Industrial Cost Research Articles

Development of a Novel Energy Saving and Environmentally Friendly Starch via a Graft Copolymerization Strategy for Efficient Warp Sizing and Easy Removal.

Warp sizing is a key process in textile production. However, before the yarn/fabric finishing, such as dyeing, the paste adhering to the warp must be eliminated to ensure optimal dyeing properties and the flexibility of the fabric. Therefore, the sizing will often consume a lot of energy and produce a lot of industrial wastewater, which will cause serious harm to the environment. In this study, we have developed an energy saving and environmentally friendly starch-based slurry by modifying natural starch with acrylamide. The paste has excellent viscosity stability and fiber adhesion, and exhibits excellent performance during warp sizing. In addition, the slurry has good water solubility at 60-70 °C, so it is easy to desize at low temperatures. Because of this, the sizing of the warp can be deslimed directly from the yarn during subsequent washing processes. This work can not only reduce some costs for the textile industry, but also achieve the purpose of energy conservation and emission reduction.

Prediction of wellbore sand production potential from analysis of petrophysical data coupled with field stress: a case study from the Shah-Deniz gas field (Caspian Sea Basin)

Identifying the optimal azimuth and inclination for wellbore drilling in sandy formations can be considered a valuable aid in reducing sand production risks, lost time, and decreasing drilling costs in the petroleum industry. Therefore, a numerical systematic approach was provided to predict sand production in wellbore SDX-5, drilled in a deep-water sandstone reservoir in the Shah-Deniz gas field (South Caspian Basin), which has never been done previously. Additionally, this systematic approach uses geomechanical and geodynamical criteria, along with petrophysical information (density and sonic log) and tectonic characteristics of the study area, which are influenced by the active tectonic stresses of the Apsheron-Balkhan zone. The subsurface data sources employed are more eco-friendly, available, and continuous than experimental tests. The computations conducted achieved azimuth, inclination, polar, and depth profile plots for the Lower Balakhany Formation. The calculations reveal that the optimum azimuth for the wellbore drilling trajectories is parallel to SHmax and oblique drilling to near horizontal is the result of optimum inclination. Polar plots showed optimum azimuth, inclination, and effect of wellbore trajectory on critical collapse pressure and collapse drawdown pressure with pressure values simultaneously, which identify safer alternatives for achieving higher petroleum production rates without sanding. Depth profile plots provide a simultaneous overview of the values of critical collapse pressure, critical sanding pressure for instantaneous drawdown, and optimum wellbore production pressure during drilling and production operations. Moreover, optimum reservoir fluid production (maximum discharge) rates can be identified and imposed as upper limits to prevent sand production.

IMPROVEMENT OF THE CLEANING SYSTEM OF OIL GAS FLOWS USING AN AERODYNAMIC INSERT

Air pollution is becoming a problem due to inefficient technological processes that accompany the mechanical processing of solid materials in various industries, including metalworking and woodworking, coal enrichment, coal burning in thermal power plants, metallurgy and construction materials industries. The problem is relevant for cement factories, since some of them use outdated equipment. Fine dust in this context becomes particularly important because the particle size of this dust affects the quality and grade of the concrete produced. Given the specifics of cement production and the goals of our research, which are to effectively collect small particles, it is important to note that wet cement production methods are not the best solution. The ideal solution for the problem of cleaning dust and gas flows in the cement industry is the use of a two-stage dust collection system, which combines an advanced cyclone and a bag filter. The system's periodic shaking mechanism allows for effective capture and control of fine dust particles, ensuring high quality cement production and reducing environmental impact. The combination of a cyclone, an acoustic coalescer and a block of bag filters, which is equipped with a periodic cleaning mechanism, as well as the addition of a system for collecting fine dust using a collector funnel, will split the collected dust into two fractions: fine (a = 10−5 to 10−7m) and coarse (a > 10-4m). The first fraction can be used to produce high-quality cement of high cost in the cement industry. The second fraction returns to the main technological process at its finishing stage.

Demand Response Scheduling Considering Pollutant Diffusion Uncertainty of Industrial Customers

The demand response scheduling scheme requires the consideration of both the industrial customers' economic cost and the environmental influences from pollutants. However, the diffusion process of the latter, although of paramount importance, is typically ignored in the existing literature. To address this issue, we propose a demand response scheduling scheme that not only precisely simulates the diffusion process through a spatio-temporal diffusion model, but incorporates the uncertainty into the diffusion trajectories via a Markov decision process. This enables the schedule-maker optimally select the industrial customers to participate in the demand response with a minimum cost while reducing the environmental influences of the pollutants simultaneously. Using it, a deep reinforcement learning approach is further advocated in the optimization procedure to improve the scalability of the proposed method. Simulation results on the modified IEEE-118 test system reveal the validity of the proposed method.

Online measurement method for dimensions of disk parts based on machine vision.

Online measurement of disk part dimensions by the standard industrial camera features low cost, high efficiency and good universality, but the impact of projection distortion and end face chamfer on measurement is needed to overcome. Present work presents a measurement method to resolve above issues based on machine vision. To improve the measurement accuracy, lower end face of a disk part is determined as calibration plane and the upper end face is measurement plane. To reduce the impact of projection distortion and chamfer on measurement, the measurement points are reconstructed on the measurement plane by re-projection. Then, the inner and outer diameters of disk parts are measured by circle geometric fitting, and the thickness is calculated by the measurement plane position. The experimental results show that the method can online measure disk part dimensions just by a single image, and accuracy meets the requirements of universal grade disk parts.

Residual Stress Measurement of Used Mining Dump Truck Frame for Remanufacturing Purposes

Remanufacturing the main frame of a mining dump truck can save cost, energy, and materials in heavy equipment industries. It also can reduce CO2 emissions for environmental preservation to achieve sustainability. However, since the mainframe received a dynamic load during operation, it presumably leaves accumulated residual stresses in the frame. The residual stress, particularly tensile residual stress, stands out as a primary contributing factor to the initiation of cracks, which may ultimately result in failures. In this paper, the residual stress of the used mining dump truck main frame was identified by modeling simulation using FEA (finite element analysis) and actual measurement using a portable x-ray residual stress analyzer with the cos α method. The results showed that the weld area subjected to dynamic loads exhibited the highest tensile residual stress, reaching approximately +772 MPa. This specific region emerges as a critical area demanding attention during the remanufacturing process. The application of PWHT (post-weld heat treatment) at 400 °C for 1 hour effectively reduced residual stress on the weld joint, predominantly tensile residual stress, by more than 80%.

Analysis of the coefficient of unpredictable costs in the construction industry in Slovakia

The main vision of the article is how the current situation in the construction industry affects the cost of construction equipment in Slovakia, because during the implementation, unforeseen costs enter the costs, which are not foreseen in the planning. Current inflation in Slovakia is one of the highest in Europe. The methods used during the research were initial quantitative questionnaires. The output of these was processed using statistical methods and subsequently evaluated. The current situation requires considerable attention in the calculation of individual construction costs. As it is a very challenging process due to the unpredictable market situation in terms of inflation, the price of energy increases, which also causes the rise in the prices of materials and wages. The data obtained can be used by construction companies to calculate the construction equipment. Construction companies in Slovakia can apply the information obtained in the preparation of a quote for construction work that includes construction equipment.

Analysis of implementing the Ukrainian healthcare reform in 2023

The main research task is to study the issue of effectiveness of implementing the healthcare reform in Ukraine using the main levers of influence on the most significant items of expenditure in the medical industry itself. Also, we investigate the main items of income and expenses of medical service providers, their specific weight and management methods for more rational use. It is worth noting that the positive dynamics in the direction of effectiveness of the healthcare industry is not only the main priority. It is also a direct tool that drives the general processes in the medical industry. Increasing the level of social protection is one of the primary goals of medicine and, as a result, improving the quality of state population life. In a chain reaction, this will lead to a reduction in costs for the healthcare industry due to faster recovery of patients and reduction of time spent in a state of temporary incapacity. One of the key aspects of the medical reform efficiency remains the issue of remuneration of workers. Before carrying out reform measures, doctor salaries were officially at the minimum level. Therefore, the principle of treatment for the patient’s money was widespread in the industry. The main motivating element of the human capital efficiency is salary – reward for work results. So, if the salary directly depends on the target indicators that must be achieved in the production process, then the employee’s motivation increases. Based on the fact that the main direction of funds expenditure at medical institutions is labour costs, the main efforts and attention should be paid in the organisational and administrative plan to work with the effective use of this item of expenses. It is worth noting that the salary of any employee is the main measure of his work efficiency. It is a motivator to improve the quality and treatment efficiency. If the amount of reward depends on the employee’s performance indicators, the system will have additional motivation not only in the quantitative characteristics of the work result, but also in the qualitative parameters.

Industrial Data-Driven Processing Framework Combining Process Knowledge for Improved Decision-Making—Part 2: Framework Application Considering Activity-Based Costing Concepts

Operating time series data collected and stored in historian must be managed to extract their full potential. Part 1 of this paper proposed a structured way (a sophisticated approach) to process industrial data; this first part explains in detail the data processing framework used as the basis for the costing analysis present in the second part of this series. The framework considers the analysis scope definition, data management steps, and operating regimes detection and identification. The added value of this proposed framework is demonstrated in Part 2 via the use of cost accounting for operational problem-solving (debottlenecking), i.e., its practicality is validated via its application alongside a cost analysis on the brownstock washing department of a kraft pulp mill. The traditional debottlenecking approach assumes a single operating condition considering that operating regimes allow for a much more sophisticated debottlenecking study of the washing department. With the use of operations-driven cost modeling (contingent on activity-based costing concepts) and processed time series data corresponding to steady-state operation, incremental profit can be assigned to each operating regime in order to identify the most cost-efficient one. The overall objective of this two-part series is to convert processed industrial steady-state data and cost information into knowledge that can be used to optimize the washing department of a chemical pulp mill. More specifically, different operating regimes are assessed, and the most suitable operating strategy is defined. The application of activity-based costing on a large amount of historically processed industrial data led to the improvement in the operation. The identified optimal way to operate (pulp throughput, pulp conductivity, defoamer and bleaching chemical quantity, etc.) led to a profit of CAD 49 M per year. Lastly, a contribution analysis of the regimes based on PCA highlighted how the process was operated when the preferred performances happened.

Economic Variables as an Early Warning Sign for Monitoring Construction Cost Indices – “An Empirical Study on Egypt”

The construction industry plays a crucial role in any nation's economic growth and prosperity through the implementation of the SDGs. Researchers reveal that the 17 SDGs are directly dependent by 17% and indirectly reliant by 27% on the construction industry's activities. In addition, the construction projects, whatever their type or components, continue for several years, during which many price changes and sharp economic fluctuations occur, whether at the local or international level, reflected in overall economic performance and the construction industry's health, leading to the project's cost changes and a shortage in the allocated budgets. Due to the difficulties this industry faces in reaching these goals, including the Egypt Vision 2030, we chose to look into these effects by using the ENR methodology to develop an explanatory construction cost indices model in Egypt similar to models used in other countries while making appropriate changes for the Egyptian markets. To illustrate the relationship between these selected economic variables and construction costs in Egypt and to act as an early warning sign to quantify, track, and predict the construction cost movements and trends in Egypt's construction sectors through a reliable model. A mixed research methodology consisted of semi-structured interviews with 15 industry experts and an empirical study covering 1990 through 2020 for selected local and international economic variables. We concluded that national and international economic variables significantly impacted as explanatory and predictive variables in Egypt's construction industry's cost indices; these variables are as follows: gross domestic product (GDP), consumer price index (CPI), USD to EGP exchange rate ($), inflation rate, lending rate, money supply, and unemployment rate, as well as international crude oil prices, gold prices, and copper prices. Nevertheless, further investigation is required with more economic variables across various construction industry sectors over various time intervals and different time series statistical and econometric modeling techniques.

Impact of the Global COVID -19 Pandemic on the Earnings of the Construction Industry

The past two and half years has witnessed the huge impact of COVID-19 on the world economy. Construction industry is a pillar of the economy, buildings such as factories and warehouses and structures such as roads, docks, and dams required by various material production departments of the national economy are all products of the construction industry; machinery and equipment of industrial enterprises must also be installed by construction enterprises to form the final production capacity. is going through huge effect caused by COVID-19.This research aims to develop an understanding of how much, from which aspects and at what ratio the COVID -19 pandemic have affected the earning of construction industry by calculating the relative earnings of the construction industry through the data collected about four cities around the world. The result showed that Both the income and cost of the construction industry suffered from loss at the first stage of covid-19 pandemic. While London and NYC went through more loss in construction industry compared with Beijng and Wuhan.

Application of computational fluid dynamics simulation in predicting food protein denaturation: numerical studies on selected food products - a review*

Abstract Protein denaturation is a common process in the food industry, which can impact food quality and safety. Computational Fluid Dynamics (CFD) is a powerful tool that can be used to predict protein denaturation in food products. In this review article, we present an overview of the application of CFD simulation in predicting protein denaturation in food products. We discuss the factors that influence protein denaturation, the importance of predicting protein denaturation, and the various numerical methods used in protein denaturation studies. The main focus of the article is the use of CFD simulation in predicting protein denaturation in selected food products, such as milk, meat, and eggs. We provide examples of numerical studies that have been conducted on these products, and we discuss the results and implications of these studies. The use of CFD simulation can help to optimize food processing conditions, improve food quality and safety, and reduce waste and costs in the food industry. Overall, this review article highlights the importance of using advanced computational tools such as CFD simulation in food science, research and development. Highlights The use of CFD simulation can predict protein denaturation in food products. Numerical studies were conducted on selected food products to analyze protein denaturation. CFD simulation provides a powerful tool for optimizing food processing technologies. The results from the numerical studies can be used to improve the quality and safety of food products. The application of CFD simulation can lead to more efficient and sustainable food production practices.

2 × 4.5 kW bidirectional output near-single-mode quasi-continuous wave monolithic fiber laser

Quasi-continuous wave (QCW) laser has a very broad application in the industrial field, especially in additive manufacturing, surface treatment, laser cutting, laser cleaning, and laser drilling. Compared with the unidirectional fiber laser, the bidirectional output can be achieved two ports high power output with only one resonator, which can greatly reduce the industrial cost. However, there are few researches on QCW fiber lasers with bidirectional output. Here, we optimized and demonstrated a bidirectional output QCW laser with output power of 2 × 4.5 kW based on a double-clad ytterbium-doped fiber with a core/cladding diameter of 25/400 μm. The peak power at both ends reached 4515 W and 4694 W, respectively. The Raman suppression ratio at both ends of A and B is about 12 dB, and the beam quality factor M2 is about 1.37 and 1.42, respectively. The corresponding optical-to-optical efficiency is 79%. To the best of our knowledge, this is the highest peak power of QCW laser with near-single-mode beam quality in a bidirectional structure laser.

The green economic impact of a green comprehensive industry agglomeration: An example from the sports industry

The optimization of industrial structure and layout is essential for promoting the high-quality development of the regional economy. As a typical example of a green comprehensive industry, the agglomerations of the sports industry have the potential to release additional green benefits. Consequently, this paper uses the balanced panel data of 30 provinces, municipalities, and autonomous regions in China from 1998 to 2021 as samples and, based on the strategic background of China's dual-carbon target and the re-interpretation of the green economy, uses the Super-SBM model to re-measure the green economic efficiency of each region and applies the dynamic spatial Durbin model and the dynamic panel system GMM model to evaluate the direct effect, mediating mechanism, spatial spillover effect, and heterogeneity effect of sports industry agglomeration on the regional green economic efficiency. Empirical findings indicate that: (1) The improvement of green economic efficiency under China's dual-carbon target has the characteristics of dynamic accumulation, and there is a siphon effect between neighboring regions. (2) The effects of sports industry agglomeration on local green economy efficiency show an "inverted U-shape" with a positive spatial spillover effect on the green economy efficiency of neighboring regions; this conclusion is robust. (3) The green economy effect of sports industry agglomeration is more significant in the central and western regions, regions with strict environmental regulations, and regions with a higher willingness for resident participation in sports due to industrial density, compliance costs, and characteristics of sports industry development. (4) Sports industry agglomeration can promote regional green economy efficiency by escaping natural resource dependence and increasing healthy human capital; technological innovation, rationalization of industrial structure, and labor transfer serve as "inverted U-shaped" mediators between sports industry agglomeration and regional green economy efficiency. This study expands the meso- and spatial-level perspectives of the impact of the agglomeration of green industries and comprehensive industries on green development. It is of great theoretical and practical importance for promoting the construction of a regional green industrial system and the high-quality development of the green economy.

Teaching the Complex Dynamics of Clean Energy Subsidies With the Help of a Model-as-Game

The economic and policy justifications for clean energy subsidies are complex and difficult to internalize. A subsidy induces additional consumers to buy, reducing carbon emissions through reduced fossil fuel consumption. Over the long term, subsidies encourage industry investment and cost reductions. Ideally, subsidies can be removed when the technology is broadly competitive. Deciding on an appropriate level of government subsidy is complex because a decision-maker should balance government expenditures and benefits over both time and space. A subsidy can be excessive when government costs are too high and/or many consumers would have purchased the unsubsidized product, but can also be too low if insufficient to encourage adoption. In order to educate non-experts on these ideas, we created a case study about the topic, consisting of teaching materials and a cooperative multiplayer game that is playable in small groups in 15–30 min. We have used the case study in both university courses and public-facing events and believe that it would be of interest as teaching material for cost-benefit analysis, government subsidy design, clean energy policy, and science and technology policy education or training. After 15 min with the game, players have a basic understanding of all the important factors and dynamics of subsidy design. For the reader, this article offers a specific example of how to translate a sophisticated technoeconomic decision model into an educational game and includes rules and supplementary materials needed to cover the topic of subsidy design and to try the game in courses and general public settings.

High-intensity ultrasound promoted the maturation of high-salt liquid-state soy sauce: A mean of enhancing quality attributes and sensory properties

High-intensity ultrasound was used as a means to promote maturation of soy sauce. The optimal conditions for ultrasound treatment were 90℃ at an ultrasound intensity of 39.48 W/cm2 for 60 min. The total reducing sugars and soluble salt-free solids content was significantly increased after ultrasound-assisted maturation. The free amino acid content was significantly decreased, mainly due to the Maillard reaction (MR). The promoted MR produced several types of flavor compounds, including esters, pyrazines, and ketones, which imparted an attractive aroma to the maturated soy sauce. The proportion of peptides with a molecular weight of 1–5 kDa provided umami as an important flavor characteristic, and the content in the ultrasound-matured soy sauce (10.19 %) was significantly higher than that in the freshly prepared soy sauce (8.34 %) and the thermally treated sample (8.89 %). Ultrasound-assisted maturation would improve product quality and meanwhile, shorten the duration and reduce the cost for the soy sauce industry.

Rancang Bangun Sistem Monitoring Daya Listrik Cerdas Berbasis Internet of Things Menggunakan Mikrokontroler Arduino Mega Pro 2560 Dan ESP8266-01

This intelligent electricity monitoring system aims to overcome the problem of excessive electricity use which results in skyrocketing electricity costs in homes and industries, as well as minimizing the high risk of damage to household equipment due to excessive loads. The intelligent electricity monitoring system is an instrument designed using an Arduino Mega 2560 as a microcontroller, ESP8266-01 as a WiFi module, an I2C LCD as a display, an audio jack socket as a sensor input, a resistor as a voltage divider and a current sensor. YHDC SCT013 as a current measurement tool. From now on, the Arduino Mega 2560 and ESP8266-01 will send monitoring data to users using Internet of Things (IoT) based technology. Notifications will appear on the LCD and on the blynk platform or application screen.

Dense neural network based arrhythmia classification on low-cost and low-compute micro-controller

The electrocardiogram (ECG) monitoring device is an expensive albeit essential device for the treatment and diagnosis of cardiovascular diseases (CVD). The cost of this device typically ranges from $2000 to $10000. Several studies have implemented ECG monitoring systems in micro-controller units (MCU) to reduce industrial development costs by up to 20 times. However, to match industry-grade systems and display heartbeats effectively, it is essential to develop an efficient algorithm for detecting arrhythmia (irregular heartbeat). Hence in this study, a dense neural network to detect arrhythmia on the Arduino Nano is developed. The Nano consists of the ATMega328 microcontroller with a 16 MHz clock, 2 KB of SRAM, and 32 KB of program memory. Additionally, the AD8232 SparkFun Single-Lead Heart Rate Monitor is used as the ECG sensor. The implemented neural network model consists of two layers (excluding the input) with 10 and four neurons respectively with sigmoid activation function. However, four approaches are explored to choose the appropriate activation functions. The model has a size of 1.267 KB, achieves an F1 score (macro-average) of 78.3% for classifying four types of arrhythmia, an accuracy rate of 96.38%, and requires 0.001314 MOps of floating-point operations (FLOPs). It significantly outperformed recent studies in terms of neural network metrics and compute resource usage efficiency.

An analysis of cost and revenue of Bakery Industry in Dharan

The research paper aims to analyse the cost and revenue of bakery industry in Dharan. This research is based on primary data. To achieve the objective, quantitative and qualitative research designs have been used. Bakery industry is the emerging business industry in Dharan. Bakery industry is a huge business that caters to people's weaknesses for tasty breads, cakes, pies and sweet rolls. It is revealed that the cost and revenue of bakery products have highest mean values whereas location is least important than other dimensions. There is various bakery industry in Dharan, which produce different types of Bakery products and it provides various job opportunities. Lack of skilled manpower, scarcity of water, sufficient amount of food product are major problems of bakery industry and high price of raw material is another major problem of bakery industry in Dharan.

Cost Percentage of Waste Management to Overall Costs in Hospitality Industry

For any business start up this a key part that how to manage finances and what are the initial set up costs and legal documents and procedures for that start up. Every hotel generates a big volume of waste annually so during the Hotel business start up planning it’s a very important factor that how the hotel will manage the waste generated from hotel and guests and what will be initial set up cost for waste management system and what are the monthly or annual cost to run the waste management system ideally. Hotel waste management is an essential part of running a successful hotel. Waste is not only expensive to have collected, but also represents a waste of valuable resources and supplies which were paid for in the first place. Hospitality businesses can take some simple actions to minimize their costs by preventing waste and correctly segregating what goes into bins.As staff manages waste every day, they are best placed to identify improved waste management measures so make sure to engage with them and train them for optimize the waste management system.