Search results for: aerospace manufacturing

Authors: Băilă Diana Irinel, Păcurar Răzvan, Păcurar Ancuța

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In the last years, composite materials are increasingly used in automotive, aeronautic, aerospace, construction applications. Composite materials have been used in aerospace in applications such as engine blades, brackets, interiors, nacelles, propellers/rotors, single aisle wings, wide body wings. The fields of use of composite materials have multiplied with the improvement of material properties, such as stability and adaptation to the environment, mechanical tests, wear resistance, moisture resistance, etc. The composite materials are classified concerning type of matrix materials, as metallic, polymeric and ceramic based composites and are grouped according to the reinforcement type as fibre, obtaining particulate and laminate composites. Production of a better material is made more likely by combining two or more materials with complementary properties. The best combination of strength and ductility may be accomplished in solids that consist of fibres embedded in a host material. Polyester is a suitable component for composite materials, as it adheres so readily to the particles, sheets, or fibres of the other components. The important properties of the reinforcing fibres are their high strength and high modulus of elasticity. For applications, as in automotive or in aeronautical domain, in which a high strength-to-weight ratio is important, non-metallic fibres such as fiberglass have a distinct advantage because of their low density. In general, the glass fibres content varied between 9 to 33% wt. in the composites. In this article, high-performance types of composite materials glass-epoxy and glass-polyester used in automotive domain will be analyzed, performing tensile and flexural tests and SEM analyzes.

Keywords: glass-polyester composite, glass fibre, traction and flexion tests, SEM analyzes

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Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

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To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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Authors: Anjali G. Pillai, S. Chadrakaran

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The extensive amount of sludge generated throughout the world, as a part of water treatment works, have caused various social and economic issues, such as a demand on landfill spaces, increase in environmental pollution and raising the waste management cost. With growing social awareness about toxic incinerator emissions and the increasing concern over the disposal of sludge on the agricultural land, the recovery of sewage sludge as a building and construction raw material can be considered as an innovative approach to tackle the sludge disposal problem. The proposed work aims at studying the recycling ability of the sludge, generated from the water treatment process, by incorporating it into the fired clay brick units. The work involves initial study of the geotechnical characteristics of the brick-clay and the sludge. Chemical compatibility of both the materials will be analyzed by X-ray fluorescence technique. The variation in the strength aspects with varying proportions of sludge i.e. 10%, 20%, 30% and 40% in the sludge-clay mix will also be determined by the proctor density test. Based on the optimum moisture content, the sludge-clay bricks will be manufactured in a brick manufacturing plant and the modified brick units will be tested to determine the variation in compressive strength, bulk density, firing shrinkage, shrinkage loss and initial water absorption rate with respect to the conventional clay bricks. The results will be compared with the specifications given in Indian Standards to arrive at the potential use of the new bricks. The durability aspect will be studied by conducting the leachate analysis test using atomic adsorption spectrometry. The lightweight characteristics of the sludge modified bricks will be ascertained with the scanning electron microscope technique which will be indicative of the variation in pore structure with the increase in sludge content within the bricks. The work will determine the suitable proportion of the sludge – clay mix in the brick which can then be effectively implemented. The feasibility aspect of the work will be determined for commercial production of the units. The work involves providing a strategy for conversion of waste to resource. Moreover, it provides an alternative solution to the problem of growing scarcity of brick-clay for the manufacturing of fired clay bricks.

Keywords: eco-bricks, green construction material, sludge amended bricks, sludge disposal, waste management

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Authors: P. S. Hsi, Y. F. Wang, Y. F. Ho, P. C. Hung

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The aim of the present study was to explore the dermal exposure assessment model of chemicals that have been developed abroad and to evaluate the feasibility of chemical dermal exposure assessment model for manufacturing industry in Taiwan. We conducted and analyzed six semi-quantitative risk management tools, including UK - Control of substances hazardous to health ( COSHH ) Europe – Risk assessment of occupational dermal exposure ( RISKOFDERM ), Netherlands - Dose related effect assessment model ( DREAM ), Netherlands – Stoffenmanager ( STOFFEN ), Nicaragua-Dermal exposure ranking method ( DERM ) and USA / Canada - Public Health Engineering Department ( PHED ). Five types of manufacturing industry were selected to evaluate. The Monte Carlo simulation was used to analyze the sensitivity of each factor, and the correlation between the assessment results of each semi-quantitative model and the exposure factors used in the model was analyzed to understand the important evaluation indicators of the dermal exposure assessment model. To assess the effectiveness of the semi-quantitative assessment models, this study also conduct quantitative dermal exposure results using prediction model and verify the correlation via Pearson's test. Results show that COSHH was unable to determine the strength of its decision factor because the results evaluated at all industries belong to the same risk level. In the DERM model, it can be found that the transmission process, the exposed area, and the clothing protection factor are all positively correlated. In the STOFFEN model, the fugitive, operation, near-field concentrations, the far-field concentration, and the operating time and frequency have a positive correlation. There is a positive correlation between skin exposure, work relative time, and working environment in the DREAM model. In the RISKOFDERM model, the actual exposure situation and exposure time have a positive correlation. We also found high correlation with the DERM and RISKOFDERM models, with coefficient coefficients of 0.92 and 0.93 (p<0.05), respectively. The STOFFEN and DREAM models have poor correlation, the coefficients are 0.24 and 0.29 (p>0.05), respectively. According to the results, both the DERM and RISKOFDERM models are suitable for performance in these selected manufacturing industries. However, considering the small sample size evaluated in this study, more categories of industries should be evaluated to reduce its uncertainty and enhance its applicability in the future.

Keywords: dermal exposure, risk management, quantitative estimation, feasibility evaluation

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Authors: Adria Kajenski, Guinevere Strack, Edward Kingsley, Shahriar Khushrushahi, Alkim Akyurtlu

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Radio Frequency (RF) metasurfaces are arrangements of subwavelength elements interacting with electromagnetic radiation. These arrangements affect polarization state, amplitude, and phase of impinged radio waves; for example, metasurface designs are used to produce functional passband and stopband filters. Recent advances in additive manufacturing techniques have enabled the low-cost, rapid fabrication of ultra-thin metasurface elements on flexible substrates such as plastic films, paper, and textiles. Furthermore, scalable manufacturing processes promote the integration of fabric-based RF metasurfaces into the market of sensors and devices within the Internet of Things (IoT). The design and fabrication of metasurfaces on textiles require a multidisciplinary team with expertise in i) textile and materials science, ii) metasurface design and simulation, and iii) metasurface fabrication and testing. In this presentation, we will discuss RF metasurfaces on fabric with an emphasis on how the materials, including fabric and inks, along with fabrication techniques, affect the RF performance. We printed metasurfaces using a direct-write approach onto various woven and non-woven fabrics, as well as on fabrics coated with either thermoplastic or thermoset coatings. Our team also performed a range of tests on the printed structures, including different inks and their curing parameters, wash durability, abrasion resistance, and RF performance over time.

Keywords: electronic textiles, metasurface, printed electronics, flexible

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Authors: Shryas Bhurat, Aryan Vashistha, Sampreet Dinakar Nayak, Ayush Gupta

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As the technology is advancing more towards high computational resources, there is a paradigm shift in the usage of these resources to optimize the design process. This paper discusses the usage of ‘Generative Design using Artificial Intelligence’ to build better models that adapt the operations like selection, mutation, and crossover to generate results. The human mind thinks of the simplest approach while designing an object, but the intelligence learns from the past & designs the complex optimized CAD Models. Generative Design takes the boundary conditions and comes up with multiple solutions with iterations to come up with a sturdy design with the most optimal parameter that is given, saving huge amounts of time & resources. The new production techniques that are at our disposal allow us to use additive manufacturing, 3D printing, and other innovative manufacturing techniques to save resources and design artistically engineered CAD Models. Also, this paper discusses the Genetic Algorithm, the Non-Domination technique to choose the right results using biomimicry that has evolved for current habitation for millions of years. The computer uses parametric models to generate newer models using an iterative approach & uses cloud computing to store these iterative designs. The later part of the paper compares the topology optimization technology with Generative Design that is previously being used to generate CAD Models. Finally, this paper shows the performance of algorithms and how these algorithms help in designing resource-efficient models.

Keywords: genetic algorithm, bio mimicry, generative modeling, non-dominant techniques

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Ebrahim Sabermaash Eshghi, Donna Sandsmark

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Nowadays, successful companies try to create a reliable and unique competitive position in the market. It is important to consider that only choosing and codifying a competitive strategy appropriate with the market conditions does not have any influence on the final performance of the company by itself, but it is the connection and interaction between upstream level strategies and functional level strategies which leads to development of company performance in its operating environment. Given the importance of the subject, this study tries to investigate effective factors on product performance and prioritize them. This study was done with quantitative-qualitative approach (interview and questionnaire). In sum, 103 informed managers and experts of Pars-Khazar Company were investigated in a census. Validity of measure tools was approved through experts’ judgments. Reliability of the tools was also gained through Cronbach's Alpha Coefficient as 0.930 and in sum, validity and reliability of the tools was approved generally. Analysis of collected data was done through Spearman Correlation Test and Friedman Test using SPSS software. The results showed that management of distribution and demand process (0.675), management of Product Pre-test (0.636) and Manufacturing and inventory management(0.628) had the highest correlation with product performance. Prioritization of factors of structure of launching new products based on the average showed that management of volume of launched products and Manufacturing and inventory management had the most importance.

Keywords: product performance, home appliances, market, case study

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Authors: Ariadna Manresa, Ines Ferrer

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Introduction: Ultrasonic moulding process (USM) is a recent injection technology used to manufacture micro components. It is able to melt small amounts of material so the waste of material is certainly reduced comparing to microinjection molding. This is an important advantage when the materials are expensive like medical biopolymers. Micro-scaled components are involved in a variety of uses, such as biomedical applications. It is required replication fidelity so it is important to stabilize the process and minimize the variability of the responses. The aim of this research is to investigate the influence of the main process parameters on the filling behaviour, the dimensional accuracy and the cavity pressure when a micro-plate is manufactured by biomaterials such as PLA and PCL. Methodology or Experimental Procedure: The specimens are manufactured using a Sonorus 1G Ultrasound Micro Molding Machine. The used geometry is a rectangular micro-plate of 15x5mm and 1mm of thickness. The materials used for the investigation are PLA and PCL due to biocompatible and degradation properties. The experimentation is divided into two phases. Firstly, the influence of process parameters (vibration amplitude, sonotrodo velocity, ultrasound time and compaction force) on filling behavior is analysed, in Phase 1. Next, when filling cavity is assured, the influence of both cooling time and force compaction on the cavity pressure, part temperature and dimensional accuracy is instigated, which is done in Phase. Results and Discussion: Filling behavior depends on sonotrodo velocity and vibration amplitude. When the ultrasonic time is higher, more ultrasonic energy is applied and the polymer temperature increases. Depending on the cooling time, it is possible that when mold is opened, the micro-plate temperature is too warm. Consequently, the polymer relieve its stored internal energy (ultrasonic and thermal) expanding through the easier direction. This fact is reflected on dimensional accuracy, causing micro-plates thicker than the mold. It has also been observed the most important fact that affects cavity pressure is the compaction configuration during the manufacturing cycle. Conclusions: This research demonstrated the influence of process parameters on the final micro-plated manufactured. Future works will be focused in manufacturing other geometries and analysing the mechanical properties of the specimens.

Keywords: biomaterial, biopolymer, micro injection molding, ultrasound

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Authors: ZeinolAbedin Rahmani, Marzieh Evazi Borazjani, Nooshin Salehi

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Organizations are increasingly facing changes and developments scientific, technological, social, cultural changes among these organizations those ones are reckoned successful and effective that in addition to coordinating the development of modern society can forecast future changes and be able to accommodate these changes in order to create favorable developments to build a better future. But we can change that with the changes that occur in the organization of the program it will distinguish. Today's organizations need leaders that change and grow them have to survive. In fact, without transformational managers and leaders, it is certainly difficult to create changes in organizations. Both private and public organizations need to increase knowledge and awareness of the cause widespread changes in the structure, culture and practice for the viability and sustainability of life and growth and development. By now, different signs have determined different causes for a suitable function of employees. However, the important thing is that the commitment of the employees to their organization has always been very important. Since the decrease of organization commitment causes the high rate of absenteeism, turnover intentions, and even to reduce the impact of health staff. and these factors prevent organizations from achieving its goals. If organizations want to retain staff, the organization must find a way to be happy and continue their work with commitment, motivation, and willingness. So here is the need for strong leaders, analysts, creative and transformational upper ranks more than ever is felt. The aim of this study is to revise history, the leadership style of managers shipbuilding company by using the MLQ model.

Keywords: leadership style, managers, organizational, manufacturing company, sustainability of life

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Authors: S. Vignesh, N. Vishnu, S. Vigneshwaran, M. Vishnu Anand, Dinesh Kumar Babu, V. R. Sanal Kumar

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The study of the primary flow velocity and the self impinging secondary jet flow mixing is important from both the fundamental research and the application point of view. Real industrial configurations are more complex than simple shear layers present in idealized numerical thrust-vectoring models due to the presence of combustion, swirl and confinement. Predicting the flow features of self impinging secondary jets in a supersonic primary flow is complex owing to the fact that there are a large number of parameters involved. Earlier studies have been highlighted several key features of self impinging jets, but an extensive characterization in terms of jet interaction between supersonic flow and self impinging secondary sonic jets is still an active research topic. In this paper numerical studies have been carried out using a validated two-dimensional k-omega standard turbulence model for the design optimization of a thrust vector control system using shock induced self impinging secondary flow sonic jets using non-reacting flows. Efforts have been taken for examining the flow features of TVC system with various secondary jets at different divergent locations and jet impinging angles with the same inlet jet pressure and mass flow ratio. The results from the parametric studies reveal that in addition to the primary to the secondary mass flow ratio the characteristics of the self impinging secondary jets having bearing on an efficient thrust vectoring. We concluded that the self impinging secondary jet nozzles are better than single jet nozzle with the same secondary mass flow rate owing to the fact fixing of the self impinging secondary jet nozzles with proper jet angle could facilitate better thrust vectoring for any supersonic aerospace vehicle.

Keywords: fluidic thrust vectoring, rocket steering, supersonic to sonic jet interaction, TVC in aerospace vehicles

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Authors: Monika Balach, Iwona Frydrych, Agnieszka Cichocka

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The objective of this research is to develop an algorithm, taking into account material type and body type that will describe the fabric properties and quality of fit of a garment to the body. One of the objectives of this research is to develop a new algorithm to simulate cloth draping within CAD/CAM software. Existing virtual fitting does not accurately simulate fabric draping behaviour. Part of the research into virtual fitting will focus on the mechanical properties of fabrics. Material behaviour depends on many factors including fibre, yarn, manufacturing process, fabric weight, textile finish, etc. For this study, several different fabric types with very different mechanical properties will be selected and evaluated for all of the above fabric characteristics. These fabrics include woven thick cotton fabric which is stiff and non-bending, woven with elastic content, which is elastic and bends on the body. Within the virtual simulation, the following mechanical properties can be specified: shear, bending, weight, thickness, and friction. To help calculate these properties, the KES system (Kawabata) can be used. This system was originally developed to calculate the mechanical properties of fabric. In this research, the author will focus on three properties: bending, shear, and roughness. This study will consider current research using the KES system to understand and simulate fabric folding on the virtual body. Testing will help to determine which material properties have the largest impact on the fit of the garment. By developing an algorithm which factors in body type, material type, and clothing function, it will be possible to determine how a specific type of clothing made from a particular type of material will fit on a specific body shape and size. A fit indicator will display areas of stress on the garment such as shoulders, chest waist, hips. From this data, CAD/CAM software can be used to develop garments that fit with a very high degree of accuracy. This research, therefore, aims to provide an innovative solution for garment fitting which will aid in the manufacture of clothing. This research will help the clothing industry by cutting the cost of the clothing manufacturing process and also reduce the cost spent on fitting. The manufacturing process can be made more efficient by virtual fitting of the garment before the real clothing sample is made. Fitting software could be integrated into clothing retailer websites allowing customers to enter their biometric data and determine how the particular garment and material type would fit their body.

Keywords: 3D scanning, fabric mechanical properties, quality of fit, virtual fitting

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Authors: Abdolmajid Mosleh, Afzal Ghasimi

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The purpose of this research is to investigate and identify effective factors that can improve the quality of personal performance in industrial companies. In the present study, it was assumed that the hidden variables of talent management could be explained by an important part of the variance in improving the quality of employee performance. This research is targeted in terms of applied research. The statistical population of the research is SAIPA automobile company with a number (N=10291); the sample of 380 people was selected based on the Cochran formula in a random sampling method among employed people. The measurement tool in this research was a questionnaire of 33 items with a control questionnaire that included two talent management departments (talent identification and talent exploitation) and improvements in staff performance (enhancement of technical and specialized capabilities, managerial capability, organizational interaction, and communication). The reliability of the internal consistency method was confirmed by the Cronbach's alpha coefficient and the two half-ways. In order to determine the validity of the questionnaire structure, confirmatory factor analysis was used. Based on the results of the data analysis, the effect of talent management on improving the quality of staff performance was confirmed. Based on the results of inferential statistics and structural equations of the proposed model, it had high fitness.

Keywords: employee performance, talent management, performance improvement, SAIPA automobile manufacturing company

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Authors: Atousa Khodadadyan, Ali Rostami

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The objective of off-site construction manufacturing is to utilise the workforce and machinery in a controlled environment without external interference for higher productivity and quality. The usage of prefabricated components can save up to 14% of the total energy consumption in comparison with the equivalent number of cast-in-place ones. Despite the benefits of prefabrication construction, its current project practices encompass technical and managerial issues. Building design, precast components’ production, logistics, and prefabrication installation processes are still mostly discontinued and fragmented. Furthermore, collaboration among prefabrication manufacturers, transportation parties, and on-site assemblers rely on real-time information such as the status of precast components, delivery progress, and the location of components. From the technical point of view, in this industry, geometric variability is still prevalent, which can be caused during the transportation or production of components. These issues indicate that there are still many aspects of prefabricated construction that can be developed using disruptive technologies. Practical real-time risk analysis can be used to address these issues as well as the management of safety, quality, and construction environment issues. On the other hand, the lack of research about risk assessment and the absence of standards and tools hinder risk management modeling in prefabricated construction. It is essential to note that no risk management standard has been established explicitly for prefabricated construction projects, and most software packages do not provide tailor-made functions for this type of projects.

Keywords: project risk management, risk analysis, risk modelling, prefabricated construction projects

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Authors: Talha Khan, Surendhar Kumaran, Rajeev Nair

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The development of economical, efficient, and reliable next-generation thermal and water management systems to provide efficient cooling and water management technologies is being pursued application in compact and lightweight spacecraft. The elimination of liquid-vapor phase change-based thermal and water management systems is being done due to issues with the reliability and robustness of this technology. To achieve the motive of implementing the principle of using an innovative evaporator and condenser design utilizing bimodal wicks manufactured using a microsecond pulsed CO₂ laser has been proposed in this study. Cylin drical, multilayered capillary copper wicks with a substrate diameter of 39 mm are additively manufactured using a pulsed laser. The copper particles used for layer-by-layer addition on the substrate measure in a diameter range of 225 to 450 micrometers. The primary objective is to develop a novel, high-quality, fast turnaround, laser-based additive manufacturing process that will eliminate the current technical challenges involved with the traditional manufacturing processes for nano/micro-sized powders, like particle agglomeration. Raster-scanned, pulsed-laser sintering process has been developed to manufacture 3D wicks with controlled porosity and permeability.

Keywords: liquid-vapor phase change, bimodal wicks, multilayered, capillary, raster-scanned, porosity, permeability

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Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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Authors: Tansel Comoglu

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Orally fast disintegrating tablets (FDTs or ODTs) have become popular during the last decade, and manufacturing of ODTs is getting a rapidly growing area in the pharmaceutical industry. The concept of ODTs has emerged from the desire to provide patients with more conventional means of taking their medication. Drugs, that have satisfactory absorption from the oral mucosa or aimed for immediate therapeutic activity can be formulated in ODTs. After placing the ODT into the mouth, these tablets dissolve or disintegrate in the mouth usullay less than a minute, in the absence of additional water. Even though the ODT technology has taken an important path, as proved by a large group of commercial products on the drug market, there are so many problems to be solved in ODT formulations such as; formulation of hydrophobic drugs is stil a challenge, especially when the amount of drug is high. As these tablets dissolve or disintegrate in the mouth without the need of additional water, taste masking of active ingredients becomes essential in these systems because the drug is entirely released in the mouth. In ODT technology, coping with the taste of drugs is still a challenge. Resins or sweeteners or other techniques are also used in the formulation to aid taste-masking of the API. Another important factor to consider is whether they can be manufactured using conventional equipment and processes, as this will have a positive influence on manufacturing costs. Some products, however, may require a more costly, special unitdose packaging if the dosage form is fragile. In this overview, benefits, various formulation technologies, clinical studies and some future research trends of ODTs will be discussed.

Keywords: orally fast disintegrating tablets, benefits, formulation technologies, future research trends

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Authors: Gaurav Gupta, Jitendra Mahakud

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This study focuses on the significance of internal financing constraints on the determination of corporate fixed investments in the case of Indian manufacturing companies. Financing constraints companies which have less internal fund or retained earnings face more transaction and borrowing costs due to imperfections in the capital market. The period of study is 1999-2000 to 2013-2014 and we consider 618 manufacturing companies for which the continuous data is available throughout the study period. The data is collected from PROWESS data base maintained by Centre for Monitoring Indian Economy Pvt. Ltd. Panel data methods like fixed effect and random effect methods are used for the analysis. The Likelihood Ratio test, Lagrange Multiplier test, and Hausman test results conclude the suitability of the fixed effect model for the estimation. The cash flow and liquidity of the company have been used as the proxies for the internal financial constraints. In accordance with various theories of corporate investments, we consider other firm specific variable like firm age, firm size, profitability, sales and leverage as the control variables in the model. From the econometric analysis, we find internal cash flow and liquidity have the significant and positive impact on the corporate investments. The variables like cost of capital, sales growth and growth opportunities are found to be significantly determining the corporate investments in India, which is consistent with the neoclassical, accelerator and Tobin’s q theory of corporate investment. To check the robustness of results, we divided the sample on the basis of cash flow and liquidity. Firms having cash flow greater than zero are put under one group, and firms with cash flow less than zero are put under another group. Also, the firms are divided on the basis of liquidity following the same approach. We find that the results are robust to both types of companies having positive and negative cash flow and liquidity. The results for other variables are also in the same line as we find for the whole sample. These findings confirm that internal financing constraints play a significant role for determination of corporate investment in India. The findings of this study have the implications for the corporate managers to focus on the projects having higher expected cash inflows to avoid the financing constraints. Apart from that, they should also maintain adequate liquidity to minimize the external financing costs.

Keywords: cash flow, corporate investment, financing constraints, panel data method

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Authors: A. S. V. Carvalho, J. Luis, L. S. O. Pires, J. M. Oliveira

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Additive manufacturing technologies (AM) experienced a remarkable growth in the latest years due to the development and diffusion of a wide range of three-dimensional (3D) printing techniques. Nowadays we can find techniques available for non-industrial users, like fused filament fabrication, but techniques like 3D printing, polyjet, selective laser sintering and stereolithography are mainly spread in the industry. Robocasting (R3D) shows a great potential due to its ability to shape materials with a wide range of viscosity. Industrial porcelain compositions showing different rheological behaviour can be prepared and used as candidate materials to be processed by R3D. The use of this AM technique in industry is very residual. In this work, a specific porcelain composition with suitable rheological properties will be processed by R3D, and a systematic study of the printing parameters tuning will be shown. The porcelain composition was formulated based on an industrial spray dried porcelain powder. The powder particle size and morphology was analysed. The powders were mixed with water and an organic binder on a ball mill at 200 rpm/min for 24 hours. The batch viscosity was adjusted by the addition of an acid solution and mixed again. The paste density, viscosity, zeta potential, particle size distribution and pH were determined. In a R3D system, different speed and pressure settings were studied to access their impact on the fabrication of porcelain models. These models were dried at 80 °C, during 24 hours and sintered in air at 1350 °C for 2 hours. The stability of the models, its walls and surface quality were studied and their physical properties were accessed. The microstructure and layer adhesion were observed by SEM. The studied processing parameters have a high impact on the models quality. Moreover, they have a high impact on the stacking of the filaments. The adequate tuning of the parameters has a huge influence on the final properties of the porcelain models. This work contributes to a better assimilation of AM technologies in ceramic industry. Acknowledgments: The RoboCer3D project – project of additive rapid manufacturing through 3D printing ceramic material (POCI-01-0247-FEDER-003350) financed by Compete 2020, PT 2020, European Regional Development Fund – FEDER through the International and Competitive Operational Program (POCI) under the PT2020 partnership agreement.

Keywords: additive manufacturing, porcelain, robocasting, R3D

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Authors: Young Jae Choung, Seoung Bum Kim

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Statistical Process Control (SPC) is a popular technique for process monitoring. A widely used tool in SPC is a control chart, which is used to detect the abnormal status of a process and maintain the controlled status of the process. Traditional control charts, such as Hotelling’s T2 control chart, are effective techniques to detect abnormal observations and monitor processes. However, many complicated manufacturing systems exhibit nonlinearity because of the different demands of the market. In this case, the unregulated use of a traditional linear modeling approach may not be effective. In reality, many industrial processes contain the nonlinear and time-varying properties because of the fluctuation of process raw materials, slowing shift of the set points, aging of the main process components, seasoning effects, and catalyst deactivation. The use of traditional SPC techniques with time-varying data will degrade the performance of the monitoring scheme. To address these issues, in the present study, we propose a parameterless self-organizing map (PLSOM)-based control chart. The PLSOM-based control chart not only can manage a situation where the distribution or parameter of the target observations changes, but also address the nonlinearity of modern manufacturing systems. The control limits of the proposed PLSOM chart are established by estimating the empirical level of significance on the percentile using a bootstrap method. Experimental results with simulated data and actual process data from a thin-film transistor-liquid crystal display process demonstrated the effectiveness and usefulness of the proposed chart.

Keywords: control chart, parameter-less self-organizing map, self-organizing map, time-varying property

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Authors: Doris Lacej, Eni Bushi

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Cleaning and disinfection procedures are essential for maintaining the cleanliness status of the pharmaceutical manufacturing environment particularly of the cleanrooms and sterile unit area. The Good Manufacturing Practice (GMP) Annex 1 recommendation highly requires the implementation of the standard and validated cleaning and disinfection protocols. However, environmental monitoring has shown that even a validated cleaning method with certified agents may result in the presence of atypical microorganisms’ colony that exceeds GMP limits for a specific cleanroom area. In response to this issue, this case study aims to arrive at the root cause of the microbial contamination observed in the sterile production environment in Profarma pharmaceutical industry in Albania through applying a problem-solving practical approach that ensures the appropriate sterility grade. The guidelines and literature emphasize the importance of several factors in the prevention of possible microbial contamination occurring in cleanrooms, grade A and C. These factors are integrated into a practical framework, to identify the root cause of the presence of Aspergillus Niger colony in the sterile production environment in Profarma pharmaceutical industry in Albania. In addition, the application of a semi-automatic disinfecting system such as H2O2 FOG into sterile grade A and grade C cleanrooms has been an effective solution in eliminating the atypical colony of Aspergillus Niger. Selecting the appropriate detergents and disinfectants at the right concentration, frequency, and combination; the presence of updated and standardized guidelines for cleaning and disinfection as well as continuous training of operators on these practices in accordance with the updated GMP guidelines are some of the identified factors that influence the success of achieving sterility grade. However, to ensure environmental sustainability it is important to be prepared for identifying the source of contamination and making the appropriate decision. The proposed case-based practical approach may help pharmaceutical companies to achieve sterile production and cleanliness environmental sustainability in challenging situations. Apart from the integration of valid agents and standardized cleaning and disinfection protocols according to GMP Annex 1, pharmaceutical companies must be careful and investigate the source and all the steps that can influence the results of an abnormal situation. Subsequently apart from identifying the root cause it is important to solve the problem with a successful alternative approach.

Keywords: cleanrooms, disinfectants, environmental monitoring, GMP Annex 1

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Authors: Udeh Nneka Evelyn

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The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

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Authors: Mohsen Yaghmor, Sima Radmanesh

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Rapid environmental changes have been threatening the life of many organizations. Enabling and productivity of human resource should be considered as the most important issue in order to increase performance and ensure survival of the organizations. In this research, the effectiveness of management factory in productivity and inability of human resource have been identified and reviewed at glance. Afterwards, answers were sought to questions "What are the factors effecting productivity and enabling of human resource?" and "What are the priority order based on effective management of human resource in Fars Poultry Complex?". A specified questionnaire has been designed regarding the priorities and effectiveness of the identified factors. Six factors were specified consisting of: individual characteristics, teaching, motivation, partnership management, authority or power submission and job development that have most effect on organization. Then a questionnaire was specified for priority and effect measurement of specified factors that were reached after collecting information and using statistical tests of Keronchbakh alpha coefficient r = 0.792, so that we can say the questionnaire has sufficient reliability. After information analysis of specified six factors by Friedman test their effects were categorized. Measurement on organization respectively consists of individual characteristics, job development or enrichment, authority submission, partnership management, teaching and motivation. Lastly, approaches has been introduced to increase productivity of manpower.

Keywords: productivity, empowerment, enrichment, authority submission, partnership management, teaching, motivation

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Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

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Authors: Sanjal Gavande, Thomas Mazzuchi, Shahram Sarkani

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In a complex aerospace operational environment, identifying failures in a procedure involving multiple human-machine interactions are difficult. These failures could lead to accidents causing loss of hardware or human life. The likelihood of failure further increases if operational procedures are tested for a novel system with multiple human-machine interfaces and with no prior performance data. The existing approach in the literature of reviewing complex operational tasks in a flowchart or tabular form doesn’t provide any insight into potential system failures due to human decision-making ability. To address these challenges, this research explores an agent-based simulation approach for reliability assessment and fault detection in complex human-machine systems while utilizing a human decision-making model. The simulation will predict the emergent behavior of the system due to the interaction between humans and their decision-making capability with the varying states of the machine and vice-versa. Overall system reliability will be evaluated based on a defined set of success-criteria conditions and the number of recorded failures over an assigned limit of Monte Carlo runs. The study also aims at identifying high-likelihood failure locations for the system. The research concludes that system reliability and failures can be effectively calculated when individual human and machine agent states are clearly defined. This research is limited to the operations phase of a system lifecycle process in an aerospace environment only. Further exploration of the proposed agent-based and human decision-making model will be required to allow for a greater understanding of this topic for application outside of the operations domain.

Keywords: agent-based model, complex human-machine system, human decision-making model, system reliability assessment

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Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

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The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

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Authors: Zhiyong Li, Hiroshi Katayama

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Since 1990s, e-commerce and internet business have been grown gradually over the word and customers tend to express their demand attributes in terms of specification requirement on parts, component, product structure etc. This paper deals with designing effective decoupling points for build to order systems under e-commerce environment, which can be realized through tradeoff relation analysis between two major criteria, customer order lead time and value of work in progress. These KPIs are critical for successful BTO business, namely time-based service effectiveness on coping with customer requirements for the first issue and cost effective ness with risk aversive operations for the second issue. Approach of this paper consists of investigation of successful business standing for BTO scheme, manufacturing model development of this scheme, quantitative evaluation of proposed models by calculation of two KPI values under various decoupling point distributions and discussion of the results brought by pattern of decoupling point distribution, where some cases provide the pareto optimum performances. To extract the relevant trade-off relation between considered KPIs among 2-dimensional resultant performance, useful logic developed by former research work, i.e. Katayama and Fonseca, is applied. Obtained characteristics are evaluated as effective information for managing BTO manufacturing businesses.

Keywords: build-to-order (BTO), decoupling point, e-commerce, order-to-delivery lead time (ODLT), work in progress (WIP)

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Authors: Agidew Abay, Nobuhiro Hosoe

Abstract:

Ethiopia signed the AfCFTA in 2018 and is in ongoing negotiations to join the WTO. To assess the potential impacts of joining these trade agreements on Ethiopia's trade, output, and welfare, we conducted a comprehensive analysis using a world trade computable general equilibrium (CGE) model. The results of our policy experiment, which include scenarios involving the reduction of tariff and non-tariff measures, indicate that AfCFTA and WTO accession would positively affect Ethiopia's welfare, with WTO membership expected to bring more significant benefits. On the one hand, AfCFTA membership would significantly increase Ethiopian imports from AfCFTA regions while decreasing imports from non-AfCFTA regions. Conversely, it would boost Ethiopian exports to Southern Africa while showing minimal change to other AfCFTA and non-AfCFTA regions. By contrast, WTO membership would significantly increase Ethiopia’s imports from Asia and North Africa and decrease those from Europe, the rest of the world, and East Africa. It would increase exports to all regions, especially Europe, Asia, and the rest of the world. In terms of industrial output, while these two trade deals would largely favor agriculture and the meat and livestock sector and harm many manufacturing sectors (especially the light manufacturing sector), the impact of WTO accession on the Ethiopian economy would be overwhelmingly more significant than that of AfCFTA.

Keywords: trade liberalization, AfCFTA, WTO, computable general equilibrium model, tariff, non-tariff measures

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