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Literatura académica sobre el tema "Intelligent and Flexible Manufacturing"

Autor: Grafiati

Publicado: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Intelligent and Flexible Manufacturing"

1

CHANDRA, J. y J. TALAVAGE. "Intelligent dispatching for flexible manufacturing". International Journal of Production Research 29, n.º 11 (noviembre de 1991): 2259–78. http://dx.doi.org/10.1080/00207549108948082.

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Varvatsoulakis, M. N., G. N. Saridis y P. N. Paraskevopulos. "Intelligent organization for flexible manufacturing". IEEE Transactions on Robotics and Automation 16, n.º 2 (abril de 2000): 180–89. http://dx.doi.org/10.1109/70.843174.

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Ju, Canze. "3D Printing Distributed Mold Intelligent Manufacturing Model Analysis". Highlights in Science, Engineering and Technology 76 (31 de diciembre de 2023): 65–70. http://dx.doi.org/10.54097/h18q1h39.

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In recent years, with the rapid development of technologies such as 3D printing, distributed manufacturing, and intelligent management, the manufacturing industry is undergoing a revolutionary transformation. The emerging 3D printing distributed mold intelligent manufacturing mode combines these cutting-edge technologies, aiming to achieve personalized and flexible production. This is leading the manufacturing industry towards intelligence and customization. This paper discusses the core concepts and key technical elements of 3D printing distributed mold intelligent manufacturing mode. This model combines 3D printing technology, distributed manufacturing, and intelligent management to achieve personalized and flexible production. From cloud intelligent platform, 3D printing manufacturing, distributed manufacturing to business model innovation, the management characteristics of this model in production, design, value chain management and business are discussed. Examples such as Quirky and 3D Systems are used to illustrate the practical application and innovation of the model. This model not only promotes innovation in manufacturing, but also brings new prospects for personalized production and consumption patterns.

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Kostal, P., A. Mudrikova y D. Michal. "Possibilities of intelligent flexible manufacturing systems". IOP Conference Series: Materials Science and Engineering 659 (31 de octubre de 2019): 012035. http://dx.doi.org/10.1088/1757-899x/659/1/012035.

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Ahmad, M. Munir y William G. Sullivan. "Flexible automation and intelligent manufacturing 2001". Robotics and Computer-Integrated Manufacturing 18, n.º 3-4 (junio de 2002): 169–70. http://dx.doi.org/10.1016/s0736-5845(02)00026-1.

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Woo, K. B., K. S. Seo, I. S. Ahn, C. H. Lee y S. K. Shin. "Intelligent Controller for Flexible Manufacturing System". IFAC Proceedings Volumes 25, n.º 7 (mayo de 1992): 79–84. http://dx.doi.org/10.1016/s1474-6670(17)52343-5.

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ALI, AHAD. "FUZZY LOGIC BASED UNCERTAINTY REPRESENTATION AND SIMULATION IN A FLEXIBLE ASSEMBLY SYSTEM". International Journal of Modeling, Simulation, and Scientific Computing 03, n.º 03 (17 de mayo de 2012): 1250013. http://dx.doi.org/10.1142/s1793962312500134.

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This paper provides intelligent simulation approach using manufacturing uncertainty in the form of simulation intelligence to improve the performances of manufacturing production system. It shows how simulation can be used to evaluate alternative designs in an uncertain manufacturing environment. Fuzzy rule-based manufacturing uncertainties are addressed in this study. A combination of product mix and production volume is analyzed using intelligent simulation model for an optimal production design. The intelligent simulation approach would improve the modeling accuracy in terms of more realistic presentation of uncertain activities. The proposed intelligent simulation modeling shows significant improvement and validated with real life application.

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Wang, Xi. "Design of Customized Intelligent Manufacturing Information Interaction System Based on Virtual Technology". Journal of Physics: Conference Series 2074, n.º 1 (1 de noviembre de 2021): 012043. http://dx.doi.org/10.1088/1742-6596/2074/1/012043.

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Abstract With the continuous development of information technology, system intelligence is leading the next round of “industrial revolution”, especially the intelligent manufacturing industry has become the core of improving industrial productivity. Intelligent manufacturing involves each link in the manufacturing industry, which is the most critical part of intelligent manufacturing is intelligent production, through intelligent manufacturing related technology to optimize the production mode of manufacturing to promote the production state more flexible and integrated. Intelligent manufacturing is based on computer simulation technology and information and communication technology, optimize the production design of the factory and simplify the production process of the factory, the purpose is to reduce the waste of resources and improve the reasonable allocation of production resources.

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Weller, R. y J. W. Schulte. "Flexible Optimisation Tools for Intelligent Manufacturing Systems". IFAC Proceedings Volumes 27, n.º 4 (junio de 1994): 477–82. http://dx.doi.org/10.1016/s1474-6670(17)46069-1.

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Mekid, S., P. Pruschek y J. Hernandez. "Beyond intelligent manufacturing: A new generation of flexible intelligent NC machines". Mechanism and Machine Theory 44, n.º 2 (febrero de 2009): 466–76. http://dx.doi.org/10.1016/j.mechmachtheory.2008.03.006.

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Tesis sobre el tema "Intelligent and Flexible Manufacturing"

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Fan, I.-P. "Intelligent flexible manufacturing system control". Thesis, Cranfield University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.234483.

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Rogers, Paul. "Object-oriented modelling of flexible manufacturing cells". Thesis, University of Cambridge, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276540.

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Leitão, Paulo. "An agile and adaptive holonic architecture for manufacturing control". Doctoral thesis, Universidade do Porto, Faculdade de Engenharia, 2004. http://hdl.handle.net/10198/1440.

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In the last decades significant changes in the manufacturing environment have been noticed: moving from a local economy towards a global economy, with markets asking for products with high quality at lower costs, highly customised and with short life cycle. In this environment, the manufacturing enterprises, to avoid the risk to lose competitiveness, search to answer more closely to the customer demands, by improving their flexibility and agility, while maintaining their productivity and quality. Actually, the dynamic response to emergence is becoming a key issue, due to the weak response of the traditional manufacturing control systems to unexpected disturbances, mainly because of the rigidity of their control architectures. In these circumstances, the challenge is to develop manufacturing control systems with autonomy and intelligence capabilities, fast adaptation to the environment changes, more robustness against the occurrence of disturbances, and easier integration of manufacturing resources and legacy systems. Several architectures using emergent concepts and technologies have been proposed, in particular those based in the holonic manufacturing paradigm. Holonic manufacturing is a paradigm based in the ideas of the philosopher Arthur Koestler, who proposed the word holon to describe a basic unit of organisation in biological and social systems. A holon, as Koestler devised the term, is an identifiable part of a (manufacturing) system that has a unique identity, yet is made up of sub-ordinate parts and in turn is part of a larger whole. The introduction of the holonic manufacturing paradigm allows a new approach to the manufacturing problem, bringing the advantages of modularity, decentralisation, autonomy, scalability, and re-use of software components. This dissertation intends to develop an agile and adaptive manufacturing control architecture to face the current requirements imposed to the manufacturing enterprises. The architecture proposed in this dissertation addresses the need for the fast reaction to disturbances at the shop floor level, increasing the agility and flexibility of the enterprise, when it works in volatile environments, characterised by the frequent occurrence of unexpected disturbances. The proposed architecture, designated by ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), is based in the holonic manufacturing paradigm, build upon autonomous and cooperative holons, allowing the development of manufacturing control applications that present all the features of decentralised and holonic systems. ADACOR holonic architecture introduces an adaptive control that balances dynamically between a more centralised structure and a more decentralised one, allowing to combine the global production optimisation with agile reaction to unexpected disturbances. Nas últimas décadas têm-se assistido a mudanças significativas no ambiente de fabrico: evoluindo de uma economia local para um economia global, com os mercados a procurar produtos com elevada qualidade a baixos preços, altamente customizados e com um ciclo de vida curto. Neste ambiente, as empresas de manufactura, para evitar o risco de perda de competitividade, procuram responder às solicitações dos clientes, melhorando a sua flexibilidade e agilidade, mantendo os mesmos índices de produtividade e qualidade. Na verdade, a resposta dinâmica à emergência está a tornar-se num assunto chave, devido `a fraca resposta a perturbações que os sistemas de controlo de fabrico tradicionais apresentam, principalmente devido à rigidez das suas arquitecturas de controlo. Nestas circunstâncias, é fundamental o desenvolvimento de sistemas de controlo de fabrico com capacidades de autonomia e inteligência, rápida adaptação às mudanças, maior robustez à ocorrência de perturbações e fácil integração de recursos físicos e sistemas legados. Diversas arquitecturas usando conceitos e tecnologias emergentes têm sido propostas, em particular algumas baseadas no paradigma da produção holónica. O paradigma da produção holónica é inspirado nas ideias de Arthur Koestler, que propôs a palavra holon para descrever uma unidade básica de organização de sistemas biológicos e sociais. Um holon, de acordo com a definição de Koestler, é uma parte identificável do sistema com identidade única, composta por sub-partes e fazendo simultaneamente parte do todo. A introdução do paradigma da produção holónica permite uma nova abordagem aos sistemas de controlo de fabrico, trazendo vantagens de modularidade, descentralização, autonomia, escalabilidade e reutilização de componentes. Esta dissertação pretende desenvolver uma arquitectura de controlo ágil e adaptativa que suporte os requisitos actuais impostos `as empresas de manufactura. A arquitectura proposta visa a necessidade de uma reacção rápida a perturbações, ao nível da planta fabril, melhorando a flexibilidade e agilidade da empresa quando esta opera em ambientes voláteis, caracterizados pela ocorrência frequente de perturbações inesperadas. A arquitectura proposta, designada por ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), é baseada no paradigma da produção holónica e construída sobre holons autónomos e cooperativos, permitindo o desenvolvimento de aplicações de controlo de fabrico que apresentem todas as características dos sistemas descentralizados e holónicos. A arquitectura holónica ADACOR introduz um controlo adaptativo que balança dinamicamente entre uma estrutura de controlo mais centralizada e uma mais descentralizada, permitindo combinar a optimização da produção com a ágil reacção a perturbações.

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Reyes, Moro Antonio. "Scheduling of flexible manufacturing systems integrating Petri nets and artificial intelligence methods". Thesis, Liverpool John Moores University, 2000. http://researchonline.ljmu.ac.uk/5527/.

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The work undertaken in this thesis is about the integration of two well-known methodologies: Petri net (PN) model Ii ng/analysis of industrial production processes and Artificial Intelligence (AI) optimisation search techniques. The objective of this integration is to demonstrate its potential in solving a difficult and widely studied problem, the scheduling of Flexible Manufacturing Systems (FIVIS). This work builds on existing results that clearly show the convenience of PNs as a modelling tool for FIVIS. It addresses the problem of the integration of PN and Al based search methods. Whilst this is recognised as a potentially important approach to the scheduling of FIVIS there is a lack of any clear evidence that practical systems might be built. This thesis presents a novel scheduling methodology that takes forward the current state of the art in the area by: Firstly presenting a novel modelling procedure based on a new class of PN (cb-NETS) and a language to define the essential features of basic FIVIS, demonstrating that the inclusion of high level FIVIS constraints is straight forward. Secondly, we demonstrate that PN analysis is useful in reducing search complexity and presents two main results: a novel heuristic function based on PN analysis that is more efficient than existing methods and a novel reachability scheme that avoids futile exploration of candidate schedules. Thirdly a novel scheduling algorithm that overcomes the efficiency drawbacks of previous algorithms is presented. This algorithm satisfactorily overcomes the complexity issue while achieving very promising results in terms of optimality. Finally, this thesis presents a novel hybrid scheduler that demonstrates the convenience of the use of PN as a representation paradigm to support hybridisation between traditional OR methods, Al systematic search and stochastic optimisation algorithms. Initial results show that the approach is promising.

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Kim, Doosuk Mechanical &amp Manufacturing Engineering Faculty of Engineering UNSW. "Intelligent scheduling and control of automated guided vehicle considering machine loading in a flexible manufacturing system: using hopfield networks and simulation". Awarded by:University of New South Wales. School of Mechanical and Manufacturing Engineering, 2006. http://handle.unsw.edu.au/1959.4/29542.

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Flexible manufacturing systems (FMS) have received increasing attention from researchers and practitioners due to their potential advantages: quicker response to market changes, reduction in work-in-process (WIP), high inventory turnover and high levels of productivity. Two groups of problems in an FMS are of importance: (1) design problems and (2) operational problems. Operational problems can be effectively separated into 4 sub-problems: planning, grouping, machine loading problem (MLP) and scheduling. Problems from machine loading to scheduling and control of an FMS can be handled with neural networks approaches and simulation. The machine loading problem as a combinatorial optimization problem is actually a classic problem in operations research and is known to be NP-hard. MLP formulated as 0-1 integer programming problems has been solved by the methods of linearizing the nonlinear terms, branch and bound algorithm, and heuristic methods which have also been popularly applied. Hopfield Networks as a class of artificial neural networks have been adapted as an efficient method to solve the MLP, as these are able to find the solutions quickly through massive and parallel computation. Unfortunately, the quality of the solutions can occasionally be poor owing to the values of the weighting parameters in the energy function of the Hopfield Networks. One alternative approach used is to imbed mean field annealing into Hopfield Networks. The hybrid method of Hopfield Networks and mean field annealing can find near-optimal solutions as well as overcome the difficulties with decisions about the weighting of parameters in the energy function. The AGV scheduling problem can be regarded as the problem of selecting appropriate dispatch rules. Many dispatch rules have been introduced by a number of researchers. Even though vqarious formulations of the FMS scheduling problem can be presented, simulation methods are popular and often used. A solution methodology for MLP and AGV scheduling problems is proposed and specific models based on the literature are subjected to experimented through simulation. The proposed methodology can be also applied without difficulty to of breakdowns of machines and AGV. Results from simulation experiment s show that superior performance and capability of the proposed to existing methods are demonstrated by applying them to the test problems represented by simulation..

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6

Ghosal, Subhabrata. "Object Oriented Simulation of Agent Based Flexible Manufacturing System with Dynamic Routing and Scheduling". Ohio University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1438812428.

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Touzani, Hicham. "Planification Multi-Robot du Problème de Répartition de Tâches avec Évitement Automatique de Collisions et Optimisation du Temps de Cycle : Application à la Chaîne de Production Automobile". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST079.

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Dans l’industrie automobile, plusieurs robots sont nécessaires pour réaliser simultanément des séquences de soudage sur un même véhicule. L’attribution et la coordination des tâches de soudage entre les robots est une phase manuelle et exigeante qui doit être optimisée à l’aide d’outils automatiques. Le temps de cycle de la cellule dépend fortement de différents facteurs robotiques tels que la répartition des tâches entre les robots, les solutions de configuration et l’évitement d’obstacles. De plus, un aspect clé, souvent négligé dans l’état de l’art, est de définir une stratégie pour résoudre le séquencement des tâches robotiques avec une intégration efficace de l’évitement de collisions robot-robot. Cette thèse est motivée par la résolution de ce problème industriel et cherche à relever différents défis de recherche. Elle commence par présenter les solutions de pointe actuelles en matière de planification robotique. Une enquête approfondie est menée sur les solutions académiques/industrielles existantes pour résoudre le problème de répartition des tâches robotiques, en particulier pour les systèmes multi-robot. Cette enquête permet d’identifier les défis lors de l’intégration de plusieurs facteurs robotiques dans le processus d’optimisation. Cette thèse présente un algorithme itératif efficace qui génère une solution de haute qualité pour le problème de répartition de tâches multi-robot. Ce dernier gère non seulement les facteurs robotiques mentionnés, mais également les aspects liés aux contraintes d’accessibilité et à l’évitement de collisions mutuelles. De plus, un planificateur fait maison (RoboTSPlanner) gérant des robots à six axes a été validé dans un scénario de cas réel. Afin d’assurer l’exhaustivité de la méthodologie proposée, nous effectuons une optimisation dans l’espace des tâches, de configuration et de coordination de manière synergique. Par rapport aux approches existantes, la simulation comme les expérimentations réelles révèlent des résultats positifs en termes de temps de cycle et montrent la capacité de cette méthode à s’interfacer à la fois avec les logiciels de simulation industrielle et les outils ROS-I
In the automotive industry, several robots are required to simultaneously carry out welding sequences on the same vehicle. Assigning and coordinating welding tasks between robots is a manual and challenging phase that must be optimized using automatic tools. The cycle time of the cell strongly depends on different robotic factors such as the task allocation among the robots, the configuration solutions, and obstacle avoidance. Moreover, a key aspect, often neglected in the state-ofthe- art, is to define a strategy to solve the robotic task sequencing with an effective robot-robot collision avoidance integration. This thesis is motivated by solving this industrial problem and seeks to raise different research challenges. It begins by presenting the current state-of-the-art solutions regarding robotic planning. An in-depth investigation is carried out on the related existing academic/industrial solutions to solve the robotic task sequencing problem, particularly for multi-robot systems. This investigation helps identify the challenges when integrating several robotic factors into the optimization process. An efficient iterative algorithm that generates a high-quality solution for the Multi-Robotic Task Sequencing Problem is presented. This algorithm manages not only the mentioned robotic factors but also aspects related to accessibility constraints and mutual collision avoidance. In addition, a home-developed planner (RoboTSPlanner) handling six-axis robots has been validated in a real case scenario. In order to ensure the completeness of the proposed methodology, we perform optimization in the task, configuration, and coordination space in a synergistic way. Compared to the existing approaches, both simulation and real experiments reveal positive results in terms of cycle time and show the ability of this method to be interfaced with both industrial simulation software and ROS-I tools

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Demesure, Guillaume. "Coordination et planification de systèmes multi-agents dans un environnement manufacturier". Thesis, Valenciennes, 2016. http://www.theses.fr/2016VALE0029/document.

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Cette thèse porte sur la navigation d'agents dans un environnement manufacturier. Le cadre général du travail relève de la navigation d'AGVs (véhicules autoguidés), transportant librement et intelligemment leur produit. L'objectif est de proposer des outils permettant la navigation autonome et coopérative d’une flotte d’AGVs dans des systèmes de production manufacturiers où les contraintes temporelles sont importantes. Après la présentation d'un état de l'art sur chaque domaine (systèmes manufacturiers et navigation d'agents), les impacts de la mutualisation entre ceux-ci sont présentés. Ensuite, deux problématiques, liées à la navigation d'agents mobiles dans des environnements manufacturiers, sont étudiées. La première problématique est centrée sur la planification de trajectoire décentralisée où une fonction d'ordonnancement est combinée au planificateur pour chaque agent. Cette fonction permet de choisir une ressource lors de la navigation afin d'achever l'opération du produit transporté le plus tôt possible. La première solution consiste en une architecture hétérarchique où les AGVs doivent planifier (ou mettre à jour) leur trajectoire, ordonnancer leur produit pour l'opération en cours et résoudre leurs propres conflits avec les agents à portée de communication. Pour la seconde approche, une architecture hybride à l'aide d'un superviseur, permettant d'assister les agents durant leur navigation, est proposée. L'algorithme de planification de trajectoire se fait en deux étapes. La première étape utilise des informations globales fournies par le superviseur pour anticiper les collisions. La seconde étape, plus locale, utilise les données par rapport aux AGVs à portée de communication afin d'assurer l'évitement de collisions. Afin de réduire les temps de calcul des trajectoires, une optimisation par essaims particulaires est introduite. La seconde problématique se focalise sur la commande coopérative permettant un rendez-vous d'agents non holonomes à une configuration spécifique. Ce rendez-vous doit être atteint en un temps donné par un cahier des charges, fourni par le haut-niveau de contrôle. Pour résoudre ce problème de rendez-vous, nous proposons une loi de commande à temps fixe (i.e. indépendant des conditions initiales) par commutation permettant de faire converger l’état des AGVs vers une resource. Des résultats numériques et expérimentaux sont fournis afin de montrer la faisabilité des solutions proposées
This thesis is focused on agent navigation in a manufacturing environment. The proposed framework deals with the navigation of AGVs (Automated Guided Vehicles), which freely and smartly transport their product. The objective is to propose some tools allowing the autonomous and cooperative navigation of AGV fleets in manufacturing systems for which temporal constraints are important. After presenting the state of the art of each field (manufacturing systems and agent navigation), the impacts of the cross-fertilization between these two fields are presented. Then, two issues, related to the navigation of mobile agents in manufacturing systems, are studied. The first issue focuses on decentralized motion planning where a scheduling function is combined with the planner for each agent. This function allows choosing a resource during the navigation to complete the ongoing operation of the transported product at the soonest date. The first proposed approach consists in a heterarchical architecture where the AGVs have to plan (or update) their trajectory, schedule their product and solve their own conflict with communicating agents. For the second approach, hybrid architecture with a supervisor, which assists agents during the navigation, is proposed. The motion planning scheme is divided into two steps. The first step uses global information provided by the supervisor to anticipate the future collisions. The second step is local and uses information from communicating agents to ensure the collision avoidance. In order to reduce the computational times, a particle swarm optimization is introduced. The second issue is focused on the cooperative control, allowing a rendezvous of nonholomic agents at a specific configuration. This rendezvous must be achieved in a prescribed time, provided by the higher level of control. To solve this rendezvous, a fixed time (i.e. independent of initial conditions) switching control law is proposed, allowing the convergence of agent states towards a resource configuration. Some numerical and experimental results are provided to show the feasibility of the proposed methods

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Selke, Klaus Kurt Willi. "Intelligent assembly in flexible automation". Thesis, University of Hull, 1988. http://hydra.hull.ac.uk/resources/hull:8053.

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This work investigates the automation of assembly cells and the need to incorporate sensor-guided decision techniques. The experience of industry in this area is examined by observing a real cell on the shop floor. From the collected data conclusions point to an alternative error interpretation which describes the successful completion rather than an enumeration of errors. A methodology for the description of the process in robotic assembly is developed. The constituent phases in handling components are identified as Feeding, Transport and Mating. Each phase has well defined characteristic properties which can be determined using appropriate sensing mechanisms. The mating phase is given special attention by proposing the method of information Spaces as a suitable frame work for sensor fusion and context directed interpretation. Thus the successful progress is described regarding any deviations as errors. They in turn can be interpreted in the context in which they were encountered and recovery is accomplished in the demonstration cell by operator taught routines. Where error repetition occurs, a simple look-up technique suffices to remove the need for another operator intervention. The required data structures and the implementation of the experimental cell are discussed. It is concluded from the results that the principle of knowledge-based assembly control exhibits an intelligent behaviour which contributes to an increase in the cell productivity. This method addresses only a part of the overall problem of assembly automation, but it has a central place in the system and could be extended to the complete system.

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Aluskan, Aziz Batur. "Emulated Flexible Manufacturing Facility". [Florida] : State University System of Florida, 1999. http://etd.fcla.edu/etd/uf/1999/amj9902/aluskan.pdf.

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Thesis (M.S.)--University of Florida, 1999.
Title from first page of PDF file. Document formatted into pages; contains x, 90 p.; also contains graphics. Vita. Includes bibliographical references (p. 89).

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Libros sobre el tema "Intelligent and Flexible Manufacturing"

1

(Firm), Innovation 128, ed. Intelligent manufacturing systems. Paris, France: Innovation 128, 1991.

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Andrew, Kusiak, ed. Intelligent design and manufacturing. New York: Wiley, 1992.

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3

Silva, Francisco J. G., António B. Pereira y Raul D. S. G. Campilho, eds. Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-38241-3.

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Silva, Francisco J. G., Luís Pinto Ferreira, José Carlos Sá, Maria Teresa Pereira y Carla M. A. Pinto, eds. Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-38165-2.

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International, Conference on Intelligent Flexible Autonomous Manufacturing Systems: Towards Rapid Design Exploration and Optimization (2000 Coimbatore Institute of Technology). Intelligent, flexible, autonomous manufacturing systems: Proceedings of the International Conference on Intelligent, Flexible, Autonomous Manufacturing Systems: Towards Rapid Design Exploration and Optimization. New Delhi: Tata McGraw-Hill Pub. Co., 2000.

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Kim, Kyoung-Yun, Leslie Monplaisir y Jeremy Rickli, eds. Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-18326-3.

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Kim, Kyoung-Yun, Leslie Monplaisir y Jeremy Rickli, eds. Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-17629-6.

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Azevedo, Américo. Advances in Sustainable and Competitive Manufacturing Systems: 23rd International Conference on Flexible Automation & Intelligent Manufacturing. Heidelberg: Springer International Publishing, 2013.

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1940-, Itō Y., ed. Human-intelligence-based manufacturing. London: Springer-Verlag, 1993.

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Japan/U, S. A. Symposium on Flexible Automation (4th 1992 San Francisco Calif ). Proceedings of the 1992 Japan/U.S.A. Symposium on Flexible Automation. New York, N.Y: American Society of Mechanical Engineers, 1992.

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Capítulos de libros sobre el tema "Intelligent and Flexible Manufacturing"

1

Joshi, Sanjay y Richard Wysk. "Intelligent Control of Flexible Manufacturing Systems". En Modern Production Concepts, 416–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76401-1_27.

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Ben-Arieh, David y Eric D. Carley. "Qualitative intelligent modeling of manufacturing systems". En Computer control of flexible manufacturing systems, 264–84. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1230-7_10.

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Malhotra, Vasdev. "Artificial Intelligence and Flexible Manufacturing Systems". En Advanced Manufacturing Processes, 72–81. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003476375-7.

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Thie, Michael y Dragan Stokic. "Knowledge Based Methods and Tools for TQM in Small Batch Flexible Manufacturing and Complex Assembly". En Intelligent Systems for Manufacturing, 459–68. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-0-387-35390-6_40.

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Schleicher, Tim y Angelika C. Bullinger. "Assistive Robots in Highly Flexible Automotive Manufacturing Processes". En Advances in Intelligent Systems and Computing, 203–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96068-5_23.

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Lechuga, Gilberto Pérez y Francisco Martínez Sánchez. "Modeling and Optimization of Flexible Manufacturing Systems: A Stochastic Approach". En Intelligent Computing & Optimization, 539–46. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00979-3_57.

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Nacsa, János. "Logical Communication Levels in an Intelligent Flexible Manufacturing System". En IFIP Advances in Information and Communication Technology, 37–42. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-0-387-35492-7_4.

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Herrera-García, María-Cristina y Claudia-Yohana Arias-Portela. "Flexible Manufacturing Systems: A Methods Engineering and Operations Management Approach". En Advances in Intelligent Systems and Computing, 760–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68017-6_113.

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Gotz, Joelton Deonei, José Rodolfo Galvão, Alexandre Silveira, Emilson Ribeiro Viana, Fernanda Cristina Correa y Milton Borsato. "Intelligent Management for Second-Life Lithium-Ion Batteries with Backup Cells". En Flexible Automation and Intelligent Manufacturing: Establishing Bridges for More Sustainable Manufacturing Systems, 1011–18. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-38165-2_116.

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Shaw, Michael J. y Andrew B. Whinston. "Applying Distributed Artificial Intelligence to Flexible Manufacturing". En Advanced Information Technologies for Industrial Material Flow Systems, 81–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74575-1_5.

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Actas de conferencias sobre el tema "Intelligent and Flexible Manufacturing"

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Gaughran, W. F. "INTELLIGENT MANUFACTURING AND LATERALISATION". En Flexible Automation and Intelligent Manufacturing, 1997. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1997.890.

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Parthasarathi, S., J. R. Cook y J. Kajuch. "INTELLIGENT PROCESSING OF MATERIALS". En Flexible Automation and Integrated Manufacturing 1994. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1994.810.

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Lemnios, Z. J. "Flexible Intelligent Process Equipment". En International Symposium on Semiconductor Manufacturing. IEEE, 1993. http://dx.doi.org/10.1109/issm.1993.670304.

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Balic, Joze y Franci Cus. "CONTRIBUTION TO INTELLIGENT CAD/CAM SYSTEM". En Flexible Automation and Integrated Manufacturing 1999. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1999.140.

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Quintas, Antonio y Paulo Leitao. "A MANUFACTURING CELL CONTROLLER ARCHITECTURE". En Flexible Automation and Intelligent Manufacturing, 1997. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1997.460.

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Sormaz, Dusan. "MODELING OF MANUFACTURING ACTIVITIES FOR INTELLIGENT INFORMATION INTEGRATION". En Flexible Automation and Integrated Manufacturing 1999. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1999.530.

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Kale, M. S. y S. S. Pande. "INTELLIGENT SETUP GENERATION FOR AUTOMATED FIXTURE PLANNING". En Flexible Automation and Integrated Manufacturing 1998. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1998.500.

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Pande, S. S. y T. S. Suneel. "INTELLIGENT CNC TURNING USING ARTIFICIAL NEURAL NETWORKS". En Flexible Automation and Integrated Manufacturing 1998. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1998.530.

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Ulrich, Heinz y Willi Durig. "DESIGN AND REALIZATION OF INTELLIGENT AUTOMATED WORK-CELLS". En Flexible Automation and Intelligent Manufacturing, 1997. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1997.470.

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Sullivan, William G. "ECONOMIC VALUE ADDED BY MANUFACTURING FIRMS". En Flexible Automation and Intelligent Manufacturing, 1997. Connecticut: Begellhouse, 2023. http://dx.doi.org/10.1615/faim1997.50.

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Informes sobre el tema "Intelligent and Flexible Manufacturing"

1

Hollingsworth, Ethan. Intelligent Flexible Manufacturing Cell. Gaithersburg, MD: National Institute of Standards and Technology, 2023. http://dx.doi.org/10.6028/nist.gcr.23-046.

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Simpson, L. Trajectory Oriented and Fault Tolerant Based Intelligent Process Control for Flexible CIGS PV Module Manufacturing: Phase 1 Final Technical Report, March 2003. Office of Scientific and Technical Information (OSTI), febrero de 2004. http://dx.doi.org/10.2172/15006748.

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Simpson, L. Trajectory Oriented and Fault Tolerant Based Intelligent Process Control for Flexible CIGS PV Module Manufacturing Scale-Up: Phase II, Annual Technical Report, March 2004. Office of Scientific and Technical Information (OSTI), noviembre de 2004. http://dx.doi.org/10.2172/15011700.

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Simpson, L., J. Britt, R. Birkmire y T. Vincent. Trajectory-Oriented and Fault-Tolerant-Based Intelligent Process Control for Flexible CIGS PV Module Manufacturing; Final Technical Report, 13 May 2002--30 May 2005. Office of Scientific and Technical Information (OSTI), octubre de 2005. http://dx.doi.org/10.2172/15020505.

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Kaminski, Paul G. DOD Acquisition and Flexible Manufacturing. Fort Belvoir, VA: Defense Technical Information Center, marzo de 1996. http://dx.doi.org/10.21236/ada340350.

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Moran, Angela L. y Dawn R. White. Intelligent Processing for Spray Metal Manufacturing. Fort Belvoir, VA: Defense Technical Information Center, junio de 1990. http://dx.doi.org/10.21236/ada226499.

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Albus, J. S., H. A. Scott, E. Messina, H. M. Huang, A. J. Horst, J. L. Michaloski, T. R. Kramer et al. An intelligent systems architecture for manufacturing (ISAM):. Gaithersburg, MD: National Institute of Standards and Technology, 2002. http://dx.doi.org/10.6028/nist.ir.6771.

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Jacobs-Blecha, Charlotte, John J. Bartholdi, Donald D. Eisenstein, H. D. Ratliff y Richard Carey. Flexible Work Group Methods in Apparel Manufacturing. Fort Belvoir, VA: Defense Technical Information Center, abril de 1993. http://dx.doi.org/10.21236/ada268548.

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Darrow, William P. A survey of flexible manufacturing systems implementations. Gaithersburg, MD: National Bureau of Standards, 1986. http://dx.doi.org/10.6028/nbs.ir.86-3413.

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Lee, Myong S. Stimuli-Responsive Intelligent Nanomaterials Self-Assembled from Rigid Flexible Molecules. Fort Belvoir, VA: Defense Technical Information Center, noviembre de 2010. http://dx.doi.org/10.21236/ada532895.

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