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Marehalli, Jayavardhan N. "Assembly Sequence Optimization and Assembly Path Planning". Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/44837.
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This thesis addresses two important aspects of automatic assembly viz., assembly sequence planning and assembly path planning. These issues are addressed separately starting with sequence planning followed by assembly path planning.
For efficient assembly without feedback systems (or, passive assembly), an assembler should know the ideal orientation of each component and the order in which to put the parts together (or, assembly sequence). A heuristic is presented to find the optimal assembly sequence and prescribe the orientation of the components for a minimum set of grippers = ideally one. The heuristic utilizes an index of difficulty (ID) that quantifies assembly. The ID for each task in the assembly process is computed on the basis of a number of geometrical and operational properties. The objective of the optimization problem here is to minimize the assembly ID and categorize parts/subassemblies based on their preferred direction of assembly while allowing re-orientation of the base part. It is assumed that the preferred direction of assembly is vertically downward, consistent with manual as well as most automatic assembly protocols. Our attempt is to minimize the number of degrees of freedom required in a re-orienting fixture and derive the requirements for such a fixture. The assembly of a small engine is used as an example in this study due to the variety of ideally rigid parts involved.
In high precision assembly tasks, contact motion is common and often desirable. This entails a careful study of contact states of the parts being assembled. Recognition of contact states is crucial in planning and executing contact motion plans due to inevitable uncertainties. Dr. Jing Xiao of UNCC introduced the concept of principal contacts (PC) and contact formation (CF) for contact state recognition. The concept of using CFs (as sets of PCs) has the inherent advantage that a change of CF is often coincident with a discontinuity of the general contact force (force and torque). Previous work in contact motion planning has shown that contact information at the level of PCs along with the sensed location and force information is often sufficient for planning high precision assembly operations. In this thesis, we present results from experiments involving planned contact motions to validate the notion of PCs and CFs -- an abrupt change in general contact force often accompanies a change between CFs. We are only concerned with solving the 2D peg-in-corner problem.Master of Science
2
Gu, Yunqing. "Graphical integration of robot programming and sequence planning for mechanical assembly". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0019/MQ54893.pdf.
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Ab, Rashid Mohd Fadzil Faisae. "Integrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation". Thesis, Cranfield University, 2013. http://dspace.lib.cranfield.ac.uk/handle/1826/8257.
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In assembly optimisation, Assembly Sequence Planning (ASP) and Assembly Line Balancing (ALB) optimisations currently performed in serial, present an opportunity for integration, allowing benefits such as larger search space leading to better solution quality, reduced error rate in planning and fast time-to-market for a product. The literature survey highlights the research gaps, where the existing integrated ASP and ALB optimisation is limited to a Genetic Algorithm (GA) based approach, while Particle Swarm Optimisation (PSO) demonstrates better performance in individual ASP and ALB optimisation compared to GA. In addition, the existing works are limited to simple assembly line problems which run a homogeneous model on an assembly line. The aim of this research is to establish a methodology and algorithm for integrating ASP and ALB optimisation using Particle Swarm Optimisation. This research extends the problem type to integrated mixed-model ASP and ALB in order to generalise the problem. This research proposes Multi-Objective Discrete Particle Swarm Optimisation (MODPSO), to optimise integrated ASP and ALB. The MODPSO uses the Pareto-based approach to deal with the multi-objective problem and adopts a discrete procedure instead of standard mathematical operators to update its position and velocity. The MODPSO algorithm is tested with a wide range of problem difficulties for integrated single-model and mixed-model ASP and ALB problems. In order to supply sufficient test problems that cover a range of problem difficulties, a tuneable test problem generator is developed. Statistical tests on the algorithms’ performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger non-dominated solution numbers in Pareto optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixed-model ASP and ALB problems. The performance of the MODPSO algorithm is finally validated using artificial problems from the literature and real-world problems from assembly products.
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Nguyen, Dang Tan. "Entwicklung eines effizienten Montageplanungssystems auf Basis von Funktionsfolgen". Universitätsverlag Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A33551.
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Die gängige Methodik zum Konzipieren automatisierter Montagesysteme umfasst die Planung der Montage und die physische Entwicklung der technischen Gesamtlösung. Zur Abbildung der konkreten Aufgabe werden standardisierte Symbole in einem Ablaufplan miteinander verknüpft. Die Hauptaufgabe des Konstrukteurs ist die Auswahl und die Zusammenstellung einer optimalen Konfiguration der Funktionsträger sowie deren Implementierung in einer Gesamtlösung unter Berücksichtigung der vorgegebenen Randbedingungen. Das Problem ist der fehlende Informationsgehalt der bisher eingesetzten Handhabungssymbole und Symbole zur Ermittlung der Funktionsträger zur Beschreibung der Montage- und Handhabungsplanung sowie die fehlende Vorgehensweise zur Auswahl der Funktionsträger aus den verschiedenen Varianten nach minimaler Taktzeit und Gesamtanschaffungskosten.
Zur Realisierung eines effizienten Montageplanungssystems leitet sich daher die Zielstellung ab, den Informationsgehalt der standardisierten Symbole zu erweitern und mit logischen Schnittstellen für eine automatisierte Verknüpfung in der Funktionsfolge auszustatten. Diese neuen Symbole beinhalten die Definition der Funktionen sowie alle Randbedingungen und Parameter zur eindeutigen Beschreibung der Handhabungsaufgabe. Mithilfe dieser Parameter werden Anforderungslisten erstellt und nach passenden Anlagenkomponenten gesucht. Zur Auswahl der optimalen Komponenten des Montagesystems wird das lineare Optimierungsproblem hinsichtlich der Kombination aus Taktzeit und Gesamtanschaffungskosten gelöst.The common methodology for designing automated assembly systems involves the assembly planning and the physical development of overall technical solution. To illustrate the concrete task, standardized symbols are connected together in a flowchart. The designer's main task is the selection and the composition of an optimal configuration of the functional carriers as well as their implementation in an overall solution in consideration of the predetermined boundary conditions. One problem is the lack of information content of the previously used handling symbols and the symbols for determining the functional carriers, which describe the assembly and handling planning. The other is the insufficient methods for selecting the functional carriers from the different variants based on minimum cycle time and total acquisition cost. In order to realize an efficient assembly planning system, the objective is therefore to expand the information content of the standardized symbols and equip them with logical interfaces for automated connection in the functional sequence. These new symbols contain the definition of the functions as well as all boundary conditions and parameters for the unambiguous description of the handling task. These parameters are utilised to create requirement lists and search for suitable plant components. In order to select the optimal components of the assembly system, the linear optimization problem regarding the combination of cycle time and total acquisition costs is solved.
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Elhoud, Anass. "Artificial intelligence-based approach for acceleration & optimization of hybrid production line preliminary design in the automotive industry". Electronic Thesis or Diss., Bourgogne Franche-Comté, 2024. http://indexation.univ-fcomte.fr/nuxeo/site/esupversions/d3a97160-65a3-48c3-b8c5-c431847fc587.
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Dans l’industrie automobile compétitive, l’optimisation des lignes de production est essentielle pour améliorer l’efficacité et la rentabilité. Cette thèse propose une solution complète développée en collaboration avec un acteur majeur du secteur automobile, s’attaquant à trois défis principaux : la planification des séquences d’assemblage, l’équilibrage des ressources et l’évaluation dynamique des performances. La première solution optimise les séquences d’assemblage pour minimiser l’utilisation des ressources et les coûts de production en utilisant l’apprentissage par renforcement et le regroupement hiérarchique. La deuxième solution traite de l’équilibrage des lignes d’assemblage en utilisant des algorithmes métaheuristiques pour réduire le temps de cycle sans augmenter les ressources. La troisième solution améliore les performances dynamiques des lignes de production en cas d’événements stochastiques, tels que les pannes et les retards, grâce à la gestion des stocks et aux stratégies de contrôle optimal. Chaque solution a été validée dans des environnements industriels réels, démontrant des améliorations significatives en termes d’efficacité et de performance des lignes de productionIn the competitive automotive industry, optimizing production lines is crucial for enhancing efficiency and profitability. This thesis presents a comprehensive solution developed in collaboration with a leading automotive company, tackling three key challenges: assembly sequence planning, resource balancing, and dynamic performance evaluation. The first solution optimizes assembly sequences to minimize resource usage and production costs using reinforcement learning and hierarchical clustering. The second solution addresses assembly line balancing, employing metaheuristic algorithms to reduce cycle time without increasing resources. The third solution improves dynamic production line performance under stochastic events, such as breakdowns and delays, through inventory management and optimal control strategies. Each solution was validated in real industrial environments, demonstrating substantial improvements in production line efficiency and performance
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Wu, Song-Dar, e 吳松達. "Subassembly Extraction in Assembly Sequence Planning". Thesis, 1993. http://ndltd.ncl.edu.tw/handle/22814477819154410863.
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碩士大葉大學
事業經營研究所
81
Subassembly approach has been applied by today''s industry to reduce the complexity of assembly sequencing for complex assemblies. By analyzing assembly mating conditions, a connection-contact graph is constructed to identify the key components for subassembly extraction. After removing the connection between key components, independent and stable subassemblies can be obtained. In c addition, assembly time is applied to evaluate different subassembly combinations for the selection of better subassembly extraction. Matrix representation and algorithm areproposed for computerization. Finally, an example is presented for the study.
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Chiang, Yu-Cheng, e 蔣佑政. "Considering Bevel Assembly in Intelligent Robot of Assembly Sequence Planning". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/qet475.
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碩士國立臺北科技大學
工業工程與管理系
106
Nowadays, Industry 4.0 is the trend of global automation technology. It derives a new type of manufacturing. In Industry 4.0, the Cyber-Physical System (CPS) is an important core, which makes the manufacturing process more intelligent. Because the assembly operation has a considerable influence on the manufacturing cost and time, intelligent assembly becomes one of the important keys in CPS intelligent manufacturing. In order to implement intelligent assembly, the cooperation between assembly robot and Assembly Sequence Planning (ASP) must be considered, but the manual coding the robot program is time consuming and requires specialization knowledge and experience. In the past research on intelligent assembly, interference checking often does not consider the components own Local Coordinate System (LCS). If the component has an inclined interference and only use the global coordinate system (GCS) to generate the ASP, it will generate wrong ASP. Because the GCS moves in the direction of the orthogonal axis, it is not possible to check the interference relationship in the direction of the non-orthogonal axis. This study proposes a Local Coordinate Cyber-Physical Intelligent Assembly System (LCCPIAS). The user only needs to input the CAD image file and generate the assembly sequence through the proposed method. The robot assembly can be modularized and the robot grammar can be automatically generated to achieve intelligent assembly. The method proposed in this study not only solves the problems that cannot be solved by the previous literature, but also leads to a more suitable assembly sequence for the robot than the previous method, and at the same time can solve the problems of assembly and automation of the inclined assembly. The method proposed in this study is great help to achieve intelligent assembly.
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LYU, Shao-Ren, e 呂紹任. "Intelligent KBE system for assembly sequence planning". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/28379050088160941570.
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碩士中華大學
機械工程學系碩士班
97
The purposed research is to build an intelligent KBE system for assembly sequence planning (ASP) .The knowledge-driven concept of product design is a novel trend of current computer aided design (CAD) system, knowledge-based engineering (KBE) can be an integrated processing technology, which merges the original engineering design experiences, design achievements and domain know-how, fulfills the connections with CAX (CAD/CAM/CAE/CAPP/CAI) system via the knowledge reuse, and further reduces the workloads of product development and promptly boosts the design efficiencies. Therefore, the purposed research joins back-propagation neural network (BPNN) algorithm and UG NX/KF second development module to create feasible assembly sequences. System user can easily access the volume, weight and feature number through NX system, and input the related parameters such as contact relationship number and total penalty value, and predict the feasible assembly sequence via a robust BPNN engine. In addition, the existing system can demonstrate the explosion views and vivid assembly simulations, save the entire assembly information, and setup a splendid knowledge base. Finally, the study apply the toy car model as a learning (training) sample and toy motorbike model, real-world brushless DC fan as testing and verified samples. The results show that the proposed model can efficiently generate BPNN engines, facilitate assembly sequence optimization and allow the designers to recognize the contact relationships, assembly difficulties and assembly constraints of three-dimensional (3D) components in a virtual environment type.
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Pan, Chunxia. "Integrating CAD files and automatic assembly sequence planning /". 2005.
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10
Shih, Wei-Feng, e 石豐維. "Computer-Aided Assembly Sequence Planning Using Simulated Annealing". Thesis, 2001. http://ndltd.ncl.edu.tw/handle/87028953120959661768.
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碩士大葉大學
工業工程研究所
89
The purpose of this project is to establish a computer -aided model for assembly sequence planning using simulated annealing approach. Four evaluation criteria such as directionality, fixture complexity, direction change and tool change are developed for systematic evaluation of the assembly sequences. Then, simulated annealing algorithm have been adopted for solution procedure for assembly sequence planning. In addition, the solution quality and solving efficiency are tested for the computer-aided model being developed. Finally, real-world examples are adopted for illustrating and validating the performance of the computer-aided SA model for assembly sequence planning.
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Shih-Chun, Lai, e 賴仕椿. "Assembly Evaluation Model With Concurrent Consideration of Design for Flexible Assembly and Assembly Sequence Planning". Thesis, 1998. http://ndltd.ncl.edu.tw/handle/45322450707626536500.
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碩士大葉大學
工業工程研究所
86
The purpose of this project is to develop an assembly evaluation model withconcurrent consideration of Design for Flexible Assembly(DFA) and AssemblySequence Planning(ASP). By applying the concepts of Design for Flexible assemblyin the early stage of the design process, flexible assembly products can be designedand thus increase the flexibility of the assembly systems. In addition, AssemblySequence Planning helps the selection of the best assembly sequence in which partsof subassemblies are put together in the mechanical assembly of a product that candrasticlly affect the affect the efficiency of the assembly process. Based on thestudies of DFA and ASP, the project takes a concurrent engineering approach by integratingthe DFA in the design stage with the ASP in the manufacturing stage in order todelelop an assembly evaluation model for assembly product design and process planning.The DFA module includes the functions of Flexibility Criteria, Flexibility Evaluationand Redesign Diagnosis. The ASP module includes the functions of Sequence Representation,Sequence Evaluation and AI Search Algorithm. Finally, an example is adopted forthe application and illustration of the concurrent assembly evaluation model being developed.
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Lin, Tzu-Ting, e 林子婷. "Assembly Sequence Planning and Supplier Selection with Limited Capacity". Thesis, 2011. http://ndltd.ncl.edu.tw/handle/t6ggsz.
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碩士國立臺北科技大學
工業工程與管理研究所
99
This study focuses on the production planning in supply chain system with multiple plants of multi products. The optimal suppliers combination and production resource allocation are decided in this production plan with introducing the assembly sequence planning and operation assignment technologies. In this study, a multi-objective optimization model is developed and a modified multi-objective algorithm is proposed to solve the optimization model, The solving results show that the optional suppliers combination, production plan for each assembly plant and transportation plant between supplier and plant when the central assembly plant receives the order with considering the capacities of plants. The modify algorithm is based in NSGA-II, is called W-NSGA2, which introduces the mechanisms of maximum number of follower tasks and maximum task time to the initial solution generation to enhance the solving performance of NSGA-II. Finally, the case of tap assembly operations is used to compare the solving performance among W-NSGA2, NSGA-II, and NSPSO. The results show that the W-NSGA2 has the best solution quality for the proposed problems.
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Jhang, Jia Fong, e 張家鳳. "An Evaluation Model for Integrating the Assembly Sequence Planning". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/88958333757218173774.
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碩士元智大學
工業工程與管理學系
92
In recent years, a company emphasizes on shorten of time-to-market for new and low-priced product to meet customers’ demands to stay competitive and sustainable under global competitive environment. Due to the rapid change of production environment, the enterprise gradually moves towards on the multi-members design of cross region and the multi-plants manufacture industry. Because Design for assembly(DFA) may simultaneously pay attention to the programs of design and assembly, it certainly shorten the time of development and reduce the product total cost. Under the concept of “Collaborative Design”, the purpose of this thesis is to develop an integrated evaluation model with the assembly sequence planning, DFA analysis and design change for multi-plants manufacture. The objective of this thesis is to develop an integrated model in two phases. The first phase is to search for the possible assembly sequences, according to the component of product being divided into subassembly and the constraints of operation. The model is aimed at minimizing the total assembly cost to obtain the best multi-plant assembly sequences. The second phase is based on the optimal assembly sequence of the first model to conform DFA analysis, including Functional analysis and Manual handling analysis. We can understand the component needed to be improved and finish the design change through collaborative discussion and the duty assignment. The model is aimed at minimizing the total production cost to obtain the best DFA design project. The enterprise may stand on the multi-plants integrated assembly sequence planning and DFA evaluation model in this thesis to assist in making strategic decision.
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Lin, Shiuh-Sheng, e 林旭昇. "Solving assembly sequence planning problems using heuristic search strategies". Thesis, 1993. http://ndltd.ncl.edu.tw/handle/52191569624339759528.
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Chen, Kuan-Hsiang, e 陳冠翔. "Suppliers Selection Model Construction and Production Planning-Assembly Sequence Planning and Defective Rate". Thesis, 2013. http://ndltd.ncl.edu.tw/handle/y9hs6f.
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碩士國立臺北科技大學
工業工程與管理系碩士班
101
Nowadays, the customer’s demand varies fast. The factory must produce product that customer need. Moreover, the globalization make the collaboration between factories become more and more important. In this case, supply chain management and suppliers selections play a key role in production. This study base on the suppliers selection criteria, construct a suppliers selection model. Additionally, this study adds time windows constraints into the suppliers selections model. On the other hand, in the part of production planning, most of the past researches assume that one factory produce one product. Actually, this assumption is not conform with the reality. To improve the assumption, this study assume that one factory produce multi-products. In addition, this study adds assembly sequence planning and assembly line balancing into production planning. For the completeness, this study adds robust optimization based on the defective rate in production planning, increases the robustness of the solutions. In the end, this study combine Guided GA and NSGA-II to solve suppliers selection and production planning and construct them into a system, let the leader make decision fast and effectively.
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WANG, CHI-HSIN, e 王啟鑫. "The Research of Intelligent Assembly Sequence Planning in Industrial 4.0". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/mw8uve.
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碩士東海大學
工業工程與經營資訊學系
105
Currently, Industry 4.0 is becoming a worldwide trend of automation technology; it is generating a new type of manufacturing model. In the Industry 4.0 paradigm, the cyber–physical system (CPS) is a paramount core element that increases the intelligence of the manufacturing process. A CPS provides intelligent interactions that connect virtual and real environments. To provide manufacturing flexibility, a CPS adjusts manufacturing parameters automatically according to feedback from an intelligent system. Without exception, intelligent assembly operation is an essential key to intelligent manufacturing by using a CPS. To complete an intelligent assembly operation, cooperation between a robotic arm and an assembly sequence planning (ASP) system is necessary. However, ASP and manually writing software for robots are both time consuming; both require professional knowledge and experience. Therefore, this paper proposes a cyber–physical assembly system to achieve two objectives. First, this paper presents a dual-projection interference analysis approach (DPIAA) that analyzes the relations between components. Second, this paper generates optimal assembly sequences automatically to produce suitable assembly sequences that robotic arms can use to perform assembly operations. Furthermore, this paper uses three computer-aided design models to verify that the DPIAA is faster than comparable methods and that the optimized assembly sequences are more suitable to perform the operation through robotic arm than other optimized sequences. In future assembly factories, the proposed method can facilitate intelligent manufacturing.
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TAI, PEI-HAO, e 戴培豪. "A Knowledge-Based Engineering System for Integral Assembly Sequence Planning". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/42203602470957292159.
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博士中華大學
科技管理學系(所)
97
Research in assembly planning can be categorized into three types of approach: graph-based, knowledge-based and artificial intelligence approaches. The main drawbacks of the above approaches are as follows: the first is time-consuming; the second approach is difficult to find the optimal solution; and the third approach requires a high computing efficiency. To tackle these problems, this study develops a three-stage approach (i.e., firstly create a correct CAD-oriented explosion graph and then find a graph-based assembly sequence using Above graph, relational model graph and assembly precedence diagram; at last, generating a feasible assembly sequence) integrated with robust back-propagation neural network (BPNN) engines via Taguchi method and design of experiment (DOE), and a knowledge-based engineering (KBE) system to assist the assembly engineers in promptly predicting a near-optimal assembly sequence for mechanical or plastic products. The research focuses on building a novel KBE system for assembly sequence planning (ASP), which joins BPNN predictor and Siemens NX/KF second development module together to create feasible assembly sequences. System user can easily access the volume, weight and feature number through Unigraphics NX system interface, and input the related parameters such as contact relationship number and total penalty value, and predict the feasible assembly sequence via a robust BPNN engine. Furthermore, the proposed system can demonstrate the explosion views and vivid assembly simulations, save the entire assembly information, and setup a consolidate knowledge base. Finally, three real-world examples- the toy car model as a learning (training) sample, toy motorbike model and a brushless DC fan as verifying (testing) samples, are dedicated to evaluating the feasibility of the proposed KBE system in terms of the differences in assembly sequences. The results show that the proposed model can efficiently generate robust BPNN engines, facilitate feasible assembly sequences and allow the designers to recognize the contact relationships, assembly difficulties and assembly constraints of three-dimensional (3D) components in a virtual environment type.
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Yu, Fang-Yu, e 游芳瑜. "Integrated Assembly and Disassembly Sequence Planning Using Particle Swarm Optimization". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/71243443290133843850.
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碩士元智大學
工業工程與管理學系
97
In light of the raising environmental consciousness, there are more and more countries adopting policies on sustainability. European Union applied the Waste Electrical and Electronic Equipment regulations, which require the enterprises who sell the electrical product to Europe take the responsibility for recycling the product. Some research has shown that more than two thirds of products’ success is almost decided on the design stage. Therefore, product designers nowadays are encouraged to design their products based on the product life cycle. As a result, considering a product’s disassembly and recycle cost becomes an important issue. In the past, most research considers a product’s disassembly sequence to be the inverse of assembly sequence. But in real case as long as it doesn’t against the product’s assembly interference, the disassembly sequence need not to be the inverse of assembly. In addition, when a company designs their product manufacturing process, there could be many assembly alternatives to choose from – The assembly method with lower cost might have much higher disassembly cost. Hence, in this research we will use a total cost estimation method to the minimization of the total cost. Using Particle Swarm Optimization (PSO) as the solving tool, through the coding technique, we try to solve the assembly sequence and disassembly sequence at the same dimension search space. After a decoding process, we would get a best assembly method, assembly sequence, and disassembly sequence. Finally we use Exhaustive Enumeration Method to enumerate all the possible sequences to compare with the results of PSO.
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Lin, Yao-Ying, e 林瑤瑩. "A Bi-objective Model for Concurrent Planning of Supplier Selection and Assembly Sequence Planning". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/u67c4x.
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碩士國立臺北科技大學
工業工程與管理研究所
97
This study discussed parts supplier selection for central assembly plant. In addition to the delivery state of suppliers, the production conditions of the central assembly plant should be considered. A bi-objective optimal mathematical model was thus established for supplier selection in this study, which incorporates assembly sequence planning (ASP). At the same time, the hybrid multi-objective algorithm (HMOA) which combines Non-dominated sorting genetic algorithm II (NSGA-II) and Non-dominated sorting particle swarm optimization (NSPSO) was used to solve the model for a case of stapler assembly, in order to validate the solving effects of HMOA. The results showed that HMOA is not only more exact than NSGA-II and NSPSO, but also have a better distribution and a wider extent than NSGA-II.
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Meng, Ling-Peng, e 孟令鵬. "Using Artificial Immune Algorithms to Slove Connector-based Assembly Sequence Planning Problems". Thesis, 2007. http://ndltd.ncl.edu.tw/handle/13841043592303722793.
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碩士國立勤益科技大學
工業工程與管理系
95
For most industrial products, the assembly costs take up a big part among the total product costs. The so-called assembly sequence planning need to take into subtle consideration certain constraint factors such as geometry data from CAD, tools and fixtures so as to work out a correct and complete assembly sequence. Then, a assemble task in which components are turned into a final product according to the specific assembly plan. In the research, the related algorithms are conducted in the connector-based environment. The so-called connector can be defined as the description of products based on the combination of parts. Because connectors cover more engineering information, they can serve as concept product building blocks in the design stages. In the past, Tseng (2006) and Tseng et al. (2007) had the experience for improving the Genetic Algorithms to solve the assembly planning problems in the larger constraint problems. Guided Genetic Algorithms recommended by Tseng (2006) have the defects to fall into the local optimal scraps. Besides, Memetic Genetic Algorithms suggested by Tseng et al. (2007) feature the better solution but excessive time-consuming system. In this study, the Artificial Immune Algorithms (AIAs) which are derivate from the antibody and antigen’s undivided and memorial characteristics towards the adaptive immune response of biological immune system are proposed to solve the connector-based assembly planning problems. Focusing on the better reproduction of the antibody then put into the memory zone while keeping the memory zone various. Furthermore, practical examples are provided to illustrate the feasibility of AIAs. It is found that AIAs can achieve the dual purpose, the good quality solution and acceptable execution time. Finally, the author tries to realize the assembly planning system by using the tool of Unified Modeling Language (UML). This approach can effectively integrate the solver such as genetic algorithms or artificial immune algorithms and the connector-based assembly data environment.
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Tseng, Chao-Hsiang, e 曾昭翔. "Computer Aided Assembly Sequence Planning for Electronics Products－Using Methods-Time Measurement". Thesis, 2001. http://ndltd.ncl.edu.tw/handle/84528621571105157432.
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碩士元智大學
工業工程研究所
89
Over the last few years, because the trend of product diversification increases and product life cycle is very short, it’s so difficult to fulfill the task in assembly systems that installing highly automated production system is inefficient. Therefore, it’s necessary to maintain manual systems in assembly shops in the future. In past research of process planning as to manual assembly sequence were obtained by Methods-Times Measurement (MTM) that depended on experience or try test again and again. As the demand for more products component, products diversification and short lift cycle of products , this method is inefficient without evaluation standard. As a result, the planning of manual assembly sequence that how to integrated design and production work to match with computerization is the important question. In this research, a graph-based approach is used to establish a State-Space Assembly Sequence Tree for electronics products. According to manual motion characteristics, manual assembly motion is classified. And then, this study make concept of set and second integration motion principle (SIMP) to decide the number of necessary parts of unit. Finally, we make use of MTM and expert system to evaluate manual assembly sequence to obtain the lowest time by evaluation indicatives. The objective of this research is to develop a systematic evaluation method to plan manual assembly sequence for electronics product. As getting assembly information of product model, we can get knowledge of manual assembly sequence and manipulation for products right now.
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Yang, Jia-Haur, e 楊家豪. "The Application of Genetic Algorithm on Computer Aided Assembly Sequence Planning Problem". Thesis, 1997. http://ndltd.ncl.edu.tw/handle/44673535597211913861.
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碩士國立臺灣大學
工業工程學研究所
85
A liaison information based assembly model is formulatedto facilitate computer-aided assembly planning and analysis.Liaison information, consisting of contacting and fitting information, is systematically specified by the planner following the presented guidelines, which are well-definedby a variety of symbols to represent mating conditionsbetween a pair, based on geometrical relations, of parts.Formulation rules are therefore defined to generate assemblyprecedence constraints form the specified liaison information.Two types of assembly constraints are defined namely sandwichedand blocked constraints. To facilitate assembly sequence planning evaluation, a practical cost function is presented toincorporateassembly instability, gripper changeover, assembly stroke reorientation,supporter flipover, and fixturing complexity.Three feasible assembly plan searching algorithms are presented: a depth-first searching algorithm, a heuristic algorithm, and a genetic algorithm. These algorithms are used to illustrate the possible optimal assembly sequences. To study the influence of parameters used in the presented genetic algorithm and to obtain an appropriate combination of parametersused in the presented genetic algorithm and to obtain an appropriate combination of these parameters, experiment design is conducted and result is presented. Assembly examples are used to show the use of thesealgorithms. Moreover, a PC based computer-aided assembly planning and analysis system is developed with user-friendly graphics userinterface and graphics animation.
23
Hardas, Chinmaya S. "Component placement sequence optimization in printed circuit board assembly using genetic algorithms". Thesis, 2003. http://hdl.handle.net/1957/30048.
Texto completo da fonteResumo:
Over the last two decades, the assembly of printed circuit boards (PCB) has generated
a huge amount of industrial activity. One of the major developments in PCB assembly
was introduction of surface mount technology (SMT). SMT has displaced through-hole
technology as a primary means of assembling PCB over the last decade. It has
also made it easy to automate PCB assembly process.
The component placement machine is probably the most important piece of
manufacturing equipment on a surface mount assembly line. It is used for placing
components reliably and accurately enough to meet the throughput requirements in a
cost-effective manner. Apart from the fact that it is the most expensive equipment on
the PCB manufacturing line, it is also often the bottleneck. There are a quite a few
areas for improvements on the machine, one of them being component placement
sequencing. With the number of components being placed on a PCB ranging in
hundreds, a placement sequence which requires near minimum motion of the
placement head can help optimize the throughput rates.
This research develops an application using genetic algorithm (GA) to solve the
component placement sequencing problem for a single headed placement machine. Six
different methods were employed. The effects of two parameters which are critical to
the execution of a GA were explored at different levels. The results obtained show that
the one of the methods performs significantly better than the others. Also, the
application developed in this research can be modified in accordance to the problems
or machines seen in the industry to optimize the throughput rates.Graduation date: 2004
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Wang, Jen-Chi, e 王仁祺. "Applying Case-Based Reasoning and Particle Swarm Optimization Algorithm to Construct Modular of Assembly and Disassembly Sequence Planning". Thesis, 2010. http://ndltd.ncl.edu.tw/handle/64633277647044247520.
Texto completo da fonteResumo:
碩士元智大學
工業工程與管理學系
98
As the raising environmental consciousness, there are more and more countries adopting policies on sustainability. That causes manufacturers that have to take the responsibility for recycling the waste product. Because changing consumption type cause the electrical waste product’s lifecycle be short. Considering the end of lifecycle is promotes the product design’s value. That will let the waste product to be useful. Based on the above, product designer have to consider the goal of modular design that easy to assemble, maintenance, disassemble and recycle. As a result, considering a product’s modular design becomes an important issue that redue the cost of assembly and disassembly. In the past, most researchs consider a product’s assembly and disassembly sequence. But in real case, it doesn’t against the component’s real relationship, that one component has more then one combination’s relation of components. The relation of assembly and disassembly sequence affect the change times of tool and angle. Hence, in this research we will use a total cost estimation method to the minimization of the total cost.Integrating Case-Based Reasoning（CBR）with Particle Swarm Optimization (PSO) as the solving tool, CBR will design the modular , and PSO use the modular’s result to solve three problems of the assembly sequence 、 disassembly sequence and assembly and disassembly sequence at the same time.Through the coding technique, we try to solve the assembly and disassembly sequence at the same dimension search space. In this case, we solve the sequence of component’s real relationship. After a decoding process, we would get a best assembly modular and component sequence, and disassembly modular and component sequence.
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Chiang, Chun-Lin, e 江俊霖. "Assembly Sequences Planning of Combine Factory Assembly Subcontractors". Thesis, 2002. http://ndltd.ncl.edu.tw/handle/81280514525267340515.
Texto completo da fonteResumo:
碩士元智大學
工業工程與管理學系
91
In the past, research related to assembling sequence planning has been based on individualized factories. Until recent years, for the purposes of industrial specification and production, many factories gradually build other sub-factories or merge with other resources that force individualized factories bypass their own problems onto complex multi-factorial planning systems. Thus, an interconnected multi-factorial model is formed. Within the model, a product needs at least more than one factory to process its parts until it is finally completed. In assembly, each factory is responsible for only one part of the product. Therefore, current production mode and company manner do not support individualized factories, neither do they comply with the past trend of one-company-one-factory principle. To summarize, individualized factory assembly model is not applicable in the current production mode. Under the current trend that more diversification and specification is in effect, planning of an interconnected multi-factorial assembling sequence must be considered. Regarding the planning of an interconnected multi-factorial assembling sequence, the paper proposes two set of sub-assembly. The first set of sub-assembly is completed in an individualized factory, using an assembly status graph to establish an assembly precedence graph and determine the sub-assembly; the second set of sub-assembly is completed with several aggregated outcomes of chosen elements. One assumption is that the exact number of factories remains unknown until a factory sitemap is obtained that indicates the best solution. Also, the takeover action is determined by the concept of centralized satellite model which reveals the current status, and the choice sequence order is used to evaluate the minimum time cost. Then, several operation cost functions are developed to analyze parts that are about to be assembled, use SAST to search for all assembly sequence, and determine the best interconnected multi-factorial assembly sequence. The paper aims specifically for electronic products that are in need of assembly. The objective is to develop a systematic method and cost analysis trend in order to find the minimum cost of interconnected multi-factorial assembly sequence, thus keeping the cost of assembling parts at minimum.
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Lin, Chi-Hung, e 林吉宏. "Planning and Evaluation of Integrated Machining and Assembly Sequences Using Genetic Algorithms". Thesis, 2000. http://ndltd.ncl.edu.tw/handle/01275837295634467623.
Texto completo da fonteResumo:
碩士元智大學
工業工程研究所
88
In current process planning approaches, assembly sequence planning and machining sequence planning are performed individually. The relationships between assembly and machining have been ignored in the past. In design of some assembly parts, some precision, tolerance, and technique requirements, can not be completed during the assembly process. It is required to machine a subassembly formed by assembling a group of parts. Also, a machining process maybe needed to machine some portions of a completely assembled product. Therefore, the assembly sequence needs to be mixed with machining sequence and there may exist interactions between assembly and machining. Thus, the evaluation and analysis of assembly and machining sequences must be considered simultaneously in the planning phase. In this research, a graph-based approach is used to establish a hierarchical assembly precedence graph and assembly operation element graph. Then, several operation cost functions are developed to evaluate the assembly and machining cost. The genetic algorithms are applied to search the best solution. The integrated assembly and machining sequences are analyzed and the lowest cost can be evaluated using the genetic algorithms. The cost functions include accessibility cost, stability cost, parallelism cost, workstation cost, machine operation cost, tool cost, tool change cost, setup cost, movement cost and clustering cost. The objective of this research is developed a systematic method to solve the integrated assembly and machining problem and to find the minimum cost of an assembly part.
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Tsai, Cha-Li, e 蔡佳利. "Research for Integrated Planning of Machining and Assembly Sequences in Combine Factory". Thesis, 2003. http://ndltd.ncl.edu.tw/handle/55726849956549947060.
Texto completo da fonteResumo:
碩士元智大學
工業工程與管理學系
91
Due to the rapid change of global economic environment and industrial framework, the competition strategy of enterprise have becoming to focus on customer demand. A variety demand to the product makes the manufacturing procedure of assembly become complexity. Planning in one factory will no more meet the demand of product. Therefore, how to planning for multi-plant assembly and machining sequences has been a key issue in the product development process because of the cost savings that can be gained by using a good assembly and machining sequence to manufacture a product. In this research, the assessment models of the construction of assembly and machining process can be divides into three phases. In the first phase, the component of product being divided into subassembly and outline the constraints of machining. In the second phase, the assembly and machining constrains will be the searching constrains, to searching for the possible assembly and machining operation sequences. In the third phase, all of the assembly machining sequence will be assessed. This model is aimed at minimizing the total production cost to obtain the best multi-plan sequences. After the information of production format, operation equipments, equipment of every plan and costs had been knew, using linear planning and three-phase assessment model which suggested here to obtain the best multi-plan assembly and machining sequences with the goal of minimizing the total costs. The enterprise may according the assessment model in this research to use as an important technique of decision assist strategy.
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Chen, Jian-Yu, e 陳建宇. "Assembly Sequences Planning in a Multi-Plant Manufacturing Environment Using Genetic Algorithms and Particle Swarm Optimization". Thesis, 2008. http://ndltd.ncl.edu.tw/handle/25559278552240123434.
Texto completo da fonteResumo:
碩士元智大學
工業工程與管理學系
96
Due to the product design have becoming variety and complexity. The enterprises in order to enhance the competitiveness use the multi-plant planning. The assembly sequence in multi-plant planning, it not only considers the assembly sequence to each component but also assign the component to a feasible plant. Therefore, the single-plant planning for assembly is no longer applied to the problem. How to solve the assembly sequence problem quickly in multi-plant planning has been a key issue. In this thesis, using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) solve the assembly sequence problem in multi-plant planning. The objective is to obtain optimum the assembly sequence in multi-plant for the minimum cost. The assembly sequence problem in multi-plant planning combines the sequence problem and the assignment problem. We using GA solve two problems at same time by a special encoding rule. And in PSO, we using different definition at multi-dimension in order to solve assignment and sequence problem at same time. Cases are given to show the effectiveness of two algorithm can find the solutions which close to optimal, and characteristics of the algorithm are discussed.
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Hung, Tzu-Yin, e 洪梓茵. "Applying Case-Based Reasoning and Genetic Algorithm to Construct an Assembly Sequences Planning in Multi-Plant Manufacturing Environment". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/60014764182184097829.
Texto completo da fonteResumo:
碩士元智大學
工業工程與管理學系
97
In order to fulfill the various marketing requirements, the classification of product components into subassemblies becomes more complicated; therefore, it is a tendency to have modular design of product components under customize manufacturing environment. In product assembly process, modular design is provided with flexible and economic specialties, also integrate components with similar function and characteristic to simple modules for complete the specific assembly sequence. Customers’ satisfaction is the main propose of product requirement, either varied regulation and design, or the demand of high quality and high yield rate in the manufacturing environment, enterprises must integrate multi-plant resource planning to enhance the competitiveness. In this thesis, attempting to construct an assembly sequences planning in multi-plant manufacturing environment by integrating Case-Based Reasoning（CBR）with Genetic Algorithm（GA）. By applying CBR approach solving new problem by adapting solution that were used to solve previous similar problems, to modularized product components quickly and be suitable for assigning subassemblies in multi-plant assembly sequence. Afterwards, using GA with a special encoding rule solving assembly sequence problem and multi-plant subassembly assignment problem at the same time, then decoding the chromosome to obtain the assembly sequences planning in multi-plant manufacturing environment with the minimize total assembly cost.