Surface Quality Assessment Research Articles

Effect of sample pretreatment on pelletization and performance of laser-induced breakdown spectroscopy for predicting key soil properties

Laser-induced breakdown spectroscopy (LIBS) is a promising analytical technique for determining soil properties in a rapid, cost-effective, and environmentally friendly manner. However, an optimal sample pretreatment method that enhances sample homogeneity for improved prediction accuracy is needed. In this study, the effect of different sample pretreatments on pelletization of soil samples, and prediction of texture and soil organic carbon (SOC) content, was assessed. Four pretreatments, namely 2 mm, 200 μm, and 100 μm sieved, and milled pretreatment, were applied to 133 soil samples representing a wide variability in texture and SOC content range. Visual assessment of soil pellet surface quality was done where poor surfaces, deemed unsuitable for LIBS measurement, were separated from the good-surface pellets. Partial least square regression (PLSR) models for the pretreatments across the investigated soil properties were compared, followed by interval partial least square regression (iPLSR), to evaluate potential improvements in the accuracy of the prediction models. The ratio of performance to interquartile distance (RPIQ) was used to rank the PLSR models for each pretreatment across the soil properties. The 100 μm pretreatment had the highest number of good-surface pellets followed by the 2 mm pretreatment, and lastly the 200 μm and milled pretreatments, which were comparable. The milled pretreatment achieved the best model for sand prediction (RPIQ = 7), followed by the 2 mm pretreatment for clay prediction (RPIQ = 2.5), 100 μm pretreatment for silt prediction (RPIQ = 2), and the milled pretreatment for SOC prediction (RPIQ = 1). A reduction in RMSEP of 31%, 23%, and 11% for the prediction of sand, SOC, and silt content, respectively was achieved by the milled pretreatment while the 100 μm pretreatment recorded a 15% reduction in RMSEP for the prediction of silt content. Overall, PLSR performed better than iPLSR for the prediction of texture (apart from clay) and SOC. These results show that sample pretreatment that involves sieving, or milling, influences the pellet surface quality and the prediction accuracy of texture and SOC content.

Optimization of multiple surface roughness characteristics of mild steel turned product using weighted principal component and Taguchi method

This paper presents a hybrid approach utilizing Principal Component Analysis (PCA) integrated with the Taguchi Method to address a multi-criteria optimization problem in the turning process of a cylindrical mild-steel workpiece using a High-Speed Steel tool. Suitable turning process parameters are identified to comply with multiple requirements and assessment of surface quality. The traditional Taguchi method has limitations in solving multi-criteria optimization problems since quality characteristics need to be uncorrelated or independent. To overcome this, PCA was employed to identify independent or uncorrelated quality indices named Principal Components. The study demonstrates the feasibility of PCA and the Taguchi method to forecast an optimal parameter setting for assessing surface quality, followed by confirmatory tests. This paper showcases the mix of PCA and Taguchi methods for multi-criteria optimization and off-line control of correlated multiple surface quality characteristics in turning processes.

Bacteriological quality assessment of poultry chicken meat and meat contact surfaces for the presence of targeted bacteria and determination of antibiotic resistance of Salmonella spp. in Pakistan

During the slaughtering process, the meat product cross-contaminates with the surrounding contact surfaces. This study aimed to assess the level of microbial contamination of poultry chicken meat and contact surfaces at poultry slaughterhouses in the Hyderabad and Jamshoro districts of Pakistan. A total of 38 slaughter shops were selected, and from each shop, three types of samples were collected. All the samples were assessed for the presence of three microbes, Salmonella, Shigella, and E. coli by using some culture-based techniques, and for Salmonella, antibiotic resistance was also determined. Results revealed that Shigella was present in 86.8% of knives, 94.7% of chopping board and 97.3% of meat samples. While, the E. coli was present in 86.8% of knife, 97.3% of chopping board, and 97.3% of meat samples. Salmonella was detected in 97.3% of knives, 92% of chopping boards, and 97.3% of meat samples. All the isolates of Salmonella exhibited resistance to one or more antibiotics. Resistance to ampicillin, gentamicin, cefotaxime, erythromycin, neomycin, streptomycin, and sulphamethoxazole were evident in 91.7%, 25.6%, 32.1%, 40.3%, 33.9%, 34.8%, and 52.2% respectively. However, only 6.4% of isolates showed resistance to azithromycin (6.4%), and none of them showed resistance to ceftazidime. Moreover, 61.4% (67/109) of isolates were multiple drug-resistance (MDR). A high prevalence of Salmonella, Shigella, and E. coli in meat and on contact surfaces can be considered a major risk for human health. It is vital to continue developing strategies to limit the danger of foodborne diseases in slaughtering facilities.

On communicating extruded aluminium surface quality along the supply chain – a customer approach to sustainable surfaces

Today, far too many products are scrapped due to surface related issues, products with perfect function but with minor surface blemishes. The complaints are often offset by goodwill commitments from suppliers at great cost to them and delivery delays and lead time costs for customers. The reason is that the industry relies on several non-standardized classification systems for surface quality that are based on various combinations of and designations for surface defects, assessed by visual inspections at a defined distance to determine the severity of any detected surface deviations. These similar classification systems provide far too much scope for subjective and non-repeatable assessments causing communication problems between customer and producer at all stages in the supply chain. To challenge this situation, a common toolbox to communicate, describe and define surface quality should be developed, i.e. a standardisation of surface quality assessment including various effects and defects with a jointly established nomenclature and evaluation parameters. This work presents the first step of a research project bringing together 11 suppliers and OEMs along the supply chain, from the delivery of raw aluminium to finished alumina profiles included in consumer products. The final goal of the project is to develop an ‘objective classification of visual requirements’ on alumina profiles towards increased sustainability and decreased material wastage. Presented result is a common terminology with links to the process chain, surface defect geometry and visual appearance aiming at making the communication between producers and buyers of the aluminium profiles clearer and more unambiguous when it comes to specification and requirements of profile surfaces in each of the supply-chain links. Future work will add measurable parameters specifying surface quality.

Single-Point and Surface Quality Assessment Algorithm in Continuous Production with the Use of 3D Laser Doppler Scanning Vibrometry System.

In the current economic situation of many companies, the need to reduce production time is a critical element. However, this cannot usually be carried out with a decrease in the quality of the final product. This article presents a possible solution for reducing the time needed for quality management. With the use of modern solutions such as optical measurement systems, quality control can be performed without additional stoppage time. In the case of single-point measurement with the Laser Doppler Vibrometer, the measurement can be performed quickly in a matter of milliseconds for each product. This article presents an example of such quality assurance measurements, with the use of fully non-contact methods, together with a proposed evaluation criterion for quality assessment. The proposed quality assurance algorithm allows the comparison of each of the products' modal responses with the ideal template and stores this information in the cloud, e.g., in the company's supervisory system. This makes the presented 3D Laser Vibrometry System an advanced instrumentation and data acquisition system which is the perfect application in the case of a factory quality management system based on the Industry 4.0 concept.

Assessment of the hydrochemical composition of groundwater and development of new operating scenarios for water supply (Tajikistan)

The main study task was dictated by the growth rate of water consumption, namely the development of new scenarios for the exploitation of groundwater for water supply purposes. The assessment of surface and groundwater quality in the area showed a tendency to increase mineralization, hardness, a number of chemical components (up to exceeding the limited concentration). Analysis and interpretation of long-term groundwater chemical data, as well as the intensity of surface runoff, within the study area, allowed us to identify anthropogenic influence on the amount of runoff. According to the results of the study, the growth of infiltration nutrition (due to the expansion of irrigation areas) is reflected into deterioration of groundwater quality. In addition, the existing water intakes are located within the city limits, which creates an additional threat of bacterial and organic pollution. The new scenarios of groundwater exploitation are based on the features of the hydrogeological section, the results of hydrochemical studies, the amount of groundwater reserves of individual aquifers, calculations of sanitary protection zones of water intakes. The Amwells module (ANSDIMAT software package) was used to estimate groundwater reserves, so an analytical model was created based on the actual material. Thus, an extremely demanded detailed characterization of the groundwater of the studied area was carried out, some of which are suitable for use as drinking water.

Ground Surface Quality Assessment Using P-wave Velocity from 2-D Seismic Refraction Method

A good strength level of the ground surface is the main concern in an area with rapid housing infrastructure development, such as Baitussalam district-Aceh Besar, Indonesia. A seismic refraction method was applied with three similar profile lines using PASI 16S – 24P equipment and 10 Hz vertical geophones to identify the sub-surface layer. The result was processed using Winsism software and Surfer 8. The results of seismic refraction were deduced and correlated with conventional geotechnical investigation obtained by a previous study. The results of 3 survey lines show that the area has two main layers. The first layer was interpreted as overburden (soil and clayey sand) with a compressional wave velocity (Vp) value of fewer than 1.8 km/s. The second layer produces a high velocity of more than 2 km/s. This second layer is interpreted as highly to moderately weathered rock. The results of seismic refraction surveys of the present study suggest a reasonably good correlation with the standard penetration test (SPT) and rock quality designation (RQD) obtained in the previous investigation. The strength level of the second layer showed N-SPT of 65 and RQD of at least 50%.

Self-Supporting Structures Produced through Laser Powder Bed Fusion of AlSi10Mg Alloy: Surface Quality and Hole Circularity Tolerance Assessment

In the context of the Design for Additive Manufacturing (DfAM), the elimination and/or reduction of support structures for the parts is a key issue for process optimization in terms of sustainability and surface quality. In this work, the assessment of the surface quality of overhanging thin walls and unsupported holes with different diameters (4, 6, 8 mm) was carried out through confocal microscopy, SEM-EDS analysis and CMM measurements. To this aim, two different types of AlSi10Mg alloy parts were produced with the L-PBF technology, having self-supporting features such as thin walls and holes with different overhang angles. The results showed that (i) unsupported, down-facing surfaces can be printed consecutively without supports up to a 30° overhang angle and with a surface roughness (Sa) ranging from 3 to 40 µm; (ii) unsupported holes can be produced as well, having a mean circularity tolerance ranging from 0.03 to 0.55 mm, regardless of the diameter value; (iii) density and microstructure analysis both revealed that the parts’ integrity was not affected by the design choices.

Assessment of surface quality in extrusion honing process using dimensional analysis approach

It is critical to obtain the desired surface quality on machined parts’ internal and external portions. The estimated level of surface texture can be induced on the outer regions using traditional finish machining processes such as grinding, honing, and so on. While the problem emerges when processing miniature core components such as micro bores and inlet/outlet valves. The EH approach overcomes this limitation of the conventional finishing method. It is a novel micromachining process that extrudes pressured flow of carrier media combined with abrasives into the confined passage to generate the desired level of surface texture. Due to the abrasion process, micromachining occurs by taking away negligible stock material. The present study focus on the impact of the number of passes at the specimen’s entry and exit sides of the carrier media. The improvements in the surface finish (Ra) on both sides, i.e. entry and exit, are also evaluated. A dimensionless expression for Ra is also developed. The relation is implemented using Buckingham’s π theorem, and the developed model is compared with experimental results. SEM analysis is made to portray surface texture produced by selected

Assessment of Surface Quality in Extrusion Honing Process Using Dimensional Analysis Approach

It is critical to obtain the desired surface quality on the internal and external portions of machined part. The estimated level of surface texture can be induced on the exterior regions using traditional finishing processes such as grinding, honing, and so on. While the problem emerges when processing core miniature components such as micro bores, inlet/outlet valves etc. The EH process overcomes this limitation of conventional finishing method. It is a novel micro machining process that extrudes the pressured flow of carrier media blended with abrasives into the confined passage to generate desired level of surface texture. Owing to abrasion process micro machining occurs by taking away the negligible amount of stock material. The present study focuses on the impact of number of passes at the specimen’s entry and exit sides of the carrier media. The improvements in surface finish (Ra) on both side i.e., entry and exit are evaluated as well. A dimensionless expression for Ra is also developed. The relationship is implemented using Buckingham’s π theorem and comparison of developed model is performed with experimental results. SEM analysis is made to portray surface texture produced by selected process parameters such as number of passes, volume fraction and grit size of abrasive grains.

Tool wear mechanisms and surface quality assessment during micro-milling of high entropy alloy FeCoNiCrAlx

High entropy alloys (HEA) are widely used in high-strength tools, high-temperature molds, and corrosion-resistant components. This work focused on tool wear and surface quality during micro-milling HEA FeCoNiCrAlx (x = 0.1, 0.5, 1) with different Al element content. Tool wear appeared more severe with the increase of Al element content. Tool wear patterns mainly included flank wear, adhesive material, micro-chipping, coating peeling, substrate tearing and edge fracture. The combined effects of adhesive wear, mechanical shock damage, abrasive wear, and oxidative wear were the primary reasons of tool wear mechanisms, while the diffusion wear was less noticeable. Moreover, the surface qualities including surface roughness, surface defects and edge burrs changed worse with the increase of Al element content and tool wear.

Quality assessment of surface and sediment pore waters and their behaviours using WQI index and geostatistics approaches. Case study: El Malleh dam reservoir, Morocco

The El Malleh dam reservoir is an important water source for irrigation and protection against flooding in the Mohammedia region of the kingdom of Morocco. However, flash floods threaten the sustainability of the reservoir by sedimentation and water quality contamination. Pollution sources could arise from sediment mobilization in the reservoir bottom, or carry by water flow from the watershed to the dam reservoir. The current study evaluates the surface and pore water quality, focuses on their behaviour based on the laboratory results, the Water Quality Index (WQI) and statistical analysis. The results show that the concentration of nutrients was not significant. The concentrations of major elements differ from surface waters to pore waters and from one parameter to another. For instance, the Cl concentration in the surface water ranged from 852 mg L−1 to 1065 mg L−1, and from 10 mg L−1 to 7810 mg L−1 for pore water. Besides that, the calculation of WQI indicated that the sediment pore water quality was unsuitable, and the surface waters quality was in a poor and very poor category.

Studies of mechanical and technological parameters and evaluation of the role of lustrous carbon carriers in green moulding sands with hybrid bentonite

Green moulding sands containing special carbonaceous additives, which are the source of lustrous carbon (LC), are discussed in this paper. Five potential lustrous carbon carriers, i.e., two types of hard coal dust (No.1 and No.2), amorphous graphite (No.3) and two hydrocarbon resins (No.4 and No.5), were selected for tests as carbonaceous additives to conventional moulding sands. To better emphasize the differences in the additives used, reference green moulding sand (GMS1) was prepared and subjected to a wide range of basic tests focussed on technological parameters, such as permeability (Pw), friability (Fw), Dietert mouldability test (PD) and compactability (Z) and mechanical parameters, such as compressive strength (Rcw), tensile strength (Rmw), strength in the transformation zone (Rkw). The proposed comprehensive spectrum of tests was repeated on sands with five carbonaceous additives. The most important for the use of additives as carbon carriers was to interrelate the content of lustrous carbon (LC), loss on ignition (LOI) and the obtained results of mechanical and technological tests carried out on conventional moulding sands with the surface quality of iron castings. For this purpose, a series of iron castings was made in the prepared moulding sands and used for the assessment of surface quality based on a number of roughness parameters (Ra, Rz, Rp, Rq, Rv, Rlr, RSm). As a result of the studies it was found that the carbonaceous additives proposed for use help to obtain high-quality surfaces in iron castings.

A study on the roughness detection for machined surface covered with chips based on deep learning

In the cutting process, the visual surface roughness detection method is easily affected by interference factors such as chip, resulting in measurement accuracy errors and wrong quality assessment of the machined surfaces. This work proposes a method of anti-interference roughness detection based on image inpainting and convolutional neural network model. A CNN classification model was established to detect the machined surface images. Meanwhile, the established CBAM Res-Unet semantic segmentation model and PConv-Net image inpainting model are combined to locate and inpaint the chip interference regions. Among them, the CBAM Res-Unet model realizes the automatic positioning and segmentation of the chip interference region, the mask image output by the model is used in the input of the PConv-Net image inpainting model. The PConv-Net model adopts partial convolutional strategies for full convolution and realizes the automated update mask image mechanism. It can inpaint any non-central and irregular regions and result in a great detection for machined surfaces covered with random and irregular chip interference regions. Furtherly, the CNN model, CBAM Res-Unet model and PConv-Net model are combined to a complete anti-interference detection method. The detection success rate of our method can reach 90.0 % for images with chip interference, the relative error of the detection can be controlled within 6.8 % and the average detection time of a single image is 0.79 s, which has high detection accuracy and efficiency and provides a certain technical support for the surface detection.

Assessment of Surface and Groundwater Quality in and Around Benue State Brewery Limited (BBL) in Makurdi Town, Benue State, Nigeria.

Assessment of Surface and Groundwater Quality in and Around Benue State Brewery Limited (BBL) in Makurdi Town, Benue State, Nigeria.

A deep-learning-based in-situ surface anomaly detection methodology for laser directed energy deposition via powder feeding

Laser Directed Energy Deposition via Powder Fed (LDED-PF) based Metal Additive Manufacturing suffers from inferior dimensional accuracy mainly due to thermal cycling, localized heat accumulation, inconsistency in the powder stream, deviation in the speed of the motion system and powder focus, etc. In-situ monitoring, along with defect detection algorithms, can be used for avoiding unpredictable build failures while minimizing the time and cost of exhaustive ex-situ characterization techniques. Existing surface quality assessment techniques for LDED-PF mainly focus on intermittent process monitoring, data acquisition, data post-processing, feature extraction, and error identification. The present work investigates the development of a novel in-situ monitoring software platform that can be used for the surface anomaly detection of LDED-PF parts using machine learning techniques. Despite the existing methods in the literature, this technique has shown high robustness and high confidence in defect detection regardless of the geometry, and varied density of point clouds. First, a novel method is developed to calibrate the laser line scanner with respect to the robotic end-effector with the sub 0.5 mm accuracy. Subsequently, 2D surface profiles obtained from the LDED-PF built part surface using the laser scanner are stitched together to create an accurate 3D point cloud representation. Further, the point cloud data is processed, and defect detection is carried out using unsupervised learning and supervised (deep) learning techniques. The overall accuracy and mean IoU of 91.3 % and 83.3 % are achieved, respectively. The study paves the way for the development of automatic tool path generation for the LDED-PF process to build high-quality components.

Quantitative Surface Quality Assessment of Car Outer Panels with a Virtual Light Room

Perception is reality. A customers’ perception about the quality of a car is closely linked to the aspect of its outer panels and that reality translates into what motivates customers to choose one car over another. The smoothness of the panels, how much gap is visible and how that looks; these visual cues are considerations within a customer’s decision-making process. The process of choosing a new car is certainly subjective and varies from customer to customer, but Original Equipment Manufacturers (OEMs) agree that the visual appeal of the body of a car is a key factor. Building a car only to find surface imperfections results in huge costs in postproduction rectifying those perceived defects. The further into production these defects are found the more expensive it is to fix them. Some OEMs release cars into the buying cycle knowing that their engineering teams are still struggling to fix surface defects. There is a solution to this though. Numerical simulation. This action can and should be used to find surface defects very early in the design process. Surface quality assessment via numerical simulation is achieved by analysing different contours that relate stress or strain values. Other subjective criteria exist, but it is often very difficult to ascertain if a surface defect is severe enough to be detected by human eye. This paper describes a simulation methodology that, when used along with a software that reads surface light distortions and rates them, will give reliable results allowing engineers to fix problems before a car is built. This technology was developed using actual data supplied by a partnering OEM. Current examples will be presented, comparing parts “as designed” with parts “as manufactured”. After manufacturing parts will show variations caused by the stamping process such as skid marks, bumps, hollows, etc. All that can be accurately predicted by simulation.

Assessment of Surface and Groundwater Quality and their Suitability for Irrigation Purposes in Odisha, Eastern India

The study was conducted during the pre-monsoon period in April-May 2019 to monitor the quality of different water sources for assessing their suitability for irrigation purposes in Odisha state of eastern India. Twenty-seven surface water and twenty-one groundwater samples were collected and analyzed for chemical parameters. The suitability of the surface and groundwater for irrigation were evaluated based on pH, residual sodium bicarbonate (RSBC), electrical conductivity (EC), sodium adsorption ratio (SAR), Adjusted SAR (Adj. SAR), residual sodium carbonate (RSC), soluble sodium percentage (SSP), permeability index (PI), Kelly’s ratio (KR), Chloride (Cl-), boron (B), nitrate (NO3-), iron (Fe), Manganese (Mn), zinc (Zn), copper (Cu), chromium (Cr) and cadmium (Cd). Results showed that three rivers, Mahanadi, Brahmani and Bansadhara, were found medium salinity (EC 0.25-0.75 dSm-1), and all the rivers have no sodicity problem with RSC within the permissible limit of 2.5 meqL-1 and free of chloride and boron toxicity. All the surface water samples were safe with respect to Zn (2 mgL-1), Cu (0.2 mgL-1), Fe (5 mgL-1), Mn (0.2 mgL-1) and Cr (0.1 mgL-1). Four rivers were exceeded the maximum permissible limit of Cd. All the groundwater samples were found below the toxicity level and safe concerning Cl-, NO3-, B, Zn (2 mgL-1), Cu (0.2 mgL-1), Fe (5 mgL-1), Mn (0.2 mgL-1) and Cr (0.1 mgL-1) where Cd content of three sources exceeded the MPL (OUAT Agronomy Farm 0.011 mgL-1, Putibandh of Sambalpur 0.011 mgL-1 and Rourkela 0.010 mgL-1). Results depicted that all the surface water samples collected from nine different rivers are of good quality and suitable for irrigation purpose except for some specific limitations. Among all the groundwater sources, groundwaters of the Putibandh area in Sambalpur district are found very poor in quality and unsuitable for irrigation.

SPHERICAL TRANSFORMER FOR QUALITY ASSESSMENT OF PEDIATRIC CORTICAL SURFACES.

Brain cortical surfaces, which have an intrinsic spherical topology, are typically represented by triangular meshes and mapped onto a spherical manifold in neuroimaging analysis. Inspired by the strong capability of feature learning in Convolutional Neural Networks (CNNs), spherical CNNs have been developed accordingly and achieved many successes in cortical surface analysis. Motivated by the recent success of the transformer, in this paper, for the first of time, we extend the transformer into the spherical space and propose the spherical transformer, which can better learn contextual and structural features than spherical CNNs. We applied the spherical transformer in the important task of automatic quality assessment of infant cortical surfaces, which is a necessary procedure to identify problematic cases due to extremely low tissue contrast and strong motion effects in pediatric brain MRI studies. Experiments on 1,860 infant cortical surfaces validated its superior effectiveness and efficiency in comparison with spherical CNNs.

An overview on dry eye disease diagnosis: options for new non-invasive testing technologies

This literature review intends to provide an overview of the new non-invasive testing technologies and their role in the diagnosis of dry eye disease (DED). Including imaging technologies of tear volume, tear film stability, meibomian glands morphology and function, corneal morphology, biomarkers and ocular surface temperature, as well as tear osmolarity, optical quality, blinking test and so on. New testing technologies can provide an indirect and objective assessment of the ocular surface, tear condition and visual quality. Testing technologies, such as tear volume, meibography and tear osmolarity have been widely recognized and applied in clinical practice, showing higher specificity and sensitivity than traditional tests. Others, such as strip meniscometry, interferometer, light scattering technology, double-pass system, blinking test and so on, are currently in the stage of clinical research and improvement, and may translate to routine clinical detection techniques in the future. The new non-invasive testing technologies can non-invasively evaluate the ocular surface and tears, and measure the changes of components related to the disease, which play an important role in the diagnosis, classification, clinical management and curative effect evaluation of DED.