Search results for: low series manufacturing

Authors: Pramod Keshav Kolase, Atul K. Desai

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This paper presents the experimental investigation results of Ultrasonic Pulse Velocity (UPV) tests conducted on roller compacted concrete pavement (RCCP) material containing Class F fly ash of as mineral admixture and triangular polyester fiber as a secondary reinforcement. The each mix design series fly ash content is varied from 0% to 45 % and triangular polyester fiber 0% to 0.75% by volume fraction. In each series and for different ages of curing (i.e. 7, 28 and 90 days) forty-eight cube specimens are cast and tested for compressive strength and UPV. The UPV of fly ash was found to be lower for all mixtures at 7 days in comparison with control mix concrete. But at 28, 56 days and 90 days the UPV were significantly improved for all the mixes. Relationships between compressive strength of RCCP and UPV and Dynamic Elastic Modulus are proposed for all series mixes.

Keywords: compressive strength, dynamic elastic modulus, fly ash, fiber, roller compacted concrete, ultrasonic pulse velocity

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Authors: Monika Chuchro

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This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

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Authors: Fawad Hussain, Mohammad Basir Bin Saud, Mohd Azwardi Md Isa

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The aim of this study is to empirically investigate the mediating impact of export performance (EP) between technological advancement capabilities (TAC) and business performance (BP) of Malaysian manufacturing MSME’s. Firm’s technological advancement resources are hypothesized as a platform to enhance both exports and business performance of manufacturing MSMEs in Malaysia. This study is twofold, primary it has investigated that technological advancement capabilities helps to appreciates main performance measures noted in terms of export performance and Secondly it investigates that how efficiently and effectively technological advancement capabilities can contributes in overall Malaysian MSME’s business performance. Smart PLS-3 statistical software is used to know the association between technological advancement capabilities, MSME’s export performance and business performance. In this study the data was composed from Malaysian manufacturing MSME’s in east coast industrial zones known as manufacturing hub of MSMEs. Seven Hundred and Fifty (750) questionnaires were distributed but only 148 usable questionnaires are returned. The finding of this study indicated that technological advancement capabilities helps to strengthen the export in term of time and cost efficient and it plays a significant role in appreciating their business performance. This study is helpful for small and medium enterprises owners who intent to expand their business overseas and though smart technological advancement resources they can achieve their business competitiveness and excellence both at local and international markets.

Keywords: technological advancement capabilities, export performance, business performance, small and medium manufacturing enterprises, malaysia

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Authors: Cansu Kandemir, Marco Franchino

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To attain sustainability goals, the manufacturing industries must assess and improve their processes, adopt the latest technologies, and ensure minimal environmental impact. Ongoing debates claim that the definition of sustainability and its assessment is vague. Companies struggle with understanding which processes they should prioritise and necessitate a methodology to aid decision-making. For that reason, our investigation focused on defining a prioritisation guide to help to manufacture engineers identify areas of a facility to prioritise de-carbonisation efforts based on existing sources of data. The authors at the University of Sheffield Advanced Manufacturing Research Centre (AMRC) worked with a range of major businesses, including Food and Drink (Moy Park), Automotive (Nissan), Aerospace and Defence (BAE, Meggitt, Leonardo, and GKN) and Technology (Accenture and Intellium AI). Collected information has been integrated into a prioritisation guide framework that helps process comparison and decision-making. The framework developed in this study aims to ensure that companies have guidance on where to focus their efforts whilst striving to fulfil their environmental and societal obligations.

Keywords: decision making, sustainability, carbon emissions, manufacturing

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: lean manufacturing, DOE, value stream mapping, textiles

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Authors: Sadman Durlov, Aditya Ganesh-Ram, Hamidreza Hekmatjou, Md Najmus Salehin, Nora Shayesteh Ameri

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In the field of additive manufacturing, tungsten stands out for its exceptional resistance to high temperatures, making it an ideal candidate for use in extreme conditions. However, its inherent brittleness and vulnerability to thermal cracking pose significant challenges to its manufacturability. This study explores the microstructural evolution of tungsten processed through layer-wise rolling in laser powder bed fusion additive manufacturing, utilizing a comprehensive approach that combines advanced simulation techniques with empirical research. We aim to uncover the complex processes of plastic deformation and microstructural transformations, with a particular focus on the dynamics of grain size, boundary evolution, and phase distribution. Our methodology employs a combination of simulation and experimental data, allowing for a detailed comparison that elucidates the key mechanisms influencing microstructural alterations during the rolling process. This approach facilitates a deeper understanding of the material's behavior under additive manufacturing conditions, specifically in terms of deformation and recrystallization. The insights derived from this research not only deepen our theoretical knowledge but also provide actionable strategies for refining manufacturing parameters to improve the tungsten components' mechanical properties and functional performance. By integrating simulation with practical experimentation, this study significantly enhances the field of materials science, offering a robust framework for the development of durable materials suited for challenging operational environments. Our findings pave the way for optimizing additive manufacturing techniques and expanding the use of tungsten across various demanding sectors.

Keywords: additive manufacturing, layer wise rolling, refractory materials, in-situ microstructure modifications

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Authors: Mohammed Alharbi, Clare Wood, Vasileios Samaras

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Sustainability leadership is a controversial topic, particularly in the engineering context. The theoretical and practical technical focus of the engineering profession impacts our lives. Technologically, engineers significantly contribute to our modern civilization. Industrial revolutions are among the top engineering accomplishments that have contributed to the flourishing of our life. However, engineers have not always received the credit they deserve; instead, they have been blamed for the advent of various global issues, among them the global warming phenomena that are believed to be a result of the industrial revolutions. Global challenges demand engineers demonstrate more than their technical skills for effective contribution to a sustainable future. As a result, engineering leadership has emerged as a new research field. Sustainable manufacturing is a cornerstone for sustainable development. Investigating the change to more sustainable manufacturing practices is a significant issue for all, and even more in the field of engineering leadership. Engineers dominate the manufacturing industry; however, one of the main criticism of engineers is the lack of leadership skills. The literature on engineering leadership has not highlighted enough the engineers' leadership ability in leading sustainable manufacturing. Since we are at the cusp of a new industrial revolution -Industry 4.0, it is vital to investigate the ability of engineers to lead the industry towards a sustainable future. The primary purpose of this paper is to evaluate engineers' sustainability leadership competencies utilizing The Cambridge University Behavioral Competency Model. However, the practical application of the Cambridge model is limited due to the absence of a reliable measurement tool. Therefore, this study developed a valid and reliable survey instrument tool compatible with the Cambridge model as a secondary objective. More than 300 Saudi engineers from the manufacturing industry responded to an online questionnaire collected through the Qualtrics platform and analyzed using SPSS software. The findings provide a contemporary understanding of engineers' mindset related to sustainability leadership. The output of this research study could be valuable in designing effective engineering leadership programs in academia or industry, particularly for enhancing a sustainable manufacturing environment.

Keywords: engineer, leadership, manufacturing, sustainability

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Authors: J. H. Park, S. K. Lee, Y. W. Kim, D. C. Ko

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A large variety of pipe flange is required in marine and construction industry.Pipe flanges are usually welded or screwed to the pipe end and are connected with bolts.This approach is very simple and widely used for a long time, however, it results in high development cost and low productivity, and the productions made by this approach usually have safety problem at the welding area.In this research, a new approach of forming pipe flange based on cold forging and floating die concept is presented.This innovative approach increases the effectiveness of the material usage and save the time cost compared with conventional welding method. To ensure the dimensional accuracy of the final product, the finite element analysis (FEA) was carried out to simulate the process of cold forging, and the orthogonal experiment methods were used to investigate the influence of four manufacturing factors (pin die angle, pipe flange angle, rpm, pin die distance from clamp jig) and predicted the best combination of them. The manufacturing factors were obtained by numerical and experimental studies and it shows that the approach is very useful and effective for the forming of pipe flange, and can be widely used later.

Keywords: cold forging, FEA (finite element analysis), forge-3D, rotating forming, tubes

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed-length window in the past as an explicit input. In this paper, we study how the performance of predictive models changes as a function of different look-back window sizes and different amounts of time to predict the future. We also consider the performance of the recent attention-based Transformer models, which have had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (RNN, LSTM, GRU, and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the UCI website, which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean Average Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: air quality prediction, deep learning algorithms, time series forecasting, look-back window

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Authors: Malki Nadia Fatima Zahra, Kellal Cheimaa, Brahimi Houria

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Aim of the study is to show the role of total Quality Management on firm performance; the research relied on the views of sample managers working in the Marinel pharmaceutical company. The research aims to achieve many objectives, including increasing awareness of the concepts of Total Quality Management on Firm Performance, especially in the manufacturing firm, providing a future vision of the possibility of success, and the actual application of the Principles of Total Quality Management in the manufacturing company. The research adopted a default model was built after a review and analysis of the literature review in the context of one hypothesis main points at the origin of a group of sub-hypotheses. The research presented a set of conclusions, and the most important of these conclusions was there is a relationship between the Principles of TQM and Firm Performance.

Keywords: total quality management, TQM dimension, firm performance, strategies

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Authors: Aljoša Šorgo

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Recent scholarship on Phrygian has begun to more closely examine the long-held belief that Greek and Phrygian are two very closely related languages. It is now clear that Graeco-Phrygian can be firmly postulated as a subclade of the Indo-European languages. The present paper will focus on the reconstruction of the phonological and phonetic segments of Proto-Graeco-Phrygian (= PGPh.) by providing relevant correspondence sets and reconstructing the classes of segments. The PGPh. basic vowel system consisted of ten phonemic oral vowels: */a e o ā ē ī ō ū/. The correspondences of the vowels are clear and leave little open to ambiguity. There were four resonants and two semi-vowels in PGPh.: */r l m n i̯ u̯/, which could appear in both a consonantal and a syllabic function, with the distribution between the two still being phonotactically predictable. Of note is the fact that the segments *m and *n seem to have merged when their phonotactic position would see them used in a syllabic function. Whether the segment resulting from this merger was a nasalized vowel (most likely *[ã]) or a syllabic nasal *[N̥] (underspecified for place of articulation) cannot be determined at this stage. There were three fricatives in PGPh.: */s h ç/. *s and *h are easily identifiable. The existence of *ç, which may seem unexpected, is postulated on the basis of the correspondence Gr. ὄς ~ Phr. yos/ιος. It is of note that Bozzone has previously proposed the existence of *ç ( < PIE *h₁i̯-) in an early stage of Greek even without taking into account Phrygian data. Finally, the system of stops in PGPh. distinguished four places of articulation (labial, dental, velar, and labiovelar) and three phonation types. The question of which three phonation types were actually present in PGPh. is one of great importance for the ongoing debate on the realization of the three series in PIE. Since the matter is still very much in dispute, we ought to, at this stage, endeavour to reconstruct the PGPh. system without recourse to the other IE languages. The three series of correspondences are: 1. Gr. T (= tenuis) ~ Phr. T; 2. Gr. D (= media) ~ Phr. T; 3. Gr. TA (= tenuis aspirata) ~ Phr. M. The first series must clearly be reconstructed as composed of voiceless stops. The second and third series are more problematic. With a bottom-up approach, neither the second nor the third series of correspondences are compatible with simple modal voicing, and the reflexes differ greatly in voice onset time. Rather, the defining feature distinguishing the two series was [±spread glottis], with ancillary vibration of the vocal cords. In PGPh. the second series was undergoing further spreading of the glottis. As the two languages split, this process would continue, but be affected by dissimilar changes in VOT, which was ultimately phonemicized in both languages as the defining feature distinguishing between their series of stops.

Keywords: bottom-up reconstruction, Proto-Graeco-Phrygian, spread glottis, syllabic resonant

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Authors: Chukwumeka Daniel Ezeliora

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The Nigerian manufacturing sector plays a pivotal role in the country's economic growth and development. However, it faces numerous challenges, including operational inefficiencies and inherent risks that hinder its sustainable growth. This research aims to address these challenges by exploring the integration of Lean and Six Sigma methodologies into the manufacturing processes, ultimately enhancing operational effectiveness and risk mitigation. The core of this research involves the development of a sustainable Lean Six Sigma framework tailored to the specific needs and challenges of Nigeria's manufacturing environment. This framework aims to streamline processes, reduce waste, improve product quality, and enhance overall operational efficiency. It incorporates principles of sustainability to ensure that the proposed methodologies align with environmental and social responsibility goals. To validate the effectiveness of the integrated Lean Six Sigma approach, case studies and real-world applications within select manufacturing companies in Nigeria will be conducted. Data were collected to measure the impact of the integration on key performance indicators, such as production efficiency, defect reduction, and risk mitigation. The findings from this research provide valuable insights and practical recommendations for selected manufacturing companies in South East Nigeria. By adopting sustainable Lean Six Sigma methodologies, these organizations can optimize their operations, reduce operational risks, improve product quality, and enhance their competitiveness in the global market. In conclusion, this research aims to bridge the gap between theory and practice by developing a comprehensive framework for the integration of Lean and Six Sigma methodologies in Nigeria's manufacturing sector. This integration is envisioned to contribute significantly to the sector's sustainable growth, improved operational efficiency, and effective risk mitigation strategies, ultimately benefiting the Nigerian economy as a whole.

Keywords: lean six sigma, manufacturing, risk mitigation, sustainability, operational efficiency

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Authors: George Nyori Makari

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Data on 92 industrial organizations point to the existence of relationships between advanced manufacturing technology (AMT) adoption and some aspects of organizational structure, including the number of specialized sub-units, the number of levels of authority, span of control, degree of role programming specification, degree of communication programming specification and the degree of output programming. Primary finding is that as the investments and integration of AMTs increases, the more likely the foregoing aspects of structure increase. The findings hold with size and a number of other organizational variables controlled. The results indicate that a company’s capacity to assimilate technology depends on its organizational capabilities. The study encapsulates the need for companies to increase their organizational capabilities during investment and integration of AMTs.

Keywords: advanced manufacturing technology, adoption, organizational structure, Kenya

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Authors: Tariq Aljuneidi, Akif Asil Bulgak

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Remanufacturing may be defined as the process of bringing used products to “like-new” functional state with warranty to match, and it is one of the most popular product end-of-life scenarios. An efficient remanufacturing network lead to an efficient design of sustainable manufacturing enterprise. In remanufacturing network, products are collected from the customer zone, disassembled and remanufactured at a suitable remanufacturing facility. In this respect, another issue to consider is how the returned product to be remanufactured, in other words, what is the best layout for such facility. In order to achieve a sustainable manufacturing system, Cellular Manufacturing System (CMS) designs are highly recommended, CMSs combine high throughput rates of line layouts with the flexibility offered by functional layouts (job shop). Introducing the CMS while designing a remanufacturing network will benefit the utilization of such a network. This paper presents and analyzes a comprehensive mathematical model for the design of Dynamic Cellular Remanufacturing Systems (DCRSs). In this paper, the proposed model is the first one to date that consider CMS and remanufacturing system simultaneously. The proposed DCRS model considers several manufacturing attributes such as multi-period production planning, dynamic system reconfiguration, duplicate machines, machine capacity, available time for workers, worker assignments, and machine procurement, where the demand is totally satisfied from a returned product. A numerical example is presented to illustrate the proposed model.

Keywords: cellular manufacturing system, remanufacturing, mathematical programming, sustainability

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Authors: Muriel Canas-Walker

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The 2012 TV series "The Legend of Zhen Huan" is one of the most popular and influential historical dramas on Chinese television and is regularly discussed on Chinese social media such as Weibo. Set in the Qing dynasty, the 76 episodes series features palace intrigues focused on female characters. In the Forbidden City, concubines must survive the cruelty of an extreme polygamy system, constantly competing against each other. The patriarchal oppression of the women sequestred in the harem relies on fierce female competition and does not leave much room for compassion. Using Michel Foucault’s theory of power, feminist theories, and visual anthropology, this paper analyzes the complex relationships between the female characters, from their rise to power to their fall from grace, from alliances to betrayals, from sorority to sororicide. This analysis aims to understand what makes this series particularly popular with young female audiences in China and explain its importance in Chinese media.

Keywords: Chinese TV Drama, feminism, popular culture, Theory of Power

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Authors: Tehreem Fatima, Enjun Xia

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The research investigates the relationship between total oil consumption and transport oil consumption, GDP, oil price, and oil reserve in order to forecast future oil demand in China. Annual time series data is used over the period of 1980 to 2015, and for this purpose, an oil demand function is estimated by applying structural time series model (STSM). The technique also uncovers the Underline energy demand trend (UEDT) for China oil demand and GDP, oil reserve, oil price and UEDT are considering important drivers of China oil demand. The long-run elasticity of total oil consumption with respect to GDP and price are (0.5, -0.04) respectively while GDP, oil reserve, and price remain (0.17; 0.23; -0.05) respectively. Moreover, the Estimated results of long-run elasticity of transport oil consumption with respect to GDP and price are (0.5, -0.00) respectively long-run estimates remain (0.28; 37.76;-37.8) for GDP, oil reserve, and price respectively. For both model estimated underline energy demand trend (UEDT) remains nonlinear and stochastic and with an increasing trend of (UEDT) and based on estimated equations, it is predicted that China total oil demand somewhere will be 9.9 thousand barrel per day by 2025 as compare to 9.4 thousand barrel per day in 2015, while transport oil demand predicting value is 9.0 thousand barrel per day by 2020 as compare to 8.8 thousand barrel per day in 2015.

Keywords: china, forecasting, oil, structural time series model (STSM), underline energy demand trend (UEDT)

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Authors: Ssu-Han Chen, Der-Baau Perng

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Molding process in IC manufacturing secures chips against the harms done by hot, moisture or other external forces. While a chip was being molded, defects like cracks, dilapidation, or voids may be embedding on the molding surface. The molding surfaces the study poises to treat and the ones on the market, though, differ in the surface where texture similar to defects is everywhere. Manual inspection usually passes over low-contrast cracks or voids; hence an automatic optical inspection system for molding surface is necessary. The proposed system is consisted of a CCD, a coaxial light, a back light as well as a motion control unit. Based on the property of statistical textures of the molding surface, a series of digital image processing and classification procedure is carried out. After training of the parameter associated with above algorithm, result of the experiment suggests that the accuracy rate is up to 93.75%, contributing to the inspection quality of IC molding surface.

Keywords: molding surface, machine vision, statistical texture, discrete Fourier transformation

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Authors: Eyal Rosen

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This study is aimed to report a possible effect of the presence of dental implants on the development of crown or root fractures in adjacent natural teeth. A series of 26 cases of teeth diagnosed with crown or root fractures following the placement of adjacent dental implants is presented. In addition, a comprehensive systematic review of the literature was performed to detect other studies that evaluated this possible complication. The case series analysis revealed that all crown-fractured teeth were non-endodontically treated teeth (n=18), and all root fractured teeth were endodontically treated teeth (n=8). The time from implant loading to the diagnosis of a fracture in an adjacent tooth was longer than 1 year in 78% of cases. The majority of crown or root fractures occurred in female patients, over 50 years of age, with an average age of 59 in the crown fractures group, and 54 in the root fractures group. Most of the patients received 2 or more implants. Nine (50%) of the teeth with crown fracture were molars, 7 (39%) were mandibular premolars, and 2 (11%) were incisor teeth. The majority of teeth with root fracture were premolar or mandibular molar teeth (6 (75%)). The systematic review of the literature did not reveal additional studies that reported on this possible complication. To the best of the author’s knowledge this case series, although limited in its extent, is the first clinical report of a possible serious complication of implants, associated fractures in adjacent endodontically and non-endodontically treated natural teeth. The most common patient profile found in this series was a woman over 50 years of age, having a fractured premolar tooth, which was diagnosed more than 1 year after reconstruction that was based on multiple adjacent implants. Additional clinical studies are required in order to shed light on this potential serious complication.

Keywords: complications, dental implants, endodontics, fractured teeth

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Authors: Protik Basu, Indranil Ghosh, Pranab K. Dan

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Lean management is an integrated socio-technical system to bring about a competitive state in an organization. The purpose of this paper is to explore and integrate the role of customers and suppliers with the internal practices of the Indian manufacturing industries towards successful implementation of lean manufacturing (LM). An extensive literature survey is carried out. An attempt is made to build an exhaustive list of all the input manifests related to customers, suppliers and internal practices necessary for LM implementation, coupled with a similar exhaustive list of the benefits accrued from its successful implementation. A structural model is thus conceptualized, which is empirically validated based on the data from the Indian manufacturing sector. With the current impetus on developing the industrial sector, the Government of India recently introduced the Lean Manufacturing Competitiveness Scheme that aims to increase competitiveness with the help of lean concepts. There is a huge scope to enrich the Indian industries with the lean benefits, the implementation status being quite low. Hardly any survey-based empirical study in India has been found to integrate customers and suppliers with the internal processes towards successful LM implementation. This empirical research is thus carried out in the Indian manufacturing industries. The basic steps of the research methodology followed in this research are the identification of input and output manifest variables and latent constructs, model proposition and hypotheses development, development of survey instrument, sampling and data collection and model validation (exploratory factor analysis, confirmatory factor analysis, and structural equation modeling). The analysis reveals six key input constructs and three output constructs, indicating that these constructs should act in unison to maximize the benefits of implementing lean. The structural model presented in this paper may be treated as a guide to integrating customers and suppliers with internal practices to successfully implement lean. Integrating customers and suppliers with internal practices into a unified, coherent manufacturing system will lead to an optimum utilization of resources. This work is one of the very first researches to have a survey-based empirical analysis of the role of customers, suppliers and internal practices of the Indian manufacturing sector towards an effective lean implementation.

Keywords: customer management, internal manufacturing practices, lean benefits, lean implementation, lean manufacturing, structural model, supplier management

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Filip Stojcevski, Tim Hilditch, Luke Henderson

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Although carbon fibre composites are becoming ever more prominent in the engineering industry, interfacial failure still remains one of the most common limitations to material performance. Carbon fiber surface treatments have played a major role in advancing composite properties however research into the influence of manufacturing variables on a fiber manufacturing line is lacking. This project investigates the impact of altering carbon fiber manufacturing conditions on a production line (specifically electrochemical oxidization and sizing variables) to assess fiber-matrix adhesion. Pristine virgin fibers were manufactured and interfacial adhesion systematically assessed from a microscale (single fiber) to a mesoscale (12k tow), and ultimately a macroscale (laminate). Correlations between interfacial shear strength (IFSS) at each level is explored as a function of known interfacial bonding mechanisms; namely mechanical interlocking, chemical adhesion and fiber wetting. Impact of these bonding mechanisms is assessed through extensive mechanical, topological and chemical characterisation. They are correlated to performance as a function of IFSS. Ultimately this study provides a bottoms up approach to improving composite laminates. By understanding the scaling effects from a singular fiber to a composite laminate and linking this knowledge to specific bonding mechanisms, material scientists can make an informed decision on the manufacturing conditions most beneficial for interfacial adhesion.

Keywords: carbon fibers, interfacial adhesion, surface treatment, sizing

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Authors: M. Pappa, C. Efstathiou, G. Livanos, P. Xidas, D. Vakondios, E. Maravelakis, M. Zervakis, A. Antoniadis

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The choice of cutting tools in manufacturing processes is an essential parameter on which the required manufacturing time, the consumed energy and the cost effort all depend. If the number of tool changing times could be minimized or even eliminated by using a single convex tool providing multiple profiles, then a significant benefit of time and energy saving, as well as tool cost, would be achieved. A typical machine contains a variety of tools in order to deal with different curvatures and material removal rates. In order to minimize the required cutting tool changes, Actively Deformable micro-Cutters (ADmC) will be developed. The design of the Actively Deformable micro-Cutters will be based on the same cutting technique and mounting method as that in typical cutters.

Keywords: deformable cutters, cutting tool, milling, turning, manufacturing

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Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

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Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate

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Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.

Keywords: gears, whine noise, manufacturing variability, mount vibration variability

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Authors: Messis A., Adjebli A., Ayeche R., Talbi M., Tighilet K., Louardiane M.

Abstract:

Cancers are the second cause of death worldwide. Prevalence and incidence of cancers is getting increased by aging and population growth. This study aims to predict and modeling the evolution of breast, Colorectal, Lung, Bladder and Prostate cancers over the period of 2014-2019. In this study, data were analyzed using time series analysis with double exponential smoothing method to forecast the future pattern. To describe and fit the appropriate models, Minitab statistical software version 17 was used. Between 2014 and 2019, the overall trend in the raw number of new cancer cases registered has been increasing over time; the change in observations over time has been increasing. Our forecast model is validated since we have good prediction for the period 2020 and data not available for 2021 and 2022. Time series analysis showed that the double exponential smoothing is an efficient tool to model the future data on the raw number of new cancer cases.

Keywords: cancer, time series, prediction, double exponential smoothing

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Authors: Sastry Y. Kandukuri, Isak Andersen

Abstract:

Despite recent advances in the manufacturing sector, quality issues remain a frequent occurrence, and can result in fatal accidents, equipment downtime, and loss of life. Adequate quality is of high importance in high-risk industries such as sea-going vessels and offshore installations in which third party quality assurance and product control play an important essential role in ensuring manufacturing quality of critical components. Classification societies play a vital role in mitigating risk in these industries by making sure that all the stakeholders i.e. manufacturers, builders, and end users are provided with adequate rules and standards that effectively ensures components produced at a high level of quality based on the area of application and risk of its failure. Quality issues have also been linked to the lack of competence or negligence of stakeholders in supply value chain. However, continued actions and regulatory reforms through modernization of rules and requirements has provided additional tools for purchasers and manufacturers to confront these issues. Included among these tools are updated ‘approval of manufacturer class programs’ aimed at developing and implementing a set of standardized manufacturing quality metrics for use by the manufacturer and verified by the classification society. The establishment and collection of manufacturing and testing requirements described in these programs could provide various stakeholders – from industry to vessel owners – with greater insight into the state of quality at a given manufacturing facility, and allow stakeholders to anticipate better and address quality issues while simultaneously reducing unnecessary failures that are costly to the industry. The publication introduces, explains and discusses critical manufacturing and testing requirements set in a leading class society’s approval of manufacturer regime and its rationale and some case studies.

Keywords: classification society, manufacturing, materials processing, materials testing, quality control

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Authors: Budi Nurani Ruchjana, Atje Setiawan Abdullah, I. Gede Nyoman Mindra Jaya, Eddy Hermawan

Abstract:

In this paper, we propose the application package to estimate parameters of spatiotemporal model based on the multivariate time series analysis using the R open-source software. We build packages mainly to estimate the parameters of the Generalized Space Time Autoregressive (GSTAR) model. GSTAR is a combination of time series and spatial models that have parameters vary per location. We use the method of Ordinary Least Squares (OLS) and use the Mean Average Percentage Error (MAPE) to fit the model to spatiotemporal real phenomenon. For case study, we use oil production data from volcanic layer at Jatibarang Indonesia or climate data such as rainfall in Indonesia. Software R is very user-friendly and it is making calculation easier, processing the data is accurate and faster. Limitations R script for the estimation of model parameters spatiotemporal GSTAR built is still limited to a stationary time series model. Therefore, the R program under windows can be developed either for theoretical studies and application.

Keywords: GSTAR Model, MAPE, OLS method, oil production, R software

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Authors: Raed El-Khalil, Hussein Zeaiter

Abstract:

Managing and improving efficiency in the current highly competitive global automotive industry demands that companies adopt leaner and more flexible systems. During the past 20 years the domestic automotive industry in North America has been focusing on establishing new management strategies in order to meet market demands. 98The lean management process also known as Toyota Manufacturing Process (TPS) or lean manufacturing encompasses tools and techniques that were established in order to provide the best quality product with the fastest lead time at the lowest cost. The following paper presents a study that focused on improving labor efficiency at one of the Big Three (Ford, GM, Chrysler LLC) domestic automotive facility in North America. The objective of the study was to utilize several lean management tools in order to optimize the efficiency and utilization levels at the “Pre-Marriage” chassis area in a truck manufacturing and assembly facility. Utilizing three different lean tools (i.e. Standardization of work, 7 Wastes, and 5S) this research was able to improve efficiency by 51%, utilization by 246%, and reduce operations by 14%. The return on investment calculated based on the improvements made was 284%.

Keywords: lean manufacturing, standardized work, operation efficiency, utilization

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Authors: Seyedvahid Najafi, Viliam Makis

Abstract:

In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems

Procedia PDF Downloads 94