Search results for: cost analysis

Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Jyun-Huei Huang, Ting-I Lee

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Urban heat island effect is derived from the reduction of vegetative cover by urban development. Because plants can improve air quality and microclimate, green walls have been applied as a sustainable design approach to cool building temperature. By using plants to green vertical surfaces, they decrease room temperature and, as a result, decrease the energy use for air conditioning. Based on their structures, green walls can be divided into two categories, green façades and living walls. A green façade uses the climbing ability of a plant itself, while a living wall assembles planter modules. The latter one is widely adopted in public space, as it is time-effective and less limited. Although a living wall saves energy spent on cooling, it is not necessarily cost-effective from the perspective of a lifecycle analysis. The Italian study shows that the overall benefit of a living wall is only greater than its costs after 47 years of its establishment. In Taiwan, urban greening policies encourage establishment of green walls by referring to their benefits of energy saving while neglecting their low performance on cost-effectiveness. Thus, this research aims at understanding the perception of appliers and consumers on the cost-effectiveness of their living wall products from the lifecycle viewpoint. It adopts semi-structured interviews and field observations on the maintenance of the products. By comparing the two results, it generates insights for sustainable urban greening policies. The preliminary finding shows that stakeholders do not have a holistic sense of lifecycle or cost-effectiveness. Most importantly, a living wall well maintained is often with high input due to the availability of its maintenance budget, and thus less sustainable. In conclusion, without a comprehensive sense of cost-effectiveness throughout a product’s lifecycle, it is very difficult for suppliers and consumers to maintain a living wall system while achieve sustainability.

Keywords: case study, maintenance, post-occupancy evaluation, vertical greening

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Authors: R. B. Patil, B. S. Kothavale, L. Y. Waghmode

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Today, the CNC turning center becomes an important machine tool for manufacturing industry worldwide. However, as the breakdown of a single CNC turning center may result in the production of an entire plant being halted. For this reason, operations and preventive maintenance have to be minimized to ensure availability of the system. Indeed, improving the availability of the CNC turning center as a whole, objectively leads to a substantial reduction in production loss, operating, maintenance and support cost. In this paper, fault tree analysis (FTA) method is used for reliability analysis of CNC turning center. The major faults associated with the system and the causes for the faults are presented graphically. Boolean algebra is used for evaluating fault tree (FT) diagram and for deriving governing reliability model for CNC turning center. Failure data over a period of six years has been collected and used for evaluating the model. Qualitative and quantitative analysis is also carried out to identify critical sub-systems and components of CNC turning center. It is found that, at the end of the warranty period (one year), the reliability of the CNC turning center as a whole is around 0.61628.

Keywords: fault tree analysis (FTA), reliability analysis, risk assessment, hazard analysis

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Authors: Riyad Awad, Abdulmohsen Alghadeer, Meshari Otaibi

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Proper operation and maintenance (O&M) activities of high voltage equipment can lead to an increased asset lifecycle and maintain its integrity and reliability. Such a vital process is important to be proactively considered during equipment design and manufacturing phases by removing and eliminating any obstacles in the equipment which adversely affect the (O&M) activities. This paper presents a gap analysis pertaining to difficulties in performing operations and maintenance (O&M) high voltage electrical equipment, includes power transformers, switch gears, motor control center, disconnect switches and circuit breakers. The difficulties are gathered from field personnel, equipment design review comments, quality management system, and lessons learned database. The purpose of the gap analysis is to mitigate and prevent the (O&M) difficulties as early as possible in the design stage of the equipment lifecycle. The paper concludes with several recommendations and corrective actions for all identified gaps in order to reduce the cost (O&M) difficulties and improve the equipment lifecycle.

Keywords: operation and maintenance, high voltage equipment, equipment lifecycle, reduce the cost of maintenance

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Authors: Majid AghaAlikhani, Mostafa Hojati, Saeid Satari-Yuzbashkandi

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This paper studies energy use patterns and relationship between energy input and yield for soybean (Glycine max (L.) Merrill) in Mazandaran province of Iran. In this study, data were collected by administering a questionnaire in face-to-face interviews. Results revealed that the highest share of energy consumption belongs to chemical fertilizers (29.29%) followed by diesel (23.42%) and electricity (22.80%). Our investigations showed that a total energy input of 23404.1 MJ.ha-1 was consumed for soybean production. The energy productivity, specific energy, and net energy values were estimated as 0.12 kg MJ-1, 8.03 MJ kg-1, and 49412.71 MJ.ha-1, respectively. The ratio of energy outputs to energy inputs was 3.11. Obtained results indicated that direct, indirect, renewable and non-renewable energies were (56.83%), (43.17%), (15.78%) and (84.22%), respectively. Three econometric models were also developed to estimate the impact of energy inputs on yield. The results of econometric models revealed that impact of chemical, fertilizer, and water on yield were significant at 1% probability level. Also, direct and non-renewable energies were found to be rather high. Cost analysis revealed that total cost of soybean production per ha was around 518.43$. Accordingly, the benefit-cost ratio was estimated as 2.58. The energy use efficiency in soybean production was found as 3.11. This reveals that the inputs used in soybean production are used efficiently. However, due to higher rate of nitrogen fertilizer consumption, sustainable agriculture should be extended and extension staff could be proposed substitution of chemical fertilizer by biological fertilizer or green manure.

Keywords: Cobbe Douglas function, economical analysis, energy efficiency, energy use patterns, soybean

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Authors: Christos Spandonidis, Stefanos Tsantilas, Elias Sedikos, Nektarios Galiatsatos, Fotios Giannopoulos, Panagiotis Papadopoulos, Nikolaos Demagos, Dimitrios Reppas, Christos Giordamlis

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In the present paper, a low cost, compact and modular Internet of Things (IoT) platform for air quality monitoring in urban areas is presented. This platform comprises of dedicated low cost, low power hardware and the associated embedded software that enable measurement of particles (PM2.5 and PM10), NO, CO, CO₂ and O₃ concentration in the air, along with relative temperature and humidity. This integrated platform acts as part of a greater air pollution data collecting wireless network that is able to monitor the air quality in various regions and neighborhoods of an urban area, by providing sensor measurements at a high rate that reaches up to one sample per second. It is therefore suitable for Big Data analysis applications such as air quality forecasts, weather forecasts and traffic prediction. The first real world test for the developed platform took place in Thessaloniki, Greece, where 16 devices were installed in various buildings in the city. In the near future, many more of these devices are going to be installed in the greater Thessaloniki area, giving a detailed air quality map of the city.

Keywords: distributed sensor system, environmental monitoring, Internet of Things, smart cities

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Authors: Mahshid Hatamzad, Geanette Polanco

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Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Soheila Sadeghi

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Infrastructure projects often encounter contract variations that can significantly deviate from the original tender estimates, leading to cost overruns, schedule delays, and financial implications. This research aims to quantitatively assess the impact of changes in contract variations on project performance by conducting an in-depth analysis of a comprehensive dataset from the Regional Airport Car Park project. The dataset includes tender budget, contract quantities, rates, claims, and revenue data, providing a unique opportunity to investigate the effects of variations on project outcomes. The study focuses on 21 specific variations identified in the dataset, which represent changes or additions to the project scope. The research methodology involves establishing a baseline for the project's planned cost and scope by examining the tender budget and contract quantities. Each variation is then analyzed in detail, comparing the actual quantities and rates against the tender estimates to determine their impact on project cost and schedule. The claims data is utilized to track the progress of work and identify deviations from the planned schedule. The study employs statistical analysis using R to examine the dataset, including tender budget, contract quantities, rates, claims, and revenue data. Time series analysis is applied to the claims data to track progress and detect variations from the planned schedule. Regression analysis is utilized to investigate the relationship between variations and project performance indicators, such as cost overruns and schedule delays. The research findings highlight the significance of effective variation management in construction projects. The analysis reveals that variations can have a substantial impact on project cost, schedule, and financial outcomes. The study identifies specific variations that had the most significant influence on the Regional Airport Car Park project's performance, such as PV03 (additional fill, road base gravel, spray seal, and asphalt), PV06 (extension to the commercial car park), and PV07 (additional box out and general fill). These variations contributed to increased costs, schedule delays, and changes in the project's revenue profile. The study also examines the effectiveness of project management practices in managing variations and mitigating their impact. The research suggests that proactive risk management, thorough scope definition, and effective communication among project stakeholders can help minimize the negative consequences of variations. The findings emphasize the importance of establishing clear procedures for identifying, assessing, and managing variations throughout the project lifecycle. The outcomes of this research contribute to the body of knowledge in construction project management by demonstrating the value of analyzing tender, contract, claims, and revenue data in variation impact assessment. However, the research acknowledges the limitations imposed by the dataset, particularly the absence of detailed contract and tender documents. This constraint restricts the depth of analysis possible in investigating the root causes and full extent of variations' impact on the project. Future research could build upon this study by incorporating more comprehensive data sources to further explore the dynamics of variations in construction projects.

Keywords: contract variation impact, quantitative analysis, project performance, claims analysis

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Authors: Ali Yasin, Ali Kamran, Muhammad Safdar

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In order to reduce the hefty cost involved in terms of time and project cost, the development and application of advanced numerical tools to address the burn-back analysis problem in solid rocket motor design and development is the need of time. Several advanced numerical schemes have been developed in recent times, but their usage in the design of propellant grain of solid rocket motors is very rare. In this paper, an advanced numerical technique named the Level-Set method has been utilized for the burn-back analysis of star grain to study the effect of geometrical parameters on ballistic performance indicators such as solid loading, neutrality, and sliver percentage. In the level set technique, simple finite difference methods may fail quickly and require more sophisticated non-oscillatory schemes for feasible long-time simulation. For internal ballistic calculations, a simplified equilibrium pressure method is utilized. Preliminary results of the operative conditions, for all the combustion time, of star grain burn-back using level set techniques are compared with published results using CAD technique to test the developed numerical model.

Keywords: solid rocket motor, internal ballistic, level-set technique, star grain

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Authors: Abderrahim Bouftou, Kaoutar Aghmih, Fatima Lakhdar, Saâd Oukkass, Sanaa Majid

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Biodegradable and renewable-based polymeric packaging like cellulose acetate (CA) is an alternative to petroleum-based polymers, in the way of low cost and also creates a positive outcome on both environmentally. The objective of the present research was to develop bioactive packaging films from cellulose acetate incorporated with a low-cost cypress essential oil (EO). We prepared cellulose acetate films via solvent casting method incorporating 0, 10, 30, and 60 % (w/w) of EO, with the purpose of evaluating the possible changes caused by the cypress essential oil on the properties of the packaging. The films were characterized using FTIR, TGA, XRD and other analysis technologies. The mechanical, antibacterial and antioxidant properties of the films were analyzed. FTIR and XRD analysis indicated that cypress EO was homogenously distributed on the film. Meanwhile, TGA analysis demonstrated that the addition of EO had an impact on thermal properties. The impact of EO on mechanical and optical properties was explored. The results displayed that antibacterial activity against Escherichia coli and Staphylococcus aureus increased as cypress essential oil percentage increased in cellulose acetate films. Moreover, free radical scavenger activity by DPPH of cellulose acetate films improved by increasing the cypress essential oil concentration. These results indicate that the films of cellulose acetate containing cypress essential oil have potential for use as active packaging for foods.

Keywords: cellulose acetate, essential oil, active packaging, antibacterial, antioxidant

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Authors: Esabelle Lo Yan Yam, Pheak Chhoun, Sovannary Tuot, Emily Lancsar, Siyan Yi

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Persons living with HIV (PLHIV) need lifelong antiretroviral treatment (ART) to keep their viral load suppressed to an undetectable level, maintain a healthy immune system, and reduce the risk of transmitting HIV to others. However, many factors affect PLHIV's adherence to ART, including access to antiretrovirals (ARV), stigma, lack of social support, and the burden of seeking lifelong care. Community-based care has been shown to be instrumental in the experience of PLHIV in many countries, including Cambodia. In this study based in Cambodia, a community-based ART delivery (CAD) intervention involving community action workers (CAWs) who are PLHIVs was introduced. These workers collect pre-packaged ARVs from the ART clinics and dispense them to PLHIVs in the communities. The quasi-experimental study involved approximately 2000 stable PLHIV in the intervention arm and another 2000 PLHIV in the control arm (receiving usual care). A cost-effectiveness analysis is currently conducted to complement the clinical effectiveness of the CAD intervention on the care continuum and treatment outcomes for stable PLHIV, as well as the operational effectiveness in increasing the efficiency of the ART clinics and the health system. The analysis will consider health system and societal perspectives based on primary outcomes, including retention in care, viral load suppression, and adherence to ART. Additionally, a consultation with the National Centre for HIV/AIDS, Dermatology, and STD under the Cambodia Ministry of Health will be done to discuss the conduct of a budget impact analysis that can quantify the financial impact on the government's budget when adopting the CAD intervention at the provincial and national levels. The budget impact analysis will take into consideration various scaling-up scenarios for the interventions in the country. The research will assess the cost-effectiveness of the CAD intervention to support national stakeholders in Cambodia to make an informed decision on the adoption and scaling up of the intervention in Cambodia. The results are currently being analyzed and will be available at the time of the conference.

Keywords: Cambodia, community intervention, economic evaluation, global health, HIV/AIDs, implementation research

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Authors: Alesandro Romero, Inaki Maulida Hakim

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This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck; the average efficiency was 97,4 % with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. Furthermore, from the calculation of logistics cost of the ideal condition, it brings savings of Rp53.011.800,00 in a month. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost Rp3.966.559,40 per day, and increase the average of the truck efficiency 8,78% per day.

Keywords: efficiency, logistic cost, milkrun, saving methode, simulation

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Authors: Lim Sanny, Felix Christian

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The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

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Authors: Busaba Phurksaphanrat

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This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions.

Keywords: multi-mode resource constrained project scheduling problem, fuzzy set, goal programming, pre-emptive fuzzy goal programming

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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: Yendo Hu, Xu-Yu Wu, Dylan Oh

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GPS-Denied drones open the possibility of indoor applications, including dynamic arial surveillance, inspection, safety enforcement, and discovery. Indoor swarming further enhances these applications in accuracy, robustness, operational time, and coverage. For micro-drones, power management becomes a critical issue, given the battery payload restriction. This paper proposes an application enabling battery replacement solution that extends the micro-drone active phase without human intervention. First, a framework to quantify the effectiveness of a power management solution for a drone fleet is proposed. The operation-to-non-operation ratio, ONR, gives one a quantitative benchmark to measure the effectiveness of a power management solution. Second, a survey was carried out to evaluate the ONR performance for the various solutions. Third, through analysis, this paper proposes a solution tailored to the indoor micro-drone, suitable for swarming applications. The proposed automated battery replacement solution, along with a modified micro-drone architecture, was implemented along with the associated micro-drone. Fourth, the system was tested and compared with the various solutions within the industry. Results show that the proposed solution achieves an ONR value of 31, which is a 1-fold improvement of the best alternative option. The cost analysis shows a manufacturing cost of $25, which makes this approach viable for cost-sensitive markets (e.g., consumer). Further challenges remain in the area of drone design for automated battery replacement, landing pad/drone production, high-precision landing control, and ONR improvements.

Keywords: micro-drone, battery swap, battery replacement, battery recharge, landing pad, power management

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Authors: Iman Shabanzadeh

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Earthquake is known as one of the most frequent natural hazards in Iran. Therefore, policy making to improve the strengthening of structures is one of the requirements of the approach to prevent and reduce the risk of the destructive effects of earthquakes. In order to choose the optimal policy in the face of earthquakes, this article tries to examine the cost of financial damages caused by earthquakes in the building sector and compare it with the costs of retrofitting. In this study, the results of adopting the scenario of "action after the earthquake" and the policy scenario of "strengthening structures before the earthquake" have been collected, calculated and finally analyzed by putting them together. Methodologically, data received from governorates and building retrofitting engineering companies have been used. The scope of the study is earthquakes occurred in the geographical area of Iran, and among them, eight earthquakes have been specifically studied: Miane, Ahar and Haris, Qator, Momor, Khorasan, Damghan and Shahroud, Gohran, Hormozgan and Ezgole. The main basis of the calculations is the data obtained from retrofitting companies regarding the cost per square meter of building retrofitting and the data of the governorate regarding the power of earthquake destruction, the realized costs for the reconstruction and construction of residential units. The estimated costs have been converted to the value of 2021 using the time value of money method to enable comparison and aggregation. The cost-benefit comparison of the two policies of action after the earthquake and retrofitting before the earthquake in the eight earthquakes investigated shows that the country has suffered five thousand billion Tomans of losses due to the lack of retrofitting of buildings against earthquakes. Based on the data of the Budget Law's of Iran, this figure was approximately twice the budget of the Ministry of Roads and Urban Development and five times the budget of the Islamic Revolution Housing Foundation in 2021. The results show that the policy of retrofitting structures before an earthquake is significantly more optimal than the competing scenario. The comparison of the two policy scenarios examined in this study shows that the policy of retrofitting buildings before an earthquake, on the one hand, prevents huge losses, and on the other hand, by increasing the number of earthquake-resistant houses, it reduces the amount of earthquake destruction. In addition to other positive effects of retrofitting, such as the reduction of mortality due to earthquake resistance of buildings and the reduction of other economic and social effects caused by earthquakes. These are things that can prove the cost-effectiveness of the policy scenario of "strengthening structures before earthquakes" in Iran.

Keywords: disaster economy, earthquake economy, cost-benefit analysis, resilience

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Authors: Ayudhia P. Gusti, Semin

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It is known that total operating cost of a vessel is dominated by the cost of fuel consumption. How to reduce the fuel cost of ship so that the operational costs of fuel can be minimized is the question that arises. As the basis of these kinds of problem, sailing speed determination is an important factor to be considered by a shipping company. Optimal speed determination will give a significant influence on the route and berth schedule of ships, which also affect vessel operating costs. The purpose of this paper is to clarify some important issues about ship speed optimization. Sailing speed, displacement, sailing time, and specific fuel consumption were obtained from shipping log data to be further analyzed for modeling the speed optimization. The presented speed optimization model is expected to affect the fuel consumption and to reduce the cost of fuel consumption.

Keywords: maritime transportation, reducing fuel, shipping log data, speed optimization

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Authors: Rehan Ullah

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This paper explores the hypothesis that technology can be used to improve product quality, speed up delivery and reduced cost. For companies improving the quality of their products, reducing the cost and improving the speed of delivery makes them favorable to the client who feels like all their needs have been met. The research occurs between the months of January 2018 to April 2018 which is about four months. The research experiment design uses the pretest-posttest experimental design set up between two companies both using the traditional method of manufacturing with no technology. In one company technology is introduced while in the other company the process remains the same traditional method of production. Both companies analyze the results at the end of a four-month period before a conclusion is drawn from both the pretest and the final test. The experiment results show that technology improves quality of the product, improves the speed of delivery while at the same time reduce cost benefiting both the producer and the client. Technology should, therefore, be implemented in companies to give them an edge over the competition. With technology in companies, the United States can reclaim production from overseas companies that have taken over by providing cheap labor. Better satisfied customers mean more production which in turn means more jobs for the people in the United States.

Keywords: technology, quality of product, speed up delivery, cost

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Authors: Mazlynda Md Yusuf, Wafa' Mahadzir, Mohamad Yazis Ali Basah

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Nowadays, financing long-term care for elderly people is a crucial issue, either towards the family members or the care institution. Corresponding with the growing number of ageing population in Malaysia, there’s a need of concern on the uncertaintiness of future family care and the need for long-term care services. Moreover, with the increasing cost of living, children feels the urge of needing to work and receive a fixed monthly income that results to sending their elderly parents to care institutions. Currently, in Malaysia, the rates for private nursing homes can amount up to RM 4,000 per month excluding medical treatments and other recurring expenses. These costs are expected to be paid using their Employees Provident Fund (EPF) savings that they accumulate during their working years, especially for those working under private sectors. Hence, this study identifies the adequacy of EPF in funding the cost of long-term care service during old age. This study used a hypothetical simulation model to simulate different scenarios. The findings of this study could be used for individuals to prepare on the importance of planning for retirement, especially with the increasing cost of long-term care services.

Keywords: long-term care cost, employees provident fund Malaysia, ageing population, Malaysian elderly

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Authors: Barbara Eschen Danielsen, Morten Niels Baxter, Per Sieverts Nielsen

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Europe is currently in an energy and climate crisis, which requires more sustainable solutions than what has been used to before. Europe uses 40% of its energy in buildings so there has come a significant focus on trying to find and commit to new initiatives to reduce energy consumption in buildings. The European Union has introduced a building standard in 2021 to be upheld by 2030. This new building standard requires a significant reduction of CO2 emissions from both privately and publicly owned buildings. The overall aim is to achieve a zero-emission building stock by 2050. EU is revising the Energy Performance of Buildings Directive (EPBD) as part of the “Fit for 55” package. It was adopted on March 14, 2023. The new directive’s main goal is to renovate the least energy-efficient homes in Europe. There will be a cost for the home owner with a renovation project, but there will also be an improvement in energy efficiency and, therefore, a cost reduction. After the implementation of the EU directive, many homeowners will have to focus their attention on how to make the most effective energy renovations of their homes. The new EU directive will affect almost one million Danish homes (30%), as they do not meet the newly implemented requirements for energy efficiency. The problem for this one mio homeowners is that it is not easy to decide which renovation project they should consider. The houses are build differently and there are many possible solutions. The main focus of this paper is to identify the most impactful solutions and evaluate their impact and evaluating them with a criteria based sustainability indicator framework. The result of the analysis give each homeowner an insight in the various renovation options, including both advantages and disadvantages with the aim of avoiding unnecessary costs and errors while minimizing their CO2 footprint. Given that the new EU directive impacts a significant number of home owners and their homes both in Denmark and the rest of the European Union it is crucial to clarify which renovations have the most environmental impact and most cost effective. We have evaluated the 10 most impactful solutions and evaluated their impact in an indicator framework which includes 9 indicators and covers economic, environmental as well as social factors. We have packaged the result of the analysis in three packages, the most cost effective (short term), the most cost effective (long-term) and the most sustainable. The results of the study secure transparency and thereby provides homeowners with a tool to help their decision-making. The analysis is based on mostly qualitative indicators, but it will be possible to evaluate most of the indicators quantitively in a future study.

Keywords: energy efficiency, building renovation, renovation solutions, building energy performance criteria

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Authors: Moyosooore A. Babalola, Ayodeji S. Ogunleye

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The main focus of the study was to determine the profitability of investment in the Oil Palm value chain of Osun State, Nigeria in 2015. The specific objectives were to describe the socio-economic characteristics of Oil Palm investors (producers, processors and marketers), to determine the profitability of the investment to investors in the Oil Palm value chain, and to determine the factors affecting the profitability of the investment of the oil palm investors in Osun state. A sample of 100 respondents was selected in this cross-sectional survey. Multiple stage sampling procedure was used for data collection of producers and processors while purposive sampling was used for marketers. Data collected was analyzed using the following analytical tools: descriptive statistics, budgetary analysis and regression analysis. The results of the gross margin showed that the producers and processors were more profitable than the marketers in the oil palm value chain with their benefit-cost ratios as 1.93, 1.82 and 1.11 respectively. The multiple regression analysis showed that education and years of experience were significant among marketers and producers while age and years of experience had significant influence on the gross margin of processors. Based on these findings, improvement on the level of education of oil palm investors is recommended in order to address the relatively low access to post-primary education among the oil palm investors in Osun State. In addition to this, it is important that training be made available to oil palm investors. This will improve the quality of their years of experience, ensuring that it has a positive influence on their gross margin. Low access to credit among processors and producer could be corrected by making extension services available to them. Marketers would also greatly benefit from subsidized prices on oil palm products to increase their gross margin, as the huge percentage of their total cost comes from acquiring palm oil.

Keywords: oil palm, profitability analysis, regression analysis, value chain

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Hung-Chi Chang

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For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

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Authors: Meng Wu

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Unmanned aerial vehicle (UAV) landing technology is a common task that is required to be fulfilled by fly robots. In this paper, the crazyflie2.0 is located by ultra-wideband (UWB) localization system that contains 4 UWB anchors. Another UWB anchor is introduced and installed on a stationary platform. One cost function is designed to find the minimum distance between crazyflie2.0 and the anchor installed on the stationary platform. The coordinates of the anchor are unknown in advance, and the goal of the cost function is to define the location of the anchor, which can be considered as an optimal landing point. When the cost function reaches the minimum value, the corresponding coordinates of the UWB anchor fixed on the stationary platform can be calculated and defined as the landing point. The simulation shows the effectiveness of the method in this paper.

Keywords: UAV landing, UWB localization system, UWB anchor, cost function, stationary platform

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Authors: Kaddour Ziani, Méghit Boumédiène Khaled

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Forty Hamra single non-castrated male lambs were included in the present study. Traits analyzed were weighted at birth (BW) every 20 days. At 99.15±1.07 days old, the animals were weaned, then divided in two identical groups: control and experimental lambs (n=20) according to their live weight; 24.63±0.47 and 24.35±0.64 Kg respectively. During 59 days, two varieties of feed were given to assess the growth performance. The feeding system consisted of supplying a commercial concentrate (corn based) for control lambs. However, a similar amount of experimental concentrate (barley based) was given to the experimental ones. Both diets were supplemented with 200g straw of barley/animal/ration. 10 lambs fed with experimental concentrate were slaughtered at 37.85±0.78 Kg live weight. The growth performance, the diet cost, and some of the carcass and meat characteristics were evaluated. Chemical analysis of both given diets showed an elevated crude fibre content in the commercial concentrate. However, the experimental concentrate contained higher amounts of calcium. Both groups grew at a similar rate (p > 0.05) and showed the same final body weight. Concerning the cost of the given diet, a significant difference has been found (p ≤ 0.001), between both diets. This could affect the price of the produced meat. The dressing percentage was 46.65%, with 2.49% of carcass shrink. Furthermore, an interesting percentage of total muscle was obtained (63.73%) with a good carcass conformation scoring 9.56. Compared to other breed sheep, “Hamra” carcass could be considered as the most valuable economically.

Keywords: Carcass characteristics, feeding cost, growth performance, Hamra lamb, meat

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Authors: Aysun Pınarbaşı, Béla Vizvári

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The countries are the units that procure the vaccines during the COVID-19 pandemic. The delivered quantities are huge. The countries must bear the inventory holding cost according to the variation of stock quantities. This cost depends on the speed of the vaccination in the country. This speed is time-dependent. The vaccinated portion of the population can be approximated by the cumulative distribution function of the Cauchy distribution. A model is provided for determining the minimal-cost inventory policy, and its optimality conditions are provided. The model is solved for 20 countries for different numbers of procurements. The results reveal the individual behavior of each country. We provide an inventory policy for the pandemic period for the countries. This paper presents a deterministic model for vaccines with a demand rate variable over time for the countries. It is aimed to provide an analytical model to deal with the minimization of holding cost and develop inventory policies regarding this aim to be used for a variety of perishable products such as vaccines. The saturation process is introduced, and an approximation of the vaccination curve of the countries has been discussed. According to this aspect, a deterministic model for inventory policy has been developed.

Keywords: covid-19, vaccination, inventory policy, bounded total demand, inventory holding cost, cauchy distribution, sigmoid function

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Authors: Henry Kelly, Helena Shaw

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This paper will seek how innovative methods from Health Economics and, to a lesser extent, wellbeing analysis can be applied in the Cost-Benefit Analysis (CBA) of transport infrastructure and policy interventions. The context for this will focus on the framework articulated by the UK Treasury (finance department) and the English Department for Transport. Both have well-established methods for undertaking CBA, but there is increased policy interest, particularly at a regional level of exploring broader strategic goals beyond those traditionally associated with transport user benefits, productivity gains, and labour market access. Links to different CBA approaches internationally, such as New Zealand, France, and Wales will be referenced. By exploring a complementary method of accessing the impacts of policies through the quantification of health impacts is a fruitful line to explore. In a previous piece of work, 14 impact pathways were identified, mapping the relationship between transport and health. These are wide-ranging, from improved employment prospects, the stress of unreliable journey times, and air quality to isolation and loneliness. Importantly, we will consider these different measures of health from an intersectional point of view to ensure that the basis that remains in the health industry does not get translated across to this work. The objective is to explore how a CBA based on these pathways may, through quantifying forecast impacts in terms of Quality-Adjusted Life Years may, produce different findings than a standard approach. Of particular interest is how a health-based approach may have different distributional impacts on socio-economic groups and may favour distinct types of interventions. Consideration will be given to the degree this approach may double-count impacts or if it is possible to identify additional benefits to the established CBA approach. The investigation will explore a range of schemes, from a high-speed rail link, highway improvements, rural mobility hubs, and coach services to cycle lanes. The conclusions should aid the progression of methods concerning the assessment of publicly funded infrastructure projects.

Keywords: cost-benefit analysis, health, QALYs transport

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Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Frederick Huie, Lauren Fusfeld, William Burchenal, Scott Howell, Alyssa McVey, Thomas F. Goss

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Alzheimer’s Disease (AD) is a degenerative brain disease characterized by memory loss and cognitive decline that presents a substantial economic burden for patients and health insurers in the US. This study evaluates the payer budget impact of the DISCERN™ test in the diagnosis and management of patients with symptoms of dementia evaluated for AD. DISCERN™ comprises three assays that assess critical factors related to AD that regulate memory, formation of synaptic connections among neurons, and levels of amyloid plaques and neurofibrillary tangles in the brain and can provide a quicker, more accurate diagnosis than tests in the current diagnostic pathway (CDP). An Excel-based model with a three-year horizon was developed to assess the budget impact of DISCERN™ compared with CDP in a Medicare Advantage plan with 1M beneficiaries. Model parameters were identified through a literature review and were verified through consultation with clinicians experienced in diagnosis and management of AD. The model assesses direct medical costs/savings for patients based on the following categories: •Diagnosis: costs of diagnosis using DISCERN™ and CDP. •False Negative (FN) diagnosis: incremental cost of care avoidable with a correct AD diagnosis and appropriately directed medication. •True Positive (TP) diagnosis: AD medication costs; cost from a later TP diagnosis with the CDP versus DISCERN™ in the year of diagnosis, and savings from the delay in AD progression due to appropriate AD medication in patients who are correctly diagnosed after a FN diagnosis.•False Positive (FP) diagnosis: cost of AD medication for patients who do not have AD. A one-way sensitivity analysis was conducted to assess the effect of varying key clinical and cost parameters ±10%. An additional scenario analysis was developed to evaluate the impact of individual inputs. In the base scenario, DISCERN™ is estimated to decrease costs by $4.75M over three years, equating to approximately $63.11 saved per test per year for a cohort followed over three years. While the diagnosis cost is higher with DISCERN™ than with CDP modalities, this cost is offset by the higher overall costs associated with CDP due to the longer time needed to receive a TP diagnosis and the larger number of patients who receive a FN diagnosis and progress more rapidly than if they had received appropriate AD medication. The sensitivity analysis shows that the three parameters with the greatest impact on savings are: reduced sensitivity of DISCERN™, improved sensitivity of the CDP, and a reduction in the percentage of disease progression that is avoided with appropriate AD medication. A scenario analysis in which DISCERN™ reduces the utilization for patients of computed tomography from 21% in the base case to 16%, magnetic resonance imaging from 37% to 27% and cerebrospinal fluid biomarker testing, positive emission tomography, electroencephalograms, and polysomnography testing from 4%, 5%, 10%, and 8%, respectively, in the base case to 0%, results in an overall three-year net savings of $14.5M. DISCERN™ improves the rate of accurate, definitive diagnosis of AD earlier in the disease and may generate savings for Medicare Advantage plans.

Keywords: Alzheimer’s disease, budget, dementia, diagnosis.

Procedia PDF Downloads 137