Industrial Environmental Conditions Research Articles

Smart Machinery Monitoring System berbasis Mobile Application

This research designs and implements a Mobile Application-Based Smart Machinery Monitoring System as a solution for monitoring machine conditions in industrial environments. Using Flutter as a mobile application development framework and utilizing internet connection capabilities, this research aims to increase monitoring efficiency and minimize the risk of machine failure. With a responsive interface, this application allows real-time access to machine conditions from various mobile devices. Internet of Things (IoT) integration allows machine sensors to communicate with applications, providing accurate and direct data. This research is expected to make a positive contribution to industrial operational efficiency, make it easier for users to monitor machine conditions, and support the industry's evolution towards an era of better connectivity.

Deep adaptive sparse residual networks: A lifelong learning framework for rotating machinery fault diagnosis with domain increments

Rotating machinery operates continuously for long periods of time under varying conditions in actual industrial environments. The number of fault samples increases with equipment operating time, whereas differences in data distribution are inevitable because of varying operating conditions. As a result, fault diagnosis of rotating machinery poses challenges related to the fault domain increments. In addition, the issue of catastrophic forgetting, where previously learned knowledge significantly affects the model's performance, remains a critical concern. Deep adaptive sparse residual network (DASRN), a new lifelong learning-based method, is proposed to overcome these challenges. The DASRN model is constructed based on an improved deep residual network. The model uses a task-aware dynamic masking strategy to adjust the retention and utilization of blank weights in the network, thereby balancing the model's memory and learning capabilities, mitigating catastrophic forgetting. Furthermore, throughout the entire training process of the model, a dynamic data removal strategy is applied to eliminate easily distinguishable samples. This approach adaptively allocates higher weights to more challenging samples, enhancing the model's learning efficiency while consolidating the sparsity within the model. Finally, the effectiveness of the proposed DASRN is validated on bearing datasets from the Chinese CRH380A high-speed train gearbox and integrated wheelset transmission test rig. Results demonstrate that DASRN provides an effective solution for catastrophic forgetting and domain incremental scenarios in rotating machinery fault diagnosis tasks.

Exploring electromembrane extraction and liquid membrane for efficient removal of heavy metals from aqueous solutions: An overview

Environmental pollution is experiencing an alarming surge within the global ecosystem, warranting urgent attention. Among the significant challenges that demand immediate resolution, effective treatment of industrial pollutants stands out prominently, which for decades has been the focus of most researchers for sustainable industrial development aiming to remove those pollutants and recover some of them. The liquid membrane (LM) method, specifically electromembrane extraction (EME), offers promise. EME deploys an electric field, reducing extraction time and energy use while staying eco-friendly. However, there's a crucial knowledge gap. Despite strides in understanding and applying EME, optimizing it for diverse industrial pollutants and environmental conditions remains uncharted. Future research must expand EME's applicability, assess its environmental impact versus other methods, and boost scalability, cost-effectiveness, and energy efficiency in industry. Advances in novel liquid membrane materials can enhance extraction efficiency and selectivity, aiming to provide efficient, sustainable industrial pollutant treatment. This research provides a review of the existing practices in the field of liquid membranes when coupled with the application of an electric field.

Analysis The Impact Of Industrial Areas On HIV Aids Incidence

Research Background : South Jepara Regency is an industrial area that absorbs a lot of labor around the company's establishment. Over time, the incidence of HIV AIDS has increased. Data from the Jepara health office in Pecangaan District in 2018 reached 48 cases, in Mayong District in 2018 it reached 29 cases and in Kalimatan District in 2018 it reached 21 cases.Research Objective: To analyze the impact of industrial estates on the incidence of HIV AIDS.Research Methods: This type of research is qualitative with in-depth interview data collection techniques. Time of data collection in November 2019. The research location is Pecangaan, Kalinyamatan and Mayong Districts, Jepara Regency, Central Java. The number of research informants is 10 people. Miles and Huberman interactive data analysisThe results of the study: the positive impact of increasing economic welfare and reducing the number of unemployed, while the negative impact of water pollution, the proliferation of hangouts and the construction of many boarding houses.Conclusion: Industrial growth in the southern part of Jepara Regency, has positive and negative impacts. Industrial environmental conditions as an indirect cause of the increasing incidence of HIV AIDS.

Preparation of Aerogel-like Silica Foam with the Hollow-Sphere-Based 3D Network Skeleton by the Cast-in Situ Method and Ambient Pressure Drying.

Silica aerogels have incomparable advantages among thermal insulation materials because of their ultralow density and thermal conductivity, but cumbersome production processes, high cost, and low mechanical stability limit their practical application. In this study, a novel aqueous process to prepare lightweight aerogel-like silica foams (ASFoams) through the cast-in situ method and ambient pressure drying was proposed with multiblock polyurethane surfactant as the vesicle template. ASFoams possess a unique loose stacking morphology of the silica hollow sphere with a 3D network structure as the skeleton, which endues ASFoams with a low density of 0.059 g/cm3, low thermal conductivity of 36.1 mW·k-1·m-1, and pretty good mechanical properties. These properties make ASFoams a promising option for thermal insulation in industrial, aerospace, and other extreme environmental conditions. In addition, the micromorphology of ASFoams can be adjusted by changing the reaction conditions, which may provide a facile method for the preparation of a silica aerogel-like foam with adjustable microstructure.

Shift Register, Reconvergent-Fanout (SiRF) PUF Implementation on an FPGA

Physical unclonable functions (PUFs) are gaining traction as an attractive alternative to generating and storing device keying material over traditional secure non-volatile memory (NVM) technologies. In this paper, we propose an engineered delay-based PUF called the shift-register, reconvergent-fanout (SiRF) PUF, and present an analysis of the statistical quality of its bitstrings using data collected from a set of FPGAs subjected to extended industrial temperature-voltage environmental conditions. The SiRF PUF utilizes the Xilinx shift register primitive and an engineered network of logic gates that are designed to distribute signal paths over a wide region of the FPGA fabric using a MUXing scheme similar in principle to the shift-rows permutation function within the Advanced Encryption Standard algorithm. The shift register is utilized in a unique fashion to enable individual paths through a Xilinx 5-input LUT to be selected as a source of entropy by the challenge. The engineered logic gate network utilizes reconvergent-fanout as a means of adding entropy, eliminating bias and increasing uncertainty with respect to which paths are actually being timed and used in post-processing to produce the secret key or authentication bitstring. The SiRF PUF is a strong PUF build on top of a network with 10’s of millions of possible paths.

Corrosion resistance and metallurgical behaviour of CMT welded Al-LCS dissimilar butt joint exposed in simulated industrial environment

Cold Metal Transfer welding is a predominant process for joining the Aluminium and Low Carbon Steel (LCS) dissimilar joints with enhanced properties. In addition, these joints have vast application in various simulated industrial environmental conditions. However, the formation of thick intermetallic layers during welding over these joints leads to invoking the corrosion attack and causing a catastrophic failure that is the primary concern in life prediction of the joint. Hence, the corrosion behaviour of AL-LCS dissimilar butt joint exposed in the simulated industrial environment has been studied experimentally and it has been compared with the Cold Metal Transfer (CMT) welded aluminium and LCS similar joints. The potentiodynamic polarization and the electrochemical impedance spectroscopy were carried out in 3.5% aggressive sodium chloride medium with varying benzotriazole corrosion inhibitor with varying the concentrations like 10 ppm, 15 ppm and 20 ppm. The results showed that the corrosion resistance behaviour of CMT welded dissimilar joints are increased with increasing inhibitor concentration. The inhibitor showed effective performance, and the efficiency is also found to be 78–80% at 20ppm, which revealed the enhanced corrosion resistance of dissimilar metal joints in simulated industrial conditions. Finally, the dissimilar joints are characterized by sophisticated analytical techniques.

Concentrations and distribution of chlorinated paraffins in Belgian foods

This study reports on concentrations of short- and medium-chain chlorinated paraffins (SCCPs and MCCPs, respectively) in a wide range of food samples (n = 211) purchased in Belgium during 2020. Samples were analysed by gas chromatography-mass spectrometry (GC-MS) and quantified using chlorine content calibration. ∑SCCPs were present above LOQ in 25% of samples with an overall range of <LOQ to 58 ng/g wet weight (ww), while ∑MCCPs were identified in 66% of samples ranging from <LOQ to 250 ng/g ww. ∑MCCP concentrations were greater than those of ∑SCCPs in all 48 samples in which both groups were detected with an average ∑MCCP/∑SCCP ratio of 5.8 (ranging from 1.3 to 81). In general, the greatest CP concentrations were observed in foods classified as animal and vegetable fats and oils and sugar and confectionary for both SCCPs and MCCPs. Significant correlations between lipid content in food samples and CP levels illustrated the role of lipids in accumulating CPs within foodstuffs, while industrial processing, food packaging and environmental conditions are each likely to contribute to overall CP loads. Selected samples (n = 20) were further analysed by liquid chromatography-high resolution MS (LC-HRMS) to investigate homologue profiles and the occurrence of long-chain CPs (LCCPs). LCCPs were detected in 35% of the 20 subset samples while the HRMS results for SCCPs and MCCPs matched closely with those obtained by GC-MS. This study reveals the widespread occurrence of SCCPs and MCCPs in Belgian food and indicates that LCCPs may represent a substantial contribution to overall CP levels in foodstuffs.

A performance degradation prediction approach for turbo-generator bearing considering complex working conditions based on clustering indicator and self-optimized deep learning model

The reliability of turbo-generator bearings affects the stability and safety of power plants. To detect early symptoms of failure, prediction of the performance degradation of turbo-generator bearings is particularly important. At present, most related research relies on accelerated degradation test platforms; however, the industrial field environment and complex working conditions may affect practical application. In this study, a performance degradation prediction approach for turbo-generator bearings considering complex working conditions based on a clustering indicator and a self-optimized deep learning model (SODLM) is proposed. First, the Dirichlet process-Gaussian mixture clustering model is introduced to construct the performance degradation indicator (PDI) of the turbo-generator. Then through introducing the hyper-parameter constraint, the hyper-parameter influence significance comparison mechanism, and the minimum training epoch, an improved hyperband (IH) is established to realize the automatic tuning of the hyper-parameters in the prediction model. Furthermore, the SODLM is constructed based on the IH and a stacked one-dimensional convolutional neural network. Finally, the performance degradation trend of a turbo-generator bearing in a practical industrial field is successfully predicted through the proposed approach. The experimental analysis demonstrates that the proposed PDI avoids the influence of sampling frequency and complex working conditions. Compared with traditional optimization algorithms and prediction models, the proposed performance degradation prediction approach demonstrates better accuracy and stability.

Comparative high temperature oxidation studies of HVOF IN 625 coating on T22 boiler steel at 900 °C and 700 °C

Abstract IN 625 coating was deposited on T22 boiler tube steel by high velocity oxy fuel (HVOF) process to increase high-temperature corrosion resistance. High-temperature oxidation behavior of steel with and without coating has been examined at 700 °C and 900 °C under cyclic conditions. Each cycle consisted 1 h of heating in the silicon carbide tube furnace followed by 20 min of cooling in air. The cyclic oxidation conditions have been chosen as these conditions resembles actual industrial environment conditions where occurrence of shutdown is very frequent. Cyclic studies give the more severe conditions for testing and may be similar to the actual industrial environment of frequent breakdown/shutdown occurrence. Thermo gravimetric technique was implemented to study the kinetics of corrosion by observing weight change after each cycle. The bare steel experienced higher weight gain, which may be credited to the development of un-protective Fe2O3 dominated oxide scales. Evaluation of corrosive products was done using X-ray diffraction (XRD), scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDAX) and X-ray mapping techniques. It was observed that the uncoated steel suffered corrosion in the form of spalling and peeling up of its oxide scale. On the converse, the IN 625 coating provided significant resistance to the corrosion. The IN 625 coating was found to be more protective at 700 °C than at 900 °C. The better air oxidation resistance in the coatings may be attributed to the phases discovered in the oxide scale of the coated specimens which mainly consisted of oxides and spinals of nickel and chromium. The information gathering from the investigation will be useful to explore the possibility of the use of the HVOF spray coatings on the boiler tubes working in the range of 700–900 °C.

TrustData: Trustworthy and Secured Data Collection for Event Detection in Industrial Cyber-Physical System

In this article, an industrial cyber-physical system (ICPS) is utilized for monitoring critical events such as structural equipment conditions in industrial environments. Such a system can easily be a point of attraction for the cyberattackers, in addition to system faults, severe resource constraints (e.g., bandwidth and energy), and environmental problems. This makes data collection in the ICPS untrustworthy, even the data are altered after the data forwarding. Without validating this before data aggregation, detection of an event through the aggregation in the ICPS can be difficult. This article introduces TrustData, a scheme for high-quality data collection for event detection in the ICPS, referred to as “Trust worthy and secured Data collection” scheme. It alleviates authentic data for accumulation at groups of sensor devices in the ICPS. Based on the application requirements, a reduced quantity of data is delivered to an upstream node, say, a cluster head. We consider that these data might have sensitive information, which is vulnerable to being altered before/after transmission. The contribution of this article is threefold. First, we provide the concept of TrustData to verify whether or not the acquired data are trustworthy (unaltered) before transmission, and whether or not the transmitted data are secured (data privacy is preserved) before aggregation. Second, we utilize a general measurement model that helps to verify acquired signal untrustworthy before transmitting toward upstream nodes. Finally, we provide an extensive performance analysis through a real-world dataset, and our results prove the effectiveness of TrustData.

An empirical model on the impact of foreign direct investment on China's environmental pollution: analysis based on simultaneous equations.

This paper analyses the link between foreign direct investment (FDI) and economic growth and their subsequent impact on environmental pollution in China. The simultaneous equation method was used with data from 31 provinces in China covering the period between 1995 and 2016. The findings indicate that the effect of FDI on economic growth, industrial structure, and environmental pollution control positively impacts on China's industrial pollution control and environmental conditions, implying that China should encourage foreign capital investments that come with advanced production technology and green production processes. This will enhance efficient resource utilization, adherence to environmental standards, and ensuring sustainable economic development.

REFLECTOMETRY AT LINE MAIN PIPELINE INFRASTRUCTURE MONITORING

Background Currently, an important problem in the operation of the line main pipeline is the timely detection of stability loss, due to which the operational reliability of the pipeline is reduced, industrial safety indicators, environmental conditions, and uninterrupted supply of hydrocarbon materials are deteriorating. Aims and Objectives To develop a system for monitoring the pipeline stability state in real time. Methods To achieve the aim, empirical (in the form of experiment) and theoretical (analysis and synthesis) research methods were chosen. The following tasks were posed and solved: to select equipment, to conduct experiment planning, to perform bench tests; to identify patterns and propose mathematical models, based on which to develop an algorithm for pipeline stability assessment in real time. Results The results obtained indicate the feasibility and advisability of this approach applying to existing pipelines. Implementation of the proposed algorithm allows to achieve the aim: knowing the magnitude of the power loss of the scattering signal, one can determine the current (actual) pipeline curvature radius in real conditions and in any section using the proposed mathematical model, evaluate its stability and analyze the stress state of the pipeline section (calculate stress) without opening it at any time using a reflectometer, well-known techniques and the corresponding calculation program.

The main directions of development of the international legal mechanism for regulating environmental migration

The article analyzes directions of development of the international legal mechanism for regulating environmental migration. Two directions were described. The first one involves the extension of the 1951 UN Convention on the Legal Status of Refugees to environmental migrants who have left their permanent places of residence due to an environmental degradation caused by natural or man-made disasters or negative impacts of industrial and economic activities. The second way to create an international legal mechanism for regulating environmental migration and protecting environmental migrants is to develop and adopt a new international agreement governing actions of the international community aimed to protect environmental migrants. The analysis allows for the conclusion that the first direction seems to be the most optimal due to the similar status of asylum seekers and people who have left their places of permanent residence as a result of natural disasters or industrial accidents, environmental and climatic conditions.

A Study on Minimization of Injury and Accidental Causes in Different Operational Sections of RMG Industries in Bangladesh

The primary objective of this study is to investigate the industrial accident in readymade garments (RMG) industries and find out the ways how this risk of injuries and accidents can be mitigating by implementing safety rules and suggestions. The paper discusses in brief the risk of injury and accidental causes of workers in various sections like dyeing, cutting, sewing, printing and finishing of RMG industries based upon the industrial environment and working conditions. The sample respondents are selected from the different industries in Tangail district. Purposive sampling technique is followed for data collection, where different level of respondents is interviewed for collecting information from selective garments industry. After analyzing the collected data, the major accidental causes and injuries faced by the workers in those selective units are indicated for which there have been noticed a massive fall down of workers’ efficiency. Indicating those problems, improvement proposals are given to those industries and implemented over a course of month. From the proposed improvement proposal, it is found that, the rate of injury and accidental risks have been decreased far better than before and almost all risks can be properly controlled if the managing as well as responsible parties try to follow the risk controlling technique properly.

THE EFFECT OF FAMILY OWNERSHIP ON PROFIT AND PERFORMANCE COMPANY MANAGEMENT: BASED ON THE THEORY OF STEWARDSHIP

This study examines the relationship between family ownership of a company and its implications for earnings quality. In the family ownership, the family can affect the quality of earnings that are reported in two ways, namely through the entrenchment and the alignment effect. Earnings are managed opportunistically shows a low earnings quality. Whereas the influence of alignment shows a high quality where earnings are not managed opportunistically. The study also examines if the family ownership has a positive effect on company performance. There are five factors that affect innate accruals quality, namely the company size, the standard deviation of operating cash flows, the standard deviation of sales, duration of operating cycles, and negative earnings. Quality of accruals consists of accruals that reflect economic conditions and accruals that reflect managerial choices. This study shows that family-owned companies in Indonesia do not perform earnings management opportunistically. Earnings management used is the one that is in line with the company’s business model, company industrial environment and economic conditions as represented by innate accruals. This suggests that family ownership has an earnings quality and shows an alignment of interest between the company management and the owners. Thus the alignment of the interests lends support to the stewardship theory.

Microstructure of As-cast Co-Cr-Mo Alloy Prepared by Investment Casting

The microstructure of a cobalt-base alloy (Co-Cr-Mo) obtained by an investment casting process was studied. This alloy complies with the ASTM F75 standard and is widely used in the manufacturing of orthopedic implants owing to its high strength, good corrosion resistance, and excellent biocompatibility. This work focuses on the resulting microstructures arising from normal industrial environmental conditions. The characterization of the samples was carried out using optical microscopy, field emission scanning electron microscopy and energy-dispersive spectroscopy. In this study, the as-cast microstructure is an γ-Co (face-centered cubic) dendritic matrix with the presence of a secondary phase, such as M23C6 carbides precipitated at grain boundaries and interdendritic zones. These precipitates are the main strengthening mechanism in this type of alloy. Other minority phases, such as the σ phase, were also detected, and their presence could be linked to the manufacturing process and environment.

Enhancing the localised corrosion resistance of 316L stainless steel via FBR-CVD chromising treatment

ABSTRACTThe resistance of stainless steels to localised corrosion can be adversely affected by environmental and metallurgical heterogeneities existed in complex industrial infrastructures such as seawater desalination plants exposed to aggressive evnironments. It is therefore critical to enhance the localised corrosion resistance and understand the corrosion behaviour of stainless steels in complex and aggressive industrial environmental conditions. In this work, the localised corrosion resistance of chromised stainless steel 316L (SS316L) in simulated seawater desalination systems has been investigated by electrochemical and surface analytical techniques. It has been found that chromising processes have improved the localised corrosion resistance of SS316L by reducing its susceptibility to pitting, crevice, and welding zone corrosion in simulated seawater desalination environments. This increased corrosion resistance has been explained by electrochemical polarisation studies and surface analysis showing that the chromising treatment at 1050°C resulted in a continuous and stable chromium-enriched layer on the SS316L surface.

Corrosion Characteristics of New Superalloy Under Industrial Environmental Conditions

Corrosion behavior of new superalloy was studied in industrial environment at different temperatures by using various selected electrochemical techniques. The results revealed that the alloy is able to form protective oxide scale on its surface at higher temperatures and consequently the corrosion rate is low. The new alloy is found to degrade due to pitting corrosion at 40 and 50 °C and general corrosion at 25 °C. The scanning electron microscope results confirmed the electrochemical results. The energy-dispersive spectroscopy results confirmed the presence of oxides of nickel and alloying elements present in the superalloy. Based on the results obtained with different techniques, the alloy is recommended to fabricate different components for industrial applications with suitable protective coatings.

Haematological Indicators of Exposure to Petroleum Products in Petroleum Refining and Distribution Industry Workers in Nigeria

Objective: Exposures to hazardous conditions in industrial environments often results in sundry health effects among workers. The study investigated haematological effects of occupational activities in the petroleum refining and distribution industry in Nigeria. Methodology: Adopting routine laboratory methods, haematological indices were investigated in whole blood from randomly selected workers of Port Harcourt Refining Company (PHRC) and Pipelines and Petroleum Product Marketing Company (PPMC) both in Alesa-Eleme near Port Harcourt, Nigeria, as well as non-oil work civil servants serving as control subjects. Results: Erythrocyte Sedimentation Rate (ESR) ranged 1-100 (Mean:10.94 ± 11.82 mm/hr) in oil workers against 1-36 (Mean:6.6 ± 7.81 mm/hr) in non-oil workers (P 0.05); Parked Cell Volume (PCV): 25.00-58.00 (43.31 ± 4.09%) vs.30-49 (42.70 ± 5.01%) (P>0.05); Platelets: 75.00 × 109-430.00 × 109 (232.41 ± 63.18 × 109/L) vs. 141.00 × 109 -382.00 × 109 (239.23 ± 57.30 × 109/L) (P>0.05); White Blood Cell (WBC):3.20 × 109-86.00 × 109 (7.07 ± 6.61 × 109/L) vs. 4.9 × 109-11.00 × 109 (7.36 ± 1.64 × 109/L) (P>0.05). For the WBC differentials, the values were: lymphocytes: 18.00 × 109-75.00 × 109 (52.28 ± 9.25 × 109/L) vs. 25.00 ×109-57.00 × 109 (41.60 ± 10.16 × 109/L) (P<0.01); and granulocytes: 25.00 × 109-82.00 × 109 (47.72 ± 9.24 × 109/L) vs. 43 × 109-75 × 109 (58.40 ± 10.16 × 109/L (P<0.01). Conclusion: Although mean values were still within parametric reference ranges, some variations were observed in the oil workers when compared to the controls: while granulocytes consistently decreased significantly (P<0.01), consistent significant increases in lymphocytes (P<0.01) and ESR (P<0.05) were observed, indicating a possibility of functional aberration following haematopoietic toxicity in the oil workers. Findings suggest petroleum refining and distribution industrial environments as being furnished with potentially haematotoxic substances, and haematopoietic toxicity as part of potential health effects of exposures in this industry in Nigeria. Though gender classification showed no appreciable impact, age grouping suggests that the health effects indicated by the observed variations are likely to rear up from age 40 yr. Changes observed for exposure groupings and statistically significant correlations between age, exposure (service) period and most of the parameters suggest that both age and exposure period have strong impacts in defining the patterns of variations observed in the haematological indices among the oil workers. Findings indicate a need for frequent environmental and biological monitoring for a safer and healthier workplace and workforce respectively.