Compliance flow: an intelligent workflow management system to support engineering processes

This work is about extending the scope of current workflow management systems to support engineering processes. On the one hand engineering processes are relatively dynamic, and on the other their specification and performance are constrained by industry standards and guidelines for the sake of product acceptability, such as IEC 61508 for safety and ISO 9001 for quality. A number of technologies have been proposed to increase the adaptability of current workflow systems to deal with dynamic situations. A primary concern is how to support open-ended processes that cannot be completely specified in detail prior to their execution. A survey of adaptive workflow systems is given and the enabling technologies are discussed. Engineering processes are studied and their characteristics are identified and discussed. Current workflow systems have been successfully used in managing "administrative" processes for some time, but they lack the flexibility to support dynamic, unpredictable, collaborative, and highly interdependent engineering processes. [Continues.

A multi-agent approach for design consistency checking

The last decade has seen an explosion of interest to advanced product development methods, such as Computer Integrated Manufacture, Extended Enterprise and Concurrent Engineering. As a result of the globalization and future distribution of design and manufacturing facilities, the cooperation amongst partners is becoming more challenging due to the fact that the design process tends to be sequential and requires communication networks for planning design activities and/or a great deal of travel to/from designers' workplaces. In a virtual environment, teams of designers work together and use the Internet/Intranet for communication. The design is a multi-disciplinary task that involves several stages. These stages include input data analysis, conceptual design, basic structural design, detail design, production design, manufacturing processes analysis, and documentation. As a result, the virtual team, normally, is very changeable in term of designers' participation. Moreover, the environment itself changes over time. This leads to a potential increase in the number of design. A methodology of Intelligent Distributed Mismatch Control (IDMC) is proposed to alleviate some of the related difficulties. This thesis looks at the Intelligent Distributed Mismatch Control, in the context of the European Aerospace Industry, and suggests a methodology for a conceptual framework based on a multi-agent architecture. This multi-agent architecture is a kernel of an Intelligent Distributed Mismatch Control System (IDMCS) that aims at ensuring that the overall design is consistent and acceptable to all participating partners. A Methodology of Intelligent Distributed Mismatch Control is introduced and successfully implemented to detect design mismatches in complex design environments. A description of the research models and methods for intelligent mismatch control, a taxonomy of design mismatches, and an investigation into potential applications, such as aerospace design, are presented. The Multi-agent framework for mismatch control is developed and described. Based on the methodology used for the IDMC application, a formal framework for a multi-agent system is developed. The Methods and Principles are trialed out using an Aerospace Distributed Design application, namely the design of an A340 wing box. The ontology of knowledge for agent-based Intelligent Distributed Mismatch Control System is introduced, as well as the distributed collaborative environment for consortium based projects

An integration framework for managing rich organisational process knowledge

The problem we have addressed in this dissertation is that of designing a pragmatic framework for integrating the synthesis and management of organisational process knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a methodological approach to acquiring information about the process domain. We show that this initial domain specification can be translated into a common constraint-based model of activity (based on the work of Tate, 1996c and 1996d) which can then be operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a sorted first-order logic. The model combines perspectives covering both the space of behaviour as well as the space of decisions. Synthesised or modified processes/plans can be translated to and from the common representation in order to support knowledge sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf

ACTAS: Adaptive Composition and Trading with Agents for Services

Mainly in business domains, the vision of gaining flexible, adaptive service environments is based on the standardization and practical proliferation of (Semantic) Web Services, ontologies, and agents. The standards of Web Services and their Service-oriented Architectures (SOA) became the standard paradigm for software component integration. Dynamic changes and the permanently increasing amount of available e-services of different domains are a challenge of Service Discovery and Composition. Mediation between different approaches and expert knowledge is often necessary for the composition of services of different domains. Semantic enhancements, Autonomic Service Discovery, and the research for more holistic concepts for the classification of e-services are current attempts of overcoming this challenge, in order to reach the ultimate goal of Autonomic SOC

Component-based records: a novel method to record transaction design work

The growing pressures from global competitive markets signal the inevitable challenge for companies to rapidly design and develop new successful products. To continually improve design quality and efficiency, companies must consider how to speed design processes, minimise human-errors, avoid unnecessary iterations, and sustain knowledge embedded in the design process. All of these issues strongly concern one topic: how to make and exploit records of design activities. Using process modelling ideas, this paper introduces a new method called component-based records, in place of traditional design reports. The proposed method records transaction elements of the actual design processes undertaken in a design episode, which aims to continually improve design quality and efficiency, reduce designers’ workload for routine tasks, and sustain competitiveness of companies

A knowledge based approach to integration of products, processes and reconfigurable automation resources

The success of next generation automotive companies will depend upon their ability to adapt to ever changing market trends thus becoming highly responsive. In the automotive sector, the assembly line design and reconfiguration is an especially critical and extremely complex job. The current research addresses some of the aspects of this activity under the umbrella of a larger ongoing research project called Business Driven Automation (BDA) project. The BDA project aims to carry out complete virtual 3D modeling-based verifications of the assembly line for new or revised products in contrast to the prevalent practice of manual evaluation of effects of product change on physical resources. [Continues.

Generic autonomic adapter architecture and policy model for semantic socio-cyber-physical collaborative network

The cyber-physical system aims to improve the quality of life of citizens by providing intelligent and automated services in a wide variety of sectors like transportations, healthcare,enterprises, self-driving cars, energy sectors and so forth. Recently, considerable amounts of researches have focused on integrating cyber-physical systems in a social context. The idea is to socially connect cyber-physical resources (i.e., physical devices, software elements,networked components, digital contents, etc.) so that they can interact and collaborative for autonomous decision making like humans social networking. However, several challenges remain concerning the designing appropriate methodologies, frameworks and techniques for supporting cyber-physical relation and collaboration within the social context. Most of the existing social software modelling focuses on maintaining human-to-human or human-to object centric interaction only. Existing systems do not recognise how socio-cyber-physical resources can maintain their social status, communicate and interact with both humans and non human entities. The reason may be the lack of understanding and limited approaches or methodologies to semantically (a formal characterisation of the information) represent the socio-cyber-physical resources relation and interactions in a collaborative network. This limits data integration, interoperability, and knowledge discovery from its underlying data sources. Semantic Web’s ontology with a software agent model can help to overcome this limitation by describing and interconnecting socio-cyber-physical objects in a social space.The software agents can act as a representative of these resources to track, manage and update their collaborative activities in a social world.Nevertheless, due to the exponential network growth and uncertainties, the states and relations among socio-cyber-physical objects may keep changing when they are in different situations. Therefore, it is an ardours task and error-prone for humans or traditional software agents to keep track, manage and maintain the larger number of socio-cyber-physical resources and their social dynamics. One potential and flexible solution to this problem is to leverage the autonomic computing approach with social and adaptive goals to make the socio-cyber physical network self-managed and adaptive. Autonomic Computing (AC) approach has laid the necessary foundation to tackle this challenge by developing policy-based Autonomic Adapter (AA) model (e.g., autonomous agent). The AAs can continuously monitor socio cyber-physical resource status, analyse the situation and make a collaborative decision based on the policy knowledge defined by the system administrator. However, autonomic computing model must rely on input knowledge to decide self management operations such as “what”, “where” and “how” to perform the adaptation to the system. Previously, adaptation approaches in a different context have been done in an ad-hoc manner based on the algorithms to predict future circumstances and embed in the program code. This approach is inflexible to dynamic and uncertain environments where system configuration needs to adjust frequently. Defining a flexible policy model and integrating policy into knowledge repository outside the code itself is the most appropriate to manage the autonomic system behaviours during the run-time. Sadly, there has been relatively a little work on developing appropriate policy model and specification language for domain neutral autonomic system.To fulfil the above gaps, our proposed solutions in this thesis has three core contribution to the knowledge. First, we address the establishment of both socio-cyber-physical and human relations and interactions within a social-collaborative network. To achieve this, we propose a software agent-centric Semantic Social-Collaborative Network (SSCN) that provides the functionality to represent and manage cyber-physical resources in a social network. We discuss how nonhuman resources can be represented as socially connected nodes and manage by the software agents. The SSCN is supported by an extended ontology model for semantically describing the concept, properties and relations of human and nonhuman resources. A Java-based software agent API has been implemented to demonstrate some actions performed on behalf of the nonhuman resources in a real-world collaborative healthcare system called, GRiST (www.egrist.org). Second, we propose a Generic Autonomic Social-Collaborative Framework (GASCF) with a policy-based Autonomic Adapter (AA) architecture. The AAs are capable of monitoring system resources, analysing context information, and act accordingly using high-level policy. The AAs can also communicate and exchange data with other AAs through a social network for collaborative decisions making like human social interaction.Third, we propose Event-Condition-Action (ECA) rule-based policy model and specification language for AA by defining Policy Schema Definition (PSD) and Policy Script Specification(PSS) languages, modelled with XML syntax. Finally, we test and evaluate our approach by implementing it to the extended GRiST socio-healthcare service context and eGRiST clinical decision support system. We demonstrate and evaluate how socio-cyber-physical relation,interaction and autonomous decision-making is achieved by integrating AAs and using policy specification to manage AAs behaviour within socio-cyber-physical medical context

Analysis of manufacturing operations using knowledge- Enriched aggregate process planning

Knowledge-Enriched Aggregate Process Planning is concerned with the problem of supporting agile design and manufacture by making process planning feedback integral to the design function. A novel Digital Enterprise Technology framework (Maropoulos 2003) provides the technical context and is the basis for the integration of the methods with existing technologies for enterprise-wide product development. The work is based upon the assertion that, to assure success when developing new products, the technical and qualitative evaluation of process plans must be carried out as early as possible. An intelligent exploration methodology is presented for the technical evaluation of the many alternative manufacturing options which are feasible during the conceptual and embodiment design phases. 'Data resistant' aggregate product, process and resource models are the foundation of these planning methods. From the low-level attributes of these models, aggregate methods to generate suitable alternative process plans and estimate Quality, Cost and Delivery (QCD) have been created. The reliance on QCD metrics in process planning neglects the importance of tacit knowledge that people use to make everyday decisions and express their professional judgement in design. Hence, the research also advances the core aggregate planning theories by developing knowledge-enrichment methods for measuring and analysing qualitative factors as an additional indicator of manufacturing performance, which can be used to compute the potential of a process plan. The application of these methods allows the designer to make a comparative estimation of manufacturability for design alternatives. Ultimately, this research should translate into significant reductions in both design costs and product development time and create synergy between the product design and the manufacturing system that will be used to make it. The efficacy of the methodology was proved through the development of an experimental computer system (called CAPABLE Space) which used real industrial data, from a leading UK satellite manufacturer to validate the industrial benefits and promote the commercial exploitation of the research

Newcomer Retention and Productivity in Online Peer-Production Communities

University of Minnesota Ph.D. dissertation. July 2018. Major: Computer Science. Advisor: Joseph Konstan. 1 computer file (PDF); x, 159 pages.Online communities are online interaction spaces for people that break the barriers of time, space, and scale and provide opportunities for companionship and social support, information exchange, retail, and entertainment. Among them are online peer production communities that have a fantastic business model where volunteers come together to produce content and drive traffic to these sites. Although as a class these communities are successful, the success of individual communities greatly varies. To become and remain successful, these communities must meet a number of challenges related to starting communities, retention of members, encouraging commitment, and contribution from their members, regulating the behavior of members and so on. This dissertation focuses on the specific challenge of newcomer retention and productivity in the context of online peer-production communities. Exploring three different communities with entirely different structures and compositions – MovieLens, GitHub, and Wikipedia and building upon prior work in this space, this dissertation offers a number of important predictors of retention and productivity of newcomers. First, this dissertation explores the value of early activity diversity in the presence of the amount of early activity as a predictor of newcomer retention. Second, this dissertation digs into more fundamental psychological traits of newcomers such as personality and presents findings on relationships between personality and newcomer retention, preferences, and productivity. Third, this dissertation explores and presents results on the relationship between community interactions (apart from norms, policies and rigid structures) and newcomer retention. Fourth, this dissertation studies and presents the effects of various kinds of prior experience of newcomers on retention and productivity in a new group they join. This dissertation concludes by offering a number of directions for future research