World Academy of Science, Engineering and Technology

Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

Procedia PDF Downloads 141

Authors: Dylan Santos De Pinho, Arnaud Gay De Combes, Matthieu Steuhlet, Claude Jeannerat, Nabil Ouerhani

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The Industry 4.0 initiative has been launched to address huge challenges related to ever-smaller batch sizes. The end-user need for highly customized products requires highly adaptive production systems in order to keep the same efficiency of shop floors. Most of the classical Software solutions that operate the manufacturing processes in a shop floor are based on rigid Manufacturing Execution Systems (MES), which are not capable to adapt the production order on the fly depending on changing demands and or conditions. In this paper, we present a highly modular and flexible solution to orchestrate a set of production systems composed of a micro-milling machine-tool, a polishing station, a cleaning station, a part inspection station, and a rough material store. The different stations are installed according to a novel matrix configuration of a 3x3 vertical shelf. The different cells of the shelf are connected through horizontal and vertical rails on which a set of shuttles circulate to transport the machined parts from a station to another. Our software solution for orchestrating the tasks of each station is based on a Multi-Agent System. Each station and each shuttle is operated by an autonomous agent. All agents communicate with a central agent that holds all the information about the manufacturing order. The core innovation of this paper lies in the path planning of the different shuttles with two major objectives: 1) reduce the waiting time of stations and thus reduce the cycle time of the entire part, and 2) reduce the disturbances like vibration generated by the shuttles, which highly impacts the manufacturing process and thus the quality of the final part. Simulation results show that the cycle time of the parts is reduced by up to 50% compared with MES operated linear production lines while the disturbance is systematically avoided for the critical stations like the milling machine-tool.

Keywords: multi-agent systems, micro-manufacturing, flexible manufacturing, transfer systems

Procedia PDF Downloads 122

Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

Procedia PDF Downloads 132

Authors: Nadhifah A. Nugraha, Dida D. Damayanti, Widia Juliani

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Airplanes manufacturing is growing along with the increasing demand from consumers. The helicopter's tail called Tailboom is a product of the helicopter division at XYZ Corp, where the Tailboom assembly line is a pull system. Based on observations of existing conditions that occur at XYZ Corp, production is still unable to meet the demands of consumers; lead time occurs greater than the plan agreed upon by the consumers. In the assembly process, each work station experiences a lack of parts and components needed to assemble components. This happens because of the delay in getting the required part information, and there is no warning about the availability of parts needed, it makes some parts unavailable in assembly warehouse. The lack of parts and components from the previous work station causes the assembly process to stop, and the assembly line also stops at the next station. In its completion, the production time was late and not on the schedule. In resolving these problems, the controlling process is needed, which is controlling the assembly line to get all components and subassembly in the right amount and at the right time. This study applies one of Just In Time tools, namely Kanban and automation, should be added as efficiently and effectively communication line becomes electronic Kanban. The problem can be solved by reducing non-value added time, such as waiting time and idle time. The proposed results of controlling the assembly line of Tailboom result in a smooth assembly line without waiting, reduced lead time, and achieving production time according to the schedule agreed with the consumers.

Keywords: kanban, e-Kanban, lead time, pull system

Procedia PDF Downloads 102

Authors: Vojo George Fasinu, Nadaraj Govender, Predeep Kumar

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An Antenna, which remains the hub of technological development in Africa had been found to be a course that is been taught and designed in an abstract manner in some universities. One of the reasons attached to this is that the appropriate approach of teaching antenna design is not yet understood by many engineering academics in some universities in South Africa. Also, another problem reported is the main difficulty encountered when interpreting and applying some of the mathematical concepts learned into their practical antenna design course. As a result of this, some engineering experts classified antenna as a mysterious technology that could not be described by anybody using mathematical concepts. In view of this, this paper takes it as its point of departure in explaining what an antenna is all about with a strong emphasis on its mathematical modelling. It also argues that the place of modelling mathematical concepts into the teaching of engineering design cannot be overemphasized. Therefore, it explains the mathematical concepts adopted during the teaching of an antenna design course, the Strategies of modelling those mathematics concepts, the behavior of antennas, and their mathematics usage were equally discussed. More so, the paper also sheds more light on mathematical modelling in South Africa context, and also comparative analysis of mathematics concepts taught in mathematics class and mathematics concepts taught in engineering courses. This paper focuses on engineering academics teaching selected topics in electronic engineering (Antenna design), with special attention on the mathematical concepts they teach and how they teach them when teaching the course. A qualitative approach was adopted as a means of collecting data in order to report the naturalistic views of the engineering academics teaching Antenna design. The findings of the study confirmed that some mathematical concepts are being modeled into the teaching of an antenna design with the adoption of some teaching approaches. Furthermore, the paper reports a didactical-realistic mathematical model as a conceptual framework used by the researchers in describing how academics teach mathematical concepts during their teaching of antenna design. Finally, the paper concludes with the importance of mathematical modelling to the engineering academics and recommendations for further researchers.

Keywords: modelling, mathematical concepts, engineering, didactical, realistic model

Procedia PDF Downloads 176

Authors: Azhar Ulhaq, Zubair Yameen, Almas Anjum

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Frequency behaviour of self-excited induction generator (SEIG) wind turbines during control mode transition from grid connected to islanded mode is studied in detail. A robust control scheme for frequency regulation based on combined action of STATCOM, energy storage system (ESS) and pitch angle control for wind powered microgrid (MG) is proposed. Suggested STATCOM controller comprises a 3-phase voltage source converter (VSC) that contains insulated gate bipolar transistors (IGBTs) based pulse width modulation (PWM) inverters along with a capacitor bank. Energy storage system control consists of current controlled voltage source converter and battery bank. Both of them acting simultaneously after detection of island compensates for reactive and active power demands, thus regulating frequency at point of common coupling (PCC) and also improves load stability. STATCOM integrates at point of common coupling and ESS is connected to microgrids main bus. Results reveal that proposed control not only stabilizes frequency during transition duration but also minimizes sudden frequency imbalance caused by load variation or wind intermittencies in islanded operation. System is investigated with and without suggested control scheme. The efficacy of proposed strategy has been verified by simulation in MATLAB/Simulink.

Keywords: energy storage system, island, wind, STATCOM, self-excited induction generator, SEIG, transient

Procedia PDF Downloads 144

Authors: V. Reyes, P. Ferreira

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In response to high levels of competitiveness, industrial systems have evolved to improve productivity. As a consequence, a rapid increase in volume production and simultaneously, a customization process require lower costs, more variety, and accurate quality of products. Reducing time-cycle production, enabling customizability, and ensure continuous quality improvement are key features in advance intelligent industry. In this scenario, customers and producers will be able to participate in the ongoing production life cycle through real-time interaction. To achieve this vision, transparency, predictability, and adaptability are key features that provide the industrial systems the capability to adapt to customer demands modifying the manufacturing process through an autonomous response and acting preventively to avoid errors. The industrial system incorporates a diversified number of components that in advanced industry are expected to be decentralized, end to end communicating, and with the capability to make own decisions through feedback. The evolving process towards advanced intelligent industry defines a set of stages to empower components of intelligence and enhancing efficiency to achieve the decision-making stage. The integrated system follows an industrial cyber-physical system (CPS) architecture whose real-time integration, based on a set of enabler technologies, links the physical and virtual world generating the digital twin (DT). This instance allows incorporating sensor data from real to virtual world and the required transparency for real-time monitoring and control, contributing to address important features of the advanced intelligent industry and simultaneously improve sustainability. Assuming the industrial CPS as the core technology toward the latest advanced intelligent industry stage, this paper reviews and highlights the correlation and contributions of the enabler technologies for the operationalization of each stage in the path toward advanced intelligent industry. From this research, a real-time integration architecture for a cyber-physical system with applications to collaborative robotics is proposed. The required functionalities and issues to endow the industrial system of adaptability are identified.

Keywords: cyber-physical systems, digital twin, sensor data, system integration, virtual model

Procedia PDF Downloads 107

Authors: S. N. Susenburger, D. Boecker

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In the age of Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), where digital transformation is challenging long standing traditional hardware and manufacturing companies, innovation needs a different methodology, strategy, mindset, and culture. What used to be a mindset of scaling per quantity is now shifting to orchestrating ecosystems, platform business models and service bundles. While large corporations are trying to mimic the nimbleness and versatile mindset of startups in the core of their digital strategies, they’re at the frontier of facing one of the largest organizational and cultural changes in history. This paper elaborates on how a manufacturing giant transformed its Corporate Information Technology (IT) to enable digital and Internet of Things (IoT) business while establishing the mindset and the approaches of the Innovation Inside-Out/Outside-In Strategy. It gives insights into the core elements of an innovation culture and the tactics and methodologies leveraged to support the cultural shift and transformation into an IoT company. This paper also outlines the core elements for an innovation culture and how the persona 'Connected Engineer' thrives in the digital innovation environment. Further, it explores how tapping domain-focused ecosystems in vibrant innovative cities can be used as a part of the strategy to facilitate partner co-innovation. Therefore, findings from several use cases, observations and surveys led to conclusion for the strategy tandem of Innovation Inside-Out/Outside-In. The findings indicate that it's crucial in which phases and maturity level the Innovation Inside-Out/Outside-In Strategy is activated: cultural aspects of the business and the regional ecosystem need to be considered, as well as cultural readiness from management and active contributors. The 'not invented here syndrome' is a barrier of large corporations that need to be addressed and managed to successfully drive partnerships, as well as embracing co-innovation and a mindset shifting away from physical products toward new business models, services, and IoT platforms. This paper elaborates on various methodologies and approaches tested in different countries and cultures, including the U.S., Brazil, Mexico, and Germany.

Keywords: innovation management, innovation culture, innovation methodologies, digital transformation

Procedia PDF Downloads 132

Authors: Harish Kumar Ponnappan, Joseph C. Chen

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The main objective of this research is to optimize the surface roughness of a milling operation on AISI 1018 steel using live tooling on a HAAS ST-20 lathe. In this study, Taguchi analysis is used to optimize the milling process by investigating the effect of different machining parameters on surface roughness. The L₉ orthogonal array is designed with four controllable factors with three different levels each and an uncontrollable factor, resulting in 18 experimental runs. The optimal parameters determined from Taguchi analysis were feed rate – 76.2 mm/min, spindle speed 1150 rpm, depth of cut – 0.762 mm and 2-flute TiN coated high-speed steel as tool material. The process capability Cp and process capability index Cpk values were improved from 0.62 and -0.44 to 1.39 and 1.24 respectively. The average surface roughness values from the confirmation runs were 1.30 µ, decreasing the defect rate from 87.72% to 0.01%. The purpose of this study is to efficiently utilize the Taguchi design to optimize the surface roughness in a milling operation using live tooling.

Keywords: live tooling, surface roughness, taguchi analysis, CNC milling operation, CNC turning operation

Procedia PDF Downloads 132

Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

Procedia PDF Downloads 133

Authors: Amna Batool

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Agile methodology is the current most popular technique in software development projects. Agile methods in software development bring optimistic impact on software performances, quality and customer satisfaction. There are some organizations and small-medium enterprises adopting agile into their local software development projects as well as in distributed software development projects. Adopting agile methods in local software development projects is valuable. However, agile global software deployment needs an attention. There are different key challenges in agile global software development that need to resolve and enhance the global software development cycles. The proposed systematic literature review investigates all key challenges of agile in global software development. Moreover, a quantitative methodology (an actual survey) targeted to present a real case scenario of these particular key challenges faced by one of the software houses that is BestWeb Malaysia. The outcomes of systematic literature and the results of quantitative methodology are compared with each other to evaluate if the key challenges pointed out in systematic review still exist. The proposed research and its exploratory results can assist small medium enterprises to avoid these challenges by adopting the best practices in their global software development projects. Moreover, it is helpful for novice researchers to get valuable information altogether.

Keywords: agile software development, ASD challenges, agile global software development, challenges in agile global software development

Procedia PDF Downloads 150

Authors: Yiwei Huang, Chunyu Zhao, Jingjing Ding

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Electrical Resistivity Tomography has been widely used in the medicine and the geology, such as the imaging of the lung impedance and the analysis of the soil impedance, etc. Linear Back Projection is the core algorithm of Electrical Resistivity Tomography, but the traditional Linear Back Projection can not make full use of the information of the electric field. In this paper, an imaging method of Parallel Electrode Linear Back Projection for Electrical Resistivity Tomography is proposed, which generates the electric field distribution that is not linearly related to the traditional Linear Back Projection, captures the new information and improves the imaging accuracy without increasing the number of electrodes by changing the connection mode of the electrodes. The simulation results show that the accuracy of the image obtained by the inverse operation obtained by the Parallel Electrode Linear Back Projection can be improved by about 20%.

Keywords: electrical resistivity tomography, finite element simulation, image optimization, parallel electrode linear back projection

Procedia PDF Downloads 144

Authors: Ugochukwu Ejike Akpudo, Jank-Wook Hur

Abstract:

The increasing demand for improved productivity, maintainability, and reliability has prompted rapidly increasing research studies on the emerging condition-based maintenance concept- Prognostics and health management (PHM). Varieties of fuel pumps serve critical functions in several hydraulic systems; hence, their failure can have daunting effects on productivity, safety, etc. The need for condition monitoring and assessment of these pumps cannot be overemphasized, and this has led to the uproar in research studies on standard feature extraction techniques for optimized condition assessment of fuel pumps. By extracting time-based, frequency-based and the more robust time-frequency based features from these vibrational signals, a more comprehensive feature assessment (and selection) can be achieved for a more accurate and reliable condition assessment of these pumps. With the aid of emerging deep classification and regression algorithms like the locally linear embedding (LLE), we propose a method for comprehensive condition assessment of electromagnetic fuel pumps (EMFPs). Results show that the LLE as a comprehensive feature extraction technique yields better feature fusion/dimensionality reduction results for condition assessment of EMFPs against the use of single features. Also, unlike other feature fusion techniques, its capabilities as a fault classification technique were explored, and the results show an acceptable accuracy level using standard performance metrics for evaluation.

Keywords: electromagnetic fuel pumps, comprehensive feature extraction, condition assessment, locally linear embedding, feature fusion

Procedia PDF Downloads 111

Authors: Rene Hellmuth, Jorg Frohnmayer

Abstract:

The requirements of the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Even today, the methods and process models used in factory planning are predominantly based on the classical planning principles of Schmigalla, Aggteleky and Kettner, which, however, are not specifically designed for reorganization. In addition, they are designed for a largely static environmental situation and a manageable planning complexity as well as for medium to long-term planning cycles with a low variability of the factory. Existing approaches already regard factory planning as a continuous process that makes it possible to react quickly to adaptation requirements. However, digital factory models are not yet used as a source of information for building data. Approaches which consider building information modeling (BIM) or digital factory models in general either do not refer to factory conversions or do not yet go beyond a concept. This deficit can be further substantiated. A method for factory conversion planning using a current digital building model is lacking. A corresponding approach must take into account both the existing approaches to factory planning and the use of digital factory models in practice. A literature review will be conducted first. In it, approaches to classic factory planning and approaches to conversion planning are examined. In addition, it will be investigated which approaches already contain digital factory models. In the second step, an approach is presented how digital factory models based on building information modeling can be used as a basis for augmented reality tablet applications. This application is suitable for construction sites and provides information on the costs and time required for conversion variants. Thus a fast decision making is supported. In summary, the paper provides an overview of existing factory planning approaches and critically examines the use of digital tools. Based on this preliminary work, an approach is presented, which suggests the sensible use of digital factory models for decision support in the case of conversion variants of the factory building. The augmented reality application is designed to summarize the most important information for decision-makers during a reconstruction process.

Keywords: augmented reality, digital factory model, factory planning, restructuring

Procedia PDF Downloads 132

Authors: Rene Hellmuth

Abstract:

The requirements for the factory planning and the building concerned have changed in the last years. Factory planning has the task of designing products, plants, processes, organization, areas, and the building of a factory. Regular restructuring gains more importance in order to maintain the competitiveness of a factory. Restrictions regarding new areas, shorter life cycles of product and production technology as well as a VUCA (volatility, uncertainty, complexity and ambiguity) world cause more frequently occurring rebuilding measures within a factory. Restructuring of factories is the most common planning case today. Restructuring is more common than new construction, revitalization and dismantling of factories. The increasing importance of restructuring processes shows that the ability to change was and is a promising concept for the reaction of companies to permanently changing conditions. The factory building is the basis for most changes within a factory. If an adaptation of a construction project (factory) is necessary, the inventory documents must be checked and often time-consuming planning of the adaptation must take place to define the relevant components to be adapted, in order to be able to finally evaluate them. The different requirements of the planning participants from the disciplines of factory planning (production planner, logistics planner, automation planner) and industrial construction planning (architect, civil engineer) come together during reconstruction and must be structured. This raises the research question: Which requirements do the disciplines involved in the reconstruction planning place on a digital factory model? A subordinate research question is: How can model-based decision support be provided for a more efficient design of the conversion within a factory? Because of the high adaptation rate of factories and its building described above, a methodology for rescheduling factories based on the requirements engineering method from software development is conceived and designed for practical application in factory restructuring projects. The explorative research procedure according to Kubicek is applied. Explorative research is suitable if the practical usability of the research results has priority. Furthermore, it will be shown how to best use a digital factory model in practice. The focus will be on mobile applications to meet the needs of factory planners on site. An augmented reality (AR) application will be designed and created to provide decision support for planning variants. The aim is to contribute to a shortening of the planning process and model-based decision support for more efficient change management. This requires the application of a methodology that reduces the deficits of the existing approaches. The time and cost expenditure are represented in the AR tablet solution based on a building information model (BIM). Overall, the requirements of those involved in the planning process for a digital factory model in the case of restructuring within a factory are thus first determined in a structured manner. The results are then applied and transferred to a construction site solution based on augmented reality.

Keywords: augmented reality, digital factory model, factory planning, restructuring

Procedia PDF Downloads 121

Authors: R. Hellmuth

Abstract:

The orientation of flexibility and adaptability with regard to factory planning is at machine and process level. Factory buildings are not the focus of current research. Factory planning has the task of designing products, plants, processes, organization, areas and the construction of a factory. The adaptability of a factory can be divided into three types: spatial, organizational and technical adaptability. Spatial adaptability indicates the ability to expand and reduce the size of a factory. Here, the area-related breathing capacity plays the essential role. It mainly concerns the factory site, the plant layout and the production layout. The organizational ability to change enables the change and adaptation of organizational structures and processes. This includes structural and process organization as well as logistical processes and principles. New and reconfigurable operating resources, processes and factory buildings are referred to as technical adaptability. These three types of adaptability can be regarded independently of each other as undirected potentials of different characteristics. If there is a need for change, the types of changeability in the change process are combined to form a directed, complementary variable that makes change possible. When planning adaptability, importance must be attached to a balance between the types of adaptability. The vision of the intelligent factory building and the 'Internet of Things' presupposes the comprehensive digitalization of the spatial and technical environment. Through connectivity, the factory building must be empowered to support a company's value creation process by providing media such as light, electricity, heat, refrigeration, etc. In the future, communication with the surrounding factory building will take place on a digital or automated basis. In the area of industry 4.0, the function of the building envelope belongs to secondary or even tertiary processes, but these processes must also be included in the communication cycle. An integrative view of a continuous communication of primary, secondary and tertiary processes is currently not yet available and is being developed with the aid of methods in this research work. A comparison of the digital twin from the point of view of production and the factory building will be developed. Subsequently, a tool will be elaborated to classify digital twins from the perspective of data, degree of visualization, and the trades. Thus a contribution is made to better integrate the secondary and tertiary processes in a factory into the added value.

Keywords: adaptability, digital factory twin, factory planning, industry 4.0

Procedia PDF Downloads 147

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

Abstract:

Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

Procedia PDF Downloads 148

Authors: Mohd Javaid, Shahbaz Khan, Abid Haleem

Abstract:

Purpose: Large numbers of 3D printing technologies are now available for sophisticated applications in different fields. Additive manufacturing has established its dominance in design, development, and customisation of the product. In the era of developing technologies, there is a need to identify the appropriate technology for different application. In order to fulfil this need, two widely used printing technologies such as Fused Deposition Modeling (FDM), and Binding-Jet 3D Printing are compared for effective utilisation in the current scenario for different applications. Methodology: Systematic literature review conducted for both technologies with applications and associated factors enabling for the same. Appropriate MCDM tool is used to compare critical factors for both the technologies. Findings: Both technologies have their potential and capabilities to provide better direction to the industry. Additionally, this paper is helpful to develop a decision support system for the proper selection of technologies according to their continuum of applications and associated research and development capability. The vital issue is raw materials, and research-based material development is key to the sustainability of the developed technologies. FDM is a low-cost technology which provides high strength product as compared to binding jet technology. Researcher and companies can take benefits of this study to achieve the required applications in lesser resources. Limitations: Study has undertaken the comparison with the opinion of experts, which may not always be free from bias, and some own limitations of each technology. Originality: Comparison between these technologies will help to identify best-suited technology as per the customer requirements. It also provides development in this different field as per their extensive capability where these technologies can be successfully adopted. Conclusion: FDM and binding jet technology play an active role in industrial development. These help to assist the customisation and production of personalised parts cost-effectively. So, there is a need to understand how these technologies can provide these developments rapidly. These technologies help in easy changes or in making revised versions of the product, which is not easily possible in the conventional manufacturing system. High machine cost, the requirement of skilled human resources, low surface finish, and mechanical strength of product and material changing option is the main limitation of this technology. However, these limitations vary from technology to technology. In the future, these technologies are to be commercially viable for efficient usage in direct manufacturing of varied parts.

Keywords: 3D printing, comparison, fused deposition modeling, FDM, binding jet technology

Procedia PDF Downloads 99

Authors: O. A. Adeyemi, M. O. Idris, W. A. Oke, O. T. Olorode, S. O. Alayande, A. E. Adeoye

Abstract:

The purpose of this paper is to investigate the process of capability building at subsidiary level and the challenges to such process. The relevance of external factors for capability development, have not been explicitly addressed in empirical studies. Though, internal factors, acting as enablers, have been more extensively studied. With reference to external factors, subsidiaries are actively influenced by specific characteristics of the host country, implying a need to become fully immersed in local culture and practices. Specifically, in MNCs, there has been a widespread trend in management practice to increase subsidiary autonomy,  with subsidiary managers being encouraged to act entrepreneurially, and to take advantage of host country specificity. As such, it could be proposed that: P1: The degree at which subsidiary management is connected to the host country, will positively influence the capability development process. Dynamic capabilities reside to a large measure with the subsidiary management team, but are impacted by the organizational processes, systems and structures that the MNC headquarter has designed to manage its business. At the subsidiary level, the weight of the subsidiary in the network, its initiative-taking and its profile building increase the supportive attention of the HQs and are relevant to the success of the process of capability building. Therefore, our second proposition is that: P2: Subsidiary role and HQ support are relevant elements in capability development at the subsidiary level. Design/Methodology/Approach: This present study will adopt the multiple case studies approach. That is because a case study research is relevant when addressing issues without known empirical evidences or with little developed prior theory. The key definitions and literature sources directly connected with operations of western subsidiaries in emerging markets, such as China, are well established. A qualitative approach, i.e., case studies of three western subsidiaries, will be adopted. The companies have similar products, they have operations in China, and both of them are mature in their internationalization process. Interviews with key informants, annual reports, press releases, media materials, presentation material to customers and stakeholders, and other company documents will be used as data sources. Findings: Western Subsidiaries in Emerging Market operate in a way substantially different from those in the West. What are the conditions initiating the outsourcing of operations? The paper will discuss and present two relevant propositions guiding that process. Practical Implications: MNCs headquarter should be aware of the potential for capability development at the subsidiary level. This increased awareness could induce consideration in headquarter about the possible ways of encouraging such known capability development and how to leverage these capabilities for better MNC headquarter and/or subsidiary performance. Originality/Value: The paper is expected to contribute on the theme: drivers of subsidiary performance with focus on emerging market. In particular, it will show how some external conditions could promote a capability-building process within subsidiaries.

Keywords: case studies, dynamic capability, emerging market, subsidiary

Procedia PDF Downloads 115

Authors: C. van den Berg, C. Pokpas

Abstract:

Popular discourse touts entrepreneurship as a universal solution for underdevelopment, unemployment, and poverty. Moreover, claims are made that women and other disadvantaged groups can achieve material and personal success through digital entrepreneurship. This paper examines the potential of digital technology in entrepreneurial ventures to stimulate economic growth for marginalized groups and communities. Although digital entrepreneurship is hailed as a means to empower under-resourced and socially marginalized people, these opportunities still exist within the confines of existing social and cultural practices. The perspectives of female digital entrepreneurs in developing countries are sorely understudied, particularly concerning an understanding of the complex underlying socio-cultural factors impeding women’s entrepreneurial behaviors. This qualitative study, guided by a feminist phenomenological perspective, focused on the experiences of digital female entrepreneurs in the Western Cape of South Africa. Data were collected via semi-structured interviews and analyzed through the interpretative phenomenological analysis (IPA) approach to determine the relationships between digital entrepreneurship and structural and agential enabling conditions. Findings show that digital entrepreneurship is not a panacea for economic growth in marginalized groups and communities and highlight the importance of addressing socio-cultural gender inequality to enable successful entrepreneurial activity. The paper concludes with recommendations for specialized training initiatives aimed at female entrepreneurs that address internalized constraints and barriers that keep women subservient and measures to shift gender and power beliefs. The outcome will benefit the stimulation of gender-specific public policies to develop a successful digital start-up ecosystem further.

Keywords: digital innovation, female digital entrepreneurs, feminist phenomenology, gender, marginalised communities

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Authors: Zhao Yu, Zhi-Nan Zhang

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More and more interactive devices are used in the transportation service system. Our mobile phones, on-board computers, and Head-Up Displays (HUDs) can all be used as the tools of the in-car service system. People can access smart systems with different terminals such as mobile phones, computers, pads and even their cars and watches. Different forms of terminals bring the different quality of interaction by the various human-computer Interaction modes. The new interactive devices require good ergonomics design at each stage of the whole design process. According to the theory of human factors and ergonomics, this paper compared three types of interactive devices by four driving tasks. Forty-eight drivers were chosen to experience these three interactive devices (mobile phones, on-board computers, and HUDs) by a simulate driving process. The subjects evaluated ergonomics performance and subjective workload after the process. And subjects were encouraged to support suggestions for improving the interactive device. The result shows that different interactive devices have different advantages in driving tasks, especially in non-driving tasks such as information and entertainment fields. Compared with mobile phones and onboard groups, the HUD groups had shorter response times in most tasks. The tasks of slow-up and the emergency braking are less accurate than the performance of a control group, which may because the haptic feedback of these two tasks is harder to distinguish than the visual information. Simulated driving is also helpful in improving the design of in-vehicle interactive devices. The paper summarizes the ergonomics characteristics of three in-vehicle interactive devices. And the research provides a reference for the future design of in-vehicle interactive devices through an ergonomic approach to ensure a good interaction relationship between the driver and the in-vehicle service system.

Keywords: human factors, industrial ergonomics, transportation system, usability, vehicle user interface

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Authors: Wei Lu

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With the development of information technology in China, network consumption is becoming more and more popular. As a special group, college students have a high degree of education and distinct opinions and personalities. In the future, the key groups of network consumption have gradually become the focus groups of network consumption. Studying college students’ online consumption behavior has important theoretical significance and practical value. Based on the Stimulus-Organism-Response (SOR) driving model and the structural equation model, this paper establishes the influencing factors model of College students’ online consumption behavior, evaluates and amends the model by using SPSS and AMOS software, analyses and determines the positive factors of marketing college students’ consumption, and provides an effective basis for guiding and promoting college student consumption.

Keywords: college students, online consumption, stimulate-organism-reaction driving model, structural equation model

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Authors: Mehmet Yörükoğlu, Serhat Aydın

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Since the discovery of the manuscript, mechanical methods for storing, transferring and using the information have evolved into digital methods over the time. In this process, libraries that are the center of the information have also become digitized and become accessible from anywhere and at any time in the world by taking on a structure that has no physical boundaries. In this context, some criteria for information obtained from digital libraries have become more important for users. This paper evaluates the user criteria from different perspectives that make a digital library more useful. The Step-Wise Weight Assessment Ratio Analysis-Weighted Aggregated Sum Product Assessment (SWARA-WASPAS) method is used with flexibility and easy calculation steps for the evaluation of digital library criteria. Three different digital libraries are evaluated by information technology experts according to five conflicting main criteria, ‘interface design’, ‘effects on users’, ‘services’, ‘user engagement’ and ‘context’. Finally, alternatives are ranked in descending order.

Keywords: digital library, multi criteria decision making, SWARA-WASPAS method

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Authors: Sumita Srivastava

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Despite several measures taken by the Government of India, entrepreneurship is still not perceived as a viable career option by the young generation. Although the rate of startups has improved a little after the penetration of e portals as business platforms, still the numbers are not very significant. It is also important to note that entrepreneurial initiatives are mostly taken up by graduates of premier institutions of India like Indian Institute of Technology (IITs) and Indian Institute of Management (IIMs). The scenario is not very satisfactory amongst the masses graduating from mainstream universities of the country. Indian youth at large are not attracted towards entrepreneurship as a career choice. The reason probably lies in the social fabric of the country and inappropriate education system which does not support the entrepreneurship at large amongst youth in the country. Education is critical to the development of an economy from the poverty level to the level of self-sustenance and development. The current curriculum in the majority of business schools in India prepares the average graduate to become employed by the available firms or business owners in society. For graduates in other streams, employment opportunities are very limited. The aim of this study was to identify and design entrepreneurship education contents to encourage undergraduates to pursue entrepreneurship as a career choice. This comprehensive study was conducted in multiple stages. Extensive research was conducted at each stage with an appropriate methodology. These stages of the project study were interconnected with each other, and each preceding stage provided inputs for the following stage of the study. In the first stage of the study, an empirical analysis was conducted to understand the current state of entrepreneurial intentions of undergraduates of Agra city. Various stakeholders were contacted at the stage, including students (n = 500), entrepreneurs (n = 20) and academicians and field experts (n = 10). At the second stage of the project study, a systems science technique, Nominal Group Technique (NGT) was used to identify the critical elements of entrepreneurship education in India based upon the findings of stage 1. The application of the Nominal Group Technique involved a workshop format; 15 domain experts participated in the workshop. Throughout the process, a democratic process was followed to avoid individual dominance and premature focusing on a single idea. The study obtained 63 responses from experts for effective entrepreneurship education in India. The responses were reduced to seven elements after a few thematic iterations. These elements were then segregated into content (knowledge, skills and attitude) and learning interaction on the basis of experts’ responses. After identifying critical elements of entrepreneurship education in the previous stage, the course was designed and validated at stage 3 of the project. Scientific methods were used at this stage to validate the curriculum contents and training interventions experimentally. The educational and training interventions designed through this study would not only help in developing entrepreneurial intentions but also creating skills relevant to the local entrepreneurial opportunities in the vicinity.

Keywords: curriculum design, entrepreneurial intention, entrepreneuship education, nominal group technique

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Authors: William Chung

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This paper is to study the use of multiple subproblems in Dantzig-Wolfe decomposition of linear programming (DW-LP). Traditionally, the decomposed LP consists of one LP master problem and one LP subproblem. The master problem and the subproblem is solved alternatively by exchanging the dual prices of the master problem and the proposals of the subproblem until the LP is solved. It is well known that convergence is slow with a long tail of near-optimal solutions (asymptotic convergence). Hence, the performance of DW-LP highly depends upon the number of decomposition steps. If the decomposition steps can be greatly reduced, the performance of DW-LP can be improved significantly. To reduce the number of decomposition steps, one of the methods is to increase the number of proposals from the subproblem to the master problem. To do so, we propose to add a quadratic approximation function to the LP subproblem in order to develop a set of approximate-LP subproblems (multiple subproblems). Consequently, in each decomposition step, multiple subproblems are solved for providing multiple proposals to the master problem. The number of decomposition steps can be reduced greatly. Note that each approximate-LP subproblem is nonlinear programming, and solving the LP subproblem must faster than solving the nonlinear multiple subproblems. Hence, using multiple subproblems in DW-LP is the tradeoff between the number of approximate-LP subproblems being formed and the decomposition steps. In this paper, we derive the corresponding algorithms and provide some simple computational results. Some properties of the resulting algorithms are also given.

Keywords: approximate subproblem, Dantzig-Wolfe decomposition, large-scale models, multiple subproblems

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Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Raman Kumar, Jasgurpreet Singh Chohan, Chander Shekhar Verma

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Today, the manufacturing industries respond rapidly to new demands and compete in this continuously changing environment, thus seeking out new methods allowing them to remain competitive and flexible simultaneously. The aim of the manufacturing organizations is to reduce manufacturing costs and wastes through system simplification, organizational potential, and proper infrastructural planning by using modern techniques like lean manufacturing. In India, large number of medium and large scale manufacturing industries has successfully implemented lean manufacturing techniques. Keeping in view the above-mentioned facts, different tools will be involved in the successful implementation of the lean approach. The present work is focused on the auto part manufacturing industry to improve the performance of the recliner assembly line. There is a number of lean manufacturing tools available, but the experience and complete knowledge of manufacturing processes are required to select an appropriate tool for a specific process. Fishbone diagrams (scrap, inventory, and waiting) have been drawn to identify the root cause of different. Effect of cycle time reduction on scrap and inventory is analyzed thoroughly in the case company. Results have shown that there is a decrease in inventory cost by 7 percent after the successful implementation of the lean tool.

Keywords: lean tool, fish-bone diagram, cycle time reduction, case study

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Authors: Naveen Kumar, Shyambihari Prajapati

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Industry 4.0 is the fourth industrial revolution that focuses on interconnectivity of machine to machine, human to machine and human to human via Internet of Things (IoT). Technologies of industry 4.0 facilitate communication between human and machine through IoT and forms Cyber-Physical Production System (CPPS). In CPPS, multiple shop floors sensor data are connected through IoT and displayed through sensor dashboard to the operator. These sensor dashboards have enormous amount of information to be presented which becomes complex for operators to perform monitoring, controlling and interpretation tasks. Designing handheld sensor dashboards for supervision task will become a challenge for the interface designers. This paper reports emerging technologies of industry 4.0, changing context of increasing information complexity in consecutive industrial revolutions and upcoming design challenges for interface designers in context of Industry 4.0. Authors conclude that information complexity of sensor dashboards design has increased with consecutive industrial revolutions and designs of sensor dashboard causes cognitive load on users. Designing such complex dashboards interfaces in Industry 4.0 context will become main challenges for the interface designers.

Keywords: Industry4.0, sensor dashboard design, cyber-physical production system, Interface designer

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: P. Suresh, K. Gunasekaran, R. Thanigaivelan

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Radio frequency identification (RFID) technology has been attracting considerable attention with the expectation of improved supply chain visibility for consumer goods, apparel, and pharmaceutical manufacturers, as well as retailers and government procurement agencies. It is also expected to improve the consumer shopping experience by making it more likely that the products they want to purchase are available. Recent announcements from some key retailers have brought interest in RFID to the forefront. A modified K- Means Cluster based Heuristic approach, Hybrid Genetic Algorithm (GA) - Simulated Annealing (SA) approach, Hybrid K-Means Cluster based Heuristic-GA and Hybrid K-Means Cluster based Heuristic-GA-SA for Open Loop Supply Chain Network problem are proposed. The study incorporated uniform crossover operator and combined crossover operator in GAs for solving open loop supply chain distribution network problem. The algorithms are tested on 50 randomly generated data set and compared with each other. The results of the numerical experiments show that the Hybrid K-means cluster based heuristic-GA-SA, when tested on 50 randomly generated data set, shows superior performance to the other methods for solving the open loop supply chain distribution network problem.

Keywords: RFID, supply chain distribution network, open loop supply chain, genetic algorithm, simulated annealing

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