Personal Image Classifier Based Handy Pipe Defect Recognizer (HPD): Design and Test

Moshayedi, Ata Jahangir; Khan, Amir Sohail; Yang, Shuxin; Zanjani, S. Mohammadali

doi:10.1109/icsp54964.2022.9778676

Cited by 13 publications

(10 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a consequence, novel methodologies such as meta-heuristics, hybrid and intelligent algorithms, machine learning and deep learning are proposed to encounter large-sized problems (Boysen and Emde, 2014;Fathi et al, 2014;Rao et al, 2013;Peng and Zhou, 2018;Moshayedi et al, 2023). Among which, metaheuristic algorithms are powerful in solving optimization problems and have some advantage over classical methods (Moshayedi et al, 2022a(Moshayedi et al, , 2022b(Moshayedi et al, , 2022c, thus were implemented in a vast range of research fields such as robotics (Moshayedi et al, 2020), manufacturing (Yilmaz et al, 2017), for path planning (Moshayedi et al, 2019), line balancing (Wu et al, 2021), scheduling (Yilmaz and Durmusoglu, 2019), defect detection (Moshayedi et al, 2022a(Moshayedi et al, , 2022b(Moshayedi et al, , 2022c. These methodologies mainly include the genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), artificial bee (or ant) colony (ABC, AC), non-dominated sorting GA-II (NSGA-II) along with their improved versions.…”

Section: Introductionmentioning

confidence: 99%

“…However, due to apparently degenerating environmental condition and global warming for the past several decades, manufacturers are not only confronted with massive product diversities but also obliged to promote green production (Zhou and Tan, 2018). Therefore, to avoid the massive carbon emission generated by industrial logistic vehicles (Shao et al , 2018), companies are resorting to the application of electric vehicles (EVs), which are becoming essential to many factories (Moshayedi et al , 2022a, 2022b, 2022c) due to their advantage in the absence of green-house gas (GHG) emission (Qin et al , 2021). Nevertheless, among the literatures studying EVs, very few research studies focus on bringing EVs to the part-feeding process (Zhou and Tan, 2018; Emde et al , 2018; Zhou et al , 2021).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Zhou¹,

Huang²

2023

RIA

View full text Add to dashboard Cite

Purpose The purpose of this paper is to cut down energy consumption and eliminate production waste on mixed-model assembly lines. Therefore, a supermarket integrated dynamic cyclic kitting system with the application of electric vehicles (EVs) is introduced. The system resorts to just-in-time (JIT) and segmented sub-line assignment strategies, with the objectives of minimizing line-side inventory and energy consumption. Design/methodology/approach Hybrid opposition-based learning and variable neighborhood search (HOVMQPSO), a multi-objective meta-heuristics algorithm based on quantum particle swarm optimization is proposed, which hybridizes opposition-based learning methodology as well as a variable neighborhood search mechanism. Such algorithm extends the search space and is capable of obtaining more high-quality solutions. Findings Computational experiments demonstrated the outstanding performance of HOVQMPSO in solving the proposed part-feeding problem over the two benchmark algorithms non-dominated sorting genetic algorithm-II and quantum-behaved multi-objective particle swarm optimization. Additionally, using modified real-life assembly data, case studies are carried out, which imply HOVQMPSO of having good stability and great competitiveness in scheduling problems. Research limitations/implications The feeding problem is based on static settings in a stable manufacturing system with determined material requirements, without considering the occurrence of uncertain incidents. Current study contributes to assembly line feeding with EV assignment and could be modified to allow cooperation between EVs. Originality/value The dynamic cyclic kitting problem with sub-line assignment applying EVs and supermarkets is solved by an innovative HOVMQPSO, providing both novel part-feeding strategy and effective intelligent algorithm for industrial engineering.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Zhou¹,

Huang²

2023

RIA

View full text Add to dashboard Cite

show abstract

“…By arranging a certain number of electronic devices, sensors and other devices in the cabin, service area, lavatory, passenger seats, crew rest area and other areas, the cabin crew can monitor and manage the status information of each area of the cabin, including but not limited to a series of cabin seats, PSUs, overhead bins, service area facilities, kitchen facilities, lavatory facilities, doors system, water and waste system, cabin temperature, mood lighting system, electronic dimmable windows, etc. The ability to monitor and manage the status information of each area of the cabin can greatly improve the work efficiency and quality of cabin crew and then to serve the whole cabin [1][2] [3].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Analysis of Civil Aircraft Cabin Core Network Architecture based on Daisy Chain

Xiaoqiong,

Xi,

Ruiqi

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

With the rapid development of electronic technology, the application of civil aircraft cabin electronics is becoming more and more advanced. The traditional cabin core network architecture can no longer meet current cabin application requirements. Meanwhile, there are multiple of devices with duplicated functions in cabin of civil aircraft, and the number of each device with duplicated functions is very large. In order to solve the problem of repetitive deployment of a large number of devices with duplicated functions in the cabin system, the civil aircraft cabin core network architecture is proposed to adopt a two-level daisy chain network topology which has many advantages such as high robustness, high scalability and less cables. In the design phase of civil aircraft cabin core network architecture, modeling and simulation of the network architecture through simulation tools is an important means to study, predict, justify and judge the network performance. In this paper, a two-level daisy chain network architecture model with about 67 nodes for civil aircraft cabin core network is developed and the network performance of the model mentioned above is simulated through OPNET simulation tool in order to perform a trade-off analysis and evaluate the cabin core network architecture.

show abstract

“…Imaging technology has recently advanced and improved greatly. Using image processing and machine learning for object detection or fault detection, an application was recently developed known as HPD, which helps to detect the fault of an object [10]. Some other specific object detection applications include face detection and recognition [11], text detection [12], pose detection [13], people counting [14], and wind tracking algorithms [15].…”

Section: Introductionmentioning

confidence: 99%

The Object Detection, Perspective and Obstacles In Robotic: A Review

Khan

Moshayedi

et al. 2022

EAI Endorsed Trans AI Robotics

View full text Add to dashboard Cite

A few years back, when the image processing hardware and software were created, it was limited, and most of the time, object detection would fail., But as with time, the advancement in technology has significantly changed the scenario. A lot of researchers worked in this field to carry out a solution through which they can detect objects in any field, especially in the robotic domain [1]. In today's world, with so much research in the field of deep learning, it is very easy to identify and detect any object using computer vision. This paper focuses on the various deep learning technologies and algorithms through which object detection can be done. A new and advanced deep learning technology known as salient object detection has been discussed. Also, the 3D object detection and the end-to-end approach for object detection are discussed. The existing methods of deep learning through which object detection can be done. The applications in which object detection is being used and the importance of object detection. It also reports; what the predecessors have done, what problems have been solved by them, how they solved these problems, the characteristics of the predecessors' methods and their future work.

show abstract

Personal Image Classifier Based Handy Pipe Defect Recognizer (HPD): Design and Test

Cited by 13 publications

References 23 publications

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Dynamic cyclic kitting part-feeding scheduling for mixed-model assembly line by a hybrid quantum-behaved particle swarm optimization

Simulation and Analysis of Civil Aircraft Cabin Core Network Architecture based on Daisy Chain

The Object Detection, Perspective and Obstacles In Robotic: A Review

Contact Info

Product

Resources

About