ABSTRACT
Over it's more than 100-year history, the Kennecott operation has often been at the forefront of innovation;driven by the demands of the lower grade ore-body and the higher costs of operating in the US where wages are generally higher and regulation more restrictive. One way of reducing operating costs in c/lb is to increase the lbs produced at minimal cost. Despite the relatively coarse grind at Kennecott - about 30% >150μm, approximately 20% of the Cu lost to tail is liberated chalcopyrite in the <20μm fraction, and about 30%-40% in the <37μm fraction. In 2020 Kennecott undertook a detailed plant scale test of the magnetic aggregation technology to increase copper recovery by reducing fine copper losses. A paired statistical plant test of magnetic conditioning on one rougher line showed a 1.12% increase in Cu recovery to 97% statistical confidence. The next challenge, unforeseen at the start of the project, was the fabrication and transportation to site of the equipment for the three remaining rougher rows, during the severe supply-chain constraints of the Covid pandemic in 2021. This resulted in delays and unforeseen costs as world-wide transportation became chaotic, particularly transportation via west coast USA. Nevertheless, the project was completed and commissioned, with only minor delays and cost increases, due to a flexible approach to overcoming the hurdles encountered. Copyright © 2023 by SME.
ABSTRACT
In the fourth industrial revolution age, digital transformation is crucial to the sustainable development of small- and medium-sized businesses (SMEs). This study suggests a hierarchical model based on the Technology–Organization–Environment (TOE) model with three main dimensions and nine sub-dimensions for SMEs that implemented digital transformation in the emerging economy. The fuzzy analytic hierarchical process methodology (Fuzzy AHP) was used to explore and rank determinants of the digital transformation adoption for SMEs. Data were collected by the questionnaires from 72 respondents, who were the leaders of SMEs in Vietnam. The results revealed that the environmental factor was ranked the most important factor in the pairwise comparisons of the hierarchical structure, and the sub-dimension of the customer experience was at the highest ranking of the relative pairwise comparisons of the digital transformation adoption for SMEs, followed by technological compatibility, government support, organizational support, and human resources. This research makes contributions to the topic of digital transformation from both theoretical and practical implications. The result stresses the critical significance of environmental factors in the successful adoption of digital technologies in SMEs, which adds to the perspective in the context of a growing nation.
ABSTRACT
The oil industry is experiencing a critical situation as the Covid-19 pandemic outbreak. There are several challenges that facing the industry specially the investors as the global decline in demand for Energy merchandises, the future exploration and development drilling in new assets that require massive investments is still uncertain based on the current market price and conditions. The much-reported fall in oil prices and the acute pressure on IOCs to survive in this environment led the companies to stop many ongoing projects and shrink work profile that affected the oil production all over the world. The situation in Egypt is quite challenging for the investors as Egypt is a big consumer, along with the political stability that kept the economy running directed the big IOCs to embrace innovative approaches to lower the operating costs that has the direct impact on the cost per barrel to support maintaining the country growth and secure current energy demand. Dragon Oil company as newly introduced to Egypt's market after acquiring the market shares of one of the major joint ventures in Egypt (Gulf of Suez Petroleum Company- GUPCO) in October 2019 has faced the same dilemma of exerted pressure on the expenditures (Capex and Opex) in order to cope with the global market circumstances. However that didn't deter the company to embrace an innovative way of thinking and handling for the situation. Dragon Oil/GUPCO multi-disciplinary teams achieved successfully a production incremental increase of 10,000 barrels per day through the past six month by adapting a strategic management innovative plans, alternative lower cost technical solutions, production optimization and introducing new proved technologies to the 50 years old assets. This paper will highlight the complete workflow adopted by GUPCO/Dragon Oil teams covering the whole process aspects;appraise, select, define and execution phases to achieve the company goals. The work done was including restoring production from Shut-in offshore platforms or wells via fixing the surface network using neoteric solutions, widely applying rigless interventions using several new techniques in the current producers to maximize their production and optimizing the production cycle across the four production chokes In Summary, Dragon Oil/GUPCO teams managed to increase GUPCO's production despite of the restricted budget and the negative impact of COVID-19 pandemic on the oil price and reach an outstanding performance in operation excellence and safety aspects that results in arresting the natural decline and increase the growth production by about 15% from the 2019 Average production. Copyright © 2023, Society of Petroleum Engineers.
ABSTRACT
Foamed cement was successfully used in the riserless section of an ultradeepwater well located in 11,900ft water depth. Foamed cement was selected to minimize operating costs and provide flexibility to adjust slurry density on a short notice. The seawater column exerted 5,319.1-psi hydrostatic pressure on the annulus. Consequently, nitrogen (N2) density could no longer be neglected. This paper presents simulations performed in preparation for the job, operational considerations, and post-job evaluation. The lead slurry needed a density of 1.25 SG and develops a compressive strength of at least 300 psi within 48 hr. Considering the cost and challenges associated with outsourcing resources under current Covid-19 pandemic restrictions, the foamed cement system was preferred over chemical-or particle-extended cement or blend systems. The N2 ratio for the foamed cement slurry system was 700 scf/bbl. With a base slurry pumping rate of 5 bbl/min, the required N2 pumping rate was 3,500 scf/min, which was greater than the capability of a single N2 pump (3,000-scf/min rate). Because the rig deck space could not accommodate three N2 pumps, one pump would serve as backup;thus, the final plan consisted of using two N2 pumps simultaneously. Two parallel foamed slurry treating lines were rigged up to reduce the fluid velocity in a single line. All laboratory testing was conducted locally. Additives used in the foamed slurry were environmentally friendly. A proprietary process-control system was used during the cementing operation and automatically synchronized the N2 pumps and foam pump rates with the base slurry rate. The cementing crew consisted of 11 individuals, including 2 client representatives. The entire pumping operation was completed in 10 hr. A total base slurry volume of 1016.2 bbl was continuously mixed and pumped at the density of 13.35 lbm/ gal (1.60 SG). The resulting foamed slurry volume was 1387.0 bbl with an average foam quality of 27.8% and foamed slurry density of 10.5 lbm/gal (1.26 SG). A total of 119 metric tonne of class G cement and 30,711 L of N2 were consumed during the pumping operation. The lead slurry was followed by 603.9 bbl of 15.86 lbm/gal (1.90 SG) class G cement tail slurry and 349.7 bbl of seawater for displacement. The final surface pressure was 594.6 psi. The lead slurry reached the seabed and the float shoe check was positive. No casing subsidence was observed. neglected when high-hydrostatic pressure is involved. © 2023, Offshore Technology Conference.
ABSTRACT
In-person banking is still an important part of financial services around the world. Hybrid bank branches with service robots can improve efficiency and reduce operating costs. An efficient autonomous Know-Your-Customer (KYC) is required for hybrid banking. In this paper, an automated deep learning-based framework for interbank KYC in robot-based cyber-physical banking is proposed. A deep biometric architecture was used to model the customer’s KYC and anonymise the collected visual data to ensure the customer’s privacy. The symmetric-asymmetric encryption-decryption module in addition to the blockchain network was used for secure and decentralized transmission and validation of the biometric information. A high-capacity fragile watermarking algorithm based on the integer-to-integer discrete wavelet transform in combination with the Z6 and A6 lattice vector quantization for the secure transmission and storage of in-person banking documents is also proposed. The proposed framework was simulated and validated using a Pepper humanoid robot for the automated biometric-based collection of handwritten bank checks from customers adhering to COVID-19 pandemic safety guidelines. The biometric information of bank customers such as fingerprint and name is embedded as a watermark in the related bank documents using the proposed framework. The results show that the proposed security protection framework can embed more biometric data in bank documents in comparison with similar algorithms. Furthermore, the quality of the secured bank documents is 20% higher in comparison with other proposed algorithms. Also, the hierarchal visual information communication and storage module that anonymizes the identity of people in videos collected by robots can satisfy the privacy requirements of the banks. Overall, the proposed framework can provide a rapid, efficient, and cost-effective inter-bank solution for future in-person banking while adhering to the security requirements and banking regulations. Author
ABSTRACT
Transportation and logistics costs are becoming a large portion of the operating expenses for many businesses. Recently, supply chain disruptions caused by the COVID-19 pandemic and inflation crisis have brought challenges, especially, to many small- and medium-sized companies. Not only are companies struggling with logistics costs, but logistics bottlenecks are often preventing businesses from growing, expanding, and obtaining additional market shares. According to both academics and practitioners, there must be more literature and studies to address these logistics management challenges from cost accounting perspectives. This study focuses on multiple-source and multiple-sink scenarios, in which products are delivered from various production units to various stores. Optimized solutions to these cases may suggest optimal logistics strategies in terms of the minimized costs, as well as provide insights for later profitability analysis through common cost allocations and segment income statement reports. This paper can contribute to the practical examples in logistics management for businesses and is an addition to the current literature on cost accounting issues.
ABSTRACT
Over the last year, the evolution in Robotic Process Automation (RPA) has been staggering. The automation it brings to applications has yielded efficiency, reduced operating costs, and decreased the time of research, development, and production. Industries have already integrated RPA into their workflow and are profoundly transforming into an intelligent automated industry with minimum human intervention, calling this the fourth industrial revolution. In this race of transformation, the healthcare industry is quite ahead of many other industries. It stood the test of time when COVID-19 was spreading rapidly and was also resilient against all odds. The system did experience an unprecedented crisis that depicted its weakness, fragility, and unpreparedness. The healthcare system was forced to adapt to a new paradigm. And though there was the loss of life and economy, we learned to evolve as a community to tackle this crisis. This chapter sheds light on the role of RPA and covers how these technologies can assist healthcare workers in their day-to-today activities, reviewing what the fourth industrial revolution would look like in the healthcare sector. The intelligent, automated system would provide a seamless experience of gathering information by various means, processing, and assisting healthcare workers to deliver quality treatment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Background: E-commerce has emerged as a good response to the pandemic of COVID-19. However, the costs of providing a service, which includes a driver and a vehicle, in a regular vehicle that can transport goods that need positive cold (0° to 5°C) are very high.Objectives: This paper aims to investigate how a big Portuguese retailer company can reduce its dependence on refrigerated vehicles, simplifying operations and reducing the costs of transporting positive and negative cold food.Methods/Approach: This research was carried out in a food retailer Portuguese company, more precisely in a Dark Store dedicated to the online channel. The study was developed based on the AS-IS/TO-BE process analysis methodology, starting with the analysis of the current situation, giving rise to the so-called AS-IS model.Results: It was possible to reduce costs associated with transporting positive cold goods. As a result, there are 30% fewer costs associated with order transportation. With an additional 10% in space optimization with the gain of space within the galley of each vehicle.Conclusions: The costs of transporting positive and negative cold foods were decreased, and substituting vehicles with room temperature transport reduced the need for refrigerated vehicles.
ABSTRACT
Oil and Gas industry is seeking new ways to improve efficiencies, reducing operating costs and increasing revenues in the current volatile market conditions. Data Science and all the new emerging technologies enable the discovery of new opportunities and digitalization is a vital element for making business more effective and efficient. While COVID19 has disrupted the world, ADNOC Onshore has recognized the importance of reskilling and empowering the future workforce through strategic enterprise data science and analytics program to achieve 2030 smart growth strategy. This paper talks about successful approach and enablers for development of in-house capability for transformation that lead to generating significant business value The digital transition can pose both challenges and opportunities in this transformation. ADNOC ONSHORE has developed an integrated framework to encourage and accelerate data science capabilities. This framework promotes a vision with collaborative, sustainable mechanisms to develop talent. It is not just the formal learning and additional professional qualification that make it possible to build this in house capability. There are five major areas are enabled this framework such as data science & analytics skills competency model, sustainable on-line collaborative learning program, organizational culture change, democratizing AI through open platform & a digital business model for performing real business problems/use case PoCs. Each area has a detailed program and execution strategy with a collaborative effort from technical and non-technical stakeholders. ADNOC ONSHORE has successfully implemented this framework and able to certify 20 employees as part of this program. The Data Science Competency Model identified and defined the skills required to be successful within the enterprise with a clear learning path and mentorship. The leadership played a pivotal role to encourage data driven decision making and predictive capabilities in addition to executive awareness to lead the change with clear performance indicators. By democratizing AI platform across upstream user community, six real business cases have been successfully developed with clear business value in subsurface and production workflows according to the defined digital business model. The successful business cases have improved efficiency by 75% in performing cement & corrosion log interpretation & well portfolio optimization. Data driven analytics have been evaluated in subsurface workflows such as infill location optimization, gas-lift candidate identification and they have complemented the existing techniques. The framework has been successfully extended to other group companies in ADNOC. The rapid growth of AI in business in the last five years presents an opportunity for oil and gas professionals for enhancing the skills and transformation. This paper talks about an integrated framework, learning path, democratizing AI, engagement of leadership, digital business model for business case evaluation by applying agile way of working and sustainable value creation. Copyright © 2022, Society of Petroleum Engineers.
ABSTRACT
After the political and socio-economic changes that occurred three decades ago, the interest in Bulgaria by foreign investors has grown. The traditionally good political, cultural and trade relations between Bulgaria and Germany, dating back to the end of the 19th century, were resumed. Trade exchange between the two countries, albeit with certain fluctuations, is constantly growing and in 2021 it is almost 10 billion euros. German investments in Bulgaria are also growing. About 30% of the 100 largest investors in Bulgaria are German or with German participation. German investments are evenly allocated to industries and regions of the country. The paper emphasizes the advantages that Bulgaria has and can offer to German investors, as well as the challenges that must be solved both at the country level and at the business level.
ABSTRACT
Robert Guery, Life MemberASHRAE, Ebmatingen, Switzerland * From July's "Confessions of a Control Freak," by Andy Pearson, Ph.D., C.Eng., Fellow ASHRAE, regarding cooling systems with multiple capacity stages that "hunt," in addition to increasing the stage delay time, one should also consider the cooling demand side. MemberASHRAE, Brisbane, Australia Airborne Disease Transmission Risk We read "Airborne Disease Transmission Risk and Energy Impact of HVAC Mitigation Strategies" by Michael J. Risbeck, Ph.D., et al., from May with great interest, and we agree that ventilation is a costly source of achieving adequate equivalent outdoor air (EOA) supply. [...]the cost of operating ventilation systems for reducing infection risk is much lower than the cost of taking care of a large number of infected patients.1 Overloading the health-care system is a painful lesson learned in many places.
ABSTRACT
This manuscript proposes an integrated system for treating hospital solid waste (H.S.W.) consisting of an incineration and frictional sterilization system capable of operating during normal and emergency situations. We analyzed the benefits of integrating different hospital solid waste (H.S.W.) treatment systems with the existing stand-alone incineration system, with a particular emphasis on the thermal friction sterilization integration system. The objective was to define the economic advantages and benefits in terms of resources recovery of using the thermal frictional sterilization–incineration integrated system during the hospital’s normal and emergency/pandemic operating conditions. We modeled three modeling scenarios based on normal and emergency operating conditions. The results show that the H.S.W. was composed of 74% general H.S.W. Existing incineration systems would be the most expensive process because the sanitary transportation cost represented approximately 96% of the H.S.W. costs. The hospital would realize 40–61% savings relative to the existing method if the integrated incineration–frictional systems were implemented to treat 50–70% of H.S.W.;the savings were better than in other scenarios. Proposed scenario 3 had a much better resources recovery factor than scenarios 1 and 2. This modeling study showed that a thermal frictional sterilization–incineration system could work well even under emergency conditions if the H.S.W. in-house sorting/transportation/storage process is modified to cater to other H.S.W. treatment/sterilization systems.
ABSTRACT
Computing tools applied in power systems are increasingly used to solve complex optimization problems. Power system operations research has become essential for graduate and final-year undergraduate students who want to improve their knowledge in this area. This study proposes a solution for a group of boilers and turbines to minimize operating costs using GUSEK software. The execution of the model allows us to obtain the optimal solution with the operational constraints involved and the possibility of improving with metaheuristic algorithms.
ABSTRACT
In today’s systems and networks, disruption is inevitable. Designing a reliable system to overcome probable facility disruptions plays a crucial role in planning and management. This article proposes a reliable capacitated facility joint inventory-location problem where location-independent disruption may occur in facilities. The system tries to satisfy customer’s demands and considers penalty costs for unmet customer demand. The article aims to minimize total costs such as establishing inventory, uncovered demand’s penalty, and transportation costs. While many articles in this area only use exact methods to solve the problem, this article uses a metaheuristic algorithm, the red deer algorithm, and the exact methods. Various numerical examples have shown the outstanding performance of the red deer algorithm compared to exact methods. Sensitivity analyses show the impacts of various parameters on the objective function and the optimal facility layouts. Lastly, managerial insights will be proposed based on sensitivity analysis.
ABSTRACT
Purpose>This paper aims to investigate how the relation between stock returns of US firms and West Texas Intermediate (WTI) oil prices is affected by leverage from 1990 to 2020.Design/methodology/approach>This paper examines how the relationship between stock returns of US firms and WTI oil prices is affected by leverage from 1990 to 2020 using a fixed-effect model estimation framework.Findings>Results from the fixed-effect regression models suggest that leverage effects on stock returns are pervasive both in aggregate and cross-industry levels, while the mining industry is more sensitive. In addition to the positive oil price effects attenuated by leverage at the aggregate level, the authors observe stronger marginal effects of leverage only for the mining sector. Being more exposed to commodity prices, the positive effects of oil prices on stock returns in the mining sector are offset by large debt ratios. Asymmetries, effects of debt maturity structure and implications are also discussed.Research limitations/implications>This study is grounded on the contemporary cash flow claim of leverage NOT on the long-run effect of leverage considering cash flow constraints. The oil price increase is assumed to represent an advancement of the overall economy. This study does not capture the oil prices response to some other economic forces and vice-versa.Practical implications>Mining companies should therefore reduce the stock of debt with respect to their assets to make possible the “pass-through” from oil prices to the stock market.Originality/value>Previously undocumented and the authors show that leverage reduces the total effect of oil prices on stock returns, consistent with the hypothesis. Asymmetric and debt maturity structures effects are also discussed.
ABSTRACT
Coronavirus disease 2019 (COVID-19) has affected many behaviours and aspects of society. Electricity consumption has been considerably affected by the pandemic, with significant effects on the electricity load demand profile. In this article, the impact of COVID-19 on electricity demand in the state of Florida is investigated through a novel machine learning technique. The LSTM technique shows good accuracy in forecasting the load profiles for all days studied (weekdays and weekends) and also before and during the pandemic. The UC problem is solved considering the load profiles, and the impact of COVID-19 on power plant scheduling is evaluated. The simulation results show an increase in residential demand for electricity at weekends, while both residential and commercial demand are reduced during weekdays. Therefore, the operating cost of a weekday in 2020 was lower than that in 2019, while the operating cost of a weekend was higher in 2020 than in 2019.
ABSTRACT
The COVID-19 pandemic and the implementation of Large-Scale Social Restrictions that occurred in Indonesia resulted in an economic slowdown. Then the problem that is present in the banking sector is the difficulty of debtors in fulfilling their financing obligations. The purpose of this study is to analyze the differences in the performance of the National Sharia BPR before the covid 19 pandemic and during the covid 19 pandemic for the period June 2018 -September 2021. In this study, performance was measured by the asset return ratio (ROA), capital adequacy ratio (CAR), ratio of nonperforming financing (NPF), operating expenses to operating income (BOPO), and the ratio of financing to deposit (FDR). The research is included in quantitative research with a comparative type. The data used is secondary data in the form of the financial statements of the National Sharia BPR obtained from www.ojk.co.id. Data analysis in this study used paired sample t-test analysis with the help of the SPSS version 25 program. The results showed that only CAR and NPF had significant differences before and during the COVID19 pandemic. While ROA, BOPO, and FDR had no significant differences. before and during the covid 19 pandemic. [ FROM AUTHOR] Copyright of Eduvest: Journal Of Universal Studies is the property of Green Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
In recent years, one of the key postulates in the European Union’s policy has become the development of renewable energy sources. In order to achieve the desired synergy effect, the idea of combining two selected sources of energy appeared. This article presents a technical and economic analysis of a hybrid connection of a ground source heat pump with a photovoltaic installation. Taking into account the heat demand of the building, a ground heat pump with a catalog nominal heating power of 25 kW was selected. This article presents the problem of the economic profitability of using a hybrid combination of a heat pump and photovoltaic panels in domestic hot water and central heating systems. The justification for the use of such heat sources in these installations is due to global trends and the gradual departure from conventional energy sources such as oil or gas boilers. This paper presents the economic and ecological results of using the pump heat connected together with photovoltaic panels. In the economic analysis, with the assumed installation costs related to the use of the considered heat pump and PV, two parameters commonly used in the investment analysis (static and dynamic) were used, namely, the simple payback period and the net present value of the investment. For the adopted assumptions, the usable area of the facility and the number of years of use were indicated, at which the investment in question is competitive with other alternative investment interest methods and will start to bring tangible benefits. The performed analysis also has measurable environmental benefits in the form of a reduction in carbon dioxide emissions at the level of 2893 kg/year into the atmosphere. The presented solution will help future investors understand the investment profitability mechanism for their households.
ABSTRACT
Purpose>Airport capacity constraints lead to operational congestion and delays, which have become major threats to the aviation industry. They impose large costs on airlines and their passengers. Uncertainty in demand or unexpected events can cause a mismatch between capacity and demand, resulting in either capacity oversupply, with a decrease in efficiency, or airport congestion over an extended period. Moreover, airport capacity is rather difficult to define due to its multifaceted and dynamic nature, and it depends both on the available infrastructure and on operating procedures. Additionally, traditional capacity management methods do not consider relevant behavioral economic challenges to conventional analysis, particularly failure of the expected utility hypotheses and dependence of valuations on reference points. This study aims to develop a preliminary framework to include economic concepts when evaluating expansions of airport capacity.Design/methodology/approach>This paper reviews major opportunities in airport demand and capacity management from an economic perspective while appraising the challenges involved in airport capacity expansion processes that have not been fully completely in past studies. Although welfare economics provides the conceptual foundations for demand/capacity analyses, the authors integrate the findings regarding capacity definition, uncertainty management and behavioral economics into standard economics to guide the measurement of the airport capacity expansion problem.Findings>The authors obtain several insights regarding airport capacity and demand management. First, airport capacity is a complex metric when evaluating airport expansion, and it depends both on the available infrastructure and on operating procedures. Furthermore, airport throughput is highly conditioned by factors that shape capacity and delay and shows significant variability when these factors are modified. Second, a marginal change in capacity at congested airports may have a great impact on demand distribution, airline competition, aircraft types, fares, operating revenues, route map and other characteristics of a given airport. Behavior after capacity expansion is highly reliant on the slot allocation models. Additionally, overall social welfare is usually affected after changes in infrastructure in terms of increased connectivity, economic benefits and negative externalities, including noise and local pollution. Third, on-time performance is clearly nonlinear, and thus sensitive to variations in demand and capacity. Finally, airport capacity and demand management involve a trade-off between mitigating congestion and maximizing capacity utilization, so decision-making tools are required to support and enhance policy and managerial choices. Three main challenges arise when developing new methods for evaluating airport expansions: the definition of capacity, the management of uncertainty in demand and the need to consider economic concepts.Originality/value>This paper explores and produces an in-depth understanding of the problem of airport capacity and demand balance. The authors propose a preliminary framework that considers the challenges that have been previously identified and that, particularly, provides an economic perspective for airport capacity expansion processes. This framework is completed with a theoretical model to help policymakers and airport operators when faced with a capacity development decision.
ABSTRACT
This paper study suggests the specifications for high-efficiency, short-haul utility aircraft. This class of aircraft is used extensively in the multinational express package delivery service. Concurrent with the COVID 19 pandemic upending passenger travel, there has been a broad increase in the demand for air cargo. We forecast a need for more efficient short and medium range aircraft that offer route time savings and lower operating costs. Using current market planes designed with similar mission requirements, payloads, and engines – a general plane was created and optimized around the operating model of the present-day FedEx package delivery feeder fleet. The modification and optimization process was completed using a Model-Based-Systems-Engineering (MBSE) approach utilizing Phoenix Integration’s ModelCenter, Excel, MATLAB, and SOLIDWORKS. The final design achieved 40% improvement in fuel efficiency over the current fleet, and improvements in speed, payload, and range while in compliance with FAA regulations as a class E cargo aircraft certified under 14 CFR Part 25. © 2022, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.