Diverse Industrial Areas Research Articles

METHOD OF STATISTICAL CONTROL OF A PRODUCTION PROCESS

This study presents a statistic control method for the manufacturing process. This control applies on the most diverse industrial areas such as production lines, data traffic, medical system, the evolution of social media or economic system and is one of the main tool used in the control and management of quality. We based this work on the use of the equipment of measuring horizontal projector type of profiles, StarrrettOptical, from the laboratory equipment. We can imagine an algorithm of measuring for the item “washer” and on the algorithm base, we create a measuring program of this item. Moreover, in this paper, we present on to detail the programming mode of the QuadraCheck 200 system which equip the horizontal projector for profile StarrettOptical. On the base of the data set got through a lot of measures of 14 items got through broaching on the broaching machine DPM 08 84, from the laboratory equipment, we analysed broaching process capabilities and we calculate data capability of this process and of this machine.

The analytical assessment of metal contamination in industrial soils of Saudi Arabia using the inductively coupled plasma technology

Abstract In response to significant demand for evaluating the presence of heavy elements in diverse industrial areas of Saudi Arabia, the study sought to analyze the concentration ratios of 16 elements across 11 different artificial soil types in the industrial zones situated in Riyadh, Sudair, and Al-Ahsa. To achieve this objective, the research utilized the wet digestion technique and employed an ICPE-9000 spectrophotometer for quantifying element concentrations. The study had a dual focus: initially, it sought to gauge the pollution attributed to heavy metals arising from enrichment processes, and second, it evaluated the geographical accumulation of pollutants in the soil. The results revealed varying concentration levels of heavy metals across the industrial areas under study. Specifically, the soil in the Yanbu region exhibited the highest concentration values for iron, manganese, zinc, chromium, nickel, copper, cobalt, cadmium, and beryllium. In contrast, the soil in the industrial area of Riyadh had the highest concentration values for lead, mercury (Hg), molybdenum (Mo), selenium (Se), and arsenic (As). Furthermore, the highest concentration of Cd was recorded in the soil of the Jubail region. Conversely, the soil in the Al-Ahsa region displayed the lowest concentration levels for these heavy metals. The conductivity of the synthetic soil ranged from 0.47 to 6.07 μS·cm−1, accompanied by a pH range of 6.6–8.6. The results emphasized the fluctuations in element concentrations, indicating significant implications for both environmental and human health. Notably, around 20% of the gathered samples showed concentrations of heavy elements like Mo, As, Hg, and Se that surpassed the allowable limits.

Efficient and green water softening by integrating electrochemically accelerated precipitation and microfiltration with membrane cleaning by periodically anodic polarization

• An efficient and reagent-free EAPS-MF system was developed for water softening. • A hydrophilic PTFE membrane was used as the separation medium in electrolysis cell. • The Ti microfilter with membrane cleaning by anodic polarization was used for CaCO 3 interception. • CaCO 3 precipitation rate was 349 g h −1 m −2 at 100 A m −2 with energy consumption of 1.88 kWh kg −1 . Although the electrochemical water softening in the divided cell has been proven capable of avoiding the requirement of high working electrode surface area, its industrial application is seriously constrained by the fouling of the ion exchange membrane and the lack of an environmentally friendly liquid–solid separation method. In this study, an energy-efficient and reagent-free electrochemically accelerated precipitation and microfiltration combined system (EAPS-MF) was developed for water softening. In typical operation mode A, the electrolysis cell divided by a polytetrafluoroethylene microfiltration membrane (PMM), allowing for the simultaneous production of alkaline and acidic effluents. The alkaline effluent was fed directly into the crystallizer for the formation of CaCO 3 crystals, which were intercepted by a Ti tubular microfilter. The filtrate was then blended with acidic effluent to further reduce water scaling potential by removing the residual alkalinity. In this system, the precipitation rate raised from 97.5 to 348.8 gCaCO 3 h −1 m −2 by elevating current density from 20 to 100 A m −2 , accompanying the increased specific energy consumption from 0.68 to 1.88 kWh (kgCaCO 3 ) −1 or from 0.044 to 0.44 kWh m −3 water treated. The Ti tubular membrane fouling was mainly caused by the accumulation of CaCO 3 cake on its surface, which existed in the predominant type of calcite and marginal type of vaterite. Interestingly, the fouled Ti tubular membrane could be recovered completely within 5 min just by periodically anodic polarization at a current density of 200 A m −2 without production of wasted cleaning brine. Generally, the established EAPS-MF system exhibited significant prospects in promoting the applications of the electrochemical softening process in diverse industrial areas.

Recent Advances in engineering Corynebacterium glutamicum for production of Lysine

Lysine is an essential amino acid utilised in diverse industrial areas, mostly as animal feed and food. It is synthesized by various organisms but the novel Corynebacterium glutamicum (gram positive, non sporulating bacteria) is selected anticipating to the enormous research. This research has paved a way towards enhancing the lysine productivity. Different strains of Corynebacterium glutamicum utilised many technologies for the enhanced production of L-Lysine. This literature study examines the current status of L-lysine industrial production with a focus on technology used for development irrespective of the strain and fermentation technologies through different approach of understanding of provisions (NADPH, Media source, PTS, exploit of RAM, Vector systems and promoters) with use of different methodologies. The technologies were divided into metabolic engineering, conventional gene mutations, optimization of fermentation parameters (RSM, ANN, GA), gene overexpression, gene switching and exploit of CRISPR, electric current. This review presents the methodologies which are superior at manufacturing enhanced amounts of lysine and report the techniques which assist in producing the best yield in collation with the earlier. This also focuses on the genes related to lysine export and provides conviction of utilizing lysine as an animal feed.

Deep Neural Network based Classification of Rolling Element Bearings and Health Degradation Through Comprehensive Vibration Signal Analysis

Rolling element bearings are machine components used to allow circular movement and hence deliver forces between components of machines used in diverse areas of industry. The likelihood of failure has the propensity of increasing under prolonged operation and varying working conditions. Hence, the accurate fault severity categorization of bearings is vital in diagnosing faults that arise in rotating machinery. The variability and complexity of the recorded vibration signals pose a great hurdle to distinguishing unique characteristic fault features. In this paper, the efficacy and the leverage of a pre-trained convolutional neural network (CNN) is harnessed in the implementation of a robust fault classification model. In the absence of sufficient data, this method has a high-performance rate. Initially, a modified VGG16 architecture is used to extract discriminating features from new samples and serves as input to a classifier. The raw vibration data are strategically segmented and transformed into two representations which are trained separately and jointly. The proposed approach is carried out on bearing vibration data and shows high-performance results. In addition to successfully implementing a robust fault classification model, a prognostic framework is developed by constructing a health indicator (HI) under varying operating conditions for a given fault condition.

The Effect of the Strategic Role of HR Department in Manufacturing on the Organizational Effectiveness through Education and Training Satisfaction

The purpose of this study is to find out the impact of the strategic role of the HR department in charge of human resource-related tasks, which is the subject of innovation to overcome the immediate crisis situation in the manufacturing industry, on the effectiveness of the organization through satisfaction with education and training. The result of this study is as follows: First, we verified that a strategic role of the HR department has a positive effect on education and training satisfaction. Second, the satisfaction level of education and training and the strategic role of the personnel department have a positive effect on job satisfaction among organizational effectiveness. Third, it was confirmed that education and training satisfaction was found to have a mediating effect in the relationship between HR department's strategic role and job satisfaction. We expect that the results of this study will serve as the basis for re-establishing the role of the HR department dedicated to human resources, which is the important factor not only for innovation but also for overcoming the crisis faced by SMEs and expand their authority and responsibility. The focus of this study is on manufacturing only. This industrial sector is currently facing a serious crisis due to fierce competition and rapidly changing economic environment, but it is better to expand its research focus to more diverse industrial areas.

Radio propagation models for differential GNSS based on dense point clouds

AbstractAccurate geolocation of mobile equipment operating in outdoor environments is an increasingly important question in robotics and automation. Modern geolocation systems, however, rely on the crucial ability for a mobile device to receive specific radio signals at all times. As such geolocation systems are increasingly deployed in harsh or difficult environments, for example, in the presence of tall buildings or dense forest, it becomes critical to predict how the environment will impact the propagation of these radio signals. To this effect, we present a new signal propagation model that can determine what areas would be favorable for global navigation satellite system (GNSS) positioning, based on a prior three‐dimensional (3D) point cloud map of the environment. Our model can predict both the number of usable satellites for a GNSS receiver and the strength of the reference radio signal used in the differential GNSS scenario. Contrary to others, it takes into account both signal occlusion and absorption mechanisms, given the geometry and density of the point cloud map. We designed two rugged mobile data‐collecting platforms, both to generate the 3D maps of the environment, as well as to gather various ground truth for GNSS satellite and local radio signals. Environments used for our field deployments included a boreal forest, a subarctic forest and diverse industrial areas. Experimental results indicate that our model performs well in both structured and unstructured environments, with median errors of 1.10 for the predicted number of satellites and for the strength of the differential GNSS correction signals.

Simulation strategies for the Food and Drug Administration nozzle using Nek5000

Computational fluid dynamics (CFD) is currently a versatile tool used for flow characterization in diverse areas of industry and research; however, its application in medical devices is less developed due to high regulatory standards for safety purposes. In this context, the development of a rigorous and standardized CFD methodology is essential in order to improve the accuracy and ensure the reliability of biomedical applications. To that end, the Food and Drug Administration (FDA) proposed a benchmark model of an idealized medical device to provide a common ground for verification and validation processes. Previous studies have evaluated the potential of conventional turbulence models to predict the relevant flow features in the FDA nozzle but have also been deemed inaccurate or exhibited high dependency on the numerical scheme. Furthermore, validation of computational results relied on previous experiments performed with particle image velocimetry (PIV), which also exhibited noticeable uncertainties. Here, we perform direct numerical simulations (DNSs) of the flow through the FDA nozzle configuration, at Reynolds numbers based on the throat diameter Ret = 500, 2000, 3500, and 5000, using the spectral-element code Nek5000. The predictive capabilities of the synthetic-eddy method and parabolic-inflow conditions at the inlet were tested, and the results were compared with PIV data. Our results highlight the very high sensitivity of this flow case to the inflow conditions and the disturbances at the throat, particularly when predicting the laminar–turbulent jet breakdown. Due to this extreme sensitivity, any benchmark data of this geometry need to include a very detailed characterization of both the conditions at the inflow and the throat, in order to enable relevant comparisons.

Surface integrity investigation of a Zr<SUB align="right">52.5Ti<SUB align="right">5Cu<SUB align="right">17.9Ni<SUB align="right">14.6Al<SUB align="right">10 metallic glass after grinding

Crystalline alloys, widely used in the industry, are a topic of important research regarding their integrity resistance towards machining. Such investigations are less intense when dealing with relatively newer and less popular materials such as bulk metallic glasses (BMGs). This is even truer when specific machining techniques, such as grinding, are involved. As BMG are increasingly promoted to diverse industrial areas, the study of the impact of grinding on their microstructural integrity is necessary. Indeed, the amorphous structure of BMG, at the origin of their remarkable properties, is metastable such that any exterior solicitation (heating, cooling, loading, etc.) can induce structural modifications, for instance local crystallisation, and therefore degrade or at least modify their characteristics. Using quick and straightforward characterisation techniques such as SEM imaging, optical microscopy and X-ray diffraction, the microstructural changes occurring in the BMG after severe grinding passes could be identified. It is shown that crystallisation can be detected below the grinded surface even for relatively small depth of cut. The results obtained on this peculiar composition help to propose a more generic methodology to safely use grinding on BMG.

It Is the Mix that Matters: Substrate-Specific Enzyme Production from Filamentous Fungi and Bacteria Through Solid-State Fermentation.

Fungi have a diverse spectrum of extracellular enzymes. In nature, extracellular enzymes primarily serve to procure nutrients for the survival and growth of the fungi. Complex polymers such as lignocellulose and starch as well as proteins and fats are broken down into their basic building blocks by extracellular enzymes such as amylases, proteases, lipases, xylanases, laccases, and many more.The abilities of these enzymes are made use of in diverse areas of industry, including food technology, textiles, and pharmaceuticals, and they have become indispensable for today's technology. Enzyme production is usually carried out using submerged fermentation (SmF). However, as part of the search for more sustainable uses of raw materials, solid-state fermentation (SSF) has become the focus of research.The rate of enzyme formation depends on different factors, for example, microorganism, temperature, or oxygen supply. However, one of the most important factors in enzyme production is the choice of substrate, which varies depending on the desired target enzyme. Substrates with proven effectiveness include wheat bran and straw, but unusual agricultural residues such as forage cactus pears and orange peels have surprisingly positive effects on enzyme formation as well.This review gives an overview of various technically relevant enzymes produced by filamentous fungi and suitable substrates for the production of the enzymes by SSF. Graphical Abstract.

Design of fuzzy radial basis function neural network classifier based on information data preprocessing for recycling black plastic wastes: comparative studies of ATR FT-IR and Raman spectroscopy

As large amounts of plastics are widely used in diverse areas of industry, the amount of plastic waste, including black plastics, continues to increase. In this situation, the necessity of useful recycling having limited resources gradually increases. The design of plastic classification systems for plastics recycling becomes more important to effectively address recycling activities. Until now, conventional sorting systems based on the near infrared ray technology have been used to classify plastic wastes. However, the classification of black plastic waste still remains a challenge because such materials do not reflect sufficient signals due to the absorption of laser light coming from the NIR spectrometer. In order to solve such problems, this research is focused on an efficient way to identify black plastics. Attenuated Total Reflectance (ATR) Fourier Transform Infrared Radiation (FT-IR) and a Raman spectrometer are used to carry out qualitative and quantitative analysis for the effective as well as efficient classification of black plastic wastes. In this study, to effectively classify the black plastic waste, data processing and Fuzzy Transform (F-Transform) as well as PCA-based Fuzzy Radial Basis Function Neural Networks (FRBFNNs) classifier is proposed. Input variables extracted on a basis of chemical characteristic peaks as well as interval range positioned near the chemical characteristic peaks were exploited as a way to improve the classification performance of the FRBFNN classifier. In order to evaluate the performance of the classifier, a suite of techniques including F-Transform-based as well as Principal Component Analysis (PCA)-based FRBFNNs classifier designed with the aid of Particle Swam Optimization are developed to analyze and classify black plastics.

New TiZrNbTaFe high entropy alloy used for medical applications

The paper considers a new concept of alloy with high entropy (HEA) for biomedical applications. HEAs are different from the conventional metallic materials by more than five alloying elements, in proportions between 5% and 35% at., which may form simple solid solutions with BCC and/or FCC phases instead of complicated intermetallic ones. These specific features provide HEA with excellent mechanical properties (hardness, strength, malleability), oxidation and corrosion resistance, with potential applications in diverse industrial areas. The present tendency in the newest titanium alloys generation is the decrease of elasticity modulus, with the maintaining of high mechanical characteristics. Thus, the paper considers the system TiZrNbTaFe for biomedical applications obtained by powder metallurgy (PM) route, because HEAs prepared by this method show a greater homogeneity in their microstructure compared to the segregated microstructure of melted and cast HEAs. The influence of milling time, compaction and sintering on the microstructure and mechanical and corrosion properties of the new TiZrNbTaFe alloy were investigated. The obtained properties have shown a better mechanical biocompatibility in order to use this high entropy alloy as orthopedic or dental implants. The mechanical properties of the obtained alloys are better than those of biomaterials that are used in present.

New High Entropy Alloy for Biomedical Applications

High Entropy Alloys (HEAs) represent a new concept of metallic materials, that contain 5 or more elements, in proportions from 5 at.% to 35 at.%, and form simple solid solutions (BCC and/or FCC) instead of complicated intermetallic phases. The high degree of randomness atomic HEA, gives them excellent properties: electrical, mechanical, electrochemical, ductility, anti-corrosion properties, stable structure etc, with applications in peak thus representing a growing research. These specific features provides HEA with excellent hardness, strength and wear strength, malleability, oxidation and corrosion resistance, with potential applications in diverse industrial areas [1÷4]. Considering these properties we decide to improve biomedical alloys with this new class of HEAs.

Improving Reliability of Particle Filter-Based Localization in Wireless Sensor Networks via Hybrid Particle/FIR Filtering

The need for accurate, fast, and reliable indoor localization using wireless sensor networks (WSNs) has recently grown in diverse areas of industry. Accurate localization in cluttered and noisy environments is commonly provided by means of a mathematical algorithm referred to as a state estimator or filter. The particle filter (PF), which is the most commonly used filter in localization, suffers from the sample impoverishment problem under typical conditions of real-time localization based on WSNs. This paper proposes a novel hybrid particle/finite impulse response (FIR) filtering algorithm for improving reliability of PF-based localization schemes under harsh conditions causing sample impoverishment. The hybrid particle/FIR filter detects the PF failures and recovers the failed PF by resetting the PF using the output of an auxiliary FIR filter. Combining the regularized particle filter (RPF) and the extended unbiased FIR (EFIR) filter, the hybrid RP/EFIR filter is constructed in this paper. Through simulations, the hybrid RP/EFIR filter demonstrates its improved reliability and ability to recover the RPF from failures.

Statistical Engineering—Roles for Statisticians and the Path Forward

Experts from diverse areas of industry, government, and academia are asked about the changing roles for statisticians in the SE workplace and discuss some of the opportunities and challenges for the future.

P.K. Datta and J.S. Burnell-Gray, Advances in Surface Engineering (Volumes I, II and III).

This three volume publication forms the Proceedings of the 4th International Conference on Advances in Surface Engineering which was held at the University of Northumbria's Surface Engineering Research Group, 14±17 May 1996. Volume I (338 pages) concerns the Fundamentals of Coatings. The 27 papers are divided into sections onHigh Temperature Corrosion, Aqueous Corrosion, Wear and Fatigue/Other Failure. While the aqueous corrosion papers are the most relevant to electrochemists, other useful contributions in this volume include ones on high temperature corrosion of electroless nickel coatings and the erosion resistance of electroplated chromium. The second volume (336 pages) provides 26 papers on PVD and CVD deposition methods, thermal, plasma, weld and detonation coatings, laser techniques, shot peening and electrochemical deposition strategies. This volume deserves to be read by electrochemistrs interested in metal ®nishing an surface coatings as it provides a convenient collection of papers across the boundaries of deposition techniques, physical and chemical properties of surfaces and the industrial applications of many surface ®nishing approaches. Volume III (416 pages) considers Engineering Applications in the form of 26 papers in diverse areas of industry, such as biomedical implants, aerospace, automotive, cutting tool, power generation and marine sectors. Vacuum spectroscopy techniques sit alongside classical mechanical testing. The books are well illustrated by data plots, line drawings and micrographs of engineering surfaces. The material provides a useful compilation across the ®elds of electrochemical, thermal, mechanical and gasphase coatings and surface treatment techniques. The emphasis is on practical/industrially useful surfaces in the engineering industries although ther is much useful material on emerging techniques (e.g., laser treatment strategies and the use of numerical modelling for the prediction of surface characteristics. The material should prove useful to materials scientists, coatings technologists and production engineers in addition to applied electrochemists. The books have found their way into our Applied Electrochemistry group and should prove informative for projects in the areas of electroplating, electroless plating, composite coatings and corrosion resistance. It is rare that a single book or series of books based on a conference proves to be of such widespread use by postgraduate and postdoctoral workers.