Improvement Of Production Capacity Research Articles

Optimized integration of solar energy and liquefied natural gas regasification for sustainable urban development: Dynamic modeling, data-driven optimization, and case study

As sustainable urban communities continue to seek alternative energy sources, this study explores the inclusion of renewable resources in the energy mix. With a focus on liquefied natural gas (LNG) regasification, parabolic trough solar collectors, dual-loop power cycles, proton exchange membrane electrolysis, and hydrogen liquefaction cycle, this research conducts a comprehensive examination of an integrated system. The primary objective is to provide a diverse range of valuable outputs, including electricity, liquefied hydrogen, desalinated water, and cooling for coastal areas. Through careful analysis of regional geographic features, San Francisco emerges as a suitable location due to its favorable solar radiation intensity and existing LNG transportation infrastructure. The findings reveal that the integrated system has the potential to deliver approximately 5750.4 MWh of cooling, 14988.85 MWh of electricity, and 1,491,084 m3 of fresh water, thereby significantly contributing to the city's utility demands. In terms of data-driven optimization, artificial neural networks serve as intermediary mechanisms to establish correlations between the developed code and the optimization algorithm. The results demonstrate that the optimized system exhibits notable improvements in production capacity. Moreover, significant reductions in the levelized cost of electricity (0.19 Cent/kWh), fresh water (1.22 Cent/m3), and hydrogen (0.08 $/kg) are observed. Although the optimized case entails a 16.11% higher cost rate compared to the base system, it is projected to generate a 25.59% higher profit over its operational lifespan. Additionally, the payback period of the optimized system is shortened by 6.31%, making it an attractive long-term investment for sustainable urban development.

Impact of COVID-19 on Smallholder Aquaculture Farmers and Their Response Strategies: Empirical Evidence from Bangladesh

Bangladesh’s aquaculture sector has contributed progressively to the nation’s economy over the years, but the COVID-19 pandemic has impeded fish farmers’ access to markets, reduced their production and sales capacity, resulted in lower income, and increased food security vulnerability. This study assesses how COVID-19 affects smallholder fish farmers and their response strategies by employing data collected from 250 fish farmers and traders from intensive fish-growing areas of Bangladesh. The results reveal that most farmers experienced difficulty obtaining inputs, and the price of those inputs skyrocketed during the COVID-19 period, resulting in several months of decreased production and operations. As a result of COVID-19, farm gate prices for silver carp, ruhu, common carp, grass carp, and tilapia fish dropped by 25%, 23%, 23%, 22%, 23%, and 40%, respectively. On the other hand, fish feed prices were found to increase significantly. Reduced income from fish farming and other sources has triggered a significant drop in capital for farming operations and production capacity improvement, leading to food insecurity. The most common coping strategies include reduced buying from the market (vegetables, fruits, meat, milk, etc.), relying on less expensive or less preferred food, purchasing food on credit, and selling assets. Notably, due to COVID-19, a new mode of marketing has evolved as an adaptation strategy in the fish marketing system, such as the use of the mobile phone (18%) and Facebook/internet to sell fish directly to the customer (16%). The sector requires short-term financial assistance to assist fish actors with production and marketing challenges.

Environmental Suitability Evaluation for Human Settlements of Rural Residential Areas in Hengshui, Hebei Province

To improve the development quality of rural residential areas in plain areas requires scientific evaluation. Based on the rural residential area in Hengshui City, Hebei Province, the study selected four indicators of location, production, ecology, and management, to build an evaluation model for the suitability of human settlements and evaluated rural residential areas in Hengshui City. The findings indicated the following: (1) The most suitable areas are mainly concentrated in the geographical center of Hengshui City. The generally suitable areas are mainly distributed in the east of the city. The basic suitable areas are scattered in the west and northeast of the city. The unsuitable areas are mainly concentrated in the north of the city. Most of the area of Hengshui City is suitable for the residence and development of rural residential areas, and 72.86% of rural residential areas are located in suitable areas, which is consistent with the geographical environment characteristics of plain areas. (2) The rural residential areas in unsuitable areas are mainly due to the low income, serious population loss and low urbanization rate, which are in line with the characteristics of rural residential areas. (3) The suitability of human settlements in rural residential areas in plain areas is mainly affected by the per capita agricultural land area, hydrology index, distance to river, distance to country, distance to a slow road, and distance to the fast road are low-level driving factors, of which distance to a fast road has the weakest influence. (4) There is a significant positive correlation between the environmental suitability and the distribution density of rural residential areas. The improvement of the suitability of human settlements can effectively promote the aggregation and distribution of rural residential areas. High-high clustering areas are mainly concentrated in the middle and northeast of Hengshui City, while low-low clustering areas are scattered in the north and southwest of Hengshui City. (5) The location index (LI) and management index (AI) play a limiting role in the suitability of human settlements in the northeast of Hengshui City, and the government should strengthen management intervention and infrastructure construction in the northeast of Hengshui City. The production index (PI) plays a limiting role in the suitability of human settlements in the west of Hengshui City and should consider the improvement of production capacity in the west of Hengshui City. The research results play a vital role in improving the carrying capacity of regional resources and the environment in the plain area, improving rural production, and living conditions, and promoting the development of rural planning in the whole region.

Investigation of heat treatment strategies for improvement of production capacity of coin stamping dies

This paper presents a study on the production capacity of stamping dies for minting coins under different heat treatment processes, particularly austenite temperatures, using a vacuum furnace. In the study, the specimen material was made from Bohler K340 steel. The first heat treatment strategy included heating the specimens to a stable austenite temperature at 1080°C, then holding for 120 minutes and cooling rapidly with gas quenching media with a pressure of 5 bar. Tempered treatment was performed at 500°C. Another strategy was similar to the first one, except the heating temperature at 1060°C and double tempering at 575°C. After the heat treatment process, microstructure observation and hardness testing were carried out. Finally, the production of the die capacity testing on the coining machine was conducted. The results of the specimen surface photographs of the two heat treatment strategies show a significant difference in the microstructure, similarly with the hardness value obtained from single tempering is 61.98 HRC and from double tempering is 57.94 HRC. The production capacity test result indicates that the average capacity of first and second dies are 101,250 coins and 171,150 coins, respectively. It means that the second dies exceed the minimum standard production capacity of dies as determined by the Quality Control department, which is 150,000 coins.

Experimental Study on the Effects of Pore Pressure and Slippage on the Permeability of a Fracture Network during Depressurization of Shale Gas Reservoir Production.

Hydraulic fracturing technology is an important technical means to increase shale gas production. The seepage channels formed in the hydraulic fractures during hydraulic fracturing can help increase reservoir permeability. Therefore, it is of significance to study the seepage law of the fracture network after reservoir hydraulic fracturing. In this study, hydraulic fracturing is used to fracture full-diameter shale cores, and three typical forms of hydraulic fracture networks are obtained. The characteristics of the fracture networks are analyzed by X-ray CT scanning. The effects of pore pressure and slippage on the permeability of the fracture networks are simulated by conducting experiments. The experimental results show that in the direction of gas seepage, hydraulic fractures completely penetrate the sample, and the greater the diameter and volume of the fracture, the better the hydraulic fracture conductivity. When the confining pressure remains unchanged at 50 MPa, the apparent permeability values of the hydraulic fractures with the worst and best fracture morphologies increase by 44.4 times and 2.8 times, respectively, with the decrease in the pore pressure from 30 to 2 MPa. The apparent permeability of the shale samples has a power function relationship with the pore pressure. The test results also show that the absolute permeability is positively correlated with the number of effective seepage channels in the hydraulic fractures and the number of hydraulic fractures, whereas the Klinkenberg coefficient is negatively correlated. Our research results can provide a basis for shale gas production model research and for on-site production capacity improvement. The qualitative understanding and scientific explanation of the effects of pore pressure and slippage on fracture network permeability in the process of depressurization of reservoir production have been realized.

Post-disaster recovery in industrial sectors: A Markov process analysis of multiple lifeline disruptions

Lifeline disruptions can represent a serious economic threat at various scales. However, firm-level empirical evidence regarding the consequences and reliability of lifeline services, and how lifeline service disruptions impact on economic losses after disasters, is still lacking. This study applies a temporal, non-homogeneous, Markov process approach that explicitly considers multiple lifeline service disruptions. This approach is used to quantitatively estimate the impacts of multiple lifeline disruptions on business production capacity losses. The model is illustrated based on the 2011 Great East Japan Earthquake case study with detailed information obtained from individual business recovery data. The result indicates that the restoration of lifeline systems during disruptions should consider each business service given that it significantly affects business production capacity recovery. For example, the case study results indicate that if electrical power, water and gas are disrupted, restoration of electrical power supply yields the highest influence on production capacity improvement, amounting to 15% per day on average, compared with 10% per day for gas restorations, and 8% per day for water restoration. The proposed model can provide information to business managers and policymakers on the optimum recovery strategy and on how to mitigate economic losses in disruption event cases.

Transcriptional and physiological analyses of reduced density in apple provide insight into the regulation involved in photosynthesis.

Different densities have a great influence on the physiological process and growth of orchard plants. Exploring the molecular basis and revealing key candidate genes for different densities management of orchard has great significance for production capacity improvement. In this study, transcriptome sequencing of apple trees was carried out at three different sampling heights to determine gene expression patterns under high density(HD) and low density(LD) and the physiological indices were measured to determine the effect of density change on plants. As a result, physiological indexes showed that the content of Chlorophyll, ACC, RUBP and PEP in the LD was apparently higher than that in control group(high density, HD). While the content of PPO and AO in the LD was noticeably lower than that in the HD. There were 3808 differentially expressed genes (DEGs) were detected between HD and LD, of which 1935, 2390 and 1108 DEGs were found in the three comparisons(middle-upper, lower-outer and lower-inner), respectively. 274 common differentially expressed genes (co-DEGs) were contained in all three comparisons. Functional enrichment and KEGG pathway analysis found these genes were involved in Carbon fixation in photosynthetic organisms, Circadian rhythm, Photosynthesis − antenna proteins, Photosynthesis, chlorophyll metabolism, Porphyrin, sugar metabolism and so on. Among these genes, LHCB family participated in photosynthesis as parts of photosystem II. In addition, SPA1, rbcL, SNRK2, MYC2, BSK, SAUR and PP2C are involved in Circadian rhythm, the expression of genes related to glycometabolism and hormone signaling pathway is also changed. The results revealed that the decrease of plant density changed the photosynthetic efficiency of leaves and the expression of photosynthesis-related genes, which provide a theoretical basis for the actual production regulation of apples.

Incentives for production capacity improvement in construction supplier development

<p style='text-indent:20px;'>The purpose of this paper is to investigate the supplier development (SD) in construction industry. As the supplier's production capacity cannot meet the construction requirements, the owner wants to take incentives to encourage the supplier to improve its production capacity. A principal-agent model and a Stackelberg game model are proposed to study the impact of owner's incentives including cost sharing and purchase price incentive on the production capacity improvement in SD. Furthermore, we give a sensitivity analysis of the influence of supplier's internal and external parameters, i.e., purchase quantity, cost structure, market price and market demand, etc., on the production capacity improvement. The findings of this study can help the owner to make a better decision on the incentive mechanisms for SD, resulting in both better SD practices and a win-win situation.

Production capacity analysis and energy saving of complex chemical processes using LSTM based on attention mechanism

The production data of complex chemical processes are multi-dimensional, uncertain and noisy, and it is difficult to directly control raw materials consumption and measure the product quality. Therefore, this paper proposes a production capacity analysis and energy saving model using long short-term memory (LSTM) based on attention mechanism (AM) (AM-LSTM). The weights of the results sequence in the hidden layer, which have great influence on final results in the output layer, are calculated by the AM. Then the production prediction model is built using the LSTM to extract features of the input data and multiple time series results of the hidden layer. Compared with the common LSTM, the multi-layer perceptron (MLP) and the extreme learning machine (ELM), the applicability and the effectiveness of the proposed model is validated based on University of California Irvine repository (UCI) datasets. Finally, the proposed model is applied to analyze the production capacity and the energy saving potential of the purified terephthalic acid (PTA) solvent system and the ethylene production system of the complex chemical process. The experimental results verify the practicability and accuracy of the proposed model. Furthermore, the results offer the operation guidance for production capacity improvement through saving energy and reducing the energy consumption.

Production prediction and energy-saving model based on Extreme Learning Machine integrated ISM-AHP: Application in complex chemical processes

One of the key issues of the sustainable development in all countries is industrial productivity improvement, especially the production capacity improvement and energy-saving of complex chemical processes. Therefore, this paper proposes a production prediction and energy-saving model based on Extreme Learning Machine (ELM) integrated Interpretative Structural Modeling (ISM) and Analytic Hierarchy Process (AHP). The factors that affect the productivity are divided into different levers by the ISM. And then the attributes of each layer are fused by the AHP based on the entropy weight, which greatly reduces the complexity of the input attributes. Moreover, the production prediction and energy-saving model is established based on the ELM. Compared with the traditional ELM, the validity and the practicability of the proposed method are verified by University of California Irvine (UCI) datasets. Finally, the proposed method is applied in the production capacity prediction and energy-saving of ethylene production systems and Purified Terephthalic Acid (PTA) production systems. The experimental results show the proposed method could reduce the number of hidden layer nodes and improve the training time of the ELM. Furthermore, the prediction accuracy of the ethylene production and the PTA production reaches about 99% to improve the energy efficiency of complex chemical processes.

Development Model of Engineering Manufacturing and its Application

In recent years, with the continuous improvement of production capacity, manufacturing industry restructuring and achieved great results, significantly increased the proportion of high-tech industries, some traditional industries has continued to decline. Manufacturing is the material basis of our national economy and the main industry, which largely determines the level of development of comprehensive national strength. This has brought great difficulties to the economic modeling and forecasting system. This paper presents an improved modeling and forecasting methods, recombinant methods by introducing chain data and add data growth economic indicators in an artificial neural network training, the time series data input window to solve practical engineering problems forecasts.

Improvement of production capacity and export raspberry from Republic of Serbia

In order to promote the Republic of Serbia as an investment destination and boost exports is necessary to improve the image of Republic of Serbia. The target is to produce sufficient amounts of high quality raspberries. It is necessary to promote Republic of Serbia as an attractive destination for foreign investment and promote exports of raspberries. The way to achieve the above objectives is determined strategy of international marketing. Republic of Serbia should find its way of realization of the set goals. A good example of prosperity and international promotion of the industry raspberry we can see the competitors Poland and Chile, who have been well positioned in the global market. International marketing should be supported by intensive promotion in all media and the Internet, participation in international fairs.

Improvement of Stand Jig Sealer and Its Increased Production Capacity

This paper has the objective to prove that improvement of Stand Jig Sealer can lead to the cycle time target as part of Improvement efforts and its Productivity. Prior researches through prior journals both classics journal such as Quesnay (1766) and Solow (1957) and updated journal such as Reikard (2011) researches, are mentioned and elaborated. Precisely, the research is narrowed down and specified into automotive industry and eventually the software related of SPSS and Structural Equation Modeling ( SEM ). The analysis and its method are conducted through the calculation working time. The mentioned calculation are reinforced with the hypothesis test using SPSS Version 19 and involve parameters of production efficiency, productivity calculation, and the calculation of financial investments. The results obtained are augmented achievement of cycle time target ≤ 80 seconds posterior to improvement stand jig sealer. The result from calculation of SPSS-19 version comprise the following aspects :the one-sided hypothesis test is rejection of Ho:μ≥80 seconds, the correlation rs=0.84, regression y = 0.159+0.642x, validity R table = 0.4438, reliability value of Cronbach's alpha = 0.885>0.70, independence (Chi Square) Asymp. Sig=0.028 0, PI 2.04>1, IRR 45.56%>i=12.68%, PP=1.86). The Mentioned calculation results support the hypothesis and ultimately align with the objective of this paper to prove that improvement of Stand Jig Sealer and its relation toward the cycle time target. Precisely, the improvement of production capacity of PT. Astra Daihatsu Motor.

Is there a relationship between electricity consumption and economic growth in Zimbabwe?

This paper investigated the causality relationship between electricity consumption and economic growth in Zimbabwe using a bi-variate time series framework for the period 1980 to 2011. The causality relationship between the two variables has been a subject of extensive debate for decades among economists and academics. There are four dominant perspectives with regard to the causality relationship between electricity consumption and economic growth. The first perspective maintains electricity consumption spur economic growth whilst the second perspective argues that it is economic growth that drives electricity consumption. The third perspective suggests that both electricity consumption and economic growth promotes each other whilst the fourth perspective argues that there is no causality relationship at all between the two variables both in the short and long run. Using the bi-variate causality test framework, this study failed to establish any direct causality relationship between energy consumption and economic growth. The results imply the existence of an indirect bi-directional causality relationship between the two variables. The study therefore recommends Zimbabwe authorities to address indirect factors that have a bearing on economic growth over and above scaling up investment efforts into electricity production capacity improvement infrastructure

Heritability and genetic correlation of production and reproduction traits of Simmental cows

Improvement of production capacity of cattle in terms of increasing the production of milk, milk fat and number of calves, greatly depends on phenotype and genotype variability, heritability and correlation between desirable traits, as well as on the production level of the cattle population. Heritability, as a value expressing and measuring average additive gene effect, is one of the major characteristic of quantitative traits from the point of view of creating genetically high-value cattle populations. Knowledge of the heritability is necessary in the estimation of the beeeding value of cattle and has significant impact on the selection of breeding method. Genetic correlations are very important in indirect selection where changes in one trait are induced through selection of other traits between which a genetic correlation exists. Genetic correlations can be determined in all cases where heritability coefficient can be calculated. This research included 3.461 first calving Simmental cows under control, with lactation concluded within one year. All first-calvers were reared on individual farms in the territory of Republic of Serbia. In this study, heritability and genetic correlations between the the following milk and fertility traits were investigated: duration of lactation (days)- DL, milk yield in standard lactation (kg)- MY, milk fat content in standard lactation (%)- MFC, milk fat yield in standard lactation (kg)- MFY, yield of 4% FCM in standard lactation (kg)- 4%FCM, age at first calving (days)- AC and duration of service period (days)- DSP.

연속 3 차원 튜브 벤딩장치 개발에 관한 연구

A continuous 3D tube bending machine has been developed for industrial boiler panel production. The machine consists of a main bender, a sub bender, a side bender, tube feeding rollers and control system that includes data management system. Tube position is controlled by a numerical control system. The bending former can be easily replaced according to the shape of bending form. Reduction of working time and improvement of production capacity from the practice have been achieved by bending a long tube in the machine developed.

Mass Transport to Cylindrical Electrodes Rotating in Suspensions of Inert Microspheres

Mass transfer enhancement produced by the addition of inert microspheres was investigated on a rotating cylinder electrode operating in the turbulent regime. The effects of rotation speed, rotor radius, particle size, solids volume fraction, and particle density on the rate of mass transfer were determined by limiting current measurements for ferricyanide ion reduction. In comparison to transport rates observed with clear electrolytes, up to two and a half fold higher limiting currents were obtained in concentrated suspensions containing 5–80 μm diameter microspheres with densities ranging from 0.7 to 2.1 g/cm3. Transport enhancement is attributed to the microconvective eddies produced by particle rotation in the shear field adjacent to the spinning electrode, and to the increased shear rate caused by the formation of a particle‐free wall layer. Experimental data could be correlated in the formwhere Sh, Re, and Sc are the Sherwood, Reynolds, and Schmidt numbers, respectively, and α and β are empirical functions of solids volume fraction determined from transport rate measurements. The addition of appreciable volume fractions of inert particles to the electrolyte results in significant improvements in production capacity when the latter is limited by transport rates. The use of suspended particles to achieve a given increase in limiting current density is shown to require much less power than simply increasing electrode rotation speed to enhance mass transport.