Aitor Arnaiz

E-Maintenance: Trends, Challenges and Opportunities for Modern Industry

Abstract E-Maintenance has upraised growing interest in recent years. Equipment manufacturers seek to provide equipment-related services in an effort to increase their immunity to market variations. Furthermore, both equipment manufacturers and users are paying more attention to issues such as energy-efficiency and sustainability, in parallel with safety, quality and reduced costs. This emerging market landscape has given a boost to research in e-Maintenance, aimed at making more efficient use of resources and engineering assets. However, it seems that manufacturing companies and end users are somewhat uncertain on how to go ahead but also on which are the particular benefits they may gain with the adoption of e-Maintenance technologies. One reason is that various actors in this area of research offer somewhat differing views on the issue. This paper presents a generic view of e-Maintenance and points out both the benefits as well as the hurdles there still exist on the road to support the complete life cycle of a product with e-Maintenance, while providing a critical assessment of the current state of affairs. Based on this discussion, the paper seeks to assess how e-Maintenance will develop within the next five to ten years. Special emphasis is given on how the end users can benefit from e-Maintenance i.e. how radical the change really is and what are the financial implications related to its adoption.

Economical and technological prospects for e-maintenance

E-Maintenance has raised increased interest in recent years. During the last years we have seen the development of e-Maintenance techniques. The key elements are the extensive use of Internet that has exploded and rapid development of sensors and processing power. It can be claimed that the use of e-Maintenance at the moment still is at infant stage. This paper offers a generic view of e-Maintenance and points out both the benefits as well as the hurdles there still exist on the road to support the complete life cycle of a product with e-Maintenance, while providing a critical assessment of the current state of things. Based on this discussion, the paper seeks to assess how e-Maintenance will develop within the next five to ten years. Special emphasis is given on how the end users can benefit from e-Maintenance i.e. how radical the change really is and what are the financial implications related to its adoption.

Web services system for distributed technology upgrade within an e-maintenance framework

Nowadays, industrial maintenance is one of the most important tasks in the industry because its cost is too high, usually due to poor maintenance decisions. Traditionally, corrective maintenance and preventive maintenance are performed, but both of them, the excessive and the lacking maintenance can be harmful. In the last years, CBM (Condition Based Maintenance) technology or predictive maintenance has appeared in order to establish whether the system will fail during some future period and then take actions to avoid consequences. This paper shows the e-maintenance platform nicknamed DYNAWeb which is part of DYNAMITE project. DYNAWeb develops a CBM system based on OSA-CBM standard over MIMOSA comprising broad of capabilities like sensing and data acquisition, signal processing, health assessment, prognosis... This platform ensures the integration of all the components (software and hardware) using different technologies (sensor technologies, wireless communication technology) and providing them with agents and (Semantic) Web Services to allow the integration and the reuse among different applications.

Simulation of predictive maintenance strategies for cost-effectiveness analysis

This article presents a methodology that provides a continuous assessment of predictive maintenance (PdM) technologies with respect to specific business scenarios. The methodology integrates existing reliability and maintenance business analysis techniques and standards. The positive impacts that may have implementing these technologies have always been in mind. A critical simulation step is also added where different predictive maintenance strategies are simulated in order to obtain the optimal maintenance strategy. This Monte Carlo simulation relies on the reliability information based on the probability density distribution of failure for the system or component, providing as a result the optimal strategy among the proposed options. The article finally explains how this methodology has a positive impact not only on the cost-effectiveness of maintenance processes, but also on the maintenance information available.

Optimizing E-Maintenance Through Intelligent Data Processing Systems

The landscape of maintenance and asset management has been reshaped as key technology enablers that are making a significant impact on everyday applications. The growing maturing of web-based and semantic maintenance, the ubiquity of mobile and situated computing, and the lowered costs and increased capabilities of wireless sensing and identification technologies are among the enabling technologies having the most significant impact. They are recognized as the key constituents of eMaintenance, the technological framework that empowers organizations to streamline their asset management services and data delivery across the maintenance operations chain. This paper takes a look at these key, contributing technologies, alongside their adoption prospects and current hurdles preventing the wider penetration of eMaintenance in industry.

Information and Communication Technologies Within E-maintenance

This chapter describes the state of the art in information and communication technologies (ICT) related to maintenance and its future trends. Several topics apply, from pure technological advances in acquisition, communication and storage of information, to the identification of advanced information standards for systems interoperability, such as MIMOSA and open system architecture for condition based maintenance (OSA-CBM) (Bengtsson 2004).

Towards a Semantic Outlier Detection Framework in Wireless Sensor Networks

Outlier detection in the preprocessing phase of Knowledge Discovery in Databases (KDD) processes has been a widely researched topic for many years. However, identifying the potential outlier cause still remains an unsolved challenge even though it could be very helpful for determining what actions to take after detecting it. Furthermore, conventional outlier detection methods might still overlook outliers in certain complex contexts. In this article, Semantic Technologies are used to contribute overcoming these problems by proposing the SemOD (Semantic Outlier Detection) Framework. This framework guides the data-scientist towards the detection of certain types of outliers in WSNs (Wireless Sensor Network). Feasibility of the approach has been tested in outdoor temperature sensors and results show that the proposed approach is generic enough to apply it to different sensors, even improving the accuracy, specificity and sensitivity of outlier detection as well as spotting their potential cause.

A Hybrid Optimization Algorithm for Standardization of Maintenance Plans.

This paper presents an algorithm to solve the combinatorial optimization problem in the definition of preventive maintenance plans. This problem is not easy to solve, since tasks performed on assets can be redundant or not required. The objective is a more accurate definition of plans to reduce maintenance costs, where different optimization algorithms can be used. Taking a single optimization algorithm approach could serve to find an optimal solution depending of the use case, but it does not find reliable results in a generic way. The new hybrid approach with 4 different algorithms shows that better results are obtained than the use of the individual optimization algorithms.

Sentiment Analysis Techniques for Positive Language Development

With the growing availability and popularity of opinion-rich resources such as on-line review sites and personal blogs, the use of information technologies to seek out and understand the opinions of others has increased significantly. This paper presents Posimed, a sentiment assessment approach that focuses on verbal language using information technologies for Spanish. We describe how Posimed combines natural language technologies for Spanish and expert domain knowledge to extract relevant sentiment and attitude information units from conversations between people (from interviews, coaching sessions, etc.) and supports the programmes that positivity training experts provide in order to develop the Positivity competence. We have evaluated Posimed both in a quantitative and a qualitative way and these evaluations show that Posimed provides an accurate analysis (73%) and reduces significantly (80% reduction) the time for the same job when it is performed manually by the domain expert.

A probabilistic model for cognitive-affective user state awareness

In this work we describe a cognitive model to infer the more likely users states in data-intensive contexts. Stress, mental fatigue, or even inaptitude, are selected to be inferred by the model based two sources of information: context and psycho-physiological sensors network. As long as a complex, high demanding context will predict those cognitive states that, in turn, will be diagnosed by the set of sensors (EEG and ECG). All these input variables are represented in a probabilistic model in which links are defined based on the literature. The outcome of the model is a probability of being inapt to perform in a suitable way. In case of inaptitude, assistance should be delivered to the user to normalize the current users state.