World Academy of Science, Engineering and Technology

Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 114

Authors: Irina Canco, Amela Malaj

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It is evident that there exists a relationship between supply chain management and business performance. Surveys have showed that in many cases the manager's beliefs and expectations on supply chain management do not match the reality of the business. In this context, the study of supply chain issues is of particular importance and interest considering specifically the current period. The economic problems of this period, are present in Albania as well. The complexity of the supply chain focuses on order fulfilment. Therefore, in this paper, attention will be paid to the impact of supply chain management on business performance. The objective of the paper is to find a relationship between the good supply chain management and business performance. This research is based on the results of surveys referring to the experience of successful businesses on issues related to sustainable supply chain management and its synchronization with the provision of products and services required by the final customers. This study clearly evidenced the impact of the speed of meeting customer requirements on AMAZONA performance. This was also confirmed mathematically through one of the decision criteria in conditions of uncertainty—Laplace criterion.

Keywords: supply chain management, AMAZONA, business performance, Laplace criteria

Procedia PDF Downloads 132

Authors: Tamer E. Yared

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The use of driving simulators has made laboratory testing easier. It has been proven to be valid for testing driving ability by many researchers. One benefit of using driving simulators is keeping the human subjects away from traffic hazards, which drivers usually face in a real driving environment while performing a driving experiment. In this study, a driving simulator was developed with a navigation system using a game development software (Unity 3D) and C-sharp codes to measure and evaluate driving performance, safety, and workload for different driving tasks. The driving simulator hardware included a gaming steering wheel and pedals as well as a monitor to view the driving tasks. Moreover, driver distraction was evaluated by utilizing an eye-tracking system working in conjunction with the driving simulator. Twenty subjects were recruited to evaluate driver distraction, workload, driving safety, and performance, as well as provide their feedback about the driving simulator. The subjects’ feedback was obtained by filling a survey after conducting several driving tasks. The main question of that survey was asking the subjects to compare driving on the driving simulator with real driving. Furthermore, other aspects of the driving simulator were evaluated by the subjects in the survey. The survey revealed that the recruited subjects gave an average score of 7.5 out of 10 to the driving simulator when compared to real driving, where the scores ranged between 6 and 8.5. This study is a preliminary effort that opens the door for more improvements to the driving simulator in terms of hardware and software development, which will contribute significantly to driving ability testing.

Keywords: driver distraction, driving performance, driving safety, driving simulator, driving workload, navigation system

Procedia PDF Downloads 138

Authors: Yiqiang Ni, Xuanlong Chen, Enliang Li, Linting Zheng, Shizheng Yang

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Bipolar ICs are playing an important role in military applications, mainly used in logic gates, such as inverter and NAND gate. The defect of metal break located on the step is one of the main failure mechanisms of bipolar ICs, resulting in open-circuit or functional failure. In this situation, general failure localization methods like optical beam-induced resistance change (OBIRCH) and photon emission microscopy (PEM) might not be fully effective. However, active voltage contrast (AVC) can be used as a voltage probe, which may pinpoint the incorrect potential and thus locate the failure position. Two case studies will be present in this paper on how to implement AVC for failure localization, and the detailed failure mechanism will be discussed.

Keywords: bipolar IC, failure localization, metal break, open failure, voltage contrast

Procedia PDF Downloads 255

Authors: Abdullah Faqihi, John Hedley

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Biosensors play a significant role in the healthcare sectors, scientific and technological progress. Developing electrodes that are easy to manufacture and deliver better electrochemical performance is advantageous for diagnostics and biosensing. They can be implemented extensively in various analytical tasks such as drug discovery, food safety, medical diagnostics, process controls, security and defence, in addition to environmental monitoring. Development of biosensors aims to create high-performance electrochemical electrodes for diagnostics and biosensing. A biosensor is a device that inspects the biological and chemical reactions generated by the biological sample. A biosensor carries out biological detection via a linked transducer and transmits the biological response into an electrical signal; stability, selectivity, and sensitivity are the dynamic and static characteristics that affect and dictate the quality and performance of biosensors. In this research, a developed experimental study for laser scribing technique for graphene oxide inside a vacuum chamber for processing of graphene oxide is presented. The processing of graphene oxide (GO) was achieved using the laser scribing technique. The effect of the laser scribing on the reduction of GO was investigated under two conditions: atmosphere and vacuum. GO solvent was coated onto a LightScribe DVD. The laser scribing technique was applied to reduce GO layers to generate rGO. The micro-details for the morphological structures of rGO and GO were visualised using scanning electron microscopy (SEM) and Raman spectroscopy so that they could be examined. The first electrode was a traditional graphene-based electrode model, made under normal atmospheric conditions, whereas the second model was a developed graphene electrode fabricated under a vacuum state using a vacuum chamber. The purpose was to control the vacuum conditions, such as the air pressure and the temperature during the fabrication process. The parameters to be assessed include the layer thickness and the continuous environment. Results presented show high accuracy and repeatability achieving low cost productivity.

Keywords: laser scribing, lightscribe DVD, graphene oxide, scanning electron microscopy

Procedia PDF Downloads 91

Authors: Sitrapee Changmuenwai, Sudaratana Wongweragiat

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It is important that a dry chemical fire extinguisher must be inspected for its readiness. For each inspection, the inspectors need to turn the fire extinguisher tank upside down to let the chemical inside the tank move and prevent solidification, which would make the tank not ready for usage when needed. Each tank weighs approximately 16 kg. The inspectors have to turn each tank upside down twice (2 minutes/round). They need to put the tanks over their shoulder close to their ear in order to hear the chemical flow inside the tank or use their hands to feel it. The survey and questionnaire 'The Questionnaire Know Body', which includes neck, left shoulder, upper and lower right arms suggest that all 12 security staffs have the same fatigues. The current dry chemical fire extinguisher inspection affects various ergonomic health problems. Rapid Entire Body Assessment (REBA) is used for evaluation of posture risks so that the working postures may be redesigned or corrected. The dry chemical fire extinguisher inspection equipment has been developed to reduce ergonomic health risks for the inspectors. A REBA analysis has been performed again, and the risk score has been decreased from 13 to 3. In addition, feedbacks from the first trial of the developed equipment show that there are demands to increase the installation in order to reduce the ergonomic health risks.

Keywords: dry chemical fire extinguisher inspection equipment, ergonomic, REBA, rapid entire body assessment

Procedia PDF Downloads 99

Authors: Sara A. Pakvis, Giulia Scalet, Stefania Marconi, Ferdinando Auricchio, Matthijs Langelaar

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In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape-memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the deliberate introduction of prestresses in the specimen during manufacturing, and, in combination with the right design, this enables new functionalities. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced glass transition in one material lowering its Young’s modulus, combined with an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, which results in the realization of an essentially pre-programmed deformation. As the design of such functional multi-material structures is crucial but far from trivial, a systematic methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. Specific aspects that are addressed include the interplay between the definition of the prestress and the material interpolation function used in the density-based topology description, the inclusion of a temperature-dependent stiffness relationship to simulate the glass transition effect, and the importance of the consideration of geometric nonlinearity in the finite element modeling. The efficacy of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems, both in 2D and 3D settings. Bi-layer designs composed of thermoplastic polymers are printed by means of the fused deposition modeling (FDM) technology. Acrylonitrile butadiene styrene (ABS) polymer undergoes the glass transition transformation, while polyurethane (TPU) polymer is prestressed by means of the 3D-printing process itself. Tests inducing shape transformation in the printed samples through heating are performed to calibrate the prestress and validate the modeling approach by comparing the numerical results to the experimental findings. Using the experimentally obtained prestress values, more complex designs have been generated through topology optimization, and samples have been printed and tested to evaluate their performance. This study demonstrates that by combining topology optimization and 4D-printing concepts, stimuli-responsive structures with specific properties can be designed and realized.

Keywords: 4D-printing, glass transition, shape memory polymer, topology optimization

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Authors: Steve Fish, Chris Lambert

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Cumbria is a geo-political county in Northwest England within which the Lake District National Park, a UNESCO World Heritage site is located. Whilst the area has a formidable reputation for natural beauty and historic assets, the innovation ecosystem is described as ‘patchy’ for a number of reasons. The county is one of the largest in England by area and is sparsely populated. This paper describes the needs, development and delivery of an SME business-support programme funded by the European Regional Development Fund, Lancaster University and the University of Cumbria. The Cumbria Innovations Platform (CUSP) Project has been designed to respond to the nuanced needs of SMEs in this locale, whilst promoting the adoption of research and innovation. CUSP utilizes a funnel method to support rural businesses with access to university innovation intervention. CUSP has been built on a three-tier model: Communicate, Collaborate and Create. The paper describes this project in detail and presents results in terms of output indicators achieved, a beneficiary telephone survey and wider economic forecasts. From a pragmatic point-of-view, the paper provides experiences and reflections of those people who are delivering and evaluating knowledge exchange. The authors discuss some of the benefits, challenges and implications for both policy makers and practitioners. Finally, the paper aims to serve as an invitation to others who may consider adopting a similar method of university-industry collaboration in their own region.

Keywords: regional business support, rural business support, university-industry collaboration, collaborative R&D, SMEs, knowledge exchange

Procedia PDF Downloads 99

Authors: Jiayuan Wu. Lu Hu

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With the development of the sharing economy and mobile technology, carsharing becomes more popular. In this paper, we focus on the joint optimization of one-way station-based carsharing systems. We model the problem as an integer linear program with six elements: station locations, station capacity, fleet size, initial vehicle allocation, vehicle relocation, and demand selection. A greedy-based heuristic is proposed to address the model. Firstly, initialization based on the location variables relaxation using Gurobi solver is conducted. Then, according to the profit margin and demand satisfaction of each station, the number of stations is downsized iteratively. This method is applied to real data from Chengdu, Sichuan taxi data, and it’s efficient when dealing with a large scale of candidate stations. The result shows that with vehicle relocation and demand selection, the profit and demand satisfaction of carsharing systems are increased.

Keywords: one-way carsharing, location, vehicle relocation, demand selection, greedy algorithm

Procedia PDF Downloads 100

Authors: Guilherme Baldo Carlos

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The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving.

Keywords: genetic algorithm, evolutionary algorithm, scheduling, flexible job-shop scheduling

Procedia PDF Downloads 117

Authors: Xia Luo, Cheng Zeng

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Under the promotion of the Central Committee of the Communist Party of China and the State Council in 2017, Xiong'an New Area is the third crucial new area in China established after Shenzhen and Shanghai. Its constructions' significance lies in mitigating Beijing's non-capital functions and exploring a new mode of optimizing development in densely populated and economically intensive areas. For this purpose, developing underground logistics can assume the role of goods distribution in the capital, relieve the road transport pressure in Beijing-Tianjin-Hebei Urban Agglomeration, adjust and optimize the urban layout and spatial structure of it. Firstly, the construction planning of Xiong'an New Area and underground logistics development are summarized, especially the development status abroad, the development trend, and bottlenecks of underground logistics in China. This paper explores the technicality, feasibility, and necessity of four modes of transportation. There are pneumatic capsule pipeline (PCP) technology, the CargoCap technology, cable hauled mule, and automatic guided vehicle (AGV). The above technical parameters and characteristics are introduced to relevant experts or scholars. Through establishing an indicator system, carrying out a questionnaire survey with the Delphi method, the final suggestion is obtained: China should develop logistics vehicles similar to CargoCap, adopting rail mode and driverless mode. Based on China's temporal and spatial logistics demand and the geographical pattern of Xiong'an New Area, the construction scale, technical parameters, node location, and other vital parameters of underground logistics are planned. In this way, we hope to speed up the new area's construction and the logistics industry's innovation.

Keywords: the Xiong'an new area, underground logistics, contrastive analysis, CargoCap, logistics planning

Procedia PDF Downloads 101

Authors: Yingqi Cui, Changran Huang, Raymond Lee

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In this paper, we proposed an AI Tutor using ontology and natural language process techniques to generate a computer science domain knowledge graph and answer users’ questions based on the knowledge graph. We define eight types of relation to extract relationships between entities according to the computer science domain text. The AI tutor is separated into two agents: learning agent and Question-Answer (QA) agent and developed on JADE (a multi-agent system) platform. The learning agent is responsible for reading text to extract information and generate a corresponding knowledge graph by defined patterns. The QA agent can understand the users’ questions and answer humans’ questions based on the knowledge graph generated by the learning agent.

Keywords: artificial intelligence, natural Language processing, knowledge graph, intelligent agents, QA system

Procedia PDF Downloads 145

Authors: Diana Flores Galindo, Richard Gil Herrera

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Nowadays, Lean Manufacturing and Industry 4.0 are very important in every country. One of the main benefits is continued market presence. It has been identified that there is a need to change existing educational programs, as well as update the knowledge and skills of existing employees. It should be borne in mind that behind each technological improvement, there is a human being. Human talent cannot be neglected. The main objectives of this article are to review the link between Lean Manufacturing, the incorporation of Industry 4.0 and the steps to follow to implement it; analyze the current situation and study the implications and benefits of this new trend, with a particular focus on Mexico. Lean Manufacturing and Industry 4.0 implementation waves must always take care of the most important capital – intellectual capital. The methodology used in this article comprised the following steps: reviewing the reality of the fourth industrial revolution, reviewing employees’ skills on the journey to become world-class, and analyzing the situation in Mexico. Lean Manufacturing and Industry 4.0 were studied not as exclusive concepts, but as complementary ones. The methodological framework used is focused on motivating companies’ collaborators to guarantee common results, innovate, and remain in the market in the face of new requirements from company stakeholders. The key findings were that both trends emphasize the need to improve communication across the entire company and incorporate new technologies into everyday work, from the shop floor to administrative staff, to help improve processes. Taking care of people, activities and processes will bring a company success. In the specific case of Mexico, companies in all sectors need to be aware of and implement technological improvements according to their specific needs. Low-cost labor represents one of the most typical barriers. In conclusion, companies must build a roadmap according to their strategy and needs to achieve their short, medium- and long-term goals.

Keywords: lean management, lean manufacturing, industry 4.0, motivation, SWOT analysis, Hoshin Kanri

Procedia PDF Downloads 119

Authors: Niyanta Mehra, Aakriti Khurania, Kshitij Rastogi, S. K. Garg

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There is plenty of literature available that accounts for complexity management in a supply chain. A major fraction of this literature considers a large number of parameters in order to devise management techniques. However, multiple such parameters do not directly affect the result, and incorporating these can make the analyses overly complicated. Most of the causes of supply chain inefficiencies are due to the interconnectedness and interdependencies in the structure, processes, and environment of the supply chains. The level of complexity varies across industries in terms of intensity and ease of management. After a review of the literature related to complexities in supply chains, the paper attempts to build a framework to study the relative significance of these complexities. This paper aims to identify critical complexities for the garment industry. Understanding and controlling these complexities open avenues for better supply chain management and also assist decision-makers in the garment industry in formulating risk mitigation strategies.

Keywords: complexity dimensions, garment industry, supply chain complexity, supply chain management

Procedia PDF Downloads 117

Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

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Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

Procedia PDF Downloads 117

Authors: Erika Tatiana Ruiz, Wilson Adarme Jaimes

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This abstract presents the methodology for improving the logistics processes of agricultural production units belonging to the coffee, cocoa, and fruit sectors, starting from the fundamental concepts and detailing each of the phases to carry out the diagnosis, which will be the basis for the formulation of its action plan and implementation of the maturity model. As a result of this work, the maturity model is formulated to improve logistics processes. This model seeks to: generate a progressive model that is useful for all productive units belonging to these sectors at the national level, regardless of their initial conditions, focus on the improvement of logistics processes as a strategy that contributes to improving the competitiveness of the agricultural sector in Colombia and spread the implementation of good logistics practices in postharvest in all departments of the country through autonomous tools. This model has been built through a series of steps that allow the evaluation and improvement of the logistics dimensions or indicators. The potential improvements for each dimension provide the foundation on which to advance to the next level. Within the maturity model, a methodology is indicated for the design and execution of strategies to improve its logistics processes, taking into account the current state of each production unit.

Keywords: agroindustrial, characterization, logistics, maturity model, processes

Procedia PDF Downloads 113

Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

Procedia PDF Downloads 144

Authors: Tarek Fatouh, Chehab Elbelehy, Alaa Abdelsalam, Eman Elakkad, Alaa Abdelshafie

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This paper aims to explore the possibility of time compression in Engineer to Order production networks. A case study research method is used in a Norwegian shipbuilding project by implementing a value stream mapping lean tool with total cycle time as a unit of analysis. The analysis resulted in demonstrating the time deviations for the planned tasks in one of the processes in the shipbuilding project. So, authors developed a future state map by removing time wastes from value stream process.

Keywords: engineer to order, total cycle time, value stream mapping, shipbuilding

Procedia PDF Downloads 124

Authors: Chetra Mang, Ahmadali Tahmasebimoradi, Xavier Lorang

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Lattice structures are widely used in various applications, especially in aeronautic, aerospace, and medical applications because of their high performance properties. Thanks to advancement of the additive manufacturing technology, the lattice structures can be manufactured by different methods such as laser beam melting technology. However, the presence of geometric defects in the lattice structures is inevitable due to the manufacturing process. The geometric defects may have high impact on the mechanical strength of the structures. This work analyzes the correlation between the manufacturing parameters and the mechanical strengths of the lattice structures. To do that, two types of the lattice structures; body-centered cubic with z-struts (BCCZ) structures made of Inconel718, and body-centered cubic (BCC) structures made of Scalmalloy, are manufactured by laser melting beam machine using Taguchi design of experiment. Each structure is placed on the substrate with a specific position and orientation regarding the roller direction of deposed metal powder. The position and orientation are considered as the manufacturing parameters. The geometric defects of each beam in the lattice are characterized and used to build the geometric model in order to perform simulations. Then, the mechanical strengths are defined by the homogeneous response as Young's modulus and yield strength. The distribution of mechanical strengths is observed as a function of manufacturing parameters. The mechanical response of the BCCZ structure is stretch-dominated, i.e., the mechanical strengths are directly dependent on the strengths of the vertical beams. As the geometric defects of vertical beams are slightly changed based on their position/orientation on the manufacturing substrate, the mechanical strengths are less dispersed. The manufacturing parameters are less influenced on the mechanical strengths of the structure BCCZ. The mechanical response of the BCC structure is bending-dominated. The geometric defects of inclined beam are highly dispersed within a structure and also based on their position/orientation on the manufacturing substrate. For different position/orientation on the substrate, the mechanical responses are highly dispersed as well. This shows that the mechanical strengths are directly impacted by manufacturing parameters. In addition, this work is carried out to study the uncertainty propagation of the geometric defects on the mechanical strength of the BCC lattice structure made of Scalmalloy. To do that, we observe the distribution of mechanical strengths of the lattice according to the distribution of the geometric defects. A probability density law is determined based on a statistical hypothesis corresponding to the geometric defects of the inclined beams. The samples of inclined beams are then randomly drawn from the density law to build the lattice structure samples. The lattice samples are then used for simulation to characterize the mechanical strengths. The results reveal that the distribution of mechanical strengths of the structures with the same manufacturing parameters is less dispersed than one of the structures with different manufacturing parameters. Nevertheless, the dispersion of mechanical strengths due to the structures with the same manufacturing parameters are unneglectable.

Keywords: geometric defects, lattice structure, mechanical strength, uncertainty propagation

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Authors: Jesus Kombaya, Nadia Hamani, Lyes Kermad

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The preservation of a company’s place on the market in such aggressive competition is becoming a survival challenge for manufacturers. In this context, survivors are only those who succeed to satisfy their customers’ needs as quickly as possible. The production system should be endowed with a certain level of flexibility to eliminate or reduce the rigidity of the production systems in order to facilitate the conversion and/or the change of system’s features to produce different products. Therefore, it is essential to guarantee the quality, the speed and the flexibility to survive in this competition. According to literature, this adaptability is referred to as the notion of "change". Indeed, companies are trying to establish a more flexible and agile manufacturing system through several reconfiguration actions. Reconfiguration contributes to the extension of the manufacturing system life cycle by modifying its physical, organizational and computer characteristics according to the changing market conditions. Reconfigurability is characterized by six key elements that are: modularity, integrability, diagnosability, convertibility, scalability and customization. In order to control the production systems, it is essential for manufacturers to make good use of this capability in order to be sure that the system has an optimal and adapted level of reconfigurability that allows it to produce in accordance with the set requirements. This document develops a measure of customization of reconfigurable production systems. These measures do not only impact the production system but also impact the product design and the process design, which can therefore serve as a guide for the customization of manufactured product. A case study is presented to show the use of the proposed approach.

Keywords: reconfigurable manufacturing systems, customization, measure, flexibility

Procedia PDF Downloads 99

Authors: Yinan Cao, Francine Herrmann

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Adversary emulation is a very effective concrete way to evaluate the defense of an information system or network. It is about building an emulator, which depending on the vulnerability of a target system, will allow to detect and execute a set of identified attacks. However, emulating an adversary is very costly in terms of time and resources. Verifying the information of each technique and building up the countermeasures in the middle of the test is also needed to be accomplished manually. In this article, a synthesis of previous MITRE research on the creation of the ATT&CK matrix will be as the knowledge base of the known techniques and a well-designed adversary emulation software CALDERA based on ATT&CK Matrix will be used as our platform. Inspired and guided by the previous study, a plugin in CALDERA called Tinker will be implemented, which is aiming to help the tester to get more information and also the mitigation of each technique used in the previous operation. Furthermore, the optional countermeasures for some techniques are also implemented and preset in Tinker in order to facilitate and fasten the process of the defense improvement of the tested system.

Keywords: automation, adversary emulation, CALDERA, countermeasures, MITRE ATT&CK

Procedia PDF Downloads 177

Authors: Raphael Palucci Rosa, Giuseppe Rosace

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Stereolithography (SLA) is one of the 3D-printing technologies that has been steadily growing in popularity for both industrial and personal applications due to its versatility, high accuracy, and low cost. Its printing process consists of using a light emitter to solidify photosensitive liquid resins layer-by-layer to produce solid objects. However, the majority of the resins used in SLA are derived from petroleum and characterized by toxicity, stability, and recalcitrance to degradation in natural environments. Aiming to develop an eco-friendly resin, in this work, different combinations of a standard commercial SLA resin (Peopoly UV professional) with a vegetable-based resin were investigated. To reach this goal, different mass concentrations (varying from 10 to 50 wt%) of acrylated epoxidized soybean oil (AESO), a vegetable resin produced from soyabean oil, were mixed with a commercial acrylate-based resin. 1.0 wt% of Diphenyl(2,4,6-trimethylbenzoyl) phosphine oxide (TPO) was used as photo-initiator, and the samples were printed using a Peopoly moai 130. The machine was set to operate at standard configurations when printing commercial resins. After the print was finished, the excess resin was drained off, and the samples were washed in isopropanol and water to remove any non-reacted resin. Finally, the samples were post-cured for 30 min in a UV chamber. FT-IR analysis was used to confirm the UV polymerization of the formulated resin with different AESO/Peopoly ratios. The signals from 1643.7 to 1616, which corresponds to the C=C stretching of the AESO acrylic acids and Peopoly acrylic groups, significantly decreases after the reaction. The signal decrease indicates the consumption of the double bonds during the radical polymerization. Furthermore, the slight change of the C-O-C signal from 1186.1 to 1159.9 decrease of the signals at 809.5 and 983.1, which corresponds to unsaturated double bonds, are both proofs of the successful polymerization. Mechanical analyses showed a decrease of 50.44% on tensile strength when adding 10 wt% of AESO, but it was still in the same range as other commercial resins. The elongation of break increased by 24% with 10 wt% of AESO and swelling analysis showed that samples with a higher concentration of AESO mixed absorbed less water than their counterparts. Furthermore, high-resolution prototypes were printed using both resins, and visual analysis did not show any significant difference between both products. In conclusion, the AESO resin was successful incorporated into a commercial resin without affecting its printability. The bio-based resin showed lower tensile strength than the Peopoly resin due to network loosening, but it was still in the range of other commercial resins. The hybrid resin also showed better flexibility and water resistance than Peopoly resin without affecting its resolution. Finally, the development of new types of SLA resins is essential to provide new sustainable alternatives to the commercial petroleum-based ones.

Keywords: 3D-printing, bio-based, resin, soybean, stereolithography

Procedia PDF Downloads 104

Authors: Xavier Lorang, Ahmadali Tahmasebimoradi, Chetra Mang, Sylvain Girard

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The additive manufacturing processes (e.g. selective laser melting) allow us to produce lattice structures which have less weight, higher impact absorption capacity, and better thermal exchange property compared to the classical structures. Unfortunately, geometric imperfections (defects) in the lattice structures are by-products results of the manufacturing process. These imperfections decrease the lifetime and the strength of the lattice structures and alternate their mechanical responses. The objective of the paper is to present a simulation strategy which allows us to take into account the effect of the geometric imperfections on the mechanical response of the lattice structure. In the first part, an identification method of geometric imperfection parameters of the lattice structure based on point clouds is presented. These point clouds are based on tomography measurements. The point clouds are fed into the platform LATANA (LATtice ANAlysis) developed by IRT-SystemX to characterize the geometric imperfections. This is done by projecting the point clouds of each microbeam along the beam axis onto a 2D surface. Then, by fitting an ellipse to the 2D projections of the points, the geometric imperfections are characterized by introducing three parameters of an ellipse; semi-major/minor axes and angle of rotation. With regard to the calculated parameters of the microbeam geometric imperfections, a statistical analysis is carried out to determine a probability density law based on a statistical hypothesis. The microbeam samples are randomly drawn from the density law and are used to generate lattice structures. In the second part, a finite element model for the lattice structure with the simplified geometric imperfections (ellipse parameters) is presented. This numerical model is used to simulate the generated lattice structures. The propagation of the uncertainties of geometric imperfections is shown through the distribution of the computed mechanical responses of the lattice structures.

Keywords: additive manufacturing, finite element model, geometric imperfections, lattice structures, propagation of uncertainty

Procedia PDF Downloads 161

Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

Abstract:

Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

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Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: additive manufacturing, decision-makings, environmental impact, predictive models

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Authors: Marie E. Docken

Abstract:

At some point in the lifecycle of a country, patterns of political and social unrest of varying degrees are observed. Events involving public disorder or civil disobedience may produce effects that range a wide spectrum of varying outcomes, depending on the level of unrest. Many previous studies, primarily theoretical in nature, have attempted to measure public disorder in answering why or how it occurs in society by examining causal factors or underlying issues in the social or political position of a population. The main objective in doing so is to understand how these activities evolve or seek some predictive capability for the events. In contrast, this research involves the fusion of analytics and social studies to provide more knowledge of the public disorder and civil disobedience intensity in populations. With a greater understanding of the magnitude of these events, it is believed that we may learn how they relate to extreme actions such as mass migration or violence. Upon establishing a model for measuring civil unrest based upon empirical data, a case study on various Latin American countries is performed. Interpretations of historical events are combined with analytical results to provide insights regarding the magnitude and effect of social and political activism.

Keywords: public disorder, civil disobedience, Latin America, metrics, data analysis

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Authors: Shu-Yen Wang, Shyh-Huei Hwang

Abstract:

Designated as an important architectural complex of settlement by the Ministry of Culture, Hua-Zhai Settlement located in Wang-An Township, Peng-Hu County, of Taiwan has been progressively restored year by year and is now at the revitalization and reutilization stage. Over the last 5 years, YunTech has participated in the restoration project while being in compliance with the Bureau of Cultural Heritage’s spirit of 'Living Heritage Conservation'. In this study, reflections have been made to evaluate the contemporariness of traditional settlement development from the aspects of revitalization and reutilization. On the one hand, the connection between settlers’ experiences and emotions have been clarified through the living nodes, collective memory, and social-cultural connotation. On the other hand, activity design has promoted the reconstruction of living nodes and facilitated the reconnection of collective memory, enabling us to explore the contemporariness of living nodes after the reconstruction. With the adoption of literature review, participant observation, and interview analysis methods, this study concludes the following results: 1) The node reconstruction brings back the memories and makes emotional connections: the spatial collective memory is composed of different components. During the reconstruction of node space, villagers participated not only in the narration of the history but also in the restoration of the space. This process enables villagers to bring back their memories and make emotional connections thereto. 2) Villagers’ understanding towards revitalization has been facilitated through node reconstruction: as a medium of this project, activity design has facilitated node reconstruction by offering villagers a natural environment to build up emotional connections to the settlement. This also enables us to better understand the meaning of settlement activation for the local community. 3) New connections are established in life between villagers and the university through the construction of living nodes: through the local implementation of node reconstruction, new connections have been established in life between villagers who participated in the project and the university. In the meantime, the university’s entrance to the community has also been revalued.

Keywords: collective memory, local sense of belonging, reconstruction of living nodes, the important architectural complex of Wang-An Hua-Zhai settlement

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Authors: Ahmed Barakat, Nourhan Ahmed Saad, Mahmoud Hammad

Abstract:

Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: agriculture sector, cold chain management, export companies, non-traded goods, supply chain management

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Authors: Zhaoan Wang

Abstract:

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: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

Abstract:

Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

Procedia PDF Downloads 147