Improve Production Efficiency Research Articles

Changeover minimization in the production of metal parts for car seats

We tackle a capacitated lot-sizing and scheduling problem (CLSP) with the main objective of minimizing changeover time in the production of metal parts for car seats. Changeovers occur when a machine (or production line) is reconfigured to produce a different product or part, leading to production downtime and loss of efficiency. In this study, we first provide a mixed-integer programming (MIP) formulation of the problem. We test the limits of solving the problem with commercial mathematical programming software. We also propose two approaches to tackle instances found in practice for which the mathematical programming model is not a viable solution method. Both approaches are based on partitioning the entire production of a part into production runs (or work slots). In the first approach, the work slots are assigned to machines and sequenced by a metaheuristic that follows the search principles of the GRASP (greedy randomized adaptive procedure) and VNS (variable neighborhood search) methodologies. In the second approach, we develop a Hexaly Optimizer (formerly known as LocalSolver) model to assign and sequence work slots. The study provides insights into how to minimize changeovers and improve production efficiency in metal parts manufacturing for car seats. The findings of this study have practical implications for the auto-part manufacturing industry, where efficient and cost-effective production is critical to meet the demands of the market.

Energy efficiency and economic analysis of mechanized vs conventional cotton production system: A comparative study under rainfed vertisols of Tamil Nadu

Energy efficiency plays a pivotal role in optimizing input use and improving the sustainability of agricultural practices, especially in energy-intensive crops like cotton. Due to its high economic importance, cotton cultivation has been in the need of the hour in developing mechanized cultivation practices aimed at improving production efficiency. This study evaluated energy consumption and performed an economic analysis of mechanized versus conventional cotton production under rainfed vertisols in Tamil Nadu. Among the various inputs, fertilizer application consumed the most energy in both systems, followed by labor energy differences between the 2 methods. Mechanized cultivation drastically reduced labor energy requirements (174.2 MJ/ha) compared to manual methods (2215.6 MJ/ha), highlighting the potential for labor savings. Mechanized cultivation also showed more efficient use of non-renewable energy sources, whereas conventional methods relied more on renewable energy inputs, highlighting the trade-offs between the 2 systems. Mechanized cultivation significantly reduced production costs (Rs. 74290/ha) compared to conventional methods (Rs. 140440/ha), largely due to a 47.8 % reduction in labor costs, demonstrating its economic viability. This study suggests that improving the energy efficiency of mechanized cotton production should prioritize efficient fertilizer use and reducing diesel fuel consumption through enhanced machinery performance.

МЕХАНІЗМ ФОРМУВАННЯ СТРАТЕГІЇ ІННОВАЦІЙНОГО РОЗВИТКУ БУДІВЕЛЬНИХ ПІДПРИЄМСТВ

The article identifies that as of today, Ukraine's construction industry is operating under challenging conditions during the period of the full-scale invasion of Ukraine by the Russian Federation. It was found that in 2022, the construction sector lost its position in the structure of the country's GDP by 1.6%, compared to 2020-2021, where it accounted for 2.8%. It is determined that the share of the construction industry in the GDP throughout the examined period did not exceed 3%, which is significantly lower than the corresponding period in European countries. Additionally, the article examines the mechanism for forming a strategy of innovative development for construction enterprises, which enhances their competitiveness and adaptability to market changes. The key aspects of developing an innovation strategy for construction enterprises are described: improving production efficiency; enhancing the quality and durability of structures; adapting to market conditions; ensuring competitiveness; promoting sustainable development; improving working conditions and safety on-site; attracting investment and business growth. Key steps at the main stages of developing an innovation strategy are proposed, including an analysis of the external and internal environment, the determination of strategic goals, the development of innovative solutions, investment in resources and personnel, as well as strategy monitoring and adaptation. The importance of applying various methods and tools to optimize, increase productivity, and improve enterprise adaptability was emphasized. The proposed approach allows construction companies to enhance production efficiency and achieve sustainable development in the face of modern challenges and technological changes. Keywords: innovations, innovative development, competitiveness, construction enterprise, 3D printing, modular construction.

The Path to Net-Zero in Dairy Production: Are Pronounced Decreases in Enteric Methane Achievable?

Achieving net-zero greenhouse gas (GHG) emissions in dairy production will require >50% reduction in enteric methane (CH4) emissions together with elimination of emissions from feed production, additional carbon sequestration, reduction in manure emissions, anaerobic digestion of manure, and decreased reliance on fossil fuel energy. Over past decades, improved production efficiency has reduced GHG intensity of milk production (i.e., emissions per unit of milk) in the United States, but this trend will continue only if cows are bred for increased efficiency. Genetic selection of low-CH4-producing animals, diet reformulation, use of feed additives, and vaccination show tremendous potential for enteric CH4 mitigation; however, few mitigation strategies are currently available, and added cost without increased revenue is a major barrier to implementation. Complete elimination of CH4 emissions from dairying is likely not possible without negatively affecting milk production; thus, offsets and removals of other GHGs will be needed to achieve net-zero milk production.

The impact of energy structure on agricultural green productivity in China.

The agricultural development in China is currently grappling with the challenges of limited water and soil resources, environmental pollution, and ecosystem degradation. Therefore, improving agricultural green productivity has become the focus of academic attention. Based on the panel data of 30 provinces in China from 2008 to 2020, this paper constructs an index system of agricultural productivity. Subsequently, the super-efficiency SBM model is used to calculate the green productivity of agriculture, and its characteristics are analyzed from the perspectives of temporal and spatial.Through the empirical test of threshold model, it is found that China's agricultural green productivity shows a gradual growth trend from 2008 to 2020, and the growth rate has accelerated significantly in recent years. There is a non-linear relationship between energy structure and agricultural green productivity. Especially in areas with reasonable energy structure, the increase in the proportion of coal consumption will inhibit the improvement of green agricultural productivity. This paper suggests reducing dependence on fossil energy, improving market mechanism and optimizing resource utilization in order to promote green agricultural production in China. This study expands the research perspective of agricultural green productivity, provides new research methods and ideas for related fields, and provides a reasonable energy allocation plan for agricultural production, which helps to improve production efficiency and reduce costs.

Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses

This review examines the increasing application of artificial intelligence (AI) and/or machine learning (ML) in microalgae processes, focusing on their ability to improve production efficiency, yield, and process control. AI/ML technologies are used in various aspects of microalgae processes, such as real-time monitoring, species identification, the optimization of growth conditions, harvesting, and the purification of bioproducts. Commonly employed ML algorithms, including the support vector machine (SVM), genetic algorithm (GA), decision tree (DT), random forest (RF), artificial neural network (ANN), and deep learning (DL), each have unique strengths but also present challenges, such as computational demands, overfitting, and transparency. Despite these hurdles, AI/ML technologies have shown significant improvements in system performance, scalability, and resource efficiency, as well as in cutting costs, minimizing downtime, and reducing environmental impact. However, broader implementations face obstacles, including data availability, model complexity, scalability issues, cybersecurity threats, and regulatory challenges. To address these issues, solutions, such as the use of simulation-based data, modular system designs, and adaptive learning models, have been proposed. This review contributes to the literature by offering a thorough analysis of the practical applications, obstacles, and benefits of AI/ML in microalgae processes, offering critical insights into this fast-evolving field.

Fe/Co-modified Enteromorpha bio-hydrochar enhanced anaerobic digestion of chicken manure with sulfadimethazine: focusing on synergistic mechanism and microbial community succession

Abstract Residual antibiotics in chicken manure may interfere with the stability of anaerobic digestion (AD) and inhibit resource utilization efficiency. In this study, we aimed to enhance chicken manure bio-methanation in AD with high-concentration of sulfamethazine (SMZ) by adding metal (Fe, Co)-modified Enteromorpha-based hydrochar (Co-HC, Fe-HC). The results showed that Fe-HC and Co-HC increased the degree of acidogenesis by 1.25 times and 1.58 times, respectively. The maximum protein concentration in EPS was increased by 47.64% and 72.5% after adding Fe-HC and Co-HC. However, only Co-HC demonstrated notable improvements in both methane production and SMZ removal efficiency. Electrochemical analysis showed that Co-HC possessed a richer variety of oxygen and nitrogen functional groups, along with superior electron exchange capabilities compared to Fe-HC. Furthermore, microbiological assessments revealed that Co-HC enriched syntrophic bacteria (such as Syntrophomonas and Mesotoga), facilitating direct interspecies electron transfer (DIET) and subsequently enhancing biomethane production. The abundance of genes involved in electron transfer increased significantly with Co-HC, with a maximum increase of 75.86% in Co1.5-HC treatment. Additionally, the elimination of antibiotic resistance genes (sul1, sul2) increased by 65.66% in the Co1.5-HC treatment. This study offers a theoretical foundation and empirical support for the synergistic improvement of livestock and poultry manure containing high antibiotic concentrations, thereby helping to overcome challenges posed by recalcitrant substances. Graphical Abstract

Has Trade Liberalization Promoted Energy Efficiency in Enterprises?

Improving energy efficiency is a way for China’s economy to achieve sustainable development. Using data on listed industrial enterprises in China from 2000 to 2022, we investigate the impact of trade liberalization on the energy efficiency of Chinese firms and its mechanism of action at the micro-firm level. Our findings suggest that trade liberalization has greatly contributed to firms’ energy efficiency and the main conclusions in this paper still hold after a series of robustness tests. Further research shows that two channels that contribute to the improvement of firms’ energy efficiency are the expansion of the firm’s size and the improvement of production efficiency induced by trade liberalization. Another significant route according to which trade liberalization influences energy efficiency improvements by firms is the dynamic decomposition of industrial energy efficiency, which shows that 70.07% of industrial energy efficiency enhancement is due to structural adjustments. The heterogeneity analysis results show that the energy saving impact of trade liberalization is stronger for non-exporting, foreign-funded, growth-oriented enterprises that are based in the eastern region. Our study presents new ideas for the realization of energy conservation and emissions reduction from the perspective of trade liberalization, which is instructive in regard to the improvement of sustainable development of enterprises.

Roasted sesame oil: A review on production technology, flavor chemistry, and other related issues

AbstractSesame oil (SO) produced through roasting technology offers pleasant flavor, often named roasted sesame oil (RSO) in the market. During the RSO production process, roasting is an essential technology in determining the flavor of RSO, which directly influences the consumer acceptance. Therefore, the present work systematically offers current knowledge on flavors and related issues of RSO, which will focus on production technologies (i.e., roasting technology, extraction technology, subsequent processing technology), flavor characteristics and flavor compounds, formation pathways of major flavor compounds (i.e., Maillard reaction pathway, oil oxidation pathway, thermal degradation pathway), and effects of roasting on the nutrition and safety. In addition, the present work provides an outlook for the future development of RSO industry, including the establishment of a grading system for the evaluation of RSO flavors, high‐value utilization of by‐products from RSO processing, and how to improve production efficiency of RSO. This work could provide a better understanding of RSO roasting process and promising information for better production of aromatic, nutritious and safe RSO by controlling/innovating the roasting process.

Development of Software for Hydrometallurgical Calculation of Metal Extraction

Hydrometallurgy plays a critical role in the metallurgical industry by providing an efficient method for extracting metals from ores and secondary materials using aqueous solutions. This approach is particularly advantageous for processing low-grade and complex ores, as well as secondary resources that cannot be effectively processed by traditional pyrometallurgical methods. The objective of this study is to develop specialized software to automate and optimize the calculations necessary for metal extraction in hydrometallurgical processes. The software integrates a complete computational framework for automating the various stages of the hydrometallurgical process, including ore composition initialization, total element mass calculations, and the determination of metal concentrations in both metal products (matte) and by-products (slag). The methodology involves the design and implementation of a web-based application using Django for the user interface and MySQL for robust data storage. The computational module, written in Python, automates the mathematical operations required to simulate complex chemical reactions and metal extraction processes. This module supports real-time processing and ensures accurate calculations for each stage of metal extraction, including leaching, extraction, re-extraction, sorption, and electrolysis. The software also features detailed tables and dynamic graphs that allow users to analyze the distribution of valuable metals and assess the influence of key operational parameters on extraction efficiency. The results show that the developed software successfully manages large datasets, enhances the precision of hydrometallurgical calculations, and minimizes the risk of human error. The implementation of the software leads to significant improvements in the economic efficiency of production by optimizing metal recovery rates and reducing operational costs. Additionally, it supports comprehensive process control by providing actionable insights into each stage of extraction, thus improving the quality of the final metal product. Overall, the software represents a significant technological advancement in the field, offering a scalable solution for industries aiming to streamline hydrometallurgical processes.

Sustainability in Long-Term Surface Mine Planning: A Systematic Review of Operations Research Applications

The mining industry, critical for global resource supply, has historically been linked to significant environmental degradation and social challenges, including habitat disruption, water and soil contamination, as well as fatalities. But recently, the industry has been undergoing a transformative change to meet evolving environmental and societal expectations. Operations Research (OR) provides essential tools and techniques to optimize decision-making processes in this context. This paper presents a comprehensive review of different OR methods and their applications in balancing economic, social, and environmental objectives in surface mine planning. Of the 63 papers reviewed, 45 were published by researchers from three main countries: Canada, the United States, and Australia, with 73% of these papers appearing in journals. This review highlighted that linear programming (LP), dynamic programming (DP), Lagrangian relaxation (LR), stochastic programming, and metaheuristics are among the most widely applied methods in surface mine planning within a sustainable development (SD) context. By evaluating the strengths and limitations of these techniques, this review offers valuable insights for researchers and practitioners aiming to improve production efficiency and sustainability through advanced planning strategies.

Plastic Injection Molding Process Analysis: Data Integration and Modeling for Improved Production Efficiency

This paper presents a comprehensive analysis of the plastic injection molding process through the integration of data acquisition technologies and classification models. In collaboration with a company specializing in plastic injection, data were extracted directly from the machine during a specific period at the beginning of a shift change. These data were subjected to exploratory analysis to identify correlations between important variables, such as injection time, cycle time, and mold pressures. Additionally, classification models, including Random Forest and Logistic Regression, were constructed to predict and classify the process state based on these variables. The model results demonstrated high predictive performance, with 99.5% accuracy for Random Forest and 97% for Logistic Regression. These results provide a strong foundation for the early identification of potential problems and informed decision making to improve the efficiency of the plastic injection molding process. This study contributes to the advancement of the integration of intelligent technologies in industrial process optimization, aligned with the principles of Industry 4.0.

Application of the Finite Element Method for Analyzing the Vibration Characteristics of a Spindle System and Fault Diagnosis

The performance of a spindle will gradually decline, the vibration intensity will increase, and the temperature rise will become abnormal with the accumulation of service time. Consequently, the accuracy of the machining product will not meet its production requirements. Studies on the variation characteristics of the spindle unit have clarified the reasons for its abnormal vibration and temperature rise, in principle, to help enterprises conduct preventive maintenance before any serious failure occurs and improve production efficiency. Based on the Timoshenko beam model and rotor dynamics theory, this study uses the finite element method (FEM) to analyze the vibration characteristics of the spindle rotor system. Moreover, it thoroughly analyzes the influence of the spindle bearing heat on the stiffness of the spindle system and identifies the resonance conditions of the spindle rotor within the power frequency range. This research has identified that when the vibration frequency of the spindle operates at a speed of 12,000 r/min, if its vibration frequency is lower than 200 Hz, it will be affected by abnormal vibrations during startup, which will weaken the health status of the spindle and reduce its service life. Similarly, when the working speed of the spindle is 30,000 r/min, if its vibration frequency is lower than 50 Hz, abnormal vibration will occur during startup and operation, thereby reducing its service life.

Analisis Perhitungan Biaya Pesanan dalam Menentukan Harga Pokok Produksi Job Order Costing Kue Karawo

This study aims to analyze the calculation of order costs in determining the cost of production for Karawo Cakes using the job order costing method. This method allows the company to determine production costs more accurately by allocating direct and indirect costs to each specific order. In this research, data were collected through interviews and direct observation of the production process of Karawo Cakes at one of the SMEs in Gorontalo, namely Toko Karwo Li Maya. The results of the analysis indicate that the use of the job order costing method can provide more detailed and accurate information regarding the components of production costs, including raw materials, direct labor, and factory overhead. This information is crucial in determining competitive selling prices and improving production efficiency. Thus, the job order costing method helps the company improve the accuracy of production cost calculations and supports better decision-making in pricing strategies.

Optimizing Fermentation Strategies for Enhanced Tryptophan Production in Escherichia coli: Integrating Genetic and Environmental Controls for Industrial Applications

Tryptophan is an essential aromatic amino acid widely used in the pharmaceutical, agricultural, and feed industries. Microbial fermentation, mainly using Escherichia coli, has become the preferred method for its production due to sustainability and lower costs. Optimizing tryptophan production requires careful control of various fermentation parameters, including nutrients, pH, temperature, and dissolved oxygen (DO) levels. Glucose, as the primary carbon source, must be fed at controlled rates to avoid metabolic overflow, which leads to by-product accumulation and reduced production efficiency. Nitrogen sources, both organic (such as yeast extract) and inorganic (like ammonium), influence biomass growth and tryptophan yield, with ammonium levels requiring careful regulation to avoid toxic accumulation. Phosphate enhances growth but can lead to by-product formation if used excessively. pH is another critical factor, with an optimal range between 6.5 and 7.2, where enzyme activity is maximized. Temperature control promotes growth and production, particularly between 30 °C and 37 °C. High DO levels increase tryptophan titers by boosting the pentose phosphate pathway and reducing by-products like acetate. Furthermore, surfactants and supplements such as betaine monohydrate and citrate help alleviate osmotic stress and enhance precursor availability, improving production efficiency. Careful manipulation of these parameters allows for high-density cell cultures and significant tryptophan accumulation, making microbial fermentation competitive for large-scale production.

Synergistic abatement effects of Broadband China and environmental regulation: Firm-level evidence

Based on the new era context of digital economy and green development, this study uses Broadband China (BC) as a quasi-natural experiment, combining its strategic interaction with environmental regulation (ER), to empirically test the policy synergistic abatement effect of BC and ER. BC has resulted in an average of 6 % reduction in corporate carbon emissions, and the BC–ER policy interaction has encouraged firms to further reduce their emissions. This policy mix mainly exerts an abatement effect on firms by increasing green factors at the input–output stage and improving production efficiency. Furthermore, the digitalization effect of BC reduces corporate carbon emissions. Our empirical results are stronger for firms with high financial constraints, non-heavily polluting firms, non-high-technology firms, state-owned enterprises, and developed urban agglomerations. Furthermore, BC significantly suppresses the sectoral and spatial spillover effects of corporate carbon emissions, and external shocks to ER exacerbate this suppression effect. This study provides empirical evidence supporting the “tripartite win–win” of digital construction, green transformation, and energy conservation.

Research on Developing Cyclone Coupling Techniques for Heterogeneous Separators with Design Optimization of Hydrocyclone Separators

Abstract: Hydrocyclone separator is a widely used equipment in the field of liquid-solid separation due to its simple structure, convenient operation, and high separation efficiency. This paper provides a comprehensive review of the working principles, application areas, design optimization, and performance evaluation of hydrocyclone separators, while discussing their future development trends. In addition, particular attention has been given to the aspects related to patents in this study.The focus is on analyzing the structural parameters and flow field characteristics of hydrocyclone separators, as well as the different effects on separation efficiency caused by various hydrocyclone structures and adjustments in hydrocyclone size. The research analysis is conducted on the inlet, cylindrical section, overflow pipe section, cone section, hydrocyclone materials, and other parts, taking into account detailed analysis of operational conditions such as inlet flow rate, pressure drop, separation efficiency, and fluid properties. The future development trend of hydraulic hydrocyclone separators lies in refinement, intelligence, multifunctionality, integration, and energy-saving and environmental protection. In the field of liquid-solid separation, the integration of hydrocyclone separation technology and intelligent devices is becoming increasingly important, and future research will focus on developing new hydrocyclone coupling separation techniques to further improve production efficiency and convenience in daily life. The application prospects are broad, and it is expected to bring significant economic and social benefits to society. It also possesses the potential for patent protection.

Bayesian Evaluation of Growth Rates and Kleiber's Ratios in Harnali Sheep: Dissecting Maternal and Additive Genetic Contributions.

Understanding the genetic basis of growth and metabolic traits in sheep is crucial for improving production efficiency and sustainability. The current study aimed to estimate the genetic influences, both direct and maternal, on growth rate and Kleiber's ratio traits in Harnali sheep using pedigree data under Bayesian inference. The data pertained to 2404 animals spanned over 24 years (1998-2021). Fixed factors such as birth period, lamb sex and dam's weight at lambing were considered. The traits studied included average daily gains (ADGs) categorised into ADG1 (birth to weaning age), ADG2 (weaning to 6 months of age) and ADG3 (6-12 months of age), as well as corresponding Kleiber's ratios (KR1, KR2 and KR3). Six single-trait animal models were employed to estimate covariance components and heritabilities, integrating direct additive and maternal effects alongside significant fixed factors using THRGIBBS1F90 and POSTGIBBSF90 programmes. Direct heritability estimates were obtained for ADG1 (0.11 ± 0.05), ADG2 (0.06 ± 0.03), ADG3 (0.03 ± 0.03), KR1 (0.07 ± 0.03), KR2 (0.06 ± 0.03) and KR3 (0.05 ± 0.03). Maternal genetic effects have contributed significant particularly to pre-weaning traits. The study identified an antagonistic relationship between direct additive and maternal genetic effects. Positive genetic and phenotypic correlations emphasised the intricate relationship between growth and metabolic efficiency in Harnali sheep. The current study offers critical insights into the genetic basis of growth and metabolic traits in Harnali sheep, ultimately contributing to more efficient and sustainable sheep production systems.

Application of Biofloc Techznology as an Environmentally Friendly Solution to Increase the Productivity of Freshwater Fish Cultivation

This study explores the application of Biofloc Technology (BFT) as an environmentally friendly solution to increase the productivity of freshwater fish cultivation. Using a qualitative research approach based on a comprehensive literature review and library research, the paper examines the effectiveness of Biofloc in improving water quality, reducing feed costs, and enhancing fish growth rates. BFT promotes the growth of beneficial microbial communities that convert organic waste into protein-rich bioflocs, which serve as a supplementary feed for fish. This technology minimizes water exchange, conserves resources, and mitigates environmental pollution in aquaculture systems. The study highlights various successful implementations of Biofloc in freshwater aquaculture, noting significant improvements in production efficiency and sustainability compared to traditional farming methods. Moreover, the paper discusses the economic and environmental benefits of adopting Biofloc Technology, including reduced dependency on high-cost commercial feed and lower environmental impact due to decreased water usage and waste output. The findings suggest that Biofloc Technology is a promising innovation for sustainable aquaculture, providing both ecological and economic advantages. This research provides insights for policymakers, fish farmers, and aquaculture industry stakeholders interested in adopting eco-friendly practices to enhance productivity while protecting aquatic ecosystems

The Economic Impact of Successful Businesspeople: The Dual Effect of Wealth Creation and Spending

This article explores the complex impact of successful businesspeople on others and society through wealth creation and spending in their economic lives. The article begins by defining the concept of a “successful businesspeople” and points out its diversity in different historical and political contexts. Then, from an economic perspective, this paper analyzes how successful businesspeople can positively impact society by promoting economic growth, improving production efficiency, creating jobs, and donating to philanthropy in their different roles as investors, producers, consumers, donors, and employers. However, the article also points out the negative externalities that can be brought about by successful businesspeople, such as environmental damage, labor problems, data privacy violations, and public health risks. By citing historical and modern examples, such as Andrew · Carnegie, Henry · Ford, Jeff · Bezos, and Elon · Musk, this article further elaborates on how the economic behavior of successful businessmen has both positive and negative effects, and emphasizes the importance of understanding these complex relationships.