Integrated Project Support Study Group : findings

The challenges of the LHC project have lead CERN to produce a comprehensive set of project management tools covering engineering data management, project scheduling and costing, event management and document management. Each of these tools represents a significant and world-recognised advance in their respective domains. Reviewing the offering on the eve of LHC commissioning one can identify three major challenges: 1. How to integrate the tools to provide a uniform and integrated full-product lifecycle solution 2. How to evolve the functionality in certain areas to address weaknesses identified with our experience in constructing the LHC and integrate emerging industry best practices 3. How to coherently package the offering not just for future projects in CERN, but moreover in the context of providing a centre of excellence for worldwide collaboration in future HEP projects

Decision support system for building information modeling (BIM) software selection: A case study in construction feasibility stage

The adoption of Building Information Modelling (BIM) software has proven to be beneficial to the construction industry to improve the design, analysis, construction, operation and data management. Due to the variety of BIM software on the market, choosing the right BIM software in construction projects is deemed to be a complicated decision making process. Previous studies revealed that software selection is mainly made based on popularity and recommendation from other companies. Consequently, inaccurate selection would lead to the underutilised features and negative effect the investment on the BIM software. Based on literature, there is a lack of systematic approach to select the right BIM software for specific project requirements. This highlights the needs for decision making tools to select the appropriate BIM software. This research aims to develop a Decision Support System (DSS) named topsis4BIM which integrates graphical user interfaces, BIM features database, Fuzzy TOPSIS and Web 2.0 tools. A real construction project was used as a case study for demonstrating and validating the DSS framework. The findings indicate that the use of topsis4BIM improves the BIM software selection process compared to the current practice. In addition, it also produce a new framework for the next generation DSS using Web 2.0 tools. The study introduces an innovative and economical decision making approach that can guide construction practitioners towards the betterment of BIM adoption

Ubiquitous Manufacturing Requirements for Product Data Management

Ubiquitous manufacturing rather straightforwardly means the usage and utility of ubiquitous computing concepts and technologies in manufacturing. Simply put this means embedding more intelligence into objects of the production line, making them communicate and using all data this generates to further enhance the functionality and visibility of the production. The study is structured into theory and empirical sections. Theory part is a literature review for defining the concepts of ubiquitous computing, product data management and ubiquitous manufacturing. Along with the definition of ubiquitous manufacturing, ubiquitous computing ideas are used to build ubiquitous manufacturing concepts. These definitions and concepts are then used as a foundation for defining the requirements that the ubiquitous manufacturing sets on product data management. The requirement definition mainly studies the role and availability of product information, regarding different phases and aspects of the product and its manufacturing. In the empirical part of the study a data model is built for product structure management, which aims to fulfill the needs and requirements posed in the theory section of the study. The developed data model is also put into test in a case study section, where a pilot production line, that realizes single ubiquitous manufacturing concept, is built at The Technical Research Centre of Finland VTT. The conclusion of the study discusses the implications of the study and of ubiquitous manufacturing in general. The study concludes that one of the key possibilities of ubiquitous computing in manufacturing environment is the development of product data management to the level of real-world single item management. This real-time information of singular items enables development of production through better controllability, monitoring and optimization. In a ubiquitous manufacturing concept such as this, the main requirements for PDM are real-time singular level information management, and possibility to model product manufacturing phases in addition to modeling products./Kir11Ubiikilla valmistuksella tarkoitetaan varsin suoraviivaisesti jokapaikan tietotekniikan käyttöä valmistuksen apuna. Yksinkertaisesti tämä tarkoittaa tiedon ja älyn lisäämistä tuotantolinjan kappaleisiin, kuten työkaluihin ja komponentteihin, näiden kappaleiden välistä kommunikointia sekä tästä syntyvän uuden tiedon käyttämistä toiminnan analysoimiseen ja kehittämiseen. Tämän työn pääasiallinen sisältö on tutkia millaisia vaatimuksia ubiikki valmistus aiheuttaa tuotetiedonhallinnalle. Työ jakautuu teoria- ja empiriaosuuksiin. Teoriaosuudessa aihetta lähestytään kirjallisuusselvityksen keinoin ubiikin tietotekniikan ja tuotetiedonhallinnan määrittelyn ja vaatimusten kautta, siirtyen lopulta ubiikkiin valmistukseen. Samalla tutkitaan lyhyesti ubiikin tietotekniikan mahdollistamia konsepteja ja uusia toimintatapoja valmistusympäristöissä. Näiden konseptien pohjalta tehdään vaatimusmäärittely siitä, mitä vaatimuksia ubiikki valmistus aiheuttaa tiedonhallinnalle ja etenkin tuotetiedonhallinnalle. Empiriaosuudessa muotoillaan tuotteelle tietorakenne, joka vastaa ubiikin valmistuksen tarpeisiin ja vaatimuksiin. Tätä tuotteen tietorakennetta testataan vielä lyhyesti case-tutkimuksena toteuttamalla Teknologian Tutkimuskeskus VTT:n Espoon tiloissa kokeellinen tuotantolinja, johon on liitetty ubiikkia toiminnallisuutta. Lopuksi työssä käsitellään vielä tutkimuksen tuloksia sekä ubiikin tuotannon vaatimuksia ja mahdollisuuksia yleensä ottaen. Keskeisinä ubiikin valmistuksen mahdollisuuksina työssä nousee esille tuotetiedonhallinnan kehittäminen jokapaikan teknologioiden avulla reaalimaailman kappalekohtaiselle tasolle, jossa on keskeistä erottaa, mitä tietoa kustakin yksittäisestä tuotteesta talletetaan millekin tasolle. Tämä reaaliaikainen kappalekohtainen tiedonhallinta mahdollistaa tuotannon tehostamisen muun muassa paremman ohjattavuuden, optimoinnin sekä tarkkailun kautta. Tällöin tuotetiedonhallinnalle asetettuja päävaatimuksia ovatkin juuri reaaliaikainen kappalekohtainen toiminta sekä valmius mallintaa itse tuotteiden lisäksi myös tuotteiden valmistusvaiheit

The purposes of performance dashboard use: A case of a procurement performance management SaaS provider.

Objectives of the Study The main objective of this study is to find out how do end-users of the Case Company use performance dashboards to support decisions for measuring and managing procurement performance. Academic background and methodology Performance dashboards are a type of performance management system that brings together key performance metrics of an organisation or an individual on one display. A visual interface of performance dashboards is just a small part of what most users see. However, this information system for decision support is built on business intelligence technology as well as performance management and measurement principles. The relevant theory on performance dashboards, procurement performance management based and instruments of evaluating Information System Use were reviewed. Furthermore, a case study in the form of an online survey and semi-structured interviews was conducted with three client companies of the Case Company that provides its procurement performance management dashboards on software as a service basis. The Doll and Torkzadeh's tool for multidimensional measurement of system-use was applied in an online survey to identify usage purposes. The results from the survey were qualitatively confirmed and enriched with the evidence from the semi-structured interviews conducted with the selected end-users. Findings and conclusions The main finding of the research was that the Case Company's application was most extensively used by strategic level employees, primarily for communication and decision rationalizing purposes. Moreover, the application is most valued by the client companies for enabling a consolidated view on purchasing by integrating data from different sources of an organisation; its ability to tackle an analysis of direct and especially indirect spend; and its function as a convenient communication platform between different business and geographical units of an organisation

The effect of faculty performance measurement systems on student retention

Institutions of higher learning have been tracking student course-drop rates as a measure of student success along with faculty performance data. However, there is a lack of understanding as to how faculty performance data influences drop rates. The purpose of this study was to determine whether faculty knowledge of performance data creates a difference in drop rates. This study combined theories of performance measurement, decision support, self-determination theory (SDT), and personal decision making (PDM) as a conceptual foundation that linked faculty knowledge to student success. The specific research question addressed if data can be used to assist faculty efforts in reducing student attrition. This experimental longitudinal study tested the effect of faculty knowledge of personal performance measures on student course-drop rates. A sample of 32 subjects from a major university were randomly selected and assigned to equivalent-groups that included an experimental group, which received performance feedback and instruction, and an uninformed control group. Paired sample t-tests indicated a significant 32.8% reduction in student attrition for faculty in the experimental group, compared to a 10.3% increase in attrition observed for the control group faculty. Results suggest that providing faculty access to performance data via a decision support system will result in a reduction of student course drop rates. The key social value for this study is to provide a blueprint in collecting, structuring, and disseminating data that assist faculty and institutions in addressing student persistence. Students who persist in their courses have a greater potential of completing their studies and thus gaining access to better paying careers, higher levels of self-esteem, and an overall improved quality of life

Building a Strong Undergraduate Research Culture in African Universities

Africa had a late start in the race to setting up and obtaining universities with research quality fundamentals. According to Mamdani [5], the first colonial universities were few and far between: Makerere in East Africa, Ibadan and Legon in West Africa. This last place in the race, compared to other continents, has had tremendous implications in the development plans for the continent. For Africa, the race has been difficult from a late start to an insurmountable litany of problems that include difficulty in equipment acquisition, lack of capacity, limited research and development resources and lack of investments in local universities. In fact most of these universities are very recent with many less than 50 years in business except a few. To help reduce the labor costs incurred by the colonial masters of shipping Europeans to Africa to do mere clerical jobs, they started training ―workshops‖ calling them technical or business colleges. According to Mamdani, meeting colonial needs was to be achieved while avoiding the ―Indian disease‖ in Africa -- that is, the development of an educated middle class, a group most likely to carry the virus of nationalism. Upon independence, most of these ―workshops‖ were turned into national ―universities‖, but with no clear role in national development. These national ―universities‖ were catering for children of the new African political elites. Through the seventies and eighties, most African universities were still without development agendas and were still doing business as usual. Meanwhile, governments strapped with lack of money saw no need of putting more scarce resources into big white elephants. By mid-eighties, even the UN and IMF were calling for a limit on funding African universities. In today‘s African university, the traditional curiosity driven research model has been replaced by a market-driven model dominated by a consultancy culture according to Mamdani (Mamdani, Mail and Guardian Online). The prevailing research culture as intellectual life in universities has been reduced to bare-bones classroom activity, seminars and workshops have migrated to hotels and workshop attendance going with transport allowances and per diems (Mamdani, Mail and Guardian Online). There is need to remedy this situation and that is the focus of this paper

Textual data mining applications for industrial knowledge management solutions

In recent years knowledge has become an important resource to enhance the business and many activities are required to manage these knowledge resources well and help companies to remain competitive within industrial environments. The data available in most industrial setups is complex in nature and multiple different data formats may be generated to track the progress of different projects either related to developing new products or providing better services to the customers. Knowledge Discovery from different databases requires considerable efforts and energies and data mining techniques serve the purpose through handling structured data formats. If however the data is semi-structured or unstructured the combined efforts of data and text mining technologies may be needed to bring fruitful results. This thesis focuses on issues related to discovery of knowledge from semi-structured or unstructured data formats through the applications of textual data mining techniques to automate the classification of textual information into two different categories or classes which can then be used to help manage the knowledge available in multiple data formats. Applications of different data mining techniques to discover valuable information and knowledge from manufacturing or construction industries have been explored as part of a literature review. The application of text mining techniques to handle semi-structured or unstructured data has been discussed in detail. A novel integration of different data and text mining tools has been proposed in the form of a framework in which knowledge discovery and its refinement processes are performed through the application of Clustering and Apriori Association Rule of Mining algorithms. Finally the hypothesis of acquiring better classification accuracies has been detailed through the application of the methodology on case study data available in the form of Post Project Reviews (PPRs) reports. The process of discovering useful knowledge, its interpretation and utilisation has been automated to classify the textual data into two classes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Metodología de implantación de modelos de gestión de la información dentro de los sistemas de planificación de recursos empresariales. Aplicación en la pequeña y mediana empresa

La Siguiente Generación de Sistemas de Fabricación (SGSF) trata de dar respuesta a los requerimientos de los nuevos modelos de empresas, en contextos de inteligencia, agilidad y adaptabilidad en un entono global y virtual. La Planificación de Recursos Empresariales (ERP) con soportes de gestión del producto (PDM) y el ciclo de vida del producto (PLM) proporciona soluciones de gestión empresarial sobre la base de un uso coherente de tecnologías de la información para la implantación en sistemas CIM (Computer-Integrated Manufacturing), con un alto grado de adaptabilidad a la estnictura organizativa deseada. En general, esta implementación se lleva desarrollando hace tiempo en grandes empresas, siendo menor (casi nula) su extensión a PYMEs. La presente Tesis Doctoral, define y desarrolla una nueva metodología de implementación pan la generación automática de la información en los procesos de negocio que se verifican en empresas con requerimientos adaptados a las necesidades de la SGSF, dentro de los sistemas de gestión de los recursos empresariales (ERP), atendiendo a la influencia del factor humano. La validez del modelo teórico de la metodología mencionada se ha comprobado al implementarlo en una empresa del tipo PYME, del sector de Ingeniería. Para el establecimiento del Estado del Arte de este tema se ha diseñado y aplicado una metodología específica basada en el ciclo de mejora continua de Shewhart/Deming, aplicando las herramientas de búsqueda y análisis bibliográfico disponibles en la red con acceso a las correspondientes bases de datos