Visual Components (Finland)

Abstract Aircraft assembly is a complex process associated with different stakeholders, which strongly impacts the R&D cost for the entire aircraft lifecycle management. Traditional aircraft assembly process is designed based on a document-centric approach which cannot provide graphical notations for engineers to understand the entire assembly process. Moreover, it is difficult to make use of simulation to analyze the assembly process in an automatic way that increases the R&D cost for the assembly process design. In this paper, a semantic modeling approach is proposed to support aircraft assembly process formalism and performance analysis of the entire assembly process. First, semantic modeling language KARMA is used to develop meta-models based on the basic elements of discrete event simulation model for aircraft assembly process modeling. After KARMA models are developed, ontology model is generated from KARMA models for implementing the automatic simulation execution by using the discrete event simulation.KeywordsModel-based systems engineeringSemantic modelingKARMA languageDiscrete event simulationAircraft assembly

Logistics management plays an essential role in supporting the primary activities in manufacturing industries. Similarly, in the construction industry, logistics operations are a crucial part that directly influence the construction operations. Construction operations management requires various stakeholders to collaborate through effective communication and prompt information sharing. However, logistics management in construction is often challenged by insufficient information management, lack of formalized information standards and poor information interoperability among heterogeneous systems. Semantic Web technologies advance information management support and improve information interoperability. In this research, we present a domain-level ontology as a common information reference for standardizing and integrating construction logistics information, and finally to improve the efficiency and transparency of logistics information management. The proposed ontology provides information interoperability between logistics management and construction workflow management. The ontology was evaluated by automatic consistency checking and answering the competency questions (CQs) via SPARQL queries. Furthermore, we used actual schedule and material delivery data of a construction project to evaluate the proposed ontology to see if it could support the material kitting logistics practice. We provide a valid ontology that is able support the logistics information management for the construction. The research is limited to providing a single example application of the ontology. Future research should focus on extending the ontology for different specific solutions to yield standardized information management for construction operations.

A single isolated ski was suspended from a six-component wind tunnel balance and three angles, the angle of attack, the yaw angle and the edge angle were adjustable during the test. Increasing yaw angle from 0 to 15° increased the lift coefficient CL from 0.42 to 0.90 at edge angle 0° and from 0.70 to 0.87 at edge angle 10°, respectively. Increasing yaw angle also increased the sensitivity of the ski to changes in edge angle, i.e., increasing the edge angle (20°–45°) decreased the CL and the ratio C_{L}^{2}/{C_D} with large yaw angles. However, to maximize the lift-to-drag ratio with a typical angle of attack of 30° in ski jumping, it may be reasonable to have an edge angle of 5°–10° on skis as the ratio C_{L}^{2}/{C_D} increased from 1.24 to 1.35 when edge angle increased from 0° to 10°.

Manufacturing is a critical industry for all major economies. Every individual and industry depends on manufactured goods, which makes manufacturing crucial to the national economies. Competition is increasingly hard and globalization is leading to worldwide distribution of production, products and services, affecting all countries and economical regions. At the same time, markets are changing. Customers call for faster product changes and demand products, which are increasingly targeted to individual needs. Mass production is therefore replaced by customised and personalised production of individual products.\nDistributed simulation has the potential to become widely applicable for geographically-dispersed manufacturing environments, as is the case with desktop manufacturing or rapidly deployable micro-assembly stations. This thesis focuses on creating a generic framework that permits the distribution of manufacturing simulations, which was one of the goals of the MS2Value (Modeling and Simulation of Manufacturing Systems for Value Chains) project.\nCompanies, nowadays, normally have their activities and resources geographically dispersed, which represents a challenge for the reusability and interconnection of their manufacturing simulation models. Different approaches have been taken by different communities like the research and military community, but no solution has been presented yet in the manufacturing field.\nThe thesis work presented here proposes the use of the HLA (High Level Architecture) in combination with a simulation software as a solution to these problems. This proposal is demonstrated by an implementation of a distributed simulation using 3DCreate and an open source RTI (Runtime Infrastructure). /Kir10

Accurate anatomical localisation of abnormalities observed in brain perfusion single-photon emission computed tomography (SPECT) is difficult, but can be improved by correlating data from SPECT and other tomographic imaging modalities. For this purpose we have developed software to register, analyse and display 99mTc-hexamethylpropyleneamine oxime SPECT and 1.0 T MRI of the brain. For registration of SPECT and MRI data external skin markers containing 99mTc (220 kBq) in 50 microliters of coconut butter were used. The software is coded in the C programming language, and the X Window system and the OSF/Motif standards are used for graphics and definition of the user interface. The registration algorithm follows a noniterative least-squares method using singular value decomposition of a 3 x 3 covariance matrix. After registration, the image slices of both data sets are shown at identical tomographic levels. The registration error in phantom studies was on average 4 mm. In the two-dimensional display mode the orthogonal cross-sections of the data sets are displayed side by side. In the three-dimensional mode MRI data are displayed as a surface-shaded 3 D reconstruction and SPECT data as cut planes. The usefulness of this method is demonstrated in patients with cerebral infarcts, brain tumour, herpes simplex encephalitis and epilepsy.