Search results for: product optimization

Authors: Daljinder Singh, J.S.Dhillon, Balraj Singh

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According to no free lunch theorem, a single search technique cannot perform best in all conditions. Optimization method can be attractive choice to solve optimization problem that may have exclusive advantages like robust and reliable performance, global search capability, little information requirement, ease of implementation, parallelism, no requirement of differentiable and continuous objective function. In order to synergize between exploration and exploitation and to further enhance the performance of Bat algorithm, the paper proposed a modified bat algorithm that adds additional search procedure based on bat’s previous experience. The proposed algorithm is used for solving the economic load dispatch (ELD) problem. The practical constraint such valve-point loading along with power balance constraints and generator limit are undertaken. To take care of power demand constraint variable elimination method is exploited. The proposed algorithm is tested on various ELD problems. The results obtained show that the proposed algorithm is capable of performing better in majority of ELD problems considered and is at par with existing algorithms for some of problems.

Keywords: bat algorithm, economic load dispatch, penalty method, variable elimination method

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Authors: Manish Manohar Hingorani

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The purpose of the research is to find out the level of understanding, adoption, and implementation of CRM in Indian Businesses, either product/ service and the processes which should be followed to ensure minimal to no customer churn and further enhance loyalty. The study used comprehensive qualitative interviews of 36 respondents across mid and senior-level management in product and services organizations of Indian origin. The findings of the study exhibit a gap between the understanding, adoption and implementation of CRM in the Indian context. Different Industries have attributed different levels of understanding, adoption, and limited implementation studies on CRM to the Indian context exists in different industries, but studies related to the consequences of not understanding the true meaning of CRM at the grass root level and further than on non-adoption and non-implementation will have an adverse effect on the customer loyalty, and customer satisfaction leading to customer churn. As this was a qualitative approach, the analysis was content-based and discourse based. The responses were taken from mid to very-senior management decision-makers in organizations of Indian origin.

Keywords: customer relationship management, Indian consumer, customer loyalty, customer experience, customer satisfaction

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Authors: Cavidan Yakupoglu, Kurt Rohloff

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In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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Authors: I. O. Nascimento, J. T. Manzi

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The drying process is an important operation in the chemical industry and it is widely used in the food, grain industry and fertilizer industry. However, for demanding a considerable consumption of energy, such a process requires a deep energetic analysis in order to reduce operating costs. This paper deals with thermodynamic optimization applied to rotary dryers based on the entropy production minimization, aiming at to reduce the energy consumption. To do this, the mass, energy and entropy balance was used for developing a relationship that represents the rate of entropy production. The use of the Second Law of Thermodynamics is essential because it takes into account constraints of nature. Since the entropy production rate is minimized, optimals conditions of operations can be established and the process can obtain a substantial gain in energy saving. The minimization strategy had been led using classical methods such as Lagrange multipliers and implemented in the MATLAB platform. As expected, the preliminary results reveal a significant energy saving by the application of the optimal parameters found by the procedure of the entropy minimization It is important to say that this method has shown easy implementation and low cost.

Keywords: thermodynamic optimization, drying, entropy minimization, modeling dryers

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Authors: Sanchita Abrol, Kunal Rana, Ankit Dhir, S. K. Gupta

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According to N.R.E.L.’s findings, 700 crore gallons of petrol is used annually to run the air conditioners of passenger vehicles (nearly 6% of total fuel consumption in the USA). Beyond fuel use, the Environmental Protection Agency reported that refrigerant leaks from auto air conditioning units add an additional 5 crore metric tons of carbon emissions to the atmosphere each year. The objective of our project is to deal with this vital issue by carefully modifying the interiors of a car thereby increasing its mileage and the efficiency of its engine. This would consequently result in a decrease in tail emission and generated pollution along with improved car performance. An automatic mechanism, deployed between the front and the rear seats, consisting of transparent thermal insulating sheet/curtain, would roll down as per the requirement of the driver in order to optimize the volume for effective air conditioning, when travelling alone or with a person. The reduction in effective volume will yield favourable results. Even on a mild sunny day, the temperature inside a parked car can quickly spike to life-threatening levels. For a stationary parked car, insulation would be provided beneath its metal body so as to reduce the rate of heat transfer and increase the transmissivity. As a result, the car would not require a large amount of air conditioning for maintaining lower temperature, which would provide us similar benefits. Authors established the feasibility studies, system engineering and primarily theoretical and experimental results confirming the idea and motivation to fabricate and test the actual product.

Keywords: automation, car, cooling insulating curtains, heat optimization, insulation, reduction in tail emission, mileage

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Authors: Enver Kucukkulahli, Pakize Erdogmus, Kemal Polat

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The 2D image segmentation is a significant process in finding a suitable region in medical images such as MRI, PET, CT etc. In this study, we have focused on 2D MRI images for image segmentation process. We have designed a GUI (graphical user interface) written in MATLABTM for 2D MRI images. In this program, there are two different interfaces including data pre-processing and image clustering or segmentation. In the data pre-processing section, there are median filter, average filter, unsharp mask filter, Wiener filter, and custom filter (a filter that is designed by user in MATLAB). As for the image clustering, there are seven different image segmentations for 2D MR images. These image segmentation algorithms are as follows: PSO (particle swarm optimization), GA (genetic algorithm), Lloyds algorithm, k-means, the combination of Lloyds and k-means, mean shift clustering, and finally BBO (Biogeography Based Optimization). To find the suitable cluster number in 2D MRI, we have designed the histogram based cluster estimation method and then applied to these numbers to image segmentation algorithms to cluster an image automatically. Also, we have selected the best hybrid method for each 2D MR images thanks to this GUI software.

Keywords: image segmentation, clustering, GUI, 2D MRI

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Authors: Alireza Alizadeh, Hossein Ghadimi, Oveis Abedinia, Noradin Ghadimi

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A Particle Swarm Optimization with Time Varying Acceleration Coefficients (PSO-TVAC) is proposed to determine optimal economic load dispatch (ELD) problem in this paper. The proposed methodology easily takes care of solving non-convex economic load dispatch problems along with different constraints like transmission losses, dynamic operation constraints and prohibited operating zones. The proposed approach has been implemented on the 3-machines 6-bus, IEEE 5-machines 14-bus, IEEE 6-machines 30-bus systems and 13 thermal units power system. The proposed technique is compared to solve the ELD problem with hybrid approach by using the valve-point effect. The comparison results prove the capability of the proposed method giving significant improvements in the generation cost for the economic load dispatch problem.

Keywords: PSO-TVAC, economic load dispatch, non-convex cost function, prohibited operating zone, transmission losses

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Authors: Morteza Malek Yarand, Hadi Saebi Monfared

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This study aimed at designing and developing a mechanical force gauge for the square watermelon mold for the first time. It also tried to introduce the square watermelon characteristics and its production limitations. The mechanical force gauge performance and the product itself were also described. There are three main designable gauge models: a. hydraulic gauge, b. strain gauge, and c. mechanical gauge. The advantage of the hydraulic model is that it instantly displays the pressure and thus the force exerted by the melon. However, considering the inability to measure forces at all directions, complicated development, high cost, possible hydraulic fluid leak into the fruit chamber and the possible influence of increased ambient temperature on the fluid pressure, the development of this gauge was overruled. The second choice was to calculate pressure using the direct force a strain gauge. The main advantage of these strain gauges over spring types is their high precision in measurements; but with regard to the lack of conformity of strain gauge working range with water melon growth, calculations were faced with problems. Finally the mechanical pressure gauge has advantages, including the ability to measured forces and pressures on the mold surface during melon growth; the ability to display the peak forces; the ability to produce melon growth graph thanks to its continuous force measurements; the conformity of its manufacturing materials with the required physical conditions of melon growth; high air conditioning capability; the ability to permit sunlight reaches the melon rind (no yellowish skin and quality loss); fast and straightforward calibration; no damages to the product during assembling and disassembling; visual check capability of the product within the mold; applicable to all growth environments (field, greenhouses, etc.); simple process; low costs and so forth.

Keywords: mechanical force gauge, mold, reshaped fruit, square watermelon

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Authors: Bryan Young, Andrew Wodehouse, Marion Sheridan

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The availability of working memory has long been identified as a critical aspect of an instructional design. Many conventional instructional procedures impose irrelevant or unrelated cognitive loads on the learner due to the fact that they were created without contemplation, or understanding, of cognitive work load. Learning to physically operate traditional products can be viewed as a learning process akin to any other. As such, many of today's products, such as cars, boats, and planes, which have traditional controls that predate modern user-centered design techniques may be imposing irrelevant or unrelated cognitive loads on their operators. The goal of the research was to investigate the fundamental relationships between physical inputs, resulting actions, and learnability. The results showed that individuals can quickly adapt to input/output reversals across dimensions, however, individuals struggle to cope with the input/output when the dimensions are rotated due to the resulting increase in cognitive load.

Keywords: cognitive load theory, instructional design, physical product interactions, usability design

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Authors: Jonathan Olusegun Famoroti, Mathew Ekundayo Rotimi, Mishelle Doorasamy

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This study offers an empirical investigation into some selected macroeconomic drivers of the monetary policy rate in member countries of the West African Monetary Zone (WAMZ), considering both internal and external variables. We employed Autoregressive Distributed Lag (ARDL) to carry out the investigation between monetary policy and some macroeconomic variables in both the long-run and short-run relationship. The results suggest that the drivers of the policy rate in this zone, in the long run, include, among others, global oil price, exchange rate, inflation rate, and gross domestic product, while in the short run, federal fund rate, trade openness, exchange rate, inflation rate, and gross domestic product are core determinants of the policy rate. Therefore, in order to ensure long-run stability in the policy rate among the members’ states, these drivers should be given closer consideration so that the trajectory for effective structure can be designed and fused into the economic structure and policy frameworks accordingly.

Keywords: monetary policy rate, macroeconomic variables, WAMZ, ARDL

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Authors: Avinash Thakur, Parmjit S. Panesar, Manohar Singh

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The distribution coefficient, KD for the reactive extraction of lactic acid from aqueous solutions of lactic acid using 10-30% (v/v) tri-n-octyl amine (extractant) dissolved in n-hexane (inert diluent) and 20% (v/v) oleyl alcohol (modifier) was optimized by using response surface methodology (RSM). A three level Box-Behnken design was employed for experimental design, analysis of the results and to depict the combined interactive effect of seven independent variables, viz lactic acid concentration (cl), pH, TOA concentration in organic phase (ψ), treat ratio (φ), temperature (T), agitation speed (ω) and batch agitation time (τ) on distribution coefficient of lactic acid. The regression analysis recommended that the quadratic model is significant (R2 and adjusted R2 are 98.72 % and 98.69 % respectively) for analysis. A numerical optimization had resulted in maximum lactic acid distribution coefficient (KD) of 3.16 at the optimized values for test variables, cl, pH, ψ, φ, T, ω and τ as 0.15 [M], 3.0, 22.75% (v/v), 1.0 (v/v), 26°C, 145 rpm and 23 min respectively. A good agreement between the predicted and experimentally obtained values for distribution coefficient using the optimized conditions was exhibited.

Keywords: Distribution coefficient, tri-n-octylamine, lactic acid, response surface methodology

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Authors: Muhamad Afiq Faisal, Yahaya, Mohd Faizal, Hamzah

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Genetic modification technology allows scientists to alter the genetic information of a particular organism. The technology allows the production of genetically modified organism (GMO) that has the enhanced property compared to the unmodified organism. The application of such technology is not only in agriculture industry, it is now has been applied extensively in biopharmaceutical industry such as transgenic vaccines. In Malaysia, Biosafety Act 2007 has been enacted in which all GMO-based products must be labeled with adequate information before being marketed. This paper aims to determine the awareness level amongst Malaysian consumers on the GM products available in the market and the efficiency of information supplied in the GM product labeling. The result of the survey will serve as a guideline for Malaysia government agency bodies to provide comprehensive yet efficient information to consumers for the purpose of GM product labeling in the near future. In conclusion, the efficiency of information delivery plays a vital role in ensuring that the information is being conveyed clearly to Malaysian consumers during the selection process of GM products available in the market.

Keywords: genetic modification technology, genetically modified organisms, genetically modified organism products labeling, Biosafety Act 2007

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Authors: Achim Kampker, Heiner Hans Heimes, Mathias Ordung, Nemanja Sarovic

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A key component of the drive train of electric vehicles is the lithium-ion battery system. Among various other components, such as the battery management system or the thermal management system, the battery system mostly consists of several cells which are integrated mechanically as well as electrically. Due to different vehicle concepts with regards to space, energy and power specifications, there is a variety of different battery systems. The corresponding assembly lines are specially designed for each battery concept. Minor changes to certain characteristics of the battery have a disproportionally high effect on the set-up effort in the form of high change-related costs. This paper will focus on battery systems which are made out of battery cells with a prismatic format. The product architecture and the assembly process will be analyzed in detail based on battery concepts of existing electric cars and key variety-causing drivers will be identified. On this basis, several measures will be presented and discussed on how to change the product architecture and the assembly process in order to reduce change-related costs.

Keywords: assembly, automotive industry, battery system, battery concept

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Authors: Timothée Bligny, Clément Codron, Antoine Estruch, Nicolas Girodet, Clément Ginet

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Collateralized Debt Obligations are not as widely used nowadays as they were before 2007 Subprime crisis. Nonetheless there remains an enthralling challenge to optimize cash flows associated with synthetic CDOs. A Gaussian-based model is used here in which default correlation and unconditional probabilities of default are highlighted. Then numerous simulations are performed based on this model for different scenarios in order to evaluate the associated cash flows given a specific number of defaults at different periods of time. Cash flows are not solely calculated on a single bought or sold tranche but rather on a combination of bought and sold tranches. With some assumptions, the simplex algorithm gives a way to find the maximum cash flow according to correlation of defaults and maturities. The used Gaussian model is not realistic in crisis situations. Besides present system does not handle buying or selling a portion of a tranche but only the whole tranche. However the work provides the investor with relevant elements on how to know what and when to buy and sell.

Keywords: synthetic collateralized debt obligation (CDO), credit default swap (CDS), cash flow optimization, probability of default, default correlation, strategies, simulation, simplex

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Authors: Mohadese Hashemi, Elham Akhoundi Kharanaghi, Fatemeh Haghiralsadat, Mojgan Yazdani, Omid Javani, Mahboobe Sharafodini, Davood Rajabi

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Niosomes are non-ionic surfactant vesicles in aqueous media resulting in closed bilayer structures that can be used as carriers of hydrophilic and hydrophobic compounds. The use of niosomes for encapsulation of essential oils (EOs) is an attractive new approach to overcome their physicochemical stability concerns include sensibility to oxygen, light, temperature, and volatility, and their reduced bioavailability which is due to low solubility in water. EOs are unstable and fragile volatile compounds which have strong interest in pharmaceutical due to their medicinal properties such as antiviral, anti-inflammatory, antifungal, and antioxidant activities without side effects. Trachyspermum copticum (ajwain) is an annual aromatic plant with important medicinal properties that grows widely around Mediterranean region and south-west Asian countries. The major components of the ajwain oil were reported as thymol, γ-terpinene, p-cymene, and carvacrol which provide antimicrobial and antioxidant activity. The aim of this work was to formulate ajwain essential oil-loaded niosomes to improve water solubility of natural product and evaluate its physico-chemical features and stability. Ajwain oil was obtained through steam distillation using a clevenger-type apparatus and GC/MS was applied to identify the main components of the essential oil. Niosomes were prepared by using thin film hydration method and nanoparticles were characterized for particle size, dispersity index, zeta potential, encapsulation efficiency, in vitro release, and morphology.

Keywords: trachyspermum copticum, ajwain, niosome, essential oil, encapsulation

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Authors: Haruna Daddau

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This study investigates the effect of sustainable supply chain management (SSCM) on the performance of agricultural firms in Nigeria. Green packaging, product design, waste reduction and supply chain design were examined. The ecological modernization theory, which suggests the economic benefit of the environment, was used to underpin the study. The research is quantitative in nature, and a survey research method was adopted where information was obtained using questionnaires distributed directly to the top managers of 6 agricultural firms in Nigeria. STATA and SPSS were used for the data analysis, and regression analysis was used to examine the effects. Findings showed that SSCM positively improves the performance of the firms. Also, detailed information about the study’s selected variables' effect on performance was provided. Additionally, the significant role of SSCM in accelerating the firms’ performance was highlighted. It is recommended that SSCM should be given serious attention by integrating it into the overall firm's business strategy.

Keywords: sustainable supply chain management, green packaging, product design, waste reduction, supply chain design and performance

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Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

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Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

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Authors: Heitor Oliveira, Gabriele De-Waal, Juergen Schmenger, Lynsey Godfrey, Tibor Kovacs

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Rheolaser MASTER™ makes use of multiple scattering of light, caused by scattering objects in a continuous medium (such as droplets and particles in colloids), to characterize the viscoelasticity of soft materials. It offers an alternative to conventional rheometers to characterize viscoelasticity of products such as hair cosmetics. Up to six simultaneous measurements at controlled temperature can be carried out simultaneously (10-15 min), and the method requires only minor sample preparation work. Conversely to conventional rheometer based methods, no mechanical stress is applied to the material during the measurements. Therefore, the properties of the exact same sample can be monitored over time, like in aging and stability studies. We determined the elastic index (EI) of water/emulsion mixtures (1 ≤ fat alcohols (FA) ≤ 5 wt%) and emulsion/gel-network mixtures (8 ≤ FA ≤ 17 wt%) and compared with the elastic/sorage mudulus (G’) for the respective samples using a TA conventional rheometer with flat plates geometry. As expected, it was found that log(EI) vs log(G’) presents a linear behavior. Moreover, log(EI) increased in a linear fashion with solids level in the entire range of compositions (1 ≤ FA ≤ 17 wt%), while rheometer measurements were limited to samples down to 4 wt% solids level. Alternatively, a concentric cilinder geometry would be required for more diluted samples (FA > 4 wt%) and rheometer results from different sample holder geometries are not comparable. The plot of the rheolaser output parameters solid-liquid balance (SLB) vs EI were suitable to monitor product aging processes. These data could quantitatively describe some observations such as formation of lumps over aging time. Moreover, this method allowed to identify that the different specifications of a key raw material (RM < 0.4 wt%) in the respective gel-network (GN) product has minor impact on product viscoelastic properties and it is not consumer perceivable after a short aging time. Broadening of a RM spec range typically has a positive impact on cost savings. Last but not least, the photon path length (λ*)—proportional to droplet size and inversely proportional to volume fraction of scattering objects, accordingly to the Mie theory—and the EI were suitable to characterize product destabilization processes (e.g., coalescence and creaming) and to predict product stability about eight times faster than our standard methods. Using these parameters we could successfully identify formulation and process parameters that resulted in unstable products. In conclusion, Rheolaser allows quick and reliable characterization of viscoelastic properties of hair cosmetics that are related to their performance and stability. It operates in a broad range of product compositions and has applications spanning from the formulation of our hair cosmetics to fast release criteria in our production sites. Last but not least, this powerful tool has positive impact on R&D development time—faster delivery of new products to the market—and consequently on cost savings.

Keywords: colloids, hair cosmetics, light scattering, performance and stability, soft materials, viscoelastic properties

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Yuan Long, Fabrizio Ceschin, David Harrison

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Environmental sustainability is under the threat of excessive single-use plastic packaging waste, and current waste management fails to address this issue. Therefore, it has led to a reidentification of the alternative, which can curb the packaging waste without reducing social needs. Reusable packaging represents a circular approach to close the loop of consumption in which packaging can stay longer in the system to satisfy social needs. However, the implementation of reusable packaging is fragmented and lacks systematic approaches. The product-service system (PSS) is widely regarded as a sustainable business model innovation for embracing circular consumption. As a result, applying PSS to reusable packaging solutions will be promising to address the packaging waste issue. This paper aims at filling the knowledge gap relating to apply PSS to reusable packaging solutions and provide a strategic design tool that could support packaging professionals to design reusable packaging solutions. The methodology of this paper is case studies and workshops to provide a design tool. The respondents are packaging professionals who are packaging consultants, NGO professionals, and entrepreneurs. 57 cases collected show that 15 archetypal models operate in the market. Subsequently, a polarity diagram is developed to embrace those 15 archetypal models, and a total number of 24 experts were invited for the workshop to evaluate the design tool. This research finally provides a strategic design tool to support packaging professionals to design reusable packaging solutions. The application of the tool is to support the understanding of the reusable packaging solutions, analyzing the markets, identifying new opportunities, and generate new business models. The implication of this research is to provide insights for academics and businesses in terms of tackling single-use packaging waste and build a foundation for further development of the reusable packaging solution tool.

Keywords: environmental sustainability, product-service system, reusable packaging, design tool

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Authors: Cuong D. Dao, Rob J.I. Basten, Andreas Hartmann

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This paper studies the optimal maintenance planning of preventive maintenance and renewal activities for components in a single railway track when the available time for maintenance is limited. The rail-track system consists of several types of components, such as rail, ballast, and switches with different preventive maintenance and renewal intervals. To perform maintenance or renewal on the track, a train free period for maintenance, called a possession, is required. Since a major possession directly affects the regular train schedule, maintenance and renewal activities are clustered as much as possible. In a highly dense and utilized railway network, the possession time on the track is critical since the demand for train operations is very high and a long possession has a severe impact on the regular train schedule. We present an optimization model and investigate the maintenance schedules with and without the possession capacity constraint. In addition, we also integrate the social-economic cost related to the effects of the maintenance time to the variable possession cost into the optimization model. A numerical example is provided to illustrate the model.

Keywords: rail-track components, maintenance, optimal clustering, possession capacity

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Authors: Anne Schattel, Mitja Echim, Christof Büskens

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Trajectory planning for deep space missions has become a recent topic of great interest. Flying to space objects like asteroids provides two main challenges. One is to find rare earth elements, the other to gain scientific knowledge of the origin of the world. Due to the enormous spatial distances such explorer missions have to be performed unmanned and autonomously. The mathematical field of optimization and optimal control can be used to realize autonomous missions while protecting recourses and making them safer. The resulting algorithms may be applied to other, earth-bound applications like e.g. deep sea navigation and autonomous driving as well. The project KaNaRiA ('Kognitionsbasierte, autonome Navigation am Beispiel des Ressourcenabbaus im All') investigates the possibilities of cognitive autonomous navigation on the example of an asteroid mining mission, including the cruise phase and approach as well as the asteroid rendezvous, landing and surface exploration. To verify and test all methods an interactive, real-time capable simulation using virtual reality is developed under KaNaRiA. This paper focuses on the specific challenge of the guidance during the cruise phase of the spacecraft, i.e. trajectory optimization and optimal control, including first solutions and results. In principle there exist two ways to solve optimal control problems (OCPs), the so called indirect and direct methods. The indirect methods are being studied since several decades and their usage needs advanced skills regarding optimal control theory. The main idea of direct approaches, also known as transcription techniques, is to transform the infinite-dimensional OCP into a finite-dimensional non-linear optimization problem (NLP) via discretization of states and controls. These direct methods are applied in this paper. The resulting high dimensional NLP with constraints can be solved efficiently by special NLP methods, e.g. sequential quadratic programming (SQP) or interior point methods (IP). The movement of the spacecraft due to gravitational influences of the sun and other planets, as well as the thrust commands, is described through ordinary differential equations (ODEs). The competitive mission aims like short flight times and low energy consumption are considered by using a multi-criteria objective function. The resulting non-linear high-dimensional optimization problems are solved by using the software package WORHP ('We Optimize Really Huge Problems'), a software routine combining SQP at an outer level and IP to solve underlying quadratic subproblems. An application-adapted model of impulsive thrusting, as well as a model of an electrically powered spacecraft propulsion system, is introduced. Different priorities and possibilities of a space mission regarding energy cost and flight time duration are investigated by choosing different weighting factors for the multi-criteria objective function. Varying mission trajectories are analyzed and compared, both aiming at different destination asteroids and using different propulsion systems. For the transcription, the robust method of full discretization is used. The results strengthen the need for trajectory optimization as a foundation for autonomous decision making during deep space missions. Simultaneously they show the enormous increase in possibilities for flight maneuvers by being able to consider different and opposite mission objectives.

Keywords: deep space navigation, guidance, multi-objective, non-linear optimization, optimal control, trajectory planning.

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Authors: Akhmad F. K. Khitam, Yi Tai, Hsin-Yun Lee

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In the modern research of construction management, the goals of scheduling are not only to finish the project within the limited duration, but also to improve the impact of people and environment. Especially for the impact to the pedestrian and vehicles, the considerable social cost should be estimated in the total performance of a construction project. However, the site environment has many differences between projects. These interactions affect the requirement and goal of scheduling. It is difficult for schedule planners to quantify these interactions. Therefore, this study use 3D dynamic simulation technology to plan the schedule of the construction engineering projects that affect the current space users (i.e., the pedestrians and vehicles). The proposed model can help the project manager find out the optimal schedule to minimize the inconvenience brought to the space users. Besides, a roadwork project and a building renovation project were analyzed for the practical situation of engineering and operations. Then this study integrates the proper optimization algorithms and computer technology to establish a decision support model. The proposed model can generate a near-optimal schedule solution for project planners.

Keywords: scheduling, simulation, optimization, pedestrian and vehicle behavior

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Authors: Hoyeon Park, Kyoung-jae Kim

Abstract:

The product recommendation is a field of research that has received much attention in the recent information overload phenomenon. The proliferation of the mobile environment and social media cannot help but affect the results of the recommendation depending on how the factors of the user's situation are reflected in the recommendation process. Recently, research has been spreading attention to the context-aware recommender system which is to reflect user's contextual information in the recommendation process. However, until now, most of the context-aware recommender system researches have been limited in that they reflect the passive context of users. It is expected that the user will be able to express his/her contextual information through his/her active behavior and the importance of the context-aware recommender system reflecting this information can be increased. The purpose of this study is to propose a context-aware recommender system that can reflect the user's emotional state as an active context information to recommendation process. The context-aware recommender system is a recommender system that can make more sophisticated recommendations by utilizing the user's contextual information and has an advantage that the user's emotional factor can be considered as compared with the existing recommender systems. In this study, we propose a method to infer the user's emotional state, which is one of the user's context information, by using the user's facial expression data and to reflect it on the recommendation process. This study collects the facial expression data of a user who is looking at a specific product and the user's product preference score. Then, we classify the facial expression data into several categories according to the previous research and construct a model that can predict them. Next, the predicted results are applied to existing collaborative filtering with contextual information. As a result of the study, it was shown that the recommended results of the context-aware recommender system including facial expression information show improved results in terms of recommendation performance. Based on the results of this study, it is expected that future research will be conducted on recommender system reflecting various contextual information.

Keywords: context-aware, emotional state, recommender systems, business analytics

Procedia PDF Downloads 233

Authors: Feixiang Zhao, Shuangcheng Jia, Qian Li

Abstract:

High-precision measurement of the target’s position and size is one of the hotspots in the field of vision inspection. This paper proposes a three-dimensional object positioning and measurement method using a monocular camera and GPS, namely the Distance Area Number-New Minimize Projection Error (DAN-NMPE). Our algorithm contains two parts: DAN and NMPE; specifically, DAN is a picture sequence algorithm, NMPE is a relatively positive optimization algorithm, which greatly improves the measurement accuracy of the target’s position and size. Comprehensive experiments validate the effectiveness of our proposed method on a self-made traffic sign dataset. The results show that with the laser point cloud as the ground truth, the size and position errors of the traffic sign measured by this method are ± 5% and 0.48 ± 0.3m, respectively. In addition, we also compared it with the current mainstream method, which uses a monocular camera to locate and measure traffic signs. DAN-NMPE attains significant improvements compared to existing state-of-the-art methods, which improves the measurement accuracy of size and position by 50% and 15.8%, respectively.

Keywords: monocular camera, GPS, positioning, measurement

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Authors: E. Benga, T. Tengen, A. Alugongo

Abstract:

Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

Procedia PDF Downloads 383

Authors: M. S. Yalfani, J. Kohzadi, P. Ghadimi, S. Sobhani, M. Ghadimi

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The use of oil and water-soluble corrosion inhibitors has been established in Iranian oil and gas production systems for a long time. Imidazoline and its derivatives are being extensively used which are known as conventional corrosion inhibitors. This type of product has shown significant performance and low side effects, so that could monopolize the market of inhibitors in this region. However, the price growth of imidazolines, as well as the development of new lower-cost components with similar or even higher performance than imidazoline, have influenced the exclusive market of imidazoline-based products. During the latest years, pyridine and its derivatives have challenged imidazoline due to their remarkable anticorrosive properties and lower prices as well. Recently, we presented a formulated water-soluble inhibitor based on pyridine - an alkyl pyridine quaternary salt (APQS) - which could successfully pass all lab tests and eventually succeeded in being applied in an offshore sweet oil pipeline. The product was able to achieve high corrosion protection (> 90 %) with the LPR technique at low dosages of 15-25 ppm under severe corrosion conditions. Moreover, the lab test results showed that the APQS molecule is able to form a strong and persistent bond with the metal surface. The product was later nominated to be evaluated through a field trial in an offshore sweet oil pipeline where PH2S < 0.05 psi and CO2 is 6.4 mol%. The three-month trial - extended to six months- resulted in remarkable internal protection obtained by continuous injection of 10 ppm inhibitor, which was as low as 1 mpy measured by both weight loss corrosion coupons and online ER probes. In addition, no side effects, such as tight emulsion and stable foaming, were observed. The residual of the corrosion inhibitor was measured at the end of the pipeline to ensure the full coverage of the inhibitor throughout the pipeline. Eventually, these promising results were able to convince the end user to consider pyridine-based inhibitors as a reliable alternative to imidazoline.

Keywords: corrosion inhibitor, pyridine, sweet oil, pipeline, offshore

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Authors: Gloria Patricia Manurung

Abstract:

Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

Procedia PDF Downloads 232

Authors: Sanyka Banerjee, Saikat Nandi, P. K. Dan

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Synchronizers as an integral part of gearbox is a key element in the transmission system in automotive. The performance of synchronizer affects transmission efficiency and driving comfort. Synchronizing mechanism as a major component of transmission system must be capable of preventing vibration and noise in the gears. Gear shifting efficiency improvement with an aim to achieve smooth, quick and energy efficient power transmission remains a challenge for the automotive industry. Performance of the synchronizer is dependent on the features and characteristics of its sub-components and therefore analysis of the contribution of such characteristics is necessary. An important exercise involved is to identify all such characteristics or factors which are associated with the modeling and analysis and for this purpose the literature was reviewed, rather extensively, to study the mathematical models, formulated considering such. It has been observed that certain factors are rather common across models; however, there are few factors which have specifically been selected for individual models, as reported. In order to obtain a more realistic model, an attempt here has been made to identify and assimilate practically all possible factors which may be considered in formulating the model more comprehensively. A simulation study, formulated as a block model, for such analysis has been carried out in a reliable environment like MATLAB. Lower synchronization time is desirable and hence, it has been considered here as the output factors in the simulation modeling for evaluating transmission efficiency. An improved synchronizer model requires optimized values of sub-component design parameters. A parametric optimization utilizing Taguchi’s design of experiment based response data and their analysis has been carried out for this purpose. The effectiveness of the optimized parameters for the improved synchronizer performance has been validated by the simulation study of the synchronizer block model with improved parameter values as input parameters for better transmission efficiency and driver comfort.

Keywords: design of experiments, modeling, parametric optimization, simulation, synchronizer

Procedia PDF Downloads 316

Authors: Charles Chikwendu Okpala, Christopher Chukwutoo Ihueze

Abstract:

As a technique that reduces variation in a product by lessening the sensitivity of the design to sources of variation, rather than by controlling their sources, Taguchi Robust Design entails the designing of ideal goods, by developing a product that has minimal variance in its characteristics and also meets the desired exact performance. This paper examined the concept of the manufacturing approach and its application to brake pad product of an automotive parts manufacturing company. Although the firm claimed that only defects, excess inventory, and over-production were the few wastes that grossly affect their productivity and profitability, a careful study and analysis of their manufacturing processes with the application of Single Minute Exchange of Dies (SMED) tool showed that the waste of waiting is the fourth waste that bedevils the firm. The selection of the Taguchi L9 orthogonal array which is based on the four parameters and the three levels of variation for each parameter revealed that with a range of 2.17, that waiting is the major waste that the company must reduce in order to continue to be viable. Also, to enhance the company’s throughput and profitability, the wastes of over-production, excess inventory, and defects with ranges of 2.01, 1.46, and 0.82, ranking second, third, and fourth respectively must also be reduced to the barest minimum. After proposing -33.84 as the highest optimum Signal-to-Noise ratio to be maintained for the waste of waiting, the paper advocated for the adoption of all the tools and techniques of Lean Production System (LPS), and Continuous Improvement (CI), and concluded by recommending SMED in order to drastically reduce set up time which leads to unnecessary waiting.

Keywords: lean production system, single minute exchange of dies, signal to noise ratio, Taguchi robust design, waste

Procedia PDF Downloads 127