Industrial Problems Research Articles

Development and assessment of an integrated wind energy system for green steelmaking based on electric arc furnace route

Optimizing energy structure is important for coping with the increasing environmental problems in iron and steel industry. Wind energy is one of typical zero-carbon, inexhaustible, and accessible energy source for alleviating energy dilemma. In this paper, the electric arc furnace steelmaking processes integrated with wind energy system (EAF-WES) is developed. The input-output data of 1214 and 1536 heats with 30 % and 50 % hot metal ratio are traced and collected. Life cycle assessment and techno-economic analysis of EAF route integrated with traditional energy system (EAF-TES) and EAF-WES are further researched and compared from perspectives of life cycle carbon footprint (LCCF), production cost, wind energy price (WEP), carbon efficiency, carbon reduction benefit (CRB), and carbon tax. The results indicate that EAF-WES enjoys lower LCCF but higher production cost and carbon efficiency than EAF-TES. Considering the price fluctuations, the optimal EAF steelmaking pattern with lowest production cost under different extent of WEP and carbon tax is suggested. When the electricity price is 0.043 and 0.046 $/kWh, the CRB is balanced. It is concluded that EAF-WES is a low-carbon, high-productive, environmentally friendly, and economical route. This research is expected to supply a technical idea for energy conservation and emission reduction in future steel production.

Development of a Waste Management Strategy in a Steel Company

The management of waste, especially ferrous waste, poses great problems in the steel industry due to strict regulations on preventing, reducing, or even eliminating the factors that generate a high degree of environmental pollution (landfills resulting from the steel industry and adjacent industries—mining, energy, etc.). The present paper presents a synthesis of the specialized literature regarding the processes used, both worldwide and nationally, regarding the transformation of raw materials (ores or concentrates) and iron-containing waste (steel mill dust, mill scale and scale, sludge from agglomeration factories, sideritic waste, etc.) into by-products that can be used in the steel industry. For technological reasons, the option of pelletizing powdered waste was applied—in laboratory conditions, according to its own recipes, with results that justify the application of the technology on an industrial scale (appearance after hardening; drop resistance). The aim of the paper was to identify a practical solution; based on this solution, original conceptual models of organizational strategies (management and processing, respectively, recovery of ferrous waste within steel companies) were developed, such as a concentration strategy, diversification, vertical integration, etc. Within graphical representations of the proposed strategies, other processing variants were mentioned: agglomeration; briquetting.

Comparison of various drying methods on color, texture, nutritional components, and antioxidant activity of tumorous stem mustard

Exploring new dehydration technology can help to deal with the challenge of quality preservation and high salt waste brine problem in pickled mustard industry. In the current study, effects of vacuum freeze-drying (FD), heat pump drying (HPD), air-impingement jet drying (AIJD), and hot air drying (HD), on color, texture, nutritional component, and antioxidant capacity of tumorous stem mustard were determined. All drying methods significantly affected color and texture. The ascorbic acid (Vc), reducing sugar, protein, total phenolic content (TPC), ABTS, DPPH, and FRAP level of tumorous stem mustard were 123.20–768.74 mg/100 g, 2.49–17.90 g/100 g, 30.74–53.03 g/100 g, 1.98–4.13 mg gallic acid equivalent (GAE)/g, 1.42–8.28 mg Vc/g, 1.04–9.73 mg Vc/g, and 2.11–6.83 mg Vc/g, respectively. The content of individual phenolics were influenced by drying methods, and ferulic acid was determined as a major phenolic compound for all samples (8.15–65.43 μg/g). The content of total phenolic and monomeric polyphenols except for ferulic acid, positively correlated to their antioxidant activity. Furthermore, HD, FD, and AIJD were beneficial to promote the production of umami amino acids and reduce bitter amino acids, thus improving the flavor of tumorous stem mustard. The quality of tumorous stem mustard of FD was closest to that of fresh tumorous stem mustard. Overall, the drying technology is promising to replace the salt infiltration process to realize the dehydration of tumorous stem mustard in the manufacturing of pickled mustard.

Synthesis of rice husk ash based alkaline activators for geopolymer binder systems: A review

At present, geopolymer binders have been considered to be one of the most promising low-carbon building materials. Apart from low carbon emissions, the production of geopolymer materials also helps in mitigating several industrial solid waste management problems. The geopolymer binder can be produced using any aluminosilicate waste material followed by mixing with an alkaline activator. However, the major limitation associated with geopolymers is their production cost which is slightly higher than traditional cement-based binders. Out of all the ingredients, sodium silicate is found to be the most expensive and least environment friendly material. Several researchers have therefore utilized many silica-rich waste products such as rice husk ash (RHA) based silicate solution as a low-cost alternative to commercial sodium silicate solution. In this regard, this paper provides an in-depth review of the past literature to understand the properties of geopolymer binders produced using RHA-derived alkaline activator. The production process, and the factors affecting dissolution of RHA have been elaborated. Further, the properties such as compressive strength, and microstructure have been detailed. Lastly, the sustainability and lifecycle assessment of geopolymers synthesized using RHA-based sodium silicate solution are presented. The information provided in this study shall encourage the scientific community to adopt RHA-based sodium silicate as a cost-effective, and environment friendly activator to produce geopolymers.

New energy vehicle technology research - Charging technology

In recent years, Chinas economic development is becoming more and more rapid, leading to the increasingly serious pollution emission problem of traditional fuel vehicles. In order to solve the environmental problems, the transformation of automobiles has become an urgent problem. At the present stage, electric vehicles are also widely concerned by all sectors of society because of their low carbon emissions, energy saving and low use cost. With the rapid growth of electric vehicle sales, the demand for charging piles is rising, and the mainstream charging facilities for new energy vehicles are still in short supply. Therefore, we need to focus on efficient wireless charging to solve the major problems in the current electric vehicle industry. This paper analyzes the wireless dynamic energy transmission technology, extending the service life of the battery, how to reduce the cost, the optimization of coil parameters design, the offset of transmission coil and receiving coil, foreign body detection and overheating problems.

Characterization of camphor: thymol or dl-menthol eutectic mixtures; Structure, thermophysical properties, and lidocaine solubility

The low solubility of drugs in aqueous media is a major problem for the pharmaceutical industry. Among the solutions proposed, the use of eutectic mixtures can be highlighted. In them, the components used can also increase the therapeutic advantages of the active principle. In this work, we analyzed the solubility of lidocaine in mixtures of camphor + thymol or dl-menthol. These binary eutectic solvents were also characterized. For all this, several NMR techniques were used and different thermophysical properties (density, speed of sound, refraction index, isobaric molar heat capacity, surface tension, and kinematic viscosity) were measured. The results indicated that the interaction of camphor with thymol was stronger than with dl-menthol, providing a more compact fluid. On the contrary, the steric hindrance was greater in the mixture with dl-menthol, giving rise to a more viscous liquid. Furthermore, the lidocaine was significantly more soluble (up to 540 times) in these mixtures than in water. The lidocaine showed the strongest interactions with thymol molecules, somewhat weaker with dl-menthol, and the weakest were with camphor ones.

Combinatorial optimization methods for yarn dyeing planning

AbstractManaging yarn dyeing processes is one of the most challenging problems in the textile industry due to its computational complexity. This process combines characteristics of multidimensional knapsack, bin packing, and unrelated parallel machine scheduling problems. Multiple customer orders need to be combined as batches and assigned to different shifts of a limited number of machines. However, several practical factors such as physical attributes of customer orders, dyeing machine eligibility conditions like flotte, color type, chemical recipe, and volume capacity of dye make this problem significantly unique. Furthermore, alongside its economic aspects, minimizing the waste of natural resources during the machine changeover and energy are sustainability concerns of the problem. The contradictory nature of these two makes the planning problem multi-objective, which adds another complexity for planners. Hence, in this paper, we first propose a novel mathematical model for this scientifically highly challenging yet very practical problem from the textile industry. Then we propose Adaptive Large Neighbourhood Search (ALNS) algorithms to solve industrial-size instances of the problem. Our computational results show that the proposed algorithm provides near-optimal solutions in very short computational times. This paper provides significant contributions to flexible manufacturing research, including a mixed-integer programming model for a novel industrial problem, providing an effective and efficient adaptive large neighborhood search algorithm for delivering high-quality solutions quickly, and addressing the inefficiencies of manual scheduling in textile companies; reducing a time-consuming planning task from hours to minutes.

A novel fuzzy scenario-based stochastic general best-worst method

The best-worst method (BWM) is a popular multi-criteria decision-making (MCDM) method known for the low number of pairwise comparisons and high consistency. General BWM (GBWM) is a new version of BWM that considers the interdependencies between interwind factors in MCDM problems. This study proposes a fuzzy stochastic GBWM for weighting intertwined factors using a scenario-based approach in complex intertwined or hierarchical networks under uncertainty. Fuzzy stochastic GBWM provides decision-makers with a wide range of weights, from fuzzy-stochastic weights to stochastic weights (defuzzified weights), fuzzy weights, and deterministic weights to use with different assumptions in the decision-making process. We demonstrate the efficacy and applicability of the proposed method with a well-known car-buying problem in the literature and a real-world problem in the transportation industry.

Application of Three-Dimensional Porous Aerogel as Adsorbent for Removal of Textile Dyes from Water

The textile industry is one of the most important industries in the European Union. The main environmental problems of the textile industry are the high water consumption, the generated pollution, the variety of chemicals used and the high energy demand. Recently, adsorbents with a large specific surface area and low weight, such as aerogels, have attracted great interest as promising materials for removing dyes from polluted water. Cellulose aerogels are inexpensive and non-toxic. Langmuir and Freundlich isotherms were chosen as the best method to describe the performance of the adsorbent. In this study, the adsorption efficiency of Congo red, Naphthol green B, Rhodamine B and Methylene blue were determined by using an adsorbent synthesized from paper and cardboard waste. The total organic carbon concentration was chosen as an indicator of the concentration of the dyes in the solutions. The aerogel capsules had 5% cellulose content. It was found that the adsorption capacity of the aerogel in the solutions of Congo red varied from 0.028 mg/g to 14.483 mg/g; in the solutions of Naphthol green B, from 0.013 mg/g to 7.698 mg/g; in the solutions of Rhodamine B, from 0.020 mg/g to 8.768 mg/g; and in the solutions of Methylene blue, from 0.024 mg/g to 13.538 mg/g.

The Fungal Diversity and Potential Pathogens Associated with Postharvest Fruit Rot of 'Huangguan' Pear (Pyrus bretschneideri) in Hebei Province, China.

Postharvest fruit rot caused by pathogens is a serious problem in the pear industry. This study investigated the fungal diversity and main pathogens and identified a new pathogen in the stored 'Huangguan' pear (Pyrus bretschneideri Rehd.), the dominant pear variety in northern China. We sampled 20 refrigeration houses from five main producing regions in Hebei Province and used Illumina sequencing technology to detect the fungal composition. Alternaria (56.3%) was the most abundant fungus, followed by Penicillium (9.2%) and Monilinia (6.2%). We also isolated and identified nine strains of Alternaria and four strains of Penicillium. Moreover, we observed a new postharvest fruit disease in 'Huangguan' pear caused by Stemphylium eturmiunum, which was confirmed by phylogenetic analysis by combining the sequences of three conserved genes, including internal transcribed spacer, gapdh, and calmodulin. This study marks the first documentation of S. eturmiunum causing fruit rot in 'Huangguan' pears, offering valuable insights for identifying and controlling this newly identified postharvest disease.

Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems

Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems

Thermomechanical Pathways for Accurate Microstructural Control of Ti–7Ag Alloy: Towards a New Generation of Antibacterial Materials for Medical Applications

This study delved into exploring microstructural states in a Ti–7Ag alloy to achieve targeted functional and structural properties. Specifically, the focus was on attaining a homogeneously precipitated state and a solid solution, known for their potential to combine functional traits like corrosion resistance and antibacterial activity with structural properties such as mechanical strength. However, obtaining these optimized microstructures presents challenges due to kinetic considerations. A key finding of this study was the crucial role of a pre-deformation stage, prior to heat treatment, to create an even distribution of fine Ti2Ag precipitates. Moreover, we demonstrated that starting from this precipitated state, a controlled dissolution step could yield a single-phase solid solution with similar grain size. Therefore, a tailored set of thermomechanical treatments was developed to achieve both microstructures, and these metallurgical states were fully characterized combining SEM (BSE imaging and EDS analysis), TEM, and XRD. Associated mechanical properties were also assessed by tensile testing. In addition, the process was proven to be robust enough to overcome potential industrial problems, such as slow cooling rates when water-quenching large ingots. Considering the limited existing documentation on microstructural features in Ti–Ag alloys, this work on this model alloy significantly advanced our current understanding of the broader Ti–Ag alloy system by providing new data and showcasing a tailored approach involving thermomechanical treatments.

Election Optimizer Algorithm: A New Meta-Heuristic Optimization Algorithm for Solving Industrial Engineering Design Problems

This paper introduces the election optimization algorithm (EOA), a meta-heuristic approach for engineering optimization problems. Inspired by the democratic electoral system, focusing on the presidential election, EOA emulates the complete election process to optimize solutions. By simulating the presidential election, EOA introduces a novel position-tracking strategy that expands the scope of effectively solvable problems, surpassing conventional human-based algorithms, specifically, the political optimizer. EOA incorporates explicit behaviors observed during elections, including the party nomination and presidential election. During the party nomination, the search space is broadened to avoid local optima by integrating diverse strategies and suggestions from within the party. In the presidential election, adequate population diversity is maintained in later stages through further campaigning between elite candidates elected within the party. To establish a benchmark for comparison, EOA is rigorously assessed against several renowned and widely recognized algorithms in the field of optimization. EOA demonstrates superior performance in terms of average values and standard deviations across the twenty-three standard test functions and CEC2019. Through rigorous statistical analysis using the Wilcoxon rank-sum test at a significance level of 0.05, experimental results indicate that EOA consistently delivers high-quality solutions compared to the other benchmark algorithms. Moreover, the practical applicability of EOA is assessed by solving six complex engineering design problems, demonstrating its effectiveness in real-world scenarios.

Supramolecular-assisted nanocomposite coatings with sustainable and robust resistance to microbially mediated biofouling and corrosion

Surface-adhering biofilms contribute significantly to irreversible biofouling and corrosion, presenting a multi-trillion-dollar annual problem in public health and industry. Strategies employing antibacterial elements are emerging to fabricate multifunctional coatings that effectively combat such microbially produced damage. However, rapid, reliable, and robust surface engineering remains challenging due to stability limitations and intricate anti-biofilm additive dynamics. Herein, a silver-capsule-conjugated polyurethane coating with high stability and antimicrobial efficacy in a cooperative manner is developed through controlled supramolecular self-assembly. Polyvinylpyrrolidone (PVP)-mediated molecule entanglement breaks through the incompatibility between polymeric components and nanomaterials, strengthening the dispersion and fixation of encapsulated silver nanoparticles. The facilitation and control of the nanoscale interfacial binding significantly suppresses the aggregation of inorganic nanoparticles and consequent microcracks development, giving rise to mechanical robustness and thermal stability of the hybrid coating under extreme conditions. A synergistic combination of exposed residues, electrostatic, and coordination interactions could readily integrate the resultant coating on virtually arbitrary material surfaces. This composite coating exhibits broad-spectrum and high bactericidal efficiencies of 99.99 % against Staphylococcus aureus and Escherichia coli, as well as excellent biofilm formation suppression. Moreover, our coating has robust resistance to microbial-influenced corrosion (MIC) and can even endure 720 h of salt spray. This study deciphers a general code for creating stable and durable nanohybrid coatings to mitigate microbially related risks.

Technology impact: A study on the performance appraisal process in the IT industry

This study investigates the impact of technology on the performance appraisal process within the IT industry. Rapid advancements in technology have transformed traditional performance appraisal methods, and understanding the implications of these changes is crucial for organizations striving to optimize their performance management strategies. The use of technology for performance appraisals in the IT industry can introduce several problems that can negatively impact the evaluation process and employee morale. Automated systems may rely on irrelevant or incomplete metrics that do not capture important qualitative aspects of performance. These systems may be prone to errors, biases, and inaccuracies in data collection and interpretation. The findings of this study reveal the significant impact of technology on the performance appraisal process in the IT industry. There are potential solutions for mitigating performance appraisal problems in the IT industry. To ensure that performance appraisal systems are relevant and accurate, organizations can involve employees in the development of metrics and provide regular feedback. The integration of digital tools has enhanced the efficiency and accuracy of data collection, tracking, and analysis, leading to streamlined processes, reduced administrative burdens, and increased data reliability. Real-time communication channels have facilitated more frequent and timely feedback, fostering employee engagement and development.

Network-based visualisation of frequent sequences.

Frequent sequence pattern mining is an excellent tool to discover patterns in event chains. In complex systems, events from parallel processes are present, often without proper labelling. To identify the groups of events related to the subprocess, frequent sequential pattern mining can be applied. Since most algorithms provide too many frequent sequences that make it difficult to interpret the results, it is necessary to post-process the resulting frequent patterns. The available visualisation techniques do not allow easy access to multiple properties that support a faster and better understanding of the event scenarios. To answer this issue, our work proposes an intuitive and interactive solution to support this task, introducing three novel network-based sequence visualisation methods that can reduce the time of information processing from a cognitive perspective. The proposed visualisation methods offer a more information rich and easily understandable interpretation of sequential pattern mining results compared to the usual text-like outcome of pattern mining algorithms. The first uses the confidence values of the transitions to create a weighted network, while the second enriches the adjacency matrix based on the confidence values with similarities of the transitive nodes. The enriched matrix enables a similarity-based Multidimensional Scaling (MDS) projection of the sequences. The third method uses similarity measurement based on the overlap of the occurrences of the supporting events of the sequences. The applicability of the method is presented in an industrial alarm management problem and in the analysis of clickstreams of a website. The method was fully implemented in Python environment. The results show that the proposed methods are highly applicable for the interactive processing of frequent sequences, supporting the exploration of the inner mechanisms of complex systems.

Bacterial enrichment prior to third-generation metagenomic sequencing improves detection of BRD pathogens and genetic determinants of antimicrobial resistance in feedlot cattle.

Bovine respiratory disease (BRD) is one of the most important animal health problems in the beef industry. While bacterial culture and antimicrobial susceptibility testing have been used for diagnostic testing, the common practice of examining one isolate per species does not fully reflect the bacterial population in the sample. In contrast, a recent study with metagenomic sequencing of nasal swabs from feedlot cattle is promising in terms of bacterial pathogen identification and detection of antimicrobial resistance genes (ARGs). However, the sensitivity of metagenomic sequencing was impeded by the high proportion of host biomass in the nasal swab samples. This pilot study employed a non-selective bacterial enrichment step before nucleic acid extraction to increase the relative proportion of bacterial DNA for sequencing. Non-selective bacterial enrichment increased the proportion of bacteria relative to host sequence data, allowing increased detection of BRD pathogens compared with unenriched samples. This process also allowed for enhanced detection of ARGs with species-level resolution, including detection of ARGs for bacterial species of interest that were not targeted for culture and susceptibility testing. The long-read sequencing approach enabled ARG detection on individual bacterial reads without the need for assembly. Metagenomics following non-selective bacterial enrichment resulted in substantial agreement for four of six comparisons with culture for respiratory bacteria and substantial or better correlation with qPCR. Comparison between isolate susceptibility results and detection of ARGs was best for macrolide ARGs in Mannheimia haemolytica reads but was also substantial for sulfonamide ARGs within M. haemolytica and Pasteurella multocida reads and tetracycline ARGs in Histophilus somni reads. By increasing the proportion of bacterial DNA relative to host DNA through non-selective enrichment, we demonstrated a corresponding increase in the proportion of sequencing data identifying BRD-associated pathogens and ARGs in deep nasopharyngeal swabs from feedlot cattle using long-read metagenomic sequencing. This method shows promise as a detection strategy for BRD pathogens and ARGs and strikes a balance between processing time, input costs, and generation of on-target data. This approach could serve as a valuable tool to inform antimicrobial management for BRD and support antimicrobial stewardship.

A study revealing mechanisms behind the stone cell of Yali pear degradation by mixed‐culture fermentation of lactic acid bacteria and yeast

AbstractThe presence of stone cells in pears is recognized as a problem for the pear processing industry. Bacillus and mold can degrade stone cells because of their potential to digest cellulose and lignin, but they cannot be used for the degradation test of pear stone cells. In this study Lactoplantibacillus plantarum JYLP‐326 was used in single culture or in the mixed culture with Saccharomyces cerevisiae Y2 to study their potential to degrade stone cells during fermentation and the mechanism of degradation was further explored. Synergy in cellulase activity was observed in the mixed‐culture where the maximum activity was observed at 96th hour of fermentation. Activities of endoglucanase, exoglucanase and β‐glucosidase were 1.75, 4.58, and 2.31. The degradation rate of stone cells in the mixed‐culture was 37.67%, which was significantly higher than that the results obtained for single cultures. The results of scanning electron microscopy (SEM) showed that the surface of the cultured stone cells became rough. Metabolomics studies confirmed the presence of specific metabolites related to the degradation of stone cells after the fermentation. It was concluded that the mixed‐culture fermentation using the above‐mentioned strains could be exploited by the pear processing industry to degrade stone cells.

Recent Advances in Preparation and Structure of Polyurethane Porous Materials for Sound Absorbing Application.

Various acoustic materials are developed to resolve noise pollution problem in many industries. Especially, materials with porous structure are broadly used to absorb sound energy in civil construction and transportation area. Polyurethane (PU) porous materials possess excellent damping properties, good toughness, and well-developed pore structures, which have a broad application prospect in sound absorption field. This work aims to summarize the recent progress of fabrication and structure for PU porous materials in sound absorption application. The sound absorption mechanisms of porous materials are introduced. Different kinds of structure for typical PU porous materials in sound absorption application are covered and highlighted, which include PU foam, modified PU porous materials, aerogel, templated PU, and special PU porous materials. Finally, the development direction and existing problems of PU material in sound absorption application are briefly prospected. It can be expected that porous PU with high sound absorption coefficient can be obtained by using some facile methods. The design and accurate regulation of porous structures or construction of multilayer sound absorption structure is favorably recommended to fulfill the high demand of industrial and commercial applications in the future work.

299 Building and maintaining an engaged undergraduate equine research team

Abstract An objective of the equine science program at Penn State is to provide the training and knowledge students need to solve problems in their lives and careers. The Equine Research Team at Penn State (PSERT) is a novel approach to meeting this objective, inspired by Dr. Max Kleiber’s “Tracer Team”, a group of faculty and graduate students that successfully studied kinetics of phosphorus and calcium metabolism in dairy cows at the University of California, Davis in the 1950s and 60s. The team allows us to address several objectives that are not easily approached using more traditional teaching environments found in the classroom or laboratory. These include 1) satisfying the demand for research experience from a large number of students, who come to research with an enormous range of ability and enthusiasm, 2) providing the hand on practice utilizing the scientific method to solve problems in the equine industry, 3) building a sense of personal responsibility and simultaneously cooperation by approaching research as a team, 4) creating an environment of academic and creative achievement outside the traditional grading system, and 5) blurring the lines that traditionally separate academic and social life at a university to create an environment much closer to what students will experience as graduates. In spring 2008, 10 undergraduate students sought formal research experience opportunities in the area of equine science. Students were organized into a team that met biweekly. Project leaders registered for independent study course credits and conducted 3 research studies in yr 1, while the rest of the team participated as volunteers. Fourteen years later, the team is still an important student organization with between 40 to 60 members on an annual basis. Over the years, the team has traveled to universities and important equine industry locations throughout the United States. Members have conceived, conducted, analyzed and presented research studies on a wide range of topics within the sphere of equine science. The team has two faculty advisors, an executive committee analogous to most student organizations, a group of research project leaders, and approximately 60 dues paying student members. The biweekly meeting is organized and led by the executive committee and generally contains the following components: update of activities, seminar provided by an outside speaker from industry or academia who has expertise in the area of equine research, presentation by one of the research project leaders, and group discussion of the project, planning of future research projects. This Equine Research Team has been and continues to be a model that can be utilized by others to successfully facilitate undergraduate student engagement in research.