Tracking decision-making during architectural design

There is a powerful cocktail of circumstances governing the way decisions are made during the architectural design process of a building project. There is considerable potential for misunderstandings, inappropriate changes, change which give rise to unforeseen difficulties, decisions which are not notified to all interested parties, and many other similar problems. The paper presents research conducted within the frame of the EPSRC funded ADS project aiming at addressing the problems linked with the evolution and changing environment of project information to support better decision-making. The paper presents the conceptual framework as well as the software environment that has been developed to support decision-making during building projects, and reports on work carried out on the application of the approach to the architectural design stage. This decision-tracking environment has been evaluated and validated by professionals and practitioners from industry using several instruments as described in the paper

Maturity integrated in a meta model of knowledge to help decision making in preliminary collaborative design of mechanical systems

La conception de systèmes mécaniques, de par son aspect pluridisciplinaire et technologique, fait intervenir et interagir différentes personnes qui travaillent et prennent des décisions ensemble, et, participent ensemble à l élaboration du produit. Elles travaillent de manière collaborative cependant elles ne se connaissent pas obligatoirement, ne se situent pas forcément géographiquement sur un site commun, n ont peut-être pas la même culture et n appartiennent pas systématiquement à la même entreprise. La conception préliminaire représente les premières phases du cycle de conception ou le produit est en cours de définition. Le nombre d incertitudes sur les paramètres et les informations produit sont très importantes. Il y a un manque de connaissances important à cette étape du processus de conception qui doit être considéré afin d améliorer et d aider les prises de décisions dans les phases amonts. C est ce manque de connaissances que je me propose de qualifier et caractériser en apportant une réponse à la question résultante: comment prendre en compte le manque de connaissances pour prendre des décisions durant la conception préliminaire collaborative ? Pour se faire, nous proposons un méta-modèle de connaissances permettant de structurer les informations du produit et les connaissances en intégrant la maturité du produit. Cette maturité est définie par une métrique et permet d identifier le niveau de connaissances des concepteurs sur le produit et d orienter la prise de décision grâce à l utilisation d une approche mixte, à la fois qualitative et quantitative. Enfin, nous évaluerons la capacité de ce méta-modèle à générer différent modèles produit, puis sa pertinence avec l implémentation sur un cas industriel.The design of mechanical systems, due to their multi-disciplinary and technological aspects, involves different people who, together, work and make decisions and jointly participate in the development of the product. They work in a collaborative manner; however, they may have different strategies, geographical positions, cultures and do not know the other members of the team. Preliminary design represents the early stages of the design cycle or product definition. A number of uncertainties regarding the parameters and product information are very important. There is an important lack of knowledge at this stage of the design process that must be managed or filled in order to improve and support the decision making in the early phases. It is this lack of knowledge that I propose to qualify and characterise, providing an answer to the question: how does one to take into account the lack of knowledge in decision making during the preliminary design collaboration? To do so, we propose a meta-model for structuring product information and knowledge by integrating product maturity. A metric allows this maturity to be defined, to identify the level of knowledge of the product designers and to guide the decision making, thanks to the use of a qualitative and quantitative approach. Finally, we evaluate the ability of the meta-model to generate the different models produced and its relevance to the implementation in an industrial case.COMPIEGNE-BU (601592101) / SudocSudocFranceF

A new trend for knowledge-based decision support systems design

Knowledge-based decision support systems (KBDSS) have evolved greatly over the last few decades. The key technologies underpinning the development of KBDSS can be classified into three categories: technologies for knowledge modelling and representation, technologies for reasoning and inference and web-based technologies. In the meantime, service systems have emerged and become increasingly important to value adding activities in the current knowledge economy. This paper provides a review on the recent advances in the three types of technologies, as well as the main application domains of KBDSS as service systems. Based on the examination of literature, future research directions are recommended for the development of KBDSS in general and in particular to support decision-making in service industry

Conceptual modeling for the design of intelligent and emergent information systems

A key requirement to today's fast changing economic environment is the ability of organizations to adapt dynamically in an effective and efficient manner. Information and Communication Technologies play a crucially important role in addressing such adaptation requirements. The notion of `intelligent software' has emerged as a means by which enterprises can respond to changes in a reactive manner but also to explore, in a pro-active manner, possibilities for new business models. The development of such software systems demands analysis, design and implementation paradigms that recognize the need for ‘co-development’ of these systems with enterprise goals, processes and capabilities. The work presented in this paper is motivated by this need and to this end it proposes a paradigm that recognizes co-development as a knowledge-based activity. The proposed solution is based on a multi-perspective modeling approach that involves (i) modeling key aspects of the enterprise, (ii) reasoning about design choices and (iii) supporting strategic decision-making through simulations. The utility of the approach is demonstrated though a case study in the field of marketing for a start-up company

Methodology for Designing Decision Support Systems for Visualising and Mitigating Supply Chain Cyber Risk from IoT Technologies

This paper proposes a methodology for designing decision support systems for visualising and mitigating the Internet of Things cyber risks. Digital technologies present new cyber risk in the supply chain which are often not visible to companies participating in the supply chains. This study investigates how the Internet of Things cyber risks can be visualised and mitigated in the process of designing business and supply chain strategies. The emerging DSS methodology present new findings on how digital technologies affect business and supply chain systems. Through epistemological analysis, the article derives with a decision support system for visualising supply chain cyber risk from Internet of Things digital technologies. Such methods do not exist at present and this represents the first attempt to devise a decision support system that would enable practitioners to develop a step by step process for visualising, assessing and mitigating the emerging cyber risk from IoT technologies on shared infrastructure in legacy supply chain systems