59,730 research outputs found
Wireless industrial monitoring and control networks: the journey so far and the road ahead
While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks
A framework for effective management of condition based maintenance programs in the context of industrial development of E-Maintenance strategies
CBM (Condition Based Maintenance) solutions are increasingly present in industrial systems due to two
main circumstances: rapid evolution, without precedents, in the capture and analysis of data and
significant cost reduction of supporting technologies. CBM programs in industrial systems can become
extremely complex, especially when considering the effective introduction of new capabilities provided
by PHM (Prognostics and Health Management) and E-maintenance disciplines. In this scenario, any CBM
solution involves the management of numerous technical aspects, that the maintenance manager needs
to understand, in order to be implemented properly and effectively, according to the company’s strategy.
This paper provides a comprehensive representation of the key components of a generic CBM solution,
this is presented using a framework or supporting structure for an effective management of the CBM
programs. The concept “symptom of failure”, its corresponding analysis techniques (introduced by ISO
13379-1 and linked with RCM/FMEA analysis), and other international standard for CBM open-software
application development (for instance, ISO 13374 and OSA-CBM), are used in the paper for the
development of the framework. An original template has been developed, adopting the formal structure
of RCM analysis templates, to integrate the information of the PHM techniques used to capture the failure
mode behaviour and to manage maintenance. Finally, a case study describes the framework using the
referred template.Gobierno de AndalucĂa P11-TEP-7303 M
Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor
The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities
Incremental Consistency Checking in Delta-oriented UML-Models for Automation Systems
Automation systems exist in many variants and may evolve over time in order
to deal with different environment contexts or to fulfill changing customer
requirements. This induces an increased complexity during design-time as well
as tedious maintenance efforts. We already proposed a multi-perspective
modeling approach to improve the development of such systems. It operates on
different levels of abstraction by using well-known UML-models with activity,
composite structure and state chart models. Each perspective was enriched with
delta modeling to manage variability and evolution. As an extension, we now
focus on the development of an efficient consistency checking method at several
levels to ensure valid variants of the automation system. Consistency checking
must be provided for each perspective in isolation, in-between the perspectives
as well as after the application of a delta.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857
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The uses of process modeling : a framework for understanding modeling formalisms
There is wide-spread recognition of the urgent need to improve software processes in order to improve the performance of software organizations. Process models are essential in achieving understanding and visibility of processes and are important for other uses including the analysis of processes for improvement. It has been increasingly difficult to compare and evaluate the variety of process modeling formalisms that have appeared in recent years without a clear understanding of precisely for what they will be used. The contribution of this paper is to provide an understanding and a fairly comprehensive catalog of the applications of process modeling for which formalisms may be used. The primary mechanism for doing this is a guided tour of the literature on process modeling supplemented by recent industrial experience. In the paper, basic definitions concerning processes, process descriptions and process modeling are reviewed and then uses of process modeling are surveyed under the following headings: communication among process participants, construction of new processes, control of processes, process· analysis, and process support by automation. Comments are offered on paradigms for process modeling formalisms and directions for future work to permit evolution of a discipline of process engineering are given
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
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