Implementation Feasibility of a Digital Nervous System for the Construction Industry: For Efficient and Effective Information Management across the Project Lifecycle

The construction industry has long been considered as highly fragmented and non-collaborative industry. This fragmentation sprouted from complex and unstructured traditional coordination processes and information exchanges amongst all parties involved in a construction project. This nature coupled with risk and uncertainty has pushed clients and their supply chain to search for new ways of improving their business process to deliver better quality and high performing product. This research will closely investigate the need to implement a Digital Nervous System (DNS), analogous to a biological nervous system, on the flow and management of digital information across the project lifecycle. This will be through direct examination of the key processes and information produced in a construction project and how a DNS can provide a well-integrated flow of digital information throughout the project lifecycle. This research will also investigate how a DNS can create a tight digital feedback loop that enables the organisation to sense, react and adapt to changing project conditions. A Digital Nervous System is a digital infrastructure that provides a well-integrated flow of digital information to the right part of the organisation at the right time. It provides the organisation with the relevant and up-to-date information it needs, for critical project issues, to aid in near real-time decision-making. Previous literature review and survey questionnaires were used in this research to collect and analyse data about information management problems of the industry – e.g. disruption and discontinuity of digital information flow due to interoperability issues, disintegration/fragmentation of the adopted digital solutions and paper-based transactions. Results analysis revealed efficient and effective information management requires the creation and implementation of a DNS.

Os Sistemas de Informação Geográfica como ferramenta de apoio à decisão em Protecção Civil

Dissertação apresentada à Escola Superior Agrária do Instituto Politécnico de Castelo Branco para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Sistemas de Informação Geográfica - Recursos Agro-Florestais e Ambientais.

Contract appraisal system (CAPPS) : version 2.20 /

"January 1991."

Operations and Planning in Sustainable Power Systems

Thesis (Ph.D.)--University of Washington, 2016-06

Organisational learning - a critical systems thinking discipline

Original Paper European Journal of Information Systems (2001) 10, 135–146; doi:10.1057/palgrave.ejis.3000394 Organisational learning—a critical systems thinking discipline P Panagiotidis1,3 and J S Edwards2,4 1Deloitte and Touche, Athens, Greece 2Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK Correspondence: Dr J S Edwards, Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK. E-mail: j.s.edwards@aston.ac.uk 3Petros Panagiotidis is Manager responsible for the Process and Systems Integrity Services of Deloitte and Touche in Athens, Greece. He has a BSc in Business Administration and an MSc in Management Information Systems from Western International University, Phoenix, Arizona, USA; an MSc in Business Systems Analysis and Design from City University, London, UK; and a PhD degree from Aston University, Birmingham, UK. His doctorate was in Business Systems Analysis and Design. His principal interests now are in the ERP/DSS field, where he serves as project leader and project risk managment leader in the implementation of SAP and JD Edwards/Cognos in various major clients in the telecommunications and manufacturing sectors. In addition, he is responsible for the development and application of knowledge management systems and activity-based costing systems. 4John S Edwards is Senior Lecturer in Operational Research and Systems at Aston Business School, Birmingham, UK. He holds MA and PhD degrees (in mathematics and operational research respectively) from Cambridge University. His principal research interests are in knowledge management and decision support, especially methods and processes for system development. He has written more than 30 research papers on these topics, and two books, Building Knowledge-based Systems and Decision Making with Computers, both published by Pitman. Current research work includes the effect of scale of operations on knowledge management, interfacing expert systems with simulation models, process modelling in law and legal services, and a study of the use of artifical intelligence techniques in management accounting. Top of pageAbstract This paper deals with the application of critical systems thinking in the domain of organisational learning and knowledge management. Its viewpoint is that deep organisational learning only takes place when the business systems' stakeholders reflect on their actions and thus inquire about their purpose(s) in relation to the business system and the other stakeholders they perceive to exist. This is done by reflecting both on the sources of motivation and/or deception that are contained in their purpose, and also on the sources of collective motivation and/or deception that are contained in the business system's purpose. The development of an organisational information system that captures, manages and institutionalises meaningful information—a knowledge management system—cannot be separated from organisational learning practices, since it should be the result of these very practices. Although Senge's five disciplines provide a useful starting-point in looking at organisational learning, we argue for a critical systems approach, instead of an uncritical Systems Dynamics one that concentrates only on the organisational learning practices. We proceed to outline a methodology called Business Systems Purpose Analysis (BSPA) that offers a participatory structure for team and organisational learning, upon which the stakeholders can take legitimate action that is based on the force of the better argument. In addition, the organisational learning process in BSPA leads to the development of an intrinsically motivated information organisational system that allows for the institutionalisation of the learning process itself in the form of an organisational knowledge management system. This could be a specific application, or something as wide-ranging as an Enterprise Resource Planning (ERP) implementation. Examples of the use of BSPA in two ERP implementations are presented.

CORD an object model supporting statistical summary information for management decision making

Information systems have developed to the stage that there is plenty of data available in most organisations but there are still major problems in turning that data into information for management decision making. This thesis argues that the link between decision support information and transaction processing data should be through a common object model which reflects the real world of the organisation and encompasses the artefacts of the information system. The CORD (Collections, Objects, Roles and Domains) model is developed which is richer in appropriate modelling abstractions than current Object Models. A flexible Object Prototyping tool based on a Semantic Data Storage Manager has been developed which enables a variety of models to be stored and experimented with. A statistical summary table model COST (Collections of Objects Statistical Table) has been developed within CORD and is shown to be adequate to meet the modelling needs of Decision Support and Executive Information Systems. The COST model is supported by a statistical table creator and editor COSTed which is also built on top of the Object Prototyper and uses the CORD model to manage its metadata.

A process framework for selecting supply system architecture in manufacturing supply chains and networks

The process framework comprises three phases, as follows: scope the supply chain/network; identify the options for supply system architecture and select supply system architecture. It facilitates a structured approach that analyses the supply chain/network contextual characteristics, in order to ensure alignment with the appropriate supply system architecture. The process framework was derived from comprehensive literature review and archival case study analysis. The review led to the classification of supply system architectures according to their orientation, whether integrated; partially integrated; co-ordinated or independent. The classification was combined with the characteristics that influence the selection of supply system architecture to encapsulate the conceptual framework. It builds upon existing frameworks and methodologies by focusing on structured procedure; supporting project management; facilitating participation and clarifying point of entry. The process framework was initially tested in three case study applications from the food, automobile and hand tool industries. A variety of industrial settings was chosen to illustrate transferability. The case study applications indicate that the process framework is a valid approach to the problem; however, further testing is required. In particular, the use of group support system technologies to support the process and the steps involving the participation of software vendors need further testing. However, the process framework can be followed due to the clarity of its presentation. It considers the issue of timing by including alternative decision-making techniques, dependent on the constraints. It is useful for ensuring a sound business case is developed, with supporting documentation and analysis that identifies the strategic and functional requirements of supply system architecture.

The Inflation Index Prognosis Based on the Method of Decision-Marking “Tree”

The description of the support system for marking decision in terms of prognosing the inflation level based on the multifactor dependence represented by the decision – marking “tree” is given in the paper. The interrelation of factors affecting the inflation level – economic, financial, political, socio-demographic ones, is considered. The perspectives for developing the method of decision – marking “tree”, and pointing out the so- called “narrow” spaces and further analysis of possible scenarios for inflation level prognosing in particular, are defined.

About Problems of Decision Making in Social and Economic Systems

The reasons of a restricted applicability of the models of decision making in social and economic systems. 3 basic principles of growth of their adequacy are proposed: "localization" of solutions, direct account of influencing of the individual on process of decision making ("subjectivity of objectivity") and reduction of influencing of the individual psychosomatic characteristics of the subject (" objectivity of subjectivity ") are offered. The principles are illustrated on mathematical models of decision making in ecologically- economic and social systems.

A dynamic feature information model for integrated manufacturing planning and optimization

This paper presents a new, dynamic feature representation method for high value parts consisting of complex and intersecting features. The method first extracts features from the CAD model of a complex part. Then the dynamic status of each feature is established between various operations to be carried out during the whole manufacturing process. Each manufacturing and verification operation can be planned and optimized using the real conditions of a feature, thus enhancing accuracy, traceability and process control. The dynamic feature representation is complementary to the design models used as underlining basis in current CAD/CAM and decision support systems. © 2012 CIRP.

Discrete-event Simulation and Optimization to Improve the Performance of a Healthcare System

Thesis (Ph.D.)--University of Washington, 2016-08

An iterative analytical design framework for the optimal designing of an off-grid renewable energy based hybrid smart micro-grid

Creative ways of utilising renewable energy sources in electricity generation especially in remote areas and particularly in countries depending on imported energy, while increasing energy security and reducing cost of such isolated off-grid systems, is becoming an urgently needed necessity for the effective strategic planning of Energy Systems. The aim of this research project was to design and implement a new decision support framework for the optimal design of hybrid micro grids considering different types of different technologies, where the design objective is to minimize the total cost of the hybrid micro grid while at the same time satisfying the required electric demand. Results of a comprehensive literature review, of existing analytical, decision support tools and literature on HPS, has identified the gaps and the necessary conceptual parts of an analytical decision support framework. As a result this research proposes and reports an Iterative Analytical Design Framework (IADF) and its implementation for the optimal design of an Off-grid renewable energy based hybrid smart micro-grid (OGREH-SμG) with intra and inter-grid (μG2μG & μG2G) synchronization capabilities and a novel storage technique. The modelling design and simulations were based on simulations conducted using HOMER Energy and MatLab/SIMULINK, Energy Planning and Design software platforms. The design, experimental proof of concept, verification and simulation of a new storage concept incorporating Hydrogen Peroxide (H2O2) fuel cell is also reported. The implementation of the smart components consisting Raspberry Pi that is devised and programmed for the semi-smart energy management framework (a novel control strategy, including synchronization capabilities) of the OGREH-SμG are also detailed and reported. The hybrid μG was designed and implemented as a case study for the Bayir/Jordan area. This research has provided an alternative decision support tool to solve Renewable Energy Integration for the optimal number, type and size of components to configure the hybrid μG. In addition this research has formulated and reported a linear cost function to mathematically verify computer based simulations and fine tune the solutions in the iterative framework and concluded that such solutions converge to a correct optimal approximation when considering the properties of the problem. As a result of this investigation it has been demonstrated that, the implemented and reported OGREH-SμG design incorporates wind and sun powered generation complemented with batteries, two fuel cell units and a diesel generator is a unique approach to Utilizing indigenous renewable energy with a capability of being able to synchronize with other μ-grids is the most effective and optimal way of electrifying developing countries with fewer resources in a sustainable way, with minimum impact on the environment while also achieving reductions in GHG. The dissertation concludes with suggested extensions to this work in the future.

Infomobility for “Car-Driver” Systems: Reference Model and Case Study

Part 21: Mobility and Logistics