Flexible and Intelligent Learning Architectures for SOS (FILA-SoS)

Multi-faceted systems of the future will entail complex logic and reasoning with many levels of reasoning in intricate arrangement. The organization of these systems involves a web of connections and demonstrates self-driven adaptability. They are designed for autonomy and may exhibit emergent behavior that can be visualized. Our quest continues to handle complexities, design and operate these systems. The challenge in Complex Adaptive Systems design is to design an organized complexity that will allow a system to achieve its goals. This report attempts to push the boundaries of research in complexity, by identifying challenges and opportunities. Complex adaptive system-of-systems (CASoS) approach is developed to handle this huge uncertainty in socio-technical systems

Towards semantics-driven modelling and simulation of context-aware manufacturing systems

Systems modelling and simulation are two important facets for thoroughly and effectively analysing manufacturing processes. The ever-growing complexity of the latter, the increasing amount of knowledge, and the use of Semantic Web techniques adhering meaning to data have led researchers to explore and combine together methodologies by exploiting their best features with the purpose of supporting manufacturing system's modelling and simulation applications. In the past two decades, the use of ontologies has proven to be highly effective for context modelling and knowledge management. Nevertheless, they are not meant for any kind of model simulations. The latter, instead, can be achieved by using a well-known workflow-oriented mathematical modelling language such as Petri Net (PN), which brings in modelling and analytical features suitable for creating a digital copy of an industrial system (also known as "digital twin"). The theoretical framework presented in this dissertation aims to exploit W3C standards, such as Semantic Web Rule Language (SWRL) and Web Ontology Language (OWL), to transform each piece of knowledge regarding a manufacturing system into Petri Net modelling primitives. In so doing, it supports the semantics-driven instantiation, analysis and simulation of what we call semantically-enriched PN-based manufacturing system digital twins. The approach proposed by this exploratory research is therefore based on the exploitation of the best features introduced by state-of-the-art developments in W3C standards for Linked Data, such as OWL and SWRL, together with a multipurpose graphical and mathematical modelling tool known as Petri Net. The former is used for gathering, classifying and properly storing industrial data and therefore enhances our PN-based digital copy of an industrial system with advanced reasoning features. This makes both the system modelling and analysis phases more effective and, above all, paves the way towards a completely new field, where semantically-enriched PN-based manufacturing system digital twins represent one of the drivers of the digital transformation already in place in all companies facing the industrial revolution. As a result, it has been possible to outline a list of indications that will help future efforts in the application of complex digital twin support oriented solutions, which in turn is based on semantically-enriched manufacturing information systems. Through the application cases, five key topics have been tackled, namely: (i) semantic enrichment of industrial data using the most recent ontological models in order to enhance its value and enable new uses; (ii) context-awareness, or context-adaptiveness, aiming to enable the system to capture and use information about the context of operations; (iii) reusability, which is a core concept through which we want to emphasize the importance of reusing existing assets in some form within the industrial modelling process, such as industrial process knowledge, process data, system modelling primitives, and the like; (iv) the ultimate goal of semantic Interoperability, which can be accomplished by adding data about the metadata, linking each data element to a controlled, shared vocabulary; finally, (v) the impact on modelling and simulation applications, which shows how we could automate the translation process of industrial knowledge into a digital manufacturing system and empower it with quantitative and qualitative analytical technics

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

Ninth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, Aarhus, Denmark, October 20-22, 2008

This booklet contains the proceedings of the Ninth Workshop on Practical Use of Coloured Petri Nets and the CPN Tools, October 20-22, 2008. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The papers are also available in electronic form via the web pages: http://www.daimi.au.dk/CPnets/workshop0

Computational intelligence based complex adaptive system-of-systems architecture evolution strategy

The dynamic planning for a system-of-systems (SoS) is a challenging endeavor. Large scale organizations and operations constantly face challenges to incorporate new systems and upgrade existing systems over a period of time under threats, constrained budget and uncertainty. It is therefore necessary for the program managers to be able to look at the future scenarios and critically assess the impact of technology and stakeholder changes. Managers and engineers are always looking for options that signify affordable acquisition selections and lessen the cycle time for early acquisition and new technology addition. This research helps in analyzing sequential decisions in an evolving SoS architecture based on the wave model through three key features namely; meta-architecture generation, architecture assessment and architecture implementation. Meta-architectures are generated using evolutionary algorithms and assessed using type II fuzzy nets. The approach can accommodate diverse stakeholder views and convert them to key performance parameters (KPP) and use them for architecture assessment. On the other hand, it is not possible to implement such architecture without persuading the systems to participate into the meta-architecture. To address this issue a negotiation model is proposed which helps the SoS manger to adapt his strategy based on system owners behavior. This work helps in capturing the varied differences in the resources required by systems to prepare for participation. The viewpoints of multiple stakeholders are aggregated to assess the overall mission effectiveness of the overarching objective. An SAR SoS example problem illustrates application of the method. Also a dynamic programing approach can be used for generating meta-architectures based on the wave model. --Abstract, page iii

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Case-Based Decision Support for Disaster Management

Disasters are characterized by severe disruptions of the society’s functionality and adverse impacts on humans, the environment, and economy that cannot be coped with by society using its own resources. This work presents a decision support method that identifies appropriate measures for protecting the public in the course of a nuclear accident. The method particularly considers the issue of uncertainty in decision-making as well as the structured integration of experience and expert knowledge

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Deducing Requirements From Agile Software Processes

In classical engineering practice, the elicitation of requirements is an important early project phase. Requirements help to define the project goals and scope, they serve as a basis for cost estimation, and in validated projects they are the cornerstone of the traceability matrix. However, requirements elicitation is difficult because of the abstract nature of the process and because there is uncertainty at the start of a project about what can be done. In recent software development practice, waterfall methods have fallen into disfavor, and agile methods are preferred. Agile methods avoid formal requirements specification, and instead use techniques such as scrums and user stories to specify development phases that are performed iteratively. In agile methods, requirements remain implicit and undocumented. While agile may avoid the difficulties of formal elicitation of requirements, it may in the process bypass the activity of analysis of user needs, and the generation of a baseline against which the implemented system can be validated. In this thesis we show that requirements can be deduced from the user stories and process maps that result from agile methodologies. A modified failure mode effects analysis approach is used to identify risks, failure modes, and countermeasures, and to evaluate risks and countermeasures by computing severity and likelihood of the risks, and the benefits of the countermeasures. The deduction of requirements from agile artifacts encourages an agile team to think through its preferences and proposed implementations, and objectively rate them. It captures the rationale for the user stories and process maps, and provides traceability from business goals to the functional requirements

Business process modelling in ERP implementation literature review

Business processes are the backbone of any Enterprise Resource Planning (ERP) implementation. Business process modelling (BPM) has become essential for modern, process driven enterprises due to the vibrant business environments. As a consequence enterprises are dealing with a substantial rate of organizational and business processes change. Business process modelling enables a common understanding and analysis of the business processes, which is the first step in every ERP implementation methodology (blueprint phase). In order to represent enterprise processes models in an accurate manner, it is paramount to choose a right business process modeling technique and tool. The problem of many ERP projects rated as unsuccessful is directly connected to a lack of use of business process models and notations during the blueprint phase. Also, blueprint implementation phase is crucial in order to fit planned processes in an organization with processes implemented in the solution. However, business analysts and ERP implementation professionals have substantial difficulties to navigate through a large number of theoretical models and representational notations that have been proposed for business process modeling (BPM). As the availability of different business process modeling references is huge, it is time consuming to make review and classification of all modeling techniques. Therefor, in reality majority of ERP implementations blueprint documents have no business process modeling included in generating blueprint documents. Choosing the right model comprise the purpose of the analysis and acquaintance of the available process modelling techniques and tools. The number of references on business modelling is quit large, so it is very hard to make a decision which modeling notation or technique to use. The main purpose of this paper is to make a review of business process modelling literature and describe the key process modelling techniques. The focus will be on all business process modeling that could be used in ERP implementations, specifically during the blueprint phase of the implementation process. Detailed review of BPM (Business process modeling) theoretical models and representational notations, should assist decision makers and ERP integrators in comparatively evaluating and selecting suitable modeling approaches