Simulation of a Production Line with Automated Guided Vehicle: A Case Study

Currently, companies have increasingly needed to improve and develop their processes to flexible the production in order to reduce waiting times and increase productivity through smaller time intervals. To achieve these objectives, efficient and automated transport and handling material systems are required. Therefore, the AGV systems (Automated Guided Vehicle) are often used to optimize the flow of materials within the production systems. In this paper, the author evaluates the usage of an AGV system in an industrial environment and analyzes the advantages, disadvantages of the project. Furthermore, the author uses the systems simulation software Promodel® 7.0 to develop a model, based on data collected from real production system, in order to analyze and optimize the use of AGVs. Throughout this paper, problems are identified as well as solution adopted by the author and the results obtained from the simulations

Simulation in Automated Guided Vehicle System Design

The intense global competition that manufacturing companies face today results in an increase of product variety and shorter product life cycles. One response to this threat is agile manufacturing concepts. This requires materials handling systems that are agile and capable of reconfiguration. As competition in the world marketplace becomes increasingly customer-driven, manufacturing environments must be highly reconfigurable and responsive to accommodate product and process changes, with rigid, static automation systems giving way to more flexible types. Automated Guided Vehicle Systems (AGVS) have such capabilities and AGV functionality has been developed to improve flexibility and diminish the traditional disadvantages of AGV-systems. The AGV-system design is however a multi-faceted problem with a large number of design factors of which many are correlating and interdependent. Available methods and techniques exhibit problems in supporting the whole design process. A research review of the work reported on AGVS development in combination with simulation revealed that of 39 papers only four were industrially related. Most work was on the conceptual design phase, but little has been reported on the detailed simulation of AGVS. Semi-autonomous vehicles (SA V) are an innovative concept to overcome the problems of inflexible -systems and to improve materials handling functionality. The SA V concept introduces a higher degree of autonomy in industrial AGV -systems with the man-in-the-Ioop. The introduction of autonomy in industrial applications is approached by explicitly controlling the level of autonomy at different occasions. The SA V s are easy to program and easily reconfigurable regarding navigation systems and material handling equipment. Novel approaches to materials handling like the SA V -concept place new requirements on the AGVS development and the use of simulation as a part of the process. Traditional AGV -system simulation approaches do not fully meet these requirements and the improved functionality of AGVs is not used to its full power. There is a considerflble potential in shortening the AGV -system design-cycle, and thus the manufacturing system design-cycle, and still achieve more accurate solutions well suited for MRS tasks. Recent developments in simulation tools for manufacturing have improved production engineering development and the tools are being adopted more widely in industry. For the development of AGV -systems this has not fully been exploited. Previous research has focused on the conceptual part of the design process and many simulation approaches to AGV -system design lack in validity. In this thesis a methodology is proposed for the structured development of AGV -systems using simulation. Elements of this methodology address the development of novel functionality. The objective of the first research case of this research study was to identify factors for industrial AGV -system simulation. The second research case focuses on simulation in the design of Semi-autonomous vehicles, and the third case evaluates a simulation based design framework. This research study has advanced development by offering a framework for developing testing and evaluating AGV -systems, based on concurrent development using a virtual environment. The ability to exploit unique or novel features of AGVs based on a virtual environment improves the potential of AGV-systems considerably.University of Skovde. European Commission for funding the INCO/COPERNICUS Projec

Optimization of Automated Guided Vehicles (AGV) Fleet Size With Incorporation of Battery Management

An important aspect in manufacturing automation is material handling. To facilitate material handling, automated transport systems are implemented and employed. The AGV (automated guided vehicle) has become widely used for internal and external transport of materials. A critical aspect in the use of AGVs is determining the number of vehicles required for the system to meet the material handling requirements. Several models and simulations have been applied to determine the fleet size. Most of these models and simulations do not incorporate the battery usage of the vehicles and the effect it can have on the throughput and the number of AGVs required for the system. The goal of this research is to develop a simulation model to determine the optimized number of AGVs that is capable of increasing throughput while meeting the material handling requirements of the system. This model incorporates the battery management aspect and issues, which are usually omitted in AGV research. This includes the charging options and strategies, the number and location of charging stations, maintenance, and extended charging. The analysis entails studying various scenarios by applying different charging options and strategies and changing different parameters to achieve improved throughput and an optimized AGV fleet size. The results clearly show that battery management can have a significant effect on the average throughput and the AGV usage. It is important that the battery management of the AGVs is addressed adequately to run an AGV system efficiently

Autonomous guided vehicles applied to industrial engineering and management studies

This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge

A petri-net based methodology for modeling, simulation, and control of flexible manufacturing systems

Global competition has made it necessary for manufacturers to introduce such advanced technologies as flexible and agile manufacturing, intelligent automation, and computer-integrated manufacturing. However, the application extent of these technologies varies from industry to industry and has met various degrees of success. One critical barrier leading to successful implementation of advanced manufacturing systems is the ever-increasing complexity in their modeling, analysis, simulation, and control. The purpose of this work is to introduce a set of Petri net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs). More specifically, this work proposes Petri nets as an integrated tool for modeling, simulation, and control of flexible manufacturing systems (FMSs). The contributions of this work are multifold. First, it demonstrates a new application of PNs for simulation by evaluating the performance of pull and push diagrams in manufacturing systems. Second, it introduces a class of PNs, Augmented-timed Petri nets (ATPNs) in order to increase the power of PNs to simulate and control flexible systems with breakdowns. Third, it proposes a new class of PNs called Realtime Petri nets (RTPNs) for discrete event control of FMS s. The detailed comparison between RTPNs and traditional discrete event methods such as ladder logic diagrams is presented to answer the basic question \u27Why is a PN better tool than ladder logic diagram?\u27 and to justify the PN method. Also, a conversion procedure that automatically generates PN models from a given class of logic control specifications is presented. Finally, a methodology that uses PNs for the development of object-oriented control software is proposed. The present work extends the PN state-of-the-art in two ways. First, it offers a wide scope for engineers and managers who are responsible for the design and the implementation of modem manufacturing systems to evaluate Petri nets for applications in their work. Second, it further develops Petri net-based methods for discrete event control of manufacturing systems

Hybrid Machine Learning/Simulation Approaches for Logistic Systems Optimization

Hoje em dia, tem-se testemunhado um abrupto crescimento e desenvolvimento da indústria, refletido no elevado grau de complexidade e inteligência que os sistemas de produção correntes apresentam, onde se destacam os sistemas logísticos. Esta incessante procura pela inovação e melhoramento contínuo são muito recorrentes na época atual, traduzindo-se em constantes transformações no conceito da qualidade de um produto. Deste modo, emerge a necessidade em otimizar os layouts fabris conduzindo a um aumento da flexibilidade face aos seus comportamentos dinâmicos. Neste seguimento surge a imprescindibilidade de aprimoramento do comportamento do veículo autónomo associado, com vista a finalidades comuns como o aumento da produtividade e minimização de custos e lead times. Neste âmbito, esta dissertação, para além da implementação do modelo de simulação do sistema logístico, desenvolve numa fase inicial comportamentos elementares a aplicar ao veículo, implementadas no próprio ambiente de simulação. Posteriormente, dado que a área de Machine Learning tem obtido tanto sucesso noutras áreas tecnológicas, surgiu o desafio da introdução do conceito de rede neuronal, através da criação de uma nova entidade designada Agente e caraterizada pela técnica de aprendizagem baseada em Reinforcement Learning. Por fim, nesta dissertação, para além de se concluir que a abordagem baseada em Reinforcement Learning proporcionou os melhores resultados de produtividade, retiraram-se ainda conclusões no que à robustez destes modelos diz respeito, a fim de avaliar a sua flexibilidade quando sujeitos a diferentes contextos, simulando um ambiente real.Nowadays, we have been witnessing an abrupt growth and development of the industry, reflected in the high level of complexity and intelligence that the current production systems present, in which the logistics systems stand out. This incessant search for innovation and continuous improvement are very common today, reproducing into constant changes in the product quality concept. In this sense, the need to optimize the factory layouts emerges, leading to an increase in flexibility because of their dynamic behaviours. In this segment, there is an essential need to improve the behaviour of the associated autonomous vehicle, to reach common objectives such as increasing the productivity and minimizing costs and lead times. In this context, this dissertation, beyond the implementation of the simulation model of the logistics system, develops, in an initial phase, elementary behaviours to be applied to the vehicle, implemented in the simulation environment itself. Subsequently, given that the Machine Learning area has been so successful in other technological areas, the challenge of introducing the concept of the neural network appears, through the creation of a new entity called Agent and characterized by the Reinforcement Learning technique. Finally, in this dissertation, in addition to concluding that the Reinforcement Learning-based approach provided the best productivity results, conclusions were also drawn regarding the robustness of these models, in order to assess their flexibility when subject to different contexts, simulating a real environment

Three essays on the battery management of automated guided vehicles

This dissertation explores battery management for automated guided vehicles (AGVs). AGVs are driver-less vehicles that usually run on batteries. According to Le-Anh and De Koster (2006), battery management of AGVs deals with the issues like how long a particular AGV will operate before its battery is recharged or replaced, capacity of the battery stations, location of the battery stations, availability of idle time for the AGVs etc. Literature on AGV systems generally ignores battery management assuming that the effect of battery management is negligible. However, there have been few studies showing that battery management can play an important role for the overall performance of an AGV system. As the competition in the business world grows, firms need to find new and innovative ways to improve their performance. In that case, battery management has the potential to be a source of competitive advantage for a firm that uses AGVs. The main reason of selecting the battery management of AGVs as the topic of this dissertation is to help enhance the literature of this topic. To fulfill that objective, this dissertation has been designed as a three-paper model so that three different attributes of battery management can be addressed extensively. Each of the three papers represents a chapter in this dissertation (i.e., chapter 2, chapter 3, and chapter 4). Chapter 2 (i.e., the first paper) is mainly based on literature review. The literature review has been augmented by the information gathered from practitioners. The purpose of chapter 2 is to have a better understanding of the battery management of AGVs and to explore common themes among different dimensions of battery management. Chapter 3 (i.e., the second paper) explores the possibility of increasing manufacturing flexibility through battery management of AGVs. This chapter shows how a firm can use battery management to meet an unexpected increase in demand for the short run. Chapter 4 (i.e., the third paper) compares and contrasts different routing techniques for battery management in order to investigate how such routing techniques can affect the productivity of an AGV system

Modelling flexible manufacturing systems through discrete event simulation

As customisation and product diversification are becoming standard, industry is looking for strategies to become more adaptable in responding to customer’s needs. Flexible manufacturing systems (FMS) provide a unique capability where there is a need to provide efficiency through production flexibility. Full potential of FMS development is difficult to achieve due to the variability of components within this complex manufacturing system. It has been recognised that there is a requirement for decision support tools to address different aspects of FMS development. Discrete event simulation (DES) is the most common tool used in manufacturing sector for solving complex problems. Through systematic literature review, the need for a conceptual framework for decision support in FMS using DES has been identified. Within this thesis, the conceptual framework (CF) for decision support for FMS using DES has been proposed. The CF is designed based on decision-making areas identified for FMS development in literature and through industry stakeholder feedback: set-up, flexibility and schedule configuration. The CF has been validated through four industrial simulation case studies developed as a part of implementation of a new FMS plant in automotive sector. The research focuses on: (1) a method for primary data collection for simulation validated through a case study of material handling robot behaviour in FMS; (2) an approach for evaluation of optimal production set-up for industrial FMS with DES; (3) a DES based approach for testing FMS flexibility levels; (4) an approach for testing scheduling in FMS with the use of DES. The study has supported the development of systematic approach for decision making in FMS development using DES. The approach provided tools for evidence based decision making in FMS