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

Maintenance modelling of complex automated guided vehicle systems

Automated guided vehicles (AGV’s) have been adopted in many industrial applications since their introduction in the 1950’s. Although still primarily used for the movement of materials around manufacturing facilities and warehouses they are also used in such applications as hospitals and transportation. Such driverless vehicles generally travel along a predefined route performing set tasks and they have been widely adopted due to their efficiency and economic benefits, Le-Anh and De Koster (2006). The availability of the vehicles is crucial to ensure that these benefits are maintained. As the complexity of industrial processes increases and fleets of AGV’s are commonly employed, maintenance and reliability issues are of increasing concern. In order to ensure that the benefits of AGV’s are utilised efficiently it is crucial that efficient maintenance strategies are employed. Hence in this work research has been undertaken into determining the optimal maintenance strategy for a complex multi AGV system. Typically a multi AGV system will consist of a number of vehicles that travel along the same route performing required tasks. Once any AGV fails it should be removed from the route as quickly as possible in order to prevent obstructing other AGV’s. In this work Coloured Petri Nets (CPN) and Genetic Algorithms are used in combination in order to determine the optimal maintenance strategy. From the research conducted it is found that the maintenance strategies adopted and the location of the maintenance site are significant factors impacting on the efficiency, cost, and productivity of a multi-AGV system

Reliability modelling of automated guided vehicles using Petri nets

Automated guided vehicles (AGVs) are being extensively used due to their attributions of high efficiency and low costs. To assure their added value, taking a typical AGV transport system as an example, the reliability issues in AGVs are investigated in this paper. First of all, the AGV transport system was mod-elled as a phased mission that comprises a few key phases. Then, the Petri net (PN) method is applied to describe the logic of the whole phase mission and based on this, the reliability of the mission is assessed via Monte-Carlo simulation. In order to validate the reliability assessment result by the PN method, the theoretical reliability of the AGV system is also assessed through performing fault tree analysis (FTA). The comparison indicates that both methods give very similar results. Thus, it can be concluded that apart from FTA, the PNs method is also a reliable tool for AGV system reliability assessment

Optimising the maintenance strategy for a multi-AGV system using genetic algorithms

Automated Guided Vehicles (AGVs) are playing increasingly vital roles in a variety of applications in modern society, such as intelligent transportation in warehouses and material distribution in automated production lines. They improve production efficiency, save labour cost, and bring significant economic benefit to end users. However, to utilise these potential benefits is highly dependent on the reliability and availability of the AGVs. In other words, an effective maintenance strategy is critical in the application of AGVs. The research activity reported in this paper is to realise an effective maintenance strategy for a multi-AGV system by the approach of Genetic Algorithms (GA). To facilitate the research, an automated material distribution system consisting of three AGVs is considered in this paper for methodology development. The movement of every AGV in the multi-AGV system, and the corrective and periodic preventive maintenances of failed AGVs are modelled using the approach of Coloured Petri Nets (CPNs). Then, a GA is adopted for optimising the maintenance and associated design and operation of the multi-AGV system. From this research, it is disclosed that both the location selection of the maintenance site and the maintenance strategies that are adopted for AGV maintenance have significant influences on the efficiency, cost, and productivity of a multi-AGV system

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

Reliability modelling of automated guided vehicles by fault tree analysis

Automated guided vehicles (AGVs) are being increasingly used for intelligent transportation and distribution of materials in warehouses and auto-production lines. In this paper, a preliminary hazard analysis of an AGV’s critical components is conducted by the approach of Failure Modes and Effects Criticality Analysis (FMECA). To implement this research, a particular AGV transport system is modelled as a phased mission. Then, Fault tree analysis (FTA) is adopted to model the causes of phase failure, enabling the probability of success in each phase and hence mission success to be determined. Through this research, a promising technical approach is established, allowing us to identify the critical AGV components and the crucial mission phases of AGVs at the design stage

Study of the resilience of nuclear power plants in response to climate change

In recent years, it has become even more challenging to ensure the safety of nuclear power plants due to accelerated climate change. This is because some existing safety systems in the plants are not able to cope with new issues introduced or aggravated by climate change. In response to this need, this paper will analyze the present related reactor safety systems and propose and discuss a measure that can potentially improve the resilience of the reactor system to climate change. To facilitate the research, the intake structure blockage caused by the outbreak of a kind of marine organism whose size varies from 4mm to 40mm, is chosen as a case study. The study will consider the ability of the system to anticipate for the events, absorb the impact of the events to the system, and recover from perturbations. To facilitate the research, a mathematical model will be developed using Petri nets to simulate the reliability and health states of the related safety systems, the occurrence of disruptive events, the corresponding responses of the nuclear system, and the possible operation states and recovery of the system from the disruptive events. The results indicated that the intake structure blockage caused by such external events cannot be ignored. The research is expected lay a solid foundation for future nuclear power system design and the resilience assessment of nuclear reactor systems

Resilience assessment for nuclear power plants using Petri nets

Since the resilience issues encountered in nuclear power plants (NPPs) has not been explicitly addressed to date, Petri net models are developed in this paper to simulate the health states of relevant facilities, immediate responses, mitigation processes, and recovery and maintenance processes in an NPP. With the aid of the models developed, the resilience of the NPP is assessed with the consideration of the influence of ageing and the impact of external events. To demonstrate the methodology developed, it is applied to assess the resilience of a single-unit pressurised heavy-water reactor system to a station blackout accident. It has been shown that the methodology developed is effective in simulating and assessing the resilience of the NPP. It is also found that the ageing and proper maintenance of facilities that do not directly affect the operation of nuclear reactors are critical to the resilience of NPPs. </p

Improving the strategy of maintaining offshore wind turbines through petri net modelling

In order to improve the operation and maintenance (O&M) of offshore wind turbines, a new Petri net (PN)-based offshore wind turbine maintenance model is developed in this paper to simulate the O&M activities in an offshore wind farm. With the aid of the PN model developed, three new potential wind turbine maintenance strategies are studied. They are (1) carrying out periodic maintenance of the wind turbine components at different frequencies according to their specific reliability features; (2) conducting a full inspection of the entire wind turbine system following a major repair; and (3) equipping the wind turbine with a condition monitoring system (CMS) that has powerful fault detection capability. From the research results, it is found that periodic maintenance is essential, but in order to ensure that the turbine is operated economically, this maintenance needs to be carried out at an optimal frequency. Conducting a full inspection of the entire wind turbine system following a major repair enables efficient utilisation of the maintenance resources. If periodic maintenance is performed infrequently, this measure leads to less unexpected shutdowns, lower downtime, and lower maintenance costs. It has been shown that to install the wind turbine with a CMS is helpful to relieve the burden of periodic maintenance. Moreover, the higher the quality of the CMS, the more the downtime and maintenance costs can be reduced. However, the cost of the CMS needs to be considered, as a high cost may make the operation of the offshore wind turbine uneconomical

Petri net modelling for achieving an optimal design of a wind turbine condition monitoring system

Condition monitoring has demonstrated its effectiveness in improving the economic return of wind turbines. However, a wind turbine consists of hundreds, even thousands, of mechanical, electrical and power electronic components. The failure of any one of them may lead to the shutdown of the turbine. For this reason, a variety of component monitoring systems have been developed dedicated to monitoring these different components. Consequently, a wind turbine usually needs to be monitored simultaneously by several different types of component monitoring systems that benefit wind turbine operation and maintenance to different extents. This not only increases the complexity of the hardware configuration but also increases the costs of the entire condition monitoring system. How to achieve a condition monitoring system that can monitor the most vulnerable components whilst bringing the most economic benefit to the wind turbine operator is an important question. The aim of this paper is to answer such a question with the aid of the Petri net modelling method. The model developed in the paper will investigate the influences of condition monitoring systems and fault detection using wind farm Supervisory Control and Data Acquisition (SCADA) system on the economic return of wind turbines, thereby providing a feasible tool for constructing an optimal wind turbine condition monitoring system