Otomatikleştirilmiş rehberli araç sistemlerinin transport tekniğinde modellemesi

The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature.Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir

Modeling Automated Guided Vehicle Systems in Material Handling

Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

Modeling Automated Guided Vehicle Systems in Material Handling

Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

Control of free-ranging automated guided vehicles in container terminals

Container terminal automation has come to the fore during the last 20 years to improve their efficiency. Whereas a high level of automation has already been achieved in vertical handling operations (stacking cranes), horizontal container transport still has disincentives to the adoption of automated guided vehicles (AGVs) due to a high degree of operational complexity of vehicles. This feature has led to the employment of simple AGV control techniques while hindering the vehicles to utilise their maximum operational capability. In AGV dispatching, vehicles cannot amend ongoing delivery assignments although they have yet to receive the corresponding containers. Therefore, better AGV allocation plans would be discarded that can only be achieved by task reassignment. Also, because of the adoption of predetermined guide paths, AGVs are forced to deploy a highly limited range of their movement abilities while increasing required travel distances for handling container delivery jobs. To handle the two main issues, an AGV dispatching model and a fleet trajectory planning algorithm are proposed. The dispatcher achieves job assignment flexibility by allowing AGVs towards to container origins to abandon their current duty and receive new tasks. The trajectory planner advances Dubins curves to suggest diverse optional paths per origin-destination pair. It also amends vehicular acceleration rates for resolving conflicts between AGVs. In both of the models, the framework of simulated annealing was applied to resolve inherent time complexity. To test and evaluate the sophisticated AGV control models for vehicle dispatching and fleet trajectory planning, a bespoke simulation model is also proposed. A series of simulation tests were performed based on a real container terminal with several performance indicators, and it is identified that the presented dispatcher outperforms conventional vehicle dispatching heuristics in AGV arrival delay time and setup travel time, and the fleet trajectory planner can suggest shorter paths than the corresponding Manhattan distances, especially with fewer AGVs.Open Acces

Automatic programming of simulation models

The concepts of software engineering were used to improve the simulation modeling environment. Emphasis was placed on the application of an element of rapid prototyping, or automatic programming, to assist the modeler define the problem specification. Then, once the problem specification has been defined, an automatic code generator is used to write the simulation code. The following two domains were selected for evaluating the concepts of software engineering for discrete event simulation: manufacturing domain and a spacecraft countdown network sequence. The specific tasks were to: (1) define the software requirements for a graphical user interface to the Automatic Manufacturing Programming System (AMPS) system; (2) develop a graphical user interface for AMPS; and (3) compare the AMPS graphical interface with the AMPS interactive user interface

Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation

Autonomous guided vehicles (AGVs) are driverless material handling systems used for transportation of pallets and line side supply of materials to provide flexibility and agility in shop-floor logistics. Scheduling of shop-floor logistics in such systems is a challenging task due to their complex nature associated with the multiple part types and alternate material transfer routings. This paper presents a decision support system capable of supporting shop-floor decision-making activities during the event of manufacturing disruptions by automatically adjusting both AGV and machine schedules in Flexible Manufacturing Systems (FMSs). The proposed system uses discrete event simulation (DES) models enhanced by the Internet-of-Things (IoT) enabled digital integration and employs a nonlinear mixed integer programming Genetic Algorithm (GA) to find near-optimal production schedules prioritising the just-in-time (JIT) material delivery performance and energy efficiency of the material transportation. The performance of the proposed system is tested on the Integrated Manufacturing and Logistics (IML) demonstrator at WMG, University of Warwick. The results showed that the developed system can find the near-optimal solutions for production schedules subjected to production anomalies in a negligible time, thereby supporting shop-floor decision-making activities effectively and rapidly