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Journal articles on the topic 'Assembly sequence planning'

Author: Grafiati

Published: 22 February 2025

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1

Wan, Weiwei, Kensuke Harada, and Kazuyuki Nagata. "Assembly sequence planning for motion planning." Assembly Automation 38, no. 2 (April 3, 2018): 195–206. http://dx.doi.org/10.1108/aa-01-2017-009.

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Purpose The purpose of this paper is to develop a planner for finding an optimal assembly sequence for robots to assemble objects. Each manipulated object in the optimal sequence is stable during assembly. They are easy to grasp and robust to motion uncertainty. Design/methodology/approach The input to the planner is the mesh models of the objects, the relative poses between the objects in the assembly and the final pose of the assembly. The output is an optimal assembly sequence, namely, in which order should one assemble the objects, from which directions should the objects be dropped and candidate grasps of each object. The proposed planner finds the optimal solution by automatically permuting, evaluating and searching the possible assembly sequences considering stability, graspability and assemblability qualities. Findings The proposed planner could plan an optimal sequence to guide robots to do assembly using translational motion. The sequence provides initial and goal configurations to motion planning algorithms and is ready to be used by robots. The usefulness of the proposed method is verified by both simulation and real-world executions. Originality/value The paper proposes an assembly planner which can find an optimal assembly sequence automatically without teaching of the assembly orders and directions by skilled human technicians. The planner is highly expected to improve teachingless robotic manufacturing.

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Proskurenko, D., O. Tretyak, M. Demchenko, and M. Filippova. "Filippova Automated planning of graduality assembly." Energy and automation, no. 5(57) (November 24, 2021): 28–44. http://dx.doi.org/10.31548/energiya2021.05.028.

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Modern industrial production requires the improvement of assembly processes, and thus increase the level of automated intelligent sequence planning. Therefore, researches in the field of automation of the sequence of assembly of products in industries are relevant at this time. In today's world there is a need to develop complex, accurate products. Problems are created in industries due to the reduction of the life cycle of products. There is a need to study the problem of assembly planning to achieve the goal of practical implementation and standardization of assembly plans. Creating graphs of the addition process is one of the problems. The assembly planning system can reduce human intervention in the process and reduce computational effort. The finished assembly contains many components that can be assembled using many sequences. A review of the methods from the literature showed that although these methods increase the automation level, they still cannot be applied to actual production because they do not take into account the experience and knowledge that can play a major role in planning and are of great value. Assembly planning, relationship charts, priority charts. Improving the assembly planning system to create a communication schedule and an assembly priority schedule was proposed. The advanced system will be used to generate possible assembly sequences with subassembly identification. A system has been developed to create alternative possible assembly sequences that can be used by component part / product designers in the early stages. A system capable of generating assembly sequences for simultaneous assembly of multiple parts has been proposed. Conclusions and work results can be applied used and improved for more productive product development by designers in the early stages and faster assembly of products in enterprises. The paper did not consider practical limitations (gravity) and irreversible assembly operations, such as permanent fastening, welding etc. Кey words: assembly, blocking graph, relation graph, sequence

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Li, Chunxi, and Wenjun Hou. "Assembly Sequence Planning Based on Hierarchical Model." Wireless Communications and Mobile Computing 2022 (February 9, 2022): 1–19. http://dx.doi.org/10.1155/2022/9461794.

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With the rapid development of intelligent manufacturing technology and ultraprecision machining, assembly technology has attracted more and more attention. Assembly sequence is an important part of assembly process planning. However, assembly sequence is affected by many complex factors, such as the time required to assemble products, the geometric feasibility of assembly sequence, and other factors (tool replacement times and assembly direction change), so it is very challenging. In this paper, an assembly information model based on geometric features of parts is proposed. The model obtains the hierarchical information of the part through the segmentation and feature reconstruction of the part. Based on the influence of the contact surface between parts on the feasible motion domain and assembly domain, the assembly constraint relationship model is established. The objective function is constructed by changing the assembly direction, changing the assembly tools, and evaluating the assembly fit type. The geometrically feasible assembly sequence is optimized to obtain the optimal assembly sequence under the existing conditions. Taking a block, a secondary reducer spindle, and a cylinder as examples, the effectiveness of the method is verified.

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Shuan-Jun Song, Shuan-Jun Song, Cheng-Hong Qiu Shuan-Jun Song, Long-Guang Peng Cheng-Hong Qiu, and Sheng Hu Long-Guang Peng. "An Assembly Line Multi-Station Assembly Sequence Planning Method Based on Particle Swarm Optimization Algorithm." 電腦學刊 33, no. 1 (February 2022): 115–25. http://dx.doi.org/10.53106/199115992022023301011.

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<p>Aiming at the problem that the existing assembly sequence planning methods are difficult to meet the multi-station assembly requirements of assembly line, an assembly sequence planning method of assembly line considering the constraints of station sequence and station capability is proposed. The multi-station assembly sequence model is established to describe the allocation scheme and assembly sequence of parts. The conditions and generating rules of feasible assembly sequence are given. The assembly time variance of each station is used as the fitness function, and the particle swarm optimization (PSO) algorithm is designed. Taking an engineering vehicle assembly as an example, the optimal integration solution of multi-station assembly sequence and job assignment is obtained by using this algorithm, and the validity of the model is verified.</p> <p> </p>

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Zhang, Yuan, Kai Fu Zhang, Jian Feng Yu, and Lei Zhao. "A Dynamic Assembly Modeling Method for Satellite Final Assembly Sequence Planning." Advanced Materials Research 156-157 (October 2010): 332–38. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.332.

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To study the effect of assembly process information combining disassemble and assemble on satellite assembly sequence, this paper presents an object-oriented and assembly information integrated model, which is composed of static model and dynamic model. The feasibility determination based on Cut-set theory is presented and the construction algorithm of dynamic model is established by static model, the dynamic assembly model tree is obtained by analyzing in layers and verifying possible states using this algorithm, where the assembly model tree includes all the geometric feasible assembly sequences of satellite. Finally, this modeling method is verified by a satellite product.

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Murayama, Takeshi, Bungo Takemura, and Fuminori Oba. "Assembly Sequence Planning Using Inductive Learning." Journal of Robotics and Mechatronics 11, no. 4 (August 20, 1999): 315–20. http://dx.doi.org/10.20965/jrm.1999.p0315.

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The authors propose acquiring heuristic rules automatically for generating assembly sequences efficiently. Heuristic rules are reduced from training examples by inductive learning. Additional training examples are made from information on assembly sequences and used for modifying heuristic rules. As the assembly sequence generation and modification of heuristic rules are executed more, heuristic rules are refined and assembly sequences are generated efficiently. An experiment demonstrated the effectiveness of the approach.

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Yokota, K., and D. R. Brough. "ASSEMBLY/DISASSEMBLY SEQUENCE PLANNING." Assembly Automation 12, no. 3 (March 1992): 31–38. http://dx.doi.org/10.1108/eb004372.

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8

Guo, Jifeng, Chengchao Bai, and Cheng Chen. "Sequence planning for human and robot cooperative assembly of large space truss structures." Aircraft Engineering and Aerospace Technology 89, no. 6 (October 2, 2017): 804–8. http://dx.doi.org/10.1108/aeat-06-2014-0093.

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Purpose In the future, large space truss structures will be likely to require on-orbit assembly. One of the several proposed methods includes cooperative assembly performed by pressure-suited astronauts during extravehicular activity (EVA) and space robots. An intelligent planning method was presented to generate optimal assembly tasks. Design/methodology/approach Firstly, the inherent hierarchical nature of truss structures allows assembly sequences to be considered from strut level and structural volume element (SVE) level. Then, a serial assembly strategy in human-robot environment was applied. Furthermore, a two-level planning algorithm was presented. At the first-level planning, one ant colony algorithm for assembly sequence planning was improved to adopt assembly direction and time as heuristic information and did not consider assembly tasks. And, at the second-level planning, another novel colony algorithm for assembly task planning mainly considered results of the first-level planning, human-robot interactive information, serial assembly strategy and assembly task distributions. Findings The proposed two-level planning algorithm is very effective for solving the human and robot cooperative assembly of large space truss structures. Research limitations/implications In this paper, the case study is based on the following assumptions: each tetrahedron is assembled by two astronauts; each pentahedron is assembled by three astronauts. Practical implications A case illustrates the results of the two-level planning. From this case study, because of geometrical symmetry nature of large space truss structures, the optimal assembly sequences are not only one. Originality/value The improved ant colony algorithm can deal with the assembly sequence and task planning in human-robot environment more effectively.

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Xing, Yan Feng, Yan Song Wang, and Xiao Yu Zhao. "A Particle Swarm Algorithm for Assembly Sequence Planning." Advanced Materials Research 97-101 (March 2010): 3243–46. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.3243.

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A particle swarm algorithm is proposed to generate optimal assembly sequences for compliant assemblies. Firstly, the liaison graph and the adjacency matrix describe the geometry of the compliant assemblies. An assembly sequence is represented by a character string, whose length is the number of all parts. The conceptual tolerance analysis is used to evaluate feasible sequences. Thereafter, the particle swarm algorithm is presented to generate assembly sequences, in which the elite ratio is applied to improve optimization results. Finally a fender assembly is used to illustrate the algorithm of assembly sequence generation and optimization.

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Zhang, Jing, Yun Sheng Yang, and Shao Wei Feng. "Method of Assembly Sequence Planning Based on Simulated Evolution Algorithm." Advanced Materials Research 490-495 (March 2012): 1171–75. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.1171.

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It is important for assemble industry to generate an optimized assembly sequences. In order to solve this problem, firstly an oriented mating graph model is proposed with the related mating matrix. Therefore an improved simulated evolution algorithm is proposed, which can compute an energy function of the assembly cost associated with the assembly sequence deduced by the graph model. The energy function can be optimized iteratively and perturbed occasionally by the simulated evolution until no further change in the energy occurs. Finally, the validity of the method is proved by a typical case.

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11

Sun, Bo, and Lu Liu. "Assembly Process Planning Method for Complex Electromechanical Products." Applied Mechanics and Materials 488-489 (January 2014): 1260–63. http://dx.doi.org/10.4028/www.scientific.net/amm.488-489.1260.

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Currently, neither the efficiency nor the effectiveness is sufficient in the area of the assemble optimization that commonly involves the genetic algorithm. A novel method to solve the cumbersome problem in the optimization of assembly sequences was proposed. On the basis of the assembly constraint matrix, the optimized assembly sequence is obtained with the proposed evaluating factors of the process requirement. That is the evolution of the original genetic algorithm to a certain extent. The effectiveness of the proposed method was proved by the comparison with the ant colony algorithm.

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12

ALFADHLANI, T. M. A. ARI SAMADHI, ANAS MA'RUF, and ISA SETIASYAH TOHA. "AUTOMATIC COLLISION DETECTION FOR ASSEMBLY SEQUENCE PLANNING USING A THREE-DIMENSIONAL SOLID MODEL." Journal of Advanced Manufacturing Systems 10, no. 02 (December 2011): 277–91. http://dx.doi.org/10.1142/s021968671100220x.

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Assembly sequence planning of a product involves several steps, including generation of precedence constraints, generation of assembly sequences, and selection of assembly sequences. Generation and selection of assembly sequences should be able to guarantee the feasibility of assembly. Assembly will be feasible if there is no collision between components when assembled. Detection of collision-free path of assembly can be done in an automated way. There are a number of collision detection methods that have been developed, but the method requires a complicated process of data geometry analysis. This paper proposes a method for detecting a collision-free path of the assembly component in a more simple way. Geometrical data required, taken from the three-dimensional (3D) solid drawing in the form of stacked drawing in computer-aided design (CAD) systems. Retrieval of geometrical data of components and detection of the collision-free path of an assembly were done in an automated way, directly from the CAD system.

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13

Liu, Peng, Linfeng Wu, Yanzhong Wang, and Lize Guo. "Optimization Method for Assembly Sequence Evaluation Based on Assembly Cost and Ontology of Aviation Reducers." Applied Sciences 14, no. 12 (June 12, 2024): 5116. http://dx.doi.org/10.3390/app14125116.

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An assembly sequence evaluation is one of the most important research directions of assembly sequence planning (ASP) for complex mechanical transmission products. Currently, aviation reducers lack a multi-perspective and multi-level evaluation of their assembly sequence. The existing evaluation indicators vary. The evaluation methods have low effectiveness and poor practicability. Therefore, a comprehensive multidimensional evaluation method for complex assembly sequences is proposed in this paper. A multidimensional comprehensive evaluation of the overall assembly quality and performance indices of aviation reducer products is realized. Firstly, the main factors affecting assembly sequence planning are considered: the attributes of the basic unit parts and the cost control of the assembly process. An evaluation index system of assembly sequence planning based on the two dimensions of assembly cost and ontology is constructed. Then, according to the multidimensional evaluation index, fuzzy evaluation theory is used to establish a fuzzy set and a matrix for each dimensional evaluation index. The index weight is divided. A comprehensive evaluation model and the function of each dimension are established. After a comprehensive evaluation, the multidimensional assembly sequence evaluation method for aviation reducers is formed. Finally, the method is applied to the assembly process of the primary reducer of a helicopter’s main reducer, and a comprehensive evaluation of its assembly sequence scheme is completed to verify the feasibility of the proposed method. This article constructs a complex assembly sequence evaluation method that includes 12 evaluation indicators, improves the assembly sequence planning evaluation index system of aviation reducers, and can effectively promote the progress of optimization technology for complex assembly sequences of aviation reducers.

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14

Sun, Zhan Lei, Peng Fei Han, and Gang Zhao. "Research on Aircraft Assembly Sequence Planning Technology Based on Key Characteristics." Applied Mechanics and Materials 328 (June 2013): 9–16. http://dx.doi.org/10.4028/www.scientific.net/amm.328.9.

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Assembly Sequence Planning (ASP) is an essential question for aircraft assembly process design. Modern aircraft assembly contains plenty of complex shape components, which have so many assembly features to ensure, this leads to a large number of feasible assembly sequences using traditional sequence planning algorithms; and it is hard to evaluate the contribution to assembly quality for every sequence. A methodology called Key Characteristics Based ASP is proposed in this paper, which can significantly reduce unavailable sequences and ensure key features for quality in assembly process designing compared with previous methods. The methodology focuses on the final assembly quality and considers it as Assembly Key Characteristics (AKCs) in the beginning of assembly process design. With tools such as AKCs decomposition, Datum Flow Chain, precedence constraint matrix, the methodology describes the main process for ASP. To verify the technologys effectiveness, this paper presents an application of the algorithm in an aircraft component assembly by an 863 program.

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Yi, Yang, Xiaojun Liu, Zhonghua Ni, Xia Tang, and Xiaokang Xu. "Research Method of Assembly Sequence Planning Based on Assembly Constraint Relationship Analysis." MATEC Web of Conferences 237 (2018): 03005. http://dx.doi.org/10.1051/matecconf/201823703005.

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In order to effectively reduce the human-computer interaction (HCI) workload before the assembly process simulation in the digital assembly environment, and to enhance the intelligence of assembly sequence planning, we introduce the assembly constraint relationship into the automatic generation of assembly sequences and propose a practical assembly sequence planning method for intelligent assembly. Firstly, starting from the assembly geometry model, an assembly model liaison graph is constructed by combining the analysis of assembly constraint relationship and the definition of disassembly direction rules. Then, according to the liaison graph, disassembly priority constraint matrix based on constraint relationship is constructed, and the automatic generation and dynamic update of the disassembly priority diagram can be realized by the definition of disassembly doubly linked list. According to the diagram, the rationality of the disassembly sequence is determined through the interference check analysis, and then the assembly sequence is automatically generated from the reversed disassembly sequence. Finally, the method in the text is verified by an example case study.

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16

Fujimoto, H., and M. F. Sebaaly. "A New Sequence Evolution Approach to Assembly Planning." Journal of Manufacturing Science and Engineering 122, no. 1 (January 1, 1999): 198–205. http://dx.doi.org/10.1115/1.538897.

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Assembly planning is the problem of finding the best or optimal sequence to assemble a product, starting from its design data. It is still solved manually in most advanced assembly plants, despite the large amount of related research. One of the main reasons might be the use of exact- and/or linear-solution approaches. This paper introduces a different approach by applying a modified genetic algorithm (GA). A “best” solution is generated without searching the complete candidate space, while search is performed on a sequence population basis. The GA is modified to cope with sequence nonlinearity and constraints. [S1087-1357(00)70401-1]

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Özmen, Özkan, Turgay Batbat, Tolgan Özen, Cem Sinanoğlu, and Ayşegül Güven. "Optimum Assembly Sequence Planning System Using Discrete Artificial Bee Colony Algorithm." Mathematical Problems in Engineering 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/3407646.

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Assembly refers both to the process of combining parts to create a structure and to the product resulting therefrom. The complexity of this process increases with the number of pieces in the assembly. This paper presents the assembly planning system design (APSD) program, a computer program developed based on a matrix-based approach and the discrete artificial bee colony (DABC) algorithm, which determines the optimum assembly sequence among numerous feasible assembly sequences (FAS). Specifically, the assembly sequences of three-dimensional (3D) parts prepared in the computer-aided design (CAD) software AutoCAD are first coded using the matrix-based methodology and the resulting FAS are assessed and the optimum assembly sequence is selected according to the assembly time optimisation criterion using DABC. The results of comparison of the performance of the proposed method with other methods proposed in the literature verify its superiority in finding the sequence with the lowest overall time. Further, examination of the results of application of APSD to assemblies consisting of parts in different numbers and shapes shows that it can select the optimum sequence from among hundreds of FAS.

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Murali, G. Bala, BBVL Deepak, MVA Raju, and BB Biswal. "Optimal robotic assembly sequence planning using stability graph through stable assembly subset identification." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 15 (April 18, 2019): 5410–30. http://dx.doi.org/10.1177/0954406219842908.

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Assembly sequence planning is one of the multi-model optimization problems, in which more than one objective function has to be optimized at a time to obtain the quality assembly sequence. Moreover obtaining the feasible sequences from the possible finite set of sequences is a difficult task as the assembly sequence planning problem is N-P hard combinatorial problem. To solve the assembly sequence planning problem, researchers have developed various techniques to obtain the optimum solution. The developed methodologies have many drawbacks like struck at local optima, poor performance, huge search space and many more. To overcome these difficulties, the current research work aims to use stability graph to generate stable assembly subsets for obtaining the optimum assembly sequences. In the proposed methodology, to reduce the search space and to obtain the quality assembly sequences, stability graph is considered. Moreover, the fitness of assembly subsets is evaluated according to the user weights at each level before proceeding to the higher levels. Due to this, the higher fitness value subsets are eliminated at each stage by which time of execution will reduce enormously. The proposed methodology has implemented on various industrial products and compared the results with the various well-known algorithms.

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Parzeller, Rafael, Dominik Koziol, Tizian Dagner, and Detlef Gerhard. "Automating the assembly planning process to enable design for assembly using reinforcement learning." Proceedings of the Design Society 4 (May 2024): 2179–86. http://dx.doi.org/10.1017/pds.2024.220.

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AbstractThis paper introduces a new concept for the automation of the assembly planning process, to enable Design for Assembly (DfA). The approach involves the application of reinforcement learning (RL) to assembly sequence planning (ASP) based on a 3D-CAD model. The ASP algorithm determines assembly sequences through assembly by disassembly. The assembly sequence is then used for the generation of subassemblies by considering the product contact information. The approach aims to support the creation of the manufacturing bill of materials (MBOM) by automating the assembly planning process.

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Murayama, Takeshi, Yuichi Mine, Hiroshi Fujinaka, and Toru Eguchi. "Assembly Sequence Planning by Probabilistic Tree Transformation." EMITTER International Journal of Engineering Technology 6, no. 2 (December 29, 2018): 354–68. http://dx.doi.org/10.24003/emitter.v6i2.308.

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Various types of computer systems including CAD/CAM systems have been introduced in machine industry. Some of the systems can handle assembly sequence planning, however it requires long time for planning. This paper proposes a method of generating assembly sequences efficiently. This method extracts some parts and/or subassemblies whose possibilities of being removed from a product are strong, and tests whether they can be removed without any geometric interference. By performing these operations repeatedly, the method generates a disassembly sequence of the product, and obtains an assembly sequence by reversing it. The extraction of some parts and/or subassemblies is performed, based on probabilistic tree transformation. The authors present a calculation example by using a software tool integrated with a CAD system.

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Zhang, Jing, Yun Sheng Yang, and Shao Wei Feng. "An Approach to Assembly Sequence Planning Using Simulated Annealing." Advanced Materials Research 457-458 (January 2012): 628–34. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.628.

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In order to solve the problem of generating and optimizing the assembly sequences of a complex assembly, the oriented-mating graph model of the assembly and the related mating matrix are created. Then an improved simulated annealing algorithm is used to solve the ASP problem. This algorithm reflects the assembly cost to an energy function associated with the assembly sequence. The energy function is iteratively minimized and occasionally perturbed by a simulated annealing until no further change in the energy occurs. Finally, a living example is given to prove the validity of the method.

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Li, Jun-Ying, and Cong Lu. "Assembly Sequence Planning with Fireworks Algorithm." International Journal of Modeling and Optimization 6, no. 3 (June 2016): 195–98. http://dx.doi.org/10.7763/ijmo.2016.v6.526.

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23

GU, P., and X. YAN. "CAD-directed automatic assembly sequence planning." International Journal of Production Research 33, no. 11 (November 1995): 3069–100. http://dx.doi.org/10.1080/00207549508904862.

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Zha, X. F., Samuel Y. E. Lim, and S. C. Fok. "Integrated knowledge-based assembly sequence planning." International Journal of Advanced Manufacturing Technology 14, no. 1 (January 1998): 50–64. http://dx.doi.org/10.1007/bf01179417.

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Wang, Yong, and Jihong Liu. "Subassembly identification for assembly sequence planning." International Journal of Advanced Manufacturing Technology 68, no. 1-4 (February 21, 2013): 781–93. http://dx.doi.org/10.1007/s00170-013-4799-y.

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J. Fendi Al-Saadi, Saleh. "An Automated Assembly Sequence Planning System." Engineering and Technology Journal 27, no. 14 (October 1, 2009): 2584–94. http://dx.doi.org/10.30684/etj.27.14.5.

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Wang, Yong, and De Tian. "A weighted assembly precedence graph for assembly sequence planning." International Journal of Advanced Manufacturing Technology 83, no. 1-4 (July 19, 2015): 99–115. http://dx.doi.org/10.1007/s00170-015-7565-5.

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Ben Hadj, Riadh, Moez Trigui, and Nizar Aifaoui. "Toward an integrated CAD assembly sequence planning solution." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 229, no. 16 (December 11, 2014): 2987–3001. http://dx.doi.org/10.1177/0954406214564412.

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Assembly sequence planning has drawn the attention of many researchers over the last years. Despite, the great development of CAD software in many aspects (simulation algorithms, interfaces, and ergonomics), automatic generation of assembly sequence planning from CAD assembly remains an issue to improve especially with the increasing complexity of industrial products. In this paper, an approach of assembly sequence planning generation from a CAD assembly model is presented. In order to generate feasible assembly sequence planning, the developed approach begins with the exploration of CAD assembly. Then, a collision analysis is performed to identify all possible obstacles during the components’ motion. An example of CAD assembly is presented in all sections of this paper in order to demonstrate the efficiency of the proposed approach.

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Su, Ying Ying, Hai Dong, and Di Liang. "Assembly Sequence Planning Based on Connector Structure and Ant Colony Algorithm." Advanced Materials Research 712-715 (June 2013): 2482–86. http://dx.doi.org/10.4028/www.scientific.net/amr.712-715.2482.

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For the purpose of effectively reducing the degree of complexity and improving the efficiency, the method of assembly sequence planning based on connector structure and ant algorithm was proposed. The concept of connector structure was presented, which was regarded as basic assembly unit to cover features of assembly parts. Then, a model of assembly sequence planning was built, which represented the precedence constraint relationship among connector structures. Additionally, the combination of the connector structure concept and characteristics of ant colony algorithm was developed for generating optimal assembly sequences under the guidance of precedence relations in the model. Finally, an example was studied to illustrate the effectiveness of the strategy.

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Enomoto, Atsuko, Noriaki Yamamoto, Yoshio Yamamura, and Yoshio Sugawara. "Process Knowledge Integrated Assembly Sequence Planning for Control Panel." International Journal of Automation Technology 14, no. 1 (January 5, 2020): 6–17. http://dx.doi.org/10.20965/ijat.2020.p0006.

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Completely automated assembly sequence planning for control panels is proposed. The proposed algorithm generates the manufacturing bill of material for the assembly processes and total assembly sequence. The algorithm integrates the knowledge of assembly process into a near optimum assembly sequence generation.

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Li, Feng Ying, Tian Long Gu, and Liang Chang. "A Symbolic OBDD-Based Algorithm for Assembly Sequence Planning." Advanced Materials Research 97-101 (March 2010): 2444–48. http://dx.doi.org/10.4028/www.scientific.net/amr.97-101.2444.

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Algorithms based on timed Petri net are competitive for solving the problem of assembly sequence planning (ASP). In order to alleviate the state-space explosion problem which is caused by the Petri net-based representation of assembly sequences and to improve the efficiency of planning algorithms, an approach based on ordinary binary decision diagrams (OBDDs) is presented in this paper. On the one hand, all the timed transitions in Petri nets are substituted by some technically designed timed transition structures; on the other hand, Petri nets used in algorithms of assembly sequence planning are represented symbolically as OBDDs. As a result, a novel assembly sequence planning algorithm based on symbolic OBDDs is presented. With the help of OBDDs, both the marking vectors and the states of Petri nets are formulated more compactly; at the same time, the searching processes can be manipulated implicitly. Therefore, compared with original algorithms, both the time performance and the space performance are improved.

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ZHA, X. F. "Neuro-fuzzy comprehensive assemblability and assembly sequence evaluation." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, no. 5 (November 2001): 367–84. http://dx.doi.org/10.1017/s0890060401155010.

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Analysis of assembly properties of a product is needed during the initial design stage in order to identify potential assembly problems, which affect product performance in the later stages of life cycle. Assemblability analysis and evaluation play a key role in assembly design, assembly operation analysis and assembly planning. This paper develops a novel approach to assemblability and assembly sequence analysis and evaluation using the concept of the fuzzy set theory and neuro-fuzzy integration. Assemblability is described by assembly-operation difficulty, which can be represented by a fuzzy number between 0 and 1. Assemblability evaluation is therefore fuzzy evaluation of assembly difficulty. The evaluation structure covers not only the assembly parts' geometric and physical characteristics, but also takes into account the assembly operation data necessary to assemble the parts. The weight of each assemblability factor is subject to change to match the real assembly environments based on expert advice. The approach has the flexibility to be used in various assembly methods and different environments. It can be used in a knowledge-based design for assembly expert system with learning ability. Through integration with the CAD system, the developed system can effectively incorporate the concurrent engineering knowledge into the preliminary design process so as to provide users with suggestions for improving a design and also helping to obtain better design ideas. The applications in assembly design and planning show that the proposed approach and system are feasible.

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Su, Ying Ying, Di Liang, and Hai Dong. "Connector Structure-Based Modeling of Assembly Sequence Planning." Applied Mechanics and Materials 496-500 (January 2014): 2729–32. http://dx.doi.org/10.4028/www.scientific.net/amm.496-500.2729.

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Assembly Sequence planning is one of the important stages during the product manufacturing process. For the purpose of effectively reducing the degree of complexity and improving the efficiency, the modeling method of assembly sequence planning based on connector structures is proposed. The concept of connector structure is presented, which is regarded as basic assembly units to cover features of assembly parts and package functional parts and connectors. The model of assembly sequence planning is built, which represents the precedence constraint relationship among connector structures. Finally, an example is studied and the model of assembly sequence planning based on connector structure is built to illustrate the effectiveness of the modeling method.

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Xiang, Hong Wei, Chang Zheng Chen, and Gao Xiang Chen. "Review of Sequence Planning of Virtual Assembly." Applied Mechanics and Materials 404 (September 2013): 748–53. http://dx.doi.org/10.4028/www.scientific.net/amm.404.748.

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Assembly sequence planning is one of the key technologies for virtual assembly. It mainly consists of three parts, i.e. assembly modeling, planning algorithm and evaluation of sequence planning. This paper presents an overview about the research status quo and methods of the above three parts, analyzes both the advantages and disadvantages of those research methods and their application scope and proposes the trends of their development.

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Tseng, Yuan-Jye, Jian-Yu Chen, and Feng-Yi Huang. "A multi-plant assembly sequence planning model with integrated assembly sequence planning and plant assignment using GA." International Journal of Advanced Manufacturing Technology 48, no. 1-4 (August 30, 2009): 333–45. http://dx.doi.org/10.1007/s00170-009-2264-8.

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Fu, Y. L., R. Li, H. B. Feng, and Y. L. Ma. "Petri Net Models for Assembly Sequences Planning." Applied Mechanics and Materials 10-12 (December 2007): 411–15. http://dx.doi.org/10.4028/www.scientific.net/amm.10-12.411.

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Assembly sequences can be represented by a Petri net(PN) which characterizes dynamic system changes and provides a tool for obtaining optimal assembly sequences. In this study some assembly operation constraints are considered in order to obtain more practical sequences which are conformed to real situations. In order to enhancing the efficiency of the assembly sequence planning, knowledge-based Petri net, combining an usual Petri net with expert’s knowledge and experiences, is proposed to construct the assembly model. With the complexity of the product, the product’s assembly model size will be too large to analysis. So the basic subnets are used to reduce the large PN. And the reduced version can be used for the analysis of the original PN. To verify the validity and efficiency of the approach, a variety of assemblies including some complicated products from industry are tested, and the corresponding results are also presented.

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Zomkowski Salvi, Anelize, and Henrique Simas. "Assembly Sequence Planning for Rectangular Modular Robots with Accessibility Constraints." Journal of Robotics 2023 (November 25, 2023): 1–20. http://dx.doi.org/10.1155/2023/3264369.

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Product assembly is the final step in a manufacturing process where the individual components of a product are joined together. Assembly sequence planning (ASP) can be defined as the problem of finding a collision-free sequence of operations that allow the product assembly. Considering that during assembly individual modules cannot pass through a gap only as large as a module side, the ASP problem can be extended to modular robots, more specifically to rectangular modular robots. The main ASPs presented in the literature that are applicable to rectangular modules do not allow configurations with narrow corridors, i.e., corridors which are too narrow for a robot to transverse. Furthermore, these ASPs do not allow preassembled substructures or the free selection of the assembly starting point. Thus, the main goal of this work is to extend the classes of rectangular modular robot configurations that can be assembled without violating the accessibility condition. This paper introduces three novel ASP for constructing planar target structures composed of rectangular modular robots. Each ASP is adequate for a different scenario. Original implementation results and mathematical proofs for the three novel ASPs are also presented. To the best of the authors’ knowledge, this is the first work that presents, considering the accessibility condition, how to obtain centralized ASPs for assembling planar structures composed of rectangular modules with narrow corridors. Furthermore, the novel ASPs allow structures composed of subsets of preassembled modules and configurations with internal holes. They also allow the choice of the assembly starting point. Moreover, the third ASP proposed in this work allows achieving discontinuous assembly paths, i.e., wherever possible, the ASP allows a novel module to not connect to the latest added robot.

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Yang, Zhuo, Cong Lu, and Hong Wang Zhao. "An Ant Colony Algorithm for Integrating Assembly Sequence Planning and Assembly Line Balancing." Applied Mechanics and Materials 397-400 (September 2013): 2570–73. http://dx.doi.org/10.4028/www.scientific.net/amm.397-400.2570.

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Assembly sequence planning (ASP) and assembly line balancing (ALB) problems are two essential problems in the assembly optimization. This paper proposes an ant colony algorithm for integrating assembly sequence planning and assembly line balancing, to deal with the two problems on parallel, and resolve the possible conflict between two optimization goals. The assembly sequence planning problem and the assembly line balancing problem are discussed, the process of the proposed ant colony algorithm is investigated. The results can provide a set of solutions for decision department in assembly planning.

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Schirmer, Fabian, Philipp Kranz, Chad G. Rose, Jan Schmitt, and Tobias Kaupp. "Towards Dynamic Human–Robot Collaboration: A Holistic Framework for Assembly Planning." Electronics 14, no. 1 (January 5, 2025): 190. https://doi.org/10.3390/electronics14010190.

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The combination of human cognitive skills and dexterity with the endurance and repeatability of robots is a promising approach to modern assembly. However, efficiently allocating tasks and planning an assembly sequence between humans and robots is a manual, complex, and time-consuming activity. This work presents a framework named “Extract–Enrich–Assess–Plan–Review” that facilitates holistic planning of human–robot assembly processes. The framework automatically Extracts data from heterogeneous sources, Assesses the suitability of each assembly step to be performed by the human or robot, and Plans multiple assembly sequence plans (ASP) according to boundary conditions. Those sequences allow for a dynamic adaptation at runtime and incorporate different human–robot interaction modalities that are Synchronized, Cooperative, or Collaborative. An expert remains in the loop to Enrich the extracted data, and Review the results of the Assess and Plan steps with options to modify the process. To experimentally validate this framework, we compare the achieved degree of automation using three different CAD formats. We also demonstrate and analyze multiple assembly sequence plans that are generated by our system according to process time and the interaction modalities used.

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Wang, Wen-Pai, and Hwai-En Tseng. "COMPLEXITY ESTIMATION FOR GENETIC ASSEMBLY SEQUENCE PLANNING." Journal of the Chinese Institute of Industrial Engineers 26, no. 1 (January 2009): 44–52. http://dx.doi.org/10.1080/10170660909509120.

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Wu, Meiping, Vittal Prabhu, and Xiaoyu Li. "Knowledge-Based Approach to Assembly Sequence Planning." Journal of Algorithms & Computational Technology 5, no. 1 (March 2011): 57–70. http://dx.doi.org/10.1260/1748-3018.5.1.57.

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Ma, Hongqin, Qingjin Peng, Jian Zhang, and Peihua Gu. "Assembly sequence planning for open-architecture products." International Journal of Advanced Manufacturing Technology 94, no. 5-8 (March 9, 2017): 1551–64. http://dx.doi.org/10.1007/s00170-017-0160-1.

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Seow, Kiam Tian, and R. Devanathan. "Temporal logic programming for assembly sequence planning." Artificial Intelligence in Engineering 8, no. 4 (January 1993): 253–63. http://dx.doi.org/10.1016/0954-1810(93)90008-4.

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Zhou, Wei, Jianjun Yan, Yong Li, Chunming Xia, and Jianrong Zheng. "Imperialist competitive algorithm for assembly sequence planning." International Journal of Advanced Manufacturing Technology 67, no. 9-12 (November 24, 2012): 2207–16. http://dx.doi.org/10.1007/s00170-012-4641-y.

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Dong, Tianyang, Ruofeng Tong, Ling Zhang, and Jinxiang Dong. "A collaborative approach to assembly sequence planning." Advanced Engineering Informatics 19, no. 2 (April 2005): 155–68. http://dx.doi.org/10.1016/j.aei.2005.05.008.

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Li, R., H. Chen, and L. Xie. "Assembly Sequence Planning Including Tool Check Based on Improved Ant-Colony Algorithm." Advanced Materials Research 670 (March 2013): 3–9. http://dx.doi.org/10.4028/www.scientific.net/amr.670.3.

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According to the characteristics and demands of assembly sequence planning (ASP) of complicated electromechanical products, the improved Ant-Colony algorithm is presented to solve the problem. In order to plan assembly sequence, Precedence Graph, which is created based on assembly model, is created to record precedence relations between components. Several mechanisms are designed to make the precedence relations correct and compendious. To examine the feasibility of the sequences for tool’s operation, a quick checking method is proposed based on Potential Interference Information, which is created by simulating the tool’s movement and checking the interference information in entire assembly. Then, the Ant Colony Algorithm is improved to generate optimal assembly sequences with the guidance of precedence relations. Two important influence factors have been taken into account in the method. (1) A Penalty-Evaporation mechanism is proposed for the algorithm to punish unfeasible solutions. (2) Via analyzing the effects of the parameters in the state transfer function, the better solution is obtained while change the fixed parameters to transforming with time. Finally, an example illustrates the effectiveness of the strategy.

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Deepak, BBVL, G. Bala Murali, MVA Raju Bahubalendruni, and BB Biswal. "Assembly sequence planning using soft computing methods: A review." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 233, no. 3 (March 29, 2018): 653–83. http://dx.doi.org/10.1177/0954408918764459.

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The implementation of artificial intelligence techniques is increasing rapidly in recent years to solve numerous engineering problems. Assembly sequence planning is one of the prominent complex combinatorial problem draw attention of industrial engineers to economize the overall manufacturing cost by minimizing the assembly time and energy. Due to large search space and multiple assembly predicate criteria, researchers are motivated towards efficient utilization of AI techniques to address the problem. Literature review on various artificial intelligence techniques for obtaining the optimal assembly sequence planning are analyzed and the limitations of the existed methodologies are discussed in detail. This review provides an outlook for the researchers on various artificial intell1igent techniques which will be useful to carry out research for obtaining the optimum assembly sequence planning while qualifying various assembly predicate criteria.

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Suszyński, Marcin, Katarzyna Peta, Vít Černohlávek, and Martin Svoboda. "Mechanical Assembly Sequence Determination Using Artificial Neural Networks Based on Selected DFA Rating Factors." Symmetry 14, no. 5 (May 16, 2022): 1013. http://dx.doi.org/10.3390/sym14051013.

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In this paper, an assembly sequence planning system, based on artificial neural networks, is developed. The problem of artificial neural network itself is largely related to symmetry at every stage of its creation. A new modeling scheme, known as artificial neural networks, takes into account selected DFA (Design for Assembly) rating factors, which allow the evaluation of assembly sequences, what are the input data to the network learning and then estimate the assembly time. The input to the assembly neural network procedure is the sequences for assembling the parts, extended by the assembly’s connection graph that represents the parts and relations between these parts. The operation of a neural network is to predict the assembly time based on the training dataset and indicate it as an output value. The network inputs are data based on selected DFA factors influencing the assembly time. The proposed neural network model outperforms the available assembly sequence planning model in predicting the optimum assembly time for the mechanical parts. In the neural networks, the BFGS (the Broyden–Fletcher–Goldfarb–Shanno algorithm), steepest descent and gradient scaling algorithms are used. The network efficiency was checked from a set of 20,000 test networks with randomly selected parameters: activation functions (linear, logistic, tanh, exponential and sine), the number of hidden neurons, percentage set of training and test dataset. The novelty of the article is therefore the use of parts of the DFA methodology and the neural network to estimate assembly time, under specific production conditions. This approach allows, according to the authors, to estimate which mechanical assembly sequence is the most advantageous, because the simulation results suggest that the neural predictor can be used as a predictor for an assembly sequence planning system.

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Su, Qiang. "A hierarchical approach on assembly sequence planning and optimal sequences analyzing." Robotics and Computer-Integrated Manufacturing 25, no. 1 (February 2009): 224–34. http://dx.doi.org/10.1016/j.rcim.2007.11.006.

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Zhang, Zaifang, Baoxun Yuan, and Zhinan Zhang. "A new discrete double-population firefly algorithm for assembly sequence planning." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 230, no. 12 (August 6, 2016): 2229–38. http://dx.doi.org/10.1177/0954405416629099.

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Assembly sequence planning is a critical step of assembly planning in product digital manufacturing. It is a combinational optimization problem with strong constraints. Many studies devoted to propose intelligent algorithms for efficiently finding a good assembly sequence to reduce the manufacturing time and cost. Considering the unfavorable effects of penalty function in the traditional algorithms, a new discrete firefly algorithm is proposed based on a double-population search mechanism for the assembly sequence planning problem. The mechanism can guarantee the population diversity and enhance the local and global search capabilities by using the parallel evolution of feasible and infeasible solutions. All parts composed of the assembly are assigned as the firefly positions, and the corresponding movement direction and distance of each firefly are defined using vector operations. Three common objectives, including assembly stability, assembly polymerization and change number of assembly direction, are taken into account in the fitness function. The proposed approach is successfully applied in a real-world assembly sequence planning case. The sizes of feasible and infeasible populations are adequately discussed and compared, of which the optimal size combination is used for initializing the firefly algorithm. The application results validate the feasibility and effectiveness of the discrete double-population firefly algorithm for solving assembly sequence planning problem.

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