Discrete-Event Simulation

Los sistemas pull de control de la producción se implementan usualmente mediante tarjetas kanban. El número de tarjetas asociado a un sistema pull puede ser determinado bien estáticamente (establecimiento de tarjetas) o dinámicamente (control de tarjetas). Debido a que el control de tarjetas parece tener unas ciertas ventajas sobre el establecimiento, se han propuesto en la literatura diversos mecanismos para controlar dinámicamente el número de tarjetas. En el presente trabajo, estudiamos la determinación de los parámetros para un mecanismo de control específico en un sistema Conwip dinámico. Nos centramos en un mecanismo específico ya que se ha probado que este mejora el funcionamiento de otros sistemas existentes en una variedad de escenarios. Sugerimos como metodología para el establecimiento de los parámetros un método estadístico basado en la técnica RSM (Response Surface Methodology). Para probar su uso, aplicamos la metodología en una línea formada por cuatro estaciones en tándem y realizamos un experimento confirmatorio en una línea formada por cinco estaciones. Los resultados muestran que la metodología propuesta es efectiva para el establecimiento de parámetros en el mecanismo de control de tarjetas bajo consideración. * Este trabajo se deriva de la participación de sus autores en un proyecto de investigación con financiación procedente del Ministerio de Educación y Ciencia (Proyecto DPI2004-02902) y con cofinanciación proveniente del Fondo europeo de desarrollo regional (FEDER).

Resource planning in service industries is a difficult task and quite different from resource planning in manufacturing. Revenue management is one concept used in service industries when capacity and inventory are challenging to identify. In this study, the company case study provides chilled storage areas for customers. Different products are served and service charging is calculated based on the product's weight and storing time. Currently, the target revenue cannot be achieved. This study presents the application of revenue management in chilled storage area allocation. From a previous study, there were four classes of products based on their importance level as A, B, C and D. Among all classes, the cost of under and overestimating demand was calculated for setting up the area allocation by following the concept of revenue management. Monte Carlo simulation was applied to simulate the existing and improved systems. The simulation results indicated that the average daily revenue could be improved when the storage area allocated to the lowest priority class (class D) was limited to be equal to the average daily demand of class D. Applying the proposed policy can help in increasing yearly revenue by approximately 73,638.75 Thai Baht. Finally, the implementation of the proposed procedure was discussed under the concept of Logistics 4.0.

DEVS (discrete event system specification) is a popular method for specifying discrete event simulation models. Though there are a number of simulators for DEVS, they usually do not provide an easy-to-use graphical interface, while, even if they do, it is simulator-specific. Thus, even if the modeler specifies the same model using DEVS, he/she has to create it from scratch for every discrete simulator. On the other hand, UML is a standard modeling language providing graphical representation of models and code generation capabilities. In this paper, we discuss our effort to combine UML with DEVS to build simulation models, promoting software engineering methods in the simulation world. Such an endeavor should facilitate a standard method to define DEVS models and promote interoperability between DEVS simulators. The first step towards this, is the formal definition of the DEVS UML 2.0 profile proposed in this paper.

Many processes in the chemical industry have some discrete phenomena superimposed on the continuous system dynamics. While the continuous behavior arises from phenomena such as mass, energy and momentum conversion, discrete behavior may occur due to physico-chemical discontinuities or discrete controller actions. Such systems which involve interaction between the continuous system dynamics and logical control functions are classified as Hybrid Systems. For such systems modeling in terms of the continuous variables alone is not sufficient. Simulation of such systems is necessary since discrete actions can trigger a qualitative change in the process model. Dynamic simulation becomes mandatory for the synthesis and validation of safety operating conditions in chemical processes or start-up and shut-down procedures. This paper presents a new hybrid simulation environment for modeling and simulation of hybrid systems. It offers a high-level design language for the automatic or semi-automatic generation of the process models. Examples of practical relevance as well as an outline for treating the logical consistency of multi-event network are given. The application of the simulation language is illustrated by means of a continuous-discrete implementation of a Dynamic Matrix Control strategy.

The generic mathematical language (GML) is a modeling formalism for the declaration of steady state, dynamic as well as combined continuous/discrete chemical processing models. It establishes the foundation for the phenomena-oriented model generation environment TechTool. This brief discussion presents an object-oriented paradigm for modeling and design based on object instantiation, prototype inheritance and interfaces. This new object relation framework in combination with dynamic compilation facilitates evolutionary model development and can be of critical importance for large-scale process models.

OntoUML is a modeling language based on an underlying foundational ontology (UFO). Over the years, it has gained increasing attention in the area of ontology-driven conceptual modeling, becoming one of the most used languages in that field. In this paper, we report on a preliminary prototype that kickstarts the creation of pre-conceptual models in OntoUML from instance-level examples in PURO, a graphical modeling language originally developed for analogously kickstarting OWL ontology skeletons.

I was now a regular part of the faculty and was concentrating on my research. I was still continuing my course on Programming, and was thinking of introducing object-oriented concepts to replace the structured concepts. Since I had become a professor in my own university, there was a pressure to visit an external university and get more experience to make up for the missing graduate work I should have done at a different institution. My background was in simulation, so I started feeling around for a postgraduate research post to involve simulation. Fortunately, my PhD advisor was a graduate of Harvard University, and he contacted his Ph.D. advisor, who told him that he needed somebody to work in Simulation, in a new area called the Standard Clock Method. After a couple of email messages to understand what the task was about, I got a letter of acceptance from Harvard to work for one year as a Postgraduate Researcher at the School of Applied Sciences.

Large-scale logistics companies deliver products using sea transportation effectively. Company X as one of the pioneer port containers service still has limitations both from minimal stacking capacity and limited equipment, 1 HMC unit and 1 unit reach adapter. The number of containers increases from 2014-2017, but the availability of tools and facilities that needed continue to cause overcapacity problem. This paper aims to determine the yard occupancy ratio (YOR), berth occupancy ratio (BOR) and utility equipment that are in accordance with the standards to prevent overcapacity at port X until 2020. This study uses extend simulation method to make improvements and analysis of conditions that running, the results of the study are recommendations for the addition of 2 units of transport and the addition of reach units of 2 units. For the YOR value, additional capacity from 2,046 TEUs was made to 3,800 TEUs so that the initial maximum YOR was 139.8% to 75.3%, while BOR still in maximu...

In a simulation project, a good conceptual model representation is critical for communicating conceptual models between stakeholders. A conceptual model describes the problem domain and model specifications. The description of the problem domain includes the objectives, inputs, outputs, content, assumptions and simplifications made in the model. The model specifications are used to specify the model's behavior. This article focuses on the representation of the model content (structure, boundary and level of detail) component of an agent-based simulation (ABS) model. For this, we propose the use of Business Process Model and Notation (BPMN) from the Object Management Group. A Web-based visual modeling tool has been developed using JavaScript to demonstrate how BPMN can be used to represent an ABS conceptual model and how the tool translates the conceptual model into code ready for execution using Repast HPC. Conceptual modeling is the process of abstracting a model from a real or proposed system into a conceptual model (Robinson 2010). There is a point in a simulation project where the conceptual modeling process occurs inside an individual modeler's mind. This 'thinking' process includes reflection on how to structure the problem and how the simulation model should be designed to help decision-makers solve the problem to hand, subject to certain constraints. At some point in the simulation project, the conceptual model needs to be communicated to other stakeholders (such as clients, simulation modelers and domain experts). Nance (1994) refers to explicit representation of the conceptual model as the communicative model. The importance of the quality of communication between stakeholders to make a simulation project (Robinson and Pidd 1998) successful makes the role of (explicit) conceptual model representation important. Onggo ( ) classifies methods for conceptual model representation into three categories: textual, pictorial and multi-faceted. It is clear that the definition of a conceptual model must affect its representation. Unfortunately, there is no single accepted definition of what a conceptual model is. Robinson (2010) discusses various conceptual model definitions and concludes that complete consensus is difficult to achieve. This is due partly to the wide range of applications of computer simulation; each application domain may have different characteristics (such as project scale and team size) and requirements (such as the criticality of model reusability). This article uses the conceptual model definition proposed in Robinson (2010), i.e., a "conceptual model is a non-software specific description of the computer simulation model (that will be, is or has been developed), describing the objectives, inputs, outputs, content, assumptions and simplifications of the model." Based on the separation between domain-oriented components and design-oriented components in a conceptual model, as proposed in , we extend Robinson's definition to include design-oriented components. These provide a representation of the problem domain which is consistent with

We present a teaching method aimed at developing higher programming skills from description to production. The model is derived from problem-based learning approaches. It is supported by an "incremental" web site that gradually introduces theoretical presentations, examples, programs and information regarding the problem. The web site is also used as a collaboration space where students can find partial solutions proposed by other teams as well as "requests" submitted by a fictitious client. At the end of the project, each product is published and the best teams are awarded a virtual medal.We had four objectives. The first was to get students to share their expertise and learn to work in teams; second, to teach students the importance of doing a conceptual analysis rather than jumping into programming; third, to introduce theoretical notions, exercises, and examples in class when the students asked for them; and finally, to get students to formulate and describe ...

Mining projects needs application of modelling and simulation techniques. Modelling and simulation can help in a better and more scientific decision making, as compared to the trial and error based managerial decisions, which often results in inefficient utilization of resources. Simulation can be applied to material handling operations using trucks and shovels, which is an integral part of surface mining operations (including quarry, open pit and open cast mining). This thesis is related to application of modelling and simulation for optimal fleet selection and resource utilization in cement quarry operations using Simio®. Materials extracted from quarry or open pit and open cast mines are often handled with conventional system of trucks and shovels, which typically constitutes 50-55% of total cost of mining operations [3]. Hence, optimal utilization of trucks and shovels is one of the goals in cement quarry operations. Cement quarry operations at Cherat Cement Company, a leading c...

While the concept of remanufacturing is gaining popularity globally, literature and theory on strategic decision-making on certifying for warranty in this area remain limited. A strategic and establish concept flow is developed based on extensive literature review and surveys with experienced experts who are dealing with remanufactured, reconditioned, rebuilt and reused components. The remanufacturing research on evaluating quality assurance of remanufactured component targets macro-level parameters and the indicators which must be confirmed for evaluation. The strategic remanufacturing factors identified from the literature review are discussed in a brainstorming session with a number of remanufacturing researchers and academic experts. The study is further broadened by industrial surveys and case studies to justify the inputs on developing a framework to certify remanufactured components. Preliminary results have established the key factors of remanufacturing quality control that might lead to the strict quality assurance of remanufactured components. Later, the developed framework can be used as a benchmarking tool to certify remanufactured components and warranty issuance. The findings serve as the foundation for further research concerning Original Equipment Manufacturer (OEM) or Original Equipment Remanufacturer (OER) and Independent Equipment Remanufacturer (IER) in the Malaysian Remanufacturing Industry.

This study presents a simulation-based procedure to analyse a production line of a metalworking company. We use a simulation tool, ProModel ® software, to reproduce the existing production line layout of the company best-selling product which represents about 70% of the total sales. Our purpose is to get information about the existing system behaviour, and to find strategies to increase actual production level to meet the market's demand. Based on an initial simulation model, different production scenarios were proposed and results have shown that it is possible to increase the production level allowing to meet the increasing demand for the product. The following changes in the production system were considered: (i) the use of intermediate stock of work-in-process items, (ii) the introduction of new equipment, and (iii) a mixed strategy where the introduction of new equipment is combined with the use of intermediate stock of work-in-process items. In summary, this research exhibits the flexibility of the simulation technique to address manufacturing problems throughout the creation of different scenarios providing some of the behaviour of the systems allowing the anticipation of final outputs.

This study presents a simulation-based procedure to analyse a production line of a metalworking company. We use a simulation tool, ProModel ® software, to reproduce the existing production line layout of the company best-selling product which represents about 70% of the total sales. Our purpose is to get information about the existing system behaviour, and to find strategies to increase actual production level to meet the market's demand. Based on an initial simulation model, different production scenarios were proposed and results have shown that it is possible to increase the production level allowing to meet the increasing demand for the product. The following changes in the production system were considered: (i) the use of intermediate stock of work-in-process items, (ii) the introduction of new equipment, and (iii) a mixed strategy where the introduction of new equipment is combined with the use of intermediate stock of work-in-process items. In summary, this research exhibits the flexibility of the simulation technique to address manufacturing problems throughout the creation of different scenarios providing some of the behaviour of the systems allowing the anticipation of final outputs.

A method for simulating power law noise in clocks and oscillators is presented based on modification of the spectrum of white phase noise, then Fourier transforming to the time domain. Symmetric real matrices are introduced whose traces-the sums of their eigenvalues-are equal to the Allan variances, in overlapping or non-overlapping forms, as well as for the corresponding forms of the modified Allan variance. Diagonalization of these matrices leads to expressions for the probability distributions for observing a variance at an arbitrary value of the sampling or averaging interval τ , and hence for estimating confidence in the measurements. A number of applications are presented for the common power-law noises.

numerical simulations are used to investigate the origins of the different wave velocities measured in dense granular samples assembled with different methods. Glass bead packings are prepared in the lab either by pouring and vibrating the dry material in a container, or by mixing with a very small amount of a viscous lubricant. Lubricated samples, although less dense, exhibit significantly higher wave velocities for confining pressures in the 100 kPa range. Numerical predictions for elastic moduli agree much better with experimental results when the computational preparation of the samples mimics the laboratory one, albeit in a simplified manner. A plausible explanation to the laboratory observations is that the coordination number, which influences the material stiffness more than its density, is notably higher in lubricated packings.

Using Anti-air warfare (AAW) tactics and concepts of operations, this research explores the effective factors of convoy operations. A discrete event simulation (DES) was built by modeling ships, and their sensors and weapons. The model was used to simulate over 1.5 million naval battles varying 99 input variables using systematically created data combinations. To select the input settings over a specific range of input variables, a nearly orthogonal nearly balanced (NOB) Latin hypercube design was used. The effects of these input changes on the outputs were analyzed. The response variable was the survival of the High Value Unit (HVU) as a binary outcome. According to the analysis, in a convoy operation under air threat, the surface-to-air missile (SAM) specifications of the screen ships, the staying power of the HVU, and the anti-ship missile (ASM) specifications of the enemy ships had the most significant effect on the survival of the HVU.

Currently the "network centric operation" and "network centric warfare" have generated a new area of research focused on determining how hierarchical organizations composed by human beings and machines make decisions over collaborative environments. One of the most stressful scenarios for these kinds of organizations is the so-called "extreme events." This dissertation provides a hybrid simulation methodology based on classical simulation paradigms combined with social network analysis for evaluating and improving the organizational structures and procedures, mainly the incident command systems and plans for facing those extreme events. According to this, we provide a methodology for generating hypotheses and afterwards testing organizational procedures either in real training systems or simulation models with validated data. As long as the organization changes their dyadic relationships dynamically over time, we propose to capture the longitudinal digraph in time and analyze it by means of its adjacency matrix. Thus, by using an object oriented approach, three domains are proposed for better understanding the performance and the surrounding environment of an emergency management organization. System dynamics is used for modeling the critical infrastructure linked to the warning alerts of a given organization at federal, state and local levels. Discrete simulations based on the defined concept of "community of state" enables us to control the complete model. Discrete event simulation allows us to create entities that represent the data and resource flows within the organization. We propose that cognitive models might well be suited in our methodology. For instance, we show how the team performance decays in time, according to the Yerkes-Dodson curve, affecting the measures of performance of the whole organizational system. Accordingly we suggest that the hybrid model could be applied to other types of organizations, such as military peacekeeping operations and joint task forces. Along with providing insight about organizations, the methodology supports the analysis of the "after action review" (AAR), based on collection of data obtained from the command and control systems or the so-called training scenarios. Furthermore, a rich set of mathematical measures arises from the hybrid models such as triad census, dyad census, eigenvalues, utilization, feedback loops, etc., which provides a strong foundation for studying an emergency management organization. Future research will be necessary for analyzing real data and validating the proposed methodology.

This paper demonstrates an architecture for suspending and resuming methods in Java using a restricted form of continuation passing style (CPS) transformation. It describes Kilim 1 , a toolkit to portably weave threads of control called Fibers, through Java code. The chief contributions of this paper are the set of design choices made for both space and time efficiency in getting one-shot continuations to work on the JVM (in some cases, 60x faster than competing approaches) and to address some tough issues traditionally passed over by others, such as handling of local subroutines and constructors. We are able to support hundreds of thousands of threads of control with switching times of the order of 3 to 4 μs on a low-powered laptop with Sun's JVM.

This applied research article explores the application of Mixed-Integer Linear Programming (MILP) to address line-balancing challenges in the garment industry, focusing on optimizing production processes under multiple constraints. By integrating MILP with Lean Methodology principles, the study demonstrates significant improvements in operational efficiency and costeffectiveness. The case study, conducted in collaboration with Prof Dr Ray WM Kong, highlights the successful implementation of MILP using IBM CPLEX Studio to optimize production order quantities across online and offline operations. The results reveal a remarkable reduction in labour costs, exceeding 50%, while effectively managing resource capacity and demand constraints. This study not only validates the theoretical underpinnings of MILP in resolving linebalancing issues but also underscores its practical applicability in modernizing garment production. The findings contribute valuable insights into the potential of advanced optimization techniques to enhance competitiveness and sustainability in the garment industry. This abstract succinctly captures the essence of the research, emphasizing the methodology, results, and significance of the study.

Dynamic queueing networks (DQN) model queueing systems where demand varies strongly with time, such as airport terminals. With rapidly rising global air passenger traffic placing increasing pressure on airport terminals, efficient allocation of resources is more important than ever. Parameter inference and quantification of uncertainty are key challenges for developing decision support tools. The DQN likelihood function is, in general, intractable and current approaches to simulation make likelihood-free parameter inference methods, such as approximate Bayesian computation (ABC), infeasible since simulating from these models is computationally expensive. By leveraging a recent advance in computationally efficient queueing simulation, we develop the first parameter inference approach for DQNs. We demonstrate our approach with data of passenger flows in a real airport terminal, and we show that our model accurately recreates the behaviour of the system and is useful for decision support. Special care must be taken in developing the distance for ABC since any useful output must vary with time. We use maximum mean discrepancy, a metric on probability measures, as the distance function for ABC. Prediction intervals of performance measures for decision support tools are easily constructed using draws from posterior samples, which we demonstrate with a scenario of a delayed flight.

This article presents applied research on line balancing within the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process, by Lean Methodology for garment modernization. It explores the application of line balancing in the modern garment industry, focusing on the significant impact of intelligent hanger systems and hanger lines on the stitching process. It aligns with Lean Methodology principles for garment modernization. Without the implementation of line balancing technology, the garment manufacturing process using hanger systems cannot improve output rates. The case study demonstrates that implementing intelligent line balancing in a straightforward practical setup facilitates lean practices combined with a digitalization system and automation. This approach illustrates how to enhance output and reduce accumulated work in progress.

The problem of calculating future capacity of a projected port involves several uncertainties, which means that it is not possible to find a single formula that considers the interaction of the different variables affecting the port’s operational performance, particularly considering that many of these variables are related to stochastic distributions and restrictions in shared resources. Only a simulation model can consider all the variables and produce a reliable projection of the port’s future behavior. It is very important to precisely estimate the figures because the demurrage costs grows exponentially as the port’s occupancy moves toward 100%, which directly affects the project’s feasibility.

This paper investigates the discrete simulation of the solution of initial-boundaryvalue problems that typically arise in technical areas. Since many of them lead to unbounded and non-self-adjoint differential operators, we have to use a rather general theory as a mathematical basis. For the class of sectorial operators with a compact resolvent operator, the solution of initial-boundary-value problem can be represented by means of a certain holomorphic semigroup. It is shown that the solution can be expanded with respect to the canonical system of the considered operator. Such an expansion corresponds to a multi-dimensional functional transformation in the frequency domain. This fact leads to simple structures for the realization of the resulting system. Computationally efficient numerical algorithms can be derived by proper methods well-known from the theory of digital signal processing.

A full representation of a simulation model encompasses the behavior of the elements that define the model, the definition of the probability distributions that define the delays of the events that control the model, the experimental framework needed for execution, and the graphical representation of certain model elements. This paper aims to use specification and description language to achieve a full model representation by adding two extensions to the language, which allows for a complete and unambiguous definition of a discrete simulation model that is similar to a common discrete operations research simulation tool.

El Efecto Látigo (En idioma inglés Bullwhip Effect) es uno de los causantes de las fluctuaciones que experimenta la proyección de la demanda a medida que se aleja del mercado a lo largo de la Cadena de Suministro (CdS), como consecuencia de falta de coordinación y sincronización entre los agentes intervinientes (Proveedor, fabricante, distribuidor, mayorista, minorista). Esta situación afecta la planificación estratégica y operativa pretendida por las organizaciones que integran la CdS, en relación a los tiempos de respuesta, capacidad de almacenamiento, administración de los costos logísticos ocultos y procesos de negociación, entre otros aspectos. Una forma de atenuar este efecto, es que la CdS Diciembre de 2013 Juan Carlos Mejía Villamizar, Óscar Palacio León, Wilson Adarme Jaimes posea un sistema de información gerencial sincronizado bajo un ambiente cooperativo de negociación. Este escenario empresarial no siempre se suele dar fácilmente, motivo por el cual se propone un método de medición y control basado en técnicas de la Dinámica de Sistemas, específicamente, la aplicación de alisado exponencial y de Holt-Winters. Estos métodos permiten transmitir los mismos patrones de demanda recibidos, sin ningún tipo de variación a lo largo de la CdS.

Simultaneous events are the events scheduled to occur at the same simulation time. This paper proposes a new event ordering mechanism for handling simultaneous events of DEVS models in distributed simulation. The DEVS formalism provides a formal framework for specifying discrete event models in a modular, hierarchical form. Thus, the formalism can ease the model verification and validation problems of distributed simulation. Also, the formalism separates models from underlying simulation algorithms. Hence, DEVS models can be simulated in both sequential and distributed environments without any modification. One important issue for such framework is to obtain the same results in both simulation environments. However, in distributed simulation of DEVS models, the processing order of simultaneous events may affect the simulation results. Thus, some ordering mechanism of events is required for well-defined simulation results. The proposed mechanism orders simultaneous events correctly with respect to their causal relationships in distributed DEVS simulation. Also, the mechanism guarantees the same ordering of simultaneous events in both sequential and distributed simulation environments. @ 1997 Elsevier Science B.V.

The flow of goods is still dominated by sea transport compared with other modes of transport so that the container terminal is very important role in the economic system of a country. The main indicator of performance of a container terminal is the total container throughput in TEUs per year. Recording is done in the process of stevedoring

The micro-mechanical behavior and damage of materials containing multiple microcracks is investigated using a mesoscopic approach. We develop an analytical and computational framework for the nucleation and interaction of microcracks near a macrocrack tip based on both the theory of elasticity and the theory of dislocations. Grain boundaries are considered as critical material points for crack initiation. The discrete model is used to investigate the relationship between the macroscopic applied stress and evolution of microcracks, yielding a micro-structurally based model for the evolution of damage consistent with some theoretical models. It is suggested that with this approach macroscopic models can be developed whose phenomenological parameters can be rigorously investigated and obtained using discrete simulation of microcracks.

This paper presents an ontology-based Virtual Factory tool to support the 3D design of factories. The official ifcOWL is the reference ontology that was adopted to develop the I/O software connector of the tool. The key advantage of the ontology interface is represented by the easy integration with other software tools that can either use the layout generated by GIOVE-VF or provide information about the evolution of the objects that can be visualized in realistic animations.

The growing importance of manufacturing SMEs within the European economy, in terms of Gross Domestic Product and number of jobs, emphasizes the need of proper ICT tools to support their competitiveness. Major ICT players already offer one-does-all Product Lifecycle Management suites, supporting several phases of the product-process-plant definition and management. However, these do also show consistent shortcomings in terms of SME accessibility, degree of personalization and they often lack of an acceptable level of interoperability. These problems are being addressed by the development of a Virtual Factory Framework (VFF), within an EU funded project. The approach is based on four pillars: 1) Semantic Shared Data Model, 2) Virtual Factory Manager (VFM), 3) Decoupled Software Tools that lay on the shared data model and can interact through the VFM, 4) Integration of Knowledge. This paper will focus on the Virtual Factory Manager, proposing an evolution of the former VFF second Pillar , that acts as a server supporting the I/O communications within the framework and its stored knowledge for the decoupled software tools needing to access its repository.

The performance evaluation of manufacturing systems is a critical and difficult task to be addressed throughout the factory life-cycle phases, including the early design, detailed design, ramp-up, reconfiguration, and monitoring. An efficient and effective performance evaluation may have a relevant impact on the profitability of an industrial company. This paper addresses the application of a data model for virtual factories to the performance evaluation problem, aiming at exploiting the interoperability with other software tools to continuously update the virtual representation of a manufacturing system, so that accurate estimations can be obtained. A test case is described and then used to check the viability of the proposed approach in the case of Discrete Event Simulation (DES) based on a commercial software tool like Arena.

Manufacturing companies have to manage a large amount of data and information. This is due to both the presence of advanced sensors systems at the shop floor level and to the spreading of simulation and decision support software tools. The exchange of simulated and real data can be effective only if interoperability is guaranteed. However, most of the software tools are based on their own data models and proprietary file formats, thus jeopardizing the interoperability. This paper presents the outcomes of a European research project, named Virtual Factory Framework (VFF), that aims at developing an integrated virtual environment to enable the interoperability between software tools supporting the factory processes along all the phases of its lifecycle. The cornerstone of the proposed VFF consists in a common Virtual Factory Data Model (VFDM) that can be considered as the shared meta-language providing a common definition of the data that are shared among the software tools connected ...

The interaction of thruster plumes with satellite components is investigated, with emphasis on undesirable effects, such as disturbance force/torque, thermal loading, and species deposition in the Korea Multipurpose Satellite-II (KOMPSAT-II) base region. The actual configuration of the satellite is simplified by the consideration of four major components of hydrazine thrusters, the S-band antenna, and the surrounding ring. For the numerical simulation, a fully unstructured three-dimensional discrete simulation Monte Carlo (DSMC) code is developed and validated. The DSMC computation allows for examination of the detailed flowfield dynamics, as well as the wall conditions, which, otherwise, would not be possible from a simplified engineering analysis. The computations show that the present thruster arrangement used in KOMPSAT-II incurs a negligible disturbance force/torque and thermal loading compared with its nominal thrust/torque and solar heating. The simulations also indicate that the species deposition is insignificant due to the high surface temperature of the satellite body. Of the chemical species considered (H 2 , N 2 , and NH 3), more H 2 molecules collide with the S-band antenna cone. This study clearly shows the usefulness of DSMC calculations for analysis of plume effects in the development phase of a satellite. Nomenclature P 0 = chamber pressure q sol = solar constant r th = radius of thrust throat r 0 = radius of thruster exit T 0 = chamber temperature x, y, z = coordinates t = time step σ T = thermal accommodation coefficient Subscript BOL = beginning of life

The paper is devoted to multiscale computer modelling of defect flows along interfaces in loaded solids. Interfaces are considered as 2D self-organized subsystems. Discrete approach of stochastic excitable cellular automata (SECA, [1,2]) was extended by adding of special algorithm of astable cellular automata (ACA) to simulate defect propagation and microcrack nucleation. SECA method provides 3D-modelling at mesoscale and it takes into account grain structure of the material; the ACA provides microscale simulations of 2D interface behaviour. Microcrack is considered as a specific "phase state" of local material volume. Defect flows are controled by specific "driving force" calculated from the values of material torsion, couple forces and hydrostatic pressures distributed at the interface. Numerical experiments of fragmentation and fracture in 2D interface show quasiperiodic cyclic character of microcrack nucleation and defect propagation. Computer simulation method based on excitable cellular automata allowed revealing undetected effects in the form of propagation of spiral waves in specimen under indentation. It is shown that rotational wave flows of defects are able to cause forming of quasiperiodical defect structures along the interface.

In this paper the risk of supply chain disruptions is investigated in relations to different policies of inventory replenishment. The increasing attention to this issue in the academic and business, has strongly motivated the development of this work, above all to obtain analysis of costs in terms of distributions and variability. The goal is to enrich literature in constant growth and allow companies to manage the risks associated with such events, providing considerations to develop appropriate mitigation strategies for the supply chain disruption risk. In addition we wanted to compare the behavior, in terms of performance, of a system managed by continuous or periodic review policy, to previous results from the literature. The implementation of a validated supply chain model is a further goal, to provide a tool for what-if analysis in not already studied disruption situations.

This paper minimizes the value of total cost and bullwhip effect in a supply chain. The objectives have been achieved through developing a new multi-objective formulation for minimizing the total cost and minimizing the bullwhip effect of a two-echelon serial supply chain. A new crossover algorithm for a fuzzy variable and a new mutation algorithm have also been proposed while applying Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to the proposed problem. The formulated problem has been simulated by Matlab software and the results of the modified NSGA-II have been compared with those of original NSGA-II. It is found from the results that the modified NSGA-II algorithm performs better than the original NSGA-II algorithm since the minimum values for both total cost and the bullwhip effect are obtained in case of the modified NSGA-II. The formulated bi-objective problem is new to the research community. The minimization of bullwhip effect has never been considered in a multi-objective optimization before. Besides crossover operator applied to the fuzzy variable and the mutation operator are newly introduced operators.

We present a study, based on simulations with SERDYCA, a spatially-explicit individual-based model of rodent dynamics, on the relation between population persistence and the presence of numerous isolated disturbances in the habitat. We are specifically interested in the effect of disturbances that do not fragment the environment on population persistence. Our results suggest that the presence of disturbances in the absence of fragmentation can actually increase the average time to extinction of the modeled population. The presence of disturbances decreases population density but can increase the chance for mating in monogamous species and consequently, the ratio of juveniles in the population. It thus provides a better chance for the population to restore itself after a severe period with critically low population density. We call this the "disturbance-forced localization effect".

We present a novel strategy for computing disparity maps from omni-directional stereo images obtained with fish-eye lenses in forest environments. At a first segmentation stage, the method identifies textures of interest to be either matched or discarded. Two of them are identified by applying the powerful Support Vector Machines approach. At a second stage, a stereovision matching process is designed based on the application of four stereovision matching constraints: epipolarity, similarity, uniqueness and smoothness. The epipolarity guides the process. The similarity and uniqueness are mapped once again through the Support Vector Machines, but under a different way to the previous case; after this an initial disparity map is obtained. This map is later filtered by applying the Discrete Simulated Annealing framework where the smoothness constraint is conveniently mapped. The combination of the segmentation and stereovision matching approaches makes the main contribution. The method is compared against the usage of simple features and combined similarity matching strategies.

This work addresses the problem of performing a formal modelling of the processes related to the surgical pavilions and an anaesthesia unit on a Chilean hospital. To perform this modelling we used Specification and Description Language (SDL). The model was very successful in order to document and to understand the tacit knowledge of the unit and facilitates the simulation.

En este articulo encontrara   los resultados de un investigacion realizada sobre la empresa Informatica y Tecnologia Stefanini S.A acerca de su actividad economica y como lleva a cabo sus procesos para ser una empresa lider con reconocimiento nacional e internacional en mas de 30 paises y una trayectoria de mas de 20 anos trabajando en soluciones de Tecnologia e Innovacion. Inicialmente se dara una breve explicacion de la empresa, su actividad economica y su estructura, pasando a explicar de forma clara el concepto de las 4p en la gestion de proyectos. Se profundizara en plasmar los conceptos y caracteristicas de personal, producto, proceso y Proyecto segun como son desarrolladas y utilizadas en esta organizacion. Para finalizar se describiran algunas conclusiones donde se explicara el aprendizaje obtenido con esta investigacion.

Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data is often used to create virtual replicas of the physical system as it progresses through real-time. There is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms. The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT conceptualisation in four dimensions, and (3) present methodological and technical insights on developing RtS with limited data. We argue that the evolution of conventional simulation models to fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily driven using historical distributions with limited real-time data feeds.

A micromechanical model for cohesive materials is derived by considering their underlying microstructure conceptualized as a collection of grains interacting through pseudo-bonds. The pseudo-bond or the inter-granular force-displacement relations are formulated taking inspiration from the atomistic-level particle interactions. These force-displacement relationships are then used to derive the incremental stiffnesses at the grain-scale, and consequently, obtain the sample-scale stress-strain relationship of a representative volume of the material. The derived relationship is utilized to study the stress-strain and failure behavior including the volume change and ''brittle" to ''ductile" transition behavior of cohesive materials under multi-axial loading condition. The model calculations are compared with available measured data for model validation. Model predictions exhibit both quantitative and qualitative consistency with the observed behavior of cohesive material.

Models from different methods and tools are integrated semantically. An integration model represents certain aspects of interest found in the individual models. It is built with the fundamental entities Event, Actor and State. Sharing entities between models improves coherence and interrelating entities adds semantic value. Some formal rigor and a common vocabulary helps getting insight and allows for automated checking. The resulting semantic net can be validated in terms of quality mre easily before the system is realized.