Novel methodology for optimising the design, operation and maintenance of a multi-AGV system

Automated guided vehicles (AGVs) have long been identified as a potential driver to improve system efficiency and lower labour costs in material handling systems. Accordingly, the reliability and availability of AGV systems is crucial to assure the stability and efficiency of these systems. However, the reliability issues and maintenance strategies of AGVs have not previously been studied sufficiently. This is even more marked in the case of multi-AGV systems that consist of fleets of AGVs. To fill this knowledge gap, research is conducted considering a multi-AGV system, consisting of three AGVs, in order to develop a scientific methodology for optimising the layout design, operation and maintenance of a multi-AGV system. Once an AGV is failed, it will be towed to the maintenance site for repair by a recycle vehicle to prevent deadlock and conflict. The efficiency of the recycling process of failed AGVs in a multi-AGV system, with respect to the change of location of the maintenance site, is analysed by the approach of coloured Petri nets (CPNs). A CPN model simulating the corrective and periodic preventive maintenance processes of failed AGVs is also developed in order to investigate the impact of different AGV maintenance strategies on the operation efficiency of the multi-AGV system. The simulation results obtained clearly show that the location of maintenance sites and maintenance strategies do have significant influence on the performance of a multi-AGV system, where corrective maintenance is an effective measure to maintain the long-term reliability and stability of the system

Monte Carlo Simulation to Compare Markovian and Neural Network Models for Reliability Assessment in Multiple AGV Manufacturing System

We compare two approaches for a Markovian model in flexible manufacturing systems (FMSs) using Monte Carlo simulation. The model which is a development of Fazlollahtabar and Saidi-Mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (AGV) namely, the reliability of machines and the reliability of AGVs in a multiple AGV jobshop manufacturing system. The current methods for modeling reliability of a system involve determination of system state probabilities and transition states. Since, the failure of the machines and AGVs could be considered in different states, therefore a Markovian model is proposed for reliability assessment. The traditional Markovian computation is compared with a neural network methodology. Monte Carlo simulation has verified the neural network method having better performance for Markovian computations.We compare two approaches for a Markovian model in flexible manufacturing systems (FMSs) using Monte Carlo simulation. The model which is a development of Fazlollahtabar and Saidi-Mehrabad (2013), considers two features of automated flexible manufacturing systems equipped with automated guided vehicle (AGV) namely, the reliability of machines and the reliability of AGVs in a multiple AGV jobshop manufacturing system. The current methods for modeling reliability of a system involve determination of system state probabilities and transition states. Since, the failure of the machines and AGVs could be considered in different states, therefore a Markovian model is proposed for reliability assessment

Diseño e implantación de una línea de AGVs

El estudio que a lo largo de este trabajo se presenta se enfoca en la modificación y puesta a punto de un circuito de vehículos de guiado automático (AGV) que se emplea para el transporte de piezas en el interior de una fábrica. Se partió de un circuito instalado al que se deseaba mejorar sus condiciones tanto de apariencia como de funcionalidad. Como estudio final, se evaluará la repercusión que la modificación llevada a cabo ha supuesto respecto al estado inicial.Departamento de Tecnología ElectrónicaMáster en Ingeniería Industria

Agent-based material transportation scheduling of AGV systems and its manufacturing applications

制度:新 ; 報告番号:甲3743号 ; 学位の種類:博士(工学) ; 授与年月日:2012/9/10 ; 早大学位記番号:新6114Waseda Universit

Supporting the design of automated guided vehicle systems in internal logistics

Applications of automated guided vehicle (AGV) systems are becoming increasingly widespread in internal logistics for performing transports automatically. Recent technological advancements in navigation and intelligence have improved the functionality of vehicles and together with attention to Industry 4.0 have created further interest in AGV systems in industry and academia. Research on AGV systems has mainly focused on technical aspects, but to support AGV system design and, thereby, be able to achieve the full potential from use of AGV systems in internal logistics, more knowledge is needed that takes further into consideration aspects related to humans and the organisation, alongside the technical aspects. The purpose of this thesis is to develop knowledge to support the design of AGV systems and three research questions are formulated. The thesis is based on three papers, two of which are based on multiple case studies and one study based on simulation modelling. The thesis results provide input to the design process for AGV systems in three main ways. First, in developing an understanding for which requirements influence an AGV systems and how the requirements can be met in the AGV system configuration. Second, regarding how the load capacity of AGVs impact the performance of the AGV system, and third by identifying challenges with respect to the work organisation and related to human factors when AGV systems are introduced in internal logistics settings

Enhancing the performance of automated guided vehicles through reliability, operation and maintenance assessment

Automated guided vehicles (AGVs), a type of unmanned moving robots that move along fixed routes or are directed by laser navigation systems, are increasingly used in modern society to improve efficiency and lower the cost of production. A fleet of AGVs operate together to form a fully automatic transport system, which is known as an AGV system. To date, their added value in efficiency improvement and cost reduction has been sufficiently explored via conducting in-depth research on route optimisation, system layout configuration, and traffic control. However, their safe application has not received sufficient attention although the failure of AGVs may significantly impact the operation and efficiency of the entire system. This issue becomes more markable today particularly in the light of the fact that the size of AGV systems is becoming much larger and their operating environment is becoming more complex than ever before. This motivates the research into AGV reliability, availability and maintenance issues in this thesis, which aims to answer the following four fundamental questions: (1) How could AGVs fail? (2) How is the reliability of individual AGVs in the system assessed? (3) How does a failed AGV affect the operation of the other AGVs and the performance of the whole system? (4) How can an optimal maintenance strategy for AGV systems be achieved? In order to answer these questions, the method for identifying the critical subsystems and actions of AGVs is studied first in this thesis. Then based on the research results, mathematical models are developed in Python to simulate AGV systems and assess their performance in different scenarios. In the research of this thesis, Failure Mode, Effects and Criticality Analysis (FMECA) was adopted first to analyse the failure modes and effects of individual AGV subsystems. The interactions of these subsystems were studied via performing Fault Tree Analysis (FTA). Then, a mathematical model was developed to simulate the operation of a single AGV with the aid of Petri Nets (PNs). Since most existing AGV systems in modern industries and warehouses consist of multiple AGVs that operate synchronously to perform specific tasks, it is necessary to investigate the interactions between different AGVs in the same system. To facilitate the research of multi-AGV systems, the model of a three-AGV system with unidirectional paths was considered. In the model, an advanced concept PN, namely Coloured Petri Net (CPN), was creatively used to describe the movements of the AGVs. Attributing to the application of CPN, not only the movements of the AGVs but also the various operation and maintenance activities of the AGV systems (for example, item delivery, corrective maintenance, periodic maintenance, etc.) can be readily simulated. Such a unique technique provides us with an effective tool to investigate larger-scale AGV systems. To investigate the reliability, efficiency and maintenance of dynamic AGV systems which consist of multiple single-load and multi-load AGVs traveling along different bidirectional routes in different missions, an AGV system consisting of 9 stations was simulated using the CPN methods. Moreover, the automatic recycling of failed AGVs is studied as well in order to further reduce human participation in the operation of AGV systems. Finally, the simulation results were used to optimise the design, operation and maintenance of multi-AGV systems with the consideration of the throughputs and corresponding costs of them.The research reported in this thesis contributes to the design, reliability, operation, and maintenance of large-scale AGV systems in the modern and rapidly changing world.</div

Technological innovation for digital supply chains within small and medium size manufacturing enterprises

The rapidly growing world of digitalisation opens the doorway for the new era of automation that plays a crucial role within the industry. Furthermore, technological innovations that are emerging every day are disrupting traditional business processes especially within small and medium size manufacturing enterprises (SMEs). The current industrial revolution pioneer for profit maximisation with cost reduction shows a significant refinement in improving sustainability that drives forward digitalisation. Evidence shows that industries have identified digitalisation as a priority in the upcoming years as the global supply chain is equipping itself with the digital world in the current industrial revolution. Economic growth is dependent on SMEs around the world where small and medium size Manufacturing Enterprises (SMMEs) play a vital role in the current competitive world while they are not able to manage their supply chains effectively and efficiently due to a lack of optimisation of digitalisation. They identify that technological innovation is evident for transforming themselves with digital supply chain, while global market leading organisations are positioning themselves with the world of digitalisation to their end consumers in their supply chain utilising technological innovation virtually driving towards a new era of a digital ecosystem. This research aims to investigate the impact of technological innovation to foster and promote digital supply chain within SMMEs. Due to the exploratory nature, this study adopted a case study approach where the data is collected using a semi-structured interview across 4 cases from three various countries. The findings indicate a lack of framework for the digitalisation of supply chains within SMMEs, in addition to a lack of technological innovation and financial constraints that served as limiting factors for digitalisation of supply chain within organisations. Further, a framework has been developed consisting of five elements that have been identified from empirical data as being critical for Digital Supply Chain (DSC) transformation. The theoretical contributions of this research are the identification of problems faced, limitations of technological innovation, and an improved understanding of how digital supply chain transformation can be initiated and achieved in the context of SMMEs. The practical contribution of this study is imbedded in the developed framework in the form of recommended strategies for SMMEs for digitalisation of supply chain