Research on Automobile Assembly Line Optimization Based on Industrial Engineering Technology and Machine Learning Algorithm

Aiming at the lack of search depth of traditional genetic algorithm in automobile assembly line balance optimization, an improved genetic algorithm based on bagging integrated clustering is proposed for balance optimization. Through the integrated learning of several K -means algorithm based learners through bagging, a population clustering analysis method based on bagging integrated clustering algorithm is established, and then, a dual objective automobile assembly line balance optimization model is established. The population clustering analysis method is used to improve the intersection link of genetic algorithm to improve the search depth. The effectiveness and search performance of the improved genetic algorithm in solving the double objective assembly line balance problem are verified in an example.

A time-saving automobile assembly state monitoring system based on channel-pruned YOLOv4 algorithm

A time-saving automobile assembly state monitoring system in industrial environment is presented in this paper. The system only needs to input a video which contains the whole detected parts and manually label in the first frame. By finding the best point for tracking and tracking the point, the dataset can be automatically generated which saves time spent on manufacturing the dataset and makes the assembly state monitoring system easy to deploy into a practical industrial environment. The target detection algorithm uses the channel-pruned YOLOv4 neural network. The experimental result shows the algorithm balances speed and accuracy. Compared to original YOLOv4, our proposed method is two times faster and the mAP is nearly equal to it. It shows that the channel pruning process dynamically improves the speed of the forward propagation without sacrifice accuracy.

PROBLEMS AND DIRECTIONS OF DEVELOPMENT OF DIGITALIZATION OF QUALITY MANAGEMENT SYSTEM OF AUTO ASSEMBLY PLANT

The article presents research on the problem of digitalization of the quality management system of an automobile assembly plant. The directions of development of the processes of informatization and digitalization of the quality management system in production are proposed.

Eco-efficient management of a feeding system in an automobile assembly-line

Purpose This study aims to reduce carbon emissions and costs in an automobile production plant by improving the operational management efficiency of a serial assembly line assisted by a feeding electric tow vehicle (ETV). Design/methodology/approach A multi-objective function is formulated to minimize the energy consumption of the ETV from which emissions and costs are measured. First, a mixed-integer linear programming model is used to solve the feeding problem for different sizes of the assembly line. Second, a bi-objective optimization (HBOO) model is used to simultaneously minimize the most eco-efficient objectives: the number of completed runs (tours) by the ETV along the assembly line, and the number of visits (stops) made by the ETV to deliver kits of components to workstations. Findings The most eco-efficient strategy is always the bi-objective optimal solution regardless of the size of the assembly line, whereas, for single objectives, the optimization strategy differs depending on the size of the assembly line. Research limitations/implications Instances of the problem are randomly generated to reproduce real conditions of a particular automotive factory according to a previous case study. The optimization procedure allows managers to assess real scenarios improving the assembly line eco-efficiency. These results promote the implementation of automated control of feeding processes in green manufacturing. Originality/value The HBOO-model assesses the assembly line performance with a view to reducing the environmental impact effectively and contributes to reducing the existent gap in the literature. The optimization results define key strategies for manufacturing industries eager to integrate battery-operated motors or to address inefficient traffic of automated transport to curb the carbon footprint.

The Japanese Production System and Its International Transferability

The Japanese production system has an ethnic or national basis. There are considered to be three production components of the system-shop-floor-centred work organization, waste-free production control, and participative management in the context of cooperative labour relations. For each of these, it is possible to set up a Japanese-type'. The author is conducting research into the overseas operations of Japanese subsidiaries in automobile assembly. Japanese multinational enterprises presumably try to apply the system to their overseas operations to take advantage of its strengths; however, given that they have moved into a foreign country, presumably Japanese enterprises have to adapt to the management environment of the local area. This research investigates the following questions: (i) Does this 'application' and 'adaptation' result in a dilemma? (ii) What is actually being applied and what has not been possible to apply? (iii) How well is the balance between 'application' and 'adaptation' being achieved? According to surveys of Japanese manufacturing plants in North America, Asia, and Europe, the application of the system is possible. Of course this does not mean that it can be applied 100%. The pattern of application varies according to the management strategy of the Japanese enterprises.