Search results for: artificial intelligence in semiconductor manufacturing

Authors: B. Ravi Kumar, S. Gajanana, K. Hemachandra Reddy, K. Udayani

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Physically into various derived shapes and sizes under the effect of externally applied forces. The spinning process is an advanced plastic working technology and is frequently used for manufacturing axisymmetric shapes. Over the last few decades, Sheet metal spinning has developed significantly and spun products have widely used in various industries. Nowadays the process has been expanded to new horizons in industries, since tendency to use minimum tool and equipment costs and also using lower forces with the output of excellent surface quality and good mechanical properties. The automation of the process is of greater importance, due to its wider applications like decorative household goods, rocket nose cones, gas cylinders, etc. This paper aims to gain insight into the conventional spinning process by employing experimental and numerical methods. The present work proposes an approach for optimizing process parameters are mandrel speed (rpm), roller nose radius (mm), thickness of the sheet (mm). Forming force, surface roughness and strain are the responses.in spinning of Aluminum (2024-T3) using DOE-Response Surface Methodology (RSM) and Analysis of variance (ANOVA). The FEA software is used for modeling and analysis. The process parameters considered in the experimentation.

Keywords: FEA, RSM, process parameters, sheet metal spinning

Procedia PDF Downloads 319

Authors: Tolulope Aremu

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The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: Daneal Rorke, Gueguim Kana

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The shift towards renewable energy sources for biofuel production has received increasing attention. However, the use and pre-treatment of lignocellulosic material are inundated with the generation of fermentation inhibitors which severely impact the feasibility of bioprocesses. This study reports the profiling of all volatile compounds generated during microwave assisted chemical pre-treatment of sorghum leaves. Furthermore, the optimization of reducing sugar (RS) from microwave assisted acid pre-treatment of sorghum leaves was assessed and gave a coefficient of determination (R2) of 0.76, producing an optimal RS yield of 2.74 g FS/g substrate. The development of an intelligent model to predict volatile compound fractions gave R2 values of up to 0.93 for 21 volatile compounds. Sensitivity analysis revealed that furfural and phenol exhibited high sensitivity to acid concentration, alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity as well. These findings illustrate the potential of using an intelligent model to predict the volatile compound fraction profile of compounds generated during pre-treatment of sorghum leaves in order to establish a more robust and efficient pre-treatment regime for biofuel production.

Keywords: artificial neural networks, fermentation inhibitors, lignocellulosic pre-treatment, sorghum leaves

Procedia PDF Downloads 247

Authors: Anett Nagy, Anna Maria Beke, Rozsa Graf, Magda Kalmar

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Premature birth involves developmental risks – the earlier the baby is born and the lower its birth weight, the higher the risks. The developmental outcomes for immature, low birth weight infants are hard to predict. Our aim is to identify the factors influencing infant and preschool-age development in very low birth weight (VLBW) and extremely low birth weight (ELBW) preterms. Sixty-one subjects participated in our longitudinal study, which consisted of thirty VLBW and thirty-one ELBW children. The psychomotor development of the infants was assessed using the Brunet-Lezine Developmental Scale at the corrected ages of one and two years; then at three years of age, they were tested with the WPPSI-IV IQ test. Birth weight, gestational age, perinatal complications, gender, and maternal education, were added to the data analysis as independent variables. According to our assessments, our subjects as a group scored in the average range in each subscale of the Brunet-Lezine Developmental Scale. The scores were the lowest in language at both measurement points. The children’s performances improved between one and two years of age, particularly in the domain of coordination. At three years of age the mean IQ test results, although still in the average range, were near the low end of it in each index. The ELBW preterms performed significantly poorer in Perceptual Reasoning Index. The developmental level at two years better predicted the IQ than that at one year. None of the measures distinguished the genders.

Keywords: preterm, extremely low birth-weight, perinatal complication, psychomotor development, intelligence, follow-up

Procedia PDF Downloads 244

Authors: Steven Ploetz, Andreas Lohmueller, Robert F. Singer

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The outstanding performance of aluminum matrix composites (AMCs) regarding stiffness/weight ratio makes AMCs attractive material for lightweight construction. Low-density boride compounds promise simultaneously an increase in stiffness and decrease in composite density. This is why boron carbide is chosen for composite manufacturing. The composites are fabricated with the stir casting process. To avoid gas entrapment during mixing and ensure nonporous composites, partial vacuum is adapted during particle feeding and stirring. Poor wettability of boron carbide with liquid aluminum hinders particle incorporation, but alloying elements such as magnesium and titanium could improve wettability and thus particle incorporation. Next to alloying elements, adapted stirring parameters and impeller geometries improve particle incorporation and enable homogenous particle distribution and high particle volume fractions of boron carbide. AMCs with up to 15 vol.% of boron carbide particles are produced via melt stirring, resulting in an increase in stiffness and strength.

Keywords: aluminum matrix composites, boron carbide, stiffness, stir casting

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Authors: Hilda Kundai Chikwanda, Lawrence Thabo Mokhadi

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The study aimed to review the factors that lead the freight railway suppliers base in South Africa (SA) to apply the Lean and Six Sigma (L&SS) methodologies. A thorough review of the factors that lead organisations, in the different industries, to implement these methodologies was done. L&SS applications were found to be prominent in the automotive industry. In particular, the railway industry in SA and the region were reviewed in terms of challenges in capturing the freight logistics market and growing market share. Qualitative methods have been used to collect primary data and descriptive statistics was used to calculate, describe, and summarize collected research data. The results show that external factors have a greater influence on the implementation of L&SS. The study drew inferences between freight railway supplier base and the application of Lean and Six Sigma (L&SS) methodologies in the SA context. It identified challenges that leads the SA freight railway to lose market share to road freight users. It further observes and recommends that L&SS methodologies are the ideal strategy required to implement a turnaround in the trajectory of freight railways as a competitive freight transport solution.

Keywords: production, methodology, manufacturing, lean, six sigma

Procedia PDF Downloads 45

Authors: Jalal Soleimannejad, Mohammad Asadizeidabadi, Mahmoud Koorki, Mojtaba Azarpira

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A significant percentage of production costs is the maintenance costs, and analysis of maintenance costs could to achieve greater productivity and competitiveness. With this is mind, the maintenance of machines and installations is considered as an essential part of organizational functions and applying effective strategies causes significant added value in manufacturing activities. Organizations are trying to achieve performance levels on a global scale with emphasis on creating competitive advantage by different methods consist of RCM (Reliability-Center-Maintenance), TPM (Total Productivity Maintenance) etc. In this study, increasing the capacity of Concentration Plant of Golgohar Iron Ore Mining & Industrial Company (GEG) was examined by using of reliability and maintainability analyses. The results of this research showed that instead of increasing the number of machines (in order to solve the bottleneck problems), the improving of reliability and maintainability would solve bottleneck problems in the best way. It should be mention that in the abovementioned study, the data set of Concentration Plant of GEG as a case study, was applied and analyzed.

Keywords: bottleneck, golgohar iron ore mining & industrial company, maintainability, maintenance costs, reliability

Procedia PDF Downloads 363

Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Junting Xiang, Jörg Uwe Schlüter, Fei Duan

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The miniaturization of gas turbines promises many advantages. Miniature gas turbines can be used for local power generation or the propulsion of small aircraft, such as UAV and MAV. However, experience shows that the miniaturization of conventional gas turbines, which are optimized at their current large size, leads to a substantial loss of efficiency and performance at smaller scales. This may be due to a number of factors, such as the Reynolds-number effect, the increased heat transfer, and manufacturing tolerances. In the present work, we focus on computational investigations of the Reynolds number effect and the wall heat transfer on the performance of axial compressor during its size change. The NASA stage 35 compressors are selected as the configuration in this study and Computational Fluid Dynamics (CFD) is used to carry out the miniaturization process and simulations. We perform parameter studies on the effect of Reynolds number and wall thermal conditions. Our results indicate a decrease of efficiency, if the compressor is miniaturized based on its original geometry due to the increase of viscous effects. The increased heat transfer through wall has only a small effect and will actually benefit compressor performance based on our study.

Keywords: axial compressor, CFD, heat transfer, miniature gas turbines, Reynolds number

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Authors: Vatsal Patel, Niraj Shah

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This paper presents the results of a laboratory study on the properties of binary blended High Performance cementitious systems containing blends of ordinary Portland cement (OPC), Porcelain Powder or Marble Powder blend proportions of 100:00, 95:05, 90:10, 85:15, 80:20 for OPC: Porcelain Powder/Marble Powder. Studies on the Engineering Properties of the cementitious concrete, namely compressive strength, flexural strength, sorptivity, rapid chloride penetration test and accelerated corrosion test have been performed and those of OPC concrete. The results show that the inclusion of Porcelain powder or Marble Powder as binary blended cement alters to a great degree the properties of the binder as well as the resulting concrete. In addition, the results show that the Porcelain powder with 85:15 proportions and Marble powder with 90:10 proportions as binary systems to produce high-performance concrete could potentially be used in the concrete construction industry particular in lowering down the volume of OPC used and lowering emission of CO2 produces during manufacturing of cement.

Keywords: accelerated corrosion, binary blended cementitious system, rapid chloride penetration, sorptivity

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Authors: Uwa C. A., Jamiru T.

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Aluminum based alloys with a certain compositional blend and manufacturing method have been reported to have excellent electrical conductors. In the current investigation, metal powders of Aluminum (Al), Copper (Cu), Niobium (Nb), and Molybdenum (Mo) were weighed in accordance with certain ratios and spread equally by combining the powder particles. The metal particles were mixed using a tube mixer for 12 hours. Before pouring into a 30mm-diameter graphite mold, pre-pressed, and placed into an SPS furnace, the thermal conductivity of the mixed metal powders was evaluated using a portable Thermtest device. Axial pressure of 50 MPa was used at a heating rate of 50 oC/min, and a multi-stage heating procedure with a holding period of 10 min. was used to sinter at temperatures between 300 oC and 480 oC. After being cooled to room temperature, the specimens were unmolded to produce the aluminum, copper, niobium, and molybdenum alloy material. The HPS 2662 Precision Four-point Probe Meter was used to determine the electrical resistivity and the values used to calculate the electrical conductivity of the sintered alloy samples. Finally, the alloy with the highest electrical conductivity and thermal conductivity qualities was the one with the following composition: Al 93.5Cu4Nb1.5Mo1. It also had a density of 3.23 g/cm3. It could be advisable for usage in automobile radiator and electric transmission line components.

Keywords: Al-Cu-Nb-Mo, electrical conductivity, alloy, sintering, thermal conductivity

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Authors: Seyedali Seyedkavoosi, Mohammad Obadat, Seantorrion Boyle

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The purpose of this study is to assess the effectiveness of a nontraditional experiential learning strategy in improving the success and interest of mechanical engineering students, using the Kinematics/Dynamics of Machine course as a case study. This upper-division technical course covers a wide range of topics, including mechanism and machine system analysis and synthesis, yet the complexities of ideas like acceleration, motion, and machine component relationships are hard to explain using standard teaching techniques. To solve this problem, a thorough design project was created that gave students hands-on experience developing, manufacturing, and testing their inventions. The main goals of the project were to improve students' grasp of machine design and kinematics, to develop problem-solving and presenting abilities, and to familiarize them with professional software. A questionnaire survey was done to evaluate the effect of this technique on students' performance and interest in mechanical engineering. The outcomes of the study shed light on the usefulness of nontraditional experiential learning approaches in engineering education.

Keywords: experiential learning, nontraditional teaching, hands-on design project, engineering education

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Authors: Cristian Pauna

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With few steps away from the 2020, investments in financial markets is a common activity nowadays. In the electronic trading environment, the automated investment software has become a major part in the business intelligence system of any modern financial company. The investment decisions are assisted and/or made automatically by computers using mathematical algorithms today. The complexity of these algorithms requires computer assistance in the investment process. This paper will present several investment strategies that can be automated with algorithmic trading for Deutscher Aktienindex DAX30. It was found that, based on several price action mathematical models used for high-frequency trading some investment strategies can be optimized and improved for automated investments with good results. This paper will present the way to automate these investment decisions. Automated signals will be built using all of these strategies. Three major types of investment strategies were found in this study. The types are separated by the target length and by the exit strategy used. The exit decisions will be also automated and the paper will present the specificity for each investment type. A comparative study will be also included in this paper in order to reveal the differences between strategies. Based on these results, the profit and the capital exposure will be compared and analyzed in order to qualify the investment methodologies presented and to compare them with any other investment system. As conclusion, some major investment strategies will be revealed and compared in order to be considered for inclusion in any automated investment system.

Keywords: Algorithmic trading, automated investment systems, limit conditions, trading principles, trading strategies

Procedia PDF Downloads 194

Authors: Sejuti Malakar

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Textile sensors have gained a lot of interest in recent years as it is instrumental in monitoring physiological and environmental changes, for a better diagnosis that can be useful in various fields like medical textiles, sports textiles, protective textiles, agro textiles, and geo-textiles. Moreover, with the development of flexible textile-based wearable sensors, the functionality of smart clothing is augmented for a more improved user experience when it comes to technical textiles. In this context, conductive textiles using new composites and nanomaterials are being developed while considering its compatibility with the textile manufacturing processes. This review aims to provide a comprehensive and detailed overview of the contemporary advancements in textile-based wearable physical sensors, used in the field of medical, security, surveillance, and protection, from a global perspective. The methodology used is through analysing various examples of integration of wearable textile-based sensors with clothing for daily use, keeping in mind the technological advances in the same. By comparing various case studies, we come across various challenges textile sensors, in terms of stability, the comfort of movement, and reliable sensing components to enable accurate measurements, in spite of progress in the engineering of the wearable. Addressing such concerns is critical for the future success of wearable sensors.

Keywords: flexible textile-based wearable sensors, contemporary advancements, conductive textiles, body conformal design

Procedia PDF Downloads 185

Authors: Kyung Min Kang, Peng Mou, Dong Xiang, Yong Yang, Gang Shen

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In this paper, planet pin parallelism error, which is one of manufacturing error of planet carrier, is employed as a main variable to influence planet load sharing factor. This error is categorize two group: (i) pin parallelism error with rotation on the axis perpendicular to the tangent of base circle of gear(x axis rotation in this paper) (ii) pin parallelism error with rotation on the tangent axis of base circle of gear(y axis rotation in this paper). For this study, the planetary gear system in 1.5MW wind turbine is applied and pure torsional rigid body model of this planetary gear is built using Solidworks and MSC.ADAMS. Based on quantified parallelism error and simulation model, dynamics simulation of planetary gear is carried out to obtain dynamic mesh load results with each type of error and load sharing factor is calculated with mesh load results. Load sharing factor formula and the suggestion for planetary reliability design is proposed with the conclusion of this study.

Keywords: planetary gears, planet load sharing, MSC. ADAMS, parallelism error

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Authors: Kolade Olawande Owoeye, George Weir

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Terrorism and extremism activities on the internet are becoming the most significant threats to national security because of their potential dangers. In response to this challenge, law enforcement and security authorities are actively implementing comprehensive measures by countering the use of the internet for terrorism. To achieve the measures, there is need for intelligence gathering via the internet. This includes real-time monitoring of potential websites that are used for recruitment and information dissemination among other operations by extremist groups. However, with billions of active webpages, real-time monitoring of all webpages become almost impossible. To narrow down the search domain, there is a need for efficient webpage classification techniques. This research proposed a new approach tagged: SentiPosit-based method. SentiPosit-based method combines features of the Posit-based method and the Sentistrenght-based method for classification of terrorism and extremism webpages. The experiment was carried out on 7500 webpages obtained through TENE-webcrawler by International Cyber Crime Research Centre (ICCRC). The webpages were manually grouped into three classes which include the ‘pro-extremist’, ‘anti-extremist’ and ‘neutral’ with 2500 webpages in each category. A supervised learning algorithm is then applied on the classified dataset in order to build the model. Results obtained was compared with existing classification method using the prediction accuracy and runtime. It was observed that our proposed hybrid approach produced a better classification accuracy compared to existing approaches within a reasonable runtime.

Keywords: sentiposit, classification, extremism, terrorism

Procedia PDF Downloads 278

Authors: E. Pretorius, A. M. Viljoen, M. van der Bank

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Introduction: The phytochemistry of Agathosma crenulata and A. betulina has been studied extensively, while their molecular analysis through DNA barcoding remains virtually unexplored. This technique can confirm the identity of plant species included in a herbal product, thereby ensuring the efficacy of the herbal product and the accuracy of its label. Materials and methods: Authentic Agathosma reference material of A. betulina (n=16) and A. crenulata (n=10) were obtained. Thirteen commercial products were purchased from various health shops around Johannesburg, South Africa, using the search term “Agathosma” or “Buchu.” The plastid regions matK and ycf1 were used to barcode the Buchu products, and BRONX analysis confirmed the taxonomic identity of the samples. UPLC-MS analyses were also performed. Results: Only (30/60) 60% of the traded samples tested from 13 suppliers contained A. betulina in their herbal products. Similar results were also obtained for the UPLC-MS analysis. Conclusion: In this study, we demonstrate the application of DNA barcoding in combination with phytochemical analysis to authenticate herbal products claiming to contain Agathosma plants as an ingredient in their products. This supports manufacturing efforts to ensure that herbal products that are safe for the consumer.

Keywords: Buchu, substitution, barcoding, BRONX algorithm, matK, ycf1, UPLC-MS

Procedia PDF Downloads 129

Authors: Rinku Varghese, S. Chandrakaran, K. Rangaswamy

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The standard one-dimensional consolidation test is used to find the consolidation behaviour of artificially consolidated organic soils. Incremental loading tests were conducted on the clay without and with organic matter. The study was conducted with soil having different organic content keeping all other parameters constant. The tests were conducted on clay and artificially prepared organic soil sample at different vertical pressure. The load increment ratio considered for the test is equal to one. Artificial organic soils are used for the test by adding starch to the clay. The percentage of organic content in starch is determined by adding 5% by weight starch into the clay (inorganic soil) sample and corresponding change in organic content of soil was determined. This was expressed as percentage by weight of starch, and it was found that about 95% organic content in the soil sample. Accordingly percentage of organic content fixed and added to the sample for testing to understand the consolidation behaviour clayey soils with organic content. A detailed study of the results obtained from IL test was investigated. The main items investigated were (i) coefficient of consolidation (cv), (ii) coefficient of volume compression (mv), (iii) coefficient of permeability (k). The consolidation parameter obtained from IL test was used for determining the creep strain and creep parameter and also predicting their variation with vertical stress and organic content.

Keywords: consolidation, secondary compression, creep, starch

Procedia PDF Downloads 281

Authors: Woo Young Jung, Sung Min Park, Ho Young Son, Viriyavudh Sim

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This study presents a way to reduce earthquake damage and emergency rehabilitation of critical structures such as schools, high-tech factories, and hospitals due to strong ground motions associated with climate changes. Regarding recent trend, a strong earthquake causes serious damage to critical structures and then the critical structure might be influenced by sequence aftershocks (or tsunami) due to fault plane adjustments. Therefore, in order to improve seismic performance of critical structures, retrofitted or strengthening study of the structures under aftershocks sequence after emergency rehabilitation of the structures subjected to strong earthquakes is widely carried out. Consequently, this study used composite material for emergency rehabilitation of the structure rather than concrete and steel materials because of high strength and stiffness, lightweight, rapid manufacturing, and dynamic performance. Also, this study was to develop or improve the seismic performance or seismic retrofit of critical structures subjected to strong ground motions and earthquake aftershocks, by utilizing GFRP-Corrugated Infill Panels (GCIP).

Keywords: aftershock, composite material, GFRP, infill panel

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Authors: Subodh Kumar, Ramkisan Pawar, Gopal D. Belurkar

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This paper describes a study for simple blanking tool. In blanking or piercing operation, punch and die should be concentric for proper cutting. In this study, tolerance analysis method is used to analyze the variation in the press tool assembly. Variation results into the eccentricity in between die and punch due to cumulative tolerance of parts used in assembly. 1D variation analysis were performed by CREO parametric computer aided design (CAD) Software Powered by CETOL 6σ computer aided tolerance analysis software. Use of CAD analysis software given the opportunity to find out the cause of variation in tool assembly. Accordingly, the new specification of tolerance and process setting for die set manufacturing has determined. Tolerance allocation and tolerance analysis method were performed iteratively to conclude that position tolerance as well as size tolerance of hole in top plate for bush and size tolerance of guide pillar were more responsible for eccentricity in punch and die. This work proposes optimum tolerance for press tool assembly parts to achieve 100 % yield for specified .015mm minimum tolerance zone.

Keywords: blanking, GD&T (Geometric Dimension and Tolerancing), DPMU (defects per million unit), press tool, stackup analysis, tolerance allocation, yield percentage

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Authors: Juliza Hidayati, Yesie M. Sinuhaji, Sawarni Hasibuan

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A company producing drinking water through many incompatibility issues that affect supply chain performance. The study was conducted to determine the factors that affect the performance of the supply chain and improve it. To obtain the dominant factors affecting the performance of the supply chain used Analytic Network Process, while to improve performance is done by using Kaizen. Factors affecting the performance of the supply chain to be a reference to identify the cause of the non-conformance. Results weighting using ANP indicates that the dominant factor affecting the level of performance is the precision of the number of shipments (15%), the ability of the fulfillment of the booking amount (12%), and the number of rejected products when signing (12%). Incompatibility of the factors that affect the performance of the supply chain are identified, so that found the root cause of the problem is most dominant. Based on the weight of Risk Priority Number (RPN) gained the most dominant root cause of the problem, namely the poorly maintained engine, the engine worked for three shifts, machine parts that are not contained in the plant. Improvements then performed using the Kaizen method of systematic and sustainable.

Keywords: analytic network process, booking amount, risk priority number, supply chain performance

Procedia PDF Downloads 294

Authors: Anis A. Ansari, M. Kamil

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The development of 3D printing technology has allowed the manufacturing industry to create parts with a high degree of automation, increased design freedom, and improved mechanical performance. Fused deposition modelling (FDM) is a 3D printing technique in which successive layers of thermoplastic polymer are deposited and controlled to create a three-dimensional product. In this study, process parameters such as nozzle temperature and printing speed were chosen to investigate their effects on hardness properties. 3D printed specimens were fabricated by an FDM 3D printer from Polylactic acid (PLA) polymer. After analysis, it was observed that the hardness property is much influenced by print speed and nozzle temperature parameters. Maximum hardness was achieved at higher print speed which indicates that the Shore D hardness is directly proportional to the print speed. Moreover, at higher print speed, it has no significant dependence on the nozzle temperature. Hardness is also influenced by nozzle temperature, though to a lesser extent. The hardness slightly lowers when the nozzle temperature is raised from 190 to 210 oC, but due to improved bonding between each raster, a further rise in temperature increases the hardness property.

Keywords: 3D printing, fused deposition modeling (FDM), polylactic acid (PLA), print speed, nozzle temperature, hardness property

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Authors: Chiang-Ho Cheng, An-Shik Yang, Hon-Yi Cheng, Ming-Yu Lai

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This paper presents the design and fabrication of a novel piezoelectric actuator for a gas micropump with check valve having the advantages of miniature size, light weight and low power consumption. The micropump is designed to have eight major components, namely a stainless steel upper cover layer, a piezoelectric actuator, a stainless steel diaphragm, a PDMS chamber layer, two stainless steel channel layers with two valve seats, a PDMS check valve layer with two cantilever-type check valves and an acrylic substrate. A prototype of the gas micropump, with a size of 52 mm × 50 mm × 5.0 mm, is fabricated by precise manufacturing. This device is designed to pump gases with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micropump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micropump and the displacement of the piezoelectric actuator, simultaneously. The gas micropump obtained higher output performance under the sinusoidal waveform of 250 Vpp. The micropump achieved the maximum pumping rates of 1185 ml/min and back pressure of 7.14 kPa at the corresponding frequency of 120 and 50 Hz.

Keywords: PDMS, check valve, micropump, piezoelectric

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Authors: J. L. Bhagoria, Ajeet Kumar Giri

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A computational investigation of various flow characteristics with artificial roughness in the form of V-types discrete ribs, heated wall of rectangular duct for turbulent flow with Reynolds number range (3800-15000) and p/e (5 to 12) has been carried out with k-e turbulence model is selected by comparing the predictions of different turbulence models with experimental results available in literature. The current study evaluates thermal performance behavior, heat transfer and fluid flow behavior in a v shaped duct with discrete roughened ribs mounted on one of the principal wall (solar plate) by computational fluid dynamics software (Fluent 6.3.26 Solver). In this study, CFD has been carried out through designing 3-demensional model of experimental solar air heater model analysis has been used to perform a numerical simulation to enhance turbulent heat transfer and Reynolds-Averaged Navier–Stokes analysis is used as a numerical technique and the k-epsilon model with near-wall treatment as a turbulent model. The thermal efficiency enhancement because of selected roughness is found to be 16-24%. The result predicts a significant enhancement of heat transfer as compared to that of for a smooth surface with different P’ and various range of Reynolds number.

Keywords: CFD, solar collector, airheater, thermal efficiency

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Authors: Hong-Yi Kuo

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Leadership is a key factor of improving workplace safety, and there have been abundant of studies which support the positive effects of appropriate leadership on employee safety performance in the western academic. However, little safety research focus on the Chinese leadership style like paternalistic leadership. To fill this gap, the resent study aims to examine the relationship between authoritarian leadership (one of the ternary mode in paternalistic leadership) and safety outcomes. This study makes hypothesis on different levels. First, on the group level, as an authoritarian leader regards safety value as the most important tasks, there would be positive effect on group safety outcomes through strengthening safety group norms by the emphasis on etiquette. Second, on the cross level, when a leader with authoritarian style has high priority on safety, employees may more obey the safety rules because of fear due to emphasis on absolute authority over the leader. Therefore, employees may show more safety performance and then increase individual safety outcomes. Survey data would be collected from 50 manufacturing groups (each group with more than 5 members and a leader) and a hierarchical linear modeling analysis would be conducted to analyze the hypothesis. Above the predictive result, the study expects to be a cornerstone of safety leadership research in the Chinese academic and practice.

Keywords: safety leadership, authoritarian leadership, group norms, safety behavior, supervisor safety priority

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: Cristian Păuna

Abstract:

After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

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Authors: Expedito Pinto De Paula Junior

Abstract:

Current systems such as artificial satellites, airplanes, automobiles, turbines, power systems and air traffic controls are becoming increasingly more complex and/or highly integrated as defined in SAE-ARP-4754A (Society Automotive Engineering - Certification considerations for highly-integrated or complex aircraft systems standard). Among other processes, the development of such systems requires careful Change and Configuration Management (CCM) to establish and maintain product integrity. Understand the maturity of CCM process based in historical approach is crucial for better implementation in hardware and software lifecycle. The sense of work organization, in all fields of development is directly related to the order and interrelation of the parties, changes in time, and record of these changes. Generally, is observed that engineers, administrators and managers invest more time in technical activities than in organization of work. More these professionals are focused in solving complex problems with a purely technical bias. CCM process is fundamental for development, production and operation of new products specially in the safety critical systems. The objective of this paper is open a discussion about the historical revision based in standards focus of CCM around the world in order to understand and reflect the importance across the years, the contribution of this process for technology evolution, to understand the mature of organizations in the system lifecycle project and the benefits of CCM to avoid errors and mistakes during the Lifecycle Product.

Keywords: changes, configuration management, historical, revision

Procedia PDF Downloads 201

Authors: Pham Duc Hieu, Do Thi Huong Lan

Abstract:

The aim of this paper is to investigate the factors affecting the extent of voluntary disclosure by examining the annual reports of 205 industrial and manufacturing companies listing on Ho Chi Minh Stock Exchange (HSX) and Hanoi Stock Exchange (HNX) for the year end of 2012. Those factors include company size, profitability, leverage, state ownership, managerial ownership, and foreign ownership, board independence, role duality and type of external auditors. Evidence from this study suggests two main findings. (1) Companies with high foreign ownership have a high level of voluntary disclosure. (2) The company size is an important factor related to the increased level of voluntary disclosure in annual reports made by Vietnamese listed companies. The larger the company, the higher the information is disclosed. However, no significant associations are found between profitability, leverage, state ownership, managerial ownership, board independence, role duality and type of external auditors as hypothesized in this study.

Keywords: voluntary disclosure, Vietnamese listed companies, voluntary, duality

Procedia PDF Downloads 410

Authors: Rehan Ullah

Abstract:

This paper explores the hypothesis that technology can be used to improve product quality, speed up delivery and reduced cost. For companies improving the quality of their products, reducing the cost and improving the speed of delivery makes them favorable to the client who feels like all their needs have been met. The research occurs between the months of January 2018 to April 2018 which is about four months. The research experiment design uses the pretest-posttest experimental design set up between two companies both using the traditional method of manufacturing with no technology. In one company technology is introduced while in the other company the process remains the same traditional method of production. Both companies analyze the results at the end of a four-month period before a conclusion is drawn from both the pretest and the final test. The experiment results show that technology improves quality of the product, improves the speed of delivery while at the same time reduce cost benefiting both the producer and the client. Technology should, therefore, be implemented in companies to give them an edge over the competition. With technology in companies, the United States can reclaim production from overseas companies that have taken over by providing cheap labor. Better satisfied customers mean more production which in turn means more jobs for the people in the United States.

Keywords: technology, quality of product, speed up delivery, cost

Procedia PDF Downloads 157