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

On-site installation flexibility for disruption management in modular off-site construction systems

Modular off-site construction is one of the methods adopted by the construction industry in a recent drive to modernise its operations and increase its productivity. Operations that were traditionally performed on-site are instead completed at an off-site factory, with finished modules then being transported on-site for installation. Operating across two locations in this way can provide numerous gains in speed, quality, and costs. However, it does mean that construction companies must now understand and manage a new and wider range of potential disruptions to their operations. This thesis is concerned with addressing disruptions that delay the delivery of modules to site. To identify operational disruptions and their corresponding disruption management strategies, an exploratory study was performed consisting of five case studies and an industrial workshop. An over-reliance on storing modules as a means of coping with disruptions was uncovered. Construction sites typically follow a fixed module installation sequence because of on-site installation constraints. As such, when delivery of a module is delayed, subsequent modules in the sequence must be stored until the delayed module arrives for installation. As the industry expands towards manufacturing larger projects at higher production rates, storage may become a less viable disruption management strategy given the lack of storage space, particularly in urban areas. To overcome these challenges, a novel disruption management strategy is proposed and evaluated: on-site installation flexibility. There are four types: vertical assignment flexibility, lateral assignment flexibility, vertical sequence flexibility, and lateral sequence flexibility. Each type relaxes one of the on-site installation constraints, thereby allowing completed modules to continue to be installed in the event of a module being disrupted. Several conclusions were drawn from studying on-site installation flexibility as a disruption management strategy. Implementation roadmaps developed during a workshop using an Impact Matrix Cross-Reference Multiplication Applied to a Classification analysis and Interpretive Structural Modelling revealed that implementing on-site installation flexibility requires coordination and many changes across a range of organisational functions. A Discrete Event Simulation model developed and applied to a case study showed that on-site installation flexibility can reduce installation delay and storage requirements. Furthermore, combining more than one type of on-site installation flexibility can significantly improve system performance. However, greater co-ordination effort would be required to control module installation operations. Finally, a Simulation-Based Optimisation model was formulated and applied to a second case study and showed that investing in a combination of on-site installation flexibilities in conjunction with other disruption management options can achieve cost savings. Hence, on-site installation flexibility was demonstrated to be a promising disruption management strategy for modular off-site construction systems

Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality

Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants

Evolutionary Algorithms and Simulation for Intelligent Autonomous Vehicles in Container Terminals

The study of applying soft computing techniques, such as evolutionary computation and simulation, to the deployment of intelligent autonomous vehicles (IAVs) in container terminals is the focus of this thesis. IAVs are a new type of intelligent vehicles designed for transportation of containers in container terminals. This thesis for the first time investigates how IAVs can be effectively accommodated in container terminals and how much the performance of container terminals can be improved when IAVs are being used. In an attempt to answer the above research questions, the thesis makes the following contributions: First, the thesis studies the fleet sizing problem in container terminals, an important design problem in container terminals. The contributions include proposing a novel evolutionary algorithm (with superior results to the state-of-the-art CPLEX solver), combining the proposed evolutionary algorithm with Monte Carlo simulation to take into account uncertainties, validating results of the uncertain case with a high fidelity simulation, proposing different robustness measures, comparing different robust solutions and proposing a dynamic sampling technique to improve the performance of the proposed evolutionary algorithm. Second, the thesis studies the impact of IAVs on container terminals’ performance and total cost, which are very important criteria in port equipment. The contributions include developing simulation models using realistic data (it is for the first time that the impact of IAVs on containers terminals is investigated using simulation models) and applying a cost model to the results of the simulation to estimate and compare the total cost of the case study with IAVs against existing trucks. Third, the thesis proposes a new framework for the simulations of container terminals. The contributions include developing a flexible simulation framework, providing a user library for users to create 3D simulation models using drag-and-drop features, and allowing users to easily incorporate their optimisation algorithms into their simulations

Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions

Purpose-Although the value of AI has been acknowledged by companies, the literature shows challenges concerning AI-enabled B2B marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation. Design/methodology/approach-Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021. Findings-Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identified the main trends in the literature, and suggest directions for future research. Practical implications-Through our identified five domains, practitioners can assess their current use of AI ability in terms of their conceptualisation capability, technological applications, and identify their future needs in the relevant domains in order to make appropriate decisions on whether to invest in AI. Thus, the research outcomes can help companies to realise their digital marketing innovation strategy through AI. Originality/value-While more and more studies acknowledge the potential value of AI in B2B marketing, few attempts have been made to synthesise the literature. The results from the study can contribute by 1) obtaining and comparing the most influential works based on a series of analyses; 2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation; and 3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field