50,326 research outputs found
Framework for Product Lifecycle Management integration in Small and Medium Enterprises networks
In order to improve the performance of extended enterprises, Small and Medium Enterprises (SMEs) must be integrated into the extended networks. This integration must be carried out on several levels which are mastered by the Product Lifecycle Management (PLM). But, PLM is underdeveloped in SMEs mainly because of the difficulties in implementing information systems. This paper aims to propose a modeling framework to facilitate the implementation of PLM systems in SMEs. Our approach proposes a generic model for the creation of processes and data models. These models are explained, based on the scope and framework of the modeling, in order to highlight the improvements provided
A requirements engineering framework for integrated systems development for the construction industry
Computer Integrated Construction (CIC) systems are computer environments through which
collaborative working can be undertaken. Although many CIC systems have been developed to demonstrate the
communication and collaboration within the construction projects, the uptake of CICs by the industry is still
inadequate. This is mainly due to the fact that research methodologies of the CIC development projects are
incomplete to bridge the technology transfer gap. Therefore, defining comprehensive methodologies for the
development of these systems and their effective implementation on real construction projects is vital.
Requirements Engineering (RE) can contribute to the effective uptake of these systems because it drives the
systems development for the targeted audience. This paper proposes a requirements engineering approach for
industry driven CIC systems development. While some CIC systems are investigated to build a broad and deep
contextual knowledge in the area, the EU funded research project, DIVERCITY (Distributed Virtual Workspace
for Enhancing Communication within the Construction Industry), is analysed as the main case study project
because its requirements engineering approach has the potential to determine a framework for the adaptation of
requirements engineering in order to contribute towards the uptake of CIC systems
Designing as Construction of Representations: A Dynamic Viewpoint in Cognitive Design Research
This article presents a cognitively oriented viewpoint on design. It focuses
on cognitive, dynamic aspects of real design, i.e., the actual cognitive
activity implemented by designers during their work on professional design
projects. Rather than conceiving de-signing as problem solving - Simon's
symbolic information processing (SIP) approach - or as a reflective practice or
some other form of situated activity - the situativity (SIT) approach - we
consider that, from a cognitive viewpoint, designing is most appropriately
characterised as a construction of representations. After a critical discussion
of the SIP and SIT approaches to design, we present our view-point. This
presentation concerns the evolving nature of representations regarding levels
of abstraction and degrees of precision, the function of external
representations, and specific qualities of representation in collective design.
Designing is described at three levels: the organisation of the activity, its
strategies, and its design-representation construction activities (different
ways to generate, trans-form, and evaluate representations). Even if we adopt a
"generic design" stance, we claim that design can take different forms
depending on the nature of the artefact, and we propose some candidates for
dimensions that allow a distinction to be made between these forms of design.
We discuss the potential specificity of HCI design, and the lack of cognitive
design research occupied with the quality of design. We close our discussion of
representational structures and activities by an outline of some directions
regarding their functional linkages
Advancing Alternative Analysis: Integration of Decision Science.
Decision analysis-a systematic approach to solving complex problems-offers tools and frameworks to support decision making that are increasingly being applied to environmental challenges. Alternatives analysis is a method used in regulation and product design to identify, compare, and evaluate the safety and viability of potential substitutes for hazardous chemicals.Assess whether decision science may assist the alternatives analysis decision maker in comparing alternatives across a range of metrics.A workshop was convened that included representatives from government, academia, business, and civil society and included experts in toxicology, decision science, alternatives assessment, engineering, and law and policy. Participants were divided into two groups and prompted with targeted questions. Throughout the workshop, the groups periodically came together in plenary sessions to reflect on other groups' findings.We conclude the further incorporation of decision science into alternatives analysis would advance the ability of companies and regulators to select alternatives to harmful ingredients, and would also advance the science of decision analysis.We advance four recommendations: (1) engaging the systematic development and evaluation of decision approaches and tools; (2) using case studies to advance the integration of decision analysis into alternatives analysis; (3) supporting transdisciplinary research; and (4) supporting education and outreach efforts
Curriculum Guidelines for Undergraduate Programs in Data Science
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
Integration of decision support systems to improve decision support performance
Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
A decision support methodology to enhance the competitiveness of the Turkish automotive industry
This is the post-print (final draft post-refereeing) version of the article. Copyright @ 2013 Elsevier B.V. All rights reserved.Three levels of competitiveness affect the success of business enterprises in a globally competitive environment: the competitiveness of the company, the competitiveness of the industry in which the company operates and the competitiveness of the country where the business is located. This study analyses the competitiveness of the automotive industry in association with the national competitiveness perspective using a methodology based on Bayesian Causal Networks. First, we structure the competitiveness problem of the automotive industry through a synthesis of expert knowledge in the light of the World Economic Forum’s competitiveness indicators. Second, we model the relationships among the variables identified in the problem structuring stage and analyse these relationships using a Bayesian Causal Network. Third, we develop policy suggestions under various scenarios to enhance the national competitive advantages of the automotive industry. We present an analysis of the Turkish automotive industry as a case study. It is possible to generalise the policy suggestions developed for the case of Turkish automotive industry to the automotive industries in other developing countries where country and industry competitiveness levels are similar to those of Turkey
An analysis of the requirements traceability problem
In this paper1, we investigate and discuss the underlying nature
of the requirements traceability problem. Our work is based on
empirical studies, involving over 100 practitioners, and an
evaluation of current support. We introduce the distinction
between pre-requirements specification (pre-RS) traceability
and post-requirements specification (post-RS) traceability, to
demonstrate why an all-encompassing solution to the problem is
unlikely, and to provide a framework through which to
understand its multifaceted nature. We report how the majority
of the problems attributed to poor requirements traceability are
due to inadequate pre-RS traceability and show the fundamental
need for improvements here. In the remainder of the paper, we
present an analysis of the main barriers confronting such
improvements in practice, identify relevant areas in which
advances have been (or can be) made, and make
recommendations for research
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