Search results for: cost savings

Authors: Edmund M. Muthigani

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Innovation in the construction industry has been characterized by new products and processes especially in slum upgrading. The need for low cost housing has motivated stakeholders to think outside the box in coming up with solutions. This paper explored innovative construction technologies that have been used in slum upgrading. The main objectives of the paper was to examine innovations in the construction housing sector and to show how incremental derived demand for decent housing has led to adoption of innovative technologies and materials. Systematic literature review was used to review studies on innovative construction technologies in slum upgrading. The review revealed slow process of innovations in the construction industry due to risk aversion by firms and the hesitance to adopt by firms and individuals. Low profit margins in low cost housing and lack of sufficient political support remain the major hurdles to innovative techniques adoption that can actualize right to decent housing. Conventional construction materials have remained unaffordable to many people and this has negated them decent housing. This has necessitated exploration of innovative materials to realize low cost housing. Stabilized soil blocks and sisal-cement roofing blocks are some of the innovative construction materials that have been utilized in slum upgrading. These innovative materials have not only lowered the cost of production of building elements but also eased costs of transport as the raw materials to produce them are readily available in or within the slum sites. Despite their shortcomings in durability and compressive strength, they have proved worthwhile in slum upgrading. Production of innovative construction materials and use of innovative techniques in slum upgrading also provided employment to the locals.

Keywords: construction, housing, innovation, slum, technology

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Authors: Chang Liu, John Nash, Stephen D. Prior

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This paper presents the design and implementation details of a complete unmanned aerial system (UAS) based on commercial-off-the-shelf (COTS) components, focusing on safety, security, search and rescue scenarios in GPS-denied environments. In particular, the aerial platform is capable of semi-autonomously navigating through extremely low-light, GPS-denied indoor environments based on onboard sensors only, including a downward-facing optical flow camera. Besides, an additional low-cost payload camera system is developed to stream both infrared video and visible light video to a ground station in real-time, for the purpose of detecting sign of life and hidden humans. The total cost of the complete system is estimated to be $1150, and the effectiveness of the system has been tested and validated in practical scenarios.

Keywords: unmanned aerial system, commercial-off-the-shelf, extremely low-light, GPS-denied, optical flow, infrared video

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Authors: Syed Asif Ali Naqvi, Muhammad Azeem Tufail

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Inadequate sanitation causes direct costs of treating illnesses and loss of income through reduced productivity. This study estimated the economic cost of health (ECH) due to poor sanitation and factors determining the lack of access to latrine for the rural, backward hamlets and slums of district Faisalabad, Pakistan. Cross sectional data were collected and analyzed for the study. As the population under study was homogenous in nature, it is why a simple random sampling technique was used for the collection of data. Data of 440 households from 4 tehsils were gathered. The ordinary least square (OLS) model was used for health cost analysis, and the Probit regression model was employed for determining the factors responsible for inaccess to toilets. The results of the study showed that condition of toilets, situation of sewerage system, access to adequate sanitation, Cholera, diarrhea and dysentery, Water and Sanitation Agency (WASA) maintenance, source of medical treatment can plausibly have a significant connection with the dependent variable. Outcomes of the second model showed that the variables of education, family system, age, and type of dwelling have positive and significant sway with the dependent variable. Variable of age depicted an insignificant association with access to toilets. Variable of monetary expenses would negatively influence the dependent variable. Findings revealed the fact, health risks are often exacerbated by inadequate sanitation, and ultimately, the cost on health also surges. Public and community toilets for youths and social campaigning are suggested for public policy.

Keywords: sanitation, toilet, economic cost of health, water, Punjab

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Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

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Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

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Authors: Michael John S. Maceda

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Waste has been a global concern aggravated by climate change. In the case of Imus, Cavite which in the past has little or no regard to waste experienced heavy flooding during August 19, 2013. This event led to a full blown implementation of Municipal Solid Waste Management integrating participation and the use of low-cost technology to reduce the amount of waste generated. The methodology employed by the city of Imus, provided a benchmark in the province of Cavite. Reducing the amount of waste generated and Solid Waste Management Cost.

Keywords: SWM, IMUS, composting, policy

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Authors: Paul Kipchumba

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Kenya is an East African Country lying at the Equator. It had a population of 46 million in 2015 with an annual growth rate of 2.7%, making a population of at least 65 million in 2030. Kenya’s GDP in 2015 was about 63 billion USD with per capita GDP of about 1400 USD. The rural population is 74%, whereas urban population is 26%. Kenya grapples with not only access to energy but also with energy security. There is direct correlation between economic growth, population growth, and energy consumption. Kenya’s energy composition is at least 74.5% from renewable energy with hydro power and geothermal forming the bulk of it; 68% from wood fuel; 22% from petroleum; 9% from electricity; and 1% from coal and other sources. Wood fuel is used by majority of rural and poor urban population. Electricity is mostly used for lighting. As of March 2015 Kenya had installed electricity capacity of 2295 MW, making a per capital electricity consumption of 0.0499 KW. The overall retail cost of electricity in 2015 was 0.009915 USD/ KWh (KES 19.85/ KWh), for installed capacity over 10MW. The actual demand for electricity in 2015 was 3400 MW and the projected demand in 2030 is 18000 MW. Kenya is working on vision 2030 that aims at making it a prosperous middle income economy and targets 23 GW of generated electricity. However, cost and non-cost factors affect generation and consumption of electricity in Kenya. Kenya does not care more about CO2 emissions than on economic growth. Carbon emissions are most likely to be paid by future costs of carbon emissions and penalties imposed on local generating companies by sheer disregard of international law on C02 emissions and climate change. The study methodology was a simulated application of carbon tax on all carbon emitting sources of electricity generation. It should cost only USD 30/tCO2 tax on all emitting sources of electricity generation to have solar as the only source of electricity generation in Kenya. The country has the best evenly distributed global horizontal irradiation. Solar potential after accounting for technology efficiencies such as 14-16% for solar PV and 15-22% for solar thermal is 143.94 GW. Therefore, the paper recommends adoption of solar power for generating all electricity in Kenya in order to attain zero carbon electricity generation in the country.

Keywords: co2 emissions, cost factors, electricity generation, non-cost factors

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Authors: A. Talaei, M. Ahiduzzaman, A. Kumar

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In Canada, an increase in the production of iron and steel is anticipated for satisfying the increasing demand of iron and steel in the oil sands and automobile industries. It is predicted that GHG emissions from iron and steel sector will show a continuous increase till 2030 and, with emissions of 20 million tonnes of carbon dioxide equivalent, the sector will account for more than 2% of total national GHG emissions, or 12% of industrial emissions (i.e. 25% increase from 2010 levels). Therefore, there is an urgent need to improve the energy intensity and to implement energy efficiency measures in the industry to reduce the GHG footprint. This paper analyzes the current energy consumption in the Canadian iron and steel industries and identifies energy efficiency opportunities to improve the energy intensity and mitigate greenhouse gas emissions from this industry. In order to do this, a demand tree is developed representing different iron and steel production routs and the technologies within each rout. The main energy consumer within the industry is found to be flared heaters accounting for 81% of overall energy consumption followed by motor system and steam generation each accounting for 7% of total energy consumption. Eighteen different energy efficiency measures are identified which will help the efficiency improvement in various subsector of the industry. In the sintering process, heat recovery from coolers provides a high potential for energy saving and can be integrated in both new and existing plants. Coke dry quenching (CDQ) has the same advantages. Within the blast furnace iron-making process, injection of large amounts of coal in the furnace appears to be more effective than any other option in this category. In addition, because coal-powered electricity is being phased out in Ontario (where the majority of iron and steel plants are located) there will be surplus coal that could be used in iron and steel plants. In the steel-making processes, the recovery of Basic Oxygen Furnace (BOF) gas and scrap preheating provides considerable potential for energy savings in BOF and Electric Arc Furnace (EAF) steel-making processes, respectively. However, despite the energy savings potential, the BOF gas recovery is not applicable in existing plants using steam recovery processes. Given that the share of EAF in steel production is expected to increase the application potential of the technology will be limited. On the other hand, the long lifetime of the technology and the expected capacity increase of EAF makes scrap preheating a justified energy saving option. This paper would present the results of the assessment of the above mentioned options in terms of the costs and GHG mitigation potential.

Keywords: Iron and Steel Sectors, Energy Efficiency Improvement, Blast Furnace Iron-making Process, GHG Mitigation

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

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Institutional design is an important aspect in efficient water resource management. In Nepal, the water supply in both farmers’- and agency-managed irrigation systems has become sub-standard because of the weak institutional framework. This study characterizes both forms of the schemes and links existing institution and governance of the schemes with its performance with reference to cost recovery, maintenance of the schemes and water distribution throughout the schemes. For this, two types of surveys were conducted. A management survey of ten farmers’-managed and five agency-managed schemes of Chitwan valley and its periphery was done. Also, a farm survey comprising 25 farmers from each of head, middle and tail regions of both schemes; Narayani Lift Irrigation Project (agency-managed) and Khageri Irrigation System (farmers’-managed) of Chitwan Valley as a case study was conducted. The results showed that cost recovery of agency-managed schemes in 2015 was less than two percent whereas service fee collection rate in farmers’-managed schemes was nearly 2/3rd that triggered poor maintenance of the schemes and unequal distribution of water throughout the schemes. Also, the institution on practice is unable to create any incentives for farmers for economical use of water as well as willingness to pay for its use. This, thus, compels the need of refined institutional framework which has been suggested in this paper aiming to improve the cost recovery and better water distribution throughout the irrigation schemes.

Keywords: cost recovery, governance, institution, schemes' performance

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Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

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Authors: Danijela Tuljak-Suban, Valter Suban

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Food as perishable goods represents a specific and sensitive part in the supply chain theory, since changing of its physical or chemical characteristics considerably influences the approach to stock management. The most delicate phase of this process is transportation, where it becomes difficult to ensure stability conditions that limit the deterioration, since the value of the deterioration rate could be easily influenced by the transportation mode. Fuzzy definition of variables allows taking into account these variations. Furthermore an appropriate choice of the defuzzification method permits to adapt results, as much as possible, to real conditions. In the article will be applied the those methods to the relationship between the deterioration rate of perishable goods and transportation by ship, with the aim: (a) to minimize the total costs function, defined as the sum of the ordering cost, holding cost, disposing cost and transportation costs, and (b) to improve supply chain sustainability by reducing the environmental impact and waste disposal costs.

Keywords: perishable goods, fuzzy reasoning, transport by ship, supply chain sustainability

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Authors: Viveka Jackson, Erouscilla Joseph, Denise Beckles, Thomas Christopher

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Sulphur Dioxide (SO2) has been defined as a non-flammable, non-explosive, colourless gas, having a pungent, irritating odour, and is one of the main gases emitted from volcanoes. Sulphur dioxide has been recorded in concentrations hazardous to humans (0.25 – 0.5 ppm (~650 – 1300 μg/m3), downwind of many volcanoes and hence warrants constant air-quality monitoring around these sites. It has been linked to an increase in chronic respiratory disease attributed to long-term exposures and alteration in lung and other physiological functions attributed to short-term exposures. Sulphur Springs in Saint Lucia is a highly active geothermal area, located within the Soufrière Volcanic Centre, and is a park widely visited by tourists and locals. It is also a current source of continuous volcanic emissions via its many fumaroles and bubbling pools, warranting concern by residents and visitors to the park regarding the effects of exposure to these gases. In this study, we introduce a novel SO2 measurement system for the monitoring and quantification of ambient levels of airborne volcanic SO2 using low-cost technology. This work involves the extensive production of low-cost SO2 monitors/samplers, as well as field examination in tandem with standard commercial samplers (SO2 diffusion tubes). It also incorporates community involvement in the volcanic monitoring process as non-professional users of the instrument. We intend to present the preliminary monitoring results obtained from the low-cost samplers, to identify the areas in the Park exposed to high concentrations of ambient SO2, and to assess the feasibility of the instrument for non-professional use and application in volcanic settings

Keywords: ambient SO2, community-based monitoring, risk-reduction, sulphur springs, low-cost

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Authors: Ashwini Gowda K. S, Archana M. R, Anjaneyappa V

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This paper presents pavement maintenance and management system (PMMS) to obtain optimum pavement maintenance and rehabilitation strategies and maintenance scheduling for a network using a multi-objective genetic algorithm (MOGA). Optimal pavement maintenance & rehabilitation strategy is to maximize the pavement condition index of the road section in a network with minimum maintenance and rehabilitation cost during the planning period. In this paper, NSGA-II is applied to perform maintenance optimization; this maintenance approach was expected to preserve and improve the existing condition of the highway network in a cost-effective way. The proposed PMMS is applied to a network that assessed pavement based on the pavement condition index (PCI). The minimum and maximum maintenance cost for a planning period of 20 years obtained from the non-dominated solution was found to be 5.190x10¹⁰ ₹ and 4.81x10¹⁰ ₹, respectively.

Keywords: genetic algorithm, maintenance and rehabilitation, optimization technique, pavement condition index

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Authors: Hamid Reza Tabatabaiefar, Bita Mansoury, Mohammad Javad Khadivi Zand

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The current energy and climate change impacts of the residential building sector in Australia are significant. Thus, the Australian Government has introduced more stringent regulations to improve building energy efficiency. In 2006, the Australian residential building sector consumed about 11% (around 440 Petajoule) of the total primary energy, resulting in total greenhouse gas emissions of 9.65 million tonnes CO2-eq. The gas and electricity consumption of residential dwellings contributed to 30% and 52% respectively, of the total primary energy utilised by this sector. Around 40 percent of total energy consumption of Australian buildings goes to heating and cooling due to the low thermal performance of the buildings. Thermal performance of buildings determines the amount of energy used for heating and cooling of the buildings which profoundly influences energy efficiency. Employing sustainable design principles and effective use of construction materials can play a crucial role in improving thermal performance of new and existing buildings. Even though awareness has been raised, the design phase of refurbishment projects is often problematic. One of the issues concerning the refurbishment of residential buildings is mostly the consumer market, where most work consists of moderate refurbishment jobs, often without assistance of an architect and partly without a building permit. There is an individual and often fragmental approach that results in lack of efficiency. Most importantly, the decisions taken in the early stages of the design determine the final result; however, the assessment of the environmental performance only happens at the end of the design process, as a reflection of the design outcome. Finally, studies have identified the lack of knowledge, experience and best-practice examples as barriers in refurbishment projects. In the context of sustainable development and the need to reduce energy demand, refurbishing the ageing residential building constitutes a necessary action. Not only it does provide huge potential for energy savings, but it is also economically and socially relevant. Although the advantages have been identified, the guidelines come in the form of general suggestions that fail to address the diversity of each project. As a result, it has been recognised that there is a strong need to develop guidelines for optimised retrofitting of existing residential buildings in order to improve their energy performance. The current study investigates the effectiveness of different energy retrofitting techniques and examines the impact of employing those methods on energy consumption of residential brick veneer buildings in Victoria (Australia). Proposing different remedial solutions for improving the energy performance of residential brick veneer buildings, in the simulation stage, annual energy usage analyses have been carried out to determine heating and cooling energy consumptions of the buildings for different proposed retrofitting techniques. Then, the results of employing different retrofitting methods have been examined and compared in order to identify the most efficient and cost-effective remedial solution for improving the energy performance of those buildings with respect to the climate condition in Victoria and construction materials of the studied benchmark building.

Keywords: brick veneer residential buildings, building energy efficiency, climate change impacts, cost effective remedial solution, energy performance, sustainable design principles

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Authors: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Ka C. Lam, Oluwafunmibi S. Idowu

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Building girth is important in building economics and mostly used in quantities take-off of various cost items. Literature suggests that the use of conceptual quantities can improve the accuracy of cost models. Girth or perimeter of a building can be used to estimate conceptual quantities. Hence, the current paper aims to model the perimeter-area function of buildings shapes for use at the conceptual design stage. A detailed literature review on existing building shape indexes was carried out. An empirical approach was used to study the relationship between area and the shortest length of a four-sided orthogonal polygon. Finally, a mathematical approach was used to establish the observed relationships. The empirical results obtained were in agreement with the mathematical model developed. A new equation termed “conceptual perimeter equation” is proposed. The equation can be used to estimate building envelope quantities such as external wall area, external finishing area and scaffolding area before sketch or detailed drawings are prepared.

Keywords: building envelope, building shape index, conceptual quantities, cost modelling, girth

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Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

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Authors: S. Abdourraziq, M. A. Abdourraziq

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One of the most famous and important applications of solar energy systems is water pumping. It is often used for irrigation or to supply water in countryside or private firm. However, the cost and the efficiency are still a concern, especially with a continued variation of solar radiation and temperature throughout the day. Then, the improvement of the efficiency of the system components is one of the different solutions to reducing the cost. In this paper, we will present a detailed definition of each element of a PV pumping system, and we will present the different MPPT algorithm used in the literature. Our system consists of a PV panel, a boost converter, a motor-pump set, and a storage tank.

Keywords: PV cell, converter, MPPT, MPP, PV pumping system

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Authors: Rodrigo Zepeda

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Transaction cost analysis (TCA) is a way of analyzing the relative performance of different intermediaries and different trading strategies for trades undertaken in financial instruments. It is a way for an investor to determine the overall quality of execution of a particular trade, and there are many different approaches to undertaking TCA. Under the updated Markets in Financial Instruments Directive (2014/65/EU) (MiFID II), investment firms are required when executing orders, to take all sufficient steps to obtain the best possible result for their clients. This requirement for 'Best Execution' must take into account price, costs, speed, likelihood of execution and settlement, size, nature or any other consideration relevant to the execution of the order. The new regulatory compliance framework under MiFID II will now also apply across a very broad range of financial instruments. This article will provide a comprehensive technical analysis of how TCA and Best Execution will significantly change under MiFID II. It will also explain why harmonization of post-trade reporting requirements under MiFID II could potentially support the development of peer group analysis, which in turn could provide a new and highly advanced framework for TCA that could more effectively support Best Execution requirements under MiFID II. The study is significant because there are no studies that have dealt with TCA and Best Execution under MiFID II in the literature.

Keywords: transaction cost analysis, execution quality, best execution, MiFID II, financial instruments

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Authors: Alireza Alesaadi

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Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Fuqiang Wang, Jun Liu, Liyan Cai

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This paper investigates the coordination of the conflicting two-stage low carbon supply chain consisting of upstream and downstream manufacturers. The conflict means that the upstream manufacturer takes action for carbon emissions reduction under carbon trading mechanism while the downstream manufacturer’s production cost rises. It assumes for the Stackelberg game that the upstream manufacturer plays as a leader and the downstream manufacturer does as a follower. Four kinds of the situation of decentralized decision making, centralized decision-making, the production cost sharing contract and the carbon emissions reduction revenue sharing contract under decentralized decision making are considered. The backward induction approach is adopted to solve the game. The results show that the more intense the conflict is, the lower the efficiency of carbon emissions reduction and the higher the retail price is. The optimal investment of the decentralized supply chain under the two contracts is unchanged and still lower than that of the centralized supply chain. Both the production cost sharing contract and the carbon emissions reduction revenue sharing contract cannot coordinate the supply chain, because that the sharing cost or carbon emissions reduction sharing revenue will transfer through the wholesale price mechanism. As a result, it requires more complicated contract forms to coordinate such a supply chain.

Keywords: cap-and-trade mechanism, carbon emissions reduction, conflict, supply chain coordination

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Authors: Laurin Zemmrich, Nicolai Stickler

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With the ongoing debate over how to incorporate sustainability, resilience, and value creation into business strategies, many procurement departments are put under pressure by governments, consumers, non-governmental organizations, and other stakeholders to disclose more information about their supply chains. According to practitioners and experts, procurement benefits the supply chain by increasing transparency and accountability, recruiting new suppliers, and supporting sustainable and ethical sourcing strategies. While most procurement departments establish these objectives, the bulk of activities are not carried out or are not regularly monitored. With the full potential of targeted sourcing still to be realized, procurement executives, in particular, are seeking for short-term cost-cutting impacts to appease external shareholders. We overcome this limitation by using an abductive approach to research and integrating empirical data from a Gioia methodology study design with relevant literature. Our analysis demonstrates that the procurement department has six essential levers aligned with sustainability, resilience, and value creation objectives and contributes to developing a new intra- and interorganizational purpose within the supply chain. Three enablers are identified as having a value-creating effect on supply chain interactions. Additionally, we discovered two impacts that alter the power balance between buyers and suppliers during transactions and have a cost-cutting or cost-avoiding effect. While cost-cutting, cost-avoidance, and dependency-reduction impacts are desirable, redistributing power may also have negative consequences. The article establishes a first strategy framework for evaluating the influence of the procurement department on supply chain transactions, allowing managers to understand better and apply the sourcing function inside a supply chain and embed it throughout the business.

Keywords: supply chain management, resilience, sustainability, value creation, purpose

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Ahmed Aisa, Tariq Iqbal

Abstract:

This letter talks about the ready-to-use design of a solar water heating system because, in Canada, the average consumption of hot water per person is approximately 50 to 75 L per day and the average Canadian household uses 225 L. Therefore, this paper will demonstrate the method of designing a solar water heating system with thermal storage. It highlights the renewable hybrid power system, allowing you to obtain a reliable, independent system with the optimization of the ingredient size and at an improved capital cost. The system can provide hot water for a big building. The main power for the system comes from solar panels. Solar Advisory Model (SAM) and HOMER are used. HOMER and SAM are design models that calculate the consumption of hot water and cost for a house. Some results, obtained through simulation, were for monthly energy production, annual energy production, after tax cash flow, the lifetime of the system and monthly energy usage represented by three types of energy. These are system energy, electricity load electricity and net metering credit.

Keywords: water heating, thermal storage, capital cost solar, consumption

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Authors: Ochuko K. Overen, Golden Makaka, Edson L. Meyer, Sampson Mamphweli

Abstract:

Low-cost housing provided for people with small incomes in South Africa are characterized by poor thermal performance. This is due to inferior craftsmanship with no regard to energy efficient design during the building process. On average, South African households spend 14% of their total monthly income on energy needs, in particular space heating; which is higher than the international benchmark of 10% for energy poverty. Adopting energy efficient passive solar design strategies and superior thermal building materials can create a stable thermal comfort environment indoors. Thereby, reducing energy consumption for space heating. The aim of this study is to analyse the thermal behaviour of a low-cost house integrated with passive solar design features. A low-cost passive solar house with superstructure fly ash brick walls was designed and constructed in Somerset East, South Africa. Indoor and outdoor meteorological parameters of the house were monitored for a period of one year. The ASTM E741-11 Standard was adopted to perform ventilation test in the house. In summer, the house was found to be thermally comfortable for 66% of the period monitored, while for winter it was about 79%. The ventilation heat flow rate of the windows and doors were found to be 140 J/s and 68 J/s, respectively. Air leakage through cracks and openings in the building envelope was 0.16 m3/m2h with a corresponding ventilation heat flow rate of 24 J/s. The indoor carbon dioxide concentration monitored overnight was found to be 0.248%, which is less than the maximum range limit of 0.500%. The prediction percentage dissatisfaction of the house shows that 86% of the occupants will express the thermal satisfaction of the indoor environment. With a good operation of the house, it can create a well-ventilated, thermal comfortable and nature luminous indoor environment for the occupants. Incorporating passive solar design in low-cost housing can be one of the long and immediate solutions to the energy crisis facing South Africa.

Keywords: energy efficiency, low-cost housing, passive solar design, rural development, thermal comfort

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Authors: Ahmed Aljudaya, Derek Ingham, Lin Ma, Kevin Hughes, Mohammed Pourkashanian

Abstract:

Researchers, power companies, and state politicians have given concentrated solar power (CSP) much attention due to its capacity to generate large amounts of electricity whereas overcoming the intermittent nature of solar resources. The Linear Fresnel Reflector (LFR) is a well-known CSP technology type for being inexpensive, having a low land use factor, and suffering from low optical efficiency. The LFR was considered a cost-effective alternative option to the Parabolic Trough Collector (PTC) because of its simplistic design, and this often outweighs its lower efficiency. The LFR has been found to be a promising option for directly producing steam to a thermal cycle in order to generate low-cost electricity, but also it has been shown to be promising for indirect steam generation. The purpose of this important analysis is to compare the annual performance of the Direct Steam Generation (DSG) and Indirect Steam Generation (ISG) of LFR power plants using molten salt and other different Heat Transfer Fluids (HTF) to investigate their technical and economic effects. A 50 MWe solar-only system is examined as a case study for both steam production methods in extreme weather conditions. In addition, a parametric analysis is carried out to determine the optimal solar field size that provides the lowest Levelized Cost of Electricity (LCOE) while achieving the highest technical performance. As a result of optimizing the optimum solar field size, the solar multiple (SM) is found to be between 1.2 – 1.5 in order to achieve as low as 9 Cent/KWh for the direct steam generation of the linear Fresnel reflector. In addition, the power plant is capable of producing around 141 GWh annually and up to 36% of the capacity factor, whereas the ISG produces less energy at a higher cost. The optimization results show that the DSG’s performance overcomes the ISG in producing around 3% more annual energy, 2% lower LCOE, and 28% less capital cost.

Keywords: concentrated solar power, levelized cost of electricity, linear Fresnel reflectors, steam generation

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Authors: Sanjoy Mukherjee

Abstract:

Discussions on concepts of Single Axis Tracker (SAT) are becoming more and more apt for developing countries like India not just as an advancement in racking technology but due to the utmost necessity of reaching at the lowest Levelized Cost of Energy (LCOE) targets. With this increasing competition and significant fall in feed-in tariffs of solar PV projects, developers are under constant pressure to secure investment for their projects and eventually earn profits from them. Moreover, being the second largest populated country, India suffers from scarcity of land because of higher average population density. So, to mitigate the risk of this dual edged sword with reducing trend of unit (kWh) cost at one side and utilization of land on the other, tracking evolved as the call of the hour. Therefore, the prime objectives of this paper are not only to showcase how STT proves to be an effective mechanism to get more gain in Global Incidence in collector plane (G_inc) with respect to traditional mounting systems but also to introduce Seasonally Tilted Tracker (STT) technology as a possible option for high latitude locations.

Keywords: tracking system, grid connected solar PV plant, CAPEX reduction, levelized cost of energy

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Authors: Masoud Rabbani, Majede Smizadeh, Hamed Farrokhi-Asl

Abstract:

We study jointly determining prices and production in a multiple period horizon under a general non-stationary stochastic demand with continuous prices. In some periods we need to increase capacity of production to satisfy demand. This paper presents a model to aid multi-period production capacity planning by quantifying the trade-off between product quality and production cost. The product quality is estimated as the statistical variation from the target performances obtained from the output tolerances of the production machines that manufacture the components. We consider different tolerance for different machines that use to increase capacity. The production cost is estimated as the total cost of owning and operating a production facility during the planning horizon.so capacity planning has cost that impact on price. Pricing products often turns out to be difficult to measure them because customers have a reservation price to pay that impact on price and demand. We decide to determine prices and production for periods after enhance capacity and consider reservation price to determine price. First we use an algorithm base on fuzzy set of the optimal objective function values to determine capacity planning by determine maximize interval from upper bound in minimum objectives and define weight for objectives. Then we try to determine inventory and pricing policies. We can use a lemma to solve a problem in MATLAB and find exact answer.

Keywords: price policy, inventory policy, capacity planning, product quality, epsilon -constraint

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Authors: Ahmed G. Mahgoub, Dahlia H. Hafez, Mostafa A. Abu Kiefa

Abstract:

The Cone Penetration Test (CPT) is a common in-situ test which generally investigates a much greater volume of soil more quickly than possible from sampling and laboratory tests. Therefore, it has the potential to realize both cost savings and assessment of soil properties rapidly and continuously. The principle objective of this paper is to demonstrate the feasibility and efficiency of using artificial neural networks (ANNs) to predict the soil angle of internal friction (Φ) and the soil modulus of elasticity (E) from CPT results considering the uncertainties and non-linearities of the soil. In addition, ANNs are used to study the influence of different parameters and recommend which parameters should be included as input parameters to improve the prediction. Neural networks discover relationships in the input data sets through the iterative presentation of the data and intrinsic mapping characteristics of neural topologies. General Regression Neural Network (GRNN) is one of the powerful neural network architectures which is utilized in this study. A large amount of field and experimental data including CPT results, plate load tests, direct shear box, grain size distribution and calculated data of overburden pressure was obtained from a large project in the United Arab Emirates. This data was used for the training and the validation of the neural network. A comparison was made between the obtained results from the ANN's approach, and some common traditional correlations that predict Φ and E from CPT results with respect to the actual results of the collected data. The results show that the ANN is a very powerful tool. Very good agreement was obtained between estimated results from ANN and actual measured results with comparison to other correlations available in the literature. The study recommends some easily available parameters that should be included in the estimation of the soil properties to improve the prediction models. It is shown that the use of friction ration in the estimation of Φ and the use of fines content in the estimation of E considerable improve the prediction models.

Keywords: angle of internal friction, cone penetrating test, general regression neural network, soil modulus of elasticity

Procedia PDF Downloads 415