Search results for: manufacturing optimization

Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

Procedia PDF Downloads 578

Authors: Payel Ghosh, Rama Chandra Pradhan, Sabyasachi Mishra

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Jamun (Syzygium cuminii L.) is one of the important indigenous minor fruit with high medicinal value. The jamun cultivation is unorganized and there is huge loss of this fruit every year. The perishable nature of the fruit makes its postharvest management further difficult. Due to the strong cell wall structure of pectin-protein bonds and hard seeds, extraction of juice becomes difficult. Enzymatic treatment has been commercially used for improvement of juice quality with high yield. The objective of the study was to optimize the best treatment method for juice extraction. Enzymes (Pectinase and Tannase) from different stains had been used and for each enzyme, best result obtained by using response surface methodology. Optimization had been done on the basis of physicochemical property, nutritional property, sensory quality and cost estimation. According to quality aspect, cost analysis and sensory evaluation, the optimizing enzymatic treatment was obtained by Pectinase from Aspergillus aculeatus strain. The optimum condition for the treatment was 44 ^oC with 80 minute with a concentration of 0.05% (w/w). At these conditions, 75% of yield with turbidity of 32.21NTU, clarity of 74.39%T, polyphenol content of 115.31 mg GAE/g, protein content of 102.43 mg/g have been obtained with a significant difference in overall acceptability.

Keywords: enzymatic treatment, Jamun, optimization, physicochemical property, sensory analysis

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

Procedia PDF Downloads 333

Authors: M. E. Khiav, D. J. Borah, H. T. S. Santos, V. T. Faria

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For automobile companies, it has become very important to ensure sound quality in manufacturing and assembling in order to prevent occurrence of defects and to reduce the amount of parts replacements to be done in the service centers during the warranty period. Statistical Process Control (SPC) is widely used as the tool to analyze the quality of such processes and plays a significant role in the improvement of the processes by identifying the patterns and the location of the defects. In this paper, a case study has been conducted on an Iranian automobile company. This paper performs a quality analysis of a particular component called “Internal Bearing for the Back Wheel” of a particular car model, manufactured by the company, based on the 10 million data received from its service centers located all over the country. By creating control charts including X bar–S charts and EWMA charts, it has been observed after the year 2009, the specific component underwent frequent failures and there has been a sharp dip in the average distance covered by the cars till the specific component requires replacement/maintenance. Correlation analysis was performed to find out the reasons that might have affected the quality of the specific component in all the cars produced by the company after the year 2009. Apart from manufacturing issues, some political and environmental factors have been identified to have a potential impact on the quality of the component. A maiden attempt has been made to analyze the quality issues within an Iranian automobile manufacturer; such issues often get neglected in developing countries. The paper also discusses the possibility of political scenario of Iran and the country’s environmental conditions affecting the quality of the end products, which not only strengthens the extant literature but also provides a new direction for future research.

Keywords: capability analysis, car manufacturing, statistical process control, quality control, quality tools

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Authors: B. Ravi Kumar, S. Gajanana, K. Hemachandra Reddy, K. Udayani

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Physically into various derived shapes and sizes under the effect of externally applied forces. The spinning process is an advanced plastic working technology and is frequently used for manufacturing axisymmetric shapes. Over the last few decades, Sheet metal spinning has developed significantly and spun products have widely used in various industries. Nowadays the process has been expanded to new horizons in industries, since tendency to use minimum tool and equipment costs and also using lower forces with the output of excellent surface quality and good mechanical properties. The automation of the process is of greater importance, due to its wider applications like decorative household goods, rocket nose cones, gas cylinders, etc. This paper aims to gain insight into the conventional spinning process by employing experimental and numerical methods. The present work proposes an approach for optimizing process parameters are mandrel speed (rpm), roller nose radius (mm), thickness of the sheet (mm). Forming force, surface roughness and strain are the responses.in spinning of Aluminum (2024-T3) using DOE-Response Surface Methodology (RSM) and Analysis of variance (ANOVA). The FEA software is used for modeling and analysis. The process parameters considered in the experimentation.

Keywords: FEA, RSM, process parameters, sheet metal spinning

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Authors: Tamas Mankovits

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Lightweight cellular-type structures like metal foams have excellent mechanical properties, therefore the interest in these materials is widely spreading as load-bearing structural elements, e.g. as implants. Numerous technologies are available to produce metal foams. In this paper the material response of closed cell foam structures produced by direct foaming and additive technology is compared. The production technology circumstances are also investigated. Geometrical variations are developed for foam structures produced by additive manufacturing and simulated by finite element method to be able to predict the mechanical behavior.

Keywords: additive manufacturing, direct foaming, finite element method, metal foam

Procedia PDF Downloads 193

Authors: Eman M. Eissa, Hany M. Hasanin, Mahmoud Abd-Elhamid, S. M. Muyeen, T. Fernando, H. H. C. Iu

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Among all available wind energy conversion systems (WECS), the direct driven permanent magnet synchronous generator integrated with power electronic interfaces is becoming popular due to its capability of extracting optimal energy capture, reduced mechanical stresses, no need to external excitation current, meaning less losses, and more compact size. Simple structure, low maintenance cost; and its decoupling control performance is much less sensitive to the parameter variations of the generator. This paper attempts to present a review of the control and optimization strategies of WECS based on permanent magnet synchronous generator (PMSG) and overview the most recent research trends in this field. The main aims of this review include; the generalized overall WECS starting from turbines, generators, and control strategies including converters, maximum power point tracking (MPPT), ending with DC-link control. The optimization methods of the controller parameters necessary to guarantee the operation of the system efficiently and safely, especially when connected to the power grid are also presented.

Keywords: control and optimization techniques, permanent magnet synchronous generator, variable speed wind turbines, wind energy conversion system

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Authors: Nico Fuchs, Fabian Wüllhorst, Laura Maier, Dirk Müller

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The decarbonization of building stocks necessitates the modernization of existing buildings. Key measures for this include reducing energy demands through insulation of the building envelope, replacing heat generators, and installing solar systems. Given limited financial resources, it is impractical to modernize all buildings in a portfolio simultaneously; instead, prioritization of buildings and modernization measures for a given planning horizon is essential. Optimization models for modernization pathways can assist portfolio managers in this prioritization. However, modeling and solving these large-scale optimization problems, often represented as mixed-integer problems (MIP), necessitates simplifying the operation of building energy systems particularly with respect to system dynamics and transient behavior. This raises the question of which level of simplification remains sufficient to accurately account for realistic costs and emissions of building energy systems, ensuring a fair comparison of different modernization measures. This study addresses this issue by comparing a two-stage simulation-based optimization approach with a single-stage mathematical optimization in a mixed-integer linear programming (MILP) formulation. The simulation-based approach serves as a benchmark for realistic energy system operation but requires a restriction of the solution space to discrete choices of modernization measures, such as the sizing of heating systems. After calculating the operation of different energy systems in terms of the resulting final energy demands in simulation models on a first stage, the results serve as input for a second stage MILP optimization, where the design of each building in the portfolio is optimized. In contrast to the simulation-based approach, the MILP-based approach can capture a broader variety of modernization measures due to the efficiency of MILP solvers but necessitates simplifying the building energy system operation. Both approaches are employed to determine the cost-optimal design and dimensioning of several buildings in a portfolio to meet climate targets within limited yearly budgets, resulting in a modernization pathway for the entire portfolio. The comparison reveals that the MILP formulation successfully captures design decisions of building energy systems, such as the selection of heating systems and the modernization of building envelopes. However, the results regarding the optimal dimensioning of heating technologies differ from the results of the two-stage simulation-based approach, as the MILP model tends to overestimate operational efficiency, highlighting the limitations of the MILP approach.

Keywords: building energy system optimization, model accuracy in optimization, modernization pathways, building stock decarbonization

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Authors: Shan Jia, Jinbao Chen, Jinhua Zhou, Jiacheng Qian

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Lunar exploration is a necessary foundation for deep-space exploration. For the functional limitations of the fixed landers which are widely used currently and are to expand the detection range by the use of wheeled rovers with unavoidable path-repeatability, a movable lunar soft-landing device based on cantilever type buffer mechanism and leg-foot type walking mechanism is presented. Firstly, a 20 DoFs quadruped configuration based on pushrod is proposed. The configuration is of the bionic characteristics such as hip, knee and ankle joints, and can make the kinematics of the whole mechanism unchanged before and after buffering. Secondly, the multi-function main/auxiliary buffers based on crumple-energy absorption and screw-nut mechanism, as well as the telescopic device which could be used to protect the plantar force sensors during the buffer process are designed. Finally, the kinematic model of the whole mechanism is established, and the configuration optimization of the whole mechanism is completed based on the performance requirements of slope adaptation and obstacle crossing. This research can provide a technical solution integrating soft-landing, large-scale inspection and material-transfer for future lunar exploration and even mars exploration, and can also serve as the technical basis for developing the reusable landers.

Keywords: configuration design, lunar soft-landing device, movable, optimization

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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

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Authors: Elimhan N. Mahmudov

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The paper concerns the necessary and sufficient conditions of optimality for Cauchy problem of fourth order discrete (PD) and discrete-approximate (PDA) inclusions. The main problem is formulation of the fourth order adjoint discrete and discrete-approximate inclusions and transversality conditions, which are peculiar to problems including fourth order derivatives and approximate derivatives. Thus the necessary and sufficient conditions of optimality are obtained incorporating the Euler-Lagrange and Hamiltonian forms of inclusions. Derivation of optimality conditions are based on the apparatus of locally adjoint mapping (LAM). Moreover in the application of these results we consider the fourth order linear discrete and discrete-approximate inclusions.

Keywords: difference, optimization, fourth, approximation, transversality

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Authors: Juan Manuel Martinez Alvarez, Michele Chiumenti

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This work explores the benefit of the thermo-metallurgical simulation to tackle the Wire Laser Additive Manufacturing (WLAM) of low-carbon steel components. The Finite Element Analysis is calibrated by process monitoring via thermal imaging and thermocouples measurements, to study the complex thermo-metallurgical behavior inherent to the WLAM process of low carbon steel parts.A critical aspect is the analysis of the heterogeneity in the resulting microstructure. This heterogeneity depends on both the thermal history and the residual stresses experienced during the WLAM process. Because of low carbon grades are highly sensitive to quenching, a high-gradient microstructure often arises due to the layer-by-layer metal deposition in WLAM. The different phases have been identified by scanning electron microscope. A clear influence of the heterogeneities on the final mechanical performance has been established by the subsequent mechanical characterization. The thermo-metallurgical analysis has been used to determine the actual thermal history and the corresponding thermal gradients during the printing process. The correlation between the thermos-mechanical evolution, the printing parameters and scanning sequence has been established. Therefore, an enhanced printing strategy, including optimized process window has been used to minimize the microstructure heterogeneity at ArcelorMittal.

Keywords: additive manufacturing, numerical simulation, metallurgy, steel

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Authors: Tahseen Saad, Halim Ceylan, Jonathan Weaver, Osman Nuri Çelik, Onur Gungor Sahin

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A new concept of uniform delay offset dependent mathematical optimization problem is derived as the main objective for this study using a differential evolution algorithm. To control the coordination problem, which depends on offset selection and to estimate uniform delay based on the offset choice in a traffic signal network. The assumption is the periodic sinusoidal function for arrival and departure patterns. The cycle time is optimized at the entry links and the optimized value is used in the non-entry links as a common cycle time. The offset optimization algorithm is used to calculate the uniform delay at each link. The results are illustrated by using a case study and are compared with the canonical uniform delay model derived by Webster and the highway capacity manual’s model. The findings show new model minimizes the total uniform delay to almost half compared to conventional models. The mathematical objective function is robust. The algorithm convergence time is fast.

Keywords: area traffic control, traffic flow, differential evolution, sinusoidal periodic function, uniform delay, offset variable

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Authors: Simon Komesker, Achim Wagner, Martin Ruskowski

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In times of volatile markets with fluctuating demand and the uncertainty of global supply chains, flexible production systems are the key to an efficient implementation of a desired production program. In this publication, the authors present a holistic information concept taking into account various influencing factors for operating towards the global optimum. Therefore, a strategy for the implementation of multi-level planning for a flexible, reconfigurable production system with an alternative production concept in the automotive industry is developed. The main contribution of this work is a system structure mixing central and decentral planning and control evaluated in a simulation framework. The information system structure in current production systems in the automotive industry is rigidly hierarchically organized in monolithic systems. The production program is created rule-based with the premise of achieving uniform cycle time. This program then provides the information basis for execution in subsystems at the station and process execution level. In today's era of mixed-(car-)model factories, complex conditions and conflicts arise in achieving logistics, quality, and production goals. There is no provision for feedback loops of results from the process execution level (resources) and process supporting (quality and logistics) systems and reconsideration in the planning systems. To enable a robust production flow, the complexity of production system control is artificially reduced by the line structure and results, for example in material-intensive processes (buffers and safety stocks - two container principle also for different variants). The limited degrees of freedom of line production have produced the principle of progress figure control, which results in one-time sequencing, sequential order release, and relatively inflexible capacity control. As a result, modularly structured production systems such as modular production according to known approaches with more degrees of freedom are currently difficult to represent in terms of information technology. The remedy is an information concept that supports cross-system and cross-level information processing for centralized and decentralized decision-making. Through an architecture of hierarchically organized but decoupled subsystems, the paradigm of hybrid control is used, and a holonic manufacturing system is offered, which enables flexible information provisioning and processing support. In this way, the influences from quality, logistics, and production processes can be linked holistically with the advantages of mixed centralized and decentralized planning and control. Modular production systems also require modularly networked information systems with semi-autonomous optimization for a robust production flow. Dynamic prioritization of different key figures between subsystems should lead the production system to an overall optimum. The tasks and goals of quality, logistics, process, resource, and product areas in a cyber-physical production system are designed as an interconnected multi-agent-system. The result is an alternative system structure that executes centralized process planning and decentralized processing. An agent-based manufacturing control is used to enable different flexibility and reconfigurability states and manufacturing strategies in order to find optimal partial solutions of subsystems, that lead to a near global optimum for hybrid planning. This allows a robust near to plan execution with integrated quality control and intralogistics.

Keywords: holonic manufacturing system, modular production system, planning, and control, system structure

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Authors: Raphael M. Rettig, Tessa C. Flatten

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This empirical study answer calls for research on Absorptive Capacity and Process Innovation. Due to the fourth industrial revolution, manufacturing companies face the biggest disruption of their production processes since the rise of advanced manufacturing technologies in the last century. Therefore, process innovation will become a critical task to master in the future for many manufacturing firms around the world. The general ability of organizations to acquire, assimilate, transform, and exploit external knowledge, known as Absorptive Capacity, was proven to positively influence product innovation and is already conceptually associated with process innovation. The presented research provides empirical evidence for this influence. The findings are based on an empirical analysis of 732 companies from seven leading and emerging countries: Brazil, China, France, Germany, India, Japan, and the United States of America. The answers to the survey were collected in February and March 2018 and addressed senior- and top-level management with a focus on operations departments. The statistical analysis reveals the positive influence of potential and Realized Absorptive Capacity on successful process innovation taking the implementation of new digital manufacturing processes as an example. Potential Absorptive Capacity covering the acquisition and assimilation capabilities of an organization showed a significant positive influence (β = .304, p < .05) on digital manufacturing implementation success and therefore on process innovation. Realized Absorptive Capacity proved to have significant positive influence on process innovation as well (β = .461, p < .01). The presented study builds on prior conceptual work in the field of Absorptive Capacity and process innovation and contributes theoretically to ongoing research in two dimensions. First, the already conceptually associated influence of Absorptive Capacity on process innovation is backed by empirical evidence in a broad international context. Second, since Absorptive Capacity was measured with a focus on new product development, prior empirical research on Absorptive Capacity was tailored to the research and development departments of organizations. The results of this study highlight the importance of Absorptive Capacity as a capability in mechanical engineering and operations departments of organizations. The findings give managers an indication of the importance of implementing new innovative processes into their production system and fostering the right mindset of employees to identify new external knowledge. Through the ability to transform and exploit external knowledge, own production processes can be innovated successfully and therefore have a positive influence on firm performance and the competitive position of their organizations.

Keywords: absorptive capacity, digital manufacturing, dynamic capabilities, process innovation

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Authors: Ashish Shukla, K. P. Mishra, Pushplata Tripathi

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This paper investigates the production and optimization of β-galactosidase enzyme using synthetic medium by isolated wild strains (S1, S2) mutated strains (M1, M2) through SSF and SmF. Among the different cell disintegration methods used, the highest specific activity was obtained when the cells were permeabilized using isoamyl alcohol. Wet lab experiments were performed to investigate the effects of carbon and nitrogen substrates present in Vogel’s medium on β-galactosidase enzyme activity using S1, S2, and M1, M2 strains through SSF. SmF experiments were performed for effects of carbon and nitrogen sources in YLK2Mg medium on β-galactosidase enzyme activity using S1, S2 and M1, M2 strains. Effect of pH on β-galactosidase enzyme production was also done using S1, S2, and M1, M2 strains. Results were found to be very appreciable in all the cases.

Keywords: β-galactosidase, cell disintegration, permeabilized, SSF, SmF

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Authors: Soheila Afkar

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Mentha piperita is a medicinal plant that contains a large amount of secondary metabolite that has adverse effect on RNA extraction. Since high quality of RNA is the first step to real time-PCR, in this study optimization of total RNA isolation from leaf tissues of Mentha piperita was evaluated. From this point of view, we researched two different total RNA extraction methods on leaves of Mentha piperita to find the best one that contributes the high quality. The methods tested are RNX-plus, modified RNX-plus (1-5 numbers). RNA quality was analyzed by agarose gel 1.5%. The RNA integrity was also assessed by visualization of ribosomal RNA bands on 1.5% agarose gels. In the modified RNX-plus method (number 2), the integrity of 28S and 18S rRNA was highly satisfactory when analyzed in agarose denaturing gel, so this method is suitable for RNA isolation from Mentha piperita.

Keywords: Mentha piperita, polyphenol, polysaccharide, RNA extraction

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Authors: May M. Youssef

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This article introduces a design, for additive manufacturing technology, face shield as Personal Protective Equipment from the respiratory viruses such as coronavirus 2. The face shields help to reduce ocular exposure and play a vital role in diverting away from the respiratory COVID-19 air droplets around the users' face. The proposed face shield comprises three assembled polymer parts. The frame with a transparency overhead projector sheet visor is suitable for frontline health care workers and ordinary citizens. The frame design allows tightening the shield around the user’s head and permits rubber elastic straps to be used if required. That ergonomically designed with a unique face mask support used in case of wearing extra protective mask was created using computer aided design (CAD) software package. The finite element analysis (FEA) structural verification of the proposed design is performed by an advanced simulation technique. Subsequently, the prototype model was fabricated by a 3D printing using Fused Deposition Modeling (FDM) as a globally developed face shield product. This study provides a different face shield designs for global production, which showed to be suitable and effective toward supply chain shortages and frequent needs of personal protective goods during coronavirus disease and similar viruses.

Keywords: additive manufacturing, Coronavirus-19, face shield, personal protective equipment, 3D printing

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Authors: N. Ourabia, M. Boubaker Ourabia

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An approach for modeling and numerical simulation of passive planar structures using the edge line concept is developed. With this method, we develop an efficient modeling technique for microstrip discontinuities. The technique obtains closed form expressions for the equivalent circuits which are used to model these discontinuities. Then, it would be easy to handle and to characterize complicated structures like T and Y junctions, truncated junctions, arbitrarily shaped junctions, cascading junctions and more generally planar multiport junctions. Another advantage of this method is that the edge line concept for arbitrary shape junctions operates with real parameters circuits. The validity of the method was further confirmed by comparing our results for various discontinuities (bend, filters) with those from HFSS as well as from other published sources.

Keywords: optimization, CAD analysis, microwave circuits, S-parameters

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Authors: Kalpana Dahiya

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This paper discusses a two-level hierarchical time minimization transportation problem, which is an important class of transportation problems arising in industries. This problem has been studied by various researchers, and a number of polynomial time iterative algorithms are available to find its solution. All the existing algorithms, though efficient, have some shortcomings. The current study proposes an alternate solution algorithm for the problem that is more efficient in terms of computational time than the existing algorithms. The results justifying the underlying theory of the proposed algorithm are given. Further, a detailed comparison of the computational behaviour of all the algorithms for randomly generated instances of this problem of different sizes validates the efficiency of the proposed algorithm.

Keywords: global optimization, hierarchical optimization, transportation problem, concave minimization

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Authors: Jan Schmitt, Sophie Fischer

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After the Corona pandemic, climate change is a further, long-lasting challenge the society must deal with. An ongoing climate change need to be prevented. Nevertheless, the adoption tothe already changed climate conditionshas to be focused in many sectors. Recently, the decisive role of the economic sector with high value added can be seen in the Corona crisis. Hence, manufacturing industry as such a sector, needs to be prepared for climate change and adaption. Several examples from the manufacturing industry show the importance of a strategic effort in this field: The outsourcing of a major parts of the value chain to suppliers in other countries and optimizing procurement logistics in a time-, storage- and cost-efficient manner within a network of global value creation, can lead vulnerable impacts due to climate-related disruptions. E.g. the total damage costs after the 2011 flood disaster in Thailand, including costs for delivery failures, were estimated at 45 billion US dollars worldwide. German car manufacturers were also affected by supply bottlenecks andhave close its plant in Thailand for a short time. Another OEM must reduce the production output. In this contribution, a game-based learning approach is presented, which should enable manufacturing companies to derive their own strategies for climate adaption out of a mix of different actions. Based on data from a regional study of small, medium and large manufacturing companies in Mainfranken, a strongly industrialized region of northern Bavaria (Germany) the game-based learning approach is designed. Out of this, the actual state of efforts due to climate adaption is evaluated. First, the results are used to collect single actions for manufacturing companies and second, further actions can be identified. Then, a variety of climate adaption activities can be clustered according to the scope of activity of the company. The combination of different actions e.g. the renewal of the building envelope with regard to thermal insulation, its benefits and drawbacks leads to a specific strategy for climate adaption for each company. Within the game-based approach, the players take on different roles in a fictionalcompany and discuss the order and the characteristics of each action taken into their climate adaption strategy. Different indicators such as economic, ecologic and stakeholder satisfaction compare the success of the respective measures in a competitive format with other virtual companies deriving their own strategy. A "play through" climate change scenarios with targeted adaptation actions illustrate the impact of different actions and their combination onthefictional company.

Keywords: business strategy, climate change, climate adaption, game-based learning

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Authors: Muhammad Tahir Hassan, Stas Burek, Muhammad Asif, Mohamed Emad

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Industrial sector in Pakistan accounts for 25% of total energy consumption in the country. The performance of this sector has been severely affected due to the adverse effect of current energy crises in the country. Energy conservation potentials of Pakistan’s industrial sectors through energy management can save wasted energy which would ultimately leads to economic and environmental benefits. However due to lack of financial incentives of energy efficiency and absence of energy benchmarking within same industrial sectors are some of the main challenges in the implementation of energy management. In Pakistan, this area has not been adequately explored, and there is a lack of focus on the need for industrial energy efficiency and proper management. The main objective of this research is to evaluate the current energy management performance of Pakistani industrial sector and empirical investigation of the existence of various barriers to industrial energy efficiency. Data was collected from the respondents of 192 small and medium-sized enterprises (SME’s) of Pakistan i.e. foundries, textile, plastic industries, light engineering, auto and spare parts and ceramic manufacturers and analysed using Statistical Package for the Social Sciences (SPSS) software. Current energy management performance of manufacturing SME’s in Pakistan has been evaluated by employing two significant indicators, ‘Energy Management Matrix’ and ‘pay-off criteria’, with modified approach. Using the energy management matrix, energy management profiles of overall industry and the individual sectors have been drawn to assess the energy management performance and identify the weak and strong areas as well. Results reveal that, energy management practices in overall surveyed industries are at very low level. Energy management profiles drawn against each sector suggest that performance of textile sector is better among all the surveyed manufacturing SME’s. The empirical barriers to industrial energy efficiency have also been ranked according to the overall responses. The results further reveal that there is a significant relationship exists among the industrial size, sector type and nature of barriers to industrial energy efficiency for the manufacturing SME’s in Pakistan. The findings of this study may help the industries and policy makers in Pakistan to formulate a sustainable energy policy to support industrial energy efficiency keeping in view the actual existing energy efficiency scenario in the industrial sector.

Keywords: barriers, energy conservation, energy management profile, environment, manufacturing SME's of Pakistan

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Authors: Juan P. Novoa, Mario A. Rios

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This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.

Keywords: transmission expansion planning, HVDC, cost optimization, energy non-supplied

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Authors: Nasim Fallahi, Erasmo Carrera, Alfonso Pagani

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Variable angle tow describes the fibres which are curvilinearly steered in a composite lamina. Significantly, stiffness tailoring freedom of VAT composite laminate can be enlarged and enabled. Composite structures with curvilinear fibres have been shown to improve the buckling load carrying capability in contrast with the straight laminate composites. However, the optimal design and analysis of VAT are faced with high computational efforts due to the increasing number of variables. In this article, an efficient optimum solution has been used in combination with 1D Carrera’s Unified Formulation (CUF) to investigate the optimum fibre orientation angles for buckling analysis. The particular emphasis is on the LE-based CUF models, which provide a Lagrange Expansions to address a layerwise description of the problem unknowns. The first critical buckling load has been considered under simply supported boundary conditions. Special attention is lead to the sensitivity of buckling load corresponding to the fibre orientation angle in comparison with the results which obtain through the Genetic Algorithm (GA) optimization frame and then Artificial Neural Network (ANN) is applied to investigate the accuracy of the optimized model. As a result, numerical CUF approach with an optimal solution demonstrates the robustness and computational efficiency of proposed optimum methodology.

Keywords: beam structures, layerwise, optimization, variable stiffness

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Authors: Suleman Bawa, Ayiku Emmanuel Lartey

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Purpose - This paper aims to examine the association between knowledge capital and multinational firms’ innovation management. We again explored the impact of transboundary investment and assimilative capacity between knowledge capital and multinational firms’ innovation management. The vital position of knowledge capital and multinational firms’ innovation management in today’s increasingly volatile environment coupled with fierce competition has been extensively acknowledged by academics and industry investment capitals. Design/methodology/approach - The theoretical association model and an empirical correlation analysis were constructed based on relevant research using data collected from 19 multinational firms in Ghana as the subject, and path analysis was constructed using SPSS 22.0 and AMOS 24.0 to test the formulated hypotheses. Findings - Varied conclusions are drawn consequential from theoretical inferences and empirical tests. For multinational firms, knowledge capital relics positively significant to multinational firms’ innovation management. Multinational firms with advanced knowledge capital likely spawn greater corporations’ innovation management. Second, transboundary investment efficiently intermediates the association between knowledge physical capital, knowledge interactive capital, and corporations’ innovation management. At the same time, this impact is insignificant between knowledge of empirical capital and corporations’ innovation management. Lastly, the impact of transboundary investment and assimilative capacity on the association between knowledge capital and corporations’ innovation management is established. We summarized the implications for managers based on our outcomes. Research limitations/implications - Multinational firms must dynamically build knowledge capital to augment corporations’ innovation management. Conversely, knowledge capital motivates multinational firms to implement transboundary investment and cultivate assimilative capacity. Accordingly, multinational firms can efficiently exploit diverse information to augment their corporate innovation management. Practical implications – This paper presents a comprehensive justification of knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry, its sequential progress, and its associated challenges. Originality/value – This paper is amongst the first to find empirical results to back knowledge capital and manufacturing firms’ innovation management by exploring the impact of transboundary investment and assimilative capacity within the manufacturing industry. Additionally, aligning knowledge as a coordinative instrument is a significant input to our discernment in this area.

Keywords: knowledge capital, transboundary investment, innovation management, assimilative capacity

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Authors: Bing–Jing Zhao, Chang-Kui Liu, Hong Wang, Min Hu

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Electron beam rapid manufacturing (EBRM) or Selective laser melting is an additive manufacturing process that uses 3D CAD data as a digital information source and energy in the form of a high-power laser beam or electron beam to create three-dimensional metal parts by fusing fine metallic powders together.Object:The present study was conducted to evaluate the mechanical properties ,the phase transformation,the corrosivity and the biocompatibility of Ti-6Al-4V by EBRM,SLM and forging technique.Method: Ti-6Al-4V alloy standard test pieces were manufactured by EBRM, SLM and forging technique according to AMS4999,GB/T228 and ISO 10993.The mechanical properties were analyzed by universal test machine. The phase transformation was analyzed by X-ray diffraction and scanning electron microscopy. The corrosivity was analyzed by electrochemical method. The biocompatibility was analyzed by co-culturing with mesenchymal stem cell and analyzed by scanning electron microscopy (SEM) and alkaline phosphatase assay (ALP) to evaluate cell adhesion and differentiation, respectively. Results: The mechanical properties, the phase transformation, the corrosivity and the biocompatibility of Ti-6Al-4V by EBRM、SLM were similar to forging and meet the mechanical property requirements of AMS4999 standard. a­phase microstructure for the EBM production contrast to the a’­phase microstructure of the SLM product. Mesenchymal stem cell adhesion and differentiation were well. Conclusion: The property of the Ti-6Al-4V alloy manufactured by EBRM and SLM technique can meet the medical standard from this study. But some further study should be proceeded in order to applying well in clinical practice.

Keywords: 3D printing, Electron Beam Rapid Manufacturing (EBRM), Selective Laser Melting (SLM), Computer Aided Design (CAD)

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Authors: Mohammad Reza Esmaili

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One of the most important parts of the restoration process of a power network is the synchronizing of its subsystems. In this situation, the biggest concern of the system operators will be the reduction of the standing phase angle (SPA) between the endpoints of the two islands. In this regard, the system operators perform various actions and maneuvers so that the synchronization operation of the subsystems is successfully carried out and the system finally reaches acceptable stability. The most common of these actions include load control, generation control and, in some cases, changing the network topology. Although these maneuvers are simple and common, due to the weak network and extreme load changes, the restoration will be associated with low speed. One of the best ways to control the SPA is to use FACTS devices. By applying a soft control signal, these tools can reduce the SPA between two subsystems with more speed and accuracy, and the synchronization process can be done in less time. Meanwhile, the unified power controller (UPFC), a series-parallel compensator device with the change of transmission line power and proper adjustment of the phase angle, will be the proposed option in order to realize the subject of this research. Therefore, with the optimal placement of UPFC in a power system, in addition to improving the normal conditions of the system, it is expected to be effective in reducing the SPA during power system restoration. Therefore, the presented paper provides an optimal structure to coordinate the three problems of improving the division of subsystems, reducing the SPA and optimal power flow with the aim of determining the optimal location of UPFC and optimal subsystems. The proposed objective functions in this paper include maximizing the quality of the subsystems, reducing the SPA at the endpoints of the subsystems, and reducing the losses of the power system. Since there will be a possibility of creating contradictions in the simultaneous optimization of the proposed objective functions, the structure of the proposed optimization problem is introduced as a non-linear multi-objective problem, and the Pareto optimization method is used to solve it. The innovative technique proposed to implement the optimization process of the mentioned problem is an optimization algorithm called the water cycle (WCA). To evaluate the proposed method, the IEEE 39 bus power system will be used.

Keywords: UPFC, SPA, water cycle algorithm, multi-objective problem, pareto

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Authors: Un-Hwan Park, Jun-Hyeok Heo, In-Sung Lee, Tae-Hyeon Oh, Dae-Gyu Park

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Nonwoven fabric such as an automobile interior material becomes consists of several material layers required for the sound-absorbing function. Because several material layers, many experimental tuning is required to achieve the target of sound absorption. Therefore, a lot of time and money is spent in the development of the car interior materials. In this study, we present the method to predict the sound-absorbing performance of the various layers with physical properties of each material. and we will verify it with the measured value of a prototype. If the sound absorption can be estimated, it can be optimized without a number of tuning tests of the interiors. So, it can reduce the development cost and time during development

Keywords: automotive interior material, sound absorbing, optimization design, nonwoven fabric

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Authors: Zhiyan Meng, Dan Liu, Jintao Meng

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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

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Authors: Ignatio Madanhire, Charles Mbohwa

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This research examines the effect of a human resource strategy and the overall equipment effectiveness as well as assessing how the combination of the two can increase a firm’s productivity. The human resource aspect is looked at in detail to assess motivation of operators through training to reduce wastage on the manufacturing shop floor. The waste was attributed to operators, maintenance personal, idle machines, idle manpower and break downs. This work seeks to investigate the concept of Total Productive Maintenance (TPM) in addressing these short comings in the manufacturing case study. The impact of TPM to increase production while, as well as increasing employee morale and job satisfaction is assessed. This can be resource material for practitioners who seek to improve overall equipment efficiency (OEE) to achieve higher level productivity and competitiveness.

Keywords: maintenance, TPM, efficiency, productivity, strategy

Procedia PDF Downloads 416