Search results for: Combined process.

Authors: W. Schellong

Abstract:

Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: Crossover technologies, data management, energy analysis, energy efficiency, process control.

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Authors: K. Atashgar

Abstract:

When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.

Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.

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Authors: A. Pancharya

Abstract:

The globalization of the Indian economy has thrown a great challenge to the Indian industries in respect of productivity, quality, cost, delivery etc. Achieving success• the global market has required fundamental shift in the way business is conducted and has dramatically affected virtually every aspect of process industry. The internal manufacturing process and supporting infrastructure should be such that it can compete successfully in global markets with better flexibility and delivery. The paper deals with a case study of a reputed process industry, some changes in the process has been suggested, which leads to reduction in labor cost and production cost.

Keywords: Indian cement industry, material handling, plant layout.

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Authors: Hacene Benkhoula, Mohamed Badreddine Benabdella, Hamid Bouzeboudja, Abderrahmane Asraoui

Abstract:

The wind is a random variable difficult to master, for this, we developed a mathematical and statistical methods enable to modeling and forecast wind power. Gaussian Processes (GP) is one of the most widely used families of stochastic processes for modeling dependent data observed over time, or space or time and space. GP is an underlying process formed by unrecognized operator’s uses to solve a problem. The purpose of this paper is to present how to forecast wind power by using the GP. The Gaussian process method for forecasting are presented. To validate the presented approach, a simulation under the MATLAB environment has been given.

Keywords: Forecasting, Gaussian process, modeling, wind power.

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Authors: Cha-Hwa Lin, Je-Wei Hu

Abstract:

The conventional GA combined with a local search algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA) for the traveling salesman problem (TSP). However, the geometric properties which are problem specific knowledge can be used to improve the search process of the HGA. Some tour segments (edges) of TSPs are fine while some maybe too long to appear in a short tour. This knowledge could constrain GAs to work out with fine tour segments without considering long tour segments as often. Consequently, a new algorithm is proposed, called intelligent-OPT hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT algorithm in order to reduce the search time for the optimal solution. Based on the geometric properties, all the tour segments are assigned 2-level priorities to distinguish between good and bad genes. A simulation study was conducted to evaluate the performance of the IOHGA. The experimental results indicate that in general the IOHGA could obtain near-optimal solutions with less time and better accuracy than the hybrid genetic algorithm with simulated annealing algorithm (HGA(SA)).

Keywords: Traveling salesman problem, hybrid geneticalgorithm, priority selection, 2-OPT.

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Authors: O. Srihakulung, Y. Soongsumal

Abstract:

Among the chemicals used for ammunition production, TNT (Trinitrotoluene) play a significant role since World War I and II. Various types of military weapon utilize TNT in casting process. However, the TNT casting process for warhead is difficult to control the cooling rate of the liquid TNT. This problem occurs because the casting process lacks the equipment to detect the temperature during the casting procedure This study presents the temperature detected by infrared camera to illustrate the cooling rate and cooling zone of curing, and demonstrates the optimization of TNT condition to reduce the risk of air gap occurred in the warhead which can result in the destruction afterward. Premature initiation of explosive-filled projectiles in response to set-back forces during gunfiring cause by casting defects. Finally the study can help improving the process of the TNT casting. The operators can control the curing of TNT inside the case by rising up the heating rod at the proper time. Consequently this can reduce tremendous time of rework if the air gaps occur and increase strength to lower elastic modulus. Therefore, it can be clearly concluded that the use of Infrared Cameras in this process is another method to improve the casting procedure.

Keywords: Infrared camera, TNT casting, warhead, curing.

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Authors: M. Mikušová

Abstract:

The main aim of this paper is to present a clear and comprehensive picture of the process of a crisis in the organization which will help to better understand its possible developments. For a description of the sequence of individual steps and an indication of their causation and possible variants of the developments, a detailed flow diagram with verbal comment is applied. For simplicity, the process of the crisis is observed in four basic phases called: symptoms of the crisis, diagnosis, action and prevention. The model highlights the complexity of the phenomenon of the crisis and that the various phases of the crisis are interweaving.

Keywords: Crisis, management, model, organization.

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Authors: Farhad Kolahan, A. Hamid Khajavi

Abstract:

Abrasive waterjet is a novel machining process capable of processing wide range of hard-to-machine materials. This research addresses modeling and optimization of the process parameters for this machining technique. To model the process a set of experimental data has been used to evaluate the effects of various parameter settings in cutting 6063-T6 aluminum alloy. The process variables considered here include nozzle diameter, jet traverse rate, jet pressure and abrasive flow rate. Depth of cut, as one of the most important output characteristics, has been evaluated based on different parameter settings. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. The pairwise effects of process parameters settings on process response outputs are also shown graphically. The proposed model is then embedded into a Simulated Annealing algorithm to optimize the process parameters. The optimization is carried out for any desired values of depth of cut. The objective is to determine proper levels of process parameters in order to obtain a certain level of depth of cut. Computational results demonstrate that the proposed solution procedure is quite effective in solving such multi-variable problems.

Keywords: AWJ cutting, Mathematical modeling, Simulated Annealing, Optimization

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Authors: R. Chalal, A. R. Ghomari

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Preparation and negotiation of innovative and future projects can be characterized as a strategic-type decision situation, involving many uncertainties and an unpredictable environment. We will focus in this paper on the bidding process. It includes cooperative and strategic decisions. Our approach for bidding process knowledge capitalization is aimed at information management in project-oriented organizations, based on the MUSIC (Management and Use of Co-operative Information Systems) model. We will show how to capitalize the company strategic knowledge and also how to organize the corporate memory. The result of the adopted approach is improvement of corporate memory quality.

Keywords: Bidding process, corporate memory, Knowledge capitalization, knowledge acquisition, strategic decisions.

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Authors: Amit Gil, Helman Stern, Yael Edan

Abstract:

A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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Authors: T.T. Wong, C.W. Leung, M.C. Wong

Abstract:

Cooktop burners are widely used nowadays. In cooktop burner design, nozzle efficiency and greenhouse gas(GHG) emissions mainly depend on heat transfer from the premixed flame to the impinging surface. This is a complicated issue depending on the individual and combined effects of various input combustion variables. Optimal operating conditions for sustainable burner design were rarely addressed, especially in the case of multiple slot-jet burners. Through evaluating the optimal combination of combustion conditions for a premixed slot-jet array, this paper develops a practical approach for the sustainable design of gas cooktop burners. Efficiency, CO and NOx emissions in respect of an array of slot jets using premixed flames were analysed. Response surface experimental design were applied to three controllable factors of the combustion process, viz. Reynolds number, equivalence ratio and jet-to-vessel distance. Desirability Function Approach(DFA) is the analytic technique used for the simultaneous optimization of the efficiency and emission responses.

Keywords: optimization, premixed slot jets

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Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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Authors: Mohamed Hafid, Marcel Lacroix

Abstract:

This study presents an inverse analysis for predicting the thermal conductivities and the heat flux of a high-temperature metallurgical reactor simultaneously. Once these thermal parameters are predicted, the time-varying thickness of the protective phase-change bank that covers the inside surface of the brick walls of a metallurgical reactor can be calculated. The enthalpy method is used to solve the melting/solidification process of the protective bank. The inverse model rests on the Levenberg-Marquardt Method (LMM) combined with the Broyden method (BM). A statistical analysis for the thermal parameter estimation is carried out. The effect of the position of the temperature sensors, total number of measurements and measurement noise on the accuracy of inverse predictions is investigated. Recommendations are made concerning the location of temperature sensors.

Keywords: Inverse heat transfer, phase change, metallurgical reactor, Levenberg–Marquardt method, Broyden method, bank thickness.

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Authors: R.Vinodha S. Abraham Lincoln, J. Prakash

Abstract:

Multi-loop (De-centralized) Proportional-Integral- Derivative (PID) controllers have been used extensively in process industries due to their simple structure for control of multivariable processes. The objective of this work is to design multiple-model adaptive multi-loop PID strategy (Multiple Model Adaptive-PID) and neural network based multi-loop PID strategy (Neural Net Adaptive-PID) for the control of multivariable system. The first method combines the output of multiple linear PID controllers, each describing process dynamics at a specific level of operation. The global output is an interpolation of the individual multi-loop PID controller outputs weighted based on the current value of the measured process variable. In the second method, neural network is used to calculate the PID controller parameters based on the scheduling variable that corresponds to major shift in the process dynamics. The proposed control schemes are simple in structure with less computational complexity. The effectiveness of the proposed control schemes have been demonstrated on the CSTR process, which exhibits dynamic non-linearity.

Keywords: Multiple-model Adaptive PID controller, Multivariableprocess, CSTR process.

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Authors: Chihhao Fan, Ming-Chu Liao

Abstract:

The purpose of this study is to investigate the chemical degradation of the organophosphorus pesticide of parathion and carbamate insecticide of methomyl in the aqueous phase through Fenton process. With the employment of batch Fenton process, the degradation of the two selected pesticides at different pH, initial concentration, humic acid concentration, and Fenton reagent dosages was explored. The Fenton process was found effective to degrade parathion and methomyl. The optimal dosage of Fenton reagents (i.e., molar concentration ratio of H2O2 to Fe2+) at pH 7 for parathion degradation was equal to 3, which resulted in 50% removal of parathion. Similarly, the optimal dosage for methomyl degradation was 1, resulting in 80% removal of methomyl. This study also found that the presence of humic substances has enhanced pesticide degradation by Fenton process significantly. The mass spectroscopy results showed that the hydroxyl free radical may attack the single bonds with least energy of investigated pesticides to form smaller molecules which is more easily to degrade either through physio-chemical or bilolgical processes.

Keywords: Fenton Process, humic acid, methomyl, parathion, pesticides

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Authors: Méryl Brothier, Dominique Moulinier, Christophe Bertaux

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The gel-supported precipitation (GSP) process can be used to make spherical particles (spherules) of nuclear fuel, particularly for very high temperature reactors (VHTR) and even for implementing the process called SPHEREPAC. In these different cases, the main characteristics are the sphericity of the particles to be manufactured and the control over their grain size. Nonetheless, depending on the specifications defined for these spherical particles, the GSP process has intrinsic limits, particularly when fabricating very small particles. This paper describes the use of secondary fragmentation (water, water/PVA and uranyl nitrate) on solid surfaces under varying temperature and vibration conditions to assess the relevance of using this new technique to manufacture very small spherical particles by means of a modified GSP process. The fragmentation mechanisms are monitored and analysed, before the trends for its subsequent optimised application are described.

Keywords: Microsphere elaboration, nuclear fuel, droplet impact , gel-supported precipitation process.

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Authors: María Fernández-Ropero, Ricardo Pérez-Castillo, Ismael Caballero, Mario Piattini

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Appropriate description of business processes through standard notations has become one of the most important assets for organizations. Organizations must therefore deal with quality faults in business process models such as the lack of understandability and modifiability. These quality faults may be exacerbated if business process models are mined by reverse engineering, e.g., from existing information systems that support those business processes. Hence, business process refactoring is often used, which change the internal structure of business processes whilst its external behavior is preserved. This paper aims to choose the most appropriate set of refactoring operators through the quality assessment concerning understandability and modifiability. These quality features are assessed through well-proven measures proposed in the literature. Additionally, a set of measure thresholds are heuristically established for applying the most promising refactoring operators, i.e., those that achieve the highest quality improvement according to the selected measures in each case.

Keywords: business process model, modifiability, refactoring, understandability

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Authors: A. Zeynolabedin, M. A. Olyaei, B. Ghiasi

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Drought is an inevitable part of the earth’s climate. It occurs regularly with no clear warning and without recognizing borders. In addition, its impact is cumulative and not immediately discernible. Iran is located in a semi-arid region where droughts occur periodically as natural hazard. Standardized Precipitation Index (SPI), Surface Water Supply Index (SWSI), and Palmer Drought Severity Index (PDSI) are three well-known indices which describe drought severity; each has its own advantages and disadvantages and can be used for specific types of drought. These indices take into account some factors such as precipitation, reservoir storage and discharge, temperature, and potential evapotranspiration in determining drought severity. In this paper, first all three indices are calculated in Aharchay river watershed located in northwestern part of Iran in East Azarbaijan province. Next, based on two other important parameters which are groundwater level and solar radiation, two new indices are defined. Finally, considering all five aforementioned indices, a combined drought index (CDI) is presented and calculated for the region. This combined index is based on all the meteorological, hydrological, and agricultural features of the region. The results show that the most severe drought condition in Aharchay watershed happened in Jun, 2004. The result of this study can be used for monitoring drought and prepare for the drought mitigation planning.

Keywords: Drought, index variation, regional assessment, monitoring.

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Authors: J. P. Chica Cano, G. Cabot, S. de Persis, F. Foucher

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Among all possibilities to combat global warming, CO₂ capture and sequestration (CCS) is presented as a great alternative to reduce greenhouse gas (GHG) emission. Several strategies for CCS from industrial and power plants are being considered. The concept of combined oxy-fuel combustion has been the most alternative solution. Nevertheless, due to the high cost of pure O₂ production, additional ways recently emerged. In this paper, an innovative combustion process for a gas turbine cycle was studied: it was composed of methane combustion with oxygen enhanced air (OEA), exhaust gas recirculation (EGR) and H₂O issuing from STIG (Steam Injection Gas Turbine), and the CO₂ capture was realized by membrane separator. The effect on this combustion process was emphasized, and it was shown that a study of the influence of H₂O dilution on the combustion parameters by experimental and numerical approaches had to be carried out. As a consequence, the laminar burning velocities measurements were performed in a stainless steel spherical combustion from atmospheric pressure to high pressure (up to 0.5 MPa), at 473 K for an equivalence ratio at 1. These experimental results were satisfactorily compared with Chemical Workbench v.4.1 package in conjunction with GRIMech 3.0 reaction mechanism. The good correlations so obtained between experimental and calculated flame speed velocities showed the validity of the GRIMech 3.0 mechanism in this domain of combustion: high H₂O dilution, low N₂, medium pressure. Finally, good estimations of flame speed and pollutant emissions were determined in other conditions compatible with real gas turbine. In particular, mixtures (composed of CH₄/O₂/N₂/H₂O/ or CO₂) leading to the same adiabatic temperature were investigated. Influences of oxygen enrichment and H₂O dilution (compared to CO₂) were disused.

Keywords: CO2 capture, oxygen enrichment, water dilution, laminar burning velocity, pollutants emissions.

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Authors: Akhilesh G. Naik, Dipankar Pal

Abstract:

In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba, Looped Karatsuba.

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Authors: Rim Bouhaouel, Naoufel Kraïem, Zuhoor Al Khanjari

Abstract:

Unified Modeling Language (UML) is considered as one of the widespread modeling language standardized by the Object Management Group (OMG). Therefore, the model driving engineering (MDE) community attempts to provide reuse of UML diagrams, and do not construct it from scratch. The UML model appears according to a specific software development process. The existing method generation models focused on the different techniques of transformation without considering the development process. Our work aims to construct an UML component from fragments of UML diagram basing on an agile method. We define UML fragment as a portion of a UML diagram, which express a business target. To guide the generation of fragments of UML models using an agile process, we need a flexible approach, which adapts to the agile changes and covers all its activities. We use the software product line (SPL) to derive a fragment of process agile method. This paper explains our approach, named RECUP, to generate UML fragments following an agile process, and overviews the different aspects. In this paper, we present the approach and we define the different phases and artifacts.

Keywords: UML, component, fragment, agile, SPL.

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Authors: Farhad Kolahan, Mehdi Heidari

Abstract:

Gas Metal Arc Welding (GMAW) processes is an important joining process widely used in metal fabrication industries. This paper addresses modeling and optimization of this technique using a set of experimental data and regression analysis. The set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry. The process variables considered here include voltage (V); wire feed rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate distance (D). The process output characteristics include weld bead height, width and penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAW process parameters. The objective is to determine a suitable set of process parameters that can produce desired bead geometry, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

Keywords: Weld Bead Geometry, GMAW welding, Processparameters Optimization, Modeling, SA algorithm

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Authors: O. Ualibek, C. Spitas, V. Inglezakis, G. Itskos

Abstract:

This study presents simulations of an aluminium melt containing an initially non-dispersed fly ash nanoparticle phase. Mixing is affected predominantly by means of forced extensional flow via either straight or slanted orifices. The sensitivity to various process parameters is determined. The simulated process is used for the production of cast fly ash-aluminium nanocomposites. The possibilities for rod and plate stock grading in the context of a continuous casting process implementation are discussed.

Keywords: Metal matrix composites, fly ash nanoparticles, aluminium 2024, agglomeration.

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Authors: Salvatore L., Pires B., Campos M. C. M., De Souza Jr M. B.

Abstract:

It is estimated that the total cost of abnormal conditions to US process industries is around $20 billion dollars in annual losses. The hydrotreatment (HDT) of diesel fuel in petroleum refineries is a conversion process that leads to high profitable economical returns. However, this is a difficult process to control because it is operated continuously, with high hydrogen pressures and it is also subject to disturbances in feed properties and catalyst performance. So, the automatic detection of fault and diagnosis plays an important role in this context. In this work, a hybrid approach based on neural networks together with a pos-processing classification algorithm is used to detect faults in a simulated HDT unit. Nine classes (8 faults and the normal operation) were correctly classified using the proposed approach in a maximum time of 5 minutes, based on on-line data process measurements.

Keywords: Fault detection, hydrotreatment, hybrid systems, neural networks.

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Authors: V. K. Singh, P. K. Padhy

Abstract:

This paper describes identification of the two poles unstable SOPDT process, especially with large time delay. A new modified relay feedback identification method for two poles unstable SOPDT process is proposed. Furthermore, for the two poles unstable SOPDT process, an additional Derivative controller is incorporated parallel with relay to relax the constraint on the ratio of delay to the unstable time constant, so that the exact model parameters of unstable processes can be identified. To cope with measurement noise in practice, a low pass filter is suggested to get denoised output signal toimprove the exactness of model parameter of unstable process. PID Lead-lag tuning formulas are derived for two poles unstable (SOPDT) processes based on IMC principle. Simulation example illustrates the effectiveness and the simplicity of the proposed identification and control method.

Keywords: IMC structure, PID Lead-lag controller, Relayfeedback, SOPDT

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Authors: M. H. Zarei, A. Nikakhtar, A. H. Roudsari, N. Madadi, K. Y. Wong

Abstract:

Improving performance measures in the construction processes has been a major concern for managers and decision makers in the industry. They seek for ways to recognize the key factors which have the largest effect on the process. Identifying such factors can guide them to focus on the right parts of the process in order to gain the best possible result. In the present study design of experiment (DOE) has been applied to a computer simulation model of brick laying process to determine significant factors while productivity has been chosen as the response of the experiment. To this end, four controllable factors and their interaction have been experimented and the best factor level has been calculated for each one. The results indicate that three factors, namely, labor of brick, labor of mortar and inter arrival time of mortar along with interaction of labor of brick and labor of mortar are significant.

Keywords: Brick laying process, computer simulation, design of experiment, significant factors.

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Authors: Sudhir Agashe, Ashok Ghatol, Sujata Agashe

Abstract:

In this paper the development of a heat exchanger as a pilot plant for educational purpose is discussed and the use of neural network for controlling the process is being presented. The aim of the study is to highlight the need of a specific Pseudo Random Binary Sequence (PRBS) to excite a process under control. As the neural network is a data driven technique, the method for data generation plays an important role. In light of this a careful experimentation procedure for data generation was crucial task. Heat exchange is a complex process, which has a capacity and a time lag as process elements. The proposed system is a typical pipe-in- pipe type heat exchanger. The complexity of the system demands careful selection, proper installation and commissioning. The temperature, flow, and pressure sensors play a vital role in the control performance. The final control element used is a pneumatically operated control valve. While carrying out the experimentation on heat exchanger a welldrafted procedure is followed giving utmost attention towards safety of the system. The results obtained are encouraging and revealing the fact that if the process details are known completely as far as process parameters are concerned and utilities are well stabilized then feedback systems are suitable, whereas neural network control paradigm is useful for the processes with nonlinearity and less knowledge about process. The implementation of NN control reinforces the concepts of process control and NN control paradigm. The result also underlined the importance of excitation signal typically for that process. Data acquisition, processing, and presentation in a typical format are the most important parameters while validating the results.

Keywords: Process identification, neural network, heat exchanger.

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Authors: I. R. Kanu, T. J. Aspray, A. J. Adeloye

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As a result of the ambiguity and complexity surrounding anaerobic digester foaming, efforts have been made by various researchers to understand the process of anaerobic digester foaming so as to proffer a solution that can be universally applied rather than site specific. All attempts ranging from experimental analysis to comparative review of other process has not fully explained the conditions and process of foaming in anaerobic digester. Studying the current available knowledge on foam formation and relating it to anaerobic digester process and operating condition, this piece of work presents a succinct and enhanced understanding of foaming in anaerobic digesters as well as introducing a simple method to identify the onset of anaerobic digester foaming based on analysis of historical data from a field scale system.

Keywords: Anaerobic digester, foam, biogas, surfactants, wastewater sludge.

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Authors: M. Pala Prasad Reddy, Jeevamma Jacob

Abstract:

Accurate dynamic modeling and analysis of flexible link manipulator (FLM) with non linear dynamics is very difficult due to distributed link flexibility and few studies have been conducted based on assumed modes method (AMM) and finite element models. In this paper a nonlinear dynamic model with first two elastic modes is derived using combined Euler/Lagrange and AMM approaches. Significant dynamics associated with the system such as hub inertia, payload, structural damping, friction at joints, combined link and joint flexibility are incorporated to obtain the complete and accurate dynamic model. The response of the FLM to the applied bang-bang torque input is compared against the models derived from LS-DYNA finite element discretization approach and linear finite element models. Dynamic analysis is conducted using LS-DYNA finite element model which uses the explicit time integration scheme to simulate the system. Parametric study is conducted to show the impact payload mass. A numerical result shows that the LS-DYNA model gives the smooth hub-angle profile.

 

Keywords: Flexible link manipulator, AMM, FEM, LS-DYNA, Bang-bang torque input.

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Authors: A. Benhadji, M. Taleb Ahmed

Abstract:

Among the various methods of treatment, advanced oxidation processes (AOP) are the most promising ones. In this study, Peroxi Electrocoagulation Process (PEP) was investigated for the treatment of detergent wastewater. The process was compared with electrooxidation treatment. The results showed that chemical oxygen demand (COD) was high 7584 mgO₂.L^-1, while the biochemical oxygen demand was low (250 mgO₂.L^-1). This wastewater was hardly biodegradable. Electrochemical process was carried out for the removal of detergent using a glass reactor with a volume of 1 L and fitted with three electrodes. A direct current (DC) supply was used. Samples were taken at various current density (0.0227 A/cm² to 0.0378 A/cm²) and reaction time (1-2-3-4 and 5 hour). Finally, the COD was determined. The results indicated that COD removal efficiency of PEP was observed to increase with current intensity and reached to 77% after 5 h. The highest removal efficiency was observed after 5 h of treatment.

Keywords: Advanced oxidation processes, chemical oxygen demand, COD, detergent, peroxi electrocoagulation process, PEP, wastewater

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