Engineering design knowledge management in de-centralised virtual enterprises

The problems of collaborative engineering design and knowledge management at the conceptual stage in a network of dissimilar enterprises was investigated. This issue in engineering design is a result of the supply chain and virtual enterprise (VE) oriented industry that demands faster time to market and accurate cost/manufacturing analysis from conception. The solution consisted of a de-centralised super-peer net architecture to establish and maintain communications between enterprises in a VE. In the solution outlined below, the enterprises are able to share knowledge in a common format and nomenclature via the building-block shareable super-ontology that can be tailored on a project by project basis, whilst maintaining the common nomenclature of the ‘super-ontology’ eliminating knowledge interpretation issues. The two-tier architecture layout of the solution glues together the peer-peer and super-ontologies to form a coherent system for both internal and virtual enterprise knowledge management and product development

Open Standard, Open Source and Peer to Peer Methods for Collaborative Product Development and Knowledge Management

Tools such as product data management (PDM) and its offspring product lifecycle management (PLM) enable collaboration within and between enterprises. Large enterprises have invariably been the target of software vendors for development of such tools, resulting in large entralized applications. These are beyond the means of small to medium enterprises (SME). Even after these efforts had been made, large enterprises face numerous difficulties with PLM. Firstly, enterprises evolve, and an evolving enterprise needs an evolving data management system. With large applications, such configuration changes have to be made at the server level by dedicated staff. The second problem arises when enterprises wish to collaborate with a large number of suppliers and original equipment manufacturer (OEM) customers. Current applications enable collaboration using business-to-business (B2B) protocols. However, these do not take into account that disparate enterprises do not have unitary data models or workflows. This is a strong factor in reducing the abilities of large enterprises to participate in collaborative project

Interorganizational Information Systems: Systematic Literature Mapping Protocol

Organizations increasingly need to establish partnerships with other organizations to face environment changes and remain competitive. This interorganizational relationship allows organizations to share resources and collaborate to handle business opportunities better. This technical report present the protocol of the systematic mapping performed to understand what is an IOIS and how these systems support interorganizational relationships

Service-oriented middleware for managing inter-enterprise collaborations

Peer reviewe

Campus Communications Systems: Converging Technologies

This book is a rewrite of Campus Telecommunications Systems: Managing Change, a book that was written by ACUTA in 1995. In the past decade, our industry has experienced a thousand-fold increase in data rates as we migrated from 10 megabit links (10 million bits per second) to 10 gigabit links (10 billion bits per second), we have seen the National Telecommunications Policy completely revamped; we have seen the combination of voice, data, and video onto one network; and we have seen many of our service providers merge into larger corporations able to offer more diverse services. When this book was last written, A CUT A meant telecommunications, convergence was a mathematical term, triple play was a baseball term, and terms such as iPod, DoS, and QoS did not exist. This book is designed to be a communications primer to be used by new entrants into the field of communications in higher education and by veteran communications professionals who want additional information in areas other than their field of expertise. There are reference books and text books available on every topic discussed in this book if a more in-depth explanation is desired. Individual chapters were authored by communications professionals from various member campuses. This allowed the authors to share their years of experience (more years than many of us would care to admit to) with the community at large. Foreword Walt Magnussen, Ph.D. Preface Ron Kovac, Ph.D. 1 The Technology Landscape: Historical Overview . Walt Magnussen, Ph.D. 2 Emerging Trends and Technologies . Joanne Kossuth 3 Network Security . Beth Chancellor 4 Security and Disaster Planning and Management Marjorie Windelberg, Ph.D. 5 Student Services in a University Setting . Walt Magnussen, Ph.D. 6 Administrative Services David E. O\u27Neill 7 The Business Side of Information Technology George Denbow 8 The Role of Consultants . David C. Metz Glossary Michelle Narcavag

A methodology for the distributed and collaborative management of engineering knowledge

The problems of collaborative engineering design and management at the conceptual stage in a large network of dissimilar enterprises was investigated. This issue in engineering design is a result of the supply chain and virtual enterprise (VE) oriented industry that demands faster time to market and accurate cost/manufacturing analysis from conception. Current tools and techniques do not completely fulfil this requirement due to a lack of coherent inter-enterprise collaboration and a dearth of manufacturing knowledge available at the concept stage. Client-server and peer to peer systems were tested for communication, as well as various techniques for knowledge management and propagation including Product Lifecycle Management (PLM) and expert systems. As a result of system testing, and extensive literature review, several novel techniques were proposed and tested to improve the coherent management of knowledge and enable inter-enterprise collaboration. The techniques were trialled on two engineering project examples. An automotive Tier-1 supplier which designs products whose components are sub­contracted to a large supply chain and assembled for an Original Equipment Manufacturer (OEM) was used as a test scenario. The utility of the systems for integrating large VEs into a coherent project with unified specifications were demonstrated in a simple example, and problems associated with engineering document management overcome via re-usable, configurable, object oriented ontologies propagated throughout the VE imposing a coherent nomenclature and engineering product definition. All knowledge within the system maintains links from specification - concept - design - testing through to manufacturing stages, aiding the participating enterprises in maintaining their knowledge and experience for future projects. This potentially speeds the process of innovation by enabling companies to concentrate on value-added aspects of designs whilst ‘bread-and-butter’ expertise is reused. The second example, a manufacturer of rapid-construction steel bridges, demonstrated the manufacturing dimension of the methodology, where the early stage of design, and the generation of new concepts by reusing existing manufacturing knowledge bases was demonstrated. The solution consisted of a de-centralised super-peer net architecture to establish and maintain communications between enterprises in a VE. The enterprises are able to share knowledge in a common format and nomenclature via the building-block shareable super-ontology that can be tailored on a project by project basis, whilst maintaining the common nomenclature of the ‘super-ontology’ eliminating knowledge interpretation issues. The two-tier architecture developed as part of the solution glues together the peer-peer and super-ontologies to form a coherent system for internal knowledge management and product development as well as external virtual enterprise product development and knowledge management. In conclusion, the methodology developed for collaboration and knowledge management was shown to be more appropriate for use by smaller enterprises collaborating in a large Virtual Enterprise than PLM technology in terms of: usability, configurability, cost of system and individual control over intellectual property rights

DATA ANALYTICS FOR CRISIS MANAGEMENT: A CASE STUDY OF SHARING ECONOMY SERVICES IN THE COVID-19 PANDEMIC

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data

Data Analytics for Crisis Management: A Case Study of Sharing Economy Services in the COVID-19 Pandemic

This dissertation study aims to analyze the role of data-driven decision-making in sharing economy during the COVID-19 pandemic as a crisis management tool. In the twenty-first century, when applying analytical tools has become an essential component of business decision-making, including operations on crisis management, data analytics is an emerging field. To carry out corporate strategies, data-driven decision-making is seen as a crucial component of business operations. Data analytics can be applied to benefit-cost evaluations, strategy planning, client engagement, and service quality. Data forecasting can also be used to keep an eye on business operations and foresee potential risks. Risk Management and planning are essential for allocating the necessary resources with minimal cost and time and to be ready for a crisis. Hidden market trends and customer preferences can help companies make knowledgeable business decisions during crises and recessions. Each company should manage operations and response during emergencies, a path to recovery, and prepare for future similar events with appropriate data management tools. Sharing economy is part of social commerce, that brings together individuals who have underused assets and who want to rent those assets short-term. COVID-19 has emphasized the need for digital transformation. Since the pandemic began, the sharing economy has been facing challenges, while market demand dropped significantly. Shelter-in-Place and Stay-at-Home orders changed the way of offering such sharing services. Stricter safety procedures and the need for a strong balance sheet are the key take points to surviving during this difficult health crisis. Predictive analytics and peer-reviewed articles are used to assess the pandemic\u27s effects. The approaches chosen to assess the research objectives and the research questions are the predictive financial performance of Uber & Airbnb, bibliographic coupling, and keyword occurrence analyses of peer-reviewed works about the influence of data analytics on the sharing economy. The VOSViewer Bibliometric software program is utilized for computing bibliometric analysis, RapidMiner Predictive Data Analytics for computing data analytics, and LucidChart for visualizing data