Manufacturing Production Research Articles

CRISPR/Cas9-Engineering for Increased Amylolytic Potential of Microbes for Sustainable Wastewater Treatment: A Review.

Amylases are pivotal enzymes with extensive industrial applications, including food processing, textile manufacturing, pharmaceuticals, and biofuel production. Traditional methods for enhancing amylase production in microbial strains often lack precision and efficiency. The advent of CRISPR/Cas9 technology has revolutionized genetic engineering, offering precise and targeted modifications to microbial genomes. This review explores the potential of CRISPR/Cas9 for improving amylase production, highlighting its advantages over conventional methods. This review discusses the mechanism of CRISPR/Cas9, the identification and targeting of key genes involved in amylase synthesis and regulation, and the optimization of expression systems. Additionally, current review examines case studies demonstrating successful CRISPR/Cas9 applications in various microbial hosts. The review also delves into the integration of CRISPR/Cas9 in wastewater treatment, where genetically engineered amylolytic strains enhance the degradation of complex organic pollutants. Despite the promising prospects, challenges such as off-target effects and regulatory considerations remain. This review provides a comprehensive overview of the current advancements, challenges, and future directions in the application of CRISPR/Cas9 technology for amylase production and environmental biotechnology.

Closed-loop supply chain decision making considering product design strategy under patent protection

This paper combines product design and patent protection and construct a dynamic decision-making model consisting of a single original manufacturer and a single remanufacturer based on Stackelberg game. We study the impact of different product design strategies on remanufacturing decisions in the presence of patent protection and explore the influencing factors of the original manufacturer's product design level. The results show that: (1) the original manufacturer’s product design level is negatively correlated with the coefficient of R&D cost impact and the coefficient of remanufacturing cost, and positively correlated with the coefficient of consumer utility impact; (2) the unit patent licensing fee is positively correlated with the coefficient of R&D cost impact and negatively correlated with the coefficient of remanufacturing cost and the coefficient of consumer utility impact; (3) under different product design strategies, product design strategies that consider both eco-orientation and remanufacturing-orientation are most conducive to the stable development of the closed-loop supply chain.

Green Transformation of Industrial Structure of Jiaxing City Driven by Synergizing the Reduction of Pollution and Carbon Emissions

The "Implementation Plan for Reduction of Pollution and Carbon Emissions" emphasizes the need to explore mechanisms for pollution and carbon emission reductions, strengthen efforts for synergistic reduction, and accelerate the green and low-carbon development in different types of cities. Thus, this study established a multi-objective optimization model for the industrial structure of the city based on green total factor productivity （GTFP）, which was applied to Jiaxing, an emerging coastal city. The results indicated an overall 8% increase in GTFP across various industries in Jiaxing from 2016 to 2019. The top three economic sectors - chemical products； electricity and thermal production and supply； and communication equipment, computers, and other electronic devices-ranked 12th, 15th, and 5th in GTFP, respectively. Conversely, industries with the top three GTFP rankings-other manufacturing products, specialized equipment, food, and tobacco-ranked 19th, 12th, and 14th in GDP, respectively. Given the mismatch between economic output and environmental benefits among different industries, deepening industrial structure adjustment and promoting synergistic pollution reduction and carbon reduction are imperative. The chemical industry （decreasing by 2%） and the electricity and thermal production and supply industry （decreasing by 1%） crucially need industrial transformation. This can be achieved by setting higher environmental thresholds, reducing the growth rate of fixed asset investment, and curbing the final consumption of these industries to enhance the efficiency of existing facilities. Meanwhile, the service industry （increasing by 5%） should be rapidly developed, while other industries can continue to grow at their current pace. The city-level industrial structure optimization model established in this study can effectively support future decision-making for the dual control of total carbon emissions and intensity, foster new-quality productivity, and promote carbon peaking and green low-carbon high-quality development in different cities.

The impacts of artificial intelligence literacy, green absorptive capacity, and green information system on green innovation

AbstractIn the contemporary digital landscape, the focus of manufacturing companies on green innovation has garnered attention in the business and academic realms. Nonetheless, the existing research system for manufacturers lacks a systematic study on how artificial intelligence literacy may bolster green innovation efforts. This study endeavors to construct a theoretical framework for artificial intelligence literacy, green information system, green absorptive capacity, and green innovation with respect to the dynamic capability theory and conducting empirical analysis utilizing survey data obtained from 288 ISO14001 manufacturing firms in Malaysia. The findings revealed that artificial intelligence literacy is a significant determinator of green absorptive capacity, the positive outcome of green absorptive capacity is green innovation, and the positive link between artificial intelligence literacy and green absorptive capacity is moderated by green information system. However, artificial intelligence literacy didn't exhibit a direct relationship with green innovation, even when considering green absorptive capacity as a mediator. These results not only offer compelling insights into the link between artificial intelligence literacy and green innovation, but also hold significant implications for academic research and policymaking concerning sustainable development and cleaner manufacturing production.

A fine-scale atlas reveals the systematic imbalance between carbon emissions and economic benefits along value chain within China

In efforts to achieve the aspiring carbon mitigation goals, China is actively seeking to reconcile the economic development and carbon reduction with diverse regional conditions. Here, we firstly integrated a national-wide atlas on the labor division of production, and decomposed value added and carbon emission along China's domestic value chain during 2007–2017. We found that the value chain roles lead to a systematic imbalance between value added and carbon emissions across regions. Over 70 % of sufferers of the inequality were located at the north, most of which were in the upstream position to supply resource and energy intermediate products of higher on-site emissions and relatively less value added in comparison to the downstream manufacturing and service products production at the coastal regions. As a result, the northern inland suffered a great deal while part of coastal regions and southern inland were beneficiaries in the participation in domestic value chain. In particular, several regions inevitably undertake industries with higher emission intensity and less gains in a sound domestic industrial chain. These strongly call for a systematically policy- or price-based mechanism to explore fair strategy for emission reduction.

TECHNOLOGY OF QUALITY CONTROL OF ADDITIVE MANUFACTURING PRODUCTS DURING PRINTING OF ELEMENTS OF ENERGY COMPLEXES

Additive manufacturing significantly impacts the energy sector through its ability to form complex geometries and optimize designs, enhancing the performance and reliability of energy systems and complexes. This type of manufacturing allows the creation of optimized parts considering energy efficiency and durability requirements, for example, heat exchangers can be designed and manufactured with a unique structure to improve their efficiency, and new energy devices and systems can be quickly prototyped for testing and optimization before mass production. The use of additive manufacturing can make parts production for energy complexes more localized and flexible, which is particularly beneficial when creating small and medium-sized energy systems. The paper discusses technologies for quality control of additive manufacturing products in the process of printing elements of energy complexes. Describes the state-of-the-art methods and controls used to ensure the high quality of 3D printed parts required for efficient operation of energy systems. Various aspects of inspection are covered, including printing process monitoring, flaw detection, material structure analysis, and geometric inspection. Examples are given of the use of various quality control methods in the context of the production of elements for energy complexes, making the article relevant for specialists in the field of additive manufacturing and energy. An analysis of existing printing technologies was carried out, and the advantages and disadvantages of each technology that is used in the process of serial production of additive manufacturing products for elements of power plants and complexes were highlighted. Keywords: technologies ofadditive manufacturing, additive manufacturing quality control software,artificial intelligence, energy complexes.

Digital twin-driven virtual commissioning for robotic machining enhanced by machine learning

Robotic machining has been increasingly applied in intelligent manufacturing production lines. Compared with the traditional machine tools, commissioning for robotic machining system (RMS) is particularly important due to the low accuracy of industrial robots (IRs). Traditional site commissioning has large workload and is difficult to handle the multi-source errors. Since digital twin (DT) provides strategies for staying synchronized with the physical entities in whole lifecycle, a DT-driven virtual commissioning (VC) system for RMS is developed in this study to improve machining accuracy and reduce the difficulty of commissioning. Firstly, the framework of DT-driven VC system is designed including several function modules such as interaction, data pre-processing, DT model of RMS (RMSDT), and optimization service. Since RMSDT is the kernel of precise VC, a machine learning-enhanced RMSDT oriented to actual machining path prediction is then constructed based on a proposed joint error equivalent strategy, which can fully consider the coupled multi-source errors of machining robot. After that, a practical consistency retention method for RMSDT is proposed based on a stepwise updating strategy, where the model performance can be maintained with low updating costs. Finally, a visual VC system is developed for the experimental 6-degree of freedom robotic milling platform to verify the feasibility and effectiveness of the VC framework. Multiple experiments are also performed to test the performance of RMSDT and contour error compensation. This study has useful reference for the enterprises engaged in RMS and has positive significance for promoting the robotic machining.

AUDIT AND QUALITY CONTROL OF FOOD PRODUCTS IN EU COUNTRIES AND THE WORLD

The article examines regulatory legal acts and other documents and literary sources regarding state control of food safety and quality in Great Britain, Germany, France, the USA and Japan. The health of every nation largely depends on the quality and safety of food products. In any country, at the state level, requirements for product safety and quality are regulated and their compliance is ensured. One of the methods of such provision is state control. The article analyzes the practices of controlling the quality and safety of food products in the USA, Germany, France, Great Britain and Japan. It was revealed that there are both common and special rules in the practice of controlling the quality and safety of food products in the studied countries. In all countries, control over the quality and safety of food products is carried out by state bodies. In all countries, during control, special attention is paid to the reliability of product labeling. Improper labeling entails banning the sale of products, removal from circulation or destruction of particularly dangerous products, and even criminal liability in France and the USA. The main responsibility for dangerous food products in all countries is borne by the manufacturers or suppliers of the products who put them into circulation. In the USA and Japan, information about the presence of allergens in a food product must be included in the labeling. In the USA, in order for the manufacturer's products to be able to be supplied for a government order, the enterprise must implement a quality management system in accordance with the requirements of ISO 9001, and in Japan, in order to obtain a permit for the manufacture of food products, it is necessary to prove that proper sanitary and hygienic control is ensured by implementing HACCP system. In Germany, Great Britain, and Japan, quality and safety control is entrusted to local self-government bodies. In Germany, there is a product safety monitoring program throughout the territory, which makes it possible to monitor the appearance of dangerous products on the market, as well as to check the effectiveness of the established MPC of dangerous substances. The presence of "passports" for ready-made food products is checked only in France, although such a document is mandatory in EU countries. In France and Japan, exceptional importance is attached to the education of schoolchildren on food safety issues.

In-house green hydrogen production for steelmaking decarbonization using steel slag as thermal energy storage material: A life cycle assessment

Steel production is a highly energy-intensive industry, responsible for significant greenhouse gas emissions. Electrification of this sector is challenging, making green hydrogen technology a promising alternative. This research performs a thermodynamic analysis of green hydrogen production for steel manufacturing using the direct reduction method. Four solid oxide electrolyzer (SOE) modules replace the traditional reformer to produce 2.88 kg/s of hydrogen gas, serving as a reducing agent for iron pellets to yield 30 kg/s of molten steel. These modules are powered by 37,801 photovoltaic units. Additionally, a thermal storage system utilizing 1342 tons of steel slag stores waste heat from Electric Arc Furnace (EAF) exhaust gases. This stored energy preheats iron scraps charged into the EAF, reducing energy consumption by 5 %. A life cycle assessment, conducted using open LCA software, reveals that the global warming potential (GWP) for the entire process, with a capacity of 30 kg/s, equates to 93 kg of CO2. The study also assesses other environmental impacts such as acidification potential, ozone formation, fine particle formation, and human toxicity. Results indicate that the EAF significantly contributes to global warming and fine particle formation, while the direct reduction process notably impacts ozone formation and acidification potential.

Joint optimization of preventive maintenance and product quality improvement policies for deteriorating manufacturing systems with quality-reliability dependency

Machine reliability and product quality are usually investigated independently in most traditional models. However, in the actual manufacturing process, machine reliability and product quality are commonly interdependent due to strong coupling between the machine and the product. In this paper, three joint optimization models for preventive maintenance (PM) and product quality improvement are developed for deteriorating manufacturing systems considering quality-reliability dependency. First, the degradation process of quality-related components (QRCs) is depicted by Gamma process, and product quality deviation is obtained by considering the quantitative relationship between the degradation of QRCs and product quality. Second, joint optimization policy of age-based maintenance and product quality improvement is proposed for deteriorating manufacturing systems with quality-reliability dependency. Third, above maintenance policy is extended to manufacturing systems processing jobs with random processing time, and then maintenance first (MF) and maintenance last (ML) policies are developed, respectively. Furthermore, we compare all of the maintenance models to determine which policy should be selected for manufacturing systems under specific conditions, and all theoretical discussions in this paper are analytically made. Finally, the effectiveness of the proposed joint policies is verified by a case study on a cylindrical gear housing machining process.

Zero Thermal Expansion via the Unconventional Sublattice‐Magnetovolume Effect in Rare‐Earth Ferrimagnets

AbstractZero thermal expansion (ZTE) alloys are critically needed in sophisticated modern industries, including telescope manufacturing, satellite technology, and semiconductor production, owing to their exceptional dimensional stability. In this study, high‐performance ZTE with a negligible coefficient of thermal expansion αv = 2.7 ppm K−1 over a broad temperature range of 10–220 K is discovered in ErCo2.8Fe0.2 magnet. Owing to an unconventional sublattice‐magnetovolume effect in the Er atoms, the negative thermal expansion in Fe‐substituted ErCo3−xFex magnets can be easily tuned to high‐performance ZTE. Moreover, the direct visualization of the magnetic transition in the predominant magnetization from the Er to the Co/Fe sublattices, as observed by the Lorentz transmission electron microscopy, further elucidates the manipulation mechanism behind the high‐performance ZTE. This study reports a convenient and effective strategy to optimize the thermal expansion characteristics of Er‐Co‐Fe magnets, which can guide future research that broadens the application scope of magnetic materials by leveraging the significant correlation between the magnetic properties and crystal structure of such systems.

State of the Art and Challenges in Complete Benzene Oxidation: A Review.

Increased levels and detrimental effects of volatile organic compounds (VOCs) on air quality and human health have become an important issue in the environmental field. Benzene is classified as one of the most hazardous air pollutants among non-halogenated aromatic hydrocarbons with toxic, carcinogenic, and mutagenic effects. Various technologies have been applied to decrease harmful emissions from various sources such as petrochemistry, steel manufacturing, organic chemical, paint, adhesive, and pharmaceutical production, vehicle exhausts, etc. Catalytic oxidation to CO2 and water is an attractive approach to VOC removal due to high efficiency, low energy consumption, and the absence of secondary pollution. However, catalytic oxidation of the benzene molecule is a great challenge because of the extraordinary stability of its six-membered ring structure. Developing highly efficient catalysts is of primary importance for effective elimination of benzene at low temperatures. This review aims to summarize and discuss some recent advances in catalyst composition and preparation strategies. Advantages and disadvantages of using noble metal-based catalysts and transition metal oxide-based catalysts are addressed. Effects of some crucial factors such as catalyst support nature, metal particle size, electronic state of active metal, redox properties, reactivity of lattice oxygen and surface adsorbed oxygen on benzene removal are explored. Thorough elucidation of reaction mechanisms in benzene oxidation is a prerequisite to develop efficient catalysts. Benzene oxidation mechanisms are analyzed based on in situ catalyst characterization, reaction kinetics, and theoretical simulation calculations. Considering the role of oxygen vacancies in improving catalytic performance, attention is given to oxygen defect engineering. Catalyst deactivation due to coexistence of water vapor and other pollutants, e.g., sulfur compounds, is discussed. Future research directions for rational design of catalysts for complete benzene oxidation are provided.

Perspectivas Económicas: Un Análisis de la Trayectoria de la Industria Farmacéutica en España

Introduction: The pharmaceutical industry plays a key role in the economy, contributing to GDP and creating stable, high-quality jobs. Its primary functions include researching, developing, and manufacturing products for the treatment and prevention of diseases. The industry's role was critical in mitigating the pandemic's impact on the country. Methodology: The study employed financial statement analysis, including horizontal analysis and profitability evaluation. Data from the SABI database, which contains economic and financial information on Spanish companies classified by their CNAE codes, was used. The analysis began with a sector-wide examination of operating income and R&D expenses, later narrowing the sample to leading companies based on key parameters. Results: The findings confirm consistent growth in operating income and R&D expenses, with peak figures during the COVID-19 pandemic. Companies like Bayer stood out for significant investments in R&D and assets, reflecting their strong industry presence. Conclusions: The pandemic positively impacted the pharmaceutical sector, providing a unique opportunity to showcase its importance to the country's economy and well-being. This period highlighted the industry's capacity for growth and its critical role in addressing public health challenges.

Therapeutic drug monitoring of elexacaftor, tezacaftor, and ivacaftor before, during, and after pregnancy in women with cystic fibrosis: An observational study

BackgroundElexacaftor/tezacaftor/ivacaftor (ETI) has improved health and increased life expectancy in many patients with cystic fibrosis (pwCF). Family planning issues have become more important since then. Many women decide to remain on modulator therapy during pregnancy despite insufficient evidence-based recommendations for continuing ETI during pregnancy and lactation. MethodsIn this retrospective observational report, we present data on maternal serum concentrations of ETI, assessed via a therapeutic drug monitoring (TDM) program established at our CF center for adults. Blood was taken during routine visits. We retrospectively analyzed the corresponding predicted forced expiratory volume in 1 s (ppFEV1), at five time points before, during, and after pregnancy. ResultsOf seven ETI-exposed pregnancies in six women between February 2021 and September 2023, the intake of ETI resulted in no maternal complications and healthy offspring. The dose was reduced in all women, 71.4 % before and 28.6 % during pregnancy, primarily as a result of side effects and/or increased ETI concentrations. Despite dose reductions, serum concentrations showed a broad distribution, with values below, within, and above the Cmax range according to the pharmacokinetic data in the manufacturer's product characteristics. Pulmonary function largely remained stable without pulmonary exacerbations requiring intravenous antibiotic treatment. ConclusionThis observational report shows the most extensive dataset for ETI concentrations during pregnancy. Individualized dose adjustments could help to resolve adverse side effects while continuing CFTR therapy. Specific populations, such as pregnant women, might benefit from a TDM. However, future research with more pharmacokinetic data from pregnant pwCF is needed.

Revealing mechanisms of processing defect mitigation in laser powder bed fusion via shaped beams using high-speed X-ray imaging

The laser powder bed fusion (LPBF) process utilizing a focused Gaussian-shaped beam faces challenges, including pore formation, melt pool fluctuation and liquid spattering. While beam shaping technology has been explored as a potential approach for defect mitigation, the beam-matter interaction dynamics during melting with shaped beams remain unclear. Here, we report the direct observation of ring-shaped beam-matter interaction dynamics, including pore formation, melt pool fluctuation and liquid spattering, and unveil defect mitigation mechanisms in ring-shaped beam laser powder bed fusion process. We find that, by spatially manipulating incident laser rays, the ring-shaped beam controls keyhole morphology, thereby managing the distribution of the reflected rays. This manipulation can effectively eliminate the formation of an unstable cavity at the keyhole tip, stabilizing the keyhole and mitigating keyhole pores. This enhanced keyhole stability effectively reduces the melt pool fluctuation, the formation of liquid breakup induced spatters and liquid droplet colliding induced large spatters in the laser powder bed fusion process. Additionally, the high-energy forefront of the ring-shaped beam effectively melts the powder bed, reducing agglomeration liquid spatter in the laser powder bed fusion process. The discovered defect mitigation mechanisms may guide the design of beam shaping strategies for simultaneously increasing the quality and productivity of metal additive manufacturing.

An OLED display fabricated through side‐by‐side pixel patterning via photolithography

AbstractWe developed a patterning technology using photolithography that eliminates the need for a fine metal mask, thereby achieving high resolution across all red‐blue‐green pixels of an organic light‐emitting diode (OLED) display. Traditional methods using fine metal masks typically restrict the resolution and size of a display. However, the proposed technology largely bypasses these constraints. Suitable for OLED applications ranging from microdisplays in augmented reality and virtual reality to large TVs exceeding 80 in., our technology overcomes limitations on alignment accuracy, fine metal mask washing, and running costs and paves the way for mass production in OLED manufacturing.

When Guests Become Hosts: The Boomerang Effect of Tourists’ Negative Behaviors on Their Country of Origin

Tourists are commonly regarded as ambassadors shaping their country’s image in international tourism. However, the role of the boomerang effect for outbound tourists on their country of origin is often overlooked in theory and practice. Through four studies, this groundbreaking research explores the boomerang effect of tourists’ negative behaviors on their home countries, encompassing the impact on tourism imports and subsequent spillover effects on manufacturing product exports. The findings reveal that tourists’ negative behaviors not only diminish the willingness of destination residents to visit the tourist-originating country by influencing perceived warmth and psychological distance but also decrease their intention to purchase manufactured products from the country of origin by amplifying psychological distance. Importantly, the moderating effect of product added value in spillover effects is highlighted. These conclusions expand the influence of tourists’ negative behaviors and innovatively bridge theoretical perspectives between the tourism and manufacturing industries on the reverse country-of-origin effects.

Enhancing end-of-life product recyclability through modular design and social engineering optimiser

Amidst the thriving landscape of manufacturing, the vision of sustainability in Industry 5.0 is becoming increasingly significant. The implementation of recycling represents a crucial step in the pursuit of sustainability, particularly in light of the mounting challenge posed by the proliferation of end-of-life (EOL) products. Addressing this challenge, we propose a novel Design for Modular Recyclability (DFMR) approach aimed at facilitating the recycling of EOL products. Our study develops a multi-objective optimisation model with a focus on maximising green recyclability and independence while minimising aggregation. We introduce an innovative Social Engineering Optimiser (SEO) to simulate behavioural patterns in complex environments, aiding in identifying and implementing effective strategies for optimal or near-optimal results in diverse scenarios. The practical effectiveness of the proposed models and algorithms is demonstrated by applying them to a real-life case study in an internal combustion engine, followed by performance comparisons with existing well-established multi-objective optimisation algorithms. The findings of our study demonstrate the efficacy of the proposed DFMR model, offering a novel approach for decision-makers to undertake EOL product recovery. This contributes to the further exploration of complex and promising paths towards sustainable manufacturing and green production that are more in line with Industry 5.0.

Implementing intelligent manufacturing policies to increase the total factor productivity in manufacturing: Transmission mechanisms through construction of industrial chains

In recent years, the Chinese government has focused on implementing intelligent manufacturing policies to improve the total factor productivity of the manufacturing industry. Using a sample of listed manufacturing companies from 2010 to 2022, we examined the long-term economic effects of government intelligent manufacturing policy incentives on the total factor productivity of the manufacturing industry. We systematically explored its transmission mechanism in the construction of industrial chains. The study found that the implementation of intelligent manufacturing policies significantly improved the level of total factor productivity in the manufacturing industry. Mechanism analysis found that intelligent manufacturing policies promoted the construction of the manufacturing industry chain through three paths: optimizing industrial chain integration, enhancing industrial chain spillover, and strengthening industrial chain resilience, thereby promoting the improvement of total factor productivity. Further analysis found significant differences in the implementation effects of different policy types and technology requirements.

Enhancing and Explaining Energy Management in Smart Manufacturing Production via ML Within the Context of Industry 4.0

Objective: The aim of this research is to identify the main barriers faced by managers and practitioners in the implementation of KM initiatives in the context of Chilean organisations and to describe the ways in which these problems are addressed by them. Theoretical Framework: This research addresses the organisational, political, social and cultural barriers faced by KM initiatives in developing country contexts. Method: This study was based on the review of twenty-six cases of knowledge management initiatives implemented between 2010 and 2022 in Chile, which were described and analysed using qualitative methodology Results and Discussion: It was found that the most important barriers to carrying out these initiatives coincide, to a large extent, with some of the characteristics of Chilean culture and society described in the literature of organisational studies, such as: lack of trust; large power distance in the organisational structure; lack of communication skills; paternalistic organisational culture, to mention a few. Also, one aspect worth highlighting is the traditional business culture that tends to focus on a "low cost" strategy and exploitation of raw materials, rather than investing in innovation. Scarce resources, problematic performance measurement and lack of knowledge management training for employees and managers were also mentioned as adverse factors. Research Implications: The relevance of this study lies in the fact that it provides insight into the main barriers faced by knowledge management initiatives in developing countries, specifically in a region such as Latin America, thus contributing to the development of this field in this region. Originality/Value: It is known that many of the new initiatives in the field of KM do not thrive or face difficult start-up challenges, limiting the number of successful initiatives in this country. This study contributes to a better understanding of the problems faced by managers carrying out KM initiatives, thus enabling them to develop better strategies and solutions for the implementation of KM projects.