assembly line
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Omega ◽  
2022 ◽  
Vol 107 ◽  
pp. 102544
Author(s):  
Ebenezer Olatunde Adenipekun ◽  
Veronique Limère ◽  
Nico André Schmid
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10.29007/qz2g ◽  
2022 ◽  
Author(s):  
Sy Hieu Dau ◽  
Quang My Han Doan ◽  
Chiu Hy Ta ◽  
Nguyen An Khang Le ◽  
Nguyen Thanh Dat Khau

In the industrial context, there are key factors that directly affect the system’s efficiency. Higher demands for both quantity and quality in today’s market call for constant research and development of technologies for automating production and quality control. Machine vision is a solution to increase speed and accuracy in defect detection. However, applications from machine vision are only effective if there is good data input. This is the reason why a machine vision system, needs high-quality input images from a well-designed illumination system. These illumination systems are designed to highlight faults in products. Therefore, the images obtained will provide optimized data for easier image processing thus directly increase the processing speed, accuracy, and overall system performance. To achieve this goal, this paper presents a few approaches to enhance and optimize images by implements illumination techniques into a miniature model of pharmaceutical bottle assembly line using machine vision as the inspector block. In this paper, we will evaluate the critical needs of using customize illumination system for quality inspection on an assembly line.


Author(s):  
Simone König ◽  
Maximilian Reihn ◽  
Felipe Gelinski Abujamra ◽  
Alexander Novy ◽  
Birgit Vogel-Heuser

AbstractThe car of the future will be driven by software and offer a variety of customisation options. Enabling these customisation options forces modern automotive manufacturers to update their standardised scheduling concepts for testing and commissioning cars. A flexible scheduling concept means that every chosen customer configuration code must have its own testing procedure. This concept is essential to provide individual testing workflows where the time and resources are optimised for every car. Manual scheduling is complicated due to constraints on time, predecessor-successor relationships, mutual exclusion criteria, resources and status conditions on the car engineering and assembly line. Applied methods to handle the mathematical formulation for the corresponding industrial optimisation problem and its implementation are not yet available. This paper presents a procedure for automated and non-preemptive scheduling in the testing and commissioning of cars, which is built on a Boolean satisfiability problem on parallel and identical machines with temporal and resource constraints. The presented method is successfully implemented and evaluated on a variant assembly line of an automotive Original Equipment Manufacturer. This paper is the starting point for an automated workflow planning and scheduling process in automotive manufacturing.


2022 ◽  
Vol 14 (2) ◽  
pp. 775
Author(s):  
Yuling Jiao ◽  
Nan Cao ◽  
Jin Li ◽  
Lin Li ◽  
Xue Deng

An aim of sustainable development of the manufacturing industry is to reduce the idle time in the product-assembly process and improve the balance efficiency of the assembly line. A priority relationship diagram is obtained on an existing assembly line in the laboratory by measuring the task time of the chassis model, analyzing the product structure, and designing the assembly process. The type-E balance model of the U-shaped assembly line is established and solved by a heuristic algorithm based on the comprehensive rank value. The type-E balance problem of the U-shaped assembly-line plan of the chassis model is obtained, and the production line layout is planned. Combining instances to compare the results of the heuristic algorithm, genetic algorithm, and simulated annealing, comparison of the results shows that the degree of load balancing is slightly higher than genetic algorithm and simulated annealing. The balance efficiencies obtained by the heuristic algorithm are smaller than the genetic algorithm and simulated annealing. The calculation time is significantly less than the genetic algorithm and simulated annealing, and the scale of instances has little effect on the calculation time. The results verify that the model and the algorithm are effective. This study provides a reference for the entire process of the U-shaped assembly-line, type-E balance and the assembly products in laboratories.


Author(s):  
Mohammed-Amine Abdous ◽  
Xavier Delorme ◽  
Daria Battini ◽  
Fabio Sgarbossa ◽  
Sandrine Berger-Douce

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