Search results for: cost savings

Authors: Auwal Mustapha Imam

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The aim of the energy management system is to monitor and control utilization, access, optimize and manage energy availability. This can be realized through real-time analyses and energy sources and loads data control in a predictive way. Smart-home monitoring and control provide convenience and cost savings by controlling appliances, lights, thermostats and other loads. There may be different categories of loads in the various homes, and the homeowner may wish to control access to solar-generated energy to protect the storage from draining completely. Controlling the power system operation by managing the converter output power and controlling how it feeds the appliances will satisfy the residential load demand. The Internet of Things (IoT) provides an attractive technological platform to connect the two and make home automation and domestic energy utilization easier and more attractive. This paper presents the use of IoT-based control topology to monitor and control power distribution and consumption by DC loads connected to single-input multiple outputs (SIMO) DC-DC converter, thereby reducing leakages, enhancing performance and reducing human efforts. A SIMO converter was first developed and integrated with the IoT/Raspberry Pi control topology, which enables the user to monitor and control power scheduling and load forecasting via an Android app.

Keywords: flyback, converter, DC-DC, photovoltaic, SIMO

Procedia PDF Downloads 47

Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

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Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: production line, layout planning, complexity measurement, optimization, mass customization

Procedia PDF Downloads 393

Authors: J. García-Pérez

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An approach to compute optimum seismic design parameters is presented. It is based on the optimization of the expected present value of the total cost, which includes the initial cost of structures as well as the cost due to earthquakes. Different types of seismicity models are considered, including one for characteristic earthquakes. Uncertainties are included in some variables to observe the influence on optimum values. Optimum seismic design coefficients are computed for three different structural types representing high, medium and low rise buildings, located near and far from the seismic sources. Ordinary and important structures are considered in the analysis. The results of optimum values show an important influence of seismicity models as well as of uncertainties on the variables.

Keywords: importance factors, optimum parameters, seismic losses, seismic risk, total cost

Procedia PDF Downloads 284

Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael

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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.

Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency

Procedia PDF Downloads 33

Authors: Sangwon Han, Chengquan Jin

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Time-cost trade-off (TCTO) is one of the most significant part of construction project management. Despite the significance, current TCTO analysis, based on the Critical Path Method, does not consider resource constraint, and accordingly sometimes generates an impractical and/or infeasible schedule planning in terms of resource availability. Therefore, resource constraint needs to be considered when doing TCTO analysis. In this research, genetic algorithms (GA) based optimization model is created in order to find the optimal schedule. This model is utilized to compare four distinct scenarios (i.e., 1) initial CPM, 2) TCTO without considering resource constraint, 3) resource allocation after TCTO, and 4) TCTO with considering resource constraint) in terms of duration, cost, and resource utilization. The comparison results identify that ‘TCTO with considering resource constraint’ generates the optimal schedule with the respect of duration, cost, and resource. This verifies the need for consideration of resource constraint when doing TCTO analysis. It is expected that the proposed model will produce more feasible and optimal schedule.

Keywords: time-cost trade-off, genetic algorithms, critical path, resource availability

Procedia PDF Downloads 186

Authors: Tony Ngoy Mbodi, Christophe Muanda

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Textile industry is considered as one of the most polluting sectors in terms of effluent volume of discharge and wastewater composition, such as dye, which represents an environmental hazard when discharged without any proper treatment. A study was conducted to investigate the capability of the use of recycled alum sludge (RAS) as an alternative treatment for the reduction of colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH adjustment from dye based synthetic textile industry wastewater. The coagulation/flocculation process was studied for coagulants of Alum:RAS ratio of, 1:1, 2:1, 1:2 and 0:1. Experiments on treating the synthetic wastewater using membrane filtration and adsorption with corn cobs were also conducted. Results from the coagulation experiment were compared to those from adsorption with corn cobs and membrane filtration experiments conducted on the same synthetic wastewater. The results of the RAS experiments were also evaluated against standard guidelines for industrial effluents treated for discharge purposes in order to establish its level of compliance. Based on current results, it can be concluded that reusing the alum sludge as a low-cost material pretreatment method into the coagulation/flocculation process can offer some advantages such as high removal efficiency for disperse dye and economic savings on overall treatment of the industry wastewater.

Keywords: alum, coagulation/flocculation, dye, recycled alum sludge, textile wastewater

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Authors: Eman Elsebaie, A. Sedrak, R. Ziada

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Introduction: In the recent decades, heart failure (HF) has become one of the most prevalent cardio-vascular disease (CVDs), especially in the elderly and the main cause of hospitalization in Egypt cardiology departments. By 2030, the prevalence of HF is expected to increase by 25%. Total direct costs will increase to $818 billion, and the total indirect cost in terms of lost productivity is close to $275 billion. The current study was conducted to estimate the economic costs of services delivered for heart failure patients at the cardiology department in Cairo University Hospitals (CUHs). Aim: To gain an understanding of the cost of heart failure disease and its main drivers aiming to minimize associated health care costs. Subjects and Methods: Economic cost analysis study was conducted for a prospective group of all cases of HF admitted to the cardiology department in CUHs from end of March till end of April 2016 and another retrospective randomized sample from patients with HF, during the first 3 months of 2016 to measure estimated average cost per patient per day. Results: The mean age of the prospective group was 48.6 ± 17.16 years versus 52.3 ± 11.5 years for the retrospective group. The median (IQR) of Length of stay was 15 (15) days in the prospective group versus 9 (16) days in the retrospective group. The average HF inpatient cost/day in the cardiology department during April 2016 was 362.32 (255.5) L.E. versus 391.2(255.9) L.E. during January and February 2016. Conclusion: Up to 70% of expenditure in the management of HF is related to hospital admission. The average cost of such an admission was 5540.03 (IQR=7507.8) L.E. and 4687.4 (IQR=7818.8) L.E. with the average cost per day estimated at 362.32 (IQR=255.5) L.E. and 386.2(IQR=255.9) L.E. in prospective and retrospective groups respectively.

Keywords: health care cost, heart failure, hospitalization, inpatient

Procedia PDF Downloads 242

Authors: Alex Ellery

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Geoengineering approaches to climate change mitigation are unpopular and regarded with suspicion. Of these, space-based approaches are regarded as unworkable and enormously costly. Here, a space-based approach is presented that is modest in cost, fully controllable and reversible, and acts as a natural spur to the development of solar power satellites over the longer term as a clean source of energy. The low-cost approach exploits self-replication technology which it is proposed may be enabled by 3D printing technology. Self-replication of 3D printing platforms will enable mass production of simple spacecraft units. Key elements being developed are 3D-printable electric motors and 3D-printable vacuum tube-based electronics. The power of such technologies will open up enormous possibilities at low cost including space-based geoengineering.

Keywords: 3D printing, in-situ resource utilization, self-replication technology, space-based geoengineering

Procedia PDF Downloads 423

Authors: B. Salehi, D. Andrews, I. Chaer, A. Gillich, A. Chalk, D. Bush

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With the rapid increase of energy consumption in buildings in recent years, especially with the rise in population and growing economies, the importance of energy savings in buildings becomes more critical. One of the key factors in ensuring energy consumption is controlled and kept at a minimum is to utilise building energy modelling at the very early stages of the design. So, building modelling and simulation is a growing discipline. During the design phase of construction, modelling software can be used to estimate a building’s projected energy consumption, as well as building performance. The growth in the use of building modelling software packages opens the door for improvements in the design and also in the modelling itself by introducing novel methods such as building information modelling-based software packages which promote conventional building energy modelling into the digital building design process. To understand the most effective implementation tools, research projects undertaken should include elements of real-world experiments and not just rely on theoretical and simulated approaches. Upon review of the related studies undertaken, it’s evident that they are mostly based on modelling and simulation, which can be due to various reasons such as the more expensive and time-consuming nature of real-time data-based studies. Taking in to account the recent rise of building energy software modelling packages and the increasing number of studies utilising these methods in their projects and research, the accuracy and reliability of these modelling software packages has become even more crucial and critical. This Energy Performance Gap refers to the discrepancy between the predicted energy savings and the realised actual savings, especially after buildings implement energy-efficient technologies. There are many different software packages available which are either free or have commercial versions. In this study, IES VE (Integrated Environmental Solutions Virtual Environment) is used as it is a common Building Energy Modeling and Simulation software in the UK. This paper describes a study that compares real time results with those in a virtual model to illustrate this gap. The subject of the study is a north west facing north-west (345°) facing, naturally ventilated, conservatory within a domestic building in London is monitored during summer to capture real-time data. Then these results are compared to the virtual results of IES VE, which is a commonly used building energy modelling and simulation software in the UK. In this project, the effect of the wrong position of blinds on overheating is studied as well as providing new evidence of Performance Gap. Furthermore, the challenges of drawing the input of solar shading products in IES VE will be considered.

Keywords: building energy modelling and simulation, integrated environmental solutions virtual environment, IES VE, performance gap, real time data, solar shading products

Procedia PDF Downloads 139

Authors: Tarek Aboueldahab, Hanan Farag

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Cost minimization of Multiple Vehicle Routing Problem becomes a critical issue in the field of transportation because it is NP-hard optimization problem and the search space is complex. Many researches use the hybridization of artificial intelligence (AI) models to solve this problem; however, it can not guarantee to reach the best solution due to the difficulty of searching the whole search space. To overcome this problem, we introduce the hybrid model of Discrete Particle Swarm Optimization (DPSO) with a passive congregation which enable searching the whole search space to compromise between both local and global search. The practical experiment shows that our model obviously outperforms other hybrid models in cost minimization.

Keywords: cost minimization, multi-vehicle routing problem, passive congregation, discrete swarm, passive congregation

Procedia PDF Downloads 98

Authors: D. T. Tran, H. P. Tran, L. G. Hoang, V. N. H. Bui, Q. T. Nguyen, A. K. Das

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This paper provides some insight information about a current situation of e-procurement implementation in Vietnam, including opportunities and challenges. A case study of Phuc Thien Company which is classified as a medium enterprise in the country, specialising on animal feed production. Since the technological development rapidly changes, companies have implemented advanced technologies in supply chain management to increase efficiency and gain collaboration amidst partners in their manufacturing and development activities. The findings of this research reveal strengths and ongoing weaknesses when Phuc Thien company internally implemented eProcurement system. Although cost savings, visibility of payment and speedy procurement process are one of the largest benefits of eProcurement implementation, the company faces greater hurdles, such as employee capability to use technology and their resistance to change, that overshadow everything else. In terms of governmental policy, the adaptation of e-invoicing has commenced since June 2015 in Vietnam, legal regulations and administrative framework related to e-Procurement carries various ambiguous in its content and extremely fragment. Hence, this adds a great burden to enterprises in general and Phuc Thien in particular in view of creating higher competitive advantage for animal feed industry in Vietnam as well as South East Asia region.

Keywords: procurement, e-procurement, animal feed industry, efficiency

Procedia PDF Downloads 334

Authors: Je-Seok Shin, Wook-Won Kim, Jin-O Kim

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The offshore wind farm needs to be designed carefully considering economics and reliability aspects. There are many decision-making problems for designing entire offshore wind farm, this paper focuses on an inner grid layout which means the connection between wind turbines as well as between wind turbines and an offshore substation. A methodology proposed in this paper determines the connections and the cable type for each connection section using K-clustering, minimum spanning tree and cable selection algorithms. And then, a cost evaluation is performed in terms of investment, power loss and reliability. Through the cost evaluation, an optimal layout of inner grid is determined so as to have the lowest total cost. In order to demonstrate the validity of the methodology, the case study is conducted on 240MW offshore wind farm, and the results show that it is helpful to design optimally offshore wind farm.

Keywords: offshore wind farm, optimal layout, k-clustering algorithm, minimum spanning algorithm, cable type selection, power loss cost, reliability cost

Procedia PDF Downloads 385

Authors: V. E. Selaule, R. M. Schoeman H. C. Z. Pienaar

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Research has shown that solar energy is a renewable energy resource with the most potential when compared to other renewable energy resources in South Africa. There are many makes of Photovoltaic (PV) panels on the market and it is difficult to assess which to use. PV panel manufacturers use Standard Test Conditions (STC) to rate their PV panels. STC conditions are different from the actual operating environmental conditions were the PV panels are used. This paper describes a practical method to determine the most cost effective available PV panel. The method shows that PV panel manufacturer STC ratings cannot be used to select a cost effective PV panel.

Keywords: PV orientation, PV panel, PV STC, Solar energy

Procedia PDF Downloads 472

Authors: Tarek Aboueldahab, Hanan Farag

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Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization.

Keywords: parallel job shop scheduling problem, artificial intelligence, discrete breeding swarm, car sequencing and operator allocation, cost minimization

Procedia PDF Downloads 188

Authors: Thiraporn Chumphuming, Nuttida Boonmathi, Supattra Thanomsiang, Tawatchai Noree, Suthee Boonchaloem, Rinyaphat Kecharananta

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This research aims to study about the formats of low-cost airlines’ services in domestic route by surveying customers’ requirements and satisfactions in choosing low-cost airlines to travel domestically. Chiang Mai International Airport and other regions in Chiang Mai are the bases where the information is quantitatively collected. Passengers and questionnaires of 400 are the data base in which the researchers collected information from. Statistic units used are Percentage, Weighted Average, and Standard Deviation. The result of the study reveals that the group of 400 representative samples chooses Air Asia the most from overall six low-cost airlines that provide domestic services. Most of the representative samples book plane tickets for their traveling and they book tickets during the promotion time that provides cheap-priced tickets. Averagely, the price for a seat in one flight is around 501-1,000 Thai baht. The result of the satisfaction’s survey analyzed by the Marketing Mix Factors (7Ps) of low-cost airlines, which is divided into 4 parts including services before ticket reservations, services before boarding/purchasing tickets (ground), In-flight services, and Services after boarding they are satisfied with the baggage claim point informing, also gives the information that the passengers are highly satisfied with every process or the services.

Keywords: low-cost airline, service, satisfaction, customers' behavior

Procedia PDF Downloads 225

Authors: Suleiman Obeidat, Nabeel Mandahawi

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In this work, the packaging process for a move is improved. The customers of this move need their household stuff to be moved from their current house to the new one with minimum damage, in an organized manner, on time and with the minimum cost. Our goal was to improve the process between 10% and 20% time efficiency, 90% reduction in damaged parts and an acceptable improvement in the cost of the total move process. The expected ROI was 833%. Many improvement techniques have been used in terms of the way the boxes are prepared, their preparation cost, packing the goods, labeling them and moving them to a place for moving out. DMAIC technique is used in this work: SIPOC diagram, value stream map of “As Is” process, Root Cause Analysis, Maps of “Future State” and “Ideal State” and an Improvement Plan. A value of ROI=624% is obtained which is lower than the expected value of 833%. The work explains the techniques of improvement and the deficiencies in the old process.

Keywords: packaging, lean tools, six sigma, DMAIC methodology, SIPOC

Procedia PDF Downloads 428

Authors: C. Hall, J. Ramos, V. Ramasamy

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Hydrocarbon-based fuel vehicles are a major contributor to air pollution due to harmful emissions produced, leading to a demand for cleaner fuel types. A leader in this pursuit is hydrogen, with its application in vehicles producing zero harmful emissions and the only by-product being water. To compete with the performance of conventional vehicles, hydrogen gas must be stored on-board of vehicles in cylinders at high pressures (35–70 MPa) and have a short refueling duration (approximately 3 mins). However, the fast-filling of hydrogen cylinders causes a significant rise in temperature due to the combination of the negative Joule-Thompson effect and the compression of the gas. This can lead to structural failure and therefore, a maximum allowable internal temperature of 85°C has been imposed by the International Standards Organization. The technological solution to tackle the issue of rapid temperature rise during the refueling process is to decrease the temperature of the gas entering the cylinder. Pre-cooling of the gas uses a heat exchanger and requires energy for its operation. Thus, it is imperative to determine the least amount of energy input that is required to lower the gas temperature for cost savings. A validated universal thermodynamic model is used to identify an energy-efficient pre-cooling strategy. The model requires negligible computational time and is applied to previously validated experimental cases to optimize pre-cooling requirements. The pre-cooling characteristics include the location within the refueling timeline and its duration. A constant pressure-ramp rate is imposed to eliminate the effects of rapid changes in mass flow rate. A pre-cooled gas temperature of -40°C is applied, which is the lowest allowable temperature. The heat exchanger is assumed to be ideal with no energy losses. The refueling of the cylinders is modeled with the pre-cooling split in ten percent time intervals. Furthermore, varying burst durations are applied in both the early and late stages of the refueling procedure. The model shows that pre-cooling in the later stages of the refuelling process is more energy-efficient than early pre-cooling. In addition, the efficiency of pre-cooling towards the end of the refueling process is independent of the pressure profile at the inlet. This leads to the hypothesis that pre-cooled gas should be applied as late as possible in the refueling timeline and at very low temperatures. The model had shown a 31% reduction in energy demand whilst achieving the same final gas temperature for a refueling scenario when pre-cooling was applied towards the end of the process. The identification of the most energy-efficient refueling approaches whilst adhering to the safety guidelines is imperative to reducing the operating cost of hydrogen refueling stations. Heat exchangers are energy-intensive and thus, reducing the energy requirement would lead to cost reduction. This investigation shows that pre-cooling should be applied as late as possible and for short durations.

Keywords: cylinder, hydrogen, pre-cooling, refueling, thermodynamic model

Procedia PDF Downloads 96

Authors: Daniel Puciato, Piotr Oleśniewicz, Julita Markiewicz-Patkowska, Krzysztof Widawski, Michał Rozpara, Władysław Mynarski, Agnieszka Gawlik, Małgorzata Dębska, Soňa Jandová

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Physical activity as a part of people’s everyday life reduces the risk of many diseases, including those induced by lifestyle, e.g. obesity, type 2 diabetes, osteoporosis, coronary heart disease, degenerative arthritis, and certain types of cancer. That refers particularly to professionally active people, including the early senior group working on non-manual positions. The aim of the study is to evaluate the relationship between physical activity and the socio-economic status of non-manual workers from Wroclaw—one of the biggest cities in Poland, a model setting for such investigations in this part of Europe. The crucial problem in the research is to find out the percentage of respondents who meet the health-related recommendations of the World Health Organization (WHO) concerning the volume, frequency, and intensity of physical activity, as well as to establish if the most important socio-economic factors, such as gender, age, education, marital status, per capita income, savings and debt, determine the compliance with the WHO physical activity recommendations. During the research, conducted in 2013, 1,170 people (611 women and 559 men) aged 21–60 years were examined. A diagnostic poll method was applied to collect the data. Physical activity was measured with the use of the short form of the International Physical Activity Questionnaire with extended socio-demographic questions, i.e. concerning gender, age, education, marital status, income, savings or debts. To evaluate the relationship between physical activity and selected socio-economic factors, logistic regression was used (odds ratio statistics). Statistical inference was conducted on the adopted ex ante probability level of p<0.05. The majority of respondents met the volume of physical effort recommended for health benefits. It was particularly noticeable in the case of the examined men. The probability of compliance with the WHO physical activity recommendations was highest for workers aged 21–30 years with secondary or higher education who were single, received highest incomes and had savings. The results indicate the relations between physical activity and socio-economic status in the examined women and men. People with lower socio-economic status (e.g. manual workers) are physically active primarily at work, whereas those better educated and wealthier implement physical effort primarily in their leisure time. Among the investigated subjects, the youngest group of non-manual workers have the best chances to meet the WHO standards of physical activity. The study also confirms that secondary education has a positive effect on the public awareness on the role of physical activity in human life. In general, the analysis of the research indicates that there is a relationship between physical activity and some socio-economic factors of the respondents, such as gender, age, education, marital status, income per capita, and the possession of savings. Although the obtained results cannot be applied for the general population, they show some important trends that will be verified in subsequent studies conducted by the authors of the paper.

Keywords: IPAQ, nonmanual workers, physical activity, socioeconomic factors, WHO

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Authors: Ihsanullah, Muataz Ali Atieh

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In this study, a low-cost adsorbent carbon fly ash (CFA) was used for the removal of Phenol from the water. The adsorbent characteristics were observed by the Thermogravimetric Analysis (TGA), BET specific surface area analyzer, Zeta Potential and Field Emission Scanning Electron Microscopy (FE-SEM). The effect of pH, agitation speed, contact time, adsorbent dosage, and initial concentration of phenol were studied on the removal of phenol from the water. The optimum values of these variables for maximum removal of phenol were also determined. Both Freundlich and Langmuir isotherm models were successfully applied to describe the experimental data. Results showed that low-cost adsorbent phenol can be successfully applied for the removal of Phenol from the water.

Keywords: phenol, fly ash, adsorption, carbon adsorbents

Procedia PDF Downloads 325

Authors: Chiranjit Das, Sanjay Jharkharia

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This study is focused on transport mode selection under lead time variability and emissions constraint. In order to reduce the carbon emissions generation due to transportation, organization has often faced a dilemmatic choice of transport mode selection since logistic cost and emissions reduction are complementary with each other. Another important aspect of transportation decision is lead-time variability which is least considered in transport mode selection problem. Thus, in this study, we provide a comprehensive mathematical based analytical model to decide transport mode selection under emissions constraint. We also extend our work through analysing the effect of lead time variability in the transport mode selection by a sensitivity analysis. In order to account lead time variability into the model, two identically normally distributed random variables are incorporated in this study including unit lead time variability and lead time demand variability. Therefore, in this study, we are addressing following questions: How the decisions of transport mode selection will be affected by lead time variability? How lead time variability will impact on total supply chain cost under carbon emissions? To accomplish these objectives, a total transportation cost function is developed including unit purchasing cost, unit transportation cost, emissions cost, holding cost during lead time, and penalty cost for stock out due to lead time variability. A set of modes is available to transport each node, in this paper, we consider only four transport modes such as air, road, rail, and water. Transportation cost, distance, emissions level for each transport mode is considered as deterministic and static in this paper. Each mode is having different emissions level depending on the distance and product characteristics. Emissions cost is indirectly affected by the lead time variability if there is any switching of transport mode from lower emissions prone transport mode to higher emissions prone transport mode in order to reduce penalty cost. We provide a numerical analysis in order to study the effectiveness of the mathematical model. We found that chances of stock out during lead time will be higher due to the higher variability of lead time and lad time demand. Numerical results show that penalty cost of air transport mode is negative that means chances of stock out zero, but, having higher holding and emissions cost. Therefore, air transport mode is only selected when there is any emergency order to reduce penalty cost, otherwise, rail and road transport is the most preferred mode of transportation. Thus, this paper is contributing to the literature by a novel approach to decide transport mode under emissions cost and lead time variability. This model can be extended by studying the effect of lead time variability under some other strategic transportation issues such as modal split option, full truck load strategy, and demand consolidation strategy etc.

Keywords: carbon emissions, inventory theoretic model, lead time variability, transport mode selection

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Authors: Carmel Khrisna Wong Moreno, Dinah M. Espina

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The increasing price of feed ingredients has prompted farmers to seek feasible feed alternatives like the utilization of locally-grown protein-rich feedstuff which is cheaper but gives a positive result in poultry production. Trichanthera gigantea, a fodder tree which is an excellent alternative as feed ingredient in the Philippines has now gained popularity as feed supplement. This study was conducted to determine the growth and laying performance of commercial hens fed with varying levels of Trichanthera gigantea leaf meal. The incorporation of Trichanthera gigantea leaf meal at 5%, 10%, and 15% into the diet of commercial hens did not affect the growth and laying performance. Results of the study revealed that the weight gain of the birds fed with Trichanthera gigantea supplemented diets was not significantly different with the control (100% commercial layer mash). The voluntary feed intake, feed conversion ratio, weekly average egg weight and egg production of the commercial hens fed with T. gigantea leaf meal supplemented diets were not significantly different from the control. Results of the study showed that the supplementation of Trichanthera gigantea leaf meal of up to 15% into the diets of commercial hens is highly acceptable since it does not affect the growth and laying performance of the birds. In addition, it would mean a 15% savings in production cost from commercial feeds.

Keywords: egg production, growth, laying performance, trichanthera gigantea (nees)

Procedia PDF Downloads 427

Authors: Sahani Rathnasiri, Pritee Ray, Sardar M. N. Isalm, Carlos A. Vega-Mejia

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This study develops a cooperative game theory-based cost-sharing contract model for a business to consumer (B2C) e-commerce supply chain to minimize the overall supply chain costs and the individual costs within an information asymmetry scenario. The objective of this study is to address the issues of strategic interactions among the key players of the e-commerce supply chain operation, which impedes the optimal operational outcomes. Game theory has been included in the field of supply chain management to resolve strategic decision-making issues; however, most of the studies are limited only to two-echelons of the supply chains. Multi-echelon supply chain optimizations based on game-theoretic models are less explored in the previous literature. This study adopts a cooperative game model to focus on the common payoff of operations and addresses the issues of information asymmetry and coordination of a three-echelon e-commerce supply chain. The cost-sharing contract model integrates operational features such as production, inventory management and distribution with the contract related constraints. The outcomes of the model highlight the importance of maintaining lower operational costs by all players to obtain benefits from the cost-sharing contract. Further, the cost-sharing contract ensures true cost revelation, and hence eliminates the information asymmetry issues among the players. Comparing the results of the contract model with the de-centralized e-commerce supply chain operation further emphasizes that the cost-sharing contract derives Pareto-improved outcomes and minimizes the costs of overall e-commerce supply chain operation.

Keywords: cooperative game theory, cost-sharing contract, e-commerce supply chain, information asymmetry

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Authors: Omar Amoudi, Latifa Al Brashdi

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Construction projects are always subject to risks and uncertainties due to its unique and dynamic nature, outdoor work environment, the wide range of skills employed, various parties involved in addition to situation of construction business environment at large. Altogether, these risks and uncertainties affect projects objectives and lead to cost overruns, delay, and poor quality. Construction projects in Oman often experience cost overruns and delay. Managing these risks and reducing their impacts on construction cost requires firstly identifying these risks, and then analyzing their severity on project cost to obtain deep understanding about these risks. This in turn will assist construction managers in managing and tacking these risks. This paper aims to investigate the main risk factors that affect construction projects cost in the Sultanate of Oman. In order to achieve the main aim, literature review was carried out to identify the main risk factors affecting construction cost. Thirty-three risk factors were identified from the literature. Then, a questionnaire survey was designed and distributed among construction professionals (i.e., client, contractor and consultant) to obtain their opinion toward the probability of occurrence for each risk factor and its possible impact on construction project cost. The collected data was analyzed based on qualitative aspects and in several ways. The severity of each risk factor was obtained by multiplying the probability occurrence of a risk factor with its impact. The findings of this study reveal that the most significant risk factors that have high severity impact on construction project cost are: Change of Oil Price, Delay of Materials and Equipment Delivery, Changes in Laws and Regulations, Improper Budgeting, and Contingencies, Lack of Skilled Workforce and Personnel, Delays Caused by Contractor, Delays of Owner Payments, Delays Caused by Client, and Funding Risk. The results can be used as a basis for construction managers to make informed decisions and produce risk response procedures and strategies to tackle these risks and reduce their negative impacts on construction project cost.

Keywords: construction cost, construction projects, Oman, risk factors, risk management

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Authors: R. Gupta, P. Jain, S. Das

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One way to approach construction scheduling optimization problem is to focus on the individual aspects of planning, which can be broadly classified as time scheduling, crew and resource management, and cost control. During the last four decades, construction planning has seen a lot of research, but to date, no paper had attempted to summarize the literature available under important heads. This paper addresses each of aspects separately, and presents the findings of an in-depth literature of the various planning techniques. For techniques dealing with time scheduling, the authors have adopted a rough chronological documentation. For crew and resource management, classification has been done on the basis of the different steps involved in the resource planning process. For cost control, techniques dealing with both estimation of costs and the subsequent optimization of costs have been dealt with separately.

Keywords: construction planning techniques, time scheduling, resource planning, cost control

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Authors: Doseong Eom, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.

Keywords: building energy management, machine learning, operation planning, simulation-based optimization

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Authors: Meisam Zargar, Yurii Pleskachov, Mostafa Abdelkader, Aldaibe Ahmed, Maryam Bayat, Malek H. Walli, Shimendi Okbagabir

Abstract:

The increased need of humankind for foodstuffs highlights the intensification of agricultural production. It is necessary either to increase the size of the sown area or to look for new approaches to improve agricultural land productivity. Developing new areas for cultivation is possible due to the intensification of soil cultivation. Nevertheless, this will decrease the effectiveness of de-carbonization programs since this approach will inevitably increase greenhouse gas emissions. Therefore, searching for new solutions to conserve natural resources while obtaining stable predicted crop yields is a vital scientific and technical task. For a long time, destructive land use methods have been used in crop production. The present stage of civilization's development and implementation of new techniques and methods of tillage and crops require the solution of technological, economic, and environmental problems simultaneously with the possibility of creating conditions for the regeneration of soil resources. Implementing these approaches became possible due to the development of new technology for the cultivation of crops based on the exact selective impact on the object of processing. This technology of particular effects of TIV combines the positive accumulated experience of traditional farming systems and resource-saving approaches. Particularly high-quality indicators and cost savings with introducing TIV can be achieved when used on row crops, including vegetables and melons.

Keywords: agricultural machinery, vegetable, irrigation, strip system

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Authors: Reza Alikhani

Abstract:

This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Temidayo. O. Osunsanmi, Clinton Aigbavboa, Ayodeji Oke

Abstract:

The construction industry is a renowned latecomer to the efficiency offered by the adoption of information technology. Whereas, the banking, manufacturing, retailing industries have keyed into the future by using digitization and information technology as a new approach for ensuring competitive gain and efficiency. The construction industry has yet to fully realize similar benefits because the adoption of ICT is still at the infancy stage with a major concentration on the use of software. Thus, this study evaluates the awareness and readiness of construction professionals towards embracing a full digitalization of the construction industry using construction 4.0. The term ‘construction 4.0’ was coined from the industry 4.0 concept which is regarded as the fourth industrial revolution that originated from Germany. A questionnaire was utilized for sourcing data distributed to practicing construction professionals through a convenience sampling method. Using SPSS v24, the hypotheses posed were tested with the Mann Whitney test. The result revealed that there are no differences between the consulting and contracting organizations on the readiness for adopting construction 4.0 concepts in the construction industry. Using factor analysis, the study discovers that adopting construction 4.0 will improve the performance of the construction industry regarding cost and time savings and also create sustainable buildings. In conclusion, the study determined that construction professionals have a low awareness towards construction 4.0 concepts. The study recommends an increase in awareness of construction 4.0 concepts through seminars, workshops and training, while construction professionals should take hold of the benefits of adopting construction 4.0 concepts. The study contributes to the roadmap for the implementation of construction industry 4.0 concepts in the South African construction industry.

Keywords: building information technology, Construction 4.0, Industry 4.0, smart site

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Authors: Tawfiq Albishri, Abdulmajeed Alqahtani

Abstract:

Battery electric vehicles (BEVs) are increasingly seen as a sustainable alternative to internal combustion engine (ICE) vehicles, primarily due to their environmental and economic benefits. Saudi Arabia's interest in investing in renewable energy and reducing greenhouse gas emissions presents significant potential for the widespread adoption of BEVs in the country. However, several factors have hindered the adoption of BEVs in Saudi Arabia, with high ownership costs being the most prominent barrier. This cost discrepancy is primarily due to the lack of localized production of BEVs and their components, leading to increased import costs, as well as the high initial cost of BEVs compared to ICE vehicles. This paper aims to evaluate the feasibility of BEVs compared to ICE vehicles in Saudi Arabia by conducting a cost of ownership analysis. Furthermore, a sensitivity analysis will be conducted to determine the most significant contributor to the ownership costs of BEVs that, if changed, could expedite their adoption in Saudi Arabia.

Keywords: battery electric vehicles, internal combustion engine, renewable energy, greenhouse gas emissions, total cost of ownership

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Authors: Yamamah Abdulrazaq, Lahieb A. Abrahim, Samuel E. Davies, Iain Shewring

Abstract:

An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal.

Keywords: demand side management, direct load control, electric water heater, indirect load control, non real-time data, real-time data

Procedia PDF Downloads 82