Search results for: cost prediction

Authors: Rui Calejo Rodrigues

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Building Refurbishing and Maintenance is a major area of knowledge ultimately dispensed to user/occupant criteria. The optimization of the service life of a building needs a special background to be assessed as it is one of those concepts that needs proficiency to be implemented. ISO 15686-2 Buildings and constructed assets - Service life planning: Part 2, Service life prediction procedures, states a factorial method based on deterministic data for building components life span. Major consequences result on a deterministic approach because users/occupants are not sensible to understand the end of components life span and so simply act on deterministic periods and so costly and resources consuming solutions do not meet global targets of planet sustainability. The estimation of 2 thousand million conventional buildings in the world, if submitted to a probabilistic method for service life planning rather than a deterministic one provide an immense amount of resources savings. Since 1989 the research team nowadays stating for CEES–Center for Building in Service Studies developed a methodology based on Montecarlo method for probabilistic approach regarding life span of building components, cost and service life care time spans. The research question of this deals with the importance of probabilistic approach of buildings life planning compared with deterministic methods. It is presented the mathematic model developed for buildings probabilistic lifespan approach and experimental data is obtained to be compared with deterministic data. Assuming that buildings lifecycle depends a lot on component replacement this methodology allows to conclude on the global impact of fixed replacements methodologies such as those on result of deterministic models usage. Major conclusions based on conventional buildings estimate are presented and evaluated under a sustainable perspective.

Keywords: building components life cycle, building maintenance, building sustainability, Montecarlo Simulation

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Authors: Yekini N. Asafe, Haastrup A. Victor, Lawal N. Olawale, Okikiola F. Mercy

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Recent increase in access to personal computer and networking systems have made it feasible to perform much of cumbersome and costly paper-based administration in all organization. Desktop computers, networking systems, high capacity storage devices and telecommunications system is currently allowing the transfer of various format of data to be processed, stored and dissemination for the purpose of decision making. Going paperless is more of benefits compare to full paper-based office. This paper proposed a model for design and implementation of e-administration system (paperless campus) for an institution of learning. If this model is design and implemented it will reduced cost and complexity of educational administration also eliminate menaces and environmental hazards attributed to paper-based administration within schools and colleges.

Keywords: e-administration, educational administration, paperless campus, paper-based administration

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

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In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

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Authors: D. De-León-Escobedo, D. J. Delgado-Hernández, S. Pérez

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A probabilistic formulation to assess the slopes safety under the hazard of strong storms is presented and illustrated through a slope in Mexico. The formulation is based on the classical safety factor (SF) used in practice to appraise the slope stability, but it is introduced the treatment of uncertainties, and the slope failure probability is calculated as the probability that SF<1. As the main hazard is the rainfall on the area, statistics of rainfall intensity and duration are considered and modeled with an exponential distribution. The expected life-cycle cost is assessed by considering a monetary value on the slope failure consequences. Alternative mitigation measures are simulated, and the formulation is used to get the measures driving to the optimal one (minimum life-cycle costs). For the example, the optimal mitigation measure is the reduction on the slope inclination angle.

Keywords: expected life-cycle cost, failure probability, slopes failure, storms

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Authors: Hagos Gebrehiwet Bahta

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Asmara, the capital city of Eritrea, is facing a sanitation challenge because the city discharges its wastewater to the environment without any kind of treatment. The aim of this research is to conduct a pre-feasibility study of using constructed wetlands in the peri-urban areas of Asmara for wastewater treatment and reuse. It was found that around 15,000 m³ of wastewater is used daily for agricultural activities, and products are sold in the city's markets, which are claimed to cause some health effects. In this study, three potential sites were investigated around Mai-Bela and an optimum location was selected on the basis of land availability, topography, and geotechnical information. Some types of local microphytes that can be used in constructed wetlands have been identified and documented for further studies. It was found that subsurface constructed wetlands can provide a sufficient pollutant removal with careful planning and design. Following the feasibility study, a preliminary design of screening, grit chamber and subsurface constructed wetland was prepared and cost estimation was done. In the cost estimation part, the filter media was found to be the most expensive part and consists of around 30% percent of the overall cost. The city wastewater drainage runs in two directions and the selected site is located in the southern sub-system, which only carries sewage (separate system). The wastewater analysis conducted particularly around this area (Sembel) indicates high heavy metal levels and organic concentrations, which reveals that there is a high level of industrial pollution in addition to the domestic sewage.

Keywords: agriculture, constructed wetland, Mai-Bela, wastewater reuse

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Authors: N. Jena, Nitin Seth

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Globalization and free trade has forced the organizations to continuously rethink and rework on the increasing cost of logistics. World wide, it is visualized that on one side the steel sector is witnessing rapid growth and on the other side it is facing huge challenges in terms of availability of raw materials for uninterrupted production. Inbound logistics also gains significant importance for ensuring the timely availability of raw materials. It is seen that in Indian steel sector logistic cost is still very large and challenging. Effectively managing the inbound logistics in steel decides the profitability and serviceability of the organization. Effective management of inbound logistics also has a major role on the inventory of the organization. Since, the logistics for the steel industry in India is evolving rapidly and it is the interplay of infrastructure, technology and new types of service providers that will define whether the industry is able to help its customers to reduce their logistics costs. Integration of Logistics has been treated as one of the most potential area for the companies to provide a base for cost reduction. In spite of the proven area for benefits for the industry, it is very surprising that none of the researchers have explored this area. Although, many researchers explored the subject of logistics in steel industry, but their perspective varied from exploring and understanding the associated cost and finding out the relations between them. Visualizing a potential gap, the present research is under taken to explore the integration opportunities in inbound logistics for steel sector. Typically in Indian steel sector where in most of the manufacturers depend on imported materials for processing the logistics is very challenging and accounts for transactions at supplier – who is situated in different country, shipper- who is transporting the material to the host country, regulators in both countries-that include customs and various clearing agents, local logistics service providers and local transporters/handlers. It is seen that In bound logistics cost in the steel sector is very high and accounts for about 15-16% of the turn over, integration of information across different channels provides and opportunity for improvements and growth of the organization. In the present paper, a case of leading steel manufacturer has been taken and the potentials for integration of information across various partners have been identified. The paper provides the identification of grey area in steel sector for major improvements in cycle time and lowering the inventories by integration of information. Finally, based on integration of information, the paper presents a business information framework for steel sector.

Keywords: integration, steel sectors, suppliers, shippers, customs and cargo agents, transporters

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Authors: Jaemin Kim, Ilsun Pang, Yongrae Cho, Kwanghun Kim, Sungsun Baik

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Manufacturing cost reduction is becoming more important due to excessive oversupply of Single crystalline ingot in recent solar market. Many companies are carrying out extensive research to grow more than one Single crystalline ingot in one batch to reduce manufacturing cost. However what most companies are finding difficult in this process is the effect on ingot due to increasing levels of impurities. Every ingot leaves a certain amount of melt after it is fully grown. This is the impurity that lowers the ingot quality. This impurity increase in the batch after second, third and more are grown subsequently in one batch. In order to solve this problem, the experiment to remove the residual melt in high temperature of hot zone was performed and succeeded. Theoretical average metal concentration of second ingot by new method was calculated and compared to it by conventional method.

Keywords: single crystal, solar cell, metal impurity, Ingot

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Authors: Arvind Kumar

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The city of Kanpur is located in the terrestrial plain area on the bank of the river Ganges and is the second largest city in the state of Uttar Pradesh. The city generates approximately 1400-1600 tons per day of MSW. Kanpur has been known as a major point and non-points-based pollution hotspot for the river Ganges. The city has a major industrial hub, probably the largest in the state, catering to the manufacturing and recycling of plastic and other dry waste streams. There are 4 to 5 major drains flowing across the city, which receive a significant quantity of waste leakage, which subsequently adds to the Ganges flow and is carried to the Bay of Bengal. A river-to-sea flow approach has been established to account for leaked waste into urban drains, leading to the build-up of marine litter. Throughout its journey, the river accumulates plastic – macro, meso, and micro, from various sources and transports it towards the sea. The Ganges network forms the second-largest plastic-polluting catchment in the world, with over 0.12 million tonnes of plastic discharged into marine ecosystems per year and is among 14 continental rivers into which over a quarter of global waste is discarded 3.150 Kilo tons of plastic waste is generated in Kanpur, out of which 10%-13% of plastic is leaked into the local drains and water flow systems. With the Support of Kanpur Municipal Corporation, 1TPD capacity MRF for drain waste management was established at Krishna Nagar, Kanpur & A German startup- Plastic Fisher, was identified for providing a solution to capture the drain waste and achieve its recycling in a sustainable manner with a circular economy approach. The team at Plastic Fisher conducted joint surveys and identified locations on 3 drains at Kanpur using GIS maps developed during the survey. It suggested putting floating 'Boom Barriers' across the drains with a low-cost material, which reduced their cost to only 2000 INR per barrier. The project was built upon the self-sustaining financial model. The project includes activities where a cost-efficient model is developed and adopted for a socially self-inclusive model. The project has recommended the use of low-cost floating boom barriers for capturing waste from drains. This involves a one-time time cost and has no operational cost. Manpower is engaged in fishing and capturing immobilized waste, whose salaries are paid by the Plastic Fisher. The captured material is sun-dried and transported to the designated place, where the shed and power connection, which act as MRF, are provided by the city Municipal corporation. Material aggregation, baling, and transportation costs to end-users are borne by Plastic Fisher as well.

Keywords: Kanpur, marine environment, drain waste management, plastic fisher

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Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

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Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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Authors: Nuran Bahar, Mehmet A. Akcayol

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In the aviation industry, many faults may occur frequently during the maintenance processes and assembly operations of complex structured aircrafts because of their high dependencies of components. These faults affect the quality of aircraft parts or developed modules adversely. Technical employee requires long time and high labor force while checking the correctness of each component. In addition, the person must be trained regularly because of the ever-growing and changing technology. Generally, the cost of this training is very high. Augmented Reality (AR) technology reduces the cost of training radically and improves the effectiveness of the training. In this study, the usage of AR technology in the aviation industry has been investigated and the effectiveness of AR with heads-up display glasses has been examined. An application has been developed for comparison of production process with AR and manual one.

Keywords: aerospace, assembly quality, augmented reality, heads-up display

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Authors: Milca F. Coelho, K. Bousson, Kawser Ahmed

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To accurately track an aerospace vehicle in a time-critical situation and in a highly nonlinear environment, is one of the strongest interests within the aerospace community. The tracking is achieved by estimating accurately the state of a moving target, which is composed of a set of variables that can provide a complete status of the system at a given time. One of the main ingredients for a good estimation performance is the use of efficient estimation algorithms. A well-known framework is the Kalman filtering methods, designed for prediction and estimation problems. The success of the Kalman Filter (KF) in engineering applications is mostly due to the Extended Kalman Filter (EKF), which is based on local linearization. Besides its popularity, the EKF presents several limitations. To address these limitations and as a possible solution to tracking problems, this paper proposes the use of the Ensemble Kalman Filter (EnKF). Although the EnKF is being extensively used in the context of weather forecasting and it is being recognized for producing accurate and computationally effective estimation on systems with a very high dimension, it is almost unknown by the tracking community. The EnKF was initially proposed as an attempt to improve the error covariance calculation, which on the classic Kalman Filter is difficult to implement. Also, in the EnKF method the prediction and analysis error covariances have ensemble representations. These ensembles have sizes which limit the number of degrees of freedom, in a way that the filter error covariance calculations are a lot more practical for modest ensemble sizes. In this paper, a realistic simulation of a radar tracking was performed, where the EnKF was applied and compared with the Extended Kalman Filter. The results suggested that the EnKF is a promising tool for tracking applications, offering more advantages in terms of performance.

Keywords: Kalman filter, nonlinear state estimation, optimal tracking, stochastic environment

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Authors: Victor Siahaan

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Coal still become the most important energy source for electricity generation known for its contribution which take the biggest portion of energy mix that a country has, for example Indonesia. The low cost of electricity generation and quite a lot of resources make this energy still be the first choice to fill the portion of base load power. To realize its significance to produce electricity, it is necessary to know the amount of coal (volume) needed to ensure that all coal power plants (CPP) in a country can operate properly. To secure the volume of coal, in this study, discussion was carried out regarding the identification of coal mining sources in Indonesia, classification of coal typical from each coal mining sources, and determination of the port of loading. By using data above, the sources of coal mining are then selected to feed certain CPP based on the compatibility of the coal typical and the lowest transport cost.

Keywords: merit order, Indonesian coal mine, electricity, power plant

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

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Authors: Magno Enrique Mendoza Meza

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This paper deals with the comparison of three control techniques: the hysteresis on-off control (HyOOC), the hybrid on-off control (HOOC) and the simple Structured Treatment Interruptions (sSTI). These techniques are applied to the mathematical model developed by Kirschner and Webb. To compare these techniques we use a cost functional that minimize the wild-type virus population and the mutant virus population, but the main objective is to minimize the systemic cost of treatment and maximize levels of healthy CD4+ T cells. HyOOC, HOOC, and sSTI are applied to the drug therapies using a reverse transcriptase and protease inhibitors; simulations show that these controls maintain the uninfected cells in a small, bounded neighborhood of a pre-specified level. The controller HyOOC and HOOC are designed by appropriate choice of virtual equilibrium points.

Keywords: virus dynamics, on-off control, hysteresis, multi-drug therapies

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Authors: Raghavi C. Janaswamy

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In the healthcare sector, heterogenous data elements such as patients, diagnosis, symptoms, conditions, observation text from physician notes, and prescriptions form the essentials of the Electronic Health Record (EHR). The data in the form of clear text and images are stored or processed in a relational format in most systems. However, the intrinsic structure restrictions and complex joins of relational databases limit the widespread utility. In this regard, the design and development of realistic mapping and deep connections as real-time objects offer unparallel advantages. Herein, a graph neural network-based classification of EHR data has been developed. The patient conditions have been predicted as a node classification task using a graph-based open source EHR data, Synthea Database, stored in Tigergraph. The Synthea DB dataset is leveraged due to its closer representation of the real-time data and being voluminous. The graph model is built from the EHR heterogeneous data using python modules, namely, pyTigerGraph to get nodes and edges from the Tigergraph database, PyTorch to tensorize the nodes and edges, PyTorch-Geometric (PyG) to train the Graph Neural Network (GNN) and adopt the self-supervised learning techniques with the AutoEncoders to generate the node embeddings and eventually perform the node classifications using the node embeddings. The model predicts patient conditions ranging from common to rare situations. The outcome is deemed to open up opportunities for data querying toward better predictions and accuracy.

Keywords: electronic health record, graph neural network, heterogeneous data, prediction

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Authors: Qing Wu, Xuchun Ye, Kirsten Corazzini

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Objective: It is increasingly recognized that patients’ rational and meaningful engagement in healthcare could make important contributions to their health care and safety management. However, recent evidence indicated that patients' actual roles in healthcare didn’t match their desired roles, and many patients reported a less active role than desired, which suggested that patient engagement in healthcare may be influenced by various factors. This study aimed to analyze influencing factors on patient engagement and explore the influence mechanism, which will be expected to contribute to the strategy development of patient engagement in healthcare. Methods: On the basis of analyzing the literature and theory study, the research framework was developed. According to the research framework, a cross-sectional survey was employed using the behavior and willingness of patient engagement in healthcare questionnaire, Chinese version All Aspects of Health Literacy Scale, Facilitation of Patient Involvement Scale and Wake Forest Physician Trust Scale, and other influencing factor related scales. A convenience sample of 580 patients was recruited from 8 general hospitals in Shanghai, Jiangsu Province, and Zhejiang Province. Results: The results of the cross-sectional survey indicated that the mean score for the patient engagement behavior was (4.146 ± 0.496), and the mean score for the willingness was (4.387 ± 0.459). The level of patient engagement behavior was inferior to their willingness to be involved in healthcare (t = 14.928, P ＜ 0.01). The influencing mechanism model of patient engagement in healthcare was constructed by the path analysis. The path analysis revealed that patient attitude toward engagement, patients’ perception of facilitation of patient engagement and health literacy played direct prediction on the patients’ willingness of engagement, and standard estimated values of path coefficient were 0.341, 0.199, 0.291, respectively. Patients’ trust in physician and the willingness of engagement played direct prediction on the patient engagement, and standard estimated values of path coefficient were 0.211, 0.641, respectively. Patient attitude toward engagement, patients’ perception of facilitation and health literacy played indirect prediction on patient engagement, and standard estimated values of path coefficient were 0.219, 0.128, 0.187, respectively. Conclusions: Patients engagement behavior did not match their willingness to be involved in healthcare. The influencing mechanism model of patient engagement in healthcare was constructed. Patient attitude toward engagement, patients’ perception of facilitation of engagement and health literacy posed indirect positive influence on patient engagement through the patients’ willingness of engagement. Patients’ trust in physician and the willingness of engagement had direct positive influence on the patient engagement. Patient attitude toward engagement, patients’ perception of physician facilitation of engagement and health literacy were the factors influencing the patients’ willingness of engagement. The results of this study provided valuable evidence on guiding the development of strategies for promoting patient rational and meaningful engagement in healthcare.

Keywords: healthcare, patient engagement, influencing factor, the mechanism

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Authors: Mojtaba Sadeghi, Farshid Baniassadi, Hamed Kashani

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One of the challenging issues faced by seismic retrofitting consultants and employers is quick decision-making on the demolition or retrofitting of a structure at the current time or in the future. For this reason, the existing models proposed by researchers have only covered one of the aspects of cost, execution method, and structural vulnerability. Given the effect of each factor on the final decision, it is crucial to devise a new comprehensive model capable of simultaneously covering all the factors. This study attempted to provide an integrated framework that can be utilized to select the most appropriate earthquake risk mitigation solution for buildings. This framework can overcome the limitations of current models by taking into account several factors such as cost, execution method, risk-taking and structural failure. In the newly proposed model, the database and essential information about retrofitting projects are developed based on the historical data on a retrofit project. In the next phase, an analysis is conducted in order to assess the vulnerability of the building under study. Then, artificial neural networks technique is employed to calculate the cost of retrofitting. While calculating the current price of the structure, an economic analysis is conducted to compare demolition versus retrofitting costs. At the next stage, the optimal method is identified. Finally, the implementation of the framework was demonstrated by collecting data concerning 155 previous projects.

Keywords: decision making, demolition, construction management, seismic retrofit

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Authors: Lucile Soudani, Hervé Illy, Rémi Bouchié

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Mould growth in living environments has been widely reported for decades all throughout the world. A higher level of moisture in housings can lead to building degradation, chemical component emissions from construction materials as well as enhancing mould growth within the envelope elements or on the internal surfaces. Moreover, a significant number of studies have highlighted the link between mould presence and the prevalence of respiratory diseases. In recent years, the proportion of biobased materials used in construction has been increasing, as seen as an effective lever to reduce the environmental impact of the building sector. Besides, bio-based materials are also hygroscopic materials: when in contact with the wet air of a surrounding environment, their porous structures enable a better capture of water molecules, thus providing a more suitable background for mould growth. Many studies have been conducted to develop reliable models to be able to predict mould appearance, growth, and decay over many building materials and external exposures. Some of them require information about temperature and/or relative humidity, exposure times, material sensitivities, etc. Nevertheless, several studies have highlighted a large disparity between predictions and actual mould growth in experimental settings as well as in occupied buildings. The difficulty of considering the influence of all parameters appears to be the most challenging issue. As many complex phenomena take place simultaneously, a preliminary study has been carried out to evaluate the feasibility to sadopt a reliability approach rather than a deterministic approach. Both epistemic and random uncertainties were identified specifically for the prediction of mould appearance and growth. Several studies published in the literature were selected and analysed, from the agri-food or automotive sectors, as the deployed methodology appeared promising.

Keywords: bio-based materials, mould growth, numerical prediction, reliability approach

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Authors: Yuan Tian, Benhe Gao

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This paper aims to investigate a two stage supply chain of one leading supplier and one following retailer that experiences two factors perturbation out of supplier's production cost, retailer's marginal cost and retail price in stochastic demand environment. Granted that risk neutral condition has long been discussed, little attention has been given to disruptions under the premise of risk neutral supplier and risk aversion retailer. We establish the optimal order quantity and revealed the profit distribution coefficient in risk-neutral static model, make adjustment under disruption scenario, and then select utility function method for risk aversion model. Using buy-back contract policy, the improvement of parameters can achieve channel coordination where Pareto optimal is realized.

Keywords: supply chain coordination, disruption management, buy-back contract, lose aversion

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Authors: Ali Heydarimoghim

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In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

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Authors: Mohammad Reza Ebrahimi, Behnaz Mahdaviani

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Increasing renewable sources such photovoltaic are the reason of environmental pollution. Because photovoltaic generates power in low voltage, first, generated power should increase. Usually, distributed generation injects their power to AC-Grid, hence after voltage increasing an inverter is needed to convert DC power to AC power. This results in utilization two series converter that grows cost, complexity, and low efficiency. In this paper a single stage inverter is utilized to boost and invert in one stage. Control of this scheme is easier, and its initial cost decreases comparing to conventional double stage inverters. A simple control scheme is used to control active power as well as minimum total harmonic distortion (THD) in injected current. Simulations in MATLAB demonstrate better outputs comparing with conventional approaches.

Keywords: maximum power point tracking, boost inverter, control strategy, three phase inverter

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Authors: Arminder Singh Walia, Vineet Srivastava, Vivek Jain

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In Electrical Discharge Machining (EDM) operations, the workpiece confers to the shape of the tool. Further, the cost of the tool contributes the maximum effect on total operation cost. Therefore, the shape and profile of the tool become highly significant. Thus, in this work, an attempt has been made to study the effect of process parameters on the shape of the tool. Copper has been used as the tool material for the machining of AISI 52100 die steel. The shape of the tool has been evaluated by determining the difference in out of roundness of tool before and after machining. Statistical model has been developed and significant process parameters have been identified which affect the shape of the tool. Optimum process parameters have been identified which minimizes the shape distortion.

Keywords: discharge current, flushing pressure, pulse-on time, pulse-off time, out of roundness, electrical discharge machining

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Authors: Prabha Rohatgi

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To obtain an efficient control over a huge amount of inventory of drugs in pharmacy department of any hospital, generally, the medicines are categorized on the basis of their cost ‘ABC’ (Always Better Control), first and then categorize on the basis of their criticality ‘VED’ (Vital, Essential, desirable) for prioritization. About one-third of the annual expenditure of a hospital is spent on medicines. To minimize the inventory investment, the hospital management may like to keep the medicines inventory low, as medicines are perishable items. The main aim of each and every hospital is to provide better services to the patients under certain limited resources. To achieve the satisfactory level of health care services to outdoor patients, a hospital has to keep eye on the wastage of medicines because expiry date of medicines causes a great loss of money though it was limited and allocated for a particular period of time. The objectives of this study are to identify the categories of medicines requiring incentive managerial control. In this paper, to minimize the total inventory cost and the cost associated with the wastage of money due to expiry of medicines, an inventory control model is used as an estimation tool and then nonlinear programming technique is used under limited budget and fixed number of orders to be placed in a limited time period. Numerical computations have been given and shown that by using scientific methods in hospital services, we can give more effective way of inventory management under limited resources and can provide better health care services. The secondary data has been collected from a hospital to give empirical evidence.

Keywords: ABC-VED inventory classification, multi item inventory problem, nonlinear programming technique, optimization of EOQ

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Authors: Sarah Abdourraziq

Abstract:

Photovoltaic (PV) water pumping system is one of the most used and important applications in the field of solar energy. However, the cost and the efficiency are still a concern, especially with continued change of solar radiation and temperature. Then, the improvement of the efficiency of the system components is a good solution to reducing the cost. The use of maximum power point tracking (MPPT) algorithms to track the output maximum power point (MPP) of the PV panel is very important to improve the efficiency of the whole system. In this paper, we will present a definition of the functioning of MPPT technique, and a detailed model of each component of PV pumping system with Matlab-Simulink, the results shows the influence of the changing of solar radiation and temperature in the output characteristics of PV panel, which influence in the efficiency of the system. Our system consists of a PV generator, a boost converter, a motor-pump set, and storage tank.

Keywords: PV panel, boost converter, MPPT, MPP, PV pumping system

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Authors: Arnab Adhikari, Arnab Bisi

Abstract:

Since the inception, the fashion apparel supply chain is facing the problem of high demand uncertainty. Often the demand volatility compels the corresponding supply chain member to incur substantial holding cost and opportunity cost in case of the overproduction and the underproduction scenario, respectively. It leads to an uncoordinated fashion apparel supply chain. There exist several scholarly works to achieve coordination in the fashion apparel supply chain by employing the different contracts such as the buyback contract, the revenue sharing contract, the option contract, and so on. Specially, the application of option contract in the apparel industry becomes prevalent with the changing global scenario. Exploration of existing literature related to the option contract reveals that most of the research works concentrate on the one direction demand adjustment i.e. either to match the demand upwards or downwards. Here, we present a holistic approach to coordinate a dyadic fashion apparel supply chain comprising one manufacturer and one retailer with the help of bidirectional option contract. We show a combination of wholesale price contract and bidirectional option contract can coordinate the under expanded supply chain. We also propose a framework that captures the variation of the apparel retailer’s order quantity and the apparel manufacturer’s production quantity with the changing exercise price for the different ranges of the option price. We analytically explore that corresponding cost parameters of the supply chain members along with the nature of demand distribution play an instrumental role in the coordination as well as the retailer’s ordering decision.

Keywords: fashion apparel supply chain, supply chain coordination, wholesale price contract, bidirectional option contract

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Authors: Govindaraj Ramanathan

Abstract:

The time delay and the structural stability are major issues in big size projects due to several factors. Improper planning and poor coordination lead to delay in construction, which sometimes result in reworking or rebuilding. This definitely increases the cost and time of project. This situation stresses the structural engineers to plan out of the limits of contemporary technology utilizing non-chronological approach with creative ideas. One of the strategies to solve this issue is through structural integrity solutions in a cost-effective way. We have faced several problems in a project worth 470 million USD, and one such issue is crane girder installation with composite steel beams. We have applied structural integrity approach with the proper and revised planning schedule to solve the problem efficiently with minimal expenses.

Keywords: construction management, delay, non-chronological approach, composite beam, structural integrity

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Authors: Alex Ellery

Abstract:

Solar power satellites (SPS), despite their promise as a clean energy source, have been relegated out of consideration due to their enormous cost and technological challenge. It has been suggested that for solar power satellites to become economically feasible, launch costs must decrease from their current $20,000/kg to < $200/kg. Even with the advent of single-stage-to-orbit launchers which propose launch costs dropping to $2,000/kg, this will not be realized. Yet, the advantages of solar power satellites are many. Here, I present a novel approach to reduce the specific cost of solar power satellites to ~$1/kg by leveraging two enabling technologies – in-situ resource utilization and 3D printing. The power of such technologies will open up enormous possibilities for providing additional options for combating climate change whilst meeting demands for global energy. From the constraints imposed by in-situ resource utilization, a novel approach to solar energy conversion in SPS may be realized.

Keywords: clean energy sources, in-situ resource utilisation, solar power satellites, thermionic emission

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Authors: Tukundane Hillary

Abstract:

This research paper analytically evaluates the project control practice levels used by the building construction companies within Kampala, Uganda. The research also assesses the outcome of project control practices on the productivity of the companies. The research was performed to ascertain the current control practices among 160 respondents from various construction companies registered with the Uganda Registration Services Bureau. This research used amalgamation from multiple literature to obtain the variables. The research adopts 34 standard control practices from four vital project control duties: planning, monitoring, analyzing, and reporting. These project control tasks were organized using mean response ratings grounded on their relevance to the construction companies. Results showed that evaluating performance with the use of curves (4.32), timely access to information and encouragement (4.55), report representation using quantitative tools 4.75, and cost value comparison application during analysis (4.76) were rated least among the control practices. On the other hand, the top project control practices included formulation of the project schedule (8.88), Project feasibility validation (8.86), Budgeting for each activity (8.84), Key project route definition (8.81), Team awareness of the budget (8.77), Setting realistic targets for projects (8.50) and Consultation from subcontractors (8.74). From the results obtained by the sample respondents specified, it can be concluded that planning is the most vital project control task practiced in the building construction industry in Uganda. In addition, this research ascertained a substantial relationship between project control practices and the performance of building construction companies. Accordingly, this research recommends that project control practices be effectively observed by both contracting and consulting companies to enhance their overall performance and governance.

Keywords: cost value, project control, cost control, time control, project performance, control practices

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Authors: Atasi Dan, Kamanio Chattopadhyay, Bikramjit Basu

Abstract:

A cost-effective titanium diboride (TiB2) paint coating has been developed on stainless steel substrate using commercially available polyvinylpyrrolidone as a binder by convenient dip-coating technique. The emittance of the coating has been explored by tailoring various process parameters to obtain highest thermal radiation. The optimized coating has achieved a high thermal emittance of 0.85. In addition, the coating exhibited an excellent thermal stability while heat-treated at 500 °C in air. Along with the emittance, the structural and physical properties of the As-deposited and heat-treated coatings have been investigated systematically. The high temperature annealing has not affected the emittance, chemical composition and morphology of the coating significantly. Hence, the fabricated paint coating is expected to open up new possibilities for using it as a low-cost, thermally stable emitter in high temperature applications.

Keywords: titanium diboride, emittance, paint coating, thermal stability

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Authors: B. Rakjarit, S. Athichanagorn

Abstract:

Double displacement process is a method in which gas is injected at an updip well to displace the oil bypassed by waterflooding operation from downdip water injector. As gas injection is costly and a large amount of gas is needed, gas dump-flood from multiple gas reservoirs is an attractive alternative. The objective of this paper is to demonstrate the benefits of the novel approach of double displacement process via gas dump-flood from multiple gas reservoirs. A reservoir simulation model consisting of a dipping oil reservoir and several underlying layered gas reservoirs was constructed in order to investigate the performance of the proposed method. Initially, water was injected via the downdip well to displace oil towards the producer located updip. When the water cut at the producer became high, the updip well was shut in and perforated in the gas zones in order to dump gas into the oil reservoir. At this point, the downdip well was open for production. In order to optimize oil recovery, oil production and water injection rates and perforation strategy on the gas reservoirs were investigated for different numbers of gas reservoirs having various depths and thicknesses. Gas dump-flood from multiple gas reservoirs can help increase the oil recovery after implementation of waterflooding upto 10%. Although the amount of additional oil recovery is slightly lower than the one obtained in conventional double displacement process, the proposed process requires a small completion cost of the gas zones and no operating cost while the conventional method incurs high capital investment in gas compression facility and high-pressure gas pipeline and additional operating cost. From the simulation study, oil recovery can be optimized by producing oil at a suitable rate and perforating the gas zones with the right strategy which depends on depths, thicknesses and number of the gas reservoirs. Conventional double displacement process has been studied and successfully implemented in many fields around the world. However, the method of dumping gas into the oil reservoir instead of injecting it from surface during the second displacement process has never been studied. The study of this novel approach will help a practicing engineer to understand the benefits of such method and can implement it with minimum cost.

Keywords: gas dump-flood, multi-gas layers, double displacement process, reservoir simulation

Procedia PDF Downloads 411