<p>In line with the company-wide CS09 project being carried out at Volvo CE Components, Cell 14 will have changes in terms of distribution of machines and parts routing to meet the lean manufacturing goals established.  These changes are of course dependant on future production volumes, as well as lot sizing and material handling considerations.</p><p>In this context, an important emphasis is given to the awareness of the performance measures that support decision making in these production development projects.  By using simulation as a confirmation tool, it is possible to re-assess these measures by testing the impact of changes in complex situations, in line with the lean manufacturing principles.</p><p>The aim of the project is to develop a discrete event simulation model following the methodology proposed by Banks et al (1999).  A model of Cell 14 will be built using the software Technomatix Plant Simulation ® which is used by the Company and the results from the simulation study will be analyzed.</p>

Fault isolation is the process of reasoning required to find the cause of a system failure. In a model-based approach, the available information is a model of the system and some observations. Using knowledge of how the system generally behaves, as given in the system model, together with partial observations of the events of the current situation the task is to deduce the failure causing event(s). In our setting, the observable events manifest themselves in a message log. We study post mortem fault isolation for moderately concurrent discrete event systems where the temporal order of logged messages contains little information. To carry out fault isolation one has to study the correlation between observed events and fault events of the system. In general, such study calls for exploration of the state space of the system, which is exponential in the number of system components. Since we are studying a restricted class of all possible systems we may apply aggressive specialized abstraction policies in order to allow fault isolation without ever considering the often intractably large state space of the system. In this thesis we describe a mathematical framework as well as a prototype implementation and an experimental evaluation of such abstraction techniques. The method is efficient enough to allow for not only post mortem fault isolation but also design time diagnosability analysis of the system, which can be seen as a non-trivial way of analyzing all possible observations of the system versus the corresponding fault isolation outcome. This work has been supported by VINNOVA’s Competence Center ISIS.

In line with the company-wide CS09 project being carried out at Volvo CE Components, Cell 14 will have changes in terms of distribution of machines and parts routing to meet the lean manufacturing goals established.  These changes are of course dependant on future production volumes, as well as lot sizing and material handling considerations. In this context, an important emphasis is given to the awareness of the performance measures that support decision making in these production development projects.  By using simulation as a confirmation tool, it is possible to re-assess these measures by testing the impact of changes in complex situations, in line with the lean manufacturing principles. The aim of the project is to develop a discrete event simulation model following the methodology proposed by Banks et al (1999).  A model of Cell 14 will be built using the software Technomatix Plant Simulation ® which is used by the Company and the results from the simulation study will be analyzed.

Dynamic balancing of computation and communication load is vital for the execution stability and performance of distributed, parallel simulations deployed on shared, unreliable resources of large-scale environments. High Level Architecture (HLA) based simulations can experience a decrease in performance due to imbalances that are produced initially and/or during run-time. These imbalances are generated by the dynamic load changes of distributed simulations or by unknown, non-managed background processes resulting from the non-dedication of shared resources. Due to the dynamic execution characteristics of elements that compose distributed simulation applications, the computational load and interaction dependencies of each simulation entity change during run-time. These dynamic changes lead to an irregular load and communication distribution, which increases overhead of resources and execution delays. A static partitioning of load is limited to deterministic applications and is incapable of predicting the dynamic changes caused by distributed applications or by external background processes. Due to the relevance in dynamically balancing load for distributed simulations, many balancing approaches have been proposed in order to offer a sub-optimal balancing solution, but they are limited to certain simulation aspects, specific to determined applications, or unaware of HLA-based simulation characteristics. Therefore, schemes for balancing the communication and computational load during the execution of distributed simulations are devised, adopting a hierarchical architecture. First, in order to enable the development of such balancing schemes, a migration technique is also employed to perform reliable and low-latency simulation load transfers. Then, a centralized balancing scheme is designed; this scheme employs local and cluster monitoring mechanisms in order to observe the distributed load changes and identify imbalances, and it uses load reallocation policies to determine a distribution of load and minimize imbalances. As a measure to overcome the drawbacks of this scheme, such as bottlenecks, overheads, global synchronization, and single point of failure, a distributed redistribution algorithm is designed. Extensions of the distributed balancing scheme are also developed to improve the detection of and the reaction to load imbalances. These extensions introduce communication delay detection, migration latency awareness, self-adaptation, and load oscillation prediction in the load redistribution algorithm. Such developed balancing systems successfully improved the use of shared resources and increased distributed simulations' performance.

Fault diagnosis in discrete event systems is studied using a state-based framework. Faults can be either intermittent or permanent. For intermittent faults, system may recover from faulty behaviour through reset. To diagnose such intermittent faults, fault counters are introduced. Fault counters record the number of intermittent faults which must have occurred according to the output observations. This provides the main diagnosis. They also record the number of possible intermittent faults which may have occurred but cannot be confirmed. This provides auxiliary diagnostic information. Fault diagnosability is then studied. Since faults may be intermittent, they may occur repeatedly. Three different notions are studied: 1-diagnosability, 1,k-diagnosability, and 1,infty-diagnosability, and criteria for each of these notions are obtained. The criteria are expressed in terms of fault counters and extend the diagnosability criteria for permanent faults. The concept of a resonant path is introduced, which plays an important role in studying diagnosability.

Fault diagnosis in discrete event systems is studied using a state-based framework. Faults can be either intermittent or permanent. For intermittent faults, system may recover from faulty behaviour through reset. To diagnose such intermittent faults, fault counters are introduced. Fault counters record the number of intermittent faults which must have occurred according to the output observations. This provides the main diagnosis. They also record the number of possible intermittent faults which may have occurred but cannot be confirmed. This provides auxiliary diagnostic information. Fault diagnosability is then studied. Since faults may be intermittent, they may occur repeatedly. Three different notions are studied: 1-diagnosability, 1,k-diagnosability, and 1,infty-diagnosability, and criteria for each of these notions are obtained. The criteria are expressed in terms of fault counters and extend the diagnosability criteria for permanent faults. The concept of a resonant path is introduced, which plays an important role in studying diagnosability.

Increasing competition from traditional and emerging channels has placed new emphasis on rapid innovation and continuous differentiation in every aspect of supply chain, from earliest production stage to the final distribution steps. To bridge the gap between brilliant ideas and successful business initiatives, leading companies implement engineering simulation particularly in logistics and supply chain management (LSCM). Discrete event simulation (DES) and system dynamics (SD) are two modeling approaches widely used in this field. However there are not much done researches about the applications of these simulation approaches in supply chain context of Swedish Manufacturing Industries (SMI). This study explores the application of DES and SD in LSCM of SMI by looking at the nature and level of issues modeled. Journal papers and master theses that use these modeling approaches to study supply chains, published between 1990 and 2012 are reviewed. A total of 39 articles are analyzed to identify the frequency with which the two simulation approaches are used as modeling tools in LSCM of SMI. Our findings suggest that DES has been used more frequently to model supply chains in SMI. The results also show that not all the LSCM issues have been addressed evenly and generally tactical/operational issues have been modeled more frequently. The results of this study inform the existing literature about the use of DES and SD in LSCM of SMI.

The creation of large-scale simulation models is a difficult and time-consuming task. Yet simulation is one of the techniques most frequently used by practitioners in Operations Research and Industrial Engineering, as it is less limited by modeling assumptions than many analytical methods. The effective generation of simulation models is an important challenge. Due to the rapid increase in computing power, it is possible to simulate significantly larger systems than in the past. However, the verification and validation of these large-scale simulations is typically a very challenging task. This thesis introduces a simulation framework that can generate a large variety of manufacturing simulation models. These models have to be described with a simulation data specification. This specification is then used to generate a simulation model which is described as a Petri net. This approach reduces the effort of model verification. The proposed Petri net data structure has extensions for time and token priorities. Since it builds on existing theory for classical Petri nets, it is possible to make certain assertions about the behavior of the generated simulation model. The elements of the proposed framework and the simulation execution mechanism are described in detail. Measures of complexity for simulation models that are built with the framework are also developed. The applicability of the framework to real-world systems is demonstrated by means of a semiconductor manufacturing system simulation model.

The problem of overcrowding is one of the serious issues that almost every emergency department (ED) in Taiwan has to face on daily basis. ED crowding results in adverse medical outcomes, decline in quality of care, and lack of the ability to provide instant medical care. One of the viable (but not necessarily preferable) solutions to ED overcrowding is ambulance diversion (AD). That is, ambulances would bypass the ED¡¦s unable to provide emergency medical service, and send patients to another emergency department. In many medical systems, ambulance diversion is being seen as a standard operating procedure, whose effectiveness needs to be carefully studied before making a sound policy. In this research, an input-throughput-output simulation model is proposed for simulating ED operation. A computer simulation program is developed based on this model to evaluate various AD initiating criteria, patient-blocking rules, and AD intervals. The crowdedness index, the patient waiting time for service, and the percentage of adverse patients were assessed to determine the impact of various AD policies. By appropriate parameter settings, this simulation model can represent medical resource providers of different scales. The results we obtained may offer insights for making effective AD policies.

Efficient management of blood throughout the countries is of great economic importance, in addition to its major impact on the success of medical operations. This study is concerned with the analysis of policies for managing a unique blood supply chain network, which is defined in the new Blood and Blood Products Law of the Republic of Turkey. The main objective of the study is to obtain a better understanding of the system, and to find improved policies to be able to manage it efficiently. A discrete event simulation model is developed to analyze the blood supply chain of a pilot region in Turkey. Effects of different management policies on the supply chain performance are analyzed. Important improvements are achieved in terms of the selected performance measures such as outdate, mismatch and shortage rates of the region. Our proposed model can be used by both national health authorities and the Turkish Red Crescent Society as a decision support tool to analyze other regions and to examine alternative policies.