Research on collaborative task assignment method of assembly line

Purpose The purpose of this paper is to construct a task assignment model for U-shaped production lines with collaborative task, which is optimized by minimizing the number of workers and balancing the workload of the operators. The ultimate goal is to increase productivity by increasing the U-line balance and balancing the load on the operators. Design/methodology/approach First, task selection and update mechanism are analyzed and the task selection mechanism suitable for collaborative task is proposed. Second, M-COMOSAL is obtained by improving the original COMOSAL. Finally, The M-COMOSAL algorithm and the COMAOSAL algorithm are used to perform job assignment on the double-acting clutch U-shaped assembly line. Findings According to the allocation scheme obtained by M-COMSOAL, the beat can be adjusted according to the change of order demand. The final allocation scheme is superior to the COMSOAL algorithm in terms of number of workers, working time, production tempo and balance rate. In particular, compared with the old scheme, the new scheme showed a decrease of 16.7% in the number of employees and a 18.8% increase in the production line balance rate. Thus, the method is helpful to reduce the number of operators and balance the workload. Originality/value The new algorithm proposed in this paper for the assignment of collaborative task can minimize the number of workers and balance the load of operators, which is of great significance for improving the balance rate of U-shaped production lines and the utilization of personnel or equipment.

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.

Optimization of disassembly line balancing using an improved multi-objective Genetic Algorithm

Disassembly activities take place in various recovery operations including remanufacturing, recycling, and disposal. Product disassembly is an effective way to recycle waste products, and it is a necessary condition to make the product life cycle complete. According to the characteristics of the product disassembly line, based on minimizing the number of workstations and balancing the idle time in the station, the harmful index, the demand index, and the number of direction changes are proposed as new optimization objectives. So based on the analysis of the traditional genetic algorithm into the precocious phenomenon, this paper constructed the multi-objective relationship of the disassembly line balance problem. The disassembly line balance problem belongs to the NP-hard problem, and the intelligent optimization algorithm shows excellent performance in solving this problem. Considering the characteristics of the traditional method solving the multi-objective disassembly line balance problem that the solution result was single and could not meet many objectives of balance, a multi-objective improved genetic algorithm was proposed to solve the model. The algorithm speeds up the convergence speed of the algorithm. Based on the example of the basic disassembly task, by comparing with the existing single objective heuristic algorithm, the multi-objective improved genetic algorithm was verified to be effective and feasible, and it was applied to the actual disassembly example to obtain the balance optimization scheme. Two case studies are given: a disassembly process of the automobile engine and a disassembly of the computer components.

Assembly line balance research methods, literature and development review

With the continuous upgrading of the manufacturing system, the assembly line balancing problem (ALBP) is gradually complicated, and the researches are constantly deepened in the application theory and solution methods. In order to clarify the research direction and development status of assembly line balancing, 89 articles are read and studied. We classify ALBPs to construct the network structure of research from horizontal classification and vertical thinking. The ALBP framework is horizontally given according to the number of models (i.e. the number of products), the layout shape of the assembly line, and the data of task time. The “seven steps for scientific paper” is vertically proposed according to the research steps to comb the research path of scientific and technological literature. The horizontal and vertical extension crosses and constructs the network structure of the ALBP. Any horizontal problem intersects with any step of the vertical “seven steps for scientific paper” to form a research point. We analyze 89 articles according to the development path from the straight line to U-shaped line and then to two-sided U-shaped/parallel U-shaped assembly line, summarize the research algorithm of assembly line balance and count the number of articles, and point out the latest research direction and algorithm development trend of assembly line balance.

Energy-Efficient Optimization of Two-Sided Disassembly Line Balance Considering Parallel Operation and Uncertain Using Multiobjective Flatworm Algorithm

The two-sided disassembly line is popular for its high-efficiency disassembly of large-volume end-of-life products. However, in the process of two-sided disassembly, some parts and components need to be disassembled in parallel, and the uncertainty of disassembly time lacks certain research. This paper constructs a fuzzy multiobjective two-sided disassembly line balance problem model based on parallel operation constraint, which aims to reduce the balance loss rate, smoothness index, and energy consumption of disassembly activities. A multiobjective flatworm algorithm based on the Pareto-dominance relationship is developed. To increase the diversity of feasible solutions in the evolution process and accelerate the convergence of Pareto-optimal solutions to prevent the random search of solution space, growth, splitting and regeneration mechanisms are embedded in the algorithm. The working mechanism and efficiency of the multiobjective flatworm algorithm are proved on a series of two-sided disassembly cases, and the excellent performance of the proposed model and algorithm are demonstrated by an actual automobile two-sided disassembly line.

An Assembly Line Balancing Application on Oven Production Line with Hyper-Heuristics

In this study, an oven assembly line that is planning to re-establish manufacturing to increase the efficiency of the assembly process. The importance of the problem emerges from a real-world application consisting of product-oriented restrictions. These multiple restricted problems address the single model assignment restricted ALB problem with positional constraints. A cost-based objective function is used to cope with this problem. The number of platformed and non-platformed stations, the number of direction changes in a station, the number of stations in which both connector and combiner are used are the cost factors of the objective function. Also, the main objective of the problem is to minimize the total number of stations while satisfying the restrictions. A simulated annealing-based hyper-heuristic is adapted and applied to the balancing problem of oven manufacturing process with assignments and operational restrictions with multiple objectives. The results show that better solutions can be found in the current line balance level while satisfying more restrictions. It is also observed that line balance can be improved depending on the relaxation of the restrictions.