Approaching simulation to modelers: a user interface for large-scale demographic simulation

Extended version / Versió extesaAgent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models such as policy studies, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.Postprint (author's final draft

On the Selection of Simulation Software for Manufacturing Application

The growing complexity of manufacturing along with the need for higher efficiency, greater flexibility, better product quality and lower cost urged the use of simulation in manufacturing systems. The number and variety of simulation software packages on the market increased as well. Consequently, the varieties of these packages led to some bewilderment on the part of potential users when faced the selection process. The present article addresses an overview of material addressed in journals, conferences, and textbooks on the selection of appropriate simulation software. It also suggests a classification of main criteria to be considered in evaluating simulation software packages. Moreover, a checklist of simulation software features with five levels of indication will be included. A proposed methodology has been employed in interpreting the checklist. Finally, future trends towards the provision of more effective selection tools will be discussed

Experimental evaluation of user performance on two-dimensional and three-dimensional perspective displays in discrete-event simulation

Several experiments were carried out to compare the impacts of using a two dimensional (2D) plan view or a three dimensional (3D) perspective view in discrete event simulation visual displays. The experiments measured the performance of participants in spotting errors, describing the model, and suggesting improvements to the system. The participants using the 3D perspective display performed much better in spotting errors, taking on average about one third of the time of participants observing the 2D display. They also did much better in describing the model. There was no significant difference in suggesting improvements although this may have been because this task was easy. Most participants preferred the 3D perspective view when asked to compare the displays. The experiments indicate that the detailed design of the visual display may have a considerable effect on some of the tasks in a simulation project and hence on whether the overall project is successful

Framework for selecting manufacturing simulation software in industry 4.0 environment

Even though the use of simulation software packages is widespread in industrial and manufacturing companies, the criteria and methods proposed in the scientific literature to evaluate them do not adequately help companies in identifying a package able to enhance the efficiency of their production system. Hence, the main objective of this paper is to develop a framework to guide companies in choosing the most suitable manufacturing simulation software package. The evaluation framework developed in this study is based on two different multi-criteria methods: analytic hierarchy process (AHP) integrated with benefits, opportunities, costs, risks (BOCR) analysis and the best-worst method (BWM). The framework was developed on the basis of the suggestions from the literature and from a panel of experts, both from academia and industry, trying to capture all the facets of the software selection problem. For testing purposes, the proposed approach was applied to a mid-sized enterprise located in the south of Italy, which was facing the problem of buying an effective simulation software for Participatory Design. From a practical perspective, the application showed that the framework is effective in identifying the most suitable simulation software package according to the needs of the company. From a theoretical point of view, the multi-criteria methods suggested in the framework have never been applied to the problem of selecting simulation software; their usage in this context could bring some advantages compared to other decision-making tools

Intelligent shop scheduling for semiconductor manufacturing

Semiconductor market sales have expanded massively to more than 200 billion dollars annually accompanied by increased pressure on the manufacturers to provide higher quality products at lower cost to remain competitive. Scheduling of semiconductor manufacturing is one of the keys to increasing productivity, however the complexity of manufacturing high capacity semiconductor devices and the cost considerations mean that it is impossible to experiment within the facility. There is an immense need for effective decision support models, characterizing and analyzing the manufacturing process, allowing the effect of changes in the production environment to be predicted in order to increase utilization and enhance system performance. Although many simulation models have been developed within semiconductor manufacturing very little research on the simulation of the photolithography process has been reported even though semiconductor manufacturers have recognized that the scheduling of photolithography is one of the most important and challenging tasks due to complex nature of the process. Traditional scheduling techniques and existing approaches show some benefits for solving small and medium sized, straightforward scheduling problems. However, they have had limited success in solving complex scheduling problems with stochastic elements in an economic timeframe. This thesis presents a new methodology combining advanced solution approaches such as simulation, artificial intelligence, system modeling and Taguchi methods, to schedule a photolithography toolset. A new structured approach was developed to effectively support building the simulation models. A single tool and complete toolset model were developed using this approach and shown to have less than 4% deviation from actual production values. The use of an intelligent scheduling agent for the toolset model shows an average of 15% improvement in simulated throughput time and is currently in use for scheduling the photolithography toolset in a manufacturing plant

Learnability makes things click : a grounded theory approach to the software product evaluation

The aim of this doctoral dissertation is to investigate the phenomenon of learnability more deeply in order to better understand the learnability process. Grounded theory was used to determine the ground concepts based on fifteen users’ (N=15) actions (N=1836) in the WebCT Campus Edition’s virtual environment. Based on this study, the phenomenon of learnability and the learnability process is understood in greater detail and defined from the human centric of view, where the human being is the key actor. This doctoral dissertation answers the following research problem: 1. How learnable is the WebCT Campus Edition’s virtual environment? 2. How can the phenomenon of learnability be defined in a new way? The WebCT Campus Edition virtual environment’s learnability was measured with performance time and directions of action. In addition, the traditional learnability metrics of performance time and direction of users’ actions was used to verify the theoretical model of learnability and its nonlinearity. The result of this study showed that the variety of the WebCT Campus Edition’s learnability was higher between the individual users than it was between the different tasks. Therefore, the variety of task difficulty, i.e. the complexity or easiness of the different part of the user interface, have less influence on learnability in the WebCT Campus Edition than do the individual users’characteristics. Thus, the research results confirm the results found in earlier studies, where two important issues for usability evaluation and therefore evaluation on learnability, are the tasks and users individual characteristics. The theoretical model of learnability with following phases of information search, data collection, knowledge management, knowledge form, knowledge build and the result of action were determined from data. The theoretical model of learnability and its main patterns of a) data collection-information search, b)knowledge build-knowledge form and c) information searchknowledge management proves that learnability is a non-linear process. Therefore, the phenomenon of learnability cannot purely be defined by the separate properties of learnability, i.e. the properties of a user interface and a progressively enhanced linear process illustrated with learning curves. The theoretical model of learnability is one of the rare models of learnability that is based on empirical data. The use of grounded theory methodology means that the phenomenon of learnability is studied through tacit knowledge, i.e. through users’ real actions and though explicit knowledge, the users cognitive processes during interaction i.e. the phenomenon of learnability is approached from the holistic point of view, where the phenomenon of learnability is seen as one holistic process. Thus triangulation, where the phenomenon is interpreted through several split case studies are therefore unnecessary in this research setting. In conclusion, too many studies are still conducted in a laboratory situation using traditional methodological paradigms. More learnability studies with new methodological approaches in the natural environments are needed were the human, learning and non-linear process of learnability are in focus. It is important to understand more deeply the process of learnability and investigate more in greater detail the key elements that enhance learnability and on the other hand, cause learnability problems for users. Finally, based on the theoretical models of learnability, we can develop tools for the commercial user interface world in order to measure and test the learnability process more precisely and better understand how skills are actually learnt and how “to click” learnability

The Impact of the User Interface on Simulation Usability and Solution Quality

This research outlines a study that was performed to determine the effects of user interface design variations on the usability and solution quality of complex, multivariate discrete-event simulations. Specifically, this study examined four key research questions: what are the user interface considerations for a given simulation model, what are the current best practices in user interface design for simulations, how is usability best evaluated for simulation interfaces, and specifically what are the measured effects of varying levels of usability of interface elements on simulation operations such as data entry and solution analysis. The overall goal of the study was to show the benefit of applied usability practices in simulation design, supported by experimental evidence from testing two alternative simulation user interfaces designed with varying usability. The study employed directed research in usability and simulation design to support design of an experiment that addressed the core problem of interface effects on simulation. In keeping with the study goal of demonstrating usability practices, the experimental procedures were analogous to the development processes recommended in supporting literature for usability-based design lifecycles. Steps included user and task analysis, concept and use modeling, paper prototypes of user interfaces for initial usability assessment, interface development and assessment, and user-based testing of actual interfaces with an actual simulation model. The experimental tests employed two interfaces designed with selected usability variations, each interacting with the same core simulation model. The experimental steps were followed by an analysis of quantitative and qualitative data gathered, including data entry time, interaction errors, solution quality measures, and user acceptance data. The study resulted in mixed support for the hypotheses that improvements in usability of simulation interface elements will improve data entry, solution quality, and overall simulation interactions. Evidence for data entry was mixed, for solution quality was positive to neutral, and for overall usability was very positive. As a secondary benefit, the study demonstrated application of usability-based interface design best practices and processes that could provide guidelines for increasing usability of future discrete-event simulation interface designs. Examination of the study results also provided suggestions for possible future research on the investigation topics

The role of simulation in developing and designing applications for 2-class motor imagery brain-computer interfaces

A Brain-Computer Interface (BCI) can be used by people with severe physical disabilities such as Locked-in Syndrome (LiS) as a channel of input to a computer. The time-consuming nature of setting up and using a BCI, together with individual variation in performance and limited access to end users makes it difficult to employ techniques such as rapid prototyping and user centred design (UCD) in the design and development of applications. This thesis proposes a design process which incorporates the use of simulation tools and techniques to improve the speed and quality of designing BCI applications for the target user group. Two different forms of simulation can be distinguished: offline simulation aims to make predictions about a user’s performance in a given application interface given measures of their baseline control characteristics, while online simulation abstracts properties of inter- action with a BCI system which can be shown to, or used by, a stakeholder in real time. Simulators that abstract properties of BCI control at different levels are useful for different purposes. Demonstrating the use of offline simulation, Chapter 3 investigates the use of finite state machines (FSMs) to predict the time to complete tasks given a particular menu hierarchy, and compares offline predictions of task performance with real data in a spelling task. Chapter 5 aims to explore the possibility of abstracting a user’s control characteristics from a typical calibration task to predict performance in a novel control paradigm. Online simulation encompasses a range of techniques from low-fidelity prototypes built using paper and cardboard, to computer simulation models that aim to emulate the feel of control of using a BCI without actually needing to put on the BCI cap. Chapter 4 details the develop- ment and evaluation of a high fidelity BCI simulator that models the control characteristics of a BCI based on the motor-imagery (MI) paradigm. The simulation tools and techniques can be used at different stages of the application design process to reduce the level of involvement of end users while at the same time striving to employ UCD principles. It is argued that prioritising the level of involvement of end users at different stages in the design process is an important strategy for design: end user input is paramount particularly at the initial user requirements stage where the goals that are important for the end user of the application can be ascertained. The interface and specific interaction techniques can then be iteratively developed through both real and simulated BCI with people who have no or less severe physical disabilities than the target end user group, and evaluations can be carried out with end users at the final stages of the process. Chapter 6 provides a case study of using the simulation tools and techniques in the development of a music player application. Although the tools discussed in the thesis specifically concern a 2-class Motor Imagery BCI which uses the electroencephalogram (EEG) to extract brain signals, the simulation principles can be expected to apply to a range of BCI systems

Simulación asistida por agentes para sistemas de fabricación inteligentes

En el área de la fabricación, la simulación es una herramienta esencial para la validación de métodos y arquitecturas antes de aplicarlos en un Entorno de Fabricación. Las herramientas de simulación actuales llevan a cabo la simulación de entornos de fabricación basándose en modelos estáticos que hacen uso de la programación de procesos de fabricación secuenciales y centralizados tradicionales, donde los mecanismos de planificación y control ofrecen una flexibilidad insuficiente para responder a los estilos de fabricación cambiantes y a los entornos de fabricación altamente mezclados y de bajo volumen. En consecuencia, las herramientas de simulación convencionales limitan la escalabilidad y reconfigurabilidad para el modelado de Sistemas de Fabricación que permitan adaptarlos ante las necesidades cambiantes del Cliente. Resulta difícil encontrar una herramienta de simulación que pueda ejecutar ``inteligentemente'' la simulación de tareas cada vez más complejas. La dificultad radica en integrar en la herramienta el conocimiento necesario del sistema original y que a la vez actúe como un asistente que proporcione consejos y guíe al usuario durante la simulación. Por ello, surge la necesidad de nuevas herramientas de simulación para fábricas que contemplen características tales como: a) flexibilidad y adaptabilidad, para modelar comportamientos complejos propios de un Sistema de Fabricación, b) escalabilidad para la integración transparente de funcionalidades adicionales, c) proactividad y reactividad para la adaptación automática ante los cambios del entorno y d) características de aprendizaje (inteligencia) basado en la experiencia adquirida durante la simulación. Por su parte, las técnicas de Inteligencia Artificial han sido utilizadas en la Fabricación Inteligente por más de dos décadas. Las técnicas del área de Inteligencia Artificial permiten la definición de unidades de fabricación distribuidas, autónomas, inteligentes, flexibles, tolerantes a fallos, reutilizables, las cuales operan como un conjunto de entidades que cooperan entre sí. Además, los recientes desarrollos en el área de los Sistemas Multiagente han traído consigo nuevas e interesantes posibilidades. Algunos investigadores han aplicado la tecnología de agentes en la integración de la fabricación empresarial, la colaboración, la planificación de procesos de fabricación, la programación para el control de planta, el manejo de materiales y la gestión de inventarios, así como la implementación de nuevos tipos de sistemas de fabricación tales como los Sistemas de Fabricación Holónicos. Teniendo en cuenta estas aplicaciones exitosas de los Sistemas Multiagente en la Fabricación Inteligente, estamos convencidos de que esta tecnología puede mejorar también el desempeño de la Simulación de Sistemas de Fabricación Inteligente. En esta tesis proponemos la definición de una Arquitectura para un Entorno de Simulación de Sistemas de Fabricación asistido por agentes. Esta arquitectura integra la funcionalidad de una herramienta de simulación tradicional, permite además la simulación de comportamientos complejos asociados a los Sistemas de Fabricación Inteligentes y proporciona soluciones y mejoras que se adaptan a las necesidades de la nueva era de fabricación.Ruiz Vega, N. (2009). Simulación asistida por agentes para sistemas de fabricación inteligentes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8314Palanci