have been performed, and five various attributes were analyzed, for example, torque, tangential force, thrust force, and also the factor of delamination (Enter & Exit). This study shows a sequential parameter selection for the drilling machining process. Using Multi-attribute optimization, order preference and optimum drilling machining process parameters are selected by the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). From the TOPSIS analysis, the best suitable optimum drilling conditions for hybrid laminates are chosen as 600 rpm and 0.02 m/min for cutting speed and feed rate, respectively. [ABSTRACT FROM AUTHOR]

The study aims to optimize process parameters such as spindle speed and feed rate so that low delamination can be obtained while drilling of Hemp-Glass Fiber/Polyester Resin Hybrid Composite. The experiments have been carried out on MTAB Vertical Machining Center. The experiment is designed, conducted and optimized according to Response Surface Methodology (RSM). Spindle speed (500 rpm and 2500 rpm) and feed rate (100 mm/min and 500 mm/min) are the levels of process parameters considered and HSS twist drill bit was used. Using the central composite design, process parameters affecting the response parameter are identified. Finally, desirability approach was adopted to select the optimal setting of process parameters. Low value of feed rate favors low delamination factor. The experimental optimal solution obtained is delamination factor of 1.24 at spindle speed of 500rpm and feed rate of 100 mm/min, which has the best desirability. The confirmation experiments have been performed and the results are in great congruence with the previous experimental results. [ABSTRACT FROM AUTHOR]

In many medical disciplines, the process of drilling into the bone plays a crucial role for the implantation or fixation of implants or reconstruction plates. During the bone drilling process, heat is generated on the drill head and within the surrounding tissue. As a result, the increased temperature can lead to thermal damage and related necrosis of the (bone) tissue. This tissue damage is dependent on different drilling parameters and can have important influence on the following tissue healing cascade and finally on implant surveillance. In this context, the present short review elucidates the current state of scientific knowledge with regard to the heat-triggering factors during the bony drilling process and how these factors can be better understood and prevented, now and in the future, through new research approaches. External and internal influencing factors during the drilling process are distinguished and methods to examine the temperature changes are compared. This mini-review further demonstrates first preliminary results of the inflammatory tissue reactions to inadequate drilling processes. Furthermore, possible solutions of new standardized ex vivo-measurement methods to better understand the factors influencing the development of heat and to reduce animal experiments are herein discussed. [ABSTRACT FROM AUTHOR]

Accurate prediction of rate of penetration is a prerequisite for optimization of drilling parameters. However, characteristics such as multiple drilling conditions, inconsistency in data length and various drilling variables can lead to inaccurate prediction of rate of penetration in actual drilling process. Therefore, it is important to use appropriate methods to predict rate of penetration for the above characteristics. This paper proposes an online prediction method of rate of penetration based on drilling conditions identification. First, data preprocessing and correlation analysis are employed to handle various drilling variables to obtain optimal model inputs. Then, dynamic time warping method is used to solve inconsistency in data length. Further, for multiple drilling conditions, the fuzzy c-means and dynamic time warping are combined to identify drilling conditions. Next, different extreme learning machine models optimized by genetic algorithm are built to predict rate of penetration for different drilling conditions. Finally, the results involving actual data illustrate that the prediction error of the proposed hybrid method of fuzzy c-means, dynamic time warping, extreme learning machine and genetic algorithm meets the requirements. The proposed hybrid method outperforms the comparative methods in four performance metrics, which verify the rationality and necessity of considering drilling conditions when predicting rate of penetration. [ABSTRACT FROM AUTHOR]

This paper presents a model for on-line prediction of a drill flank wear using changes in vibration amplitude in the drilling process. Prediction of wear-time and wear-amplitude ratio relationships during the drilling process is enabled by this mathematical model through variations in vibration amplitude signals. An empirical method for an in-process approach for quantifying tool wear, and failure following it, is the outcome of the measurement of variations in the ratio of amplitude between torsional-axial dominant first mode (TP1) and the second mode (TP2) frequency. Performance of a series of cutting tests has been undertaken to study the effect of drill flank wear and other independent cutting parameters on the vibration amplitude signals. The objective is extended to finding the relationship between amplitude signals, drill flank wear and various other independent parameters. Details of the flank wear of drill and the ratio of amplitudes seen at various working conditions were determined and collected through experimental procedures. Verification of the model was done through comparison of the experimental values with the predicted values.

With the increase of drilling depth, complicated geological environments lead to a high risk of loss and kick. Fault diagnosis plays an essential role in minimizing the financial and environmental losses of the drilling process. On account of the temporal correlation of drilling parameters, a fault diagnosis method based on feature clustering of time series data for loss and kick of the drilling process is presented in this paper. Distance correlation is conducted for parameter combination to retain the whole information of drilling process. Global trend, local trends, and approximate entropy features are extracted to illustrate the characteristic of the time series. Density-based clustering method is performed for each combination to mine the local similarity among drilling parameters. Based on the clustering results of each combination as the inputs, the Bayesian classifier is further utilized to obtain the final fault diagnosis result. Experiments are executed with the actual data collected from a practical drilling process. The results indicate that the proposed method has both low false alarm rate and low miss alarm rate. • Distance correlation is applied to discovery the nonlinear relationships of drilling parameters. • Local trend features are introduced to illustrate the internal characteristic of the time series. • Density-based clustering is conducted to mine the local similarity among drilling parameters. [ABSTRACT FROM AUTHOR]

Surface wear of drilling bit in the drilling process is complex, and the traditional wear index is not suitable to reflect the wear condition of drilling bit well; it is necessary to investigate on the appropriate wear testing and evaluation method. In this paper, a visual measurement system is set up to obtain the drilling bit wear characteristics based on machine vision. The wear area image is grayscale processed, and the gray image is thresholding segmentation processed, then the boundary feature is extracted based on the chain code method. A comprehensive evaluation system is established, in which the wear perimeter, the equivalent wear diameter, and maximum wear width of different areas are proposed as the wear indicators. The wear fusion feature based on the principal component analysis is proposed to characterize the drilling bit wear degree, the wear indicators of different regions are characterized and fused as the wear degree of different regions, then the prediction model of the drilling bit wear degree is established based on support vector machine. The results show that the predicted results are mainly consistent with the experimental results. The research of the drilling bit wear characteristics based on principal component analysis can provide guidance for the study of drilling bit wear mechanism. [ABSTRACT FROM AUTHOR]

• The different kinds of outliers in drilling process are all detected, which need to be handled differently. • The causes of anomalies are discriminated intelligently and effectively by the DTW-FCM. • While improving the data quality, the data with drilling accident characteristics is reserved. • The performance of PNN-based monitoring models are improved by the discrimination and correction. During the drilling process, the data quality influences the reliability of condition monitoring results. However, the actual drilling data may encounter various kinds of abnormal data, and different kinds of them need to be handled differently. The abnormal data caused by external factors such as sensor failure, storage errors, etc., should be corrected, while the abnormal data caused by drilling accidents should be protected. Therefore, not only the anomaly detection is needed, but the causes of anomalies should be further discriminated. This paper proposes a method for discrimination and correction of abnormal data in the drilling process. First, the local outlier factor anomaly detection algorithm is developed to detect all kinds of the abnormal data. Then, the dynamic time warping and fuzzy c-means are combined for the discrimination of causes of anomalies. Finally, the discriminated abnormal data caused by external factors are corrected with the k nearest neighbor interpolation. Simulation results involving actual data illustrate that the causes of anomalies can be discriminated effectively, and the monitoring results of monitoring models based on neural network improve after using the proposed method, which verify the necessity of anomaly discrimination. [ABSTRACT FROM AUTHOR]

The process of drilling in natural gas hydrate reservoirs in sea areas involves problems such as hydrate decomposition and wellbore instability. To study the response behaviors of a reservoir during the drilling process, a two-dimensional numerical model of drilling fluid invading a hydrate reservoir in a cylindrical coordinate system was established to simulate the processes of heat and mass transfer, gas–liquid two-phase flow, and hydrate formation and decomposition in the hydrate reservoir during the drilling process. Based on the hydrate reservoir at station W17, Shenhu area of the South China Sea, the physical property response of the hydrate reservoir under different drilling fluid temperatures and salinity values was studied. The simulation results showed that during the drilling process, the temperature and pressure of the reservoir respond rapidly in a large area, further promoting the hydrate decomposition in the reservoir around the wellbore and leading to secondary hydrate formation. Moreover, a high hydrate saturation zone appears near the decomposed hydrate area in the layer without free gas, which corresponds to the low water saturation and high salinity zone. The hydrate decomposition area in the layer with free gas is larger than that without free gas. The increase in the drilling fluid temperature significantly enhances the hydrate decomposition in both layers of the reservoir. The hydrate decomposition near the wellbore under the high drilling fluid temperature will cause a sharp increase in the pressure in the reservoir, leading to the flow of pore fluid into the wellbore. The increase in drilling fluid salinity has little effect on the range of the hydrate decomposition in the reservoir but significantly increases the salinity of the pore water in the layer with free gas. As the drilling fluid temperature increases, the possibility of the gas invasion from the reservoir into the wellbore will be greatly increased at the early stage.

Drilling is one of the costliest and risky activities in oil and gas industry due to complexity of interactions with downhole formation. Cyclic loads while drilling cause the initiation and growth of cracks in oil tubulars. This phenomenon, known as fatigue, results in permanent reduction of the failure-free service envelope of a certain tubular. Further, most of the drill string failures are triggered by fatigue, which results from repetitive cyclic bending loads and stresses in tensile or buckled drill strings. Fatigue is a cumulative and non-reversible condition induced by repetitive cyclic bending loads and tensile or buckled drill pipe stresses. Fatigue exists even though cyclic tension of the drill pipe material is much lower than static strength limit. Present work investigates fatigue capacity of the 4" WT38 drill pipe connection where cracks have been observed. In accordance with the geometry of connection, a hot spot stress from bending moment is calculated in the crack location in the first thread (upper) of the pin. The DNVGL-RP-C203 SN-curve B1 "in air" is used as relevant fatigue SN curve for the drill pipe thread location. Finite element method (FEM) is employed in modeling and analyzing of drill pipe on pin-box connections. With this method, various connections can be investigated relatively faster and cheaper compared with experimental tests. It is found that the fatigue failure may have been caused as a result of the cyclic load level and number of load cycles. A detailed discussion of the fatigue damage assessment concludes the paper. [ABSTRACT FROM AUTHOR]

During the drilling of the carbon fiber-reinforced plastic composite, delamination causes undesirable defects that degrade the quality of products. Thus, the backup plate has been adapted to the composite drilling to prevent delamination. In this study, we present a method to predict the delamination factor of composite laminate according to the cutting conditions as well as the backup plate condition using FE model. We analyzed the damage generated at the exit surface of the composite laminate, using cohesive zone model with user-defined material model of the Abaqus/Explicit software. Damage behavior was simply simulated and quantified to the delamination factor using the parameter criterion CSDMG. Furthermore, appropriate CSDMG variables were selected to predict the accurate delamination factors considering the backup plate condition. Based on the experiment, the delamination factor was calculated with the computed tomography images of the drilled workpiece to quantify the damage. Delamination factors of prediction results and experimental data were performed. It was observed that the maximum error was 10.1% and 19.6% with and without backup plate condition respectively. [ABSTRACT FROM AUTHOR]