Yu Shih, Chien-Chih Kuo, Ching-Hung Lee^*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2087-2099, 2023, DOI:10.32604/iasc.2023.027659

Abstract The recent trends in Industry 4.0 and Internet of Things have encouraged many factory managers to improve inspection processes to achieve automation and high detection rates. However, the corresponding cost results of sample tests are still used for quality control. A low-cost automated optical inspection system that can be integrated with production lines to fully inspect products without adjustments is introduced herein. The corresponding mechanism design enables each product to maintain a fixed position and orientation during inspection to accelerate the inspection process. The proposed system combines image recognition and deep learning to measure the dimensions of the thread and… More >

Yuping Deng¹, Tao Wu¹, Xi Chen^2,*, Amir Homayoon Ashrafzadeh³

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1157-1174, 2022, DOI:10.32604/iasc.2022.022606

Abstract In meteorological and electric power Internet of Things scenarios, in order to extend the service life of relevant facilities and reduce the cost of emergency repair, the intelligent inspection swarm is introduced to cooperate with monitoring tasks, which collect and process the current scene data through a variety of sensors and cameras, and complete tasks such as emergency handling and fault inspection. Due to the limitation of computing resources and battery life of patrol inspection equipment, it will cause problems such as slow response in emergency and long time for fault location. Mobile Edge Computing is a promising technology, which… More >

Jakkrit Onshaunjit, Jakkree Srinonchat^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698

Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves 100% defect detection and 99.05%… More >

Adriano G. Passos, Tiago Cousseau, Marco A. Luersen^*

Computer Systems Science and Engineering, Vol.41, No.2, pp. 583-593, 2022, DOI:10.32604/csse.2022.020020

Abstract A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products, largely used in many industrial sectors. However, computers used in the production line of small to medium size companies, in general, lack performance to attend real-time inspection with high processing demands. In this paper, a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed. The architecture is based on the state-of-the-art SqueezeNet approach, which was originally developed for usage with autonomous vehicles. The main features of the proposed model are: small… More >

Marina Davidović^1,*, Tatjana Kuzmić¹, Dejan Vasić¹, Valentin Wich², Ansgar Brunn², Vladimir Bulatović¹

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 207-226, 2021, DOI:10.32604/cmes.2021.016071

Abstract A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually. This paper presents a novel method for the detection of road defects. The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology. The defects were categorized in three major groups with the following geometric primitives: points, lines and polygons. The method suggests the detection of point objects from matched point clouds, panoramic images and ortho photos. Defects were mapped as point, line or polygon geometries, directly derived from orthomosaics… More >

Harsh Tripathi¹, Amer Ibrahim Al-Omari², Mahendra Saha¹, Ayed R. A. Alanzi^3,*

Computer Systems Science and Engineering, Vol.38, No.3, pp. 381-392, 2021, DOI:10.32604/csse.2021.015624

Abstract Recently, the Darna distribution has been introduced as a new lifetime distribution. The two-parameter Darna distribution represents is a mixture of two well-known gamma and exponential distributions. A manufacturer or an engineer of products conducts life testing to examine whether the quality level of products meets the customer’s requirements, such as reliability or the minimum lifetime. In this article, an attribute modified chain sampling inspection plan based on the time truncated life test is proposed for items whose lifetime follows the Darna distribution. The plan parameters, including the sample size, the acceptance number, and the past lot result of the… More >

C. Sivamani¹, M. Rajeswari², E. Golden Julie³, Y. Harold Robinson⁴, Vimal Shanmuganathan⁵, Seifedine Kadry⁶, Yunyoung Nam^7,*

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 1-13, 2021, DOI:10.32604/iasc.2021.013705

Abstract Road accident is a potential risk to the lives of both drivers and passers-by. Many road accidents occur due to the improper condition of the vehicle tyres after long term usage. Thus, tyres need to be inspected and analyzed while manufacturing to avoid serious road problems. However, tyre wear is a multifaceted happening. It normally needs the non-linearly on many limitations, like tyre formation and plan, vehicle category, conditions of the road. Yet, tyre wear has numerous profitable and environmental inferences particularly due to maintenance costs and traffic safety implications. Thus, the risk to calculate tyre wear is therefore of… More >

Rashid Amin^{1, *}, Mudassar Hussain², Mohammed Alhameed³, Syed Mohsan Raza⁴, Fathe Jeribi³, Ali Tahir³

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1869-1890, 2020, DOI:10.32604/cmc.2020.011758

Abstract Software Defined Networking (SDN) being an emerging network control model is widely recognized as a control and management platform. This model provides efficient techniques to control and manage the enterprise network. Another emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central controller. This data processing at the edge nodes reduces the latency and bandwidth requirements. In SDN, the controller is a single point of failure. Several security issues related to the traditional network can be solved by using SDN central management and control. Address Spoofing and Network Intrusion… More >

Deisy Chaves^1,5,*, Maria Trujillo¹, Edward Garcia², Juan Barraza², Edward Lester³, Maribel Barajas⁴, Billy Rodriguez⁴, Manuel Romero⁴, Laura Fernández-Robles⁵

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 397-405, 2020, DOI:10.32604/iasc.2020.013916

Abstract Precise automated determination of char morphologies formed by coal during combustion can lead to more efficient industrial control systems for coal combustion. Commonly, char particles are manually classified following the ICCP decision tree which considers four morphological features. One of these features is unfused material, and this class of material not characteristic of Colombian coals. In this paper, we propose new machine learning algorithms to classify the char particles in an image based system. Our hypothesis is that supervised classification methods can outperform the 4 ‘class’ ICCP criteria. In this paper we evaluate several morphological features and specifically assess the… More >

Yu-Cheng Chou¹, Wei-Chieh Liao², Yan-Liang Chen², Ming Chang², Po Ting Lin³

Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 79-90, 2019, DOI:10.31209/2018.100000011

Abstract This paper presents the Distributed Heterogeneous Inspection System (DHIS), which comprises two CUDA workstations and is equipped with CPU distributed computing, CPU concurrent computing, and GPU concurrent computing functions. Thirty-two grayscale images, each with 5,000× 12,288 pixels and simulated defect patterns, were created to evaluate the performances of three system configurations: (1) DHIS; (2) two CUDA workstations with CPU distributed computing and GPU concurrent computing; (3) one CUDA workstation with GPU concurrent computing. Experimental results indicated that: (1) only DHIS can satisfy the time limit, and the average turnaround time of DHIS is 37.65% of the time limit; (2) a… More >