12,267 research outputs found
Recommended from our members
An effective uncertainty based framework for sustainable industrial product-service system transformation
Industrial Product-Service Systems (IPS2) can provide insights to enhance the environmental sustainability and lower environmental impact. However, its successful realisation for preventing the production of waste, while increasing efficiencies in the uses of energy and human capital remains a highly convoluted problem. This research article aims to address this issue by presenting an innovative uncertainty-based framework that can be used to assist in achieving increased sustainability within the context of IPS2. The developed framework explains the drivers for decision-making and cost to enable sustainability improvements in transforming to industrial services. This is based on academic literature, and multiple case studies of seven industrial companies with over 30âŻh of semi-structured interviews. The validation of the framework through two case studies demonstrates that uncertainty management can enable resource efficiency and offer sustainable transformation to service provision
Innovation Clusters: Combining Physical and Virtual Links
Innovation is increasingly seen as a collective action which involves many different actors operating in a cluster context. These clusters are usually conceived as local agglomerations. In this paper it will be argued that they are an important tool to study innovation, but the globalisation of companies and markets and the specific requirements of innovation processes require the expansion of cluster concepts towards virtual dimensions. It will be shown that the combination of local and virtual cluster links improves access to essential resources in innovation. An examples taken from the automotive component sector will illustrate the concept.Innovation, cluster dynamics, automotive components.
Sensor Data Visualisation: A Composition-Based Approach to Support Domain Variability
International audienceIn the context of the Internet of Things, sensors are surrounding our environment. These small pieces of electronics are inserted in everyday life's elements (e.g., cars, doors, radiators, smartphones) and continuously collect information about their environment. One of the biggest challenges is to support the development of accurate monitoring dashboard to visualise such data. The one-size-fits-all paradigm does not apply in this context, as user's roles are variable and impact the way data should be visualised: a building manager does not need to work on the same data as classical users. This paper presents an approach based on model composition techniques to support the development of such monitoring dashboards, taking into account the domain variability. This variability is supported at both implementation and modelling levels. The results are validated on a case study named SmartCampus, involving sensors deployed in a real academic campus
Realising Variability in Dynamic Software Product Line Solutions
Modern systems need to be able to self-adapt to changes in user needs, and changes affecting the system itself or its environment. Dynamic software product line (DSPL) is an engineering approach for developing self-adaptive systems based on commonalities and variabilities for a family of similar systems. Currently, many DSPL approaches fail to meet all adaptability requirements, and in many cases, they are developed in a such unstructured manner that the controller is not explicitly represented, for example. We specify a two-dimension taxonomy to address basic technical issues for realising variability in DSPLs. The self-adaptation dimension classifies the different design choices for the adaptability requirements. The DSPL variability dimension classifies different design choices for implementing variability schemes and for creating different kinds of feature models. Our study was substantiated by surveying several DSPL approaches, and evaluating and comparing their different design strategies. We also summarise practical issues and difficulties, identify major trends in actual DSPL proposals, and suggest directions for future
Information standards to support application and enterprise interoperability for the smart grid
Copyright @ 2012 IEEE.Current changes in the European electricity industry are driven by regulatory directives to reduce greenhouse gas emissions, at the same time as replacing aged infrastructure and maintaining energy security. There is a wide acceptance of the requirement for smarter grids to support such changes and accommodate variable injections from renewable energy sources. However the design templates are still emerging to manage the level of information required to meet challenges such as balancing, planning and market dynamics under this new paradigm. While secure and scalable cloud computing architectures may contribute to supporting the informatics challenges of the smart grid, this paper focuses on the essential need for business alignment with standardised information models such as the IEC Common Information Model (CIM), to leverage data value and control system interoperability. In this paper we present details of use cases being considered by National Grid, the GB transmission system operator for information interoperability in pan-network system management and planning.This study is financially supported by the National Grid, UK
An overview of recent research results and future research avenues using simulation studies in project management
This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented
- âŠ