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Process Integration and Optimization for Sustainability
Number of Followers: 0  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 2509-4238 - ISSN (Online) 2509-4246
Published by Springer-Verlag Homepage  [2469 journals]
  • A Linear Programming Methodology to Optimize Decision-Making for
           Ready-Mixed Cement Products: a Case Study on Egypt’s New Administrative
           Capital

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      Abstract: Abstract Egypt has started constructing its New Administrative Capital since 2015. The new capital was designed to meet smart city standards, which presents a challenge for businesses to make the optimum business decisions given the set budget for such a project. As a result, reaching the optimum solution for allocating the needed materials to each building became important. Many researchers have considered the theory of constraints in their studies to determine the optimum product mix. Frequently, research considers the target of profit maximization to reach the optimum solution with one scenario. In this paper, we aim to solve the problem of product mix in cement production, which organizations face. The problem was formulated based on a case study in Egypt with two linear programming approaches. For this problem, many scenarios were presented under the consideration of two aspects, which are resource utilization and productivity. Data visualization was used in this paper to simplify the procedure of decision-making. Also, a dashboard web application was made for the decision makers to make it easier to create, analyze, and see different business scenarios.
      PubDate: 2022-09-19
       
  • A Sustainable Retrofit of an Industrial Heat Exchanger Network — A Case
           Study of a Gas Separation Plant in Thailand (HEN Retrofit on GSP)

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      Abstract: In this challenging work, sustainable heat integration using an industrial heat exchanger network (HEN) retrofit method by Angsutorn et al. (Chem Eng Sci 229:116005, 2021) was considered as a method for recovering waste energy to save heating and cooling utility costs of the gas separation plant Unit 5 (GSP5), a unit of the largest natural-gas separation company in Thailand. A high-energy-efficiency plant with a small heat recovery approach temperature (HRAT) of 7.5 °C, GSP5 is focused on the energy-efficiency improvement policy of the company. Our retrofit method consists of two nonlinear programming (NLP) optimization steps with the most practical retrofit concepts; installation of new heat exchanger units along with full utilization of all existing process heat exchangers without heat-transfer area modification and exchanger relocation. The retrofit design was generated at HRAT of 5.2 °C with a net present value (NPV) of $ 27,282,123 for a project life time of 20 years. Graphical
      PubDate: 2022-09-17
       
  • Ranking Green Universities from MCDM Perspective: MABAC with Gini
           Coefficient-based Weighting Method

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      Abstract: Abstract The concept of the green university has emerged due to concerns about sustainable development and the use of natural resources. Various organizations rank green or non-green universities under several criteria. The results obtained in these rankings make it possible to compare the performances of similar universities. In this study, we aim to look at the ranking of green universities from the perspective of multi-criteria decision-making. For this purpose, according to the UI GreenMetric 2021 report, 35 green universities in Europe are ranked using the multi-attributive border approximation area comparison method with Gini coefficient-based weighting method. As a result of the weight calculation with the Gini coefficient-based weighting method, it is found out that the setting and infrastructure criterion is the most important criterion, whereas the least important criterion is waste. The performance scores of green universities are obtained by using the calculated criteria weights and the Multi-Attributive Border Approximation area Comparison method. Consequently, the correlation between the original ranking and the ranking obtained by the proposed methodology used in this study has been found as 0.8151. These results show that multi-criteria decision-making methods can be used to rank green universities. As a result of the findings obtained in this study, underperformed universities in the ranking may find the opportunity to compare themselves with similar green universities. Furthermore, non-green universities may be motivated to implement green policies.
      PubDate: 2022-09-13
       
  • Analyzing the Application of the Sustainable Development Goals for Egypt
           Using a Neutrosophic Goal Programming Approach

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      Abstract: Abstract Sustainable development necessitates the implementation of appropriate policies that integrate multiple competing objectives on economic, environmental, energy, and social criteria. Multi-criteria decision analysis with goal programming is a popular and widely used technique for studying decision problems with multiple competing objectives. Real-world situations frequently involve imprecise and incomplete information, making neutrosophic goal programming models the most appealing option. We presented a novel neutrosophic goal programming model that incorporates optimal resource allocation to simultaneously satisfy prospective goals on economic development, energy consumption, workforce, and greenhouse gas emission reduction by 2030, as applied to Egypt’s key economic sectors in this paper. We also compared the outcomes of fuzzy goal programming and neutrosophic goal programming. We show that neutrosophic goal programming approach is more accurate than fuzzy goal programming approach because it deals with incomplete and indeterminate information and has three independent degrees: truth membership degree, indeterminacy–membership degree, and falsity–membership degree. The presented model examines opportunities for improvement and the effort required to implement sustainable development plans. The model also provides valuable insights to decision makers for strategic planning as well as investment allocations for sustainable development. Numerical illustration is also provided for validation and application of the proposed model.
      PubDate: 2022-09-03
       
  • Quasi-oppositional Forensic-Based Investigation for Optimal DG Selection
           for Power Loss Minimization

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      Abstract: Abstract With the emergence of smart-grid and micro-grid concept insurgence into the modern power distribution system, the present research has been forced to focus on the impact of distributed generation (DG) on the overall system performance at the planning stage. The optimal bus location and selection of the proper size of DGs in the radial distribution systems (RDS) is a major issue and needs better optimization techniques during decision making. The major intent of the study is to minimize the active power loss and that is accomplished by taking appropriate bus location, size of the DGs, and power factor as the system variables. This paper presents a quasi-oppositional forensic-based investigation (QOFBI) inspired meta-optimization approach for providing optimal results of DG allocation and sizing along with the power factor considering all the system operating constraints. To validate the superior performance of the proposed approach, IEEE 33-bus, IEEE 69-bus, and IEEE 85-bus test systems are considered for simulation. Various performance indices related to power, voltage, and stability are computed under various levels and types of DG penetration, and comparative results with recently proposed approaches are presented and analyzed. The results reveal the robustness, effectiveness, and better performance with the less computational complexity of the proposed approach.
      PubDate: 2022-09-02
       
  • Fuzzy Optimization of the Esterification Conditions of Biodiesel
           Production from Karanja Oil

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      Abstract: Abstract Current biodiesel production remains unsustainable and costly due to the use of refined edible oils as feedstock. The use of non-edible oils such as Karanja oil would contribute to making biodiesel production economically competitive based on its availability and low cost. This study determines the optimal esterification conditions of Karanja oil for biodiesel production using fuzzy optimization. It involves determining a compromise solution on the conversion of the free fatty acid (FFA) content in Karanja oil with its cumulative uncertainty error (YQ) and the total operating cost (CT). The variables considered in the esterification process include the methanol-to-oil molar ratio (4:1 to 8:1), catalyst loading (0.5 to 2.5 wt%), reaction time (60 to 120 min), and duty cycle (50 to 90%). The Pareto front generation was used to determine the upper and lower boundary limits of YQ and CT as the underlying basis in the fuzzy optimization process. Results indicated an overall satisfaction level of 64.68% for the conversion and cost. The optimal conditions of the variables were 5:1 molar ratio, 0.85 wt% catalyst loading, 79% duty cycle, and 89.35 min. These conditions yielded a YQ of 68% and a total operating cost of USD 0.12 per liter of Karanja oil esterified. A comparative assessment with a previous literature showed a conversion with an amenable compromise efficiency by 13.51% that resulted in a cheaper price (24.86% lower). This study contributes in generating more efficient process of biodiesel production through process integration.
      PubDate: 2022-09-01
       
  • Speeding-up Startup Process of a Clean Coal Supercritical Power Generation
           Station via Classical Model Predictive Control

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      Abstract: Abstract It is well known that coal-firing power plants are the slowest power plants in operation among other fossil fuel power stations, and have the highest emissions among all energy sources. This paper introduces a novel control strategy to speed up the startup process of a 600-MW cleaner supercritical coal-firing power station. The plant existing startup time is 6.9 h to reach the once-through mode of operation. Classical model predictive control (MPC) can be a computationally and a practically feasible choice to reduce that time. First, a subspace state-space identified linear model has been developed to cover the whole process from startup (0% loading) to maximum power (100% loading) and down to 55% loading with multi-input single-output (MISO) structure. Secondly, the MPC has been designed with the best parameter selection for prediction horizon, control horizon, constraints, and weighting coefficients. The MPC application has shown successful performance with an earlier/faster startup process than the existing plant situation, which has reached the once-through mode in 5.8 h (1.1 h earlier than the existing situation). Finally, the efficiency and safety limits of the supercritical pressure and temperature have been ensured by additional safety checkers with Hammerstein-Wiener Models fed by the MPC decisions, which predicts the pressure and temperature, in order to satisfy the multiple objectives of the strategy of high efficiency, lower startup time, and safe operation. The average savings in fuel and water flows are found to be 6.4626 ton/h and 28.8609 ton/h, respectively. This indicates further reduction in undesirable emissions.
      PubDate: 2022-09-01
       
  • Technical Challenges and Their Solutions for Integration of Sensible
           Thermal Energy Storage with Concentrated Solar Power Applications—a
           Review

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      Abstract: Abstract Concentrated solar power (CSP) uses solar insolation to increase the temperature of heat transfer fluid (HTF), which can be used in a power block to produce power either by using a steam turbine or gas turbine. In CSP, the levelized cost of electricity is higher than conventional sources due to the intermittent nature of solar energy. The levelized cost of electricity can be reduced by integrating CSP with thermal energy storage (TES) system. This paper comprehensively reviews sensible thermal energy storage technologies for concentrated solar power applications. It includes a brief discussion of various sensible heat TES systems, i.e., two-tank molten salt TES system, single-media TES system, and dual-media TES systems. Recent advances in the TES system show that dual-media thermocline is economically more viable as compared to others. However, it has a few technical challenges like a mechanical failure due to thermal ratcheting and varying outlet temperature. Additionally, the review presented here is useful in thermodynamic modeling of the TES system using various heat transfer models.
      PubDate: 2022-09-01
       
  • Quantification of Relationship Between Greenhouse Gas Emissions and
           Equipment Management in Mineral Industries

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      Abstract: Abstract Mining activities have significant environmental impacts. At the same time, the current living standards of humankind and growth in population require the consumption of mineral resources. The adoption of sustainable mining practices has become very important in this context. One of the most critical assets of a mining company is its equipment, which is used through all operations from drilling, blasting, loading, and hauling to processing. Most of these enormous equipment fleets, including mining trucks, are still diesel powered, leading to greenhouse gas (GHG) emissions. The development of sustainable practices for the maintenance and operation of mining equipment can help reduce emissions. This study investigates the linkage between several operational factors and GHG emissions. To this end, five different linear and nonlinear models are explored to estimate the fuel consumption of mining trucks based on payload, reliability, and road and weather conditions. It is then extended to estimate GHG emissions. The testing of these models suggests that the multivariate linear model is the most suitable one as it explains about 84% of the variability of the dependent variable (i.e., fuel consumption). The findings of the study suggest that road conditions and equipment reliability are the main factors that affect fuel consumption. For example, a change of 10% on the truck reliability results in a 6% reduction in GHG emissions, and improvement of roads from poor to well-maintained conditions contributes to a 23% reduction in GHG emissions of the mining trucks. This study thus provides useful insights that can inform sustainable mining operations.
      PubDate: 2022-09-01
       
  • Strategies for Quantifying Metal Recovery from Waste Electrical and
           Electronic Equipment (WEEE/E-waste) Using Mathematical Approach

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      Abstract: Abstract Electronic waste describes the rejected electrical or electronic products of electrical and electronic equipment which has been discarded by the user as waste with the lack of reuse or recycles. Waste electrical and electronic equipment (WEEE) are produced in large capacities and stored as electronics and further lacking in processing the waste which effects the environmental pollution. E-waste consists of several materials which are extractable and utilized as valuable source for manufacturing new products. The electronic products considered for the present study are washing machines, refrigerators, air conditioners, laptop, and computer. Approaching appropriate recycling and managing the e-waste reduce the pollution released into environment. In this present study, to estimate the quantity of e-waste from the source of generation and quantifying the transformable valuable metals by various mathematical methods are time series analysis, disposal-related analysis, material flow analysis, and input-output analysis methods. Material flow analysis (MFA) is used to quantify and systematically analyze the flow of e-waste obtained from households in Indian cities. From the data estimated with the above methods, input-output methods are the most effective method of quantification for sales-stock-lifespan data of e-waste. The e-waste forecasting was determined by MFA for the washing machines, refrigerators, air conditioners, laptop, and computer products for the year 2030. The results show the estimated quantity of more than 30% higher composition is observed from the e-waste. Economic potential is predicted as $5.279 billion in the year 2030 which helps to improve the economic development of the nation.
      PubDate: 2022-09-01
       
  • Research on Optimization of Supermarket Chain Distribution Routes Under
           O2O Model

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      Abstract: Abstract Dealing with the store distribution problems in transformation and upgrading of supermarket chains under Online-to-Offline (O2O) e-commerce model and considering the factors that affect the distribution cost and customer satisfaction, such as distribution distance, number of distribution vehicles, and delivery time, an O2O store distribution optimization model has been constructed with the purpose of minimizing total distribution cost. Moreover, a two-stage heuristic algorithm for ordering nearest distribution and mileage saving planning has been designed. The applicability and effectiveness of the model and method have been verified by enterprise case data collected. The results have shown that the total cost of distribution is obviously reduced compared with the accounting results of related models, which is suitable for supermarket chains or single-store retail enterprises with low probability of order splitting and distribution due to the shortage of certain products.
      PubDate: 2022-09-01
       
  • Performance Evaluation and Sustainability Assessment in Laser
           Micro-drilling of Carbon Nanotube-Reinforced Polymer Matrix Composite
           Using MOORA and Whale Optimization Algorithm

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      Abstract: Abstract The present work focuses on determining optimal parametric data set and sustainability assessment during laser micro-drilling of a new class of polymer matrix composite consisting of carbon nanotube. The material removal rate, taper, and heat-affected zone during machining are considered as performance measuring indices. Experiments are conducted using Taguchi’s L25 orthogonal array with cutting speed, pulse frequency, lamp current, air pressure, and pulse width as input control parameters. An overall assessment value and ranking of the desired output parameters are carried out using multi-objective optimization based on the ratio analysis (MOORA) method to acquire the best parametric setting. A second-degree regression equation is developed through MOORA-Taguchi, involving all input parameters to perform the multi-objective optimization using whale optimization algorithm which is a meta-heuristic optimization technique. To verify the adequacy of the developed model, analysis of variance tool using response surface methodology is utilized. The optimal results obtained by using the whale optimization algorithm are cutting speed of 150 (m/s), lamp current of 26 (amp), frequency of 12 (kHz), air pressure of 3 (kg/cm2), and pulse width of 30 (%) with an objective function value of 0.022715. The used technique is found to be a potential in finding multi-response optimization that can fulfill the wide necessities of process engineers working in the laser industries. It is also demonstrated that the proposed process is easing worker safety, promoting pleasant working environment and better product quality, and enhancing production rate leading to improved sustainability.
      PubDate: 2022-09-01
       
  • A Bacterial Foraging Approach for Safer Plant Layout Designs

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      Abstract: Abstract This article proposes a method to provide support to expert decision-making in designing the layout of chemical plants. Our approach applies the Bacterial Foraging Algorithm, a meta-heuristic optimization scheme, to determine an allocation of main process units in the two-dimensional space. The optimization aims at minimizing a total cost measure, which accounts for both the capital costs associated with usage of the area, piping, and secondary contention, and the expected costs generated by equipment losses incurred in case of explosions. To assess fire and explosion hazards, we use Dow’s Fire and Explosion Index, which provides a convenient means to estimate equipment allocation’s inherent danger and map it into prescriptions of minimal distances between units. The proposed solution approach provides an alternative to hard-optimization methods by allowing greater flexibility in accounting for both safety and economic aspects, while providing high-quality solutions in reduced computation time. A case study of an acrylic acid production plant, which several other papers in the literature have also used, serves the purpose of demonstrating the appropriateness and effectiveness of the method.
      PubDate: 2022-09-01
       
  • Development and Application of an Integrated Approach to Reduce Costs in
           Steel Production Planning

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      Abstract: Abstract Steel manufacturing is critical for industrial development and contributes greatly to the world’s energy consumption. A worldwide oversupply of steel has led to increased competition in the market, requiring developing countries to function on the same level as developed countries. Since energy use contributes between 20 and 40% of steel production costs, a reduction in energy consumption will result in decreased production costs, and increased competitiveness. This study therefore focuses on the development and application of an integrated approach to reduce energy costs in steel production planning. This is a new solution, as a review of existing research indicated that there is a lack of an integrated steel production planning model and application thereof on marginally profitable facilities. The key novelty lies in the integration aspect of the solution — both in terms of integrating different initiatives and different sections of such a facility. The proposed approach provides an opportunity to adapt outdated production planning methods without the use of capital, and simultaneously address resistance from personnel at these marginally profitable facilities in developing countries. The new cost model focuses on the identification, evaluation, comparison, prioritisation, implementation, and integration of steel production planning initiatives. The integration determines the effect that individual initiatives have on each other, and dynamically prioritises solutions by combining theoretically quantified benefits with practical constraints. Two initiatives were implemented on a South African facility, with an estimated cost benefit of US$0.83 million per annum (approximately R13.3 million per annum).
      PubDate: 2022-09-01
       
  • Comparative Environmental Impacts of Recycled Concrete Aggregate and
           Manufactured Sand Production

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      Abstract: Abstract Construction and demolition waste (CDW) management is essential for the sustainable development of a country. Recycled concrete aggregates (RCA) manufactured from CDW can replace a significant portion of natural aggregates in concrete as per various research studies conducted. Nowadays, various alternate waste materials are being utilised to minimise the environmental footprint of concrete. The manufactured sand (MS) is also one of the alternate materials being used in concrete production. There are significant studies available world-wide, which estimated associated environmental impacts of RCA; however, author could not find comparative study on environmental impact of RCA and manufactured sand (MS) production using optimization techniques in Indian perspective. Therefore, this study assessed the environmental impacts of producing 1-ton RCA from reclaimed concrete and MS from granite stone. Seven mid-point environmental impact (EI) categories of ReCePe method, i.e. global warming potential, human-toxicity potential, particulate matter formation potential, terrestrial acidification potential, freshwater eutrophication potential, photochemical ozone formation potential and resource use-fossil were calculated and interpreted. Analytic hierarchy process (AHP) optimization technique was used for calculating the weightage of EI categories. Hotspot and sensitivity analysis were performed to know the relevance and sensitivity of EI categories. As per the observation, CO2 emission and primary energy consumption in 1-ton RCA were 10% and 18.5% less than 1-ton MS. The suspended particulate matter and noise level in RCA were 25% higher and 9% lesser than MS. Transportation and crushing were the main contributors to EIs. This study may help in taking a calculative decision regarding utilization of RCA and MS as river sand replacement in concrete.
      PubDate: 2022-09-01
       
  • Design of Safety Zone and Optimal Risk Identification of Undesired Events
           During Loading and Unloading of LNG Terminal Using TSA-GEO: a Hybrid
           Strategy

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      Abstract: Abstract Liquefied natural gas (LNG) consumption is continuously rising in both developed and developing countries. Due to relatively cheap pricing and a large gas supply globally, most energy experts believe that major increases in LNG consumption are projected in the next decades. Many novel installations have been designed and are now implemented all over the globe in order to expand the usage of this resource. LNG is more prone to leakage when loading and unloading, thus putting the surrounding areas at greater risk of damage. Therefore, it is important to continue to improve current risk assessment strategies for dealing with safety. The objective of this work is to improve security by detecting failure patterns and minimizing problems. In this paper proposed a scheme to hybrid technique is combination of golden eagle optimizer (GEO) with tunicate swarm algorithm (TSA) and adaptive neuro fuzzy inference system (ANFIS) technique. This hybrid method is used because GEO-TSA detects leaks more accurately compared to other methods. The suggested hybrid technique-based risk assessment model may provide a fresh viewpoint on identifying leaks, hazards, and dangers, as well as assessing the development of LNG accidents from cause to effect. Furthermore, the suggested hybrid approach improves protection by detecting failure patterns and reducing issues. Finally, ANFIS is used as a reliable method for identifying risk, determining SIL rates and designing the safety zone. Predicting risk in overwork requires data on previous problems but not all data are available as all data vary from place to place. So the purpose of this job is to predict the risks from scratch without accurate data and not only that but also to anticipate the risks. This will reduce the risk of loss of life and property during periods of danger. In the proposed method is the implementation MATLAB/Simulink platform. The proposed method is comparable to methods such as particle swarm optimization (PSO) with fuzzy and whale optimization algorithm (WOA) with fuzzy.
      PubDate: 2022-09-01
       
  • Improving the Efficiency of Urban Waste Collection Using Optimization: a
           Case Study

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      Abstract: Abstract With increasing population, urbanization and industrialization, municipal solid waste management has become a key challenge for rapidly growing cities. A significant portion of solid waste management cost is associated with waste collection and transportation. This study aimed at routing and assignment of waste collection tractors to road segments so as to minimize the waste collection and transportation cost in the Kurunegala municipal council area of Sri Lanka. We constructed the waste collection network using the data obtained from the municipal council, online sources and published surveys and then formulated the corresponding waste collection problem as a capacitated arc routing problem (CARP) using binary integer programming (BIP) methods. The optimization model was developed using the PuLP modelling language in SolverStudio. We applied the model to a selected portion of the council area consisting of 5 wards currently served by 31 weekly waste collection trips which start and end at the dumping site. The optimal tractor assignment and routing policy shows potential to reduce the number of weekly trips by 19% and the weekly travelling distance of the tractors by 36%. The optimal routes tend to be cyclic routes without frequent turns and repeated travel on the same road segment. The optimal policy not only reduces the collection and transport cost, but also improves the tractor capacity utilization, assures equitable service for all residents and reduces the total time spent on waste collection, disruptions to traffic and carbon emissions.
      PubDate: 2022-09-01
       
  • Multi-objective Optimisation Using Fuzzy and Weighted Sum Approach for
           Natural Gas Dehydration with Consideration of Regional Climate

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      Abstract: Abstract The majority of the existing simulation-based research works on natural gas dehydration via absorption using tri-ethylene glycol (TEG) have focused on solving single or bi-objective problems where most of the objectives are in conflict with one another. It was not until 2017 that multi-objective problems with conflicting nature have started gaining significant interest in this field, especially those involving 3 or more objectives. In this work, a multi-objective optimisation (MOO) framework was developed involving two different techniques, i.e. the fuzzy optimisation and the weighted sum approach, for handling different conflicting objectives in a natural gas dehydration process. The developed framework is straightforward, which can be applied by anyone effortlessly and can be easily extended to data from other literatures. Two different case studies, which involved bi- and tri-objectives, are given here to illustrate the efficacy of the developed framework for improving the sustainability and performance of the natural gas dehydration process. Relative to previous works without optimisation, the optimum results obtained here provide a compromised solution between different objectives. Using fuzzy optimisation in case 1, for example, increases the net profit by 0.2% and reduces the VOC emissions by 33% (i.e. better sustainability). Although the water dew point increases by 15%, it is still within the specification range and hydrate formation will not occur.
      PubDate: 2022-09-01
       
  • Prioritization of Flexible Pavement Sections for Maintenance Using
           Multi-criteria FAHP Integrated with Multi-attribute Utility Theory

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      Abstract: Abstract Prioritizing maintenance activities is a common practice in pavement maintenance planning. Pavement maintenance and repair are costly activities, and the available budget for managing the pavement infrastructure is limited. In order to maintain pavement sections at acceptable service levels within the budget and resources available, maintenance must be prioritized. There were insufficient attributes and a lack of effective tools for ranking maintenance. In order to address this drawback, this study employs a fuzzy analytical hierarchy process integrated with multi-attribute utility theory (FAHP-MAUT) to create a prioritization system for pavement maintenance activities that incorporates most possible attributes. Pavement attributes refer to present pavement conditions and the expected parameters that pertain to its service life. The relative importance (weight factor) of attributes is derived from expert responses. Using Saaty’s scale, a questionnaire form was designed for this purpose. The data were collected through questionnaire form and from various pavement tests. The questionnaire’s detail information was collected and evaluated using FAHP, and a utility function was developed using MAUT. The utility score for each attribute was clumped together using relative weight to produce a total utility score. The total utility score was used to prioritize a network of flexible pavement. Overall pavement condition index (OPCI) has received the highest weight factor of 36.7% in the prioritization of highways. The proposed method is used to a case study of twenty-two National Highways (NH) in Bihar state (India). A sensitivity analysis is performed to investigate the impact of each attribute in the pavement prioritizing process. OPCI is observed as the most sensitive attribute and highest impact on the pavement. This study indicated the potential for prioritizing flexible pavement based on established criteria.
      PubDate: 2022-09-01
       
  • A Vendor-Managed Inventory Model for Imperfect Production Process Using
           Sustainability Investment and Energy Consumption Under Different Carbon
           Policies

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      Abstract: Abstract This study examines the impacts of sustainability investment and carbon policies in a two-level supply chain for a single product under classical and vendor-managed inventory schemes. Further, we classify the effects of carbon taxation, cap and trade, and limited carbon emission policies to reduce greenhouse gas emissions. Although the fundamental purpose of cap and trade is to minimize the carbon emission, a well-structured emission trading system can also provide considerable environmental, economic, and social advantages. The energy consumption is classified by the production and reworking process. The proposed model determines the optimal order quantity under various carbon emission rules. The sustainability investment is a financial activity that deals with projects or areas focused on environmental and natural resource protection, as well as the development of alternative energy sources. It also desires to reduce the use of fossil fuels and carbon emission. The results show that the total cost is less in limited carbon emission policies than carbon tax and cap and trade policies. Moreover, the total cost is less in vendor-managed inventory scheme compared to the classical method. The results also indicate the significance of the present models to reduce carbon emission using sustainability investments
      PubDate: 2022-09-01
       
 
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