Search results for: auto part manufacturing factory (AMF)

Authors: Nino Grigolaia

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Introduction. The paper discusses the role of the manufacturing industry in the Georgian economy, analyzes the current trends in the development of the manufacturing industry, reveals its impact on the Georgian economy, and justifies the essential importance of industrial transformation for the future development of the Georgian economy. Objectives. The main objective of research is to study development trends of the manufacturing industry of Georgia and estimate the industrial policy in Georgia. Methodology. The paper uses methods of induction, deduction, analysis, synthesis, analogy, correlation, and statistical observation. A qualitative study was conducted based on a survey of industry experts and entrepreneurs in order to identify the factors hindering and contributing to the manufacturing industry. Conclusions. The research reveals that the development of the manufacturing industry and the formation of industrial policy are of special importance for the further growth and development of the Georgian economy. Based on the research, the factors promoting and hindering the development of the manufacturing industry are identified. The need to increase foreign direct investment in the industrial sector are highlighted. Recommendations for the development of the country's manufacturing industry are developed, taking into account the competitive advantages and international experience of Georgia.

Keywords: manufacturing, industrial policy, contributing factor, hindering factor

Procedia PDF Downloads 117

Authors: Li-hsing Shih, Wei-Jen Hsu

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Recently, the sale of electrical vehicles (EVs) has increased dramatically due to maturing technology development and decreasing cost. Governments of many countries have made regulations and policies in favor of EVs due to their long-term commitment to net zero carbon emissions. However, due to uncertain factors such as the future price of EVs, forecasting the future market share of EVs is a challenging subject for both the auto industry and local government. This study tries to forecast the market share of EVs using conjoint models and Monte Carlo simulation. The research is conducted in three phases. (1) A conjoint model is established to represent the customer preference structure on purchasing vehicles while five product attributes of both EV and internal combustion engine vehicles (ICEV) are selected. A questionnaire survey is conducted to collect responses from Taiwanese consumers and estimate the part-worth utility functions of all respondents. The resulting part-worth utility functions can be used to estimate the market share, assuming each respondent will purchase the product with the highest total utility. For example, attribute values of an ICEV and a competing EV are given respectively, two total utilities of the two vehicles of a respondent are calculated and then knowing his/her choice. Once the choices of all respondents are known, an estimate of market share can be obtained. (2) Among the attributes, future price is the key attribute that dominates consumers’ choice. This study adopts the assumption of a learning curve to predict the future price of EVs. Based on the learning curve method and past price data of EVs, a regression model is established and the probability distribution function of the price of EVs in 2030 is obtained. (3) Since the future price is a random variable from the results of phase 2, a Monte Carlo simulation is then conducted to simulate the choices of all respondents by using their part-worth utility functions. For instance, using one thousand generated future prices of an EV together with other forecasted attribute values of the EV and an ICEV, one thousand market shares can be obtained with a Monte Carlo simulation. The resulting probability distribution of the market share of EVs provides more information than a fixed number forecast, reflecting the uncertain nature of the future development of EVs. The research results can help the auto industry and local government make more appropriate decisions and future action plans.

Keywords: conjoint model, electrical vehicle, learning curve, Monte Carlo simulation

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Authors: Yousef I. Salamin

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Theoretical investigations, analytical as well as numerical, have shown that electrons can be accelerated to GeV energies by the process of cyclotron auto-resonance acceleration (CARA). In CARA, the particle would be injected along the lines of a uniform magnetic field aligned parallel to the direction of propagation of a plane-wave radiation field. Unfortunately, an accelerator based on CARA would be prohibitively too long and too expensive to build and maintain. However, the process stands a better chance of success near the polar cap of a compact object (such as a neutron star, a black hole or a magnetar) or in an environment created in the wake of a binary neutron-star or blackhole merger. Dynamics of the nuclides ₁H¹, ₂He⁴, ₂₆Fe⁵⁶, and ₂₈Ni⁶², in such astrophysical conditions, have been investigated by single-particle calculations and many-particle simulations. The investigations show that these nuclides can reach ZeV energies (1 ZeV = 10²¹ eV) due to interaction with super-intense radiation of wavelengths = 1 and 10 m and = 50 pm and magnetic fields of strengths at the mega- and giga-tesla levels. Examples employing radiation intensities in the range 10³²-10⁴² W/m² have been used. Employing a two-parameter model for representing the radiation field, CARA is analytically generalized to include any state of polarization, and the basic working equations are derived rigorously and in closed analytic form.

Keywords: compact objects, cosmic-ray acceleration, cyclotron auto-resonance, polarization effects, zevatron

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Authors: J. Otegui, M. Agirre, M. A. Cestau, H. Erauskin

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The increasing accessibility of mid-priced additive manufacturing (AM) systems offers a chance to incorporate this technology into engineering instruction. Furthermore, AM facilitates the creation of manufacturing designs, enhancing the efficiency of various machines. One example of these machines is the Stirling cycle engine. It encompasses complex thermodynamic machinery, revealing various aspects of mechanical engineering expertise upon closer inspection. In this publication, the application of Stirling Engines fabricated via additive manufacturing techniques will be showcased for the purpose of instructive design and product enhancement. The performance of a Stirling engine's conventional displacer and piston is contrasted. The outcomes of utilizing this instructional tool in teaching are demonstrated.

Keywords: 3D printing, additive manufacturing, mechanical design, stirling engine.

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Authors: Dharmendra Jariwala, Robin Christian

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Thermal exposure is a common problem in every manufacturing industry where heat is used in the manufacturing process. In developing countries like India, a lack of awareness regarding the proper work environmental condition is observed among workers. Improper planning of factory building, arrangement of machineries, ventilation system, etc. play a vital role in the rise of temperature within the manufacturing areas. Due to the uncontrolled thermal stress, workers may be subjected to various heat illnesses from mild disorder to heat stroke. Heat stress is responsible for the health risk and reduction in production. Wet Bulb Globe Temperature (WBGT) index and relative humidity are used to evaluate heat stress conditions. WBGT index is a weighted average of natural wet bulb temperature, globe temperature, dry bulb temperature, which are measured with standard instrument QuestTemp 36 area stress monitor. In this study textile processing units have been selected in the industrial estate in the Surat city. Based on the manufacturing process six locations were identified within the plant at which process was undertaken at 120°C to 180°C. These locations were jet dying machine area, stenter machine area, printing machine, looping machine area, washing area which generate process heat. Office area was also selected for comparision purpose as a sixth location. Present Study was conducted in the winter season and summer season for day and night shift. The results shows that average WBGT index was found above Threshold Limiting Value (TLV) during summer season for day and night shift in all three industries except office area. During summer season highest WBGT index of 32.8°C was found during day shift and 31.5°C was found during night shift at printing machine area. Also during winter season highest WBGT index of 30°C and 29.5°C was found at printing machine area during day shift and night shift respectively.

Keywords: relative humidity, textile industry, thermal stress, WBGT

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Authors: Pranav Mohan Parki, C. Mallika Parveen, Tahseen Ahmad Khan, Mihika Shivkumar

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Additive manufacturing (AM) is one of the several manufacturing processes in use today. AM comprises of techniques such as ‘Selective Laser Sintering’ and ‘Selective Laser Melting’ etc. along with other equipment and materials has been developed way back in 1980s, although major use of these methods has risen during the last decade. AM seems to be the most efficient way when compared to the traditional machining procedures. Still many problems continue to hinder its progress to becoming the most widely used of all. This paper contributes to the better understanding of AM and also aims at providing viable solutions to these problems, which may further help in enabling AM to become the most flaw free production method.

Keywords: additive manufacturing (AM), 3D printing, prototype, laser sintering

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Authors: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Yuan-Jye Tseng, Shin-Han Lin

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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Keywords: supply chain management, green supply chain, green design, green manufacturing, mathematical model

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Authors: Wadea Ameen, Abdulrahman Al-Ahmari, Osama Abdulhameed

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Electron beam melting (EBM) is one of the modern additive manufacturing (AM) technologies. In EBM, the electron beam melts metal powder into a fully solid part layer by layer. Since EBM is a new technology, most designers are unaware of the capabilities and the limitations of EBM technology. Also, many engineers are facing many challenges to utilize the technology because of a lack of design rules for the technology. The aim of this study is to identify the capabilities and the limitations of EBM technology in fabrication of small features and overhang structures and develop a design rules that need to be considered by designers and engineers. In order to achieve this objective, a series of experiments are conducted. Several features having varying sizes were designed, fabricated, and evaluated to determine their manufacturability limits. In general, the results showed the capabilities and limitations of the EBM technology in fabrication of the small size features and the overhang structures. In the end, the results of these investigation experiments are used to develop design rules. Also, the results showed the importance of developing design rules for AM technologies in increasing the utilization of these technologies.

Keywords: additive manufacturing, design for additive manufacturing, electron beam melting, self-supporting overhang

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Authors: Ali Alhajeri, Tarig Makki, Mosa Almutahhar, Mohammed Ahmed, Usman Ali

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Metal powder is the raw material used for laser powder-bed fusion (LPBF) additive manufacturing (AM). There are many metal materials that can be used in LPBF. The properties of these materials are varied between each other, which can affect the building part. The objective of this paper is to do an overview of the titanium powders available in LBPF. Comparison between different literature works will lead us to study the similarities and differences between the powder properties such as size, shape, and chemical composition. Furthermore, the results of this paper will point out the significant titanium powder properties in order to clearly illustrate their effect on the build parts.

Keywords: LPBF, titanium, Ti-6Al-4V, Ti-5553, metal powder, AM

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Authors: Mlondi Ndovela

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Globally, the manufacturing employment has been declining and the South African manufacturing sector experiences the very same trend. Despite the commonality between the global and South African manufacturing trend, there is an understanding that local areas provide distinct contributions to the provincial/national economy. Therefore, the growth/decline of a particular manufacturing division in one local area may not be evident in another area since economic performances vary from region to region. In view of the above, the study employed the Esteban-Marquillas model of shift-share analysis (SSA) to conduct an empirical analysis of manufacturing employment performance at uMhlathuze Local Municipality in the KwaZulu-Natal province. The study set out two objectives; those are, to quantify uMhlathuze manufacturing jobs that are attributed to the provincial manufacturing employment trends and identify manufacturing divisions are growing/declining in terms of employment. To achieve these objectives, the study sampled manufacturing employment data from 2010 to 2017 and this data was categorised into ten manufacturing divisions. Furthermore, the Esteban-Marquillas model calculated manufacturing employment in terms of two effects, namely; provincial growth effect (PGE) and industrial mix effect (IME). The results show that even though uMhlathuze manufacturing sector has a positive PGE (+230), the municipality performed poorly in terms of IME (-291). A further analysis included other economic sectors of the municipality to draw employment performance comparison and the study found that agriculture; construction; trade, catering and accommodation; and transport, storage and communication, performed well above manufacturing sector in terms of PGE (+826) and IME (+532). This suggests that uMhlathuze manufacturing sector is not necessarily declining; however, other economic sectors are growing faster and bigger than it is, therefore, reducing the employment share of the manufacturing sector. To promote manufacturing growth from a policy standpoint, the government could create favourable macroeconomic policies such as import substitution policies and support labour-intensive manufacturing divisions. As a result, these macroeconomic policies can help to protect local manufacturing firms and stimulate the growth of manufacturing employment.

Keywords: allocation effect, Esteban-Marquillas model, manufacturing employment, regional competitive effect, shift-share analysis

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Authors: Chee Fai Tan, L. S. Wahidin, S. N. Khalil

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Nowadays, manufacturing cost is one of the important factors that will affect the product cost as well as company profit. There are many methods that have been used to reduce the manufacturing cost in order for a company to stay competitive. One of the factors that effect manufacturing cost is the time. Expert system can be used as a method to reduce the manufacturing time. The purpose of the expert system is to diagnose and solve the problem of design of assembly. The paper describes an architecture framework for design of assembly expert system that focuses on commercial vehicle seat manufacturing industry.

Keywords: design of assembly, expert system, vehicle seat, mechanical engineering

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Authors: Katsumi Hirata

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To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position

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Authors: Freddy Patricio Moncayo-Matute, Pablo Gerardo Peña-Tapia, Vázquez-Silva Efrén, Paúl Bolívar Torres-Jara, Diana Patricia Moya-Loaiza, Gabriela Abad-Farfán

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This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure.

Keywords: surgical planning, additive manufacturing, rapid prototyping, fused deposition modeling, custom anatomical model

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Authors: Thomas S. Abia II, Citlali Garcia-Saucedo

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A continuous copper precipitation treatment (CCPT) system was conceived at Intel Chandler Site to serve as a first-of-kind (FOK) facility-scale waste copper (Cu), nickel (Ni), and manganese (Mn) co-precipitation facility. The process was designed to treat highly variable wastewater discharged from a substrate packaging research factory. The paper discusses metals co-precipitation induced by internal changes for manufacturing facilities that lack the capacity for hardware expansion due to real estate restrictions, aggressive schedules, or budgetary constraints. Herein, operating parameters such as pH and oxidation reduction potential (ORP) were examined to analyze the ability of the CCPT System to immobilize various waste metals. Additionally, influential factors such as influent concentrations and retention times were investigated to quantify the environmental variability against system performance. A total of 2,027 samples were analyzed and statistically evaluated to measure the performance of CCPT that was internally retrofitted for Mn abatement to meet environmental regulations. In order to enhance the consistency of the influent, a separate holding tank was cannibalized from another system to collect and slow-feed the segregated Mn wastewater from the factory into CCPT. As a result, the baseline influent Mn decreased from 17.2+18.7 mg¹L^-1 at pre-pilot to 5.15+8.11 mg¹L^-1 post-pilot (70.1% reduction). Likewise, the pre-trial and post-trial average influent Cu values to CCPT were 52.0+54.6 mg¹L^-1 and 33.9+12.7 mg¹L^-1, respectively (34.8% reduction). However, the raw Ni content of 0.97+0.39 mg¹L^-1 at pre-pilot increased to 1.06+0.17 mg¹L^-1 at post-pilot. The average Mn output declined from 10.9+11.7 mg¹L^-1 at pre-pilot to 0.44+1.33 mg¹L^-1 at post-pilot (96.0% reduction) as a result of the pH and ORP operating setpoint changes. In similar fashion, the output Cu quality improved from 1.60+5.38 mg¹L^-1 to 0.55+1.02 mg¹L^-1 (65.6% reduction) while the Ni output sustained a 50% enhancement during the pilot study (0.22+0.19 mg¹L^-1 reduced to 0.11+0.06 mg¹L^-1). pH and ORP were shown to be significantly instrumental to the precipitative versatility of the CCPT System.

Keywords: copper, co-precipitation, industrial wastewater treatment, manganese, optimization, pilot study

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Authors: Efrain Rodriguez, Sergio Pertuz, Cristhian Riano

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Tool-path generation is an essential step in the FFF (Fused Filament Fabrication)-based Additive Manufacturing (AM) process planning. In the manufacture of a mechanical part by using additive processes, high resource consumption and prolonged production times are inherent drawbacks of these processes mainly due to non-optimized tool-path generation. In this work, we propose a heuristic-search intelligent algorithm-based approach for optimized tool-path generation for FFF-based AM. The main benefit of this approach is a significant reduction of travels without material deposition when the AM machine performs moves without any extrusion. The optimization method used reduces the number of travels without extrusion in comparison with commercial software as Slic3r or Cura Engine, which means a reduction of production time.

Keywords: additive manufacturing, tool-path optimization, fused filament fabrication, process planning

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

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Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

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Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

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Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability

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Authors: Ehsan Vaziri Goodarzi, Mahmood Houshmand, Omid Fatahi Valilai, Vahidreza Ghezavati, Shahrooz Bamdad

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One important paradigm of industry 4.0 is Cloud Manufacturing (CM). In CM everything is considered as a service, therefore, the CM platform should consider all service provider's capabilities and tries to integrate services in an equilibrium state. This research develops a framework for implementing manufacturing cloud service composition in the equilibrium state. The developed framework using well-known tools called axiomatic design (AD) and game theory. The research has investigated the factors for forming equilibrium for measures of the manufacturing cloud service composition. Functional requirements (FRs) represent the measures of manufacturing cloud service composition in the equilibrium state. These FRs satisfied by related Design Parameters (DPs). The FRs and DPs are defined by considering the game theory, QoS, consumer needs, parallel and cooperative services. Ultimately, four FRs and DPs represent the framework. To insure the validity of the framework, the authors have used the first AD’s independent axiom.

Keywords: axiomatic design, manufacturing cloud service composition, cloud manufacturing, industry 4.0

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Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, M. Hajdúchová, V. Enev, J. Wasserbauer

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In this present work, CoFe2-xNdxO4 (0.0 ≤ x ≥0.1) spinel ferrite nanoparticles were synthesized by starch-assisted sol-gel auto-combustion method. Powder X-ray diffraction patterns were revealed the formation of cubic spinel ferrite with the signature of NdFeO3 phase at higher Nd3+ concentration. The field emission scanning electron microscopy study demonstrated the spherical nanoparticle in the size range between 5-15 nm. Raman and Fourier Transform Infrared spectra supported the formation of the spinel ferrite structure in the nanocrystalline form. The X-ray photoelectron spectroscopy (XPS) analysis confirmed the presence of Co2+ and Fe3+ at octahedral as well as a tetrahedral site in CoFe2-xNdxO4 nanoparticles. The change in magnetic properties with a variation of concentration of Nd3+ ions in cobalt ferrite nanoparticles was observed.

Keywords: nanoparticles, spinel ferrites, sol-gel auto-combustion method, CoFe2-xNdxO4

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Authors: Eun Kyong Park

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This study explores the relationships between immigrant parents’ beliefs about bilingualism, family literacy practices, and their children’s identity development in Sydney, Australia. This project examines how these parents’ ideological beliefs and knowledge are related to their provision of family literacy practices and management of the environment for their bilingual children based on family language policy (FLP). This is a follow-up study of the author’s prior thesis that presented Korean immigrant mothers’ beliefs and decision-making in support of their children’s bilingualism. It includes fathers’ perspectives within the participating families as a whole by foregrounding their perceptions of bilingual and identity development. It adopts a qualitative approach with twelve immigrant mothers and fathers living in a Korean-Australian community whose child attends one of the communities Korean language programs. This time, it includes introspective and self-evocative auto-ethnographic data. The initial data set collected from the first part of this study demonstrated the mothers provided rich, diverse, and specific family literacy activities for their children. These mothers selected specific practices to facilitate their child’s bilingual development at home. The second part of data has been collected over a three month period: 1) a focus group interview with mothers; 2) a brief self-report of fathers; 3) the researcher’s reflective diary. To analyze these multiple data, thematic analysis and coding were used to reveal the parents’ ideologies surrounding bilingualism and bilingual identities. It will highlight the complexity of language and literacy practices in the family domain interrelated with sociocultural factors. This project makes an original contribution to the field of bilingualism and FLP and a methodological contribution by introducing auto-ethnographic input of this community’s lived practices. This project will empower Korean-Australian immigrant families and other multilingual communities to reflect their beliefs and practices for their emerging bilingual children. It will also enable educators and policymakers to access authentic information about how bilingualism is practiced within these immigrant families in multiple ways and to help build the culturally appropriate partnership between home and school community.

Keywords: bilingualism, beliefs, identity, family language policy, Korean immigrant parents in Australia

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Authors: Tyler Palma, Praveen Damasus, Michael Munther, Mehrdad Mohsenizadeh, Keivan Davami

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The advancement of additive manufacturing, in both research and commercial realms, is highly dependent upon continuing innovations and creativity in materials and designs. Additive manufacturing shows great promise towards revolutionizing various industries, due largely to the fact that design data can be used to create complex products and components, on demand and from the raw materials, for the end user at the point of use. However, it will be critical that the material properties of additively-made parts for engineering purposes be fully understood. As it is a relatively new additive manufacturing method, the response of properties of Multi Jet Fusion (MJF) produced parts to different printing parameters has not been well studied. In this work, testing of mechanical and tribological properties MJF-printed Polyamide 12 parts was performed to determine whether printing orientation in this method results in significantly different part performances. Material properties were studied at macro- and nanoscales. Tensile tests, in combination with tribology tests including steady-state wear, were performed. Results showed a significant difference in resultant part characteristics based on whether they were printed in a vertical or horizontal orientation. Tensile performance of vertically and horizontally printed samples varied, both in ultimate strength and strain. Tribology tests showed that printing orientation has notable effects on the resulting mechanical and wear properties of tested surfaces, due largely to layer orientation and the presence of unfused fused powder grain inclusions. This research advances the understanding of how print orientation affects the mechanical properties of additively manufactured structures, and also how print orientation can be exploited in future engineering design.

Keywords: additive manufacturing, indentation, nano mechanical characterization, print orientation

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Authors: Liubov Magerramova, Mikhail Petrov, Vladimir Isakov, Liana Shcherbinina, Suren Gukasyan, Daniil Povalyukhin, Olga Klimova-Korsmik, Darya Volosevich

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Aircraft engines are developing along the path of increasing resource, strength, reliability, and safety. The building of gas turbine engine body parts is a complex design and technological task. Particularly complex in the design and manufacturing are the casings of the input stages of helicopter gearboxes and central drives of aircraft engines. Traditional technologies, such as precision casting or isothermal forging, are characterized by significant limitations in parts production. For parts like housing, additive technologies guarantee spatial freedom and limitless or flexible design. This article presents the results of computational and experimental studies. These investigations justify the applicability of additive technologies (AT) to reduce the weight of aircraft housing gearbox parts by up to 32%. This is possible due to geometrical optimization compared to the classical, less flexible manufacturing methods and as-casted aircraft parts with over-insured values of safety factors. Using an example of the body of the input stage of an aircraft gearbox, visualization of the layer-by-layer manufacturing of a part based on thermal deformation was demonstrated.

Keywords: additive technologies, gas turbine engines, topological optimization, synthesis process

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Authors: Saumyaranjan Sahoo, Sudhir Yadav

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Indian manufacturing firms operating in rapidly changing and highly competitive market, over the last few decades, have embraced organization-wide transformation to achieve cultural and operational excellence. In recent years, numerous approaches have been proposed to improve business and manufacturing performance. Lean practices in particular, Total Productive Management (TPM) and Total Quality Management (TQM) have received considerable attention, as they being adopted and adapted for raising the performance standard of Indian manufacturing firms to world class levels. The complementary nature of TPM and TQM is being practiced in many companies to achieve synergy. Specifically, this research investigates whether joint TPM-TQM implementation contribute to higher business performance when compared to individual implementation. Data from 160 manufacturing firms were analyzed that demonstrate synergetic implementation of both TPM-TQM practices over a reasonable period of time, contributed in delivering better business performance as compared to individual implementation strategy.

Keywords: total productive management, total quality management, Indian manufacturing firms, business performance

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Authors: Aslı Günay Bulutsuz, Mehmet Emin Yurci

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Severe plastic deformation techniques are top-down deformation methods which enable superior mechanical properties by decreasing grain size. Different kind severe plastic deformation methods have been widely being used at various process temperature and geometries. Besides manufacturing advantages of severe plastic deformation technique, most of the types are being used only at the laboratory level. They cannot be adapted to industrial usage due to their continuous manufacturability and manufacturing costs. In order to enhance these manufacturing difficulties and enable widespread usage, different kinds of methods have been developed. In this review, a comprehensive literature research was fulfilled in order to highlight continuous severe plastic deformation methods.

Keywords: continuous manufacturing, severe plastic deformation, ultrafine grains, grain size refinement

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Authors: Gopinath Rathod, Vinod Puranik

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Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: Óscar Muñoz Garrigós, José Manuel Bernabeu Aubán

Abstract:

Time-sensitive services are the base of the cloud services industry. Keeping low service saturation is essential for controlling response time. All auto-scalable services make use of reactive auto-scaling. However, reactive auto-scaling has few in-depth studies. This presentation shows a model for reactive auto-scaling methodologies with a MAPE-k architecture. Queuing theory can compute different properties of static services but lacks some parameters related to the transition between models. Our model uses queuing theory parameters to relate the transition between models. It associates MAPE-k related times, the sampling frequency, the cooldown period, the number of requests that an instance can handle per unit of time, the number of incoming requests at a time instant, and a function that describes the acceleration in the service's ability to handle more requests. This model is later used as a solution to horizontally auto-scale time-sensitive services composed of microservices, reevaluating the model’s parameters periodically to allocate resources. The solution requires limiting the acceleration of the growth in the number of incoming requests to keep a constrained response time. Business benefits determine such limits. The solution can add a dynamic number of instances and remains valid under different system sizes. The study includes performance recommendations to improve results according to the incoming load shape and business benefits. The exposed methodology is tested in a simulation. The simulator contains a load generator and a service composed of two microservices, where the frontend microservice depends on a backend microservice with a 1:1 request relation ratio. A common request takes 2.3 seconds to be computed by the service and is discarded if it takes more than 7 seconds. Both microservices contain a load balancer that assigns requests to the less loaded instance and preemptively discards requests if they are not finished in time to prevent resource saturation. When load decreases, instances with lower load are kept in the backlog where no more requests are assigned. If the load grows and an instance in the backlog is required, it returns to the running state, but if it finishes the computation of all requests and is no longer required, it is permanently deallocated. A few load patterns are required to represent the worst-case scenario for reactive systems: the following scenarios test response times, resource consumption and business costs. The first scenario is a burst-load scenario. All methodologies will discard requests if the rapidness of the burst is high enough. This scenario focuses on the number of discarded requests and the variance of the response time. The second scenario contains sudden load drops followed by bursts to observe how the methodology behaves when releasing resources that are lately required. The third scenario contains diverse growth accelerations in the number of incoming requests to observe how approaches that add a different number of instances can handle the load with less business cost. The exposed methodology is compared against a multiple threshold CPU methodology allocating/deallocating 10 or 20 instances, outperforming the competitor in all studied metrics.

Keywords: reactive auto-scaling, auto-scaling, microservices, cloud computing

Procedia PDF Downloads 68

Authors: D. Ravinder

Abstract:

Nickel ferrites and Ni doped Lithium nano ferrites [Li0.5Fe0.5]1-xNixFe2O4 with x= 0.8 and 1.0 synthesized by citrate-gel auto combustion method. The broad peaks in the X-ray diffraction pattern (XRD) indicate a crystalline behavior of the prepared samples. Low temperature magnetization studies i,e Field Cooled (FC) and Zero Field Cooled (ZFC) magnetic studies of the investigated samples are measured by using vibrating sample magnetometer (VSM). The magnetization of the prepared samples as a function of an applied magnetic field 10 T was measured at two different temperatures 5 K and 310 K. Field Cooled (FC) and Zero Field Cooled (ZFC) magnetization measurements under an applied field of 100 Oe and 1000 Oe in the temperature range of 5–375 K were carried out.

Keywords: ferro-spinels, field cooled (FC), Zero Field Cooled (ZFC) and blocking temperature, superpara magnetism, drug delivery applications

Procedia PDF Downloads 528

Authors: D. Garg, S. Luthra, A. Haleem

Abstract:

Due to growing concern about environmental and social consequences throughout the world, a need has been felt to incorporate sustainability concepts in conventional manufacturing. This paper is an attempt to identify and evaluate drivers in implementing sustainable manufacturing in Indian context. Nine possible drivers for successful implementation of sustainable manufacturing have been identified from extensive review. Further, Decision Making Trial and Evaluation Laboratory (DEMATEL) approach has been utilized to evaluate and categorize these identified drivers for implementing sustainable manufacturing in to the cause and effect groups. Five drivers (Societal Pressure and Public Concerns; Regulations and Government Policies; Top Management Involvement, Commitment and Support; Effective Strategies and Activities towards Socially Responsible Manufacturing and Market Trends) have been categorized into the cause group and four drivers (Holistic View in Manufacturing Systems; Supplier Participation; Building Sustainable culture in Organization; and Corporate Image and Benefits) have been categorized into the effect group. “Societal Pressure and Public Concerns” has been found the most critical driver and “Corporate Image and Benefits” as least critical or the most easily influenced driver to implementing sustainable manufacturing in Indian context. This paper may surely help practitioners in better understanding of these drivers and their priorities towards effective implementation of sustainable manufacturing.

Keywords: drivers, decision making trial and evaluation laboratory (DEMATEL), India, sustainable manufacturing

Procedia PDF Downloads 359