Search results for: production scheduling.

Authors: L. Abdelmalek, M. Zerikat, M. Rahli

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In this paper, we present a comparative study of the genetic algorithms and Hessian-s methods for optimal research of the active powers in an electric network of power. The objective function which is the performance index of production of electrical energy is minimized by satisfying the constraints of the equality type and inequality type initially by the Hessian-s methods and in the second time by the genetic Algorithms. The results found by the application of AG for the minimization of the electric production costs of power are very encouraging. The algorithms seem to be an effective technique to solve a great number of problems and which are in constant evolution. Nevertheless it should be specified that the traditional binary representation used for the genetic algorithms creates problems of optimization of management of the large-sized networks with high numerical precision.

Keywords: Genetic algorithm, Flow of optimum loadimpedances, Hessians method, Optimal distribution.

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Authors: Kamal K. Bharadwaj, Basheer M. Al-Maqaleh

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In the recent past, there has been an increasing interest in applying evolutionary methods to Knowledge Discovery in Databases (KDD) and a number of successful applications of Genetic Algorithms (GA) and Genetic Programming (GP) to KDD have been demonstrated. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski & Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations, in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the 'If P Then D' part of the CPR expresses important information, while the Unless C part acts only as a switch and changes the polarity of D to ~D. This paper presents a classification algorithm based on evolutionary approach that discovers comprehensible rules with exceptions in the form of CPRs. The proposed approach has flexible chromosome encoding, where each chromosome corresponds to a CPR. Appropriate genetic operators are suggested and a fitness function is proposed that incorporates the basic constraints on CPRs. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Keywords: Censored Production Rule, Data Mining, MachineLearning, Evolutionary Algorithms.

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Authors: Lobat Taghavi, Najaf Hedayat

Abstract:

Renewable water resources are crucial production variables in arid and semi-arid regions where intensive agriculture is practiced to meet ever-increasing demand for food and fiber. This is crucial for the Dez and Moghan command areas where water delivery problems and adverse environmental issues are widespread. This paper aims to identify major problems areas using on-farm surveys of 200 farmers, agricultural extensionists and water suppliers which was complemented by secondary data and field observations during 2010- 2011 cultivating season. The SPSS package was used to analyze and synthesis data. Results indicated inappropriate canal operations in both schemes, though there was no unanimity about the underlying causes. Inequitable and inflexible distribution was found to be rooted in deficient hydraulic structures particularly in the main and secondary canals. The inadequacy and inflexibility of water scheduling regime was the underlying causes of recurring pest and disease spread which often led to the decline of crop yield and quality, although these were not disputed, the water suppliers were not prepared to link with the deficiencies in the operation of the main and secondary canals. They rather attributed these to the prevailing salinity; alkalinity, water table fluctuations and leaching of the valuable agro-chemical inputs from the plants- route zone with farreaching consequences. Examples of these include the pollution of ground and surface resources due to over-irrigation at the farm level which falls under the growers- own responsibility. Poor irrigation efficiency and adverse environmental problems were attributed to deficient and outdated farming practices that were in turn rooted in poor extension programs and irrational water charges.

Keywords: water delivery, inequity, inflexibility, conflicts, environmental impact, Dez and Moghan

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Authors: Duan Huanyun, Xu Rui, Li Jianchang, Yuan Yage, Wang Qiuxia, Nomana Intekhab Hadi

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BioEnergy is an archetypal appropriate technology and alternate source of energy in rural areas of China, and can meet the basic need for cooking fuel in rural areas. The paper introduces with an alternate mean of research that can accelerate the biogas energy production. Tithonia diversifolia or the Tree marigold can be hailed as mesophillic anaerobic digestion to increase the production of more Bioenergy. Tithonia diversifolia is very native to Mexico and Central America, which can be served as ornamental plants- green manure and can prevent soil erosion. Tithonia diversifolia is widely grown and known to Asia, Africa, America and Australia as well. Nowadays, Considering China’s geographical condition it is found that Tithonia diversifolia is widely growing plant in the many tropical and subtropical regions of southern Yunnan- which can have great usage in accelerating and increasing the Bioenergy production technology. The paper discussed aiming at proving possibility that Tithonia diversifolia can be applied in biogas fermentation and its biogas production potential, the research carried experiment on Tithonia diversifolia biogas fermentation under the mesophilic condition (35 Celsius Degree). The result revealed that Tithonia diversifolia can be used as biogas fermentative material, and 6% concentration can get the best biogas production, with the TS biogas production rate 656mL/g and VS biogas production rate 801mL/g. It is well addressed that Tithonia diversifolia grows wildly in 53 Counties and 9 cities of Yunnan Province, which mainly grows in form of the road side plants, the edge of the field, countryside, forest edge, open space; of which demersum-natures can form dense monospecific beds -causing serious harm to agricultural production landforms threatening the ecological system as a potentially harmful exotic plant. There are also found the three types of invasive daisy alien plants -Eupatorium adenophorum, Eupatorium Odorata and Tithonia diversifolia in Yunnan Province of China-among them the Tithonia diversifolia is responsible for causing serious harm to agricultural production. In this paper we have designed the experimental explanation of Biogas energy production that requires anaerobic environment and some microbes; Tithonia diversifolia plant has been taken into consideration while carrying experiments and with successful resulting of generating more BioEnergy emphasizing on the practical applications of Tithonia diversifolia. This paper aims at- to find a new mechanism to provide a more scientific basis for the development of this plant herbicides in Biogas energy and to improve the utilization throughout the world as well.

Keywords: Biogas Energy Production, Tithonia diversifolia, Energy Development, Ecological Agriculture, Eupatorium adenophorum, Eupatorium odorata, Anaerobic Fermentation, Biogas Production Potential, Mesopilic Fermentation.

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Authors: Z. Soleymani, M. Amirzadeh

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Quality Function Deployment (QFD) was developed in 1960 in Japan and introduced in 1983 in America and Europe. The paper presents a real application of this technique in a way that the method of applying QFD in design and production aero fuel pumps has been considered. While designing a product and in order to apply system engineering process, the first step is identification customer needs then its transition to engineering parameters. Since each change in deign after production process leads to extra human costs and also increase in products quality risk, QFD can make benefits in sale by meeting customer expectations. Since the needs identified as well, the use of QFD tool can lead to increase in communications and less deviation in design and production phases, finally it leads to produce the products with defined technical attributes.

Keywords: Customer voice, engineering parameters, QFD, gear pump.

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Authors: M. Safa, S. Samarasinghe

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An artificial neural network (ANN) approach was used to model the energy consumption of wheat production. This study was conducted over 35,300 hectares of irrigated and dry land wheat fields in Canterbury in the 2007-2008 harvest year.1 In this study several direct and indirect factors have been used to create an artificial neural networks model to predict energy use in wheat production. The final model can predict energy consumption by using farm condition (size of wheat area and number paddocks), farmers- social properties (education), and energy inputs (N and P use, fungicide consumption, seed consumption, and irrigation frequency), it can also predict energy use in Canterbury wheat farms with error margin of ±7% (± 1600 MJ/ha).

Keywords: Artificial neural network, Canterbury, energy consumption, modelling, New Zealand, wheat.

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Authors: Ludovic Favre, Thibaut M. Schafer, Jean-Luc Robyr, Elena-Lavinia Niederhäuser

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This paper presents an optimization method based on genetic algorithm for the energy management inside buildings developed in the frame of the project Smart Living Lab (SLL) in Fribourg (Switzerland). This algorithm optimizes the interaction between renewable energy production, storage systems and energy consumers. In comparison with standard algorithms, the innovative aspect of this project is the extension of the smart regulation over three simultaneous criteria: the energy self-consumption, the decrease of greenhouse gas emissions and operating costs. The genetic algorithm approach was chosen due to the large quantity of optimization variables and the non-linearity of the optimization function. The optimization process includes also real time data of the building as well as weather forecast and users habits. This information is used by a physical model of the building energy resources to predict the future energy production and needs, to select the best energetic strategy, to combine production or storage of energy in order to guarantee the demand of electrical and thermal energy. The principle of operation of the algorithm as well as typical output example of the algorithm is presented.

Keywords: Building’s energy, control system, energy management, modelling, genetic optimization algorithm, renewable energy, greenhouse gases, energy storage.

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Authors: D. P. Sharma, A. Chaturvedi, G.Purohit , R.Shivarudraswamy

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In today scenario, to meet enhanced demand imposed by domestic, commercial and industrial consumers, various operational & control activities of Radial Distribution Network (RDN) requires a focused attention. Irrespective of sub-domains research aspects of RDN like network reconfiguration, reactive power compensation and economic load scheduling etc, network performance parameters are usually estimated by an iterative process and is commonly known as load (power) flow algorithm. In this paper, a simple mechanism is presented to implement the load flow analysis (LFA) algorithm. The reported algorithm utilizes graph theory principles and is tested on a 69- bus RDN.

Keywords: Radial Distribution network, Graph, Load-flow, Array.

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Authors: Roman Ružarovský, Radovan Holubek, Peter Košťál

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The current trend of increasing quality and demands of the final product is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. The intelligent manufacturing paradigm includes a new approach to production system structure design. Intelligent behaviors are based on the monitoring of important parameters of system and its environment. The flexible reaction to changes. The realization and utilization of this design paradigm as an "intelligent manufacturing system" enables the flexible system reaction to production requirement as soon as environmental changes too. Results of these flexible reactions are a smaller layout space, be decreasing of production and investment costs and be increasing of productivity. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings.

Keywords: Sensory equipment, intelligent manufacturing systems, manufacturing process, control system, smart automation.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: Chung-Woon Park, Jungwoo Lee, Jong-Tae Lim

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In this paper, we propose a novel limited feedback scheme for task planning with service robots. Instead of sending the full service robot state information for the task planning, the proposed scheme send the best-M indices of service robots with a indicator. With the indicator, the proposed scheme significantly reduces the communication overhead for task planning as well as mitigates the system performance degradation in terms of the utility. In addition, we analyze the system performance of the proposed scheme and compare the proposed scheme with the other schemes.

Keywords: Task Planning, Service Robots, Limited Feedback, Scheduling

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Authors: T. Häfele, J. Kaspar, M. Vielhaber, W. Calles, J. Griebsch

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The demand for an increasing diversification of the product spectrum associated with the current huge customization desire and subsequently the decreasing unit quantities of each production lot is gaining more and more importance within a great variety of industrial branches, e.g. automotive industry. Nevertheless, traditional product development and production processes (molding, extrusion) are already reaching their limits or fail to address these trends of a flexible and digitized production in view of a product variability up to lot size one. Thus, upcoming innovative production concepts like the additive manufacturing technology basically create new opportunities with regard to extensive potentials in product development (constructive optimization) and manufacturing (economic individualization), but mostly suffer from insufficient strength regarding structural components. Therefore, this contribution presents an innovative technological and procedural conception of a hybrid additive manufacturing process (fiber-reinforced sandwich structures based on selective laser sintering technology) to overcome these current structural weaknesses, and consequently support the design of complex lightweight components.

Keywords: Additive manufacturing, fiber-reinforced plastics, hybrid design, lightweight design.

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Authors: S. Homrossukon, W. Parinyasart

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This is an applied research to propose the method for price quotation for a contract electronics manufacturer. It has had a precise price quoting method but such method could not quickly provide a result as the customer required. This reduces the ability of company to compete in this kind of business. In this case, the cause of long time quotation process was analyzed. A lot of product features have been demanded by customer. By checking routine processes, it was found that high fraction of quoting time was used for production time estimating which has effected to the manufacturing or production cost. Then the historical data of products including types, number of components, assembling method, and their assembling time were used to analyze the key components affecting to production time. The price quoting model then was proposed. The implementation of proposed model was able to remarkably reduce quoting time with an acceptable required precision.

Keywords: Price quoting, Contract manufacturer, Stepwise technique, Best subset technique.

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Authors: Ružarovský, Roman, Danišová, Nina, Velíšek, Karol

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In this contribution is presented a complex design of individual objects identification in the workplace of intelligent assembly cell. Intelligent assembly cell is situated at Institute of Manufacturing Systems and Applied Mechanics and is used for pneumatic actuator assembly. Pneumatic actuator components are pneumatic roller, cover, piston and spring. Two identification objects alternatives for assembly are designed in the workplace of industrial robot. In the contribution is evaluated and selected suitable alternative for identification – 2D codes reader. The complex design of individual object identification is going out of intelligent manufacturing systems knowledge. Intelligent assembly and manufacturing systems as systems of new generation are gradually loaded in to the mechanical production, when they are removeing human operation out of production process and they also short production times.

Keywords: system, cell, intelligent, mechanics, device

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Authors: Masaki Tajima, Kenji Imou, Shinya Yokoyama

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It was determined that woody biomass and livestock excreta can be utilized as hydrogen resources and hydrogen produced from such sources can be used to fill fuel cell vehicles (FCVs) at hydrogen stations. It was shown that the biomass transport costs for hydrogen production may be reduced the costs for co-generation. In the Tokyo Metropolitan Area, there are only a few sites capable of producing hydrogen from woody biomass in amounts greater than 200 m3/h-the scale required for a hydrogen station to be operationally practical. However, in the case of livestock excreta, it was shown that 15% of the municipalities in this area are capable of securing sufficient biomass to be operationally practical for hydrogen production. The differences in feasibility of practical operation depend on the type of biomass.

Keywords: Biomass Resources, Hydrogen Production, Hydrogen Station, Transport Cost.

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Authors: O. Zimbili, W. Salim, M. Ndambuki

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Construction and Demolition (C&D) wastes contribute the highest percentage of wastes worldwide (75%). Furthermore, ceramic materials contribute the highest percentage of wastes within the C&D wastes (54%). The current option for disposal of ceramic wastes is landfill. This is due to unavailability of standards, avoidance of risk, lack of knowledge and experience in using ceramic wastes in construction. The ability of ceramic wastes to act as a pozzolanic material in the production of cement has been effectively explored. The results proved that temperatures used in the manufacturing of these tiles (about 900⁰C) are sufficient to activate pozzolanic properties of clay. They also showed that, after optimization (11-14% substitution); the cement blend performs better, with no morphological difference between the cement blended with ceramic waste, and that blended with other pozzolanic materials. Sanitary ware and electrical insulator porcelain wastes are some wastes investigated for usage as aggregates in concrete production. When optimized, both produced good results, better than when natural aggregates are used. However, the research on ceramic wastes as partial substitute for fine aggregates or cement has not been overly exploited as the other areas. This review has been concluded with focus on investigating whether ceramic wall tile wastes used as partial substitute for cement and fine aggregates could prove to be beneficial since the two materials are the most high-priced during concrete production.

Keywords: Blended, morphological, pozzolanic properties, waste.

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Authors: Wen-Lung Huang, Shih-Pin Chen

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This paper investigates the optimization problem of multi-product aggregate production planning (APP) with fuzzy data. From a comprehensive viewpoint of conserving the fuzziness of input information, this paper proposes a method that can completely describe the membership function of the performance measure. The idea is based on the well-known Zadeh-s extension principle which plays an important role in fuzzy theory. In the proposed solution procedure, a pair of mathematical programs parameterized by possibility level a is formulated to calculate the bounds of the optimal performance measure at a . Then the membership function of the optimal performance measure is constructed by enumerating different values of a . Solutions obtained from the proposed method contain more information, and can offer more chance to achieve the feasible disaggregate plan. This is helpful to the decision-maker in practical applications.

Keywords: fuzzy data, aggregate production planning, membership function, parametric programming

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Authors: Achim Kampker, Christoph Deutskens, Heiner Hans Heimes, Mathias Ordung, Felix Optehostert

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In the past years electric mobility became part of a public discussion. The trend to fully electrified vehicles instead of vehicles fueled with fossil energy has notably gained momentum. Today nearly every big car manufacturer produces and sells fully electrified vehicles, but electrified vehicles are still not as competitive as conventional powered vehicles. As the traction battery states the largest cost driver, lowering its price is a crucial objective. In addition to improvements in product and production processes a nonnegligible, but widely underestimated cost driver of production can be found in logistics, since the production technology is not continuous yet and neither are the logistics systems. This paper presents an approach to evaluate cost factors on different designs of load carrier systems. Due to numerous interdependencies, the combination of costs factors for a particular scenario is not transparent. This is effecting actions for cost reduction negatively, but still cost reduction is one of the major goals for simultaneous engineering processes. Therefore a concurrent and phase appropriate cost valuation method is necessary to serve cost transparency. In this paper the four phases of this cost valuation method are defined and explained, which based upon a new approach integrating the logistics development process in to the integrated product and process development.

Keywords: Research and development, technology and Innovation, lithium-ion-battery production, load carrier development process, cost valuation method.

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Authors: R. Guliyev

Abstract:

The enhanced need for food items is receiving more importance due to a gradual increase in the world population and, in this scenario, fertilizers play a very important role in agriculture. In this study, the production of the normal superphosphate was investigated with a continuous chamber method by adding potassium chloride to a mixture of Hibin apatite and Kingisepp phosphorite. In the experiments, the following parameters were selected: The concentration of sulfuric acid (54–66% (w/w)), the stoichiometric norm of sulfuric acid (100, 107, 110, 114% (w/w)), the ratio of apatite/phosphorite in the mixture of phosphate (95/5, 90/10, 85/15, 80/20, 75/25, 70/30, 65/35,60/40, 55/45, 50/50 (w/w)), potassium chloride/the mixture of phosphate (1/50, 2/50, 3/50,4/50, 5/50 (w/w)), and the reaction time (2–8 min). It was observed that by adding potassium chloride to a low-grade phosphorite and using it to substitute a fraction of high-grade apatite in the normal superphosphate production not only resulted in a high-quality product but also eliminated the waiting period for the maturation of superphosphate in the storage. The objective of this study was to produce a normal superphosphate fertilizer by using a continuous chamber method in order to accelerate the production process and to reduce the environmental pollution caused by fluoride gases by eliminating the maturation time in the storage.

Keywords: Continuous chamber method, environmental pollution, fluoride gases.

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Authors: A. Shyamala Devi, K. Chitra Devi, R. Rajendiran

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A total of 6 isolates of Bacillus subtilis were isolated from oil mill waste collected in Namakkal district, Tamilnadu, India. The isolated bacteria were screened using lipase screening medium containing Tween 80. BS-3 isolate exhibited a greater clear zone than the others, indicating higher lipase activity. Therefore, this isolate was selected for media optimization studies. Ten process variables were screened using Plackett–Burman design and were further optimized by central composite design of response surface methodology for lipase production in submerged fermentation. Maximum lipase production of 16.627 U/min/ml were predicted in medium containing yeast extract (9.3636g), CaCl2 (0.8986g) and incubation periods (1.813 days). A mean value of 16.98 ± 0.2286 U/min/ml of lipase was acquired from real experiments.

Keywords: Bacillus subtilis, extracellular lipase, Plackett–Burman design, response surface methodology.

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Authors: Nikhil, Ari Visa, Chin-Chao Chen, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

A predictive clustering hybrid regression (pCHR) approach was developed and evaluated using dataset from H2- producing sucrose-based bioreactor operated for 15 months. The aim was to model and predict the H2-production rate using information available about envirome and metabolome of the bioprocess. Selforganizing maps (SOM) and Sammon map were used to visualize the dataset and to identify main metabolic patterns and clusters in bioprocess data. Three metabolic clusters: acetate coupled with other metabolites, butyrate only, and transition phases were detected. The developed pCHR model combines principles of k-means clustering, kNN classification and regression techniques. The model performed well in modeling and predicting the H2-production rate with mean square error values of 0.0014 and 0.0032, respectively.

Keywords: Biohydrogen, bioprocess modeling, clusteringhybrid regression.

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Authors: Bolarinwa K.K., Oyeyinka R.A

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The two agro-ecological zones became the focus of the study because of violent nature of the incessant conflict in the zones. The available register of farmers association was the sampling frame work where ten percent (61) farmers per state were randomly sampled. Data were collected and analysed using z-test. The research findings revealed tree crops and grains production enterprises ranked higher in Osun (rain fed zones) and Taraba states (savannah zones) respectively. Osun state entrepreneur felt the effect of the conflict on their enterprises more than Tarba state. The reasons adduced for severity of the conflict on enterprises are majority (77.0%) migrated and (75.5%) of them were not allowed to enter their farms during and when conflict deescalated unlike situation in Taraba state. The different in enterprises production level between the two agroecological zone was statistically significant at p<0.05. The conflict had severe impact on farm enterprises.

Keywords: Conflict, severity, entrepreneurs, farm enterprises and production level.

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Authors: Peter Burggräf, Matthias Dannapfel, Hanno Voet, Patrick-Benjamin Bök, Jérôme Uelpenich, Julian Hoppe

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The increasing digitalization of value chains can help companies to handle rising complexity in their processes and thereby reduce the steadily increasing planning and control effort in order to raise performance limits. Due to technological advances, companies face the challenge of smart value chains for the purpose of improvements in productivity, handling the increasing time and cost pressure and the need of individualized production. Therefore, companies need to ensure quick and flexible decisions to create self-optimizing processes and, consequently, to make their production more efficient. Lean production, as the most commonly used paradigm for complexity reduction, reaches its limits when it comes to variant flexible production and constantly changing market and environmental conditions. To lift performance limits, which are inbuilt in current value chains, new methods and tools must be applied. Digitalization provides the potential to derive these new methods and tools. However, companies lack the experience to harmonize different digital technologies. There is no practicable framework, which instructs the transformation of current value chains into digital pervasive value chains. Current research shows that a connection between lean production and digitalization exists. This link is based on factors such as people, technology and organization. In this paper, the introduced method for the determination of digitally pervasive value chains takes the factors people, technology and organization into account and extends existing approaches by a new dimension. It is the first systematic approach for the digital transformation of lean production and consists of four steps: The first step of ‘target definition’ describes the target situation and defines the depth of the analysis with regards to the inspection area and the level of detail. The second step of ‘analysis of the value chain’ verifies the lean-ability of processes and lies in a special focus on the integration capacity of digital technologies in order to raise the limits of lean production. Furthermore, the ‘digital evaluation process’ ensures the usefulness of digital adaptions regarding their practicability and their integrability into the existing production system. Finally, the method defines actions to be performed based on the evaluation process and in accordance with the target situation. As a result, the validation and optimization of the proposed method in a German company from the electronics industry shows that the digital transformation of current value chains based on lean production achieves a raise of their inbuilt performance limits.

Keywords: Digitalization, digital transformation, lean production, Industrie 4.0, value chain.

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Authors: Trung-Kien Pham, Yoonsu Nam, Hyungun Kim, Jaehoon Son

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This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbine, a set of operating conditions is identified and then a LQR controller is designed for each operating point. The feedback controller gains are then interpolated linearly to get control law for the entire operating region. Besides, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of the method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with that when using PI controller.

Keywords: variable speed variable pitch wind turbine, multi-MW size wind turbine, wind energy conversion system, LQR control.

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Authors: Kanate Pantusavase, Jaramporn Hassamontr

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This research aims to develop an algorithm to generate a schedule of multiple cranes that will maximize load throughputs in anodizing operation. The algorithm proposed utilizes an enumerative strategy to search for constant time between successive loads and crane covering range over baths. The computer program developed is able to generate a near-optimal crane schedule within reasonable times, i.e. within 10 minutes. Its results are compared with existing solutions from an aluminum extrusion industry. The program can be used to generate crane schedules for mixed products, thus allowing mixed-model line balancing to improve overall cycle times.

Keywords: Crane scheduling, anodizing operations, cycle time minimization.

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Authors: F. Saccucci

Abstract:

Gamification has now started to take root in the post-secondary classroom. Educators have learned much about gamification to date but there is still a great deal to learn. One definition of gamification is the ability to engage post-secondary students with games that are fun and correlate to class room curriculum. There is no shortage of literature illustrating the advantages of gamification in the class room. This study is an extension of similar thought as well as an extension of a previous study where in class testing proved with the used of paired T-test that gamification did significantly improve the students’ understanding of subject material. Gamification itself in the class room can range from high end computer simulated software to paper based games of which both have advantages and disadvantages. This analysis used a paper based game to highlight certain qualitative advantages of gamification. The paper based game in this analysis was inexpensive, required low preparation time for the faculty member and consumed approximately 20 minutes of class room time. Data for the study was collected through in class student feedback surveys and narrative from the faculty member moderating the game. Students were randomly selected into groups of four. Qualitative advantages identified in this analysis included: 1. Students had a chance to meet, connect and know other students. 2. Students enjoyed the gamification process given there was a sense of fun and competition. 3. The post assessment that followed the simulation game was not part of their grade calculation therefore it was an opportunity to participate in a low risk activity whereby students could subsequently self-assess their understanding of the subject material. 4. In the view of the student, content knowledge did increase after the gamification process. These qualitative advantages identified in this analysis contribute to the argument that there should be an attempt to use gamification in today’s post-secondary class room. The analysis also highlighted that eighty (80) percent of the respondents believe twenty minutes devoted to the gamification process was appropriate, however twenty (20) percentage of respondents believed that rather than scheduling a gamification process and its post quiz in the last week, a review for the final exam may have been more useful. An additional study to this hopes to determine if the scheduling of the gamification had any correlation to a percentage of the students not wanting to be engaged in the process. As well, the additional study hopes to determine at what incremental level of time invested in class room gamification produce no material incremental benefits to the student as well as determine if any correlation exist between respondents preferring not to have it at the end of the semester to students not believing the gamification process added to the increase of their curricular knowledge.

Keywords: Gamification, inexpensive, qualitative advantages, post-secondary.

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Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

Abstract:

As the limited availability of petroleum-based fuel has been a major concern, biodiesel is one of the most attractive alternative fuels because it is renewable and it also has advantages over the conventional petroleum-base diesel. At Present, productions of biodiesel generally perform by transesterification of vegetable oils with low molecular weight alcohol, mainly methanol, using chemical catalysts. Methanol is petrochemical product that makes biodiesel producing from methanol to be not pure renewable energy source. Therefore, ethanol as a product produced by fermentation processes. It appears as a potential feed stock that makes biodiesel to be pure renewable alternative fuel. The research is conducted based on two biodiesel production processes by reacting soybean oils with methanol and ethanol. Life cycle assessment was carried out in order to evaluate the environmental impacts and to identify the process alternative. Nine mid-point impact categories are investigated. The results indicate that better performance on abiotic depletion potential (ADP) and acidification potential (AP) are observed in biodiesel production from methanol when compared with biodiesel production from ethanol due to less energy consumption during the production processes. Except for ADP and AP, using methanol as feed stock does not show any advantages over biodiesel from ethanol. The single score method is also included in this study in order to identify the best option between two processes of biodiesel production. The global normalization and weighting factor based on ecotaxes are used and it shows that producing biodiesel form ethanol has less environmental load compare to biodiesel from methanol.

Keywords: Biodiesel, Ethanol, Life Cycle Assessment, Methanol, Soybean Oil.

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

Abstract:

For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: Flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis.

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Authors: Min Kyung An, Hyuk Cho

Abstract:

In this paper, we study the Minimum Latency Broadcast Scheduling (MLBS) problem in wireless sensor networks (WSNs). The main issue of the MLBS problem is to compute schedules with the minimum number of timeslots such that a base station can broadcast data to all other sensor nodes with no collisions. Unlike existing works that utilize the traditional omni-directional WSNs, we target the directional WSNs where nodes can collaboratively determine and orientate their antenna directions. We first develop a 7-approximation algorithm, adopting directional WSNs. Our ratio is currently the best, to the best of our knowledge. We then validate the performance of the proposed algorithm through simulation.

Keywords: Broadcast, collision-free, directional antenna, approximation, wireless sensor networks.

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Authors: Xin-Yu Shih, Yue-Qu Liu, Hong-Ru Chou

Abstract:

This paper presents a low-area and fully-reconfigurable Fast Fourier Transform (FFT) hardware design for 3GPP-LTE communication standard. It can fully support 32 different FFT sizes, up to 2048 FFT points. Besides, a special processing element is developed for making reconfigurable computing characteristics possible, while first-in first-out (FIFO) scheduling scheme design technique is proposed for hardware-friendly FIFO resource arranging. In a synthesis chip realization via TSMC 40 nm CMOS technology, the hardware circuit only occupies core area of 0.2325 mm² and dissipates 233.5 mW at maximal operating frequency of 250 MHz.

Keywords: Reconfigurable, fast Fourier transform, single-path delay feedback, 3GPP-LTE.

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