Search results for: production process optimization

Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Farhood Rismanchian, Seong Hyeon Park, Young Hoon Lee

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During the recent years, demand for healthcare services has dramatically increased. As the demand for healthcare services increases, so does the necessity of constructing new healthcare buildings and redesigning and renovating existing ones. Increasing demands necessitate the use of optimization techniques to improve the overall service efficiency in healthcare settings. However, high complexity of care processes remains the major challenge to accomplish this goal. This study proposes a method based on process mining results to address the high complexity of care processes and to find the optimal layout of the various medical centers in an emergency department. ProM framework is used to discover clinical pathway patterns and relationship between activities. Sequence clustering plug-in is used to remove infrequent events and to derive the process model in the form of Markov chain. The process mining results served as an input for the next phase which consists of the development of the optimization model. Comparison of the current ED design with the one obtained from the proposed method indicated that a carefully designed layout can significantly decrease the distances that patients must travel.

Keywords: Mixed Integer programming, Facility layout problem, Process Mining, Healthcare Operation Management

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Authors: Tobias Beyer, Christoph Friedrich

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Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

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Authors: Tomasz Robert Kuczerski

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The high complexity of the algorithm of the autonomous tandem detonator system creates an optimization problem due to the parallel operation of several machine states of the system. Many years of experience and classic analyses have led to a partially optimized model. Limitations on the energy resources of this class of autonomous systems make it necessary to search for more effective methods of optimisation. The use of the Quantum Approximate Optimization Algorithm (QAOA) in these studies shows the most promising results. With the help of multiple evaluations of several qubit quantum circuits, proper results of variable parameter optimization were obtained. In addition, it was observed that the increase in the number of assessments does not result in further efficient growth due to the increasing complexity of optimising variables. The tests confirmed the effectiveness of the QAOA optimization method.

Keywords: algorithm analysis, autonomous system, quantum optimization, tandem detonator

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Authors: Kang Zijian, Zhang Tingyu, Burra Venkata Durga Kumar

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This article investigates the challenges in memory migration during the live migration of virtual machines. We found three challenges probably existing in pre-copy technology. One of the main challenges is the challenge of downtime migration. Decrease the downtime could promise the normal work for a virtual machine. Although pre-copy technology is greatly decreasing the downtime, we still need to shut down the machine in order to finish the last round of data transfer. This paper provides an optimization scheme for the problems existing in pro-copy technology, mainly the optimization of the dirty page migration mechanism. The typical pre-copy technology copy n-1th’s dirty pages in nth turn. However, our idea is to create a double iteration method to solve this problem.

Keywords: virtual machine, pre-copy technology, memory migration process, downtime, dirty pages migration method

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Authors: Ľubomír Šooš, Peter Križan, Juraj Beniak, Miloš Matúš

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The success of introducing a new product on the market is the new principle of production, or progressive design, improved efficiency or high quality of manufactured products. Proportionally with the growth of interest in press-biofuels - pellets or briquettes, is also growing interest in the new design better, more efficiently machines produce pellets, briquettes or granules completely new shapes. Our department has for years dedicated to the development of new highly productive designs pressing machines and new optimized press-biofuels. In this field, we have more than 40 national and international patents. The aim of paper is description of the introduction of a new principle pelleting mill and the description of his process of research, development, manufacturing and testing to deployment into production.

Keywords: compacting process, pellets mill, design, new conception, press-biofuels, patent, waste

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Authors: Bashayer Al-Enezi, Budoor Al-Sabti, Eman Al-Durai, Fatmah Kalban, Meshael Ahmed

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Production planning and control principles are concerned with planning, controlling and balancing all aspects of manufacturing including raw materials, finished goods, production schedules, and equipment requirements. Hence, an effective production planning and control system is very critical to the success of any factory. This project will focus on the application of production planning and control principles on “The National Canned Food Production and Trading Company (NCFP)” factory to find problems or areas for improvement.

Keywords: production planning, operations improvement, inventory management, National Canned Food Production and Trading Company (NCFP)

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Authors: Szymon Kowieski, Zygmunt Mikno

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The study involved the optimization of process parameters during resistance spot welding of Al-coated martensitic boron steel 22MnB5, applied in hot stamping, performed using a programme with a multiple current impulse mode and a programme with variable pressure force. The aim of this research work was to determine the possibilities of a growth in welded joint strength and to identify the expansion of a welding lobe. The process parameters were adjusted on the basis of welding process simulation and confronted with experimental data. 22MnB5 steel is known for its tendency to obtain high hardness values in weld nuggets, often leading to interfacial failures (observed in the study-related tests). In addition, during resistance spot welding, many production-related factors can affect process stability, e.g. welding lobe narrowing, and lead to the deterioration of quality. Resistance spot welding performed using the above-named welding programme featuring 3 levels of force made it possible to achieve 82% of welding lobe extension. Joints made using the multiple current impulse program, where the total welding time was below 1.4s, revealed a change in a peeling mode (to full plug) and an increase in weld tensile shear strength of 10%.

Keywords: 22MnB5, hot stamping, interfacial fracture, resistance spot welding, simulation, single lap joint, welding lobe

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Authors: Jyothirmayee Pola

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Ideally, a test-driven development (TDD) or agile or any other process should be able to define and implement performance, scalability, and reliability (PSR) of the product with a higher quality of service (QOS) and should have the ability to fix any PSR issues with lesser cost before it hits the production. Most PSR test strategies for new product introduction (NPI) include assumptions about production load requirements but never accurate. NPE (New product Enhancement) include assumptions for new features that are being developed whilst workload distribution for older features can be derived by analyzing production transactions. This paper talks about how to shift left PSR towards design phase of release management process to get better QOS w.r.t PSR for any product under development. It also explains the ROI for future customer onboarding both for Service Oriented Architectures (SOA) and Microservices architectures and how to define PSR requirements.

Keywords: component PSR, performance engineering, performance tuning, reliability, return on investment, scalability, system PSR

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Authors: E. P. Doku-Asare, A. Essuman

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The materials used for the production of holders are mainly metals and plastic, and these materials are difficult and expensive to process; therefore, the need to explore other materials such as clay for the production of holders. Clay is a viable material for the production of holders due to its plastic nature. Using ceramic materials as a medium for the production of holders does not only serve its purpose but also economically cheaper since the material is mined in Ghana. The study also examines the aesthetic nature of the holders due to the properties found in the material used. Six holders were chosen and were made in a manner that would not take a lot of space. They are Pin holders, Paper holders, Penholders, Paperweight and Umbrella holders. The production technique employed in the execution of this project were the slab method, throwing, and press mold. Results indicated that ceramic holders are durable and long-lasting and can serve the purpose of metallic and plastic holders. The study also found that clay holders are durable due to the fact that clay is from a natural source which ensures permanence and resistance to stress. It is recommended that press molds be used in the production of holders. Clay holders last longer due to the useful properties of clay including very high hardness and strength.

Keywords: ceramics, interior design, Ghana, production technique

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Authors: Peerawat Khongkliang, Prawit Kongjan, Tsuyoshi Imai, Poonsuk Prasertsan, Sompong O-Thong

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A two-stage thermophilic fermentation and electrohydrogenesis process was used to convert cassava starch processing wastewater into hydrogen gas. Maximum hydrogen yield from fermentation stage by Thermoanaerobacterium thermosaccharolyticum PSU-2 was 248 mL H2/g-COD at optimal pH of 6.5. Optimum hydrogen production rate of 820 mL/L/d and yield of 200 mL/g COD was obtained at HRT of 2 days in fermentation stage. Cassava starch processing wastewater fermentation effluent consisted of acetic acid, butyric acid and propionic acid. The effluent from fermentation stage was used as feedstock to generate hydrogen production by microbial electrolysis cell (MECs) at an applied voltage of 0.6 V in second stage with additional 657 mL H2/g-COD was produced. Energy efficiencies based on electricity needed for the MEC were 330 % with COD removals of 95 %. The overall hydrogen yield was 800-900 mL H2/g-COD. Microbial community analysis of electrohydrogenesis by DGGE shows that exoelectrogens belong to Acidiphilium sp., Geobacter sulfurreducens and Thermincola sp. were dominated at anode. These results show two-stage thermophilic fermentation, and electrohydrogenesis process improved hydrogen production performance with high hydrogen yields, high gas production rates and high COD removal efficiency.

Keywords: cassava starch processing wastewater, biohydrogen, thermophilic fermentation, microbial electrolysis cell

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Authors: Seok Hong Min, Tae Kwon Ha

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With increasing demands for high performance materials, intensive interest on the Ti has been focused. Especially, low cost production process of Ti has been extremely necessitated from wide parts and various industries. Tetrachloride (TiCl₄) is produced by fluidized bed using high TiO₂ feedstock and used as an intermediate product for the production of metal titanium sponge. Reduction of TiCl₄ is usually conducted by Kroll process using magnesium as a reduction reagent, producing metallic Ti in the shape of sponge. The process is batch type and takes very long time including post processes treating sponge. As an alternative reduction reagent, hydrogen in the state of plasma has long been strongly recommended. Experimental confirmation has not been completely reported yet and more strict analysis is required. In the present study, hydrogen plasma reduction process has been thermodynamically analyzed focusing the effects of temperature, pressure and concentration. All thermodynamic calculations were performed using the FactSage® thermodynamical software.

Keywords: TiCl₄, titanium, hydrogen, plasma, reduction, thermodynamic calculation

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Authors: Zoe Chang, Max Williams, Gautham Das

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The purpose of this study is to evaluate the incorporation of hemp fibers (HF) in concrete. Hemp fiber reinforced concrete (HFRC) is becoming more popular as an alternative for regular mix designs. This study was done to evaluate the compressive strength of HFRC regarding mix procedure. Hemp fibers were obtained from the manufacturer and hand-processed to ensure uniformity in width and length. The fibers were added to the concrete as both wet and dry mixes to investigate and optimize the mix design process. Results indicated that the dry mix had a compressive strength of 1157 psi compared to the wet mix of 985 psi. This dry mix compressive strength was within range of the standard mix compressive strength of 1533 psi. The statistical analysis revealed that the mix design process needs further optimization and uniformity concerning the addition of HF. Regression analysis revealed the standard mix design had a coefficient of 0.9 as compared to the dry mix of 0.375, indicating a variation in the mixing process. While completing the dry mix, the addition of plain hemp fibers caused them to intertwine, creating lumps and inconsistency. However, during the wet mixing process, combining water and hemp fibers before incorporation allows the fibers to uniformly disperse within the mix; hence the regression analysis indicated a better coefficient of 0.55. This study concludes that HRFC is a viable alternative to regular mixes; however, more research surrounding its characteristics needs to be conducted.

Keywords: hemp fibers, hemp reinforced concrete, wet & dry, freeze thaw testing, compressive strength

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Authors: Riffi Mohammed Amine

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A cloud is made up of small particles of liquid water or ice suspended in the atmosphere, which generally do not reach the ground. Various methods are used to classify clouds. This article focuses specifically on a technique known as particle swarm optimization (PSO), an AI approach inspired by the collective behaviors of animals living in groups, such as schools of fish and flocks of birds, and a method used to solve complex classification and optimization problems with approximate solutions. The proposed technique was evaluated using a series of second-generation METOSAT images taken by the MSG satellite. The acquired results indicate that the proposed method gave acceptable results.

Keywords: remote sensing, particle swarm optimization, clouds, meteorological image

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Authors: K. Y. Tseng, C. Y. Wu

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This paper employs a heuristic algorithm to solve engineering problems including truss structure optimization and optimal chiller loading (OCL) problems. Two different type algorithms, real-valued differential evolution (DE) and modified binary differential evolution (MBDE), are successfully integrated and then can obtain better performance in solving engineering problems. In order to demonstrate the performance of the proposed algorithm, this study adopts each one testing case of truss structure optimization and OCL problems to compare the results of other heuristic optimization methods. The result indicates that the proposed algorithm can obtain similar or better solution in comparing with previous studies.

Keywords: differential evolution, Truss structure optimization, optimal chiller loading, modified binary differential evolution

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Authors: L. Abdou, O. Taibaoui, A. Moumen, A. Talib Ahmed

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This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum.

Keywords: distributed system, OS-CFAR system, independent sensors, simulating annealing

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Authors: Aman Sharma, Sonali Sengupta

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The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

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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: Kwan Hee Han

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In today’s business environments, frequent change of customer requirements is a tough challenge to manufacturing company. To cope with these challenges, a production planning and scheduling (PP&S) function might be established to provide accountability for both customer service and operational efficiency. Nowadays, many manufacturing firms have utilized PP&S software solutions to generate a realistic production plan and schedule to adapt to external changes efficiently. However, companies which consider the introduction of PP&S software solution, still have difficulties for selecting adequate solution to meet their specific needs. Since the task of PP&S is the one of major building blocks of SCM (Supply Chain Management) architecture, which deals with short term decision making in the production process of SCM, it is needed that the functionalities of PP&S should be analysed within the whole SCM process. The aim of this paper is to analyse the PP&S functionalities and its system architecture from the SCM perspective by using the criteria of level of planning hierarchy, major 4 SCM processes and problem-solving approaches, and finally propose a classification framework of PP&S solutions to facilitate the comparison among various commercial software solutions. By using proposed framework, several major PP&S solutions are classified and positioned according to their functional characteristics in this paper. By using this framework, practitioners who consider the introduction of computerized PP&S solutions in manufacturing firms can prepare evaluation and benchmarking sheets for selecting the most suitable solution with ease and in less time.

Keywords: production planning, production scheduling, supply chain management, the advanced planning system

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Authors: Gabriel Wosiak, Felipe Staciaki, Eryka Nobrega, Ernesto Pereira

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Hydrogen is an energy carrier with potential applications in various industries. Alkaline electrolysis is a commonly used method for hydrogen production; however, its energy cost remains relatively high compared to other methods. This is due in part to interfacial pH changes that occur during the electrolysis process. Interfacial pH changes refer to the changes in pH that occur at the interface between the cathode electrode and the electrolyte solution. These changes are caused by the electrochemical reactions at both electrodes, which consume or produces hydroxide ions (OH-) from the electrolyte solution. This results in an important change in the local pH at the electrode surface, which can have several impacts on the energy consumption and durability of electrolysers. One impact of interfacial pH changes is an increase in the overpotential required for hydrogen production. Overpotential is the difference between the theoretical potential required for a reaction to occur and the actual potential that is applied to the electrodes. In the case of water electrolysis, the overpotential is caused by a number of factors, including the mass transport of reactants and products to and from the electrodes, the kinetics of the electrochemical reactions, and the interfacial pH. An increase in the interfacial pH at the anode surface in alkaline conditions can lead to an increase in the overpotential for hydrogen production. This is because the lower local pH makes it more difficult for the hydroxide ions to be oxidized. As a result, there is an increase in the required energy to the process occur. In addition to increasing the overpotential, interfacial pH changes can also lead to the degradation of the electrodes. This is because the lower pH can make the electrode more susceptible to corrosion. As a result, the electrodes may need to be replaced more frequently, which can increase the overall cost of water electrolysis. The method presented in the paper addresses the issue of interfacial pH changes by using a cell design with a different cell design, introducing the electrode asymmetry. This design helps to mitigate the pH gradient at the anode/electrolyte interface, which reduces the overpotential and improves the energy efficiency of the electrolyser. The method was tested using a multivariate approach in both laboratory and industrial current density conditions and validated the results with numerical simulations. The results demonstrated a clear improvement (11.6%) in energy efficiency, providing an important contribution to the field of sustainable energy production. The findings of the paper have important implications for the development of cost-effective and sustainable hydrogen production methods. By mitigating interfacial pH changes, it is possible to improve the energy efficiency of alkaline electrolysis and make it a more competitive option for hydrogen production.

Keywords: electrolyser, interfacial pH, numerical simulation, optimization, asymmetric cell

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Authors: Dávid Csercsik, Péter Kádár

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In the case of the proposed method, the problem is parallelized by considering multiple possible mode of operation profiles, which determine the range in which the generators operate in each period. For each of these profiles, the optimization is carried out independently, and the best resulting dispatch is chosen. For each such profile, the resulting problem is a quadratic programming (QP) problem with a potentially negative definite Q quadratic term, and constraints depending on the actual operation profile. In this paper we analyze the performance of available MATLAB optimization methods and solvers for the corresponding QP.

Keywords: optimization, MATLAB, quadratic programming, economic dispatch

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Authors: Ganesh Dattatraya Saratale, Min Kyu Oh

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Rice straw is one of the most abundant lignocellulosic waste materials and its annual production is about 731 Mt in the world. This study treats the subject of effective utilization of this waste biomass for biofuels production. We have showed a comparative assessment of numerous pretreatment strategies for rice straw, comprising of major physical, chemical and physicochemical methods. Among the different methods employed for pretreatment alkaline pretreatment in combination with sodium chlorite/acetic acid delignification found efficient pretreatment with significant improvement in the enzymatic digestibility of rice straw. A cellulase dose of 20 filter paper units (FPU) released a maximum 63.21 g/L of reducing sugar with 94.45% hydrolysis yield and 64.64% glucose yield from rice straw, respectively. The effects of different pretreatment methods on biomass structure and complexity were investigated by FTIR, XRD and SEM analytical techniques. Finally the enzymatic hydrolysate of rice straw was used for ethanol production using developed Saccharomyces cerevisiae SR8. The developed yeast strain enabled efficient fermentation of xylose and glucose and produced higher ethanol production. Thus development of bioethanol production from lignocellulosic waste biomass is generic, applicable methodology and have great implication for using ‘green raw materials’ and producing ‘green products’ much needed today.

Keywords: rice straw, pretreatment, enzymatic hydrolysis, FPU, Saccharomyces cerevisiae SR8, ethanol fermentation

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Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Mandeep Kaur, Fatehgarh Sahib

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The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system.

Keywords: economic load dispatch, genetic algorithm, generating units, multiobjective optimization, weighting method

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Authors: Gaylord K. Booto, Marinelli Giuseppe, Helge Brattebø, Rolf A. Bohne

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Emissions reduction has emerged among the principal targets in the process of planning and designing road alignments today. Intelligent road design methods that can result in optimized alignment constitute concrete and innovative responses towards better alternatives and more sustainable road infrastructures. As the largest amount of emissions of road infrastructures occur in the operation stage, it becomes very important to consider traffic weight and distribution in alignment design process. This study analyzes the effects of four traffic factors (i.e. operating speed, vehicle category, technology and fuel type) on adjusting the vertical alignment of a given road, using optimization techniques. Further, factors’ effects are assessed qualitatively and quantitatively, and the emission profiles of resulting alignment alternatives are compared.

Keywords: alignment adjustment, emissions reduction, optimization, traffic-oriented

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Authors: Thanapat Chaireongsirikul, Apichit Svang-Ariyaskul

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An analysis of mass balance, energy performance, and environmental impact assessment were performed to evaluate bioethanol production in Thailand. Thailand is an agricultural country. Thai government plans to increase the use of alternative energy to 20 percent by 2022. One of the primary campaigns is to promote a bioethanol production from abundant biomass resources such as bitter cassava, molasses and sugarcane. The bioethanol production is composed of three stages: cultivation, pretreatment, and bioethanol conversion. All of mass, material, fuel, and energy were calculated to determine the environmental impact of three types of bioethanol production: bioethanol production from cassava (CBP), bioethanol production from molasses (MBP), and bioethanol production from rice straw (RBP). The results showed that bioethanol production from cassava has the best environmental performance. CBP contributes less impact when compared to the other processes.

Keywords: bioethanol production, biofuel, LCA, chemical engineering

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Authors: Chayonnat Thanamun, Kreangkrai Maneeintr

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For petroleum industry, polymer flooding is the one of the main methods in enhanced oil recovery (EOR) that is used water-soluble polymer such as partially hydrolyzed polyacrylamide (HPAM) to increase oil production. It is added to the flooding water to improve the mobility ratio in the flooding process. During the polymer flooding process, water is produced as a by-product along with oil and gas production. This produced water is a mixture of inorganic and organic compound. Moreover, produced water is more difficult to treat than that from water flooding. In this work, the effect of HPAM residue on the wastewater treatment from polymer flooding is studied. Polyaluminium chloride (PAC) is selected to use as a flocculant. Therefore, the objective of this study is to evaluate the effect of polymer residues in produced water on the wastewater treatment by using PAC. The operating parameters of this study are flocculant dosage ranging from 300,400 and 500 mg/L temperature from 30-50 Celsius degree and HPAM concentrations from 500, 1000 and 2000 mg/L. Furthermore, the turbidity, as well as total suspended solids (TSS), are also studied. The results indicated that with an increase in HPAM concentration, the TSS and turbidity increase gradually with the increasing of coagulant dosage under the same temperature. Also, the coagulation-flocculation performance is improved with the increasing temperature. This can be applied to use in the wastewater treatment from oil production before this water can be injected back to the reservoir.

Keywords: wastewater treatment, petroleum production, polyaluminium chloride, polyacrylamide

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Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

Abstract:

Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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Authors: Nora Arbaoui, Rachid Tadili, Ilham Ihoume

Abstract:

To improve the climatic conditions and increase production in the greenhouse during the winter season under the Mediterranean climate, this thesis project proposes a design of an integrated and autonomous solar system for heating, cooling, and conservation of production in an agricultural greenhouse. To study the effectiveness of this system, experiments are conducted in two similar agricultural greenhouses oriented north-south. The first greenhouse is equipped with an active solar system integrated into the double glazing of the greenhouse’s roof, while the second greenhouse has no system, it serves as a controlled greenhouse for comparing thermal and agronomic performance The solar system allowed for an average increase in the indoor temperature of the experimental greenhouse of 6°C compared to the outdoor environment and 4°C compared to the control greenhouse. This improvement in temperature has a favorable effect on the plants' climate and subsequently positively affects their development, quality, and production.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

Procedia PDF Downloads 98