Input Data Management (IDM) is a time consuming and costly process for Discrete Event Simulation (DES) projects. In this paper, a methodology for IDM in DES projects is described. The approach is to use a methodology to identify and collect data, then use an IDM software to extract and process the data. The IDM software will structure and present the data in Core Manufacturing Simulation Data (CMSD) format, which is aimed to be a standard data format for any DES software. The IDM methodology was previously developed and tested by Chalmers University of Technology in a case study in the automotive industry. This paper presents a second test implementation in a project at the National Institute of Standards and Technology (NIST) in collaboration with an aerospace industry partner. 1 INTRODUCTION Discrete Event Simulation (DES) has proved itself to be an effective tool for complex processes analysis (Ericsson 2005; Banks et al. 2000). The drawback of using DES is the effort required and costs spent on processing the input data from various data sources to ensure valid simulation results. Large amount of time in a DES project is needed for gathering and extracting data (Skoogh and Johansson 2007). Most of the time, the needed information can be found in various Information Technology systems (IT-systems) in the companies. However, data is usually not in the right format required for DES and IT-systems do not have a standardized way of communicating with each other. This makes it hard to integrate several ITsystems and DES software and hence customized interfaces for exchanging information often need to be developed. A reusable, neutral, standardized interface should help reduce the effort and cost related to Input Data Management (IDM) in DES projects (Johansson et al. 2007). Researchers at the National Institute of Standards and Technology (NIST) have developed the Core Manufacturing Simulation Data (CMSD) specification (SISO 2009) to create a neutral format between common production software applications and DES tools. The concept has already been tested in pilot implementations in some case studies (Heilala et al. 2008, Johansson, and Zachrisson 2006, Johansson et al. 2007). For example, the CMSD was used to generate input data that can be reused for DES models developed using both Enterprise Dynamics (ED) and Plant Simulation (Johansson et al. 2007).

Abstracf-The Homogeneous Charge Compression Ignition (HCCI) combustion concept lacks direct ignition timing control, instead the auto ignition depends on the operating condition. Since auto ignition of a homogeneous mixture is very sensitive to operating conditions, a fast combustion timing control is necessary for reliable operation. Hence, feedback is needed and the crank angle of SO% burnt (CASO) has proved to be a reliable feedback indicator of on-going combustion in practice. CAS0 or other methods for detecting on-going cylinder pressure used in the feedback control of a HCCI engine all rely on pressure sensors. This paper presents a new candidate for control of HCCI engine by using the electronic conductive properties in the reaction zone. This phenomenon is called ion current. This paper perform combustion timing control based on ion current and compare it with control based on pressure sensor. The combustion timing control is performed on cycle-to-cycle basis and the engine is a onecylinder version of a heavy duty engine equipped with a pori injection system using dual fuels.

deformed and transitional rareearth nuclei are considered in Section 2.1. The regimes of collective and single-particle rotation Obtained by cranking Of the Nilsson and Woods-Saxon sin@epartick potentials are surveyed in Section 2.2. Here it is found Collective properties at low and high spin for nuclei with Z 2 64 and N 2 82 are calculated on the basis of deformed single-particle potentials. m e calculations are confronted with the available experimental data like low-lying octupole bands, rotational bands of transitional nuclei with N 2 90 and evidence for collectivity in high-spin single-particle spectra. In the latter collective triaxiality and collective rotation perpendicular to the aligned spin are investigated by cranking and RF'A. Predicted regimes of different shapes and shape transitions at high spins are presented. In a gamma cascade calculation, it is shown how the calculated regimes for '$*Dy are consistent with the measured inclusive spectrum.

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Discrete Event Simulation (DES) is a powerful tool for efficiency improvements in production. However, instead of integrating the tool in the daily work of production engineers, companies apply it mostly in single-purpose studies such as major investment projects. One significant reason is the extensive timeconsumption for input data management, which has to be performed for every simulation analysis to avoid making decisions based upon obsolete facts. This paper presents an approach that combines automated raw data collection and automated processing of raw data to simulation information. MTConnect is used for collection of raw data and the GDM-Tool is applied for data processing. The purpose is to enable efficient reuse of DES models by reducing the time-consumption for input data management. Furthermore, the approach is evaluated using production data from the aerospace industry.