Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable ‘Human in the loop’ interactions

Towards next generation coordination infrastructures

Coordination infrastructures play a central role in the engineering of multiagent systems. Since the advent of agent technology, research on coordination infrastructures has produced a significant number of infrastructures with varying features. In this paper, we review the the state-of-the-art coordination infrastructures with the purpose of identifying open research challenges that next generation coordination infrastructures should address. Our analysis concludes that next generation coordination infrastructures must address a number of challenges: (i) to become socially aware, by facilitating human interaction within a MAS; (ii) to assist agents in their decision making by providing decision support that helps them reduce the scope of reasoning and facilitates the achievement of their goals; and (iii) to increase openness to support on-line, fully decentralised design and execution. Furthermore, we identify some promising approaches in the literature, together with the research issues worth investigating, to cope with such challenges. © Cambridge University Press, 2015.The work presented in this paper has been partially funded by projects EVE (TIN2009-14702-C02-01), AT (CSD2007-0022), and the Generalitat of Catalunya grant 2009-SGR-1434Peer Reviewe

Defining and implementing a distributed and reconfigurable information system for prognostics.

International audienceAccording to Condition Based Maintenance practitioners, various activities, ranging from data collection through the recommendation of specific maintenance actions, must be carried out to perform predictive maintenance. Nevertheless, in practice, (and in spite of recommendations like those ones of the OSA-CBM standard), defining and implementing a computer software system for CBM is not a trivial task. That can be mostly explained by the necessity of providing a distributed application that enables to share data and information in an easy but effective manner in-between various actors from various industrial plants. Following that, the aim of the paper is to describe a collaborative software that has been developed in the society e-m@systec. Its simple architecture, as well as its evolving and customizable capabilities make the global information system as useful for distributed applications. The usage of JEE technology improves the portability of the system. This software is well adapted to support predictive maintenance strategies. Thereby and as for an illustration, an example related to a prognostic problem is also described

Towards next generation coordination infrastructures

Coordination infrastructures play a central role in the engineering of multiagent systems. Since the advent of agent technology, research on coordination infrastructures has produced a significant number of infrastructures with varying features. In this paper, we review the the state-of-the-art coordination infrastructures with the purpose of identifying open research challenges that next generation coordination infrastructures should address. Our analysis concludes that next generation coordination infrastructures must address a number of challenges: (i) to become socially aware, by facilitating human interaction within a MAS; (ii) to assist agents in their decision making by providing decision support that helps them reduce the scope of reasoning and facilitates the achievement of their goals; and (iii) to increase openness to support on-line, fully decentralised design and execution. Furthermore, we identify some promising approaches in the literature, together with the research issues worth investigating, to cope with such challenges

Automatic analysis of Pole Mounted Auto-Recloser data for fault diagnosis and prognosis

Fault diagnosis is a key part of a control and protection engineer’s role to ensure the effective and stable performance of electrical power networks. One challenge is to support the analysis and application of expert judgement to the, often, large data sets generated. To assist engineers with this task and improve network reliability, this research focuses on analysing previous fault activity in order to obtain an early-warning report to assist fault diagnosis and fault prognosis. This paper details the design of an integrated system with a fault diagnosis algorithm utilising available Supervisory Control And Data Acquisition (SCADA) alarm data and 11kV distribution network data captured from Pole Mounted Auto-Reclosers (PMARs) (provided by a leading UK network operator). The developed system will be capable of diagnosing the nature of a circuit’s previous fault activity, underlying circuit activity and evolving fault activity and the risk of future fault activity. This will provide prognostic decision support for network operators and maintenance staff

A Briefing on Metrics and Risks for Autonomous Decision-Making in Aerospace Applications

Significant technology advances will enable future aerospace systems to safely and reliably make decisions autonomously, or without human interaction. The decision-making may result in actions that enable an aircraft or spacecraft in an off-nominal state or with slightly degraded components to achieve mission performance and safety goals while reducing or avoiding damage to the aircraft or spacecraft. Some key technology enablers for autonomous decision-making include: a continuous state awareness through the maturation of the prognostics health management field, novel sensor development, and the considerable gains made in computation power and data processing bandwidth versus system size. Sophisticated algorithms and physics based models coupled with these technological advances allow reliable assessment of a system, subsystem, or components. Decisions that balance mission objectives and constraints with remaining useful life predictions can be made autonomously to maintain safety requirements, optimal performance, and ensure mission objectives. This autonomous approach to decision-making will come with new risks and benefits, some of which will be examined in this paper. To start, an account of previous work to categorize or quantify autonomy in aerospace systems will be presented. In addition, a survey of perceived risks in autonomous decision-making in the context of piloted aircraft and remotely piloted or completely autonomous unmanned autonomous systems (UAS) will be presented based on interviews that were conducted with individuals from industry, academia, and government

Towards the internet of agents: an analysis of the internet of things from the intelligence and autonomy perspective

Recently, the scientific community has demonstrated a special interest in the process related to the integration of the agent-oriented technology with Internet of Things (IoT) platforms. Then, it arises a novel approach named Internet of Agents (IoA) as an alternative to add an intelligence and autonomy component for IoT devices and networks. This paper presents an analysis of the main benefits derived from the use of the IoA approach, based on a practical point of view regarding the necessities that humans demand in their daily life and work, which can be solved by IoT networks modeled as IoA infrastructures. It has been presented 24 study cases of the IoA approach at different domains ––smart industry, smart city and smart health wellbeing–– in order to define the scope of these proposals in terms of intelligence and autonomy in contrast to their corresponding generic IoT applications.En los últimos años, la comunidad científica ha mostrado un interés especial en torno al proceso de integración de la tecnología orientada a agentes sobre plataformas de Internet de las Cosas (IoT, por sus siglas en inglés). Surge así, un nuevo enfoque denominado Internet de los Agentes (IoA, por sus siglas en inglés) como una alternativa para añadir un componente de inteligencia y autonomía sobre los dispositivos y redes de IoT. El presente trabajo muestra un análisis de los principales beneficios derivados del uso del enfoque del IoA, visto desde las actuales necesidades que el ser humano demanda en su trabajo y vida cotidiana, las cuales pueden ser resueltas por redes de IoT modeladas como infraestructuras de IoA. Se plantea un total de 24 casos prácticos de aplicaciones de IoA en diferentes dominios ––industria, ciudad, y salud y bienestar inteligente–– a fin de determinar el alcance de dichas aplicaciones en términos de inteligencia y autonomía respecto a sus correspondientes aplicaciones genéricas de IoT.This study was founded by the Ecuadorian Ministry of Higher Education, Science, Technology and Innovation (SENESCYT)