BIM Integrated and Reference Process-based Simulation Method for Construction Project Planning

Die Verwendung von Simulationen zur Unterstützung traditioneller Planungsverfahren für Bauprojekte hat viele Vorteile, die in verschiedenen akademischen Forschungen vorgestellt wurden. Viele Anwendungen haben erfolgreich das Potenzial der Simulationsmethode zur Verbesserung der Qualität der Projektplanung demonstriert. Doch eine breite Anwendung der Simulationsmethoden zur Unterstützung der Planung von Bauprojekten konnte sich in der Praxis bis zum jetzigen Zeitpunkt nicht durchsetzen. Aufgrund einiger großer Hindernisse und Herausforderungen ist der Einsatz im Vergleich zu anderen Branchen noch sehr begrenzt. Die Komplexität sowie die dynamischen Wechselprozesse der unterschiedlichen Bauvorhaben stellen die erste Herausforderung dar.Die Anforderungen machen es sehr schwierig die verschieden Situationen realistisch zu modellieren und das Verhalten von Bauprozessen und die Interaktion mit den zugehörigen Ressourcen für reale Bauvorhaben darzustellen. Das ist einer der Gründe für den Mangel an speziellen Simulationswerkzeugen in der Bauprojektplanung. Die zweite Herausforderung besteht in der großen Menge an Projektinformationen, die in das Simulationsmodell integriert und während des gesamten Lebenszyklus des Projekts angepasst werden müssen. Die Erstellung von Simulationsmodellen, Simulationsszenarien sowie die Analyse und Verifizierung der Simulationsergebnisse ist langwierig. Ad-hoc Simulation sind daher nicht möglich. Zur Erstellung zuverlässiger Simulationsmodelle sind daher umfangreiche Ressourcen und Mitarbeiter mit speziellen Fachwissen erforderlich. Die vorgestellten Herausforderungen verhindern die breite Anwendung der Simulationsmethode zur Unterstützung der Bauprojektplanung und das Einsetzen der Software als wesentlicher Bestandteil des Arbeitsablaufes für die Bauplanung in der Praxis. Die Forschungsarbeit in dieser Arbeit befasst sich mit diesen Herausforderungen durch die Entwicklung eines Ansatzes sowie einer Plattform für die schnelle Aufstellung von Simulationsmodellen für Bauprojekte. Das Hauptziel dieser Forschung ist die Entwicklung eines integrierten und referenzmodellbasierten BIM Simulationsansatz zur Unterstützung der Planung von Bauprojekten und die Möglichkeit der Zusammenarbeit aller am Planungs- und Simulationsprozess beteiligten Akteure. Die erste Herausforderung wird durch die Einführung eines RPM-Konzepts (Reference Process Model) durch die Modellierung von Konstruktionsprozessen unter Verwendung von Business Process Modeling and Notation (BPMN) angegangen. Der Vorteil der RPM Modelle ist das sie bearbeitet und modifiziert können und dass sie automatisch als einsatzbereite Module in Simulationsmodelle umgewandelt werden können. Die RPM-Modelle enthalten auch Informationen zu Ressourcenanforderungen und andere verwandte Informationen für verschiedene Baubereiche mit unterschiedlichen Detaillierungsgraden. Die Verwendung von BPMN hat den Vorteil, dass die Simulationsmodellierung für das Projektteam, einschließlich derjenigen, die sich nicht mit der Simulation auskennen, flexibler, interoperabler und verständlicher ist. Bei diesem Ansatz ist die Modellierung von Referenzprozessmodellen vollständig von den Simulationskernkomponenten getrennt, um das Simulations-Toolkit generisch und erweiterbar für verschiedenste Konstruktionsbereiche wie Gebäude und Brücken. Der vorgestellte Forschungsansatz unterstützt die kontinuierliche Anwendung von Simulationsmodellen während des gesamten Projektlebenszyklus. Die Simulationsmodelle, die zur Unterstützung der Planung in der frühen Entwurfsphase erstellt werden, können von Simulationsexperten während der gesamten Planungs- und Bauphase weiter ausgebaut und aktualisiert werden. Die zweite Herausforderung wird durch die direkte Integration der Building Information Modeling (BIM) -Methode in die Simulationsmodellierung auf der Grundlage des Industry Foundation Classes-IFC (ISO 16739) , dem am häufigsten verwendeten BIM-Austauschformat, angegangen. Da die BIM-Modelle einen wichtigen Teil der Eingabeinformationen von Simulationsmodellen enthalten, können sie als Grundlage für die Visualisierung von Ergebnissen in Form von 4D-BIM-Modellen verwendet werden. Diese Integration ermöglicht die schnelle und automatische Filterung und Extraktion sowie die Umwandlung notwendiger Informationen aus BIM Entwurf-Modellen. Um die Erstellung detaillierter Projektmodelle zu beschleunigen, wurde eine spezielle Methode für die halbautomatische Top-Down-Detaillierung von Projektstammmodelle entwickelt, die notwendige Eingangsdaten für die Simulationsmodelle sind. Diese Methode bietet den Vorteil, dass Konstruktionsalternativen mit minimalen Änderungen am Simulationsmodell untersucht werden können. Der entwickelte Ansatz wurde als Software- Prototyp in Form eines modularen Construction Simulation Toolkit (CST) basierend auf der Discrete Event Simulation (DES)- Methode und eines Collaboration- Webportals (ProSIM) zum Verwalten von Simulationsmodellen implementiert. Die so eingebettete Simulation ermöglicht mit minimalen Änderungen die Bewertung von Entwurfsalternativen und Konstruktionsmethoden auf den Bauablauf. Produktions- und Logistiksvorgänge können gleichzeitig in einer einheitlichen Umgebung simuliert werden und berücksichtigen die gemeinsam genutzten Ressourcen und die Interaktion zwischen Produktions- und Logistikaktivitäten. Es berücksichtigt auch die Änderungen im Baustellenlayout während der Konstruktionsphase. Die Verifizierung und Validierung des vorgeschlagenen Ansatzes wird durch verschiedene hypothetische und reale Bauprojekten durchgeführt.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 ReferencesUsing simulation to support construction project planning has many advantages, which have been presented in various academic researches. Many applications have successfully demonstrated the potential of using simulation to improve the quality of construction project planning. However, the wide adoption of simulation has not been achieved in practice yet. It still has very limited use compared with other industries due to some major obstacles and challenges. The first challenge is the complexity of construction processes and projects planning methods, which make it very difficult to develop realistic simulation models of construction processes and represent their dynamic behavior and the interaction with project resources. This led to lack of special simulation tools for construction project planning. The second challenge is the huge amount of project information that has to be integrated into the simulation model and to be maintained throughout the design, planning and construction phases. The preparation of ad-hoc simulation models and setting up different scenarios and verification of simulation results usually takes a long time. Therefore, creating reliable simulation models requires extensive resources with advanced skills. The presented challenges prevent the wide application of simulation techniques to support and improve construction project planning and adopt it as an essential part of the construction planning workflow in practice. The research work in this thesis addresses these challenges by developing an approach and platform for rapid development of simulation models for construction projects. The main objective of this research is to develop a BIM integrated and reference process-based simulation approach to support planning of construction projects and to enable collaboration among all actors involved in the planning and simulation process. The first challenge has been addressed through the development of a construction simulation toolkit and the Reference Process Model (RPM) method for modelling construction processes for production and logistics using Business Process Modelling and Notation (BPMN). The RPM models are easy to understood also by non-experts and they can be transformed automatically into simulation models as ready-to-use modules. They describe the workflow and logic of construction processes and include information about duration, resource requirements and other related information for different construction domains with different levels of details. The use of BPMN has many advantages. It enables the understanding of how simulation models work by project teams, including those who are not experts in simulation. In this approach, the modelling of Reference Process Models is totally separated from the simulation core components. In this way, the simulation toolkit is generic and extendable for various construction types such as buildings, bridges and different construction domains such as structural work and indoor operations. The presented approach supports continuous adoption of simulation models throughout the whole project life cycle. The simulation model which supports project planning in the early design phase can be continuously extended with more detailed RPMs and updated information through the planning and construction phases. The second challenge has been addressed by supporting direct integration of Building Information Modelling (BIM) method with the simulation modelling based on the Industry Foundation Classes IFC (ISO 16739) standard, which is the most common and only ISO standard used for exchanging BIM models. As the BIM models contain the biggest part of the input information of simulation models and they can be used for effective visualization of results in the form of animated 4D BIM models. The integration between BIM and simulation enables fast and semi-automatic filtering, extraction and transformation of the necessary information from BIM models for both design and construction site models. In addition, a special top-down semi-automatic detailing method was developed in order to accelerate the process of preparing detailed project schedules, which are essential input data for the simulation models and hence reduce the time and efforts needed to create simulation models. The developed approach has been implemented as a software prototype in the form of a modular Construction Simulation Toolkit (CST) based on the Discrete Event Simulation (DES) method and an online collaboration web portal 'ProSIM' for managing simulation models. The collaboration portal helps to overcome the problem of huge information and make simulation models accessible for non simulation experts. Simulation models created by CST toolkit facilitate the evaluation of design alternatives and construction methods with minimal changes in the simulation model. Both production and logistic operations can be simulated at the same time in a unified environment and take into account the shared resources and the interaction between production and logistic activities. It also takes into account the dynamic nature of construction projects and hence the changes in the construction site layout during the construction phase. The verification and validation of the proposed approach is carried out through various academic and real construction project case studies.:1 Introduction: motivation, problem statement and objectives 1.1 Motivation 1.2 Problem statement 1.3 Objectives 1.4 Thesis Structure 2 Definitions, Related work and background information 2.1 Simulation definition 2.2 Simulation system definition 2.3 Discrete Event Simulation 2.5 How simulation works 2.6 Workflow of simulation study 2.7 Related work 2.8 Traditional construction planning methods 2.8.1 Gantt chart 2.8.2 Critical Path Method (CPM) 2.8.3 Linear scheduling method/Location-based scheduling 2.9 Business Process Model and Notation 2.10Workflow patterns 2.10.1 Supported Control Flow Patterns 3 Reference Process-based Simulation Approach 3.1 Reference Process-based simulation approach 3.2 Reference Process Models 3.3 Reference process model for single task 3.4 Reference process models for complex activities 3.5 Process Pool 3.6 Top-down automatic detailing of project schedules 3.7 Simulation model formalism 3.8 Fundamental design concepts and application scope 4 Data Integration between simulation and construction Project models 4.1 Data integration between BIM models and simulation models 4.1.1 Transformation of IFC models to Graph models 4.1.2 Checking BIM model quality 4.1.3 Filtering of BIM models 4.1.4 Semantic enrichment of BIM models 4.1.5 Reference process models and BIM models 4.2 Reference Process Models and resources models 4.3 Process models and productivity factors 5 Construction Simulation Toolkit 5.1 System architecture and implementation 5.2 Basic steps to create a CST simulation model 5.3 CST Simulation components 5.3.1 Input components 5.3.2 Process components 5.3.3 Output components 5.3.4 Logistic components 5.3.5 Collaboration platform ProSIM 6 Case Studies and Validation 6.1 Verification and Validation of Simulation Models 6.2 Verification and validation techniques for simulation models 6.3 Case study 1: generic planning model 6.4 Case study 2: high rise building 6.4.1 Scenario I: effect of changing number of workers on structural work duration 6.4.2 Scenario II: simulation of structural work on operation level 6.4.3 Scenario III: automatic generation of detailed project schedule 6.5 Case study 3: airport terminal building 6.5.1 Multimodel Container 6.5.2 Scenario I: automatic generation of detailed project schedule 6.5.3 Scenario II: Find the minimal project duration 6.5.4 Scenario III: construction work for a single floor 7 Conclusions and Future Research 7.1 Conclusions 7.2 Outlook of the possible future research topics 7.2.1 Integration with real data collecting 7.2.2 Multi-criteria optimisation 7.2.3 Extend the control-flow and resource patterns 7.2.4 Consideration of further structure domains 7.2.5 Considering of space allocation and space conflicts 8 Appendix - Scripts 9 Appendix B - Reference Process Models 9.1 Reference Process Models for structural work 9.1.1 Wall 9.1.2 Roof 9.1.3 Foundations 9.1.4 Concrete work 9.1.5 Top-Down RPMs for structural work in a work section 10 Appendix E 10.1 Basic elements of simulation models in Plant Simulation 10.2 Material Flow Objects 11 Reference

Workshop proceedings of the 1st workshop on quality in modeling

Quality assessment and assurance constitute an important part of software engineering. The issues of software quality management are widely researched and approached from multiple perspectives and viewpoints. The introduction of a new paradigm in software development – namely Model Driven Development (MDD) and its variations (e.g., MDA [Model Driven Architecture], MDE [Model Driven Engineering], MBD [Model Based Development], MIC [Model Integrated Computing]) – raises new challenges in software quality management, and as such should be given a special attention. In particular, the issues of early quality assessment, based on models at a high abstraction level, and building (or customizing the existing) prediction models for software quality based on model metrics are of central importance for the software engineering community. The workshop is continuation of a series of workshops on consistency that have taken place during the subsequent annual UML conferences and recently MDA-FA. The idea behind this workshop is to extend the scope of interests and address a wide spectrum of problems related to MDD. It is also in line with the overall initiative of the shift from UML to MoDELS. The goal of this workshop is to gather researchers and practitioners interested in the emerging issues of quality in the context of MDD. The workshop is intended to provide a premier forum for discussions related to software quality and MDD. And the aims of the workshop are: - Presenting ongoing research related to quality in modeling in the context of MDD, - Defining and organizing issues related to quality in the MDD. The format of the workshop consists of two parts: presentation and discussion. The presentation part is aimed at reporting research results related to quality aspects in modeling. Seven papers were selected for the presentation out of 16 submissions; the selected papers are included in these proceedings. The discussion part is intended to be a forum for exchange of ideas related to understanding of quality and approaching it in a systematic way

Workshop proceedings of the 1st workshop on quality in modeling

Quality assessment and assurance constitute an important part of software engineering. The issues of software quality management are widely researched and approached from multiple perspectives and viewpoints. The introduction of a new paradigm in software development – namely Model Driven Development (MDD) and its variations (e.g., MDA [Model Driven Architecture], MDE [Model Driven Engineering], MBD [Model Based Development], MIC [Model Integrated Computing]) – raises new challenges in software quality management, and as such should be given a special attention. In particular, the issues of early quality assessment, based on models at a high abstraction level, and building (or customizing the existing) prediction models for software quality based on model metrics are of central importance for the software engineering community. The workshop is continuation of a series of workshops on consistency that have taken place during the subsequent annual UML conferences and recently MDA-FA. The idea behind this workshop is to extend the scope of interests and address a wide spectrum of problems related to MDD. It is also in line with the overall initiative of the shift from UML to MoDELS. The goal of this workshop is to gather researchers and practitioners interested in the emerging issues of quality in the context of MDD. The workshop is intended to provide a premier forum for discussions related to software quality and MDD. And the aims of the workshop are: - Presenting ongoing research related to quality in modeling in the context of MDD, - Defining and organizing issues related to quality in the MDD. The format of the workshop consists of two parts: presentation and discussion. The presentation part is aimed at reporting research results related to quality aspects in modeling. Seven papers were selected for the presentation out of 16 submissions; the selected papers are included in these proceedings. The discussion part is intended to be a forum for exchange of ideas related to understanding of quality and approaching it in a systematic way

A Framework for Seamless Variant Management and Incremental Migration to a Software Product-Line

Context: Software systems often need to exist in many variants in order to satisfy varying customer requirements and operate under varying software and hardware environments. These variant-rich systems are most commonly realized using cloning, a convenient approach to create new variants by reusing existing ones. Cloning is readily available, however, the non-systematic reuse leads to difficult maintenance. An alternative strategy is adopting platform-oriented development approaches, such as Software Product-Line Engineering (SPLE). SPLE offers systematic reuse, and provides centralized control, and thus, easier maintenance. However, adopting SPLE is a risky and expensive endeavor, often relying on significant developer intervention. Researchers have attempted to devise strategies to synchronize variants (change propagation) and migrate from clone&own to an SPL, however, they are limited in accuracy and applicability. Additionally, the process models for SPLE in literature, as we will discuss, are obsolete, and only partially reflect how adoption is approached in industry. Despite many agile practices prescribing feature-oriented software development, features are still rarely documented and incorporated during actual development, making SPL-migration risky and error-prone.Objective: The overarching goal of this PhD is to bridge the gap between clone&own and software product-line engineering in a risk-free, smooth, and accurate manner. Consequently, in the first part of the PhD, we focus on the conceptualization, formalization, and implementation of a framework for migrating from a lean architecture to a platform-based one.Method: Our objectives are met by means of (i) understanding the literature relevant to variant-management and product-line migration and determining the research gaps (ii) surveying the dominant process models for SPLE and comparing them against the contemporary industrial practices, (iii) devising a framework for incremental SPL adoption, and (iv) investigating the benefit of using features beyond PL migration; facilitating model comprehension.Results: Four main results emerge from this thesis. First, we present a qualitative analysis of the state-of-the-art frameworks for change propagation and product-line migration. Second, we compare the contemporary industrial practices with the ones prescribed in the process models for SPL adoption, and provide an updated process model that unifies the two to accurately reflect the real practices and guide future practitioners. Third, we devise a framework for incremental migration of variants into a fully integrated platform by exploiting explicitly recorded metadata pertaining to clone and feature-to-asset traceability. Last, we investigate the impact of using different variability mechanisms on the comprehensibility of various model-related tasks.Future work: As ongoing and future work, we aim to integrate our framework with existing IDEs and conduct a developer study to determine the efficiency and effectiveness of using our framework. We also aim to incorporate safe-evolution in our operators

Benefits of adopting systems engineering approaches in rail projects

Systems Engineering (SE) is being increasingly used in rail projects. However, it is not entirely clear what exactly the return on investing in SE is or how to maximise this return. This thesis describes research into the relationship between the adoption of SE in rail projects and project outcomes. Using project cost and duration and system performance to measure the benefits of adopting SE is found to be problematic. Theoretical reasons and practical experience lead the writer to believe that many of the benefits of adopting SE on projects are enjoyed as a consequence of reducing change latency - the unnecessary delay in deciding to make a change. A tentative theory of how SE can reduce change latency is proposed and tested against data collected from nine rail projects. The data corroborate several causal mechanisms in the theory but also suggest that change latency depends upon other factors. For practitioners considering whether to apply SE on a project, the research findings provide encouragement but also a warning that the full benefits of applying SE will only be enjoyed if other pre-requisites for sound decision making are in place. The findings also provide guidance on how to adapt SE practices when applying them to rail projects, in order to maximise the benefits. The writer argues that change latency is a valuable metric for both practitioners and researchers and that formulating and refining explicit theories about the manner in which SE delivers benefits can assist researchers to build upon each other’s work

A bottom-up process management environment dedicated to process actors

Les organisations adoptent de plus en plus les environnements de gestion des processus car ils offrent des perspectives prometteuses d'exécution en termes de flexibilité et d'efficacité. Les environnements traditionnels proposent cependant une approche descendante qui nécessite, de la part de concepteurs, l'élaboration d'un modèle avant sa mise en oeuvre par les acteurs qui le déploient tout au long du cycle d'ingénierie. En raison de cette divergence, un différentiel important est souvent constaté entre les modèles de processus et leur mise en oeuvre. De par l'absence de prise directe avec les acteurs de terrain, le niveau opérationnel des environnements de processus est trop faiblement exploité, en particulier en ingénierie des systèmes et des logiciels. Afin de faciliter l'utilisation des environnements de processus, cette thèse présente une approche ascendante mettant les acteurs du processus au coeur de la problématique. L'approche proposée autorise conjointement la modélisation et la mise en oeuvre de leurs activités quotidiennes. Dans cet objectif, notre approche s'appuie sur la description des artéfacts produits et consommés durant l'exécution d'une activité. Cette description permet à chaque acteur du processus de décrire le fragment de processus exprimant les activités dictées par son rôle. Le processus global se décompose ainsi en plusieurs fragments appartenant à différents rôles. Chaque fragment est modélisé indépendamment des autres fragments ; il peut aussi être greffé progressivement au modèle de processus initial. La modélisation des processus devient ainsi moins complexe et plus parcellaire. En outre, un fragment de processus ne modélise que l'aspect structurel des activités d'un rôle sans anticiper sur le comportement des activités ; il est moins prescriptif qu'un ordonnancement des activités de l'acteur. Un moteur de processus basé sur la production et la consommation d'artéfacts a été développé pour promulguer des activités provenant de différents fragments de processus. Ce moteur ne requiert pas de relations prédéfinies d'ordonnancement entre les activités pour les synchroniser, mais déduit leur dépendance à partir de leurs artéfacts échangés. Les dépendances sont représentées et actualisées au sein d'un graphe appelé Process Dependency Graph (PDG) qui reflète à tout instant l'état courant de l'exécution du processus. Cet environnement a été étendu afin de gérer les changements imprévus qui se produisent inévitablement lors de la mise en oeuvre des processus. Ce dispositif permet aux acteurs de signaler des changements émergents, d'analyser les impacts possibles et de notifier les personnes affectées par les modifications. En résumé, notre approche préconise de répartir les tâches d'un processus en plusieurs fragments, modélisés et adoptés séparément par les acteurs du processus. Le moteur de processus, qui s'appuie sur la disponibilité des artéfacts pour synchroniser les activités, permet d'exécuter indépendamment les fragments des processus. Il permet aussi l'exécution d'un processus partiellement défini pour lequel certains fragments seraient manquants. La vision globale de l'état d'avancement des différents acteurs concernés émerge au fur et à mesure de l'exécution des fragments. Cette nouvelle approche vise à intégrer au mieux les acteurs du processus dans le cycle de vie de la gestion des processus, ce qui rend ces systèmes plus attractifs et plus proches de leurs préoccupations.Companies increasingly adopt process management environments, which offer promising perspectives for a more flexible and efficient process execution. Traditional process management environments embodies a top-down approach in which process modeling is performed by process designers and process enacting is performed by process actors. Due to this separation, there is often a gap between process models and their real enactments. As a consequence, the operational level of top down process environments has stayed low, especially in system and software industry, because they are not directly relevant to process actors' needs. In order to facilitate the usage of process environments for process actors, this thesis presents a user-centric and bottom-up approach that enables integration of process actors into process management life cycle by allowing them to perform both the modeling and enacting of their real processes. To this end, first, a bottom-up approach based on the artifact-centric modeling paradigm was proposed to allow each process actor to easily describe the process fragment containing the activities carried out by his role. The global process is thus decomposed into several fragments belonging to different roles. Each fragment can be modeled independently of other fragments and can be added progressively to the process model; therefore the process modeling becomes less complex and more partial. Moreover, a process fragment models only the structural aspect of a role's activities without anticipating the behavior of these activities; therefore the process model is less prescriptive. Second, a data-driven process engine was developed to enact activities coming from different process fragments. Our process engine does not require predefined work-sequence relations among these activities to synchronize them, but deduces such dependencies from their enactment-time exchanged artifacts. We used a graph structure name Process Dependency Graph (PDG) to store enactment-time process information and establish the dependencies among process elements. Third, we extend our process environment in order to handle unforeseen changes occurring during process enactment. This results in a Change-Aware Process Environment that allows process actors reporting emergent changes, analyzing possible impacts and notifying people affected by the changes. In our bottom-up approach, a process is split into several fragments separately modeled and enacted by process actors. Our data-driven process engine, which uses the availability of working artifacts to synchronize activities, enables enacting independently process fragments, and even a partially modeled process where some fragments are missing. The global process progressively emerges only at enactment time from the execution of process fragments. This new approach, with its simpler modeling and more flexible enactment, integrates better process actors into process management life cycle, and hence makes process management systems more attractive and useful for them

Ireland’s Rural Environment: Research Highlights from Johnstown Castle

ReportThis booklet gives a flavour of the current research in Teagasc Johnstown Castle Research Centre and introduces you to the staff involved. It covers the areas of Nutrient Efficiency, Gaseous emissions, Agricultural Ecology, Soils and Water quality