Search results for: Gaussian process

Authors: Prashant Parhad, Vinayak Dakre, Ajay Likhite, Jatin Bhatt

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This work mainly focuses on machinability studies of Austempered Ductile Iron (ADI). The Ductile Iron (DI) was austempered at 250 oC for different durations and the process window for austempering was established by studying the microstructure. The microstructural characterization of the material was done using optical microscopy, SEM and XRD. The samples austempered as per the process window were then subjected to turning using a TiAlN-coated tungsten carbide insert to study the effect of cutting parameters, namely the cutting speed and the depth of cut. The effect was investigated in terms of cutting forces required as well as the surface roughness obtained. The turning was conducted on a CNC turning machine and primary (Fx), radial (Fy) and feed (Fz) cutting forces were quantified with a three-component dynamometer. It was observed that the magnitude of radial force was more than that of primary cutting force for all cutting speed and for various depths of cut studied. It has also been seen that increasing the cutting speed improves the surface quality. The observed machinability behaviour was investigated in light of the microstructure of the material obtained under the given austempering conditions and a structure-property- co-relation was established between the two. For all cutting speed and depth of cut, the best machining response in terms of cutting forces and surface quality was obtained towards the centre of process window.

Keywords: process window, cutting speed, depth of cut, surface roughness

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Authors: Vishakha Parihar

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This study reports the preparation of iron metal-doped nanoparticles of Titanium dioxide by the sol-gel process and the photocatalytic degradation of dye. Nano-particles were characterized by SEM, EDX, and UV-Vis spectroscopy. The detailed study confirmed that nanoparticles have grown in high density and have good optical properties. The photocatalytic batch experiment was performed in an aqueous solution where congo red dye was used as a dye pollutant under the irradiation of ultraviolet rays created by using a mercury lamp source. Total degradation efficiency achieved was approximately 85% to 93% in the duration of 100-120 minutes of irradiation under an ultraviolet light source. The decolorization ability of this process was measured by absorbance at a maximum wavelength of 498nm. The results indicated that the iron-doped Titanium dioxide nanoparticles showed an excellent photocatalytic response to the degradation of dye under the ultraviolet light source within a very short period of time.

Keywords: titanium dioxide, nano-particles iron dope, photocatalytic degradation, Congo red dye, sol-gel process

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Authors: Mohamed A. Deyab, Ahmed E. Awadallah

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Under various conditions, we present a promising method for producing pure hydrogen energy from the electrochemical reaction of Mg metal in waste oilfield water (WOW). Mg metal and WOW are primarily consumed in this process. The results show that the hydrogen gas output is highly dependent on temperature and solution pH. The best conditions for hydrogen production were found to be a low pH (2.5) and a high temperature (338 K). For the first time, the Allyl methylimidazolium bis-trifluoromethyl sulfonyl imide) (IL) ionic liquid is used to regulate the rate of hydrogen generation. It has been confirmed that increasing the solution temperature and decreasing the solution pH accelerates Mg dissolution and produces more hydrogen per unit of time. The adsorption of IL on the active sites of the Mg surface is unrestricted by mixing physical and chemical orientation. Inspections using scanning electron microscopy (SEM), energy dispersive X-ray (EDX), and FT-IR spectroscopy were used to identify and characterise surface corrosion of Mg in WOW. This process is also completely safe and can create energy on demand.

Keywords: hydrogen production, Mg, wastewater, ionic liquid

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Authors: Kousar Shaheen

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The electoral process of Pakistan always remains underestimated due to malpractices claimed by the political leaders. The democratic system relies on public decision, selectorial process, transparent arrangements made by public administration, and governance system. Political polarization plays a vital role in any democratic system, which depends upon the way of applying leadership capabilities. In modern societies, public engagement is playing a key role in changing political polarization and implementation of the newest technologies, e-leadership and e-governance to bring e-democracy. The Overseas Pakistanis are unable to cast their votes in the selectorial process of Pakistan. To align this issue with civil society, efforts were made to implement modernized services and facilities by intervening in the Supreme Court. However, the results were found insignificant because of ineffective citizen engagement, IT-based, governance and public administration. which proved that the shifting to advanced society is crucial in Pakistan due to the elected Officials of current democratic system. It is an empirical study to involve Pakistani nationals (overseas) in the democratic process by utilizing the digital facility of vote casting. The role of Government. The role of e-leadership in changing the political polarization for the implementation of e-election will be measured by collecting data from different sources.

Keywords: e-democracy, e-leadership, political polarization, public engagement

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Authors: Wei Zha, Jingzeng Zhang, Chen Zhao, Ran Cai, Xueyuan Nie

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Cathodic plasma electrolysis (CPE) is used to create surface textures on cast iron samples for improving the tribological properties. Micro craters with confined size distribution were successfully formed by CPE process. These craters can generate extra hydrodynamic pressure that separates two sliding surfaces, increase the oil film thickness and accelerate the transition from boundary to mixed lubrication. It was found that the optimal crater size was 1.7 μm, at which the maximum lubrication efficiency was achieved. The Taguchi method was used to optimize the process parameters (voltage and roughness) for CPE surface texturing. The orthogonal array and the signal-to-noise ratio were employed to study the effect of each process parameter on the coefficient of friction. The results showed that with higher voltage and lower roughness, the lower friction coefficient can be obtained, and thus the lubrication can be more efficiently used for friction reduction.

Keywords: cathodic plasma electrolysis, friction, lubrication, plasma surface texturing

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Rima Al-Awadhi, Abdul Jaleel Tharayil

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On a regular basis, KOC engages into various types of Projects. However, due to very nature and complexity involved, each project experience generates a lot of ‘learnings’ that need to be factored into while drafting a new contract and thus avoid repeating the same mistakes. But, many a time these learnings are localized and remain as tacit leading to scope re-work, larger cycle time, schedule overrun, adjustment orders and claims. Also, these experiences are not readily available to new employees leading to steep learning curve and longer time to competency. This is to share our experience in designing and implementing a process driven architecture for the ‘lessons learnt’ knowledge sharing framework in KOC. It high-lights the ‘lessons learnt’ sharing process adopted, integration with the organizational processes, governance framework, the challenges faced and learning from our experience in implementing a ‘lessons learnt’ framework.

Keywords: lessons learnt, knowledge transfer, knowledge sharing, successful practices, Lessons Learnt Workshop, governance framework

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Authors: Antonio Brigido, Maria Meireles, Francisco Barros, Gaspar Mota, Fernanda Terra, Lidia Melo, Marcelo Reis, Camilo Souza

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As the globalization of the software process advances, companies are increasingly committed to improving software development technologies across multiple locations. On the other hand, working with teams distributed in different locations also raises new challenges. In this sense, automated processes can help to improve the quality of process execution. Therefore, this work presents the development of a tool called TSS Script that automates the sample preparation process for carrier requirements validation tests. The objective of the work is to obtain significant gains in execution time and reducing errors in scenario preparation. To estimate the gains over time, the executions performed in an automated and manual way were timed. In addition, a questionnaire-based survey was developed to discover new requirements and improvements to include in this automated support. The results show an average gain of 46.67% of the total hours worked, referring to sample preparation. The use of the tool avoids human errors, and for this reason, it adds greater quality and speed to the process. Another relevant factor is the fact that the tester can perform other activities in parallel with sample preparation.

Keywords: Android, GSD, automated testing tool, mobile products

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Authors: Nagri Sateesh, Kundavarapu Vengalrao, Kopparthi Phaneendra Kumar

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Vacuum assisted resin transfer molding (VARTM) is one of the manufacturing technique that is viable for production of fiber reinforced polymer composite components suitable for aerospace, marine and commercial applications. However, the repeatable quality of the product can be achieved by critically fixing the process parameters such as Vacuum Pressure (VP) and permeability of the preform. The present investigation is aimed at studying the effect of permeability for production of Glass Fiber Reinforced Plastic (GFRP) components with consistent quality. The VARTM mould is made with an acrylic transparent top cover to observe and record the resin flow pattern. Six layers of randomly placed glass fiber under five different vacuum pressures VP1 = 0.013, VP2 = 0.026, VP3 = 0.039, VP4 = 0.053 and VP5 = 0.066 MPa were studied. The laminates produced by this process under the above mentioned conditions were characterized with ASTM D procedures so as to study the effect of these process parameters on the quality of the laminate. Moreover, as mentioned there is a considerable effect of permeability on the impact strength and the void content in the laminates under different vacuum pressures. SEM analysis of the impact tested fractured GFRP composites showed the bonding of fiber and matrix.

Keywords: permeability, vacuum assisted resin transfer molding (VARTM), ASTM D standards, SEM

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Authors: B. R. Campomanes-Alvarez, P. Quiros, B. Fernandez

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Automatic Speech Recognition (ASR) is a machine-based process of decoding and transcribing oral speech. A typical ASR system receives acoustic input from a speaker or an audio file, analyzes it using algorithms, and produces an output in the form of a text. Some speech recognition systems use Hidden Markov Models (HMMs) to deal with the temporal variability of speech and Gaussian Mixture Models (GMMs) to determine how well each state of each HMM fits a short window of frames of coefficients that represents the acoustic input. Another way to evaluate the fit is to use a feed-forward neural network that takes several frames of coefficients as input and produces posterior probabilities over HMM states as output. Deep neural networks (DNNs) that have many hidden layers and are trained using new methods have been shown to outperform GMMs on a variety of speech recognition systems. Acoustic models for state-of-the-art ASR systems are usually training on massive amounts of data. However, audio files with their corresponding transcriptions can be difficult to obtain, especially in the Spanish language. Hence, in the case of these low-resource scenarios, building an ASR model is considered as a complex task due to the lack of labeled data, resulting in an under-trained system. Semi-supervised learning approaches arise as necessary tasks given the high cost of transcribing audio data. The main goal of this proposal is to develop a procedure based on acoustic semi-supervised learning for Spanish ASR systems by using DNNs. This semi-supervised learning approach consists of: (a) Training a seed ASR model with a DNN using a set of audios and their respective transcriptions. A DNN with a one-hidden-layer network was initialized; increasing the number of hidden layers in training, to a five. A refinement, which consisted of the weight matrix plus bias term and a Stochastic Gradient Descent (SGD) training were also performed. The objective function was the cross-entropy criterion. (b) Decoding/testing a set of unlabeled data with the obtained seed model. (c) Selecting a suitable subset of the validated data to retrain the seed model, thereby improving its performance on the target test set. To choose the most precise transcriptions, three confidence scores or metrics, regarding the lattice concept (based on the graph cost, the acoustic cost and a combination of both), was performed as selection technique. The performance of the ASR system will be calculated by means of the Word Error Rate (WER). The test dataset was renewed in order to extract the new transcriptions added to the training dataset. Some experiments were carried out in order to select the best ASR results. A comparison between a GMM-based model without retraining and the DNN proposed system was also made under the same conditions. Results showed that the semi-supervised ASR-model based on DNNs outperformed the GMM-model, in terms of WER, in all tested cases. The best result obtained an improvement of 6% relative WER. Hence, these promising results suggest that the proposed technique could be suitable for building ASR models in low-resource environments.

Keywords: automatic speech recognition, deep neural networks, machine learning, semi-supervised learning

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Authors: M. Brik, S. Harmand, I. Zaaroura

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This report, an experimental investigation, concerns the sessile daughter drop remaining during the coalescence of water drops in a liquid-liquid (LL) system. The two drops are initially vertically aligned where the sessile drop is deposited on a chemically treated super-hydrophobic surface of a cube fill of silicone oil. In order to analyze the coalescence dynamics, a series of experiments have been performed using a generation droplets system (KRUSS) that measures contact angles as well coupled with a high-speed camera (Keyence VW-9000E) to record the process at a frame rate of 15000s-1. It’s depicted that in such configuration, the head drop volume has a primordial impact on the dynamics of the coalescence process, especially at the last stage. It’s found that for a sessile drop deposited on a super-hydrophobic surface, where the contact angle is about θ ≈ 145°, the coalescence process is remarked to be complete without any recoiling of the coalesced drop or a generation of a sessile daughter drop at the super-hydrophobic surface when the head drop volume is small enough (Vₐᵦ< Vₛ up to Vₐᵦ = 3Vₛ). On the other side, the coalescence process starts to be followed by jumping off the resulted drop as well as a remaining of a small sessile daughter drop on the bottom surface of the cube from a head drop volume Vₐᵦ of about 4 times than that of the sessile drop Vₛ.

Keywords: drops coalescence, dispersed multiphase flow, drops dynamics, liquid-liquid system

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Authors: Kulachai Kultawanich, Prakob Koraneekij, Jaitip Na-Songkhla

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The way of learning has been changed into a new paradigm since the improvement of network and communication technology, so learners have to interact with massive amount of the information. Thus, information literacy has become a critical set of abilities required by every college and university in the world. Connectivism is considered to be an alternative way to design information literacy course in online learning environment, such as Virtual Classroom (VC). With the change of learning pedagogy, VC is employed to improve the social capability by integrating cloud-based technology. This paper aims to study the use of Cloud-based Virtual Classroom (CBVC) in Connectivism learning process to enhance information literacy and self-efficacy of twenty-one undergraduate students who registered in an e-publishing course at Chulalongkorn University. The data were gathered during 6 weeks of the study by using the following instruments: (1) Information literacy test (2) Information literacy rubrics (3) Information Literacy Self-Efficacy (ILSE) Scales and (4) Questionnaire. The result indicated that students have information literacy and self-efficacy posttest mean scores higher than pretest mean scores at .05 level of significant after using CBVC in Connectivism learning process. Additionally, the study identified that the Connectivism learning process proved useful for developing information rich environment and a sense of community, and the CBVC proved useful for developing social connection.

Keywords: cloud-based, virtual classroom, connectivism, information literacy

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Authors: Muhammad Idrees, Masroor Abro, Sikandar Almani

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Presently, the increasing CO₂ concentration in the atmosphere has been taken as one of the major challenges faced by the modern world. The average CO₂ in the atmosphere reached the highest value of 414.72 ppm in 2021, as reported in a conference of the parties (COP26). This study focuses on (i) the comparative study of MEA, NaOH, Acetic acid, and Na₂CO₃ in terms of their CO₂ capture performance, (ii) the significance of adding various frothing agents achieving improved absorption capacity of Na₂CO₃ and (iii) the overall economic evaluation of process with the help of Aspen Plus. The results obtained suggest that the addition of frothing agents significantly increased the absorption rate of dilute sodium carbonate such that from 45% to 99.9%. The effect of temperature, pressure and flow rate of liquid and flue gas streams on CO₂ absorption capacity was also investigated. It was found that the absorption capacity of Na₂CO₃ decreased with increasing temperature of the liquid stream and decreasing flow rate of the liquid stream and pressure of the gas stream.

Keywords: CO₂, absorbents, frothing agents, process simulation

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Authors: Ujwal Kishor Zore, Shankar Balajirao Kausley, Aniruddha Bhalchandra Pandit

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There are some important design parameters of activated sludge process (ASP) for wastewater treatment and they must be optimally defined to have the optimized plant working. To know them, developing a mathematical model is a way out as it is nearly commensurate the real world works. In this study, a mathematical model was developed for ASP, solved under activated sludge model no 1 (ASM 1) conditions and MATLAB tool was used to solve the mathematical equations. For its real-life validation, the developed model was tested for the inputs from the municipal wastewater treatment plant and the results were quite promising. Additionally, the most cardinal assumptions required to design the treatment plant are discussed in this paper. With the need for computerization and digitalization surging in every aspect of engineering, this mathematical model developed might prove to be a boon to many biological wastewater treatment plants as now they can in no time know the design parameters which are required for a particular type of wastewater treatment.

Keywords: waste water treatment, activated sludge process, mathematical modeling, optimization

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Authors: Achim Kampker, Heiner Hans Heimes, Nemanja Sarovic, Jan-Philip Ganser, Saskia Wessel, Christoph Lienemann

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The electrification of the power train is a fundamental technical transition in the automotive industry and poses a major challenge for established car companies. Providing the traction energy, requiring an ever greater amount of space within the car and having a high share of value-add the lithium-ion battery is a central component of the electric power train and a completely new component to car manufacturers at the same time. Being relatively new to the automotive industry, the current design of the product architecture and production process (including manufacturing and assembling processes) of lithium-ion battery modules do not allow for an easy and cost-efficient disassembly or product design change. Yet these two requirements will increase in importance with rising sales volumes of electric cars in the near future and need to be addressed for the electric car to be competitive with conventional power train systems. This paper focuses on the current product architecture and production process of common automotive battery modules from prismatic lithium-ion battery cells to derive impacts for a remanufacturing concept. The information necessary for this purpose were gathered by literature research, patent inquiries, industry expert interviews and first-hand experiences of the authors. On the basis of these results, the underlying causes for the design´s lack of remanufacturability and flexibility with regards to product design changes are examined. In all, this paper gives an extensive and detailed overview of the state of the art of the product architecture and production process of lithium-ion battery modules from prismatic battery cells, identifies its deficiencies and derives improvement measures.

Keywords: battery module, prismatic lithium-ion battery cell, product architecture, production process, remanufacturing, flexibility

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Authors: Nixon Kuruvila, H. V. Ravindra

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Wire-cut Electro Discharge Machining (WEDM) is a special form of conventional EDM process in which electrode is a continuously moving conductive wire. The present study aims at determining parametric influence and optimum process parameters of Wire-EDM using Taguchi’s Technique and Genetic algorithm. The variation of the performance parameters with machining parameters was mathematically modeled by Regression analysis method. The objective functions are Dimensional Accuracy (DA) and Material Removal Rate (MRR). Experiments were designed as per Taguchi’s L16 Orthogonal Array (OA) where in Pulse-on duration, Pulse-off duration, Current, Bed-speed and Flushing rate have been considered as the important input parameters. The matrix experiments were conducted for the material Oil Hardened Non Shrinking Steel (OHNS) having the thickness of 40 mm. The results of the study reveals that among the machining parameters it is preferable to go in for lower pulse-off duration for achieving over all good performance. Regarding MRR, OHNS is to be eroded with medium pulse-off duration and higher flush rate. Finally, the validation exercise performed with the optimum levels of the process parameters. The results confirm the efficiency of the approach employed for optimization of process parameters in this study.

Keywords: dimensional accuracy (DA), regression analysis (RA), Taguchi method (TM), volumetric material removal rate (VMRR)

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Authors: Andrea Macruz

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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience

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Authors: Pardeep, Yugandhar Bitla, A. K. Patra, G. A. Basheed

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The topological protected nanosized particle-like swirling spin textures, “skyrmion,” has been observed in various ferromagnets with chiral crystal structures like MnSi, FeGe, Cu₂OSeO₃ alloys, however the magnetic ordering in these systems takes place at very low temperatures. For skyrmion-based spintronics devices, the skyrmion phase is required to stabilize in a wide temperature – field (T - H) region. The equilibrium skyrmion phase (SkX) in Co₇Zn₇Mn₆ alloy exists in a narrow T – H region just below transition temperature (TC ~ 215 K) and can be quenched by field cooling as a metastable skyrmion phase (MSkX) below SkX region. To realize robust MSkX at 110 K, field sweep ac susceptibility χ(H) measurements were performed after the zero field cooling (ZFC) and field cooling (FC) process. In ZFC process, the sample was cooled from 320 K to 110 K in zero applied magnetic field and then field sweep measurement was performed (up to 2 T) in positive direction (black curve). The real part of ac susceptibility (χ′(H)) at 110 K in positive field direction after ZFC confirms helical to conical phase transition at low field HC₁ (= 42 mT) and conical to ferromagnetic (FM) transition at higher field HC₂ (= 300 mT). After ZFC, FC measurements were performed i.e., sample was initially cooled in zero fields from 320 to 206 K and then a sample was field cooled in the presence of 15 mT field down to the temperature 110 K. After FC process, isothermal χ(H) was measured in positive (+H, red curve) and negative (-H, blue curve) field direction with increasing and decreasing field upto 2 T. Hysteresis behavior in χ′(H), measured after ZFC and FC process, indicates the stabilization of MSkX at 110 K which is in close agreement with literature. Also, the asymmetry between field-increasing curves measured after FC process in both sides confirm the stabilization of MSkX. In the returning process from the high field polarized FM state, helical state below HC₁ is destroyed and only the conical state is observed. Thus, the robust MSkX state is stabilized below its SkX phase over a much wider T - H region by FC in polycrystalline Co₇Zn₇Mn₆ alloy.

Keywords: skyrmions, magnetic susceptibility, metastable phases, topological phases

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: Bussabamintra Chalauisaeng

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The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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Authors: Nibedita Pani, Vishnu Tejani, T. S. Anantha Singh

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Water pollution resulting from discharge of partial/not treated textile wastewater containing high carbon and nitrogen pollutants pose a huge threat to the environment, ecosystem, and human health. It is essential to remove carbon- and nitrogen-based organic pollutants more effectively from industrial wastewater before discharging. The present study focuses on removal of carbon-based pollutant in particular COD (chemical oxygen demand) and nitrogen-based pollutants, in particular, ammoniacal nitrogen by Fenton oxidation process using Fe²⁺ and H₂O₂ as reagents. The study was carried out with high strength wastewater containing initial COD 5632 mg/L and NH⁴⁺-N 1372 mg/L. The major operating condition like pH was varied between 1.0 to 4.0. The maximum degradation was obtained at pH 3.0 taking the molar ratio of Fe²⁺/H₂O₂ as 1:1. At this pH, the removal efficiencies of COD and ammoniacal nitrogen were found to be 77.27% and 74.9%, respectively. The Fenton process can be the best alternative for the simultaneous removal of COD and NH4+-N from industrial wastewater.

Keywords: ammoniacal nitrogen, COD, Fenton oxidation, industrial wastewater

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Authors: N. Wongsai, R. Wetprasit, V. Siddoo

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The recently introduced ISO/IEC 29110 standard Lifecycle profile for Very Small Entities (VSE) has been adopted and practiced in many small and medium software companies, including in Thailand’s software industry. Many Thai companies complete their software process improvement (SPI) initiative program and have been certified. There are, however, a number of participants fail to success. This study was concerned with the factors that influence the accomplishment of the standard implementation in various VSE characteristics. In order to achieve this goal, exploring and extracting critical factors from prior studies were carried out and then the obtained factors were validated by the standard experts. Data analysis of comments and recommendations was performed using a qualitative content analysis method. This paper presents the initial set of influence factors in both positive and negative impact the ISO/IEC 29110 implementation with an aim at helping such SPI practitioners with some considerations to manage appropriate adoption approach in order to achieve its implementation.

Keywords: barriers, critical success factors, ISO/IEC 29110, Software Process Improvement, SPI, Very-Small Entity, VSE

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Authors: Vipul M. Patel, Hemantkumar B. Mehta

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Technological innovations in electronic world demand novel, compact, simple in design, less costly and effective heat transfer devices. Closed Loop Pulsating Heat Pipe (CLPHP) is a passive phase change heat transfer device and has potential to transfer heat quickly and efficiently from source to sink. Thermal performance of a CLPHP is governed by various parameters such as number of U-turns, orientations, input heat, working fluids and filling ratio. The present paper is an attempt to predict the thermal performance of a CLPHP using Artificial Neural Network (ANN). Filling ratio and heat input are considered as input parameters while thermal resistance is set as target parameter. Types of neural networks considered in the present paper are radial basis, generalized regression, linear layer, cascade forward back propagation, feed forward back propagation; feed forward distributed time delay, layer recurrent and Elman back propagation. Linear, logistic sigmoid, tangent sigmoid and Radial Basis Gaussian Function are used as transfer functions. Prediction accuracy is measured based on the experimental data reported by the researchers in open literature as a function of Mean Absolute Relative Deviation (MARD). The prediction of a generalized regression ANN model with spread constant of 4.8 is found in agreement with the experimental data for MARD in the range of ±1.81%.

Keywords: ANN models, CLPHP, filling ratio, generalized regression, spread constant

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Authors: Keshav Dubey, Swajeeth Panchangam, Arun Rajendran, Swarnim Gupta

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In the semiconductor capital equipment industry, effective modeling of repairable system reliability is crucial for optimizing maintenance strategies and ensuring operational efficiency. However, repairable system reliability modeling using a renewal process is not as popular in the semiconductor equipment industry as it is in the locomotive and automotive industries. Utilization of this approach will help optimize maintenance practices. This paper presents a structured framework that leverages both parametric and non-parametric approaches to model the reliability of repairable subsystems based on operational data, maintenance schedules, and system-specific conditions. Data is organized at the equipment ID level, facilitating trend testing to uncover failure patterns and system degradation over time. For non-parametric modeling, the Mean Cumulative Function (Mean Cumulative Function) approach is applied, offering a flexible method to estimate the cumulative number of failures over time without assuming an underlying statistical distribution. This allows for empirical insights into subsystem failure behavior based on historical data. On the parametric side, virtual age modeling, along with Homogeneous and Non-Homogeneous Poisson Process (Homogeneous Poisson Process and Non-Homogeneous Poisson Process) models, is employed to quantify the effect of repairs and the aging process on subsystem reliability. These models allow for a more structured analysis by characterizing repair effectiveness and system wear-out trends over time. A comparison of various Generalized Renewal Process (GRP) approaches highlights their utility in modeling different repair effectiveness scenarios. These approaches provide a robust framework for assessing the impact of maintenance actions on system performance and reliability. By integrating both parametric and non-parametric methods, this framework offers a comprehensive toolset for reliability engineers to better understand equipment behavior, assess the effectiveness of maintenance activities, and make data-driven decisions that enhance system availability and operational performance in semiconductor fabrication facilities.

Keywords: reliability, maintainability, homegenous poission process, repairable system

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Authors: Gyeong-Sung Kim, In-soo Ahn, Yong Cho

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SBR (Sequencing Batch Reactor) process is usually applied to membrane water treatment plants to treat its concentrated wastewater. The role of SBR process is to remove COD (Chemical Oxygen Demand) and NH3 from wastewater before discharging it outside of the water treatment plant using microorganism. Microorganism’s nitrification capability is influenced by water temperature because the nitrification rate of the concentrated wastewater becomes ‘zero’ as water temperature approach 0℃. Heating system is necessary to operate SBR in winter season even though the operating cost increase sharply. The operating cost of SBR at ‘D’ RO water treatment plant in Korea was 51.8 times higher in winter (October to March) compare to summer (April to September) season in 2014. Otherwise the effluent water temperature maintained around 8℃ constantly in winter. This study focuses on application heat pump system to recover the thermal energy from the effluent water of ‘D’ RO plant so that the operating cost will be reduced.

Keywords: water treatment, water thermal energy, energy saving, RO, SBR

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

Abstract:

Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Phan Nghiem Vu, Le Tuan Vu, Ta Quang Tai

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The optimal construction design used during the execution of a construction project is a key factor in determining high productivity and customer satisfaction, however, this management process sometimes is carried out without care and the systematic method that it deserves, bringing negative consequences. This study proposes a knowledge management (KM) approach that will enable the intelligent use of experienced and acknowledged engineers to improve the management of construction design works for a project. Then a knowledge-based application to support this decision-making process is proposed and described. To define and design the system for the application, semi-structured interviews were conducted within five construction consulting organizations with the purpose of studying the way that the method’ optimizing process is implemented in practice and the knowledge supported with it. A system of an optimizing construction design works (OCDW) based on knowledge was developed then validated with construction experts. The OCDW was liked as a valuable tool for construction design works’ optimization, by supporting organizations to generate a corporate memory on this issue, reducing the reliance on individual knowledge and also the subjectivity of the decision-making process. The benefits are described as provided by the performance support system, reducing costs and time, improving product design quality, satisfying customer requirements, expanding the brand organization.

Keywords: optimizing construction design work, construction consultant organization, knowledge management, knowledge-based application

Procedia PDF Downloads 128

Authors: Muna Khethier Abbass, Khairia Salman Hussan, Huda Mohummed AbdudAlaziz

Abstract:

This work aims to study the effect of shot peening on the mechanical properties of welded joints which performed by two different welding processes: Tungsten inert gas (TIG) welding and friction stir welding (FSW) processes of aluminum alloy 6061 T6. Arc welding process (TIG) was carried out on the sheet with dimensions of (100x50x6 mm) to obtain many welded joints with using electrode type ER4043 (AlSi5) as a filler metal and argon as shielding gas. While the friction stir welding process was carried out using CNC milling machine with a tool of rotational speed (1000 rpm) and welding speed of (20 mm/min) to obtain the same butt welded joints. The welded pieces were tested by X-ray radiography to detect the internal defects and faulty welded pieces were excluded. Tensile test specimens were prepared from welded joints and base alloy in the dimensions according to ASTM17500 and then subjected to shot peening process using steel ball of diameter 0.9 mm and for 15 min. All specimens were subjected to Vickers hardness test and micro structure examination to study the effect of welding process (TIG and FSW) on the micro structure of the weld zones. Results showed that a general decay of mechanical properties of TIG and FSW welded joints comparing with base alloy while the FSW welded joint gives better mechanical properties than that of TIG welded joint. This is due to the micro structure changes during the welding process. It has been found that the surface hardening by shot peening improved the mechanical properties of both welded joints, this is due to the compressive residual stress generation in the weld zones which was measured using X-Ray diffraction (XRD) inspection.

Keywords: friction stir welding, TIG welding, mechanical properties, shot peening

Procedia PDF Downloads 337

Authors: Golovchun Aleftina, Dabyltayeva Raikhan

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Nowadays, in the world of widely developing cross-cultural interactions and rapidly changing demands of the global labor market, foreign language teaching and learning has taken a special role not only in school education but also in everyday life. Cognitive Lingua-Cultural Methodology of Foreign Language Teaching originated in Kazakhstan brings a communicative approach to the forefront in foreign language teaching that gives raise a variety of techniques to make the language learning a real communication. One of these techniques is Computer Assisted Language Learning. In our article, we aim to: demonstrate what learning benefits students are likely to get by teachers having implemented computer-based technologies into foreign language teaching process; prove that technology-based classroom serves as the best tool for interactive and efficient language learning; give examples of classroom sufficient organization with computer-based activities.

Keywords: computer assisted language learning, learning benefits, foreign language teaching process, implementation, communicative approach

Procedia PDF Downloads 471