Search results for: CMOS process sensor

Authors: Supannee Chaiumporn

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This article is to introduce the meaning and form of social quality moving process as indicated by members of two suburb communities with different social and cultural contexts. The form of social quality moving process is very significant for the community and social development, because it will make the people living together with sustainable happiness. This is a qualitative study involving 30 key-informants from two suburb communities. Data were collected though key-informant interviews, and analyzed using logical content description and descriptive statistics. This research found that on the social quality component, the people in both communities stressed the procedure for social quality-making. This includes the generousness, sharing and assisting among people in the communities. These practices helped making people to live together with sustainable happiness. Living as a family or appear to be a family is the major social characteristic of these two communities. This research also found that form of social quality’s moving process of both communities stress relation of human and nature; “nature overpower humans” paradigm and influence of religious doctrine that emphasizes relations among humans. Both criteria make the form of social’s moving process simple, adaptive to nature and caring for opinion sharing and understanding among each other before action. This form of social quality’s moving process is composed of 4 steps; (1) awareness building, (2) motivation to change, (3) participation from every party concerned (4) self-reliance.

Keywords: social quality, form of social quality moving process, happiness, different social and cultural context

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Authors: Indre Brazauskaite, Vilte Auruskeviciene

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The paper explores the Stage-Gate framework application for innovation maturity among small and medium-sized enterprises (SMEs). Innovation management becomes an essential business survival process for all sizes of organizations that can be evaluated and audited systemically. This research systemically defines and assesses the innovation process from the perspective of the company’s top management. Empirical research explores attitudes and existing practices of innovation management in SMEs in Baltic countries. It structurally investigates the current innovation management practices, level of standardization, and potential challenges in the area. Findings allow to structure of existing practices based on an institutionalized model and contribute to a more advanced understanding of the innovation process among SMEs. Practically, findings contribute to advanced decision-making and business planning in the process.

Keywords: innovation measure, innovation process, SMEs, stage-gate framework

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Authors: Sukhwinder Singh Jolly

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Metal spinning is one such process in which the stresses are localized to a small area and the material is made to flow or move over the mandrel with the help of spinning tool. Spinning of tubular products can be performed by two techniques, forward spinning and backward spinning. Many researchers have studied the process both experimentally and analytically. An effort has been made to apply the process to the spinning of thin wall, highly precision, small bore long tube in hard-to-work materials such as titanium.

Keywords: metal spinning, hard-to-work materials, roller diameter, power consumption

Procedia PDF Downloads 388

Authors: K. N. Umesh

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Wood Polymer Composites (WPC) were synthesized artificially by combining polypropylene, wood and resin. It is difficult to obtain a good surface finish by conventional machining on WPC because of material degradation due to excessive heat generated during the process. In order to preserve the material property and deliver a better surface finish and accuracy, a proper solution is devised for the machining of wood composites at low temperature. This research focuses on studying the effects of parameters of cryogenic machining on sawdust incorporated polypropylene composite material, in view of evolving the most suitable composition and an appropriate combination of process parameters. The machining characteristics of the six different compositions of WPC were evaluated by analyzing the trend. An attempt is made to determine proper combinations material composition and process control parameters, through process capability studies. A WPC of 80%-wood (saw dust particles), 20%-polypropylene and 0%-resin was found to be the best alternative for obtaining the best surface finish under cryogenic machining conditions.

Keywords: Cryogenic Machining, Process Capability, Surface Finish, Wood Polymer Composites

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Authors: Behrooz Khalilloo, Hamid Shahriari, Emad Roghanian

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Process capability indices (PCIs) are important concepts of statistical quality control and measure the capability of processes and how much processes are meeting certain specifications. An important issue in statistical quality control is parameter estimation. Under the assumption of multivariate normality, the distribution parameters, mean vector and variance-covariance matrix must be estimated, when they are unknown. Classic estimation methods like method of moment estimation (MME) or maximum likelihood estimation (MLE) makes good estimation of the population parameters when data are not contaminated. But when outliers exist in the data, MME and MLE make weak estimators of the population parameters. So we need some estimators which have good estimation in the presence of outliers. In this work robust M-estimators for estimating these parameters are used and based on robust parameter estimators, robust process capability indices are introduced. The performances of these robust estimators in the presence of outliers and their effects on process capability indices are evaluated by real and simulated multivariate data. The results indicate that the proposed robust capability indices perform much better than the existing process capability indices.

Keywords: multivariate process capability indices, robust M-estimator, outlier, multivariate quality control, statistical quality control

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Authors: Saleem Z. Ramadan

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The material selection problem is concerned with the determination of the right material for a certain product to optimize certain performance indices in that product such as mass, energy density, and power-to-weight ratio. This paper is concerned about optimizing the selection of the manufacturing process along with the material used in the product under performance indices and availability constraints. In this paper, the material selection problem is formulated using binary programming and solved by genetic algorithm. The objective function of the model is to minimize the total manufacturing cost under performance indices and material and manufacturing process availability constraints.

Keywords: optimization, material selection, process selection, genetic algorithm

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Authors: Ivana Mokrá

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The article deals with modelling of the fire pragmatism in the area of military management and its experimental verification. Potential approaches are based on the synergy of mathematical and theoretical ideas, operational and tactical requirements and the military decision-making process. This issue has taken on importance in recent times, particularly with the increasing trend of digitized battlefield, the development of C4ISR systems and intention to streamline the command and control process at the lowest levels of command. From fundamental and philosophical point of view, these new approaches seek to significantly upgrade and enhance the decision-making process of the tactical commanders.

Keywords: military management, decision-making process, strike modeling, experimental evaluation, pragmatism, tactical strike modeling

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Authors: Dalia Suša Vugec, Vesna Bosilj Vukšić, Ljubica Milanović Glavan

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Business process management (BPM) is a well-known holistic discipline focused on managing business processes with the intention of achieving higher level of BPM maturity and better organizational performance. In recent period, traditional BPM faced some of its limitations like model-reality divide and lost innovation. Following latest trends, as an attempt to overcome the issues of traditional BPM, there has been an introduction of applying the principles of social software in managing business processes which led to the development of social BPM. However, there are not many authors or studies dealing with this topic so this study aims to contribute to that literature gap and to examine the link between the level of BPM maturity and the usage of social BPM. To meet these objectives, a survey within the companies with more than 50 employees has been conducted. The results reveal that the usage of social BPM is higher within the companies which achieved higher level of BPM maturity. This paper provides an overview, analysis and discussion of collected data regarding BPM maturity and social BPM within the observed companies and identifies the main social BPM principles.

Keywords: business process management, BPM maturity, process performance index, social BPM

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Authors: Mohamed Ben Amar, Najib Souissi, Chedly Bradai

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A Taguchi design investigation has been made into the relationship between the ductility and process variables in a squeeze cast 2017A wrought aluminium alloy. The considered process parameters were: squeeze pressure, melt temperature and die preheating temperature. An orthogonal array (OA), main effect, signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) are employed to analyze the effect of casting parameters. The results have shown that the selected parameters significantly affect the ductility of 2017A wrought Al alloy castings. Optimal squeeze cast process parameters were provided to illustrate the proposed approach and the results were proven to be trustworthy through practical experiments.

Keywords: Taguchi method, squeeze casting, process parameters, ductility, microstructure

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Authors: R. Sabre, W. Horrigue, J. C. Simon

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This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: spectral density, stable processes, aliasing, periodogram

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Authors: Hatem Mrad, Alban Notin, Mohamed Bouazara

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Sheet metal forming process has a multiple successive steps starting from sheets fixation to sheets evacuation. Often after forming operation, the sheet has defects requiring additional corrections steps. For example, in the drawing process, the formed sheet may have several defects such as springback, localized thinning and bends. All these defects are directly dependent on process, geometric and material parameters. The prediction and elimination of these defects requires the control of most sensitive parameters. The present study is concerned with a reliable parametric study of deep forming process in order to control the localized thinning. The proposed approach will be based on stochastic finite element method. Especially, the polynomial Chaos development will be used to establish a reliable relationship between input (process, geometric and material parameters) and output variables (sheet thickness). The commercial software Abaqus is used to conduct numerical finite elements simulations. The automatized parametrical modification is provided by coupling a FORTRAN routine, a PYTHON script and input Abaqus files.

Keywords: sheet metal forming, reliability, localized thinning, parametric simulation

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Authors: Weinian Wang, Joseph C. Chen

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The objective of this research is to optimize the process of cutting cylindrical workpieces utilizing live tooling on a HAAS ST-20 lathe. Surface roughness (Ra) has been investigated as the indicator of quality characteristics for machining process. Aluminum alloy was used to conduct experiments due to its wide range usages in engineering structures and components where light weight or corrosion resistance is required. In this study, Taguchi methodology is utilized to determine the effects that each of the parameters has on surface roughness (Ra). A total of 18 experiments of each process were designed according to Taguchi’s L9 orthogonal array (OA) with four control factors at three levels of each and signal-to-noise ratios (S/N) were computed with Smaller the better equation for minimizing the system. The optimal parameters identified for the surface roughness of the turning operation utilizing live tooling were a feed rate of 3 inches/min(A3); a spindle speed of 1300 rpm(B3); a 2-flute titanium nitrite coated 3/8” endmill (C1); and a depth of cut of 0.025 inches (D2). The mean surface roughness of the confirmation runs in turning operation was 8.22 micro inches. The final results demonstrate that Taguchi methodology is a sufficient way of process improvement in turning process on surface roughness.

Keywords: CNC milling operation, CNC turning operation, surface roughness, Taguchi parameter design

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Authors: Yan Zhang

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Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. Analytics-driven predictive maintenance is gaining increasing attention in many industries such as manufacturing, utilities, aerospace, etc., along with the emerging demand of Internet of Things (IoT) applications and the maturity of technologies that support Big Data storage and processing. This study aims to build an end-to-end analytics solution that includes both real-time machine condition monitoring and machine learning based predictive analytics capabilities. The goal is to showcase a general predictive maintenance solution architecture, which suggests how the data generated from field machines can be collected, transmitted, stored, and analyzed. We use a publicly available aircraft engine run-to-failure dataset to illustrate the streaming analytics component and the batch failure prediction component. We outline the contributions of this study from four aspects. First, we compare the predictive maintenance problems from the view of the traditional reliability centered maintenance field, and from the view of the IoT applications. When evolving to the IoT era, predictive maintenance has shifted its focus from ensuring reliable machine operations to improve production/maintenance efficiency via any maintenance related tasks. It covers a variety of topics, including but not limited to: failure prediction, fault forecasting, failure detection and diagnosis, and recommendation of maintenance actions after failure. Second, we review the state-of-art technologies that enable a machine/device to transmit data all the way through the Cloud for storage and advanced analytics. These technologies vary drastically mainly based on the power source and functionality of the devices. For example, a consumer machine such as an elevator uses completely different data transmission protocols comparing to the sensor units in an environmental sensor network. The former may transfer data into the Cloud via WiFi directly. The latter usually uses radio communication inherent the network, and the data is stored in a staging data node before it can be transmitted into the Cloud when necessary. Third, we illustrate show to formulate a machine learning problem to predict machine fault/failures. By showing a step-by-step process of data labeling, feature engineering, model construction and evaluation, we share following experiences: (1) what are the specific data quality issues that have crucial impact on predictive maintenance use cases; (2) how to train and evaluate a model when training data contains inter-dependent records. Four, we review the tools available to build such a data pipeline that digests the data and produce insights. We show the tools we use including data injection, streaming data processing, machine learning model training, and the tool that coordinates/schedules different jobs. In addition, we show the visualization tool that creates rich data visualizations for both real-time insights and prediction results. To conclude, there are two key takeaways from this study. (1) It summarizes the landscape and challenges of predictive maintenance applications. (2) It takes an example in aerospace with publicly available data to illustrate each component in the proposed data pipeline and showcases how the solution can be deployed as a live demo.

Keywords: Internet of Things, machine learning, predictive maintenance, streaming data

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Authors: Hyun-Woo Cho

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It is quite important to utilize right time and intelligent production monitoring and diagnosis of industrial processes in terms of quality and safety issues. When compared with monitoring task, fault diagnosis represents the task of finding process variables responsible causing a specific fault in the process. It can be helpful to process operators who should investigate and eliminate root causes more effectively and efficiently. This work focused on the active use of combining a nonlinear statistical technique with a preprocessing method in order to implement practical real-time fault identification schemes for data-rich cases. To compare its performance to existing identification schemes, a case study on a benchmark process was performed in several scenarios. The results showed that the proposed fault identification scheme produced more reliable diagnosis results than linear methods. In addition, the use of the filtering step improved the identification results for the complicated processes with massive data sets.

Keywords: diagnosis, filtering, nonlinear statistical techniques, process monitoring

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Authors: Samhani Ismail, Tahamina Begum, Faruque Reza, Zamzuri Idris, Hafizan Juahir, Jafri Malin Abdullah

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Holy Quran, a rhymed prosed scripture has a complete literary structure that exemplifies the peak of literary beauty. Memorizing of its verses could enhance one’s memory capacity and cognition while those who are listening to its recitation it is also believed that the Holy Quran alter brainwave producing neuronal excitation engaging with cognitive processes. 28 normal healthy subjects (male =14 & female = 14) were recruited and EEG recording was done using 128-electrode sensor net (Electrical Geosics, Inc.) with the impedance of ≤ 50kΩ. They listened to Sura Fatiha recited by Sheikh Qari Abdul Basit bin Abdus Samad. Arabic news and no sound were chosen as positive and negative control, respectively. The waveform was analysed by Fast Fourier Transform (FFT) to get the power in frequency bands. Bilateral frontal (F7, F8) and temporal region (T7, T8) showed decreased power significantly in alpha wave band in respondent stimulated by Sura Fatihah recitation reflects acoustic attention processing. However, decreased in alpha power in selective attention to memorized, and in familial but not memorized language, reveals the memorial processing in long-term memory. As a conclusion, Quranic recitation relates both cognitive element of memory and language in its listeners and memorizers.

Keywords: auditory stimulation, cognition, EEG, linguistic, memory, Quranic recitation

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Authors: Marjeta Misigoj Durakovic, Maroje Soric, Lovro Stefan

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Background and aim: Physical inactivity has been linked with increased morbidity and premature mortality and adolescence has been recognised as the critical period for a decline in physical activity (PA) level. In order to properly direct interventions aimed at increasing PA, high-risk groups of individuals should be identified. Therefore, the aim of this study is to describe gender differences in: a) PA level; b) weekly PA patterns. Methods: This investigation is a part of the CRO-PALS study which is an on-going longitudinal study conducted in a representative sample of urban youth in Zagreb (Croatia). CRO-PALS involves 903 adolescents and for the purpose of this study data from a subgroup of 190 participants with information on objective PA level were analysed (116 girls; mean age [SD]=15.6[0.3] years). Duration of moderate and vigorous PA was measured during 5 consecutive by a multiple-sensor physical activity monitor (SenseWear Armband, BodyMedia inc., Pittsburgh, USA). Gender differences in PA level were evaluated using independent samples t-test. Differences in school week and weekend levels of activity were assessed using mixed ANOVA with gender as between-subjects factor. The amount of vigorous PA had to be log-transformed to achieve normality in the distribution. Results: Boys were more active than girls. Duration of moderate-to-vigorous PA averaged 111±44 min/day in boys and 80±38 min/day in girls (mean difference=31 min/day, 95%CI=20-43 min/day). Vigorous PA was 2.5 times higher in boys compared to girls (95%CI=1.9-3.5). Participants were more active during school days than on weekends. The magnitude of the difference in moderate-to-vigorous PA was similar in both gender (p value for time*gender interaction = 0.79) and averaged 19 min/day (95%CI=11-27 min/day). Similarly, vigorous PA was 36% lower on weekends compared with school days (95%CI=22-46%) with no gender difference (p value for time*gender interaction = 0.52). Conclusion: PA level was higher in boys than in girls throughout the week. Still, in both boys and girls, the amount of PA reduced markedly on weekends compared with school days.

Keywords: adolescence, multiple-sensor physical activity monitor, physical activity level, weekly physical activity pattern

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Authors: C. W. Kan

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Cotton fibre is a commonly-used natural fibre because of its good fibre strength, high moisture absorption behaviour and minimal static problems. However, one of the main drawbacks of cotton fibre is wrinkling after washing, which is recently overcome by wrinkle-resistant treatment. 1,2,3,4-butanetetracarboxylic acid (BTCA) could improve the wrinkle-resistant properties of cotton fibre. Although the BTCA process is an effective method for wrinkle resistant application of cotton fabrics, reduced fabric strength was observed after treatment. Therefore, this paper would explore the use of atmospheric pressure plasma treatment under different discharge powers as a pretreatment process to enhance the application of BTCA process on cotton fabric without generating adverse effect. The aim of this study is to provide learning information to the users to know how the atmospheric pressure plasma treatment can be incorporated in textile finishing process with positive impact.

Keywords: learning materials, atmospheric pressure plasma treatment, cotton, wrinkle-resistant, BTCA

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Authors: Shashank Bhatnagar, W. Wilfred Godfrey

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We develop in this paper, an approach to find the trendy topic, which not only considers the user-topic interaction but also considers the community, in which user belongs. This method modifies the previous approach of user-topic interaction to user-community-topic interaction with better speed-up in the range of [1.1-3]. We assume that trend detection in a social network is dependent on two things. The one is, broadcast of messages in social network governed by self-exciting point process, namely called Hawkes process and the second is, Community Rank. The influencer node links to others in the community and decides the community rank based on its PageRank and the number of users links to that community. The community rank decides the influence of one community over the other. Hence, the Hawkes process with the kernel of user-community-topic decides the trendy topic disseminated into the social network.

Keywords: community detection, community rank, Hawkes process, influencer node, pagerank, trend detection

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Authors: Maryam Shayan

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Chemical Process Simulation (CPS) software has been generally utilized by chemical (process) designers to outline, test, advance, and coordinate process plants. It is relied upon that modern scientists to bring these same critical thinking advantages to the outline and operation of industrial ecosystems can utilize CPS. This paper gives modern environment researchers and experts with a prologue to CPS and a review of compound designing configuration standards. The paper highlights late research demonstrating that CPS can be utilized to model modern industrial ecosystems, and talks about the advantages of utilizing CPS to address a portion of the specialized difficulties confronting organizations partaking in an industrial ecosystem. CPS can be utilized to (i) quantitatively assess and analyze the potential ecological and monetary advantages of material and vitality linkages; (ii) unravel general plan, retrofit, or operational issues; (iii) help to distinguish complex and frequently irrational arrangements; and (iv) assess imagine a scenario in which situations. CPS ought to be a valuable expansion to the mechanical environment tool stash.

Keywords: chemical process simulation (CPS), process plants, industrial ecosystems, compound designing

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Authors: Gurjeet Singh, M. K. Pradhan, Ajay Verma

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The plastic industry plays very important role in the economy of any country. It is generally among the leading share of the economy of the country. Since metals and their alloys are very rarely available on the earth. So to produce plastic products and components, which finds application in many industrial as well as household consumer products is beneficial. Since 50% plastic products are manufactured by injection moulding process. For production of better quality product, we have to control quality characteristics and performance of the product. The process parameters plays a significant role in production of plastic, hence the control of process parameter is essential. In this paper the effect of the parameters selection on injection moulding process has been described. It is to define suitable parameters in producing plastic product. Selecting the process parameter by trial and error is neither desirable nor acceptable, as it is often tends to increase the cost and time. Hence optimization of processing parameter of injection moulding process is essential. The experiments were designed with Taguchi’s orthogonal array to achieve the result with least number of experiments. Here Plastic material polypropylene is studied. Tensile strength test of material is done on universal testing machine, which is produced by injection moulding machine. By using Taguchi technique with the help of MiniTab-14 software the best value of injection pressure, melt temperature, packing pressure and packing time is obtained. We found that process parameter packing pressure contribute more in production of good tensile plastic product.

Keywords: injection moulding, tensile strength, poly-propylene, Taguchi

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Authors: Gherbi Khadidja

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In the Mediterranean region, water resources are limited and very unevenly distributed in space and time. The main objective of this project is the development of a wireless network for the management of water resources in northern Algeria, the Mitidja plain, which helps farmers to irrigate in the most optimized way and solve the problem of water shortage in the region. Therefore, we will develop an aid tool that can modernize and replace some traditional techniques, according to the real needs of the crops and according to the soil conditions as well as the climatic conditions (soil moisture, precipitation, characteristics of the unsaturated zone), These data are collected in real-time by sensors and analyzed by an algorithm and displayed on a mobile application and the website. The results are essential information and alerts with recommendations for action to farmers to ensure the sustainability of the agricultural sector under water shortage conditions. In the first part: We want to set up a wireless sensor network, for precise management of water resources, by presenting another type of equipment that allows us to measure the water content of the soil, such as the Watermark probe connected to the sensor via the acquisition card and an Arduino Uno, which allows collecting the captured data and then program them transmitted via a GSM module that will send these data to a web site and store them in a database for a later study. In a second part: We want to display the results on a website or a mobile application using the database to remotely manage our smart irrigation system, which allows the farmer to use this technology and offers the possibility to the growers to access remotely via wireless communication to see the field conditions and the irrigation operation, at home or at the office. The tool to be developed will be based on satellite imagery as regards land use and soil moisture. These tools will make it possible to follow the evolution of the needs of the cultures in time, but also to time, and also to predict the impact on water resources. According to the references consulted, if such a tool is used, it can reduce irrigation volumes by up to up to 40%, which represents more than 100 million m3 of savings per year for the Mitidja. This volume is equivalent to a medium-size dam.

Keywords: optimal irrigation, soil moisture, smart irrigation, water management

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Authors: Rong-Tsorng Wang

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In this paper, we derive a pricing formula for catastrophe equity put options (or CatEPut) with non-homogeneous loss and approximated compound distributions. We assume that the loss claims arrival process is a nonhomogeneous Poisson process (NHPP) representing the clustering occurrences of loss claims, the size of loss claims is a sequence of independent and identically distributed random variables, and the accumulated loss distribution forms a compound distribution and is approximated by a heavy-tailed distribution. A numerical example is given to calibrate parameters, and we discuss how the value of CatEPut is affected by the changes of parameters in the pricing model we provided.

Keywords: catastrophe equity put options, compound distributions, nonhomogeneous Poisson process, pricing model

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Authors: Adelia Desi Agnesita

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The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

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Authors: Chai Mingming, Li Lei, Lu Xiaoxia

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In this paper, the mechanism of stratified liquids’ mixing in a cylinder is investigated. It is focused on the effects of Rayleigh-Taylor Instability (RTI) and rotation of the cylinder on liquid interface mixing. For miscible liquids, Planar Laser Induced Fluorescence (PLIF) technique is applied to record the concentration field for one liquid. Intensity of Segregation (IOS) is used to describe the mixing status. For immiscible liquids, High Speed Camera is adopted to record the development of the interface. The experiment of RTI indicates that it plays a great role in the mixing process, and meanwhile the large-scale mixing is triggered, and subsequently the span of the stripes decreases, showing that the mesoscale mixing is coming into being. The rotation experiments show that the spin-down process has a great role in liquid mixing, during which the upper liquid falls down rapidly along the wall and crashes into the lower liquid. During this process, a lot of interface instabilities are excited. Liquids mix rapidly in the spin-down process. It can be concluded that no matter what ways have been adopted to speed up liquid mixing, the fundamental reason is the interface instabilities which increase the area of the interface between liquids and increase the relative velocity of the two liquids.

Keywords: interface instability, liquid mixing, Rayleigh-Taylor Instability, spin-down process, spin-up process

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Authors: Sarakorn Sukaviriya

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This paper describes the inspection procedure, root cause analysis, the rectification of crack, and how to apply the procedure with other similar plants. During the operation of the steam turbine (620MW), instruments such as speed sensor of steam turbine, the servo valve of main stop valve and electrical wires were malfunction caused by leakage steam from main steam governing valve. Therefore, the power plant decided to shutdown steam turbines for figuring out the cause of leakage steam. Inspection techniques to be applied in this problem were microstructure testing (SEM), pipe stress analysis (FEM) and non-destructive testing. The crack was initially found on main governing valve’s weldment by visual inspection. To analyze more precisely, pipe stress analysis and microstructure testing were applied and results indicated that the crack was intergranular and originated from the weld defect. This weld defect caused the notch with high-stress concentration which created crack and then propagated to steam leakage. The major root cause of this problem was an inappropriate welding process, which created a weld defect. To repair this joint from damage, we used a welding technique by producing refinement of coarse grain HAZ and eliminating stress concentration. After the weldment was completely repaired, other adjacent weldments still had risk. Hence, to prevent any future cracks, non-destructive testing (NDT) shall be applied to all joints in order to ensure that there will be no indication of crack.

Keywords: steam-pipe leakage, steam leakage, weld crack analysis, weld defect

Procedia PDF Downloads 133

Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: Haibo Zhao, Thomas Andre, Katherine Avery, Alper Kiziltas, Deborah Mielewski

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Silica aerogels were fabricated through a modified rapid supercritical extraction (RSCE) process. The silica aerogels were made using a tetramethyl orthosilicate precursor and then placed in a hot press and brought to the supercritical point of the solvent, ethanol. In order to control the pressure release without a pressure controller, a needle valve was used. The resulting aerogels were then characterized for their physical and chemical properties and compared to silica aerogels created using similar methods. The aerogels fabricated using this modified RSCE method were found to have similar properties to those in other papers using the unmodified RSCE method. Silica aerogel infused glass blanket composite, graphene reinforced silica aerogel composite were also successfully fabricated by this new method. The modified RSCE process and system is a prototype for better gas outflow control with a lower cost of equipment setup. Potentially, this process could be evolved to a continuous low-cost high-volume production process to meet automotive requirements.

Keywords: aerogel, automotive, rapid supercritical extraction process, low cost production

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Authors: Chaiwat Tantarangsee

Abstract:

The purposes of this study are 1) to study the effects of participatory error correction process and 2) to find out the students’ satisfaction of such error correction process. This study is a Quasi Experimental Research with single group, in which data is collected 5 times preceding and following 4 experimental studies of participatory error correction process including providing coded indirect corrective feedback in the students’ texts with error treatment activities. Samples include 28 2nd year English Major students, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tools for data collection include 5 writing tests of short texts and a questionnaire. Based on formative evaluation of the students’ writing ability prior to and after each of the 4 experiments, the research findings disclose the students’ higher scores with statistical difference at 0.05. Moreover, in terms of the effect size of such process, it is found that for mean of the students’ scores prior to and after the 4 experiments; d equals 1.0046, 1.1374, 1.297, and 1.0065 respectively. It can be concluded that participatory error correction process enables all of the students to learn equally well and there is improvement in their ability to write short texts. Finally, the students’ overall satisfaction of the participatory error correction process is in high level (Mean=4.32, S.D.=0.92).

Keywords: coded indirect corrective feedback, participatory error correction process, error treatment, humanities and social sciences

Procedia PDF Downloads 523

Authors: Kwan Hee Han

Abstract:

External environment of enterprise is rapidly changing majorly by global competition, cost reduction pressures, and new technology. In these situations, production scheduling function plays a critical role to meet customer requirements and to attain the goal of operational efficiency. It deals with short-term decision making in the production process of the whole supply chain. The major task of production scheduling is to seek a balance between customer orders and limited resources. In manufacturing companies, this task is so difficult because it should efficiently utilize resource capacity under the careful consideration of many interacting constraints. At present, many computerized software solutions have been utilized in many enterprises to generate a realistic production schedule to overcome the complexity of schedule generation. However, most production scheduling systems do not provide sufficient information about the validity of the generated schedule except limited statistics. Process mining only recently emerged as a sub-discipline of both data mining and business process management. Process mining techniques enable the useful analysis of a wide variety of processes such as process discovery, conformance checking, and bottleneck analysis. In this study, the performance of generated production schedule is evaluated by mining event log data of production scheduling software system by using the process mining techniques since every software system generates event logs for the further use such as security investigation, auditing and error bugging. An application of process mining approach is proposed for the validation of the goodness of production schedule generated by scheduling software systems in this study. By using process mining techniques, major evaluation criteria such as utilization of workstation, existence of bottleneck workstations, critical process route patterns, and work load balance of each machine over time are measured, and finally, the goodness of production schedule is evaluated. By using the proposed process mining approach for evaluating the performance of generated production schedule, the quality of production schedule of manufacturing enterprises can be improved.

Keywords: data mining, event log, process mining, production scheduling

Procedia PDF Downloads 279

Authors: Wanhyun Cho, Soonja Kang, Sanggoon Kim, Soonyoung Park

Abstract:

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered an efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, importance sampling, approximate posterior distribution, marginal likelihood evidence

Procedia PDF Downloads 444