Industrial Problems Research Articles

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.

Research And Analysis On The Development Of Chongqing's Convention And Exhibition Industry Under Initiative: Taking The 5th West China International Fair For Investment And Trade As An Example

How to clearly position the function of cultural exhibition, transform resource advantages into industrial advantages, and strive to build a supporting platform for the cultural exhibition industry? This paper first analyzes the opportunities of Chongqing's exhibition industry under the background of "One Belt and One Road" initiative. Taking the 5th Western China International Fair for Investment and Trade as the key point and analysis object, SPSS and other tools are used to sort out and analyze, which can point out some development status and problems of Chongqing's convention and exhibition industry.

Study on mechanical properties of polyurethane mixtures with different fillers combined with industrial problems

This paper mainly introduces the classification of polyurethane mixtures. To produce new polyurethane composites used in manufacturing, the team researched Polyurethane combined with different composites and showed the mechanical properties of the composites on a chart. When reducing-graphene oxide (GO) and multi-walled carbon nanotubes are mixed with polyurethane, the composite can increase Young’s Modulus to 615 MPa and tensile strength to 657 MPa with a weight reduction of 5%. Glass fibre filled with Polyurethane also provides a fairly Young’s Modulus (over 10000 MPa) with a high weight percent up to 20%. How to increase the content of reduced GO and carbon nanotubes in polyurethane filling will be a problem worthy of further exploration.

Investigating the Laser engraving on Polymethyl methacrylate sheets and process parameters optimization using GRA technique.

Abstract Polymethyl methacrylate (PMMA) is sound-resistant because it can lessen the transmission of outside sound waves. PMMA is widely used in many applications, such as automotive lighting, electronics and energy, health, sanitation, etc. Laser engraving for PMMA sheet panels with process parameters of good quality is a major problem in the process industry. There is a demand for surface roughness that is affected by the volume of material removal. Therefore, in this work, multi-value response optimization was performed on MRR and surface roughness during laser engraving of PMMA sheets using an optical fiber diode in a dry environment through gray relational analysis. Also, regression models are developed, and their responses are compared for their correlation. The GRA combined with the Taguchi method has proved efficient in the decision-making of multi-responses in a laser engraving environment.

Laboratory investigation of causes of bovine abortion and stillbirth in the Republic of Korea, 2014-2020.

Bovine abortion is a critical problem in the cattle industry. Identifying causes of abortion is key to establishing appropriate herd management and prevention strategies. We used pathology examinations, detection of etiologic agents, and serology to determine the cause of bovine abortions in Korea. We analyzed 360 abortion and stillbirth cases submitted to the Animal and Plant Quarantine Agency from December 2014 to January 2020. The putative cause of abortion was identified in 140 of 360 (38.9%) cases; 124 of the 140 (88.6%) cases were attributed to infections. The most common etiologic agents detected were bovine viral diarrhea virus (65 of 360; 18.1%), Coxiella burnetii (19 of 360; 5.3%), Leptospira spp. (13 of 360; 3.6%), Listeria monocytogenes (9 of 360; 2.5%), and Neospora caninum (8 of 360; 2.2%). Minor abortifacient pathogens included Brucella abortus (2 of 360; 0.6%), bovine alphaherpesvirus 1 (2 of 360; 0.6%), Akabane virus (2 of 360, 0.6%), and bovine ephemeral fever virus (1 of 360; 0.3%). Non-infectious conditions included congenital anomalies (7 of 360; 1.9%), goiter (7 of 360; 1.9%), and vitamin A deficiency (2 of 360; 0.6%). Our diagnostic rate in cases with placenta submitted (42 of 86; 48.8%) was significantly higher than in cases without placenta (98 of 274; 35.8%), which highlights the value of submitting placentas. Our results confirm the status of the large variety of causative agents associated with abortions in cattle in Korea.

Optimization and performance indication of surrounding gate tunnel field‐effect transistors based on machine learning

AbstractSelecting designs that efficiently optimize multiple objectives simultaneously is an important problem in several distinct industries. Typically, there is not a single ideal design; rather, there are several Pareto‐optimal designs that provide the best possible trade‐offs between the objectives. However, evaluating every design might be expensive, making a thorough search for the whole Pareto optimum set impractical. The aforementioned issue with technology computer‐aided design (TCAD) while investigating a multidimensional parameter set for device design is addressed using Pareto active learning (PAL) and the nondominated sorting genetic algorithm‐III (NSGA‐III) which are metaheuristics‐based multiobjective optimization (MOO) techniques. NSGA‐III adeptly analyzes the tradeoffs among multiple objectives while ensuring diversity in the design space. PAL forecasts the Pareto‐optimal set with intelligence by deliberately sampling the design space. This work focusses on improving the performance of surrounding gate tunnel field‐effect transistors (SGTFETs) by optimizing and assessing their complex designs in terms of multiple objectives, including power, energy, speed, and variability. This paper presents a novel MOO framework that incorporates machine learning (ML) approaches, including NSGA‐III and PAL in SGTFETs technology. The framework provides effective global optimization without gradients, allowing for the automatic recognition of the best solutions. The outcomes show the possibility of ML‐based MOO to create next‐generation nanoscale transistors.

Topological numbers of fuzzy soft graphs and their applications in globalizing the world by mutual trade

In this research draft, by keeping in view, the importance of Zagreb numbers, first we defined some familiar graph families and their degrees in fuzzy soft environment, and then by converting these two novel topological numbers in fuzzy soft framework, their formulae are calculated for these graphical networks. An application of international trade using two kinds of routes is also discussed in the article, and by comparing the results efficiency of both the numbers is compared and analyzed how topological descriptors are useful in examining the progress and profit in the countries, that are a part of the project. Graphs are used in the modeling of links and processes within physical, biological, social, and information systems. A fuzzy graph is the most adaptable tool in mathematics, which describes the fuzzy relationship between objects. Fuzzy graphs are very helpful to give more accuracy to the system as compared to crisp graphs. A classification of the universe with respect to certain specified parameters is known as a soft set. It is a new method for simulating ambiguity and uncertainty. Soft set theory was created by Molodtsov in 1999 as a method for simulating vagueness and uncertainty. Soft set theory is presently used widely in academia to address decision-making issues. The concept of soft graphs is used to provide a parameterized point of view for graphs. In many areas of mathematics and chemistry, as well as in network theory, spectral graph theory, and molecular chemistry, the Zagreb numbers are crucial graph parameters. Due to the importance and significance of Zagreb numbers, in this research article we define these graph parameters in fuzzy soft environment and then derived the fundamental formula for first and second Zagreb numbers of some popular graph families. Also by keeping in view the importance of graph theory in solving decision making problems in business industry, and the most generic behavior of fuzzy soft graph due to its parameterized nature we use our work in application of decision making in trade among different nations.

Spare parts recommendation for corrective maintenance of capital goods considering demand dependency

We consider a maintenance service provider that services geographically dispersed customers with its local service engineers. Traditionally, when a system failure is reported, a service engineer makes a diagnostic visit to the customer’s location to perform corrective maintenance. If spare parts are required, they are ordered and a second visit is scheduled at a later date to complete the corrective maintenance. In this paper, the service provider can proactively send spare parts to the customer to avoid the costly second visit. Motivated by a real-world problem in the high-tech industry, our model considers the cost of a second visit, fixed shipment costs, retrieval costs for the parts that are sent to the customer, and send-back costs for the parts that are sent but not used for corrective maintenance. The uncertainty in the set of parts required for corrective maintenance is modeled with a general distribution that can capture the dependencies between demands for different spare parts. We formulate an integer linear program to find the optimal set of spare parts that minimizes the expected total cost. We derive analytical results for the structure of the optimal policy and compare the optimal policy with two benchmark policies from practice. We observe that the policies from practice often find the optimal policy, and a new heuristic policy that exploits the structure of the optimal policy, on average, performs better than the benchmark policies.

Strength and Compressibility Characteristics of An Expansive Soil with addition of GGBS and Alkali Activated Slag

Abstract: The phenomenal development in civil engineering infrastructure in developing countries like India, soil stabilization has emerged as à key problem in the engineering industry. Engineers have been attempting to enhance the engineering properties of low-quality soil due to their negative impact on project performance. With increasing awareness of environmental issues, there has been a remarkable shift towards green and sustainable technologies. Reuse of waste materials have been advocated for quite a while to improve the properties of poor soils open up to new avenue and double advantage of waste management. In the project investigation an attempt to evacuate the Plasticity characteristics, Strength characteristics and Compressibility characteristics were conducted on selected soil as per Indian Standards using GGBS and Alkali Activated Solution (AAS) with different percentages and curing for 0,3,7,14, and 28 days to analyze the variation of engineering properties. From the results combination of (GGBS + AAS) proved to increase of strength and reduce compressibility characteristics. The combination of GGBS + AAS is cost effective, non-destructive, low energy demanding and ecofriendly than GGBS to the selected expansive soil.

РАЗРАБОТКА АППАРАТНОЙ ЧАСТИ И 3D-МОДЕЛИРОВАНИЕ КОРПУСА СИСТЕМЫ ТЕХНИЧЕСКОГО ЗРЕНИЯ ДЛЯ ОПРЕДЕЛЕНИЯ ПАРАМЕТРОВ КОРНЕПЛОДОВ САХАРНОЙ СВЁКЛЫ

One of the problems of the sugar industry is the high quality loss of sugar beet roots during storage. The development of a technical vision system is aimed at ensuring greater safety of raw materials during harvesting and storage by analyzing raw materials arriving at factories. The concepts of technical vision and technical vision systems and its components are described in the work. The process of distribution of trucks at the receiving point of sugar factories by humans is considered. The purpose of the article is formulated, which is to develop the hardware of the technical vision system, as well as 3D modeling of the body. All characteristics of all components for the technical vision system have been determined. Based on the characteristics, components were selected to create the system. A block diagram of a technical vision system has been developed and described, including a power supply, a twoposition toggle switch, a DC-DC converter unit, a fuse block, a controller, an eight-channel relay module, a galvanic isolation module, a USB splitter with active power supply, a USB-UART converter, spotlight, laser distance sensor, industrial camera, USB modem, LED display, thermostat, heating plate, case fan, thermistor. The 3D modeling method is the KOMPAS-3D environment, in which models such as the protective housing of the technical vision system and the bracket for mounting it on site were created. The case is printed from PLA plastic, as it has high hardness and density, as a result of which the likelihood of the case breaking is low. The bracket is made of heat treated steel for high strength and durability. Based on the results of the work performed, the technical vision system was sent for testing and identification of deficiencies to the receiving point of a sugar factory in the Kursk region.

EFFICIENCY OF COMPLICATED WELL STOCK OPERATION

One of the key problems of the oil industry is the of asphalt-resin-paraffin deposit (ARPD) formation which affects the efficiency of well equipment operation. This leads to significant economic losses during extraction and transportation of products. In conditions of a reduction in the resource base of liquid hydrocarbons, the inability of constant monitoring the well operation process becomes a critical factor for the technical and economic aspects of the activities of oil and gas production departments. The factors influencing the intensity of ARPD formation including changes in the characteristics of productive formations and the use of reservoir pressure maintenance are analyzed. The need to ARPD control within the framework of various systems and geological and technical measures is important for effective control of sediment intensity. Taking into account the nonlinearity of the ARPD formation process is a key point in solving urgent issues of well safe operation. An integrated approach taking into account the peculiarities of the ARPD formation at various facilities to increase the efficiency and durability of downhole equipment is recommended.

Many-to-many locomotive routing problem for the steel industry

The locomotive routing problem (LRP) considers the transportation of non-motorised containers called torpedo ladle cars (TPCs) within a steelworks. Locomotives are responsible for picking up and delivering TPCs to fulfil requests for various facilities, including steelmaking, ironmaking, heating, and repair facilities. This study introduces the many-to-many locomotive routing problem (M2MLRP), specifically tailored for the steel industry. M2MLRP was formulated using pattern- and routing-based models, and a logic-based Benders-decomposition-based matheuristic algorithm was developed. The pattern-based model successfully solved 20 small randomly generated instances, while the proposed matheuristic algorithm demonstrated the rapid generation of near-optimal solutions. Notably, unlike the pattern- and routing-based models, the proposed algorithm extended its capability to generate good feasible solutions for medium- and large-sized instances. Across all instances, the matheuristic algorithm outperformed both the routing-based model and an adaptive large neighbourhood search algorithm, showcasing its superior solution quality. This study provides a significant contribution to the field by being the first to address M2MLRP in the context of the steel industry.

MiR-214-PTEN pathway is a potential mechanism for stress-induced immunosuppression affecting chicken immune response to avian influenza virus vaccine

Stress-induced immunosuppression (SIIS) is one of common problems in the intensive poultry industry, affecting the effect of vaccine immunization and leading to high incidences of diseases. In this study, the expression characteristics and regulatory mechanisms of miR-214 in the processes of SIIS and its influence on the immune response to avian influenza virus (AIV) vaccine in chicken were explored. The qRT-PCR results showed that serum circulating miR-214 was significantly differentially expressed (especially on 2, 5, and 28 days post immunization (dpi)) in the processes, so had the potential as a molecular marker. MiR-214 expressions from multiple tissues were closely associated with the changes in circulating miR-214 expression levels. MiR-214-PTEN regulatory network was a potential key regulatory mechanism for the heart, bursa of Fabricius, and glandular stomach to participate in the process of SIIS affecting AIV immune response. This study can provide references for further understanding of stress affecting immune response.

SIMULATION ANALYSIS OF SHELL AND TUBE HEAT EXCHANGER USING DIFFERENT FLUIDS

There are many models to characterize the behavior of the heat exchangers encountered in many industries. There are several correlations available, so that the heat transferred and the thermal stresses can be evaluated. Shell and Tube heat exchangers are having special importance in boilers, oil coolers, condensers, and pre -heaters. They are also widely used in process applications as well as the refrigeration and air conditioning industry. The robustness and medium weighted shape of Shell and Tube heat exchangers make them well suited for high pressure operations. The present work deals with the design and analysis of water-cooled shell and tube condenser and we have shown how to done the thermal analysis by using theoretical formula, for this we have chosen an industrial problem of 8 ton capacity of counter flow shell and tube heat exchanger of water type. The condenser is designed using theoretical procedures. The condenser is modeled by using the dimensions obtained from the design procedures. Then thermal analysis is carried out in SOLIDWORK flow simulation. The results obtained through the analysis are discussed in detail and compared with analytic values. .Key Words: Heat exchanger, Perforated rings, Reynolds number, Overall heat transfer coefficient.

Analytical monitoring of milk production in Ukraine

Introduction. The dairy industry is socially oriented, and its products should provide Ukrainian consumers with high-quality and nutritious dairy food products. Together with the products of other processing branches of the agro-industrial complex, these are the basis of ensuring food security. Among the branches of the food industry, the dairy industry ranks fourth in terms of the volume of industrial products sold. The population's well-being depends not only on the effective development of the dairy industry but also on reducing social tensions. The article aims to analyze the state of milk production by category of farms in Ukraine. The research process applied the methods of comparison, analysis, theoretical generalization, and logical generalization. The dialectical research method became the methodological basis. The article analyzes the dynamics of milk production in all categories of farms and finds out that there was a significant decrease in it due to military operations, the deterioration of the state of cattle feeding, the increase in the cost of raw material production due to the increase in prices for electricity, fuel, and logistics services was established. The main problems of the dairy industry are substantiated by the low level of technological equipment of dairies, outdated equipment, underdevelopment of the market infrastructure, low level of supply of raw materials and capacity utilization, low quality of final products of dairy industry enterprises; limitation of the possibility of broad differentiation of the assortment due to the low quality of raw materials; decrease in demand for processing products due to the low purchasing power of the population of the region, in particular rural areas; high level of competition from powerful enterprises equipped with modern equipment and technologies. In the raw materials market, district-scale enterprises face significant competition from leading enterprises in large cities, which can offer higher purchase prices to agricultural producers. Conditions for increasing the volume of milk production in modern conditions are proposed and substantiated. Keywords: production indicators, milk, dairy industry, annual yield, cattle.