Failure Of Mechanical Components Research Articles

Mechanical behavior and microstructural deformation mechanisms of Ti-6Al-4V helix springs under prolonged extreme cryogenic temperatures and constant loading

The prolonged mechanical performance degradation and failure of elastic components in mechanical systems can pose significant safety risks and disrupt related operations. While helical compression springs' mechanical behavior and failure mechanisms at high temperatures have been well-studied, their mechanical properties and microstructural deformation mechanisms at extreme cryogenic temperatures remain largely unexplored. This paper conducts experiments to investigate the detailed mechanical properties and microstructural evolution of Ti-6Al-4V helix springs under such conditions. Initially, we examined the mechanical properties at cryogenic temperatures and compared them with those at high temperatures. It was observed that the logarithmic constitutive model applicable at high temperatures does not suitably describe the spring's mechanical behavior at cryogenic temperatures. At extremely low temperatures, the mechanical properties of the spring were enhanced. Furthermore, we characterized the microstructural deformation mechanisms using electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM), including twinning, slip activation, and dislocation evolution. The findings suggest that the deformation mechanism in Ti-6Al-4V springs under cryogenic conditions is predominantly governed by twinning and basal and prismatic slip. Due to the significant increase in the critical resolved shear stress (CRSS) of the pyramidal slip systems at cryogenic temperatures, these slip systems may not be activated during the deformation process. Additionally, the volume fraction of twinning shows a significant positive correlation with both cryogenic temperature and mechanical stress.

One Dimensional (1D) Column Buckling Factor Analysis of Al-2024 Alloy Panel

The failure mode of buckling in science is caused by mathematical instability. Material failures and structural variability, acknowledged as buckling, are two of the most common causes of the failure of mechanical components suddenly. Whenever a wall made of a larger material than either of the two other dimensions of the wall is put under axial compression, because of its size, its axial displacement will be much smaller than the size of its lateral deflection, which is a phenomenon known as buckling. In the present study, Al 2024 alloy panel, is used for buckling factor analysis and understanding the effect of boundary conditions based on Euler's formulae approach. The buckling factor was obtained for different boundary conditions by taking the length, width, and thickness panel. The theoretical buckling factor is calculated using the abovementioned formula for other boundary conditions. Then the panel analysis is done in Nastran-Patran software for different boundary conditions to compare results.

Technique for Introducing Internal Defects with Arbitrary Sizes and Locations in Metals via Additive Manufacturing and Evaluation of Fatigue Properties

Mechanical component failure is usually caused by metal fatigue originating from small defects in metallic materials. Thus, it is important to precisely capture the fatigue properties of materials containing small defects. Fatigue tests of materials with artificial surface defects introduced by drilling have been conducted. Using the resulting data, an equation for predicting the material fatigue limit has been proposed on the basis of the √area parameter model, and its effectiveness has been confirmed for various materials. However, for additive manufactured (AM) materials that contain internal defects resulting in failure, controlling the size of the defect where the fracture originates is extremely difficult. Therefore, verification of the predictive ability of the √area parameter model for AM materials is impossible, in contrast with other materials that fail because of surface defects. In this context, developing a technique to intentionally introduce internal defects with arbitrary sizes at arbitrary locations can provide insights that help predict the fatigue limit of AM materials. This study aimed to establish a technology for quantitatively evaluating the effect of internal defects on the fatigue properties of AM materials by introducing internal defects with arbitrary sizes at arbitrary locations via AM. Specimens with different defect sizes and locations were prepared. Prior to the fatigue tests, the defect sizes and locations were measured non-destructively via X-ray computed tomography (CT). The fatigue tests were conducted in air at room temperature. All the specimens failed because of the intentionally introduced internal defects, and the fatigue lives became shorter with increasing defect sizes, except for the specimens with defects adjacent to the surface. In those cases, fatigue cracks easily reached the surface; therefore, the fatigue lives were speculated to be shorter than those of the specimens with the same defect sizes. Moreover, the defect sizes determined from the fracture surfaces by scanning electron microscopy were nearly consistent with those determined by X-ray CT.

(115) Mechanical and Anatomic Indications for Inflatable Penile Prosthesis Revision

Abstract Introduction Implantation of an inflatable penile prosthesis (IPP) is considered the gold standard for definitive treatment of men with refractory erectile dysfunction. As mechanical devices, IPPs have a finite lifespan, thus often requiring surgical revision or replacement of components over time. Objective To characterize the location of IPP mechanical component failure in patients presenting for revision or explant and stratify them by device manufacturer [Boston Scientific (BSc) and Coloplast (CP)]. Methods A retrospective chart review of our large, single-surgeon, tertiary referral center penile prosthesis database between 2007-2022 was completed to identify all men who underwent IPP revision (partial or full device) or explant. Only cases having intraoperative documentation of cause for IPP failure and device manufacturer were included. Reasons for revision or replacement surgery were categorized into mechanical (tubing, cylinder, or reservoir leak and pump malfunction) and non-mechanical (component herniation, erosion, or crossover). All revisions performed due to non-mechanical reasons were excluded from analysis. Chi-square analysis was used to assess failure rates and causes. A Student’s T-test was used to assess time to revision and demographics. Results Among 933 IPP cases, we identified 133 patients who underwent 272 revision procedures; 154 met inclusion criteria (96 BSc and 58 CP). Forty-four (29%) of those surgeries were revisions of devices placed by outside surgeons, and 110 (71%) were revisions of IPPs inserted at our institution. Average patient age was 67 years for BSc and 63 years for CP (p = 0.086), and the average BMI was 28.7 for BSc and 30.8 for CP (p = 0.122). Time to revision was similar between brands at an average of 39 months for BSc and 56 months for CP (p = 0.11). Eighty-one (53%) of the surgeries were revisions of one affected implant component, 56 (36%) were full device removal/replacement, and 17 (11%) were full explants. Coloplast devices required revision more frequently due to tubing fracture (p < 0.01), and BSc devices required revision more frequently due to pump malfunction (p = 0.02). Both devices rarely failed due to cylinder or reservoir defects (Figure). Conclusions Although time to revision was similar between the two brands, CP devices malfunctioned more often due to tubing fracture whereas BSc devices failed more often due to pump malfunction. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Boston Scientific, Coloplast

The Effect of Stress Ratio on Fatigue Cracks Growth Rate in Aluminum Alloy

The financial and societal consequences of the sudden failure of various mechanical structures and components can occasionally be severe. As a result, there has been extensive research done on fatigue failure in both the scientific and industrial fields. The impact of stress ratio adjustments on the rates of fatigue fracture propagation for an aluminum alloy has been investigated in the current study. This aluminum alloy was extracted from a Russian MI25 helicopter's primary blade. The stress intensity factor was calculated and employed by creating an initial crack in the test specimens after a specimen of MI25 blade was cut into testing specimens with standard dimensions. A special program was written specifically for this purpose to draw a graph of the stress intensity factor range (k) with value of the propagation of fatigue cracks (da / dN) at each stress ratio (R); Propagation of fatigue cracks has been studied. Finally, the relationship between the two different stress ratios has been discovered. Between the two, a comparison has been established. The findings indicated that when the stress ratio rises, so too does the rate at which fatigue cracks form. Conversely, with a negative stress ratio, the negative increase leads to a reduction in the rate at which fatigue cracks grow. The data have been examined, and during the second stage of crack propagation, where (R = 0.0), pertinent equations that are compatible with the Paris equation have been discovered.

The Effect of Stress Ratio on Fatigue Cracks Growth Rate in Aluminum Alloy

The financial and societal consequences of the sudden failure of various mechanical structures and components can occasionally be severe. As a result, there has been extensive research done on fatigue failure in both the scientific and industrial fields. The impact of stress ratio adjustments on the rates of fatigue fracture propagation for an aluminum alloy has been investigated in the current study. This aluminum alloy was extracted from a Russian MI25 helicopter's primary blade. The stress intensity factor was calculated and employed by creating an initial crack in the test specimens after a specimen of MI25 blade was cut into testing specimens with standard dimensions. A special program was written specifically for this purpose to draw a graph of the stress intensity factor range (k) with value of the propagation of fatigue cracks (da / dN) at each stress ratio (R); Propagation of fatigue cracks has been studied. Finally, the relationship between the two different stress ratios has been discovered. Between the two, a comparison has been established. The findings indicated that when the stress ratio rises, so too does the rate at which fatigue cracks form. Conversely, with a negative stress ratio, the negative increase leads to a reduction in the rate at which fatigue cracks grow. The data have been examined, and during the second stage of crack propagation, where (R = 0.0), pertinent equations that are compatible with the Paris equation have been discovered.

Data-driven failure prediction and RUL estimation of mechanical components using accumulative artificial neural networks

It is necessary to develop advanced fault prognostics techniques for improving maintenance planning and scheduling to avoid unexpected shutdowns, additional expenses and decreased productivity. Such techniques include advanced failure prediction and remaining useful life (RUL) estimation of mechanical components comprising manufacturing systems with complicated structures. This study proposes a novel data-driven prognostic analysis approach for predicting the failure of a mechanical component based on its degradation path and estimating the RUL. A simulated labelled degradation dataset of a mechanical component with a predefined failure threshold was exploited. In order to increase the ability to maintain the increasing trend and the monotony of the degradation path, supervised machine learning models, including combined artificial neural network architectures and an improved version of the neuron-by-neuron training algorithm using accumulative neural networks design were applied for the prediction process.The expected degradation path was extrapolated as a testing dataset of the trained prediction model using an accumulative function. The predicted values are updated with each new data point during the training process until a failure occurs. The results show that the used approach is efficient in predicting the failure and estimating the RUL of mechanical components with high accuracy and a high prediction success rate, and it can maintain the monotonous trend of the degradation path. On the other hand, the used network architectures enable the prediction of the failures of mechanical components within a manufacturing system having a complex structure and providing a vast amount of data.

Analysis of the influence of L-PBF porosity on the mechanical behavior of AlSi10Mg by XRCT-based FEM

This work aims to present an XRCT-based FEM methodology to assess the influence of porosity defects on the mechanical behavior and failure of L-PBF AlSi10Mg components. Hence, the influence of defects on performance is estimated by means of XRCT scanning and analysis of porosity features, followed by mechanical FEM modelling of digitalized components. For this purpose, some test specimens with induced artificial porosity were manufactured by L-PBF, according to ASTM E8/E8M. Once this is done, inspection and defect characterization were carried out by means of XRCT. Porosity features such as void size, shape and location, apart from porosity percentage, were analyzed. Then, tensile tests were carried out, followed by further inspections by XRCT in order to research the relationship between the fracture level and the porosity of the as-built sample. Afterwards, virtual tensile tests of XRCT-ed specimens were modeled by FEM technique. Results obtained by the FEM model were well-correlated with the tensile experimental results to predict both ultimate tensile strength and elongation at fracture of each specimen, showing errors below 5.2%. However, the results of the final fracture level predicted by FEM analysis reveal that possibly underestimated and/or non-detected defects on the AlSi10Mg specimens seem to influence the accuracy of the fracture level prediction in some samples. Thus, XRCT arises as an ideal technology for the assessment of L-PBF-ed components.

Finite Element Analysis of the Reduction in Stress Concentration Factors in Shrink Fits by Using Contact Rings

As it is well known, shrink fits exhibit a stress concentration at the hub edges that can cause the failure of such mechanical components. A method for reducing such a stress concentration is placing a contact ring between the hub and the shaft. To achieve the desired effect, the Young Modulus of the material used for the contact ring must be lower than the one used in the hub and the shaft. Unfortunately, there are no design methods for estimating the optimal dimensions or materials of the contact ring. To fill this gap, in this study, diverse numerical simulations by the finite elements method (FEM) were carried out considering different geometries and materials in order to obtain recommendations that allow mechanical designers to significantly reduce the stress concentrations in these components. According to the obtained results, a contact ring of 25% of the hub thickness allows to significantly reduce up to 40% of the stress concentration. In addition, a linear influence of the stress reduction with the Young modulus was found thereby, and the most recommendable material for the contact ring is the one with the lowest Young modulus. On the other hand, according to the obtained results, the influence of the Poisson coefficient can be considered negligible.

Deflector shape impact on aero-acoustic noise generation and propagation

The vibroacoustic loading generated during the launch of space vehicles can cause the failure of electronic and mechanical components. Therefore, the prediction and mitigation of these vibroacoustic levels are crucial to improve the reliability of launchers and payload comfort. Because a properly designed flame deflector has the power to significantly reduce the acoustic pressure level, the aeroacoustics characteristics of diverse types of flame deflectors must be understood. Three different deflector geometries have been analysed: a wedge-type deflector, which is currently used on the VEGA rocket launch pad, a 30-degree inclined deflector, since new studies highlight its noise reduction capacity, and a flat deflector, since the impact on a flat plate is the simplest case of reflection. The sound generation and propagation in the launch platform full domain for each case were studied using dedicated computational fluid dynamics in BSC MareNostrum. To assess noise generation, the main shock waves were identified, and the evolution of the generated sound pressure was assessed. Moreover, the sound pressure levels at the fairing surface have been studied. Further research is focused right now on the use of an efficient solver running on graphics processing units that is capable of computing large-scale turbulence.

Transient-extracting transform based on non-convex sparse regularization: A useful scheme for bearing fault feature enhancement

Periodic transient shocks of vibration signals often reflect the failure of mechanical components. With the time-frequency (TF) distribution (TFD), Transient-extracting transform (TET) can descript and extract the fault-related transient component effectively. Nevertheless, vibrations collected from practical sources are always contaminated by strong background noise, thus the transient shocks are often submerged by noise components. Therefore, how to effectively extract the weak transient component from noise is an important task to achieve the bearing fault diagnosis. Considering the above issue, this paper developed a generalized mini-max concave (GMC) penalty based TET (GMCTET) for bearing fault feature enhancement. Specifically, the GMC penalty based-sparse regularization is firstly applied to the raw signal. Benefiting from the good ability of GMC penalty-based sparse regularization in both sparsity and signal fidelity. The transient shocks are initially presented, and the loss of energy amplitude of the raw signal during the processing is reduced simultaneously. Next, TET can well characterize these transient shocks via a highly readable TFD, and the transient component is extracted based on the TF coefficients. The shock structures in transient component are further highlighted after TET treatment. Finally, the bearing fault frequencies are identified through the spectrum of the extracted transient component. The effectiveness of GMCTET is verified from the comparative analysis results of the simulation and experimental studies.

Computational damage modelling of PEO coated extruded magnesium tested in slow strain rate configuration

Mechanical damage induced failure within protective coatings is one of the main reasons for loss of coating integrity. Thus, for applicability of any coating and sealing technology it is mandatory to know the stress/strain levels at which mechanical component failure will occur and it is important to understand which physical entities drive damage initiation and propagation. Within this work a model has been developed which allows correlating and study the effect of brittle porous coatings on the stress-strain curve evolution of plasma electrolytic oxidation (PEO) coated extruded Mg substrates. This is a great benefit as deriving material laws might be challenging since measured stress-strain relationships are a convolution of substrate and coating material contribution. The approach is based on a damage model which allows distinguishing between the substrate contribution model as a bulk body described by dedicated material laws, and the brittle coating contribution mathematically modelled as a boundary condition. The effect of coating thickness, the resulting steady state crack spacing and the contribution of coating porosity on the stress-strain curve is shown. The approach allows direct estimation of PEO coating barrier properties from slow-strain rate tensile testing.

Study on strain sensing property of fiber Bragg grating based on surface strain measurement of mechanical structure.

Strain monitoring is of great significance to identify the failure of key mechanical components and ensure the good operation of mechanical equipment. In terms of the common issue of the low sensitivity of fiber Bragg grating (FBG) strain sensor in strain measurement on the mechanical structure surface, this paper describes a flexible hinge strain sensor with the FBG as the sensitive element. A theoretical analysis of the sensitivity of the sensor is performed, a copper alloy material with a large elastic modulus is selected, the simulation analysis and optimization design for the structural parameters of the sensor are carried out by using ANSYS and Solidworks software, then the object of the sensor is developed according to the simulation results, and finally, the performance of the sensor is tested. The results show that the maximum deformation the sensor can measure is 0.5299 µε, the sensitivity of the sensor is ∼1.8870 pm/µε, which is approximately twice that of the bare FBG sensor, the linearity is greater than 99%, and the relative standard deviation of the repeatability is 0.9%. The results of the study provide a reference for developing the optical fiber strain sensor and further improving its sensitivity.

Failure through crack propagation in components with holes and notches: An experimental assessment of the phase field model

Fracture growth in a material is strongly influenced by the presence of inhomogeneities, which deviate crack trajectories from rectilinearity and deeply affect failure. Increasing crack tortuosity is connected to enhancement of fracture toughness, while often a crack may even be stopped when it impinges a void, which releases the stress concentration. Therefore, the determination of crack trajectories is important in the design against failure of materials and mechanical components. The recently developed phase-field approach (AT1 and AT2 models), based on a variational approach to damage localization, is believed to be particularly suited to describe complex crack trajectories. This belief is examined through a comparison between simulations and photoelastic experiments on PMMA plates, which have been designed in a new way, to highlight the effects of notches and circular holes on fracture propagation. The latter is shown to initiate from a notch and to be strongly attracted by voids. When a void is hit, fracture is arrested, unless the void contains a notch on its internal surface, from which a new crack nucleates and propagates. Different mechanical models are tested where fracture initiates and grows (i.) under Mode I compact tension, (ii.) four-point bending and (iii.) a tensile stress indirectly generated during compression of samples containing a circular hole. The experiments show that the fracture propagation may be ‘designed’ to develop in different tortuous paths, involving multiple arrests and secondary nucleation. Simulations performed with an ad hoc implemented version of the AT1 and AT2 phase-field methods (equipped with spectral decomposition, in which a crack is simulated as a highly localized zone of damage accumulation) are shown to be in close agreement with experiments and therefore confirm the validity of the approach and its potentialities for mechanical design.

Distortion after solubilization treatment of X12CrNiMoV12-3 beam-like samples: A novel FE modelling technique supported by experiments

In this work, the distortion failure of mechanical components undergoing a heat treatment is dealt with. Samples made of a 9–12% Cr steel with beam-like geometry and different set-ups in the furnace were measured with laser scanner system, before and after a solubilization (air quenching) heat treatment to evaluate its permanent deflection. A numerical model, based on the Finite Element (FE) method, was then developed and a transient thermo-mechanical analysis was performed to simulate the thermal cycle. A simulation approach, which differs from the usual methodology adopted dealing with quenching, is proposed, taking into account phase changes (Sang’s semi-empirical method) but also viscoplasticity (Nabarro-Herring creep law combined with bilinear elasto-plastic kinematic model), while the material properties were related to temperature. Comparing numerical results with experiments, it has been observed that, with respect to the case of water quenching, where the distortion is mainly related to phase transformation strains and TRIP (Transformation Induced Plasticity), in the considered case the failure seems to be mainly affected by a low-stress diffusional creep due to the proper weight, when the component is held at high temperature. The influence of different set-up to support the sample in the furnace was also investigated.

Attitude control of an underactuated satellite in presence of disturbance torque with optimal motion planning

The failure of mechanical components is a common phenomenon in satellites. This failure can happen in the satellite attitude control system, which causes that the control system of the satellite becomes underactuated. There have been many attempts to control the orientation of underactuated satellites. However, in most studies, the inertia matrix of the satellite is assumed to be diagonal with respect to the body coordinate system, and no limitations on the amount of torque applied by the reaction wheels have been considered. In this paper, at first, it is attempted to control the satellite using the motion planning method. The satellite control inputs are assumed to be cubic spline with some unknown parameters. The spline parameters are determined by minimizing a cost function defined such that the attitude of the satellite tracks desired preset values. Also, in the simulations, the inertia matrix of the satellite is considered non-diagonal and the maximum torques applied by the reaction wheels are considered limited. Then, the effect of disturbance on the controlled satellite is considered which is modeled by some external torques, and the proposed method is modified by repeating the control algorithm in short time horizons. Finally, the method is customized to be used in tracking an object by the satellite in the space which is applicable in time varying maneuvers such as observation and communications. The performance of the proposed method is demonstrated via numerical simulations.

Crack morphology in lattice-core specimens made of biopolymer via fused deposition modelling

During the last decades, it has been shown how additive manufacturing is becoming a cost-efficient alternative to produce customized parts or prototyping with traditional manufacturing processes. However, the integrity assessment of 3D printing technology parts is still challenging due to the huge number of parameters involved during the process along with the lack of industry standards. Therefore, further investigations are required to optimize the in-service behaviour of additive manufacturing parts. The objective of this work is to analyse the failure of components made from additive manufacturing under three-point bending tests in terms of crack morphology and strength. Specimens were made by a biopolymer (polylactic acid, PLA) via fused deposition modelling with different infill core densities. Next, three-point bending tests were carried out at a low strain rate under monotonic loading. In addition, three-dimensional digital image correlation was applied during tests in order to track the exterior full-field displacement and strain and output crack trajectories. The results are analysed in terms of fracture morphology and flexural strength of the post-mortem specimens, and they show the high impact of process parameters in the mechanical behaviour and failure of components made from additive manufacturing.

Modelling the nucleation and propagation of cracks at twin boundaries

Fracture arising from cracks nucleating and propagating along twin boundaries is commonly observed in metals that exhibit twinning as a plastic deformation mechanism. This phenomenon affects the failure of macroscopic mechanical components, but it is not fully understood. We present simulations in which a continuum model for discrete twins and a cohesive zone model are coupled to aid the understanding of fracture at twin boundaries. The interaction between different twin systems is modelled using a local term that depends on the continuum twin variables. Simulations reveal that the resolved shear stress necessary for an incident twin to propagate through a barrier twin can be up to eight times the resolved shear stress for twin nucleation. Interface elements are used at the interfaces between all bulk elements to simulate arbitrary intragranular cracks. An algorithm to detect twin interfaces is developed and their strength has been calibrated to give good agreement with the experimentally observed fracture path. The elasto-plastic deformation induced by discrete twins is modelled using the crystal plasticity finite element method and the stress induced by twin tips is captured. The tensile stress caused by the tip of an incident twin on a barrier twin is sufficient to nucleate a crack. A typical staircase fracture path, with cracks propagating along the twin interfaces, is reproduced only if the strength of the twin interfaces is decreased to about one-third of the strength of the bulk material. This model can be used to help understand fracture caused by the activation of multiple twin systems in different materials.

Probabilistic Analysis of Wheel Loader Failure under Rockfall Conditions Based on Bayesian Network

Rockfall is one of the most serious geological hazards in mountain regions. During the rescue situations after rockfall, the wheel loader, a vital type of modern engineering mechanism, plays an important role in relieving the obstruction of the catastrophic site. Increasing the reliability of the wheel loader during the rescue situation is quite important. This study aims to build a fault diagnosis model based on Bayesian network (BN) to diagnose the probability and path of the fault occurrence in the wheel loader during a rockfall disaster. Meanwhile, to reduce the influence of subjective factors, the fuzzy set theory is introduced into BN. The result showed that the probability of failure of the wheel loader under rockfall disaster is 13.11%. In addition, the key cause of the failure of the wheel loader under the rockfall disaster is the malfunction of mechanical parts. The probability of mechanical component failures in this case is as high as 88%, while the probability of human error is 6%. The research results not only show the ability of the BN to incorporate subjective judgment but also can provide a reference for fault diagnosis and risk assessment of wheel loaders under rockfall disaster conditions.

A Consensus Algorithm for Linear Support Vector Machines

In the era of big data, an important weapon in a machine learning researcher’s arsenal is a scalable support vector machine (SVM) algorithm. Traditional algorithms for learning SVMs scale superlinearly with the training set size, which becomes infeasible quickly for large data sets. In recent years, scalable algorithms have been designed which study the primal or dual formulations of the problem. These often suggest a way to decompose the problem and facilitate development of distributed algorithms. In this paper, we present a distributed algorithm for learning linear SVMs in the primal form for binary classification called the gossip-based subgradient (GADGET) SVM. The algorithm is designed such that it can be executed locally on sites of a distributed system. Each site processes its local homogeneously partitioned data and learns a primal SVM model; it then gossips with random neighbors about the classifier learnt and uses this information to update the model. To learn the model, the SVM optimization problem is solved using several techniques, including a gradient estimation procedure, stochastic gradient descent method, and several variants including minibatches of varying sizes. Our theoretical results indicate that the rate at which the GADGET SVM algorithm converges to the global optimum at each site is dominated by an [Formula: see text] term, where λ measures the degree of convexity of the function at the site. Empirical results suggest that this anytime algorithm—where the quality of results improve gradually as computation time increases—has performance comparable to its centralized, pseudodistributed, and other state-of-the-art gossip-based SVM solvers. It is at least 1.5 times (often several orders of magnitude) faster than other gossip-based SVM solvers known in literature and has a message complexity of O(d) per iteration, where d represents the number of features of the data set. Finally, a large-scale case study is presented wherein the consensus-based SVM algorithm is used to predict failures of advanced mechanical components in a chocolate manufacturing process using more than one million data points.This paper was accepted by J. George Shanthikumar, big data analytics.