• Geomechanics and Engineering
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• v.7 no.4
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• pp.375-401
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• 2014

It is generally accepted that material heterogeneity has a great influence on the deformation, strength, damage and failure modes of rock. This paper presents numerical simulation on rock failure process based on the characterization of rock heterogeneity by using a digital image processing (DIP) technique. The actual heterogeneity of rock at mesoscopic scale (characterized as minerals) is retrieved by using a vectorization transformation method based on the digital image of rock surface, and it is imported into a well-established numerical code Rock Failure Process Analysis (RFPA), in order to examine the effect of rock heterogeneity on the rock failure process. In this regard, the numerical model of rock could be built based on the actual characterization of the heterogeneity of rock at the meso-scale. Then, the images of granite are taken as an example to illustrate the implementation of DIP technique in simulating the rock failure process. Three numerical examples are presented to demonstrate the impact of actual rock heterogeneity due to spatial distribution of constituent mineral grains (e.g., feldspar, quartz and mica) on the macro-scale mechanical response, and the associated rock failure mechanism at the meso-scale level is clarified. The numerical results indicate that the shape and distribution of constituent mineral grains have a pronounced impact on stress distribution and concentration, which may further control the failure process of granite. The proposed method provides an efficient tool for studying the mechanical behaviors of heterogeneous rock and rock-like materials whose failure processes are strongly influenced by material heterogeneity.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.185-192
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• 2003

In this paper, the properties on the optimal replacement policies for the general failure model are developed. In the general failure model, two types of system failures may occur : one is Type I failure (minor failure) which can be removed by a minimal repair and the other, Type II failure (catastrophic failure) which can be removed only by complete repair. It is assumed that, when the unit fails, Type I failure occurs with probability 1-p and Type II failure occurs with probability p, $0\leqp\leq1$. Under the model, the system is minimally repaired for each Type I failure, and it is repaired completely at the time of the Type II failure or at its age T, whichever occurs first. We further assume that the repair times are non-negligible. It is assumed that the minimal repair times in a renewal cycle consist of a strictly increasing geometric process. Under this model, we study the properties on the optimal replacement policy minimizing the long-run average cost per unit time.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1065-1069
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• 2005

The construction failures can be decreased through continuous improvement of construction process based upon the information of construction failures. Herein, the information of construction failures can be utilized as the key factor for identifying and enhancing various ineffective construction processes that can prevent failures. This research proposes a process model for the continuous improvement of construction processes by using construction failure information. Extensive reviews and analyses of literatures related to construction failures are performed to investigate its definition, type, cause, and lessons learned. This research adapts process modeling methodology and case-based reasoning for the development of the proposed CIMCP(continuous improvement model of construction process), and then suggests its framework that contains modules of case retrieval, case index, and case adaptation.

• Journal of the Korea Safety Management & Science
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• v.23 no.3
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• pp.27-33
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• 2021

The purpose of this study is to present a novel indicator for analyzing machine failure based on its idle time and productivity. Existing machine repair plan was limited to machine experts from its manufacturing industries. This study evaluates the repair status of machines and extracts machines that need improvement. In this study, F-RPN was calculated using the etching process data provided by the 2018 PHM Data Challenge. Each S(S: Severity), O(O: Occurence), D(D: Detection) is divided into the idle time of the machine, the number of fault data, and the failure rate, respectively. The repair status of machine is quantified through the F-RPN calculated by multiplying S, O, and D. This study conducts a case study of machine in a semiconductor etching process. The process capability index has the disadvantage of not being able to divide the values outside the range. The performance of this index declines when the manufacturing process is under control, hereby introducing F-RPN to evaluate machine status that are difficult to distinguish by process capability index.

• Journal of Applied Reliability
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• v.16 no.2
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• pp.104-109
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• 2016

Purpose: The purpose of this study is to analyze fracture behavior and failure mechanism of porous titanium for dental implant fabricated by space holder process. Method: Three porous titanium specimens with a specific volume fraction of open pore were test by 3 point bending and compression stress condition, respectively. Fracture appearance was observed by scanning electron microscope and discussed in relation with oxygen content. Results: For compression-tested specimens, two specimen showed brittle failure, while the other one showed normal failure after deformation. High oxygen content was detected in the brittle-fractured specimen. Several micro-cracks initiated at the struts propagated down to the bottom of the specimen resulting in normal failure. Conclusion: Oxygen contamination during the fabrication process can leads brittle premature failure, and hence quality problem of the porous titanium for dental implant.

• Journal of the Korean Mathematical Society
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• v.61 no.4
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• pp.693-711
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• 2024

A Markov-modulated Bernoulli process is a generalization of a Bernoulli process in which the success probability evolves over time according to a Markov chain. It has been widely applied in various disciplines for modeling and analysis of systems in random environments. This paper focuses on providing analytical characterizations of the Markovmodulated Bernoulli process by introducing key metrics, including success period, failure period, and cycle. We derive expressions for the distributions and the moments of these metrics in terms of the model parameters.

• Transactions of Materials Processing
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• v.31 no.6
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• pp.384-393
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• 2022

The flow forming process consists of a split process, a divide process, and a forming process. The split process is a forming process in which rollers radially permeate a simple disc-shaped forging material and split it in both directions to form a top-bottom bidirectional cup. It is advantageous for post-processing to deepen the forming depth in the split process but this characteristic causes the failure near the edge of the mandrel during the actual process. The split process was analyzed using Rigid Plastic FEM, and the stress analysis of the mandrel was conducted to find the cause of the failure. It was found that the failure occurred due to fatigue accumulation damage caused by repeated residual stress.

• IE interfaces
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• v.15 no.1
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• pp.64-72
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• 2002

Broaching machine is widely used for machining inner shaped slots in the work-pieces, and provides vertical motion (usually hydraulically powered) between tool and work-piece. In this study, we modelled the tool life process and investigated economic tool life of broaching machine. Tool life process is divided into wear-process and succeeding failure process. Wear process is defined as machining wear and failure process as 'chipping' occurred by random shock. We modelled wear process as linear regression function for products amounts and assumed failure process as Poisson process. Economic tool life is defined as the number of lots which minimizes average tool related cost per lot and analyzed by using age replacement policy technique. As tool-related cost factors, we consider tool replacement cost, tool maintenance cost and quality costs of products. The results of this study can be applied to analyze life process of general machining tools.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1103-1110
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• 2020

In this study, a segmented model with Upside-Down bathtub shaped failure intensity for a repairable system are proposed under the assumption that the occurrences of the failures of a repairable system follow the Non-Homogeneous Poisson Process. The proposed segmented model is the compound model of S-PLP and LIP (Segmented Power Law Process and Logistic Intensity Process), that fits the separate failure intensity functions on each segment of time interval. The maximum likelihood estimation is used for estimating the parameters of the S-PLP and LIP model. The case study of system A shows that the S-PLP and LIP model fits better than the other models when compared by AICc (Akaike Information Criterion corrected) and MSE (Mean Squared Error). And it also implies that the S-PLP and LIP model can be useful for explaining the failure intensities of similar systems.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.535-541
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• 2007

The Non-homogeneous Poisson process is probably the most popular model since it can model systems that are deteriorating or improving. The renewal process is a model that is often used to describe the random occurrence of events in time. But both these models are based on too restrictive assumptions on the effect of the repair action. The Modulated Power Law Process is a suitable model for describing the failure pattern of repairable systems when both renewal-type behavior and time trend are present. In this paper we propose maximum likelihood estimation of the next failure time after the system has experienced some failures, that is, Mean Time Between Failure for the MPLP model.