This dissertation investigated issues surrounding grain harvest and transportation logistics. A discrete event simulation model of grain transportation from the field to an on-farm storage facility was developed to evaluate how truck and driver resource constraints impact material flow efficiency, resource utilization, and system throughput. Harvest rate and in-field transportation were represented as a stochastic entity generation process, and service times associated with various material handling steps were represented by a combination of deterministic times and statistical distributions. The model was applied to data collected for three distinct harvest scenarios (18 total days). The observed number of deliveries was within ± 2 standard deviations of the simulation mean for 15 of the 18 input conditions examined, and on a daily basis, the median error between the simulated and observed deliveries was -4.1%. The model was expanded to simulate the whole harvest season and include temporary wet storage capacity and grain drying. Moisture content changes due to field dry down was modeled using weather data and grain equilibrium moisture content relationships and resulted in an RMSE of 0.73 pts. Dryer capacity and performance were accounted for by adjusting the specified dryer performance to the observed level of moisture removal and drying temperature. Dryer capacity was generally underpredicted, and large variations were found in the observed data. The expanded model matched the observed cumulative mass of grain delivered well and estimated the harvest would take one partial day longer than was observed. Usefulness of the model to evaluate both costs and system performance was demonstrated by conducting a sensitivity analysis and examining system changes for a hypothetical operation. A dry year and a slow drying crop had the largest impact on the system’s operating and drying costs (12.7% decrease and 10.8% increase, respectively). The impact of reducing the drying temperature to maintain quality in drying white corn had no impact on the combined drying and operating cost, but harvest took six days longer. The reduced drying capacity at lower temperatures resulted in more field drying which counteracted the reduced drying efficiency and increased field time. The sensitivity analysis demonstrated varied benefits of increased drying and transportation capacity based on how often these systems created a bottleneck in the operation. For some combinations of longer transportation times and higher harvest rates, increasing hauling and drying capacity could shorten the harvest window by a week or more at an increase in costs of less than $12 ha-1. An additional field study was conducted to examine corn harvest losses in Kentucky. Total losses for cooperator combines were found to be between 0.8%-2.4% of total yield (86 to 222 kg ha-1). On average, the combine head accounted for 66% of the measured losses, and the total losses were highly variable, with coefficients of variation ranging from 21.7% to 77.2%. Yield and harvest losses were monitored in a single field as the grain dried from 33.9% to 14.6%. There was no significant difference in the potential yield at any moisture level, and the observed yield and losses displayed little variation for moisture levels from 33.9% to 19.8%, with total losses less than 1% (82 to 130 kg dry matter ha-1). Large amounts of lodging occurred while the grain dried from 19.8% to 14.6%, which resulted in an 18.9% reduction in yield, and harvest losses in excess of 9%. Allowing the grain to field dry generally improved test weight and reduced mechanical damage, however, there was a trend of increased mold and other damage in prolonged field drying.

The research described in this thesis is aimed to improve our knowledge of barriers to the use of OR (Operations Research) techniques in the manufacturing sector. Numerous issues have been previously identified, but the work has generally been unsystematic, or focused on the OR profession. This research is empirical, systematic, and compares a group of OR professionals to a group of manufacturing managers. The technology selected for analysis was DES (Discrete event simulation, a computer based technique for modeling complex manufacturing processes), and the companies chosen, as the focus for data collection, were based in Australia. Two major implications for practice are identified in the thesis. These two perspectives should be seen to be complementary, rather than opposing. OR professionals should place their knowledge within the mindset used by manufacturing managers, rather than attempting to displace that mindset. / Doctor of Philosophy (PhD)

<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>

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.

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.

Power quality has a great effect on the operation of system loads. To analyze its effects and the possible economic losses due to system disturbances, there is an immediate need of a power quality monitoring system. With an effective communication system, network disturbance data can be gathered and analyzed efficiently such that outage duration and its consequent losses can be reduced. This thesis presents communication network performance simulation results of different types of communication schemes used in a power quality monitoring system. Discrete event simulation method is used to study the end-to-end delay times of different communication architectures. Based on these simulation results, system designers can choose the best option to meet their data communication requirements in power quality monitoring.

Multi-core architectures are becoming more common and core counts continue to increase. There are six- and eight-core chips currently in production, such as Intel Gulftown, and many-core chips with dozens of cores, such as the Intel Teraflops 80-core chip, are projected in the next five years. However, adding more cores often does not improve the performance of applications. It would be desirable to take advantage of the multi-core environment to speed up parallel discrete event simulation. The current bottleneck for many parallel simulations is time synchronization. This is especially true for simulations of wireless networks and on-chip networks, which have low lookahead. Message passing is also a common simulation bottleneck. In order to address the issue of time synchronization, we have designed hardware at a functional level that performs the time synchronization for parallel discrete event simulation asynchronously and in just a few clock cycles, eliminating the need for global communication with message passing or lock contention for shared memory. This hardware, the Global Synchronization Unit, consists of 3 register files, each the size of the number of cores, and is accessed using 5 new atomic instructions. In order to reduce the simulation overhead from message passing, we have also designed two independent pieces of hardware at a functional level, the Atomic Shared Heap and Atomic Message Passing, which can be used to perform lock-free, zero-copy message passing on a multi-core system. The impact of these specialized hardware units on the performance of parallel discrete event simulation is assessed and compared to traditional shared-memory techniques.