The increasing competition between the companies forces them to develop the production in a continuous manner in order to maintain the competitiveness in the global market, and became as efficient and effective as possible. This master thesis is conducted at Getrag All Wheel Drive Company which is one of the largest suppliers for transmissions and powertrain systems .This Company has worked actively for long time to improve the production flow at the manufacturing departments by using usual methods. Because of the high complex and intersected flow that the company has, the management intended to adopt another approach that takes dynamic information into consideration, therefore, building a simulation model is the solution, where according to Banks et al (2001) the simulation is a duplication of a real-world process or system and its behaviour as it progress during the time, which is a very useful method to evaluate complex systems, instead of using usual mathematical means used tools. The simulation model created by using Banks et al (2001) simulation methodology, and ExtendSim software help. The resulted model used as a tool that provides great assistance to the decision makers, in order to develop the Conwip system which applied in the manufacturing line under study, and to investigate “What if” scenarios. The result of this study obtained after performing two experiments, where the first experiment gives recommendation regarding the optimal upper bound of the total amount of work that can be used in Conwip system, with the use of sensitivity analysis, and the second experiment analyse the overall all effect on the system after separating the paths of high and low volume products. This project proves the powerful side of using the simulation in situations where it’s too hard or even impossible to improve the performance of a manufacturing line i.e. when large number of variables involved and affecting the system.

Discrete Event Simulation on GPUs employing parallel heap data structure is the focus of this thesis. Two traditional algorithms, one being conservative and other being optimistic, for parallel discrete event simulation have been implemented on GPUs using CUDA. The first algorithm is the safe-window algorithm (conservative). It has produced expected performance when compared to sequential simulation. The second algorithm, known as SyncSim, is an optimistic simulation algorithm previously designed to be space efficient and reduce rollbacks. This algorithm is re-implemented on GPU platform with necessary changes on the logic simulator and the parallel heap implementation. The performance of the parallel heap when working with a logic simulator has also been validated against the results indicated in previous research paper on parallel heap without the logic simulator.

Spatio-temporal systems with heterogeneity in their structure and behavior have two major problems. The first one is that such systems extend over very large spatial and temporal domains and consume a lot of resources to simulate that they are infeasible to study with current platforms. The second one is that the data available for understanding such systems is limited. This also makes it difficult to get the data for validation of their constituent processes while simultaneously considering their global behavior. For example, the valley fever fungus considered in this dissertation is spread over a large spatial grid in the arid Southwest and typically needs to be simulated over several decades of time to obtain useful information. It is also hard to get the temperature and moisture data at every grid point of the spatial domain over the region of study. In order to address the first problem, we develop a method based on the discrete event system specification which exploits the heterogeneity in the activity of the spatio-temporal system and which has been shown to be effective in solving relatively simple partial differential equation systems. The benefit of addressing the first problem is that it now makes it feasible to address the second problem.We address the second problem by making use of a multilevel methodology based on modeling and simulation and systems theory. This methodology helps us in the construction of models with different resolutions (base and lumped models). This allows us to refine an initially constructed lumped model with detailed physics-based process models and assess whether they improve on the original lumped models. For that assessment, we use the concept of experimental frame to delimit where the improvement is needed. This allows us to work with the available data, improve the component models in their own experimental frame and then move them to the overall frame. In this dissertation, we develop a multilevel methodology and apply it to a valley fever model. Moreover, we study the model's behavior in a particular experimental frame of interest, namely the formation of new sporing sites.

Today, there is little understanding of how local decisions and disturbances impact the global performance of the supply chain. In this research, we attempt to gain insight about such relationship using multi-resolution hybrid models. To this end, a novel hybrid architecture and methodology consisting of simulation (system dynamic and discrete-event) and optimization modules is proposed. The proposed methodology, applicable to general supply chains, is divided into fours stages: plan stability analysis (Stage I), plan optimization (Stages II), schedule optimization (Stage III) and concurrent decision evaluation (Stage IV). Functional and process models of the proposed architecture are specified using formal IDEF tools. A realistic three-echelon conjoined supply chain system characterized by communicative and collaborative (VMI) configurations is analyzed in this research. Comprehensive SD models of each player of the supply chain have been developed. General conditions of the stability (settings of control parameters that produce stable response) are derived using z-transformation techniques (Stage I), and insights into the behavior of the supply chain are gained. Next, a novel method for the integration of the stability analysis with performance analysis (optimization) is presented (Stage II) by employing the derived stability conditions derived as additional constraints within the optimization models. Next, in Stage III, the scheduling at each chain partner using discrete-event simulation (DES) modeling techniques is addressed. In Stage IV, the optimality of the SD control parameters (from Stage II) and DES operational policies (from Stage III) for each member are concurrently evaluated by integrating the SD and DES models. Evaluation in Stage IV is performed to better understand the global consequence of the locally optimal decisions determined at each supply chain member. A generic infrastructure has been developed using High Level Architecture (HLA) to integrate the distributed decision and simulation models. Experiments are conducted to demonstrate the proposed architecture for the analysis of distributed supply chains. The progressions of cost based objective function from Stages I-III are compared with that from the concurrent evaluation in Stage IV. Also the ability of the proposed methodology to capture the effect of dynamic perturbations within the supply chain system is illustrated.

The source system is the real or virtual environment that we are interested in modeling. It is viewed as a source of observable data, in the form of time-indexed trajectories of variables. The data that has been gathered from observing or experimenting with a system is called the system behavior data base. The time indexed trajectories of variables provide an important clue to compose the DEVS (discrete event specification) model. Once event set is derived from the time indexed trajectories of variable, the DEVS model formalism can be extracted from the given event set. The process must not be a simple model generation but a meaningful model structuring of a request. The source data and query designed with SES are converted to XML Meta data by XML converting process. The SES serves as a compact representation for organizing all possible hierarchical composition of system so that it performs an important role to design the structural representation of query and source data to be saved. For the real data application, the model structuring with the US Climate Normals is introduced. Moreover, complex systems are able to be developed at different levels of resolution. When the huge size of source data in US Climate Normals are implemented for the DEVS model, the model complexity is unavoidable. This issue is dealt with the creation of the equivalent lumped model based on the concept of morphism. Two methods to define the resolution level are discussed, fixed and dynamic definition. Aggregation is also discussed as the one of approaches for the model abstraction. Finally, this paper will introduce the process to integrate the DEVSML(DEVS Modeling Language) engine with the DEVS model creation engine for the Web Service Oriented Architecture.

The development of controls for the execution of concurrent code is non-trivial. This work shows how existing discrete-event system (DES) theory can be successfully applied to this problem. From code without concurrency controls and a specification of desired behaviours, a DES representation of the problem is obtained, and then used to generate concurrency control code. By applying rigorously proven DES theory, the resulting code comes with guarantees not present in similar works. All control schemes generated in DES are nonblocking, yielding code that is free of both livelock and deadlock. Additionally, the generated control scheme is minimally restrictive, meaning only problematic behaviours are prevented. If the specifications cannot be enforced as presented, the largest controllable subset is instead enforced. The result, which requires no further interaction to generate, is the best possible control scheme given the interaction between the specifications and the original code. Existing methods encounter difficulties when faced with multiple specifications that interact to form deadlocks. Modular DES theory is successfully applied, allowing resolution of these conflicts without requiring the user to introduce new specifications. Moreover, the approach is independent of specific programming or specification languages. A Java implementation is given, along with two problems showing the process in action. / Thesis (Master, Computing) -- Queen's University, 2008-09-25 09:03:51.593

Discrete-Event systems (DES) is a framework in which problems are modelled as finite-state automata and a solution in the form of a supervisory control scheme can be automatically synthesized via an exhaustive search through the state space of the system. Various extensions to the standard DES framework have been introduced to allow it to be applied to a greater variety of problems. When the system in question is very large or varies with time, a limited lookahead policy can be adopted, in which control decisions are made on-the-fly by looking at finite-step projections of the behaviour of the system's underlying automata. This work presents a new approach to limited lookahead supervision which incorporates many of the extensions to DES that are already present in the literature, such as event probability and string desirability. When dealing with a limited lookahead technique, the projected system behaviour is represented as a lookahead tree with some depth limit decided on by the user. It can be difficult to strike a balance between the complexities associated with storing and analyzing the trees and the amount of information available to make decisions, both of which increase with depth. This work also presents a set of methods which are designed to aid in accurately estimating the state space of lookahead trees with the intent of simplifying the process of determining a favourable depth to use. Finally, the approaches introduced herein are applied to a simulation of an infectious disease outbreak, primarily to showcase them in action, but also for the possibility of illuminating any useful information for real-world health units. / Thesis (Master, Computing) -- Queen's University, 2012-01-20 19:35:58.007

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The state-based approach plays an important role in modeling and control of Discrete-Event Systems (DES). Based on previous work, state feedback control of DES with nonblocking is thoroughly investigated; a general construction method for memory and the corresponding predicate is also specified. Two examples are provided in illustration. Also presented is state-based control of DES with observational abstraction. Based on the existing idea of quasi-congruence, quasi-observer, as a kind of observational abstraction, is developed; its advantages and limitations are discussed by means of simple examples. Imposing an observational partition on the state set also leads to observational abstraction. On this basis, the state-feedback controller design is introduced; in particular, the notion of high and low modeling levels for DES is proposed, based on which reachability and controllability are further discussed and compared. Finally, two simple applications are provided to show the advantage of observational partition in DES analysis and control.

The state-based approach plays an important role in modeling and control of Discrete-Event Systems (DES). Based on previous work, state feedback control of DES with nonblocking is thoroughly investigated; a general construction method for memory and the corresponding predicate is also specified. Two examples are provided in illustration. Also presented is state-based control of DES with observational abstraction. Based on the existing idea of quasi-congruence, quasi-observer, as a kind of observational abstraction, is developed; its advantages and limitations are discussed by means of simple examples. Imposing an observational partition on the state set also leads to observational abstraction. On this basis, the state-feedback controller design is introduced; in particular, the notion of high and low modeling levels for DES is proposed, based on which reachability and controllability are further discussed and compared. Finally, two simple applications are provided to show the advantage of observational partition in DES analysis and control.