The requirements and needs of global data usage in product lifecycle management

This study was done for ABB Ltd. Motors and Generators business unit in Helsinki. In this study, global data movement in large businesses is examined from a product data management (PDM) and enterprise resource planning (ERP) point-of-view. The purpose of this study was to understand and map out how a large global business handles its data in a multiple site structure and how it can be applied in practice. This was done by doing an empirical interview study on five different global businesses with design locations in multiple countries. Their master data management (MDM) solutions were inspected and analyzed to understand which solution would best benefit a large global architecture with many design locations. One working solution is a transactional hub which negates the effects of multisite transfers and reduces lead times. Also, the requirements and limitations of the current MDM architecture were analyzed and possible reform ideas given.  

management as a part of product lifecycle management

Tässä työssä käsitellään maailmanlaajuisen paperi- ja sellutehtaille laitteita toimittavan yrityksen Andritz:in dokumenttien hallintaa, keskittyen lähinnä yrityksen service- liiketoiminnan ja tuotteen elinkaaren hallinnan tarpeisiin. Tarkoituksena on selvittää kuinka aikaisemmin yritykselle muihin tarkoituksiin valittu dokumenttien hallinta-järjestelmä sopii Service-liiketoiminnan tarpeisiin. Työ perustuu kirjallisuutteen sekä tekijän työn ohella sekä haastatteluin keräämään näkemykseen liiketoiminnasta tällä alalla. Työssä käsitellään yleisellä tasolla dokumenttien hallintajärjestelmiä, niiden rakennetta ja perusominaisuuksia, sekä esitellään markkinoilla olevia erityylisiä ratkaisuja. Työssä esitellään myös Andritz:in dokumenttien hallinnan nykytilaa, tuotteen elinkaaren päävaiheet, dokumenttien hallinnan merkitys niissä ja nykyisin käytössä oleva dokumenttien hallintajärjestelmä. Näiden rinnalla pyritään tuomaan esille Service- liiketoiminnan erityispiirteet ja tarpeet dokumenttien hallinnalle niiden kannalta. Työhön on sisällytetty myös käytännön esimerkki dokumenttien hallinnasta suuressa käynnissä olevassa projektissa. Projektissa käytetään dokumenttihotelli palvelua dokumenttien projektin aikaiseen hallintaan. Hotellissa olevat dokumentit tulee siirtää myös Andritzin omaan järjestelmään, tämä siirto on tehty osana työtä.

The Design of a Software Lifecycle Management Framework to a Configuration Management System

Keeping track of software assets and managing software installations in IT environments can be a hard endeavor, especially when the size and diversity of the environment grows. How to install and uninstall software efficiently and cost effectively? Are there too few or too many software licenses purchased? If installed, is the software actually in use? Software Asset Management (SAM) is a process that involves managing and optimizing the purchase, deployment, maintenance, utilization, and disposal of software applications within an organization. This master’s thesis describes a special Software Lifecycle Management Framework to provide solutions to the multitude of challenges within SAM. The main objectives when designing the framework was to provide a set of tools to control the software assets during their entire lifecycle while trying to minimize the costs related to owning and managing them.

Master data quality management in a global enterprise

In a networked business environment the visibility requirements towards the supply operations and customer interface has become tighter. In order to meet those requirements the master data of case company is seen as an enabler. However the current state of master data and its quality are not seen good enough to meet those requirements. In this thesis the target of research was to develop a process for managing master data quality as a continuous process and find solutions to cleanse the current customer and supplier data to meet the quality requirements defined in that process. Based on the theory of Master Data Management and data cleansing, small amount of master data was analyzed and cleansed using one commercial data cleansing solution available on the market. This was conducted in cooperation with the vendor as a proof of concept. In the proof of concept the cleansing solution’s applicability to improve the quality of current master data was proved. Based on those findings and the theory of data management the recommendations and proposals for improving the quality of data were given. In the results was also discovered that the biggest reasons for poor data quality is the lack of data governance in the company, and the current master data solutions and its restrictions.

Migration data collection, management, sharing in the Caribbean

Includes bibliography

Design and implementation of a testbed for data distribution management

Data Distribution Management (DDM) is a core part of High Level Architecture standard, as its goal is to optimize the resources used by simulation environments to exchange data. It has to filter and match the set of information generated during a simulation, so that each federate, that is a simulation entity, only receives the information it needs. It is important that this is done quickly and to the best in order to get better performances and avoiding the transmission of irrelevant data, otherwise network resources may saturate quickly. The main topic of this thesis is the implementation of a super partes DDM testbed. It evaluates the goodness of DDM approaches, of all kinds. In fact it supports both region and grid based approaches, and it may support other different methods still unknown too. It uses three factors to rank them: execution time, memory and distance from the optimal solution. A prearranged set of instances is already available, but we also allow the creation of instances with user-provided parameters. This is how this thesis is structured. We start introducing what DDM and HLA are and what do they do in details. Then in the first chapter we describe the state of the art, providing an overview of the most well known resolution approaches and the pseudocode of the most interesting ones. The third chapter describes how the testbed we implemented is structured. In the fourth chapter we expose and compare the results we got from the execution of four approaches we have implemented. The result of the work described in this thesis can be downloaded on sourceforge using the following link: https://sourceforge.net/projects/ddmtestbed/. It is licensed under the GNU General Public License version 3.0 (GPLv3).

Implementazione ed analisi di un framework basato su Cloud per la valutazione di algoritmi di data Distribution Management

Il Data Distribution Management (DDM) è un componente dello standard High Level Architecture. Il suo compito è quello di rilevare le sovrapposizioni tra update e subscription extent in modo efficiente. All'interno di questa tesi si discute la necessità di avere un framework e per quali motivi è stato implementato. Il testing di algoritmi per un confronto equo, librerie per facilitare la realizzazione di algoritmi, automatizzazione della fase di compilazione, sono motivi che sono stati fondamentali per iniziare la realizzazione framework. Il motivo portante è stato che esplorando articoli scientifici sul DDM e sui vari algoritmi si è notato che in ogni articolo si creavano dei dati appositi per fare dei test. L'obiettivo di questo framework è anche quello di riuscire a confrontare gli algoritmi con un insieme di dati coerente. Si è deciso di testare il framework sul Cloud per avere un confronto più affidabile tra esecuzioni di utenti diversi. Si sono presi in considerazione due dei servizi più utilizzati: Amazon AWS EC2 e Google App Engine. Sono stati mostrati i vantaggi e gli svantaggi dell'uno e dell'altro e il motivo per cui si è scelto di utilizzare Google App Engine. Si sono sviluppati quattro algoritmi: Brute Force, Binary Partition, Improved Sort, Interval Tree Matching. Sono stati svolti dei test sul tempo di esecuzione e sulla memoria di picco utilizzata. Dai risultati si evince che l'Interval Tree Matching e l'Improved Sort sono i più efficienti. Tutti i test sono stati svolti sulle versioni sequenziali degli algoritmi e che quindi ci può essere un riduzione nel tempo di esecuzione per l'algoritmo Interval Tree Matching.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

Data consistency management in an open smart home management platform

In this paper, the authors introduce a novel mechanism for data management in a middleware for smart home control, where a relational database and semantic ontology storage are used at the same time in a Data Warehouse. An annotation system has been designed for instructing the storage format and location, registering new ontology concepts and most importantly, guaranteeing the Data Consistency between the two storage methods. For easing the data persistence process, the Data Access Object (DAO) pattern is applied and optimized to enhance the Data Consistency assurance. Finally, this novel mechanism provides an easy manner for the development of applications and their integration with BATMP. Finally, an application named "Parameter Monitoring Service" is given as an example for assessing the feasibility of the system.