Journal articles on the topic 'Manufactures – Defects'
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1
Song, Wen Yan, Xin Guo Ming, Zhen Yong Wu, Zhi Tao Xu, and Li Na He. "A Bayesian Network Based Approach to Defect Prediction in New Product Development." Advanced Materials Research 328-330 (September 2011): 241–45. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.241.
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The development of new product with low cost and reliable quality is one of important means to improve customer satisfaction and increase manufactures’ profits. It is necessary to identify the key factors affecting product defects and control them early in the new product development (NPD) process with defect prediction methods, because defect prediction can effectively avoid or lower testing and unnecessary rework costs. The author proposes a new product defect prediction approach on the basis of Bayesian Network theory for decision-making in the NPD process. The proposed approach makes use of Bayesian Network to simulate defects’ formation process, and it has a strong learning ability without requiring much data at the beginning of defect prediction. Product developers can easily predict the probability of defect occurrence of new products with this practical approach. The proposed product defect prediction approach can also help to focus on key factors influencing defects most. An example of turbine valve development is used to illustrate the proposed defect prediction approach. Also, recommendations for future research have been suggested.
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Augustine, B. S. M. "Research in the Area of Material Failure in Aeroengine." Applied Mechanics and Materials 766-767 (June 2015): 562–70. http://dx.doi.org/10.4028/www.scientific.net/amm.766-767.562.
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The present investigation focuses on the influence of failure of material during maintenance of aeroengines installed in helicopters. This research study is on fifty eight engines withdrawn prematurely over a period of five years from the helicopters operated around the country before the completion of their actual life periods due to the failures of materials as serious defects. The effect of the trend of these defects was investigated thoroughly based on the analysis reports on the observation from the stripping laboratory test and the study on the investigation done thereafter at the defect investigation agency of the engine at overhaul shop. The entire study of these defects is carried out from the facts received from the analytical and experimental investigations. The remedial measures are identified and established after a deep evaluation. The causes of the factors attributing to the development of defects are found out by research analysis. They are mainly based on design, qualities of material, poor standard in quality control procedures and maintenance practices. They are implemented by the users for the achievement of reduction in the occurrence of such defects towards a significant improvement in the subsequent maintenance of aeroengines. Further, the remedial measures, besides prevention of occurrence of such defects has a great impact on the development of a high degree of aeroengine maintenance The final results of this research study are prepared as suggested measures to be forwarded for implementation to manufactures, overhaul agency and operators
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Mikhaylova, N. A., E. I. Kosarina, A. A. Demidov, and P. V. Suvorov. "Radiation control of blanks manufactured using additive technology by digital radiography." Industrial laboratory. Diagnostics of materials 88, no. 10 (October 24, 2022): 48–53. http://dx.doi.org/10.26896/1028-6861-2022-88-10-48-53.
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Additive technologies, namely selective laser melting (SLM), are often used in manufacturing products of critical duty. At the same time, the SLM process may be accompanied by the appearance of specific defects in the product. We present the results of radiation monitoring of aviation blanks manufactures using additive technology by digital radiography. A digital detector system was used as an X-ray converter. It is shown that the methods of film radiography traditionally used for control in the case of aircraft objects are not always effective. The method of digital radiography, on the contrary, is the most adequate. Comparison of the results of digital radiography with data of traditional radiography revealed that the time spent on radiation monitoring when using an automated manipulator is significantly reduced, while the monitoring performance increases dramatically. The results obtained can be used to improve the methods of radiation monitoring of aircraft objects manufactured using additive technologies.
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Muhin, Oleg. "Forecasting Locomotive Run Dynamics Given the Impact of Defects and of Junction Up-grading." Bulletin of scientific research results 2022, no. 4 (December 24, 2022): 90–105. http://dx.doi.org/10.20295/2223-9987-2022-4-90-105.
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Purpose: To improve planning system for depot and factory repairs and for locomotive up-grades in the conditions of new rolling stock delivery on the basis of life-cycle contract by the way of the development and application of mathematical model for prognosing average daily and linear runs given the impact on run of technical-technological, seasonal and random fac-tors as well as defects, limiting junctions, and their upgrading. Methods: To achieve the set goal realization, the impact assessment for non-productive downtime of new locomotives at repairs as a result of clearing of junction defects and an equipment and of downtime in wait-ing for planned repairs on dynamics of average daily and linear runs was carried out. Based on the method of multidimensional spectral singular analysis and the prognosis of time series Multi-Channel Singular Spectrum Analysis, the mathematical model on run prognosis which algorithm for, has been embodied in integrated programming environment Visual Studio (2019) on C++ programming codes. Results: Run determination method given junction and equipment possible defects and given being planned upgrading has been proposed. Practical importance: In the conditions of life-cycle contract application which frames in, the participa-tion of locomotives and their components manufacturers in the technical support of supplied products throughout their entire service-life is implied, the usage of the proposed model at re-pair program monthly, quarterly and annual planning, would reduce the downtime in waiting for putting into a repair position on account of more accurate forecast, rationally distributed repairs, materials, stock of linear equipment between service manufactures.
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Sun, Tianyu, Lei Qiao, and Mingjun Xia. "Effective Failure Analysis for Packaged Semiconductor Lasers with a Simple Sample Preparation and Home-Made PEM System." Photonics 8, no. 6 (May 24, 2021): 184. http://dx.doi.org/10.3390/photonics8060184.
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As the application requirements of semiconductor lasers continue to increase, severe challenges are brought to the reliability of semiconductor lasers. In order to promote the study of laser failure, this paper proposes an effective failure analysis method for packaged semiconductor lasers with a simple sample preparation and home-made photon emission microscopy (PEM) system. The new simple sample preparation process for failure analysis is presented and the necessary polishing fixture is designed so that sample can be obtained without expensive and complex micro-/nano-processing. Two types of home-made PEM experimental systems were established for observing the failure from the front facet and active region of semiconductor lasers. Experimental results showed that, with the proposed sample preparation flow, the home-made PEM experimental system effectively observed the leakage defects from the front facet and dark spot defects (DSDs) in the active region of semiconductor lasers. The method can help researchers and laser manufactures to perform effective failure analysis of packaged semiconductor lasers.
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Fitriana, Rina, and Nur Anisa. "Perancangan Pebaikan Kualitas Produk Baut dan Sekrup Menggunakan Metode Six Sigma dan Data Mining di PT. A." JURNAL TEKNIK INDUSTRI 9, no. 1 (July 4, 2019): 46–53. http://dx.doi.org/10.25105/jti.v9i1.4786.
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PT. A is a manufacturing company that manufactures bolts and screws in accordance with customer demand. This study aims to determine the type of dominant defect that causes a decrease in quality, the factors that cause disability and apply proposed improvements to reduce the level of disability. Improvements are made by using the Six Sigma method, namely the DMAIC stage and making a decision tree (decision tree) using the Data Mining application. Where for the DMAIC stage are: Define, Measure, Analyze, Improvement, and Control (DMAIC). At the define stage, it was found that the production process with the largest number of defects was in the process of heading with the number of defects exceeding the target of 600 PPM (parts per million) that had been determined by the factory during April - June 2017. The heading process was the most important problem focused on the research conducted. The results of identification of Critical to Quality (CTQ) for the characteristics of attribute defects in the production of bolts and screws in the heading process are head burry, head no center, head crack, and body scratch. The second stage is the measure stage, where the control used by statistical process control (SPC) for attribute data is using the P control map and is known to have a sigma 3.50 level with a DPMO value of 22,727. The third stage is the Analyze stage, analyzing the problems of the four types of defects using the Ishikawa diagram. The improvement stage resulted from the decision tree in data mining processing that is obtained by standardizing inspections with seven IF THEN RULE functions, and making maintenance activity plans in the heading process. After implementation, there is a control stage, the results of the analysis show that after implementation using the data mining method and the Six Sigma method, the sigma value has increased which was originally 3.50 to 3.67.
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Bilotta, Antonio, and Gian Piero Lignola. "Effects of Defects on Bond Behavior of Fiber Reinforced Cementitious Matrix Materials." Materials 13, no. 1 (January 1, 2020): 164. http://dx.doi.org/10.3390/ma13010164.
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High-strength fibers embedded in inorganic matrix i.e., Fiber Reinforced Cementitious Mortar materials (FRCM) are commonly used as strengthening technique for existing masonry structures, due to the low sensitivity to debonding phenomena between substrate and matrix. Nevertheless, the use of lime or cement-based matrix instead of epoxy adhesive implies that attention has to be paid to the bond behavior between the fibers and the matrix, since sliding phenomena and cohesive failures in the mortar matrix can occur. The paper aims to investigate the effect of the mechanical properties of fiber and matrix on the FRCM efficiency, and potential geometrical defects, typical of real applications. The aim is to analyze the mechanical behavior of the FRCM system by simulating hypothetical bond tests, as they are usually performed in laboratories. The bond test has a significant role, as it is used for the qualification of the material, providing sometimes very scattered results. Hence, it is particularly important and greatly discussed in the scientific community and among manufactures and practitioners. The purpose is to understand where this variability could derive from and possibly how to contain it, to improve the characterization of FRCM systems. A mechanical model has been proposed to simulate the usual bond test to focus and stress the way in which each fiber slips out of the matrix as the load increases; and this has been recognized as the main reason for scattered results in bond tests. The model was then applied to the typical cases of PBO-FRCM and Glass-FRCM, hence considering different ratios for the fiber and matrix properties.
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Blevins, Kier Maddox, Richard M. Danilkowicz, Amanda N. Fletcher, Nicholas B. Allen, Lindsey G. Johnson, and Samuel B. Adams. "In situ 3D bioprinting of musculoskeletal tissues in orthopedic surgery." Journal of 3D Printing in Medicine 6, no. 1 (March 2022): 25–36. http://dx.doi.org/10.2217/3dp-2021-0022.
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Annually, millions of Americans require some form of reconstructive surgery as the result of a traumatic injury, degenerative process or pathologic state. In the field of orthopedic surgery, the gold standard for augmenting bone, cartilage and soft tissue defects has been through the application of grafts, prostheses and soft-tissue flaps. Recently, there have been great advances within the field of tissue engineering including the development of 3D-bioprinting technology. Bioprinting uses biomaterials and cells to create 3D tissue-mimicking structures aimed at repairing or replacing damaged tissues. Further developments have led to in situ bioprinting which manufactures the tissue directly at the site of repair through handheld or portable 3D-bioprinting devices. Challenges still exist in implementing this technology. However, there is hope that one day this technology will be equipped for the operating room or clinic.
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Kumar, Satish, Tushar Kolekar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Atef Zaguia, and Chander Prakash. "A Low-Cost Multi-Sensor Data Acquisition System for Fault Detection in Fused Deposition Modelling." Sensors 22, no. 2 (January 10, 2022): 517. http://dx.doi.org/10.3390/s22020517.
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Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits such as rapid prototyping, cost-effectiveness, flexibility, and a sustainable manufacturing approach. Along with such advantages, a few defects occur in FDM products during the printing stage. Diagnosing defects occurring during 3D printing is a challenging task. Proper data acquisition and monitoring systems need to be developed for effective fault diagnosis. In this paper, the authors proposed a low-cost multi-sensor data acquisition system (DAQ) for detecting various faults in 3D printed products. The data acquisition system was developed using an Arduino micro-controller that collects real-time multi-sensor signals using vibration, current, and sound sensors. The different types of fault conditions are referred to introduce various defects in 3D products to analyze the effect of the fault conditions on the captured sensor data. Time and frequency domain analyses were performed on captured data to create feature vectors by selecting the chi-square method, and the most significant features were selected to train the CNN model. The K-means cluster algorithm was used for data clustering purposes, and the bell curve or normal distribution curve was used to define individual sensor threshold values under normal conditions. The CNN model was used to classify the normal and fault condition data, which gave an accuracy of around 94%, by evaluating the model performance based on recall, precision, and F1 score.
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Mochammad Iqbal Syidik, M Dzikron, and Iyan Bachtiar. "Perbaikan Kualitas Produk Tas Kulit dengan Menggunakan Metode Teorija Rezhenija Izobretatelskih Zadach (TRIZ) pada CV. X – Bandung." Jurnal Riset Teknik Industri 1, no. 1 (July 6, 2021): 43–48. http://dx.doi.org/10.29313/jrti.v1i1.95.
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Abstract. CV. X is a company engaged in the leather industry that manufactures wallets, bags and key chains. The company experienced a decrease in sales volume due to a decrease in product quality from defective products in the company. Leather bags have an average percentage of disability of 2.39% in 2017-2018 from the company's disability limit of 2%. The existence of these defective products requires companies to improve product quality to reduce the occurrence of defects. The method used to solve the problems that are being faced by the company is the Seven Tools Quality Control method to identify the causes of product defects, while the Rezhenija Izobretatelskih Zadach (TRIZ) method is used to design a product quality improvement plan. The result of data processing which becomes the main priority is defect cutting. The causes of cutting defects include decreased work concentration, inadequate workers, poor physical condition, no machine maintenance, blunt cutting machines, high cutting machine use intensity, work environment, hot room temperature, lack of work space lighting. All causes of product defects are designed to improve the quality of leather bag products by creating visual controls, forms for worker health, cutting knife replacement machines, installing air conditioners, and adding lights to the sewing machine.
Abstrak. CV. X merupakan perusahaan yang bergerak di bidang industri kulit yang memproduksi dompet, tas, dan gantungan kunci. Perusahaan mengalami penurunan volume penjualan yang disebabkan karena adanya penurunan kualitas produk dari produk cacat di perusahaan. Tas kulit memiliki rata-rata persentase kecacatan sebesar 2,39% pada tahun 2017-2018 dari batas kecatatan yang ditetapkan perusahaan sebesar 2%. Adanya produk cacat tersebut mengharuskan perusahaan melakukan perbaikan kualitas produk untuk mengurangi terjadinya kecacatan. Metode yang digunakan untuk menyelesaikan permasalahan yang sedang dihadapi oleh perusahaan yaitu metode Seven Tools Quality Control untuk mengidentifikasi penyebab terjadinya kecacatan produk, sedangkan metode Teorija Rezhenija Izobretatelskih Zadach (TRIZ) digunakan untuk membuat rancangan perbaikan kualitas produk. Hasil pengolahan data yang menjadi prioritas utama yaitu cacat potong. Penyebab cacat potong diantaranya yaitu konsentrasi kerja menurun, pekerja kurang hati-hati kondisi fisik kurang baik, tidak ada perawatan mesin, mesin potong tumpul, intesitas penggunaan mesin potong tinggi, lingkungan kerja, suhu ruangan panas, pencahayaan ruang kerja kurang. Semua penyebab cacat produk dibuat rancangan perbaikan untuk meningkatkan kembali kualitas produk tas kulit dengan membuat visual control, form untuk kesehatan pekerja, mesin penggantian pisau potong, pemasangan AC, serta penambahan lampu pada meisn jahit.
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Allam, Abdelrahman, Medhat Moussa, Cole Tarry, and Matthew Veres. "Detecting Teeth Defects on Automotive Gears Using Deep Learning." Sensors 21, no. 24 (December 19, 2021): 8480. http://dx.doi.org/10.3390/s21248480.
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Gears are a vital component in many complex mechanical systems. In automotive systems, and in particular vehicle transmissions, we rely on them to function properly on different types of challenging environments and conditions. However, when a gear is manufactured with a defect, the gear’s integrity can become compromised and lead to catastrophic failure. The current inspection process used by an automotive gear manufacturer in Guelph, Ontario, requires human operators to visually inspect all gear produced. Yet, due to the quantity of gears manufactured, the diverse array of defects that can arise, the time requirements for inspection, and the reliance on the operator’s inspection ability, the system suffers from poor scalability, and defects can be missed during inspection. In this work, we propose a machine vision system for automating the inspection process for gears with damaged teeth defects. The implemented inspection system uses a faster R-CNN network to identify the defects, and combines domain knowledge to reduce the manual inspection of non-defective gears by 66%.
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Teverovsky, Alexander. "The Effectiveness of Screening Techniques for Revealing Cracks in High Volumetric Efficiency MLCCs." International Symposium on Microelectronics 2013, no. 1 (January 1, 2013): 000651–56. http://dx.doi.org/10.4071/isom-2013-wp23.
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Multilayer ceramic capacitors (MLCCs) constitute the majority of components used in electronic assemblies and most of their failures are related to cracks. It is often assumed that dissipation factor (DF), insulation resistance (IR), and breakdown voltage (VBR) are characteristics that are sensitive to the presence of mechanical defects, and screening of capacitors by measurements of these characteristics, and by dielectric withstanding voltage (DWV) testing assures high quality products. This work analyzes the effectiveness of these screening techniques for revealing cracks in high-volumetric efficiency, low-voltage ceramic capacitors. Various types of class II dielectric capacitors with rated voltages from 6.3 V to 100 V, and capacitances from 0.1 μF to 100 μF from different manufactures were used in this study. Fractures in the parts were introduced mechanically and by thermal shock stress. It has been shown that cracking results in relatively minor variations of capacitance and DF. Absorption currents prevail over leakage currents during standard IR measurements at room temperatures, and at high temperatures the intrinsic leakage currents exceed substantially leakage currents caused by cracking thus masking the presence of defects. Analysis of distributions of breakdown voltages in normal capacitors and capacitors with cracks showed that the majority of defective capacitors can pass the DWV testing. New, more effective methods of electrical testing and possible improvement of the existing techniques are discussed.
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Bhattacharjee, Debraj, Prabha Bhola, and Pranab K. Dan. "Modelling of Safe Driving Assistance System for Automotive and Prediction of Accident Rates." International Journal of Ambient Computing and Intelligence 10, no. 1 (January 2019): 61–77. http://dx.doi.org/10.4018/ijaci.2019010104.
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This research article attempts to analytically determine the factors, significant for safety, in connection with driving of automotives as well as to develop a conceptual model of the driving assistance system, using the knowledge about such factors. Millions of casualties due to road accidents, happen worldwide every year and the annual average of lives lost in India alone is about hundred and fifty thousand. The causes of such accidents are attributed to road characteristic and condition, driving faults, driving conditions or traffic environmental factors and defects or functional failure in vehicle mechanism. Studies have focused primarily on these factors without associating the ‘weather' which has been reported as in a work but as an isolated factor without including the above three. This work includes all the four stated factors in modelling the driver assistance system for automatic speed control with warning system module. Further, to predict accident rates in a particular region a model using adaptive neuro fuzzy inference system (ANFIS) is proposed in this work, which may be used by the vehicle manufactures to select the right product variant to minimise accidents.
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P, Nagasankar, Sathiyamoorthy V, Gurusamy P, VinothKanna P, Manibharathi D, and Srikanth P. "Reduction of Blowholesin Aluminium High Pressure Die Casting Machine." International Journal of Engineering & Technology 7, no. 3.34 (September 1, 2018): 410. http://dx.doi.org/10.14419/ijet.v7i3.34.19336.
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The main objective of this research is to reduce the blowholes by analyzing the factors which are affected during the casting process. The process parameters are optimized and change is made in the design part to reduce the blowhole and to increase the efficiency of the high pressure die casting machines. Product manufactured from every manufacturing process shows some defects. For supplying quality product to the customer these defects must be reduced. In this work, an attempt is made to reduce the rejection due to the blowhole defect is found out through why-why analysis technique. Process capability of current high pressure die casting manufacturing process is checked. Manufacturing process found capable to manufacture the components. Current problem of blowhole defect is solved making an improvement in design of die which we insert. In gate directions are changed so as to obtain modified improved flow pattern. Using magma flow simulationsoftware existing and modified design has then been compared. It is found that, modified design shows superior results and using this, the defect of blowholes is minimized up to satisfactory level.
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Kováč, Jozef, Jaroslava Kádárová, and Lenka Kalafusová. "Specific Car Manufacturer Recalls." Applied Mechanics and Materials 816 (November 2015): 526–35. http://dx.doi.org/10.4028/www.scientific.net/amm.816.526.
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A variety of engineering errors can cause a defect in vehicles. Problems are usually concentrated on models that were produced during a certain time period at one specific plant. Consumers who encounter such problems can report them, fill petitions or put online complaints on specific car manufacturers. Vehicle defects can cause many problems and even endanger human life. That is why, in the interest of safety, any recall affecting the consumer vehicle should be completed without delay. The paper presents recalls of three car manufacturers, namely: Volkswagen group, PSA, and Kia analyzed between years 2005 to 2015. The results are presented in graphs and diagrams. First part of the paper discusses the current terminology and procedures of car recalls. In the second part the three car manufacturers are presented. Recall analysis creates the third part of the paper and the results are presented in form of graphs and diagrams. Also the error rate of each car manufacturer is calculated and presented in the paper.
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Midor, Katarzyna, and Jozef Žarnovský. "Innovative Use of Quality Management Methods for Product Improvement." Management Systems in Production Engineering 24, no. 4 (December 1, 2016): 264–67. http://dx.doi.org/10.2478/mspe-08-04-2016.
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Abstract Organisations constantly look for new, innovative solutions and methods which could be used to improve their efficiency and increase the quality of their products. Identifying the causes for returns is an important issue for modern companies, as returns are the cause for the increase in production costs and, most importantly, the loss of credibility in the eyes of the client. Therefore, for the company to be able to sustain or strengthen its position on the market, it has to follow the rules of quality management. Especially important is the rule of constant improvement. This rule is primarily connected with preventing errors and defects from occurring at all the stages of the production process. To achieve that, one must, among other things, use quality management tools. The article presents an analysis of causes for returns of a vibrating screen produced by a company which manufactures machinery and equipment for the extractive industry, using quality management tools such as the Ishikawa diagram and Pareto analysis. The analysis allowed for the identification of the causes of client returns which could not be previously identified, and proposing solutions for them.
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Ismail Mourad, Abdel-Hamid, Amir Hussain Idrisi, John Victor Christy, Dinu Thomas Thekkuden, Hamad Al Jassmi, Abdallah S. Ghazal, Mahmmoud Muhammed Syam, and Omar Darwish Ali Ahmed Al Qadi. "Mechanical Performance Assessment of Internally-Defected Materials Manufactured Using Additive Manufacturing Technology." Journal of Manufacturing and Materials Processing 3, no. 3 (August 20, 2019): 74. http://dx.doi.org/10.3390/jmmp3030074.
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Assessment of the mechanical performance of internally-defected components or struc-tures is of crucial importance to many industrial fields such as aerospace, automobile, marine, construction etc. Most of the studies available in the literature include only analytical or numerical solutions, due to difficulty in the manufacturing of a testing sample with a specific internal defect geometry for experimental evaluations. In this study, Fusion Deposition Modeling (FDM) was utilized in the 3D-printing of Polylactic Acid (PLA) samples with internal cracks, aiming to assess their impact on the samples’ mechanical performance. The defect geometry, orientation, location along the sample gauge length and the influence of the process parameters, such as the infill percentage and the material color, were investigated. The influence of the internal defects is more pronounced for a 100% infill rate if compared with a 50% infill rate as a consequence of the porosity. A maximum drop of ~14% in the peak load of defect-free samples was recorded due to the presence of the internal defect. Moreover, the additive color to the PLA material might contribute to the material strength. Generally, the findings of this work could open another door for utilizing the additive manufacturing in many research areas, with potential industrial applications relevant to the assessment of internally-defected materials.
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Mohammadi, Farnoush, Abbas Azari, Nariman Nikparto, and Heliya Ziaei. "Reconstruction of the Occipital and Parietal Congenital Defect with 3D Custom-Made Titanium Prosthesis: A Case Report with Four and a Half Years of Follow-Up and a Brief Review of Literature." Case Reports in Dentistry 2021 (October 20, 2021): 1–6. http://dx.doi.org/10.1155/2021/7027701.
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Management of patients with congenital skull defects requires a multidisciplinary approach. Considering the defect’s location and size, brain protection, and the cosmetic outcome makes such reconstructions challenging. Due to limited resemblance to skull contour and donor site morbidity of autogenous bone grafts, alloplastic materials are widely used for skull reconstructions. Titanium alloys have proper strength values, low infection rates, favorable osseointegration property, and excellent marginal adaptability when manufactured by computer-aided design (CAD) and computer-aided manufacturing (CAM). A 13-year-old female patient presented with congenital defects at the superior third of occipital bone and posterior thirds of the bilateral parietal bones. On CT scan, the exact size and shape of the defect were determined. Using CAD/CAM, a 3D virtual model of the prosthesis was designed and then printed with titanium alloy (TiAl6V4) via additive manufacturing method. The prosthesis was placed on the defect in a total surgery time of only 90 minutes. On 4.5 years of follow-up, the contour of the skull was ideal and the skin over the defect and neurologic status was intact. Due to their biocompatibility and rigidity, custom-made titanium prostheses are promising options for reconstructing complex skull defects.
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Kolanjiappan, S. "Innovative Approach in Introducing Lean Manufacturing Tools in Maintenance of Aircraft." Applied Mechanics and Materials 766-767 (June 2015): 1190–95. http://dx.doi.org/10.4028/www.scientific.net/amm.766-767.1190.
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Lean manufacturing was initially introduced successfully in Japan to enhance the production standard of cars in Toyota Company. These lean principles were initially known as Toyota Production system (TPS)[2]. Lean seeks to eliminate all forms of waste in the manufacturing process—including waste in the maintenance operation[1].This present study about lean principles if could be introduced in maintenance of aircraft the standard of maintenance process could be significantly improved. Hence study of experimental research was carried out on pre-matured failure of lifed hydraulic components of ten aircrafts. The failure rate of each component was studied in-depth to adopt remedial measures for improving its life and in turn to reduce the period of “Aircraft on Grounds”. Aircraft on ground mean unserviceable aircraft will be on ground and not suitable for flying. In addition, a deep study was made on each component to fix a Time Between Overhaul (TBO) by analyzing the failure trend of each component to determine a common and effective TBO for enhancing the serviceability rate of aircrafts. It also prevents sudden failure of components thus improving the serviceability status. In order to enhance the standard of serviceability a “Root Cause Analysis”was carried out on those defective components to suggest remedial measures to those maintenance personnel to modify the maintenance process and reduce the TBO for effective reduction in time of occurrence of the defects. These suggestive measures were implemented by the users of the ten aircrafts on trial basis. Occurrence of such defects was minimized showing significant improvement in the subsequent maintenance of aircrafts. Further, the remedial measures have a great impact on the development of a high degree of aircraft maintenance. The final results of this research study are prepared and suggested measures are forwarded for implementation to manufactures, overhaul agency and operators.
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Moshtagh, Ehsan, Morteza Eskandari-Ghadi, and Ernian Pan. "Time-harmonic dislocations in a multilayered transversely isotropic magneto-electro-elastic half-space." Journal of Intelligent Material Systems and Structures 30, no. 13 (May 23, 2019): 1932–50. http://dx.doi.org/10.1177/1045389x19849286.
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Modeling layered systems with dislocations is very challenging; yet, it is important since most smart structures are made of multilayers to make best use of the combined effective property. As such, during the manufactures, defects, such as dislocations, could be introduced in the multilayers. In this article, we analytically find, for the first time, the response of three-dimensional multilayered magneto-electro-elastic systems due to time-harmonic dislocations. The dislocations are the most general, containing the elastic dislocations and discontinuity of the electric potential and/or magnetic potential over a circular region in any layer in the medium. The fully coupled partial differential equations of motion and the Gauss law for the magneto-electro-elastic materials are solved in terms of cylindrical system of vector functions, and the dual variable and position method is further introduced to treat the multilayers. Numerical examples are carried out based on the derived analytical solution to demonstrate the effects of the time-harmonic dislocations on the induced magneto-electro-elastic fields. This analytical solution is important in both electrodynamics and elastodynamics, with possible applications in material sciences and physics. The numerical results are useful in design process of smart devices made of magneto-electro-elastic solids applicable to other engineering fields like renewable energy.
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Bonneric, Matthieu, Charles Brugger, and Nicolas Saintier. "Defect sensitivity in additively manufactured aluminium alloys: contribution of CAD artificial defects." MATEC Web of Conferences 300 (2019): 03006. http://dx.doi.org/10.1051/matecconf/201930003006.
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The prediction of the fatigue resistance of additively manufactured parts is a current issue for the materials and process qualification in aerospace industry. Despite a continuous improvement of AM process, the presence of defects cannot yet be completely avoided, and the latter are still one of the main causes of fatigue damage in AM materials. In this framework, the present work focused on the influence of defects on the uniaxial fatigue behavior of AlSi7Mg0.6 alloy produced by Selective Laser Melting (SLM). Uniaxial fatigue tests have been performed. Fatigue specimens were subjected to a T6 treatment, and then machined in order to avoid the influence of surface roughness. Besides, for some specimens, artificial defects were directly introduced through CAD. The introduction of artificial defects, whose sizes and positions are precisely controlled, aims to provide a proper assessment of defect sensitivity. X-ray tomography was used to characterize both natural and artificial defects. Finite-element calculations of the local stress fields in the vicinity of defects were conducted, accounting for the real defect geometries obtained with CT scans. The application of a non-local multiaxial fatigue criterion then allowed to analyze defect criticity.
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Tsuchiya, Shiori, and Koji Takahashi. "Improving Fatigue Limit and Rendering Defects Harmless through Laser Peening in Additive-Manufactured Maraging Steel." Metals 12, no. 1 (December 27, 2021): 49. http://dx.doi.org/10.3390/met12010049.
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Additive-manufactured metals have a low fatigue limit due to the defects formed during the manufacturing process. Surface defects, in particular, considerably degrade the fatigue limit. In order to expand the application range of additive-manufactured metals, it is necessary to improve the fatigue limit and render the surface defects harmless. This study aims to investigate the effect of laser peening (LP) on the fatigue strength of additive-manufactured maraging steel with crack-like surface defects. Semicircular surface slits with depths of 0.2 and 0.6 mm are introduced on the specimen surface, and plane bending-fatigue tests are performed. On LP application, compressive residual stress is introduced from the specimen surface to a depth of 0.7 mm and the fatigue limit increases by 114%. In a specimen with a 0.2 mm deep slit, LP results in a high-fatigue-limit equivalent to that of a smooth specimen. Therefore, a semicircular slit with a depth of 0.2 mm can be rendered harmless by LP in terms of the fatigue limit. The defect size of a 0.2 mm deep semicircular slit is greater than that of the largest defect induced by additive manufacturing (AM). Thus, the LP process can contribute to improving the reliability of additive-manufactured metals. Compressive residual stress is the dominant factor in improving fatigue strength and rendering surface defects harmless. Moreover, the trend of the defect size that can be rendered harmless, estimated based on fracture mechanics, is consistent with the experimental results.
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Himes, Emma. "NHTSA Up in the Clouds: The Formal Recall Process & Over-the-Air Software Updates." Michigan Technology Law Review, no. 28.1 (2021): 153. http://dx.doi.org/10.36645/mtlr.28.1.nhtsa.
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Software updates are pushed to vehicles “over-the-air” (OTA) with increasing frequency as they reduce costs of visiting dealerships and auto shops to receive maintenance. These updates, pushed from the cloud, have been used to remedy safety defects in vehicles and improve software controlling all aspects of vehicles from steering to rearview mirrors. Remedies of vehicle safety defects are overseen by the National Highway Traffic Safety Administration (NHTSA); however, because many OTA software updates do not remedy issues officially deemed safety defects, they are pushed straight from the manufacturer to drivers with little government oversight or transparency. NHTSA’s recall process was designed in 1966 to remedy safety defects in vehicles, resulting in a process which is now outdated for modern vehicles running on software. NHTSA has acknowledged the increased use of OTA software updates and prescribed OTA remedies for safety defects, but the current framework leaves NHTSA unable to oversee the rapid output of OTA software updates pushed by auto manufacturers. Without updating the current recall process for software related updates to vehicles, and specifically over-the-air software updates, NHTSA’s ability to oversee vehicle safety may decrease and the recall process may grow obsolete as the issues facing vehicles today have changed since Congress defined what constitutes a safety defect.
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Opryshko, L. V., and T. V. Golovnyak. "Study of surface defects in tubes made from nondeformed continuously cast billets." Metaloznavstvo ta obrobka metalìv 98, no. 2 (June 7, 2021): 54–62. http://dx.doi.org/10.15407/mom2021.02.054.
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Defects of outer and inner surfaces of hot-rolled tubes of various steel grades and sizes manufactured on tube-rolling unit with a continuous mill (TPA 30-102) at Interpipe Nikotube LLC from a nondeformed continuously cast billets produced by MZ Dniprostal LLC have been studied. Characteristic genetic and morphological signs of defects were revealed which makes it possible to reliably classify them, identify cause of defect formation and recommend measures to eliminate them. Defects on the outer and inner surfaces of tubes are of metallurgical origin and associated with quality of initial continuously cast billets (a consequence of violation of the smelting and continuous casting technology). Defects on the inner surface of tubes were caused on defects in the axial zone of original billets (unacceptable porosity, looseness, chemical inhomogeneity, liquation stripes and cracks, etc.) and are classified as steel-smelting films and bulges. It was found that displacement of the thermal center of crystallization (a feature of the machines for continuous steel casting of curvilinear type) had an additional negative effect on quality of the inner surface of the studied tubes. Defects on the outer surface of tubes are tears of burning in places of accumulation of low-melting inclusions and their eutectics, as well as steel-smelting scabs on rolled dirt and gas bubbles. Likelihood of formation of scabs on outer surface of the studied tubes over rolled crust introversions is not excluded. The study results will allow manufacturers to reliably classify defects, promptly reject tubes with unacceptable defects of metallurgical origin and minimize supply of low-quality products to consumers. These results will later be included in the classifier of defects in tubes manufactured on the TPA 30-102 unit from nondeformed continuously cast billets. The results of the study of natural signs of defects of metallurgical origin in the tube surface will be useful for elaboration of measures aimed at improvement of the technology of manufacturing initial tube billets. Keywords: tube surface defects, continuously cast billets, microstructure, rolled contamination, low-melting inclusions, eutectic, gas bubbles, decarburization, liquation.
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Biś, Jesica, Bartosz Koczurkiewicz, and Igor Mazur. "Defects and Incompatibilities of Pipes Manufactured by Pilgrim Method." New Trends in Production Engineering 2, no. 2 (December 1, 2019): 24–35. http://dx.doi.org/10.2478/ntpe-2019-0069.
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Abstract The increase in the quality requirements for the pipes and the increasing needs to reduce production costs, while increasing the efficiency of the process in market of hot rolled pipes are observed. One of the cost reduction factors is the reduction of the number of defects by early detection and, if possible, the removal of non-conformities. Incompatibility is an error that can be removed in accordance with the performance standard that does not cause defects (Norma API). The defect is imperfection that is so important that it is the basis for the removal of the product or its part based on the criteria set out in the performance standards. In pipe manufacturing processes, defects and batch incompatibilities can be distinguished, which arise in the steelworks during metal solidification and roll forming in the course of metal processing. The defect may also arise as a result of removing steel material or result from rolling processes defects. The paper presents the analysis of the process of quality control of pipes manufactured using the pilgrim method on the basis of real process data. The analysis were involved 1070 pieces of ingots from 11 different melts for rolling pipes. At various stages of production, discrepancies and defects were revealed, which were caused by metallurgical or technological defects associated with rolling pipes. The total amount of discrepancies and defects eliminated 168 pieces of finished pipes. The aim of the work is to show that by means of appropriately selected methods of eliminating imperfections, it is possible to increase the efficiency of the manufacturing process.
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Chang, Chuan-Yu, You-Da Su, and Wei-Yi Li. "Tire Bubble Defect Detection Using Incremental Learning." Applied Sciences 12, no. 23 (November 28, 2022): 12186. http://dx.doi.org/10.3390/app122312186.
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Digital shearography is a technique that has recently been applied to material inspections that cannot be performed by the naked eyes, including the detection of air bubble defects in tires. Although digital shearography detects bubbles that are not visible to the naked eyes, the process of determining tire defects still relies on field operators, with inconsistent results depending on the experiences of the field operator personnel. New or different types of bubble defects that AI models have not previously recognized are often missed, resulting in an inadequate quality detection model. In this paper, we propose a bubble defect detection method based on an incremental YOLO architecture. The data for this research was provided by the largest tire manufacturer in Taiwan. In our research, we classify the defects into six distinct categories, pre-process the images to allow better detections of less-noticeable defects, increase the amount of training data used, and generate an initial training model with the YOLO framework. We also propose an incremental YOLO method using small-model training for previously unobserved defects to improve the model detection rate. We have observed detection accuracy and sensitivity of 98% and 90% in the experimental results, respectively. The methods proposed in this paper can assist tire manufacturers in achieving semi-automatic quality inspections and labor cost reductions.
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Du Rand, Francois, Malan Van Tonder, Andre Van Der Merwe, Olaf Diegel, Devon Hagedorn-Hansen, Ian Campbell, and Ian Gibson. "Powder Bed Defects Classification: An Industry Perspective." MATEC Web of Conferences 370 (2022): 06003. http://dx.doi.org/10.1051/matecconf/202237006003.
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The manufacture of defect-free parts has been a key discussion topic with the widespread adoption of additive manufacturing by industry. While significant research has been performed on the detection of powder bed defects, the focus has been on the classification of the defects according to defect type. However, when looking at creating a closed loop feedback system, it is important for the machine to make autonomous decisions regarding defects. The focus of this paper will be to create a defect severity classification matrix based on industry partner experience as well as published literature that can be used to autonomously classify defects
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Nelson, Jared W., Trey W. Riddle, and Douglas S. Cairns. "Effects of defects in composite wind turbine blades – Part 1: Characterization and mechanical testing." Wind Energy Science 2, no. 2 (December 19, 2017): 641–52. http://dx.doi.org/10.5194/wes-2-641-2017.
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Abstract. The Montana State University Composite Material Technologies Research Group performed a study to ascertain the effects of defects that often result from the manufacture of composite wind turbine blades. The first step in this multiyear study was to systematically quantify and enter these defects into a database before embedding similar defects into manufactured coupons. Through the Sandia National Laboratories Blade Reliability Collaborative (BRC), it was determined that key defects to investigate were fiber waves and porosity. An inspection of failed commercial-scale wind turbine blades yielded metrics that utilized specific parameters to physically characterize a defect. Methods to easily and consistently discretize, measure, and assess these defects based on the identified parameters were established to allow for statistical analysis. Data relating flaw parameters to frequencies of occurrence were analyzed and found to fit within standard distributions. Additionally, mechanical testing of coupons with flaws based on these physical characterization data was performed to understand effects of these defects. Representative blade materials and manufacturing methods were utilized and both material properties and damage progression were measured. It was observed that flaw parameters directly affected the mechanical response. While the data gathered in this first step are widely useful, it was also intended for use as a foundation for the rest of the study, to perform probabilistic analysis and comparative analysis of progressive damage models.
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Tri Basuki, Rahmat, and Uly Amrina. "Rahmat Tri Basuki, Uly Amrina." Go-Integratif : Jurnal Teknik Sistem dan Industri 3, no. 02 (November 30, 2022): 87–97. http://dx.doi.org/10.35261/gijtsi.v3i02.6942.
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PT Bumimulia Indah Lestari found defects in the oil bottle packaging products it produces, which include perforated bottles, black spots on bottles, and defects on labels. The type of defect on the bottle label is the highest defect in the period from July to December 2021 compared to other defects. This research is focused on the problem of defects in the inverted label as the dominant defect of the entire defect label. Researchers use the DMAIC method to solve these problems. The improvement resulting from the DMAIC method is the manufacture of a jig tool called Jig Go No Go which aims to reduce the number of defects and increase productivity in bottle products. The implementation of the jig can reduce the defect label as a whole from 5.8% to 3.3% and the sigma value increases from 2.488 to 2.493.
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Davies, David G. "Product Liability Goes to Sea: A Survey of the Legal Liability of Sellers and Manufacturers in the Marine Industry." Marine Technology and SNAME News 26, no. 04 (October 1, 1989): 308–15. http://dx.doi.org/10.5957/mt1.1989.26.4.308.
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United States law imposes potential liability on sellers and manufacturers of maritime products that prove to be defective in design or production. The degree of their vulnerability depends on the nature of the damage that results from the defect and their legal relationship with the person who suffers the damage. When the defect results in death or bodily injury, the potentially liable party cannot act be-forehand to limit the persons to whom he is liable or the amount of his liability. Common issues in such cases are causation, often based on expert testimony or government reports, hindsight determination of design defects or failures to warn adequately of unavoidable hazards, and foreseeable human errors. If damages are "economic," however, the seller's or manufacturer's liability may be limited to those with whom he had contracted directly, and the contract can further limit the amount of liability to those persons and the methods by which they can enforce what rights they have.
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Sugoro Bhakti Sutono, Zumrotul Khamidah. "Pengendalian Kualitas Produk Unit Plastik Woven Bag Dalam Upaya Mengendalikan Tingkat Kecacatan Produk Dengan Bantuan Statistical Process Control (SPC): Studi Kasus PT. Dasaplast Nusantara." Journal of Industrial Engineering and Technology 2, no. 1 (January 31, 2022): 75–84. http://dx.doi.org/10.24176/jointtech.v2i1.7433.
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Quality is an achievement or assessment of an item or service from various factors based on the conformity of the specifications desired by the manufacturer. Good product quality can provide confidence for customers to order or cooperate in business so that it can improve the company's position against its competitors. PT. Dasaplast Nusantara is a company producing plastic woven bags or plastic sacks, the raw materials used in the manufacture of products have a high enough price, so the company must really maintain the quality of the product so that the company does not suffer a large enough loss. Thus, in this study, quality control was carried out using the Statistical Process Control (SPC) method which aims to control the level of product defects in the plastic woven bag unit. By using the SPC method, the company's defect rate is 12%, which means that the production capability is not good
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Fedorov, Vasiliy, Aleksandr Rygin, Vasiliy Klimenov, Nikita Martyushev, Anatolii Klopotov, Irina Strelkova, Sergey Matrenin, Andrey Batranin, and Valentina Deryusheva. "Structural and mechanical properties of stainless steel formed under conditions of layer-by-layer fusion of a wire by an electron beam." Metal Working and Material Science 23, no. 4 (December 13, 2021): 111–24. http://dx.doi.org/10.17212/1994-6309-2021-23.4-111-124.
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Introduction. As of today, additive technologies are among the most promising methods to manufacture various parts. They allow producing parts of complex shapes and provide their quality structure. The quality of the structure formed depends on numerous parameters: equipment type, its operation mode, materials, shielding medium, etc. Large international companies producing 3D-printers provide technological guidelines for working on it. Such guidelines include the information on the manufacturers of raw materials (printing powders), products their equipment can work with and the operation modes that should be used with such powders. These parameters should be investigated to use it on the domestic equipment developed within the framework of research programs and import substitution programs. The researchers and developers of 3D-printing equipment frequently run into a problem of using currently available raw materials for obtaining parts possessing minimal porosity, uniform structure and mechanical properties similar to that of at least cast blanks. One of the widely used materials for 3D-printing is stainless steel. It has high corrosion resistance, which reduces the requirements to the medium in which 3D printing is carried out. Manufactured stainless steel products have a good combination of strength and plastic characteristics. The aim of the study is to obtain stainless steel specimens possessing minimal number of micro- and macro-defects and uniform structure by the method of wire arc additive manufacturing using an electron-beam setup developed at Tomsk Polytechnic University. The methods to study the AISI 308LSi stainless steel 3D-printed specimens are as follows: XRD analysis, tomography, chemical analysis, metallographic analysis, microhardness testing. Results and discussion. It is established that the AISI 308LSi stainless steel specimens manufactured using the electron-beam 3D-printing setup contain no macro-defects in the bulk of the specimens. There are small microdefects represented by residual gas pores with the dimensions of no more than 5.2 μm. The microstructure of the specimens is formed close to that of coarse-grained cast austenite steels and consists of columnar grains of the γ-Fe austenite matrix and high-temperature ferrite. The interfaces between the wire layers are not pronounced; however, there are small differences in phase composition. Based on the analysis of the results obtained, it is established that the use of electron-beam 3D-printing for the manufacture of parts from AISI 308LSi steel gives a structure similar to cast austenitic steels. Macro-defects do not appear, and the number of gas pores is small.
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Acharya, Pradip, Tsuchin P. Chu, Khaled R. Ahmed, and Subash Kharel. "A Deep Learning Approach for Defect Detection and Segmentation in X-Ray Computed Tomography Slices of Additively Manufactured Components." International Journal of Artificial Intelligence & Applications 13, no. 4 (July 31, 2022): 1–15. http://dx.doi.org/10.5121/ijaia.2022.13401.
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Additive manufacturing is an emerging and crucial technology that can overcome the limitations of traditional manufacturing techniques to accurately manufacture highly complex parts. X-ray Computed Tomography (XCT) is a widely used method for non-destructive testing of AM parts. However, detection and segmentation of defects in XCT images of AM have many challenges due to contrast, size, and appearance of defects. This study developed deep learning techniques for detecting and segmenting defects in XCT images of AM. Due to a large number of required defect annotations, this paper applied image processing techniques to automate the defect labeling process. A single-stage object detection algorithm (YOLOv5) was applied to the problem of defect detection in image data. Three different variants of YOLOv5 were implemented and their performances were compared. U-Net was applied for defect segmentation in XCT slices. Finally, this research demonstrates that deep learning techniques can improve the automatic defect detection and segmentation in XCT data of AM.
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Niles, S. N., S. Fernando, and W. D. G. Lanerolle. "A System for Analysis, Categorisation and Grading of Fabric Defects using Computer Vision." Research Journal of Textile and Apparel 19, no. 1 (February 1, 2015): 59–64. http://dx.doi.org/10.1108/rjta-19-01-2015-b006.
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Inspection of fabrics is a major consideration in fabric manufacture, as well as in manufacture of garments and other fabric-based goods. In this research, a computer-based system for objective assessment of fabric defects was designed with emphasis placed on fabric defects occurring in the Sri Lankan industry. Image processing techniques were used to analyse scanned images of the test fabric, compare it with an ideal sample, and identify defects according to pre-learnt rules. The information gathered was then used to grade the fabric, either by determining the frequency of defect occurrence or assigning points. A new classification method for common defects was designed, thereby facilitating grading according to commonly used grading systems. A coding system for defects was also designed to help report defects to the user. The fabric defects were classified and stored according to the developed classification method and coding system.
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Liu, Bin, Xiaodong Xie, Junjun Xiong, Xiaopin Deng, and Hua Huang. "Electronic Current Transformer Defects Statistical Analysis of Intelligent Substation." Journal of Physics: Conference Series 2087, no. 1 (November 1, 2021): 012088. http://dx.doi.org/10.1088/1742-6596/2087/1/012088.
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Abstract In order to master operation status of the electronic current transformer(ECT), application investigation and defects statistical analysis were conducted on ECT of 110(66)kV~1000kV applied in smart substation of the State Grid Corporation of China(SGCC). The defect location, defect cause and defect type of ECT with different principles are analyzed. The results indicate that the defects of ECT are mainly concentrated in the acquisition unit, the defect rate is closely related to the reliability of electronic components, the technical level, production process and quality control of the manufacturer. In view of the typical defect analysis, the corresponding solution measures are put forward to provide reference for the subsequent research and application of ECT.
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Filippov, Andrey V., Valery E. Rubtsov, Sergei Yu Tarasov, and Vladimir A. Beloborodov. "Application of 3D Сomputed Microtomography for Investigating the Microstructural Defects of Carbon Fiber Reinforced Composite Made by 3D-Printing." Key Engineering Materials 712 (September 2016): 324–27. http://dx.doi.org/10.4028/www.scientific.net/kem.712.324.
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The microstructural defect of additive manufactured 3-component carbon fiber reinforced polymer (CFRP) composites has been studied using computed microtomography. The samples have been prepared using a 3D-printing process developed at Skolkovo Institute of Science and Technology, Russia. The research procedure has been described and internal defects of the fiber composite material have been detected and analyzed using a 3D image reconstructed from a number of cross section views. The defects larger 50 μm have been detected using the computed microtomography test. Defect-free images and defects typical for this type of composites such as delamination in polymer matrix and between fibers in a bundle, fiber breakage have been obtained.
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Bugvi, Salman Abubakar, Khurram Hameed, M. Fawad Jamil, Ali Irfan, Shahid Murtaza, Muhammad Qaiser, and Muhammad Bilal. "Performance Improvement through Value Stream Mapping – A Manufacturing Case Study." Jurnal Kejuruteraan 33, no. 4 (November 30, 2021): 1007–18. http://dx.doi.org/10.17576/jkukm-2021-33(4)-22.
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The successfulness of Value Stream Mapping (VSM) as a tool for taking a snapshot of the production flow efficiency is well established. The development of a large-scale visual map of processes and their interactions is beneficial for problem analysis and subsequent solution. Through VSM, managers gain a deeper understanding of the organization processes carried out in coordination with people in a system approach. A case study was conducted at a Small and Medium Enterprise (SME) in Pakistan which manufactures ceiling fan winding machines. The aim of this study was to explore the possibilities of shortening the lead-time, waste and highlight important strategies, steps which could be undertaken by management for improvement in productivity, cost and quality. The study maps the organization systematically through the use of VSM. The Lean Implementation Techniques (LIT) steps were followed with identification of value stream process, lean metrics, mapping of current state and proposing an improved future state value stream map. The intervention suggested is layout modification by reducing 7 stations to 6 stations and streamlining the operations. The layout modification results in lower defects, controlling overproduction, managing inventory buffers from a linear approach to an optimized level. This also resulted in reduction of processing time of each unit by around 19 % and the production lead time of 100 units by around 21%. This study through VSM proposes improvement by enforcing pull system, supplier relations, modifying layout and production processes, Just in Time (JIT) delivery of materials and parts, scheduling transport resources efficiently and reducing inventory buffers.
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Miao, Yilin, Zhewei Liu, Xiangning Wu, and Jie Gao. "Cost-Sensitive Siamese Network for PCB Defect Classification." Computational Intelligence and Neuroscience 2021 (October 12, 2021): 1–13. http://dx.doi.org/10.1155/2021/7550670.
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After the production of printed circuit boards (PCB), PCB manufacturers need to remove defected boards by conducting rigorous testing, while manual inspection is time-consuming and laborious. Many PCB factories employ automatic optical inspection (AOI), but this pixel-based comparison method has a high false alarm rate, thus requiring intensive human inspection to determine whether alarms raised from it resemble true or pseudo defects. In this paper, we propose a new cost-sensitive deep learning model: cost-sensitive siamese network (CSS-Net) based on siamese network, transfer learning and threshold moving methods to distinguish between true and pseudo PCB defects as a cost-sensitive classification problem. We use optimization algorithms such as NSGA-II to determine the optimal cost-sensitive threshold. Results show that our model improves true defects prediction accuracy to 97.60%, and it maintains relatively high pseudo defect prediction accuracy, 61.24% in real-production scenario. Furthermore, our model also outperforms its state-of-the-art competitor models in other comprehensive cost-sensitive metrics, with an average of 33.32% shorter training time.
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Jo, A., Myeong Jeong, Sang Lee, Young Moon, and Sun Hwang. "Multi-Stage Cold Forging Process for Manufacturing a High-Strength One-Body Input Shaft." Materials 14, no. 3 (January 22, 2021): 532. http://dx.doi.org/10.3390/ma14030532.
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A multi-stage cold forging process was developed and complemented with finite element analysis (FEA) to manufacture a high-strength one-body input shaft with a long length body and no separate parts. FEA showed that the one-body input shaft was manufactured without any defects or fractures. Experiments, such as tensile, hardness, torsion, and fatigue tests, and microstructural characterization, were performed to compare the properties of the input shaft produced by the proposed method with those produced using the machining process. The ultimate tensile strength showed a 50% increase and the torque showed a 100 Nm increase, confirming that the input shaft manufactured using the proposed process is superior to that processed using the machining process. Thus, this study provides a proof-of-concept for the design and development of a multi-stage cold forging process to manufacture a one-body input shaft with improved mechanical properties and material recovery rate.
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Fischer, Carl, and Christoph Schweizer. "Lifetime assessment of the process-dependent material properties of additive manufactured AlSi10Mg under low-cycle fatigue loading." MATEC Web of Conferences 326 (2020): 07003. http://dx.doi.org/10.1051/matecconf/202032607003.
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Systematic low-cycle fatigue (LCF) experiments are carried out on additive manufactured AlSi10Mg specimens for several material conditions with varying layer thickness, heat treatment, building direction and surface quality. The deformation behaviour depends significantly on the heat treatment. It is outlined that the process control and heat treatment can produce fatigue properties comparable with the cast material, whereby an as-built specimen surface leads to a lifetime reduction in all cases. The experiments are accompanied with detailed metallo- and fractographic investigations. For all tested LCF specimens, the defect type and the failure origin defect size are characterized in terms of the √area parameter by using scanning electron microscopy. The failure of the specimen is mostly caused by lack of fusion surface or near-surface defects, whereby the defect size is determined by the SLM process parameters, such as building direction, surface quality and layer thickness. On the basis of the experimental data and the observed defects, a mechanism-based, deterministic lifetime model is developed and adapted to the specific damage mechanisms of the additive manufactured AlSi10Mg alloy.
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Echeta, Ifeanyichukwu, Xiaobing Feng, Ben Dutton, Richard Leach, and Samanta Piano. "Review of defects in lattice structures manufactured by powder bed fusion." International Journal of Advanced Manufacturing Technology 106, no. 5-6 (December 30, 2019): 2649–68. http://dx.doi.org/10.1007/s00170-019-04753-4.
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AbstractAdditively manufactured lattice structures are popular due to their desirable properties, such as high specific stiffness and high surface area, and are being explored for several applications including aerospace components, heat exchangers and biomedical implants. The complexity of lattices challenges the fabrication limits of additive manufacturing processes and thus, lattices are particularly prone to manufacturing defects. This paper presents a review of defects in lattice structures produced by powder bed fusion processes. The review focuses on the effects of lattice design on dimensional inaccuracies, surface texture and porosity. The design constraints on lattice structures are also reviewed, as these can help to discourage defect formation. Appropriate process parameters, post-processing techniques and measurement methods are also discussed. The information presented in this paper contributes towards a deeper understanding of defects in lattice structures, aiming to improve the quality and performance of future designs.
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Albakri, Mohammad I., Logan D. Sturm, Christopher B. Williams, and Pablo A. Tarazaga. "Impedance-based non-destructive evaluation of additively manufactured parts." Rapid Prototyping Journal 23, no. 3 (April 18, 2017): 589–601. http://dx.doi.org/10.1108/rpj-03-2016-0046.
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Purpose This work proposes the utilization of electromechanical impedance measurements as a means of non-destructive evaluation (NDE) for additive manufacturing (AM). The effectiveness and sensitivity of the technique for a variety of defect types commonly encountered in AM are investigated. Design/methodology/approach To evaluate the feasibility of impedance-based NDE for AM, the authors first designed and fabricated a suite of test specimens with build errors typical of AM processes, including dimensional inaccuracies, positional inaccuracies and internal porosity. Two polymer AM processes were investigated in this work: material jetting and extrusion. An impedance-based analysis was then conducted on all parts and utilized, in a supervised learning context, for identifying defective parts. Findings The newly proposed impedance-based NDE technique has been proven to be an effective solution for detecting several types of print defects. Specifically, it was shown that the technique is capable of detecting print defects resulting in mass change (as small as 1 per cent) and in feature displacement (as small as 1 mm) in both extruded nylon parts and jetted VeroWhitePlus parts. Internal porosity defects were also found to be detectable; however, the impact of this defect type on the measured impedance was not as profound as that of dimensional and positional inaccuracies. Originality/value Compared to currently available NDE techniques, the newly proposed impedance-based NDE is a functional-based technique with the advantages of being cost-effective, sensitive and suitable for inspecting AM parts of complex geometry and deeply embedded flaws. This technique has the potential to bridge the existing gaps in current NDE practices, hence paving the road for a wider adoption of AM to produce mission-critical parts.
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Springer, Sebastian, Martin Leitner, Thomas Gruber, Bernd Oberwinkler, Michael Lasnik, and Florian Grün. "Fatigue Assessment of Wire and Arc Additively Manufactured Ti-6Al-4V." Metals 12, no. 5 (May 4, 2022): 795. http://dx.doi.org/10.3390/met12050795.
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Wire and arc additively manufactured (WAAM) parts and structures often present internal defects, such as gas pores, and cause irregularities in the manufacturing process. In order to describe and assess the effect of internal defects in fatigue design, this research study investigates the fatigue strength of wire arc additive manufactured structures covering the influence of imperfections, particularly gas pores. Single pass WAAM structures are manufactured using titanium alloy Ti-6Al-4V and round fatigue, tensile specimen are extracted. Tensile tests and uniaxial fatigue tests with a load stress ratio of R = 0.1 were carried out, whereby fatigue test results are used for further assessments. An extensive fractographic and metallographic fracture surface analysis is utilized to characterize and measure crack-initiating defects. As surface pores as well as bulk pores are detected, a stress intensity equivalent ΔKeqv transformation approach is presented in this study. Thereby, the defect size of the surface pore is transformed to an increased defect size, which is equivalent to a bulk pore. Subsequently, the fatigue strength assessment method by Tiryakioğlu, commonly used for casting processes, is applied. For this method, a cumulative Gumbel extreme value distribution is utilized to statistically describe the defect size. The fitted distribution with modified data reveals a better agreement with the experimental data than unmodified. Additionally, the validation of the model shows that the usage of the ΔK modified data demonstrates better results, with a slight underestimation of up to about −7%, compared to unmodified data, with an overestimation of up to about 14%, comparing the number of load cycles until failure. Hence, the presented approach applying a stress intensity equivalent transformation of surface to bulk pores facilitates a sound fatigue strength assessment of WAAM Ti-6Al-4V structures.
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Liu, Ying, Yan Tao Zhu, Feng Ming Xia, and Zhao Jun Xu. "Research on the Intelligent Manufacturing System for Lumber Cutting." Advanced Materials Research 631-632 (January 2013): 1441–44. http://dx.doi.org/10.4028/www.scientific.net/amr.631-632.1441.
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To enhance the rate of lumber cutting output and save the production cost, a new intelligent manufacture system is developed. Considering the requirements of wood surface defects detection and optimal layout, the overall structure is established. The system has six function modules, there are cutting task module, laser scanning images processing module, defects identify module, optimal layout module, machining plan module and data manage module. According to laser scanning, images processing and defects identify programs help manufacturer to get profile data, acquire profile image, extract features, and identify lumber defects. Optimal layout module gives an intelligent program to decide the maximum number of cutting board pieces and shows operator the visualized layout. Two examples are shown which apply algorithms to obtain the optimal layouts for lumber cutting. The intelligent manufacturing system helps people detect lumber defects, make the optimal machining plan and cutting material online quickly.
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Kambayashi, H., Y. Kurokawa, H. Ota, Yasuhiro Hoshiyama, and Hidekazu Miyake. "Evaluation with Surface Analysis Equipment, of Casting Defects in Cast Iron Articles (review)." Materials Science Forum 539-543 (March 2007): 1110–15. http://dx.doi.org/10.4028/www.scientific.net/msf.539-543.1110.
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Authors have reported theses concerning the cast defect for publication in journal of Japanese Foundry Engineering Society and AFS Transactions. This is a review of these reports. There are various factors in the casting defect that occurs in the article of casting metal, and specific of the generation factor is difficult. Moreover, it is necessary to decrease the casting defect to reduce the cost of goods manufactured and energy of production. It is effective to the evaluation and the classification method of the casting defect to employ Scanning Electron Microscopy with Energy Dispersion Spectrometer (SEM-EDS) and Electron Probe Micro-Analysis (EPMA). Casting defects chose the one that the incidence was high and specific of the generation factor is difficult, and the pinhole defect and inclusion defects were classified according to the generation factor, and penetration defect showed the relation of physical factor, chemical factor, and those interactions, and examined whether specific of the factor was possible by the surface analysis equipment about other defects (Blow hole, Shrinkage, Orange peel, Cold shut, Cracks and Veining).
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Uematsu, Yoshihiko, Toshifumi Kakiuchi, Yaodong Han, and Masaki Nakajima. "Proposal of Fatigue Limit Design Curves for Additively Manufactured Ti-6Al-4V in a VHCF Regime Using Specimens with Artificial Defects." Metals 11, no. 6 (June 15, 2021): 964. http://dx.doi.org/10.3390/met11060964.
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Cantilever-type rotating bending fatigue tests were conducted under a very high cycle fatigue regime using conventionally manufactured Ti-6Al-4V specimens having drilled artificial defects with different sizes. The relationship between fatigue limit and defect size was defined as a fatigue limit design curve considering the transition from the fracture-mechanics dominating area to the fatigue-limit dominating area. A conventional Murakami’s equation was applicable as a design curve of additively manufactured Ti-6Al-4V with defects at 107 cycles. However, conventional equation gave un-conservative predictions for the fatigue limit at 108 cycles. Therefore, two kinds of modified Murakami’s equation were proposed as fatigue limit design curves for the very high cycle fatigue regime. Simple parallel shift of Murakami’s equation gave a conservative fatigue limit, whilst better result was obtained by changing the slope of Murakami’s equation. The proposed design curve was valid for the defect sizes ranging from 10 to 500 μm.
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Mastap, Sushardi, Tibertius Agus Prayitno, Yustinus Suranto, and Ganis Lukmandaru. "Suitability of Teak Log Quality from Gunung Kidul and Bantul Yogyakarta Community Forest for Export Meubel Purpose." Journal of Sylva Indonesiana 4, no. 02 (August 30, 2021): 78–86. http://dx.doi.org/10.32734/jsi.v4i02.6347.
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Natural defect or poor log quality are common in community teak forests. Furniture manufacturers typically use these log types for export purposes. The aim of this study is to determine the effect of community teak forest location and teak stand age affect on teak wood quality. Three teak forest locations were Bantul and two locations in Gunung Kidul. The teak stand age class namely 6, 8, and 10 years old. The data was analyzed using SPSS 20.0 with Tukey test. The result showed that brittleness defect, sapwood defect, and different wooden knot defects were significant in all locations, while log straightness defect was found only in Dlingo. Similarly, all teak stand age (6, 8, and 10 years old) also produced the same defects such as brittleness defect, sapwood defect, and wood knot defect, while the straightness defect at the age of 10 years old was different from to other two teak stand age (6 and 8-year-old). Average teak log defects were straightness defect 1.87-3.53%, brittleness defect 1.19–6.21%, sapwood defect 1.49-4.82 cm, and wood knot defect 5.10-11.46 cm. However, the teak log quality still met the SNI 7534.2-2010 and 7535.2-2010 as raw material for exporting furniture.
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Cersullo, Nicola, Jon Mardaras, Philippe Emile, Katja Nickel, Vitus Holzinger, and Christian Hühne. "Effect of Internal Defects on the Fatigue Behavior of Additive Manufactured Metal Components: A Comparison between Ti6Al4V and Inconel 718." Materials 15, no. 19 (October 3, 2022): 6882. http://dx.doi.org/10.3390/ma15196882.
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In order to obtain a widespread application of Additive Manufactured (AM) technology in the aircraft industry for fatigue critical parts, a detailed characterization of the Fatigue and Damage Tolerance (F&DT) behavior of structural components is required. Metal AM techniques in particular are prone to internal defects inherently present due to the nature of the process, which have a detrimental effect on fatigue properties. In the present work, Ti6Al4V and Inconel 718 coupons with artificially induced defects of different dimensions were produced by the Laser Powder Bed Fusion (LPBF) technique. Fatigue tests were performed, and a different defect sensitiveness was observed between the two materials with Inconel being more defect tolerant compared to Titanium. The environmental role at the crack tip of internal defects was discussed, and based on a purely fracture mechanics approach, a simplified stress–life–defect size model was finally devised. The experimental test results together with the information obtained from the fracture surface analysis of tested samples are used to validate the model predictions. The proposed approach could be adopted to define a critical defect size map to be used for tailored Non-Destructive Testing (NDT) evaluation.
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Younas, Mahzaib, Qamar Nawaz, Isma Hamid, Syed Mushhad Mustuzhar Gilani, and M. Javed Iqbal. "A novel approach of ceramic tile crack detection using morphological operations." Mehran University Research Journal of Engineering and Technology 41, no. 2 (April 1, 2022): 146–54. http://dx.doi.org/10.22581/muet1982.2202.14.
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In ceramic tiles manufacturing industry, tiles are manufactured at large scale which makes it more challenging to ensure the quality of each tile according to the set standards. Mostly, Statistical Process Control (SPC) is used by tile manufacturers at each step to monitor various processing parameters. SPC procedures are implemented manually that requires sufficient number of experienced human resource to identify defected tiles from a batch of tiles. The manual inspection also gives low accuracy of defect detection due to human errors and hard environment. Considering these drawbacks, in this paper an automated defect detection method is proposed which is based on image processing and morphological operation to ensure the quality and standard of tiles. The proposed method resizes and converts the input RGB image into grayscale image and removes any possible noisy artifacts. An edge detection algorithm is applied on grayscale image to enhance the edges representing the cracks. Afterwards, morphological erosion and dilation operations are applied, one at a time, to get two intermediate images. Finally, edges are detected by subtracting eroded intermediate image from dilated intermediate image. For detection, the proposed algorithm does not require any separate reference image. The algorithm is tested on an image set of sixty different defected tile images and attained 92% average detection accuracy.
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Cheng, Peng Fei, Han Chen Liu, and Ying Tang Zhang. "Identification of ZnO Defect Structure by PL Spectroscopy." Advanced Materials Research 393-395 (November 2011): 135–38. http://dx.doi.org/10.4028/www.scientific.net/amr.393-395.135.
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Defect structure of ZnO determines the optoelectronic characteristics of ZnO crystal and film. The identification and modulation of the defect structure is the foundation of the manufacture of optoelectronic devices. Although a good deal of research has been carried out about intrinsic defects and doping defects in ZnO, it is difficult to obtain a conclusive result accepted by all. In the paper, ZnO film is prepared by sol-gel method and the defect structure is expressed by photoluminescent (PL) spectroscopy. Based on some basic rules the intrinsic defect structure of ZnO is confirmed and the interaction of impurity Li and intrinsic defect is discussed. At the same time, some new electronic levels are proposed. It is surprising that although there are fourteen peaks in PL spectra of ZnO film, almost all the peaks can be identified by these basic rules.