Journal articles: 'Assembly scheduling'

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Lu, Zhi Bing, Ai Min Wang, Cheng Tong Tang, and Jing Sheng Li. "Linear Rail Space Dynamic Scheduling Technology for Multi-Tasking Hybrid Assembly Sections." Applied Mechanics and Materials 271-272 (December 2012): 650–56. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.650.

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For the rapid response to production scheduling problem driven by high-density production tasks, a dynamic scheduling technology for the large precision strip products assembly with a mixture of task time nodes and line-rail space is proposed. A scheduling constrained model containing coverage, proximity, timeliness and resource is established. A linear rail space production scheduling technology using heuristic automatic scheduling and event-driven method is put forward. The time rule based on delivery and single completion assembly is formed, at the same time the space rule based on the adjacent rail and comprehensive utilization is researched. Supposing the privilege of single product assembling as the core, the scheduling parts filter method based on multiple constraints and former rules. For the space layout problem, a clingy forward and backward algorithms is proposed to judge the assemble position regarding the space comprehensive utilization rate. The classification of the various disturbances in the actual production is summarized. Three basic algorithms are proposed, including insertion, moving and re-scheduling algorithm, in order to solve the assembly dynamic scheduling problem driven by production disturbance events. Finally, take rocket as the example， the rocket assembly space production scheduling system is developed, combining with the proposed algorithm. The practicability of the system is validated using real data.

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Little, David, and Andrew Hemmings. "Scheduling Automated Assembly Systems." Assembly Automation 13, no. 4 (1993): 8–13. http://dx.doi.org/10.1108/eb004401.

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Song, Hailong, Shengluo Yang, Shuoxin Yin, Junyi Wang, and Zhigang Xu. "Intelligent Scheduling of a Pulsating Assembly Flow Shop Considering a Multifunctional Automated Guided Vehicle." Applied Sciences 15, no. 5 (2025): 2593. https://doi.org/10.3390/app15052593.

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The pulsating assembly line is widely used in modern manufacturing, particularly in high-precision industries such as aerospace, where it greatly enhances production efficiency. To achieve overall optimization, both product scheduling and Automated Guided Vehicle (AGV) scheduling must be simultaneously optimized. However, existing research predominantly focuses on product scheduling, with limited attention given to AGV scheduling. This paper proposes an optimized solution for the pulsating assembly line scheduling problem, incorporating multifunctional AGV scheduling. A mathematical model is developed and three AGV selection strategies and three AGV standby strategies are designed to optimize AGV scheduling and control. To improve scheduling efficiency, nine heuristic strategies are introduced, along with the Variable Neighborhood Descent (VND) algorithm as a metaheuristic method for product scheduling. The VND algorithm refines the solution through multiple neighborhood searches, enhancing both the precision and efficiency of product scheduling. Our experimental results demonstrate that the proposed strategies significantly improve the production efficiency of pulsating assembly workshops, reduce AGV scheduling costs, and optimize overall production workflows. This study offers novel methods for intelligent scheduling in pulsating assembly workshops, contributing to the advancement of manufacturing toward “multiple varieties, small batches, and customization”.

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Liu, Sheng Hui, Shu Li Zhang, and Hong Bo Xu. "An Assembly Scheduling Model for Complex Machine Product." Applied Mechanics and Materials 380-384 (August 2013): 4643–46. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4643.

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According to the characteristics of assembly scheduling, an assembly scheduling model for complex machine product was defined in this paper. The assembly relationship of a complex machine product is expressed by a job assembly graph. A job assembly graph is translated into an assembly process graph. The assembly process graph is a tree-form. There is a partial order between each child node and its parent in the assembly process graph. Then an assembly scheduling algorithm for complex machine product is given. The goal of the algorithm is minimizing total assembling time. The algorithm could always gain a good assembly schedule through minimizing the waiting time of all assembling operations. The feasibility and efficiency of the algorithm was verified through an example.

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Hu, Xiaomei, Zhenghao Xu, Long Yang, and Rujiang Zhou. "A Novel Assembly Line Scheduling Algorithm Based on CE-PSO." Mathematical Problems in Engineering 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/685824.

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With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved.

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Sotskov, Yuri N. "Assembly and Production Line Designing, Balancing and Scheduling with Inaccurate Data: A Survey and Perspectives." Algorithms 16, no. 2 (2023): 100. http://dx.doi.org/10.3390/a16020100.

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Assembly lines (conveyors) are traditional means of large-scale and mass-scale productions. An assembly line balancing problem is needed for optimizing the assembly process by configuring and designing an assembly line for the same or similar types of final products. This problem consists of designing the assembly line and distributing the total workload for manufacturing each unit of the fixed product to be assembled among the ordered workstations along the constructed assembly line. The assembly line balancing research is focused mainly on simple assembly line balancing problems, which are restricted by a set of conditions making a considered assembly line ideal for research. A lot of published research has been carried out in order to describe and solve (usually heuristically) more realistic generalized assembly line balancing problems. Assembly line designing, balancing and scheduling problems with not deterministic (stochastic, fuzzy or uncertain) parameters have been investigated in many published research works. This paper is about the design and optimization methods for assembly and disassembly lines. We survey the recent developments for designing, balancing and scheduling assembly (disassembly) lines. New formulations of simple assembly line balancing problems are presented in order to take into account modifications and uncertainties characterized by real assembly productions.

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Kuo, Chung Hsien, M. D. Jeng, J. J. Wing, and Tai Hong Wang. "Optimization of Component Placement Scheduling for SMT Assemblies." Materials Science Forum 505-507 (January 2006): 1123–28. http://dx.doi.org/10.4028/www.scientific.net/msf.505-507.1123.

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The surface mounting of electronic component is the major manufacturing technology for the electronic products in the last decade. The surface mounting technology (SMT) is an assembly process that assembles the surface mountable component (SMC) and the printed circuit board (PCB) together. The SMT mounter is an automatic assembly machine that processes the SMT assemblies in terms of the optical positioning and robotic handling. The SMT assembly consists of calibrating printed circuit board (PCB); vacuuming components form feeder stations; compensating the orientation of the vacuumed surface mountable component (SMC); and finally placing SMC chips on the PCB. In order to increase the throughput, the synchronous batch vacuuming of SMC components is designed. In addition, different types of component feeding and mixing in each batch increase the difficulties of finding the best component mounting sequence. In this paper, the optimal component placement scheduler is desired to perform higher assembly performance and to reduce the cycle time. The proposed optimal component placement scheduler is developed based on the rule based heuristic search approach. In addition, to evaluate the cycle time of each heuristic search, the route oriented Petri nets (ROPN) based SMT assembly models are constructed. The optimal component placement scheduler can be further determined in terms of evaluating the ROPN SMT assembly models. Finally, the practical test PCB board data is discussed in this paper.

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Wang, Zhenhua, and Youling Chen. "Research on Assembly Scheduling of Complex Electromechanical Products Based on Improved Particle Swarm Optimization." Journal of Physics: Conference Series 2229, no. 1 (2022): 012011. http://dx.doi.org/10.1088/1742-6596/2229/1/012011.

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Abstract The assembly shop production scheduling of complex electromechanical products is a typical discrete variable NP-hard problem. In order to solve the assembly job scheduling problem of a large transformer assembly shop, an improved particle swarm algorithm is used to solve the optimal assembly task scheduling result. In order to minimize the maximum completion time, the traditional particle swarm optimization (PSO) algorithm was improved according to the characteristics of large transformer assembly process. First, the two-stage coding method of process and assembly team is adopted. Then, in order to improve the quality of the initial solution, the initialization method that minimizes the completion time is selected, and the adaptive inertia weight optimization speed update formula is adopted. Finally, the simulation study is carried out with relevant example data. Compared with the traditional PSO, the maximum completion time and convergence speed are significantly improved, which verifies the effectiveness of the improved PSO, and obtains the production scheduling Gantt chart of the workshop.

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Zhang, Zhicong, Kaishun Hu, Shuai Li, Huiyu Huang, and Shaoyong Zhao. "Chip Attach Scheduling in Semiconductor Assembly." Journal of Industrial Engineering 2013 (March 26, 2013): 1–11. http://dx.doi.org/10.1155/2013/295604.

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Chip attach is the bottleneck operation in semiconductor assembly. Chip attach scheduling is in nature unrelated parallel machine scheduling considering practical issues, for example, machine-job qualification, sequence-dependant setup times, initial machine status, and engineering time. The major scheduling objective is to minimize the total weighted unsatisfied Target Production Volume in the schedule horizon. To apply Q-learning algorithm, the scheduling problem is converted into reinforcement learning problem by constructing elaborate system state representation, actions, and reward function. We select five heuristics as actions and prove the equivalence of reward function and the scheduling objective function. We also conduct experiments with industrial datasets to compare the Q-learning algorithm, five action heuristics, and Largest Weight First (LWF) heuristics used in industry. Experiment results show that Q-learning is remarkably superior to the six heuristics. Compared with LWF, Q-learning reduces three performance measures, objective function value, unsatisfied Target Production Volume index, and unsatisfied job type index, by considerable amounts of 80.92%, 52.20%, and 31.81%, respectively.

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Wang, Hao Xiang, and Hong Sen Yan. "An Adaptive Assembly Scheduling Approach in Knowledgeable Manufacturing." Applied Mechanics and Materials 433-435 (October 2013): 2347–50. http://dx.doi.org/10.4028/www.scientific.net/amm.433-435.2347.

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To address the uncertainty of production environment in aircraft engine assembly, an adaptive optimization scheduling algorithm is designed for an aircraft engine assembly line in knowledgeable manufacturing. A Q-learning adaptive scheduling model of aircraft engine assembly is built on the objective function of minimizing earliness penalty. Simulation experiments indicate that the proposed algorithm outperforms other scheduling rules much. Especially, better results are generally achieved with the increase in number of engines to show good adaptive performance.

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Xu, Guangyan, Zailin Guan, Kai Peng, and Lei Yue. "Collaborative scheduling of machining-assembly in complex multiple parallel production lines environment considering kitting constraints." International Journal of Industrial Engineering Computations 14, no. 4 (2023): 749–66. http://dx.doi.org/10.5267/j.ijiec.2023.7.003.

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In multi-stage machining-assembly production, collaborative scheduling for multiple production lines can effectively improve the execution efficiency of production planning and increase the effective output of the production system. In this paper, a production scheduling mathematical model was constructed for the collaborative scheduling problem of machining-assembly multi-production lines with kitting constraints, with the optimization objectives of minimizing assembly completion time and tardiness time. For the scheduling model, the product assembly process is constrained by the machining sequence of the jobs on the machining lines. Only by collaborating on the production scheduling schemes of the machine line and the assembly line as a whole can the output efficiency of the product on the assembly line be improved. An improved hybrid multi-objective optimization algorithm named SMOEA/D is designed to solve this scheduling model. The algorithm uses adaptive parents’ selection and mutation rate strategies and integrates the Tabu search strategy for the search process in the solution space when the solution of the sub-problem has not been improved after specified search generations, to improve the local search ability and search accuracy of MOEA/D algorithm. To verify the performance of the SMOEA/D algorithm in solving machining-assembly collaborative scheduling problems in production systems with different resource configurations and scales, two sets of numerical experiments were designed, corresponding to situations where the number of operations on each production line is equal or unequal. The running results of the proposed algorithm were compared with three other well-known multi-objective algorithms. The comparison results indicate that the SMOEA/D algorithm is effective and superior for solving such problems.

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Najam, Aaima, Faizan Ahmad, and Zeeshan Ahmed. "Dynamic-Model Assembly Line Scheduling." Research Journal of Applied Sciences, Engineering and Technology 6, no. 8 (2013): 1446–49. http://dx.doi.org/10.19026/rjaset.6.3968.

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Little, David, and Andrew Hemmings. "Automated assembly scheduling: A review." Computer Integrated Manufacturing Systems 7, no. 1 (1994): 51–61. http://dx.doi.org/10.1016/0951-5240(94)90053-1.

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Costantino, Francesco, Alberto Felice De Toni, Giulio Di Gravio, and Fabio Nonino. "Scheduling Mixed-Model Production on Multiple Assembly Lines with Shared Resources Using Genetic Algorithms: The Case Study of a Motorbike Company." Advances in Decision Sciences 2014 (October 2, 2014): 1–11. http://dx.doi.org/10.1155/2014/874031.

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The authors deal with the topic of the final assembly scheduling realized by the use of genetic algorithms (GAs). The objective of the research was to study in depth the use of GA for scheduling mixed-model assembly lines and to propose a model able to produce feasible solutions also according to the particular requirements of an important Italian motorbike company, as well as to capture the results of this change in terms of better operational performances. The “chessboard shifting” of work teams among the mixed-model assembly lines of the selected company makes the scheduling problem more complex. Therefore, a complex model for scheduling is required. We propose an application of the GAs in order to test their effectiveness to real scheduling problems. The high quality of the final assembly plans with high adherence to the delivery date, obtained in a short elaboration time, confirms that the choice was right and suggests the use of GAs in other complex manufacturing systems.

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TAO, NING-RONG, ZU-HUA JIANG, and LU ZHEN. "SPATIAL SCHEDULING AND WORKFORCE ASSIGNMENT PROBLEM IN BLOCK ASSEMBLY SHOP OF SHIPBUILDING." Asia-Pacific Journal of Operational Research 31, no. 01 (2014): 1450006. http://dx.doi.org/10.1142/s0217595914500067.

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For shipbuilding, spatial scheduling and workforce assignment are two important issues for the operation management in block assembly shops. Spatial scheduling is to decide where and when to assemble blocks, while workforce assignment is to assign working teams to the blocks. Traditionally, they are made separately at different levels in the production management framework. The combining of such decisions presents additional complexity and new problems. This paper proposes an approach that solves jointly the spatial scheduling problem and the workforce assignment problem. The objective is to improve the coordination among working teams and increase the productivity of assembly shops. A spatial layout strategy is designed according to extreme point and deep bottom left strategies. By using genetic algorithm, a solution method is developed based on the spatial layout strategy and several assignment and sequence rules. Some computational experiments are conducted to evaluate the performance of the presented algorithm and compare it with other commonly used methods. Computational results validate the effectiveness and efficiency of the proposed algorithm.

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Xu, E. B., F. F. Zou, P. P. Shan, Z. Y. Wang, and B. X. Shi. "An improved multi-objective firefly algorithm for integrated scheduling approach in manufacturing and assembly considering time-sharing step tariff." Advances in Production Engineering & Management 19, no. 1 (2024): 5–20. http://dx.doi.org/10.14743/apem2024.1.489.

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Today, energy conservation and reduction of consumption are crucial concerns for manufacturing companies. Current research on integrated scheduling of processing and assembly typically focuses only on equipment resources and processing and assembly processes. A new method for energy-saving integrated scheduling in workshops has been proposed, which incorporates the recently introduced time-of-use tiered electricity prices into the scheduling optimization model. This method also introduces an operation strategy of turning equipment on and off during idle periods. A multi-objective mathematical model was developed to minimize energy consumption and assembly delay time in the processing and assembly processes. Due to the complexity of the model, the standard firefly algorithm was improved when used to solve the model. This involved designing a three-layer encoding method and two decoding methods, and providing detailed steps of the algorithm. Using a mixed flow production line as an example, the final scheduling solutions were obtained through model construction and algorithm solving, taking into account the tiered electricity price. The results of the example demonstrate that parallel processing and assembly effectively reduce assembly delay costs, and the implementation of the on/off strategy reduces power consumption during the machining process.

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Xia, Beixin, Yuan Li, Jiayi Gu, and Yunfang Peng. "Research on Sustainable Scheduling of Material-Handling Systems in Mixed-Model Assembly Workshops Based on Deep Reinforcement Learning." Sustainability 16, no. 22 (2024): 10025. http://dx.doi.org/10.3390/su162210025.

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In order to dynamically respond to changes in the state of the assembly line and effectively balance the production efficiency and energy consumption of mixed-model assembly, this paper proposes a deep reinforcement learning sustainable scheduling model based on the Deep Q network. According to the particularity of the workshop material-handling system, the action strategy and reward and punishment function are designed, and the neural network structure, parameter update method, and experience pool selection method of the original Deep Q network dual neural network are improved. Prioritized experience replay is adopted to form a real-time scheduling method for workshop material handling based on the Prioritized Experience Replay Deep Q network. The simulation results demonstrate that compared with other scheduling methods, this deep reinforcement learning approach significantly optimizes material-handling scheduling in mixed-flow assembly workshops, effectively reducing handling distance while ensuring timely delivery to the assembly line, ultimately achieving maximum output with sustainable considerations.

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Wang, Lun, Jing Min Li, and Jin Yao. "Scheduling Platform of Semiconductor Assembly and Test Producing Line." Key Engineering Materials 474-476 (April 2011): 764–70. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.764.

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With the complexity of new products and devices increasing, the scheduling of semiconductor assembly and test producing line becomes more and more complicated. To deal with the problems of complex operation, low efficiency, high workload and unsatisfactory scheduling results in making plan, we develop a scheduling platform. This paper analyzes the features of the semiconductor assembly and test producing line, and builds the system from function design and database construction. At last, it presents the application of the system. Now the platform has successfully applied in a certain large semiconductor production enterprise. It helps schedulers make the scheduling more accurately and more conveniently; the scheduling results also can be supported for further decision-making clearly.

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S, Saravanakumar. "Simultaneous Scheduling of Assembly and Production Shops Using GA based Heuristic." International Journal of Psychosocial Rehabilitation 24, no. 4 (2020): 6128–39. http://dx.doi.org/10.37200/ijpr/v24i4/pr2020423.

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TURITTO, Michele, and Svetan RATCHEV. "Towards Microfeeding Devices for Ultra Precision Assembly(Manufacturing systems and Scheduling)." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2005.2 (2005): 403–8. http://dx.doi.org/10.1299/jsmelem.2005.2.403.

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Xiao, Can Jun, Jin Ming Li, and Jin Yao. "Semiconductor Assembly and Test Production Line Simulation Technology." Advanced Materials Research 490-495 (March 2012): 3562–67. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.3562.

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The technology to simulate the semiconductor production line, consider main factors that will impact the production, and get the output from the simulation system as the reference for production scheduling is presented in this paper. By initiating the simulation model, include the die delivery information, equipment occupation information and etc. base on the FIFO (first in first out) and other principles, simulated the discrete event with four categories and also for two basic actions. The prediction result aligned with the actual production by T test. Changing the scheduling schemes at the same initial state of product line, engineer could obtain the optimal scheduling scheme by the comparing different simulation results. This study is not only an efficient, visual scheduling method, but also it is the basis for product re-scheduling. And this technology has been deployed in one ATM (Assembly and Test Manufacturing factory) factory in Chengdu and gets positive feedback.

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Yu, Fengxiao, Yipu Peng, Jian Li, Guangqi Zhou, and Li Chen. "An Analysis of Optimization for Car PBS Scheduling Based on Greedy Strategy State Transition Algorithm." Applied Sciences 13, no. 10 (2023): 6194. http://dx.doi.org/10.3390/app13106194.

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The differences in constraints between an automotive painting workshop and a final assembly workshop can lead to production scheduling disruptions, and using the Painted Body Store (PBS) in automotive manufacturing can optimize production scheduling to meet the production requirements of the final assembly workshop. This is achieved by establishing a multi-objective mixed-integer optimization scheduling model for PBS and solving the model using a state transition algorithm based on the greedy strategy; finally, a comparison was made with the classical genetic algorithm. The results show that the optimal objective function is achieved when the body sequence movement iterations for data sets N and R are 34 and 54, respectively. At this point, the highest objective function scores are 23.46 and 49.79, and vehicles entering the PBS scheduling system from the painting-to-assembly line require 31 and 38 sequence adjustments, respectively. Compared with the classical genetic algorithm, the simulation results show that the state transition algorithm based on the greedy strategy is significantly better; it can also perform well in discrete sequence movement operations, demonstrating strong global search capabilities and fast convergence. It provides a new approach for optimizing vehicle scheduling in the automotive painting-to-assembly line.

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Gao, Yan, Xin Zhang, and Jian Zhong Xu. "An Improved Production Scheduling Algorithm Based on Resource Constraints." Applied Mechanics and Materials 455 (November 2013): 619–24. http://dx.doi.org/10.4028/www.scientific.net/amm.455.619.

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For resource-constrained project scheduling problems, with aircraft assembly as its background, we established its mathematics model as constraint satisfaction problem. An improved critical path scheduling algorithm is proposed, considering the constraints of precedence relations, resource constraints and space constraints, through the two stages of planning, reaching for aircraft assembly task scheduling optimization objectives. Through the given numerical example results show that, when the objective consists in minimizing the project duration, the algorithm has better performance.

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Shang, Zhengyang, Jinan Gu, Wei Ding, and Enock A. Duodu. "Spatial Scheduling Optimization Algorithm for Block Assembly in Shipbuilding." Mathematical Problems in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/1923646.

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Block assembly consumes the majority of processing time and resources in shipbuilding, and the block spatial scheduling (BSS) related to block assembly has been widely studied as the key to improve shipbuilding efficiency. BSS is a complicated NP-hard problem that aims to minimize the makespan. Since each block has specific building time and space constraints, the BSS problem can be hardly found with an acceptable solution by using constant scheduling rules. Thus, in this study, we considered the BSS problem as a time-constrained 3D bin packing mathematical model and proposed an allocation algorithm, best contact algorithm (BCA), that is more suitable for dynamic processes. Then, for global optimization of the BSS problem, we regarded the starting time of each block as a variable and used the genetic algorithm (GA) to operate and optimize the block assembly sequence. Finally, we tested the BCA + GA scheduling system with real data from a shipyard and thereby determined the block scheduling status and the daily utilization rate of the work plate. Comparison shows that the proposed algorithm is able to get shorter makespan and better block scheduling effect; it realized the optimization of the block spatial scheduling dynamically.

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Fazlollahtabar, Hamed. "Parallel autonomous guided vehicle assembly line for a semi-continuous manufacturing system." Assembly Automation 36, no. 3 (2016): 262–73. http://dx.doi.org/10.1108/aa-08-2015-065.

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Purpose This paper aims to propose a parallel automated assembly line system to produce multiple products in a semi-continuous system. Design/methodology/approach The control system developed in this research consists of a manufacturing system for two-level hierarchical dynamic decisions of autonomous/automated/automatic-guided vehicles (AGVs) dispatching/next station selection and machining schedules and a station control scheme for operational control of machines and components. In this proposed problem, the assignment of multiple AGVs to different assembly lines and the semi-continuous stations is a critical objective. AGVs and station scheduling decisions are made at the assembly line level. On the other hand, component and machining resource scheduling are made at the station level. Findings The proposed scheduler first decomposes the dynamic scheduling problems into a static AGV and machine assignment during each short-term rolling window. It optimizes weighted completion time of tasks for each short-term window by formulating the task and resource assignment problem as a minimum cost flow problem during each short-term scheduling window. A comprehensive decision making process and heuristics are developed for efficient implementation. A simulation study is worked out for validation. Originality/value Several assembly lines are configured to produce multiple products in which the technologies of machines are shared among the assembly lines when required. The sequence of stations is pre-specified in each assembly line and the components of a product are kept in machine magazine. The transportation between the stations in an assembly line (intra assembly line) and among stations in different assembly lines (inter assembly line) are performed using AGVs.

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Muñoz-Sánchez, Rafael, Iris Martínez-Salazar, José Luis González-Velarde, and Yasmín Á. Ríos Solís. "Two hybrid flow shop scheduling lines with assembly stage and compatibility constraints." PLOS ONE 19, no. 6 (2024): e0304119. http://dx.doi.org/10.1371/journal.pone.0304119.

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Two hybrid flow shop scheduling lines must be coordinated to assemble batches of terminated products at their last stage. Each product is thus composed of two jobs, each produced in one of the lines. The set of jobs is to be processed in a series of stages to minimize the makespan of the scheduling, but jobs forming a product must arrive at the assembly line simultaneously. We propose a mixed integer linear programming model. Then, based on the model, we propose a pull-matheuristic algorithm. Finally, we present two metaheuristics, a greedy randomized adaptive search procedure and a biased random key genetic algorithm, and compare all the methodologies with real-based instances of a production scheduling problem in the automobile manufacturing industry. The greedy algorithm yields high-quality solutions, while the genetic one offers the best computational times.

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Croci, F., M. Perono, and A. Pozzetti. "PCB assembly scheduling through kit concept." Production Planning & Control 11, no. 2 (2000): 141–52. http://dx.doi.org/10.1080/095372800232342.

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Van Brussel, H. "Planning and Scheduling of Assembly Systems." CIRP Annals 39, no. 2 (1990): 637–44. http://dx.doi.org/10.1016/s0007-8506(07)63000-5.

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Kusiak, Andrew. "Scheduling flexible machining and assembly systems." Annals of Operations Research 15, no. 1 (1988): 337–52. http://dx.doi.org/10.1007/bf02186802.

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Weigert, G., and T. Henlich. "Simulation-based scheduling of assembly operations." International Journal of Computer Integrated Manufacturing 22, no. 4 (2009): 325–33. http://dx.doi.org/10.1080/09511920802225914.

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Ghauvet, Fabrice, and Jean-Marie Proth. "On-Line Scheduling In Assembly Processes." INFOR: Information Systems and Operational Research 39, no. 3 (2001): 245–56. http://dx.doi.org/10.1080/03155986.2001.11732440.

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Jiang, Nan-Yun, and Hong-Sen Yan. "Integrated optimization of production planning and scheduling in uncertain re-entrance environment for fixed-position assembly workshops." Journal of Intelligent & Fuzzy Systems 42, no. 3 (2022): 1705–22. http://dx.doi.org/10.3233/jifs-211159.

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For the fixed-position assembly workshop, the integrated optimization problem of production planning and scheduling in the uncertain re-entrance environment is studied. Based on the situation of aircraft assembly workshops, the characteristics of fixed-position assembly workshop with uncertain re-entrance are abstracted. As the re-entrance repetition obeys some type of probability distribution, the expected value is used to describe the repetition, and a bi-level stochastic expected value programming model of integrated production planning and scheduling is constructed. Recursive expressions for start time and completion time of assembly classes and teams are confirmed. And the relation between the decision variable in the lower-level model of scheduling and the overtime and earliness of assembly classes and teams in the upper-level model of production planning is identified. Addressing the characteristics of bi-level programming model, an alternate iteration method based on Improved Genetic Algorithm (AI-IGA) is proposed to solve the models. Elite Genetic Algorithm (EGA) is introduced for the upper-level model of production planning, and Genetic Simulated Annealing Algorithm based on Stochastic Simulation Technique (SS-GSAA) is developed for the lower-level model of scheduling. Results from our experiments demonstrate that the proposed method is feasible for production planning and optimization of the fixed-position assembly workshop with uncertain re-entrance. And algorithm comparison verifies the effectiveness of the proposed algorithm.

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Nie, Li, Yue Wei Bai, Xin Jiang, and Chang Tao Pang. "An Approach for Level Scheduling Mixed Models on an Assembly Line in a JIT Production System." Applied Mechanics and Materials 697 (November 2014): 473–77. http://dx.doi.org/10.4028/www.scientific.net/amm.697.473.

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A mixed-model assembly line (MMAL) is a type of production system that is capable of producing different models of a common base product simultaneously. Mixed-model assembly line level scheduling problem (MMALSP) is a challenge for Just-in-time (JIT) production systems. In the paper, a mixed-model assembly line level scheduling model is proposed which considers multiple objectives simultaneously. The considered objectives include the variation in parts consumption considering the batch part supply, inventory cost and maximum transportation load. An approach based on genetic algorithm is proposed to solve the multiple objectives problem. In order to translate individuals in the GA population into candidate scheduling schemes a delivery scheduling algorithm (DSA) is proposed. In addition, dimensionless processing technique is employed in the design of the fitness function in order to comprehensively evaluate different individual considering three objectives simultaneously. The approach’s performance is validated through comprehensive experiment.

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Jiang, Tianhua, Lu Liu, Huiqi Zhu, and Yaping Li. "An Improved Elephant Herding Optimization for Energy-Saving Assembly Job Shop Scheduling Problem with Transportation Times." Axioms 11, no. 10 (2022): 561. http://dx.doi.org/10.3390/axioms11100561.

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The energy-saving scheduling problem (ESSP) has gained increasing attention of researchers in the manufacturing field. However, there is a lack of studies on ESSPs in the assembly job shop environment. In contrast with traditional scheduling problems, the assembly job shop scheduling problem (AJSP) adds the additional consideration of hierarchical precedence constraints between different jobs of each final product. This paper focuses on developing a methodology for an energy-saving assembly job shop scheduling problem with job transportation times. Firstly, a mathematical model is constructed with the objective of minimizing total energy consumption. Secondly, an improved elephant herding optimization (IEHO) is proposed by considering the problem’s characteristics. Finally, thirty-two different instances are designed to verify the performance of the proposed algorithm. Computational results and statistical data demonstrate that the IEHO has advantages over other algorithms in terms of the solving accuracy for the considered problem.

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KURASHIGE, Kenji, Yoshinari YANAGAWA, Shigeji MIYAZAKI, and Yoshimasa KAMEYAMA. "Mixed-Model Assembly Line Scheduling in Consideration of Assembly Time." Transactions of the Japan Society of Mechanical Engineers Series C 64, no. 624 (1998): 3238–45. http://dx.doi.org/10.1299/kikaic.64.3238.

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Jeong, Bongju, Seung-Bae Sim, and Hosang Jung. "Heuristics for assembly operation scheduling problem in flexible assembly systems." International Journal of Advanced Manufacturing Technology 29, no. 9-10 (2006): 1033–40. http://dx.doi.org/10.1007/s00170-005-2605-1.

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Skornyakova, E. A., V. M. Vasyukov, and V. S. Sulaberidze. "Algorithmisation methods for scheduling in high-performance assembly manufacturing." Journal of «Almaz – Antey» Air and Space Defence Corporation, no. 4 (December 30, 2018): 15–22. http://dx.doi.org/10.38013/2542-0542-2018-4-15-22.

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The authors analysed the most popular production planning and scheduling software systems. Their main disadvantage is that they lack lean manufacturing tools. There exists a demand for client-oriented systems based on lean principles. The paper describes a unique algorithm for computing the optimum takt time, which forms the basis of the scheduling system developed by the authors. We present methods of algorithmising the scheduling process and results of generating schedules using several algorithms

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Lin, Yi Li, and Jian Feng Lu. "Research on the Assembly Line Scheduling of Fixed Objects for the Large Complex Products." Applied Mechanics and Materials 483 (December 2013): 538–41. http://dx.doi.org/10.4028/www.scientific.net/amm.483.538.

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According to the complexity of the assembly line for the large complex products, a new production pattern with fixed objects for the mixed model assembly line is proposed. Improved GA is used to solve the scheduling problem .In this paper, a production scheduling system is developed. It can speed up the production cycle, lower the cost, improve the productivity and so on.

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Liang, Erlei, Dongling Jiang, Chengling Liu, and Tingyu Duan. "Intelligent scheduling optimization of prefabricated components for assembly buildings." Advances in Computer and Engineering Technology Research 1, no. 2 (2024): 19. http://dx.doi.org/10.61935/acetr.2.1.2024.p19.

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Prefabricated construction, as an emerging architectural model, has the characteristics of fast construction process and flexible design, and has been widely used in the field of architecture in China. As the core component of prefabricated buildings, the schedule of prefabricated components directly affects the progress and quality of the project. This study extends the volume of prefabricated components from a single building to a group of buildings, designs and solves an intelligent scheduling scheme model based on project construction schedule and procurement plan, and proposes two reference building group scheduling schemes and their applicable conditions. Genetic algorithm is used to optimize vehicle scheduling and transportation paths to achieve intelligent scheduling of prefabricated components in prefabricated building groups, ensuring project progress and quality.

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Rao, Youfu, Zhihuang Chen, Weikang Fang, and Zailin Guan. "Research on Simulation Based Dynamic Scheduling Strategy of the Logistics Distribution System for Assembly Lines in Engineering Machinery." Journal of Physics: Conference Series 2101, no. 1 (2021): 012046. http://dx.doi.org/10.1088/1742-6596/2101/1/012046.

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Abstract The objective of designing a logistics system for assembly production planning should be accurate, efficient distribution, and low cost. It is difficult to use mathematical methods to solve the design of logistics distribution route planning for a given layout of assembly lines which often be restricted. We take the logistics distribution system for actual assembly lines of engineering machinery as the research object, and analyze its current status. And we build a 3D simulation model of the corresponding scene, and use a variety of logistics scheduling methods to optimize the logistics distribution system. Considering the congestion strategy characteristics of some distribution channels, adjustment strategy of time window is proposed, and a dynamic scheduling strategy of congestion is designed. Combined with the simulation tests, we analyze and optimize the solution suitable for the actual assembly lines. The results show that our strategy had better performance than other common scheduling strategies. And the proposed strategy could optimize the material distribution system of assembly lines, reduced the number of vehicles and the cost of the enterprise.

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Muñoz-Guevara, John Andrés, Eliana Toro-Ocampo, and Mario Cesar Vélez-Gallego. "Robotic assembly systems planning and scheduling problems: A revie." International Journal of Industrial Engineering Computations 15, no. 4 (2024): 845–70. http://dx.doi.org/10.5267/j.ijiec.2024.8.001.

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Evolving market trends, characterized by an increasing demand for personalized products with short life cycles and variable demands, pose a significant challenge to the industry. One of the industry's strategies is to adopt robotic assembly systems to improve productivity and increase system flexibility. The widespread adoption of robots in assembly processes is evident; however, success is not guaranteed with implementation alone. Equally critical is addressing assembly planning and scheduling problems in robotic systems. To facilitate understanding, this review offers, in Section 2, a classification of robotic assembly systems, with an emphasis on a new layout termed the robotic matrix-structure assembly system. Section 3 classifies the planning and scheduling problems applied to the robotic assembly systems. In Section 4, we discuss the approaches and techniques used to formulate and solve the planning and programming challenges. Finally, statistical data are presented to illustrate current research trends and identify gaps for future research.

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Liu, Zhuo, David K. H. Chua, and Hwee Wee Keng. "A Simulation Model for Spatial Scheduling of Dynamic Block Assembly in Shipbuilding." Journal of Engineering, Project, and Production Management 1, no. 1 (2011): 3–12. http://dx.doi.org/10.32738/jeppm.201107.0002.

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Liu, Junli, Deyu Zhang, Zhongpeng Liu, Tianyu Guo, and Yanyan Yan. "Construction of a Digital Twin System and Dynamic Scheduling Simulation Analysis of a Flexible Assembly Workshops with Island Layout." Sustainability 16, no. 20 (2024): 8851. http://dx.doi.org/10.3390/su16208851.

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Assembly Workshops with Island Layout (AWIL) possess flexible production capabilities that realize product diversification. To cope with the complex scheduling challenges in flexible workshops, improve resource utilization, reduce waste, and enhance production efficiency, this paper proposes a production scheduling method for flexible assembly workshops with an island layout based on digital twin technology. A digital twin model of the workshop is established according to production demands to simulate scheduling operations and deal with complex scheduling issues. A workshop monitoring system is developed to quickly identify abnormal events. By employing an event-driven rolling-window rescheduling technique, a dynamic scheduling service system is constructed. The rolling window decomposes scheduling problems into consecutive static scheduling intervals based on abnormal events, and a genetic algorithm is used to optimize each interval in real time. This approach provides accurate, real-time scheduling decisions to manage disturbances in workshop production, which can enhance flexibility in the production process, and allows rapid adjustments to production plans. Therefore, the digital twin system improves the sustainability of the production system, which will provide a theoretical research foundation for the real-time and unmanned production scheduling process, thereby achieving sustainable development of production.

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Cheng, Jie. "The Fault Diagnosis Method of Mixed-Model Assembly Line Based on Dynamic Causality Bayesian Network." Applied Mechanics and Materials 310 (February 2013): 592–95. http://dx.doi.org/10.4028/www.scientific.net/amm.310.592.

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For timely diagnosing the faults of mixed-model assembly line, and highly eliminating abnormal the production line, the time causality relation in the faults of mixed-model assembly line was Fuzzy discretized by the introduction of fuzzy set theory, and the fault diagnosis method of mixed-model assembly line based on dynamic causality bayesian network was established in this paper. Finally, a fault diagnosis simulation system of mixed-model assembly line based on dynamic causality bayesian network was demonstrated and validated by QUEST software. It has shown the proposed method can improve the benefit of production scheduling, and provide a support for adapting to complex and dynamic production scheduling in mixed-model flow production.

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Wang, Xiao, Mei Liu, Peisi Zhong, Chao Zhang, and Dawei Zhang. "A Discrete Cooperative Control Method for Production Scheduling Problem of Assembly Manufacturing System." Sustainability 15, no. 18 (2023): 13785. http://dx.doi.org/10.3390/su151813785.

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With a sharp decrease in resource utilization of the complex production process, integrated scheduling methods are urgently needed in assembly manufacturing industries. To this end, this paper presents an integrated scheduling with jobs processing and assembly sequence (ISJPAS) problem where jobs and assemblies can be processed simultaneously. As the first contribution to this work, we develop a mixed integer nonlinear programming model (MINLP) that aims at minimizing maximum completion time and determining the earliness and tardiness of jobs and resulting inventory time. The structured property of the optimal scheduling solution is analyzed with regard to job sequencing and assembly sequencing. The NP-hard nature of the problem is proved, which provides upper and lower bounds on the optimal solution. Second, an efficient discrete assembly time and arrival time control (DAATC) method is presented based on continuous time variable control models. From a modified set of benchmark problems, the proposed method is tested by comparing four assembly association levels in real applications. The comparisons indicate the potentiality of our method to satisfy the due date. Lastly, relevance of practical applications are discussed, and several future research avenues are emphasized.

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Zheng, Peng, Peng Zhang, Ming Wang, and Jie Zhang. "A Data-Driven Robust Scheduling Method Integrating Particle Swarm Optimization Algorithm with Kernel-Based Estimation." Applied Sciences 11, no. 12 (2021): 5333. http://dx.doi.org/10.3390/app11125333.

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The assembly job shop scheduling problem (AJSSP) widely exists in the production process of many complex products. Robust scheduling methods aim to optimize the given criteria for improving the robustness of the schedule by organizing the assembly processes under uncertainty. In this work, the uncertainty of process setup time and processing time is considered, and a framework for the robust scheduling of AJSSP using data-driven methodologies is proposed. The framework consists of obtaining the distribution information of uncertain parameters based on historical data and using a particle swarm optimization (PSO) algorithm to optimize the production schedule. Firstly, the kernel density estimation method is used to estimate the probability density function of uncertain parameters. To control the robustness of the schedule, the concept of confidence level is introduced when determining the range of uncertain parameters. Secondly, an interval scheduling method constructed using interval theory and a customized discrete PSO algorithm are used to optimize the AJSSP with assembly constraints. Several computational experiments are introduced to illustrate the proposed method, and these were proven effective in improving the performance and robustness of the schedule.

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Mazur, Michał, and Antoni Niederliński. "A Two-stage approach for an optimum solution of the car assembly scheduling problem Part 1. Problem statement, solution outline and tutorial example." Archives of Control Sciences 25, no. 3 (2015): 355–65. http://dx.doi.org/10.1515/acsc-2015-0023.

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Abstract A new approach to solving realistic car assembly scheduling problems for mixed model assembly line is presented. It is proposed to decompose the problem into two subproblems: 1) a sequencing problem that generates admissible car sequences fulfilling capacity constraints for all car models in the production plan, 2) a scheduling problem that determines an admissible car sequence with shortest makespan. The details of this approach are illustrated by a simple numerical example.

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Jeong, B. J. "Evaluation of assembly sequences using generalized flexible assembly systems scheduling problem." Computers & Industrial Engineering 33, no. 3-4 (1997): 777–80. http://dx.doi.org/10.1016/s0360-8352(97)00251-9.

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DAR-EL, E. M., and M. RABINOVITCH. "Optimal planning and scheduling of assembly lines†." International Journal of Production Research 26, no. 9 (1988): 1433–50. http://dx.doi.org/10.1080/00207548808947958.

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Hatami, Sara, Rubén Ruiz, and Carlos Andrés-Romano. "The Distributed Assembly Permutation Flowshop Scheduling Problem." International Journal of Production Research 51, no. 17 (2013): 5292–308. http://dx.doi.org/10.1080/00207543.2013.807955.

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Journal articles on the topic 'Assembly scheduling'

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