Gregoris Mentzas

A proactive decision making framework for condition-based maintenance

– The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM. , – Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed. , – In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified. , – The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required. , – The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.

Managing Imprecise Criteria in Cloud Service Ranking with a Fuzzy Multi-criteria Decision Making Method

The increase of cloud technology solutions has made the evaluation and selection of desired cloud services, a cumbersome task for the user. In particular, the lack of standard mechanisms that allow the comparison of cloud service specifications against user requirements taking into account the implicit uncertainty and vagueness is a major hindrance during the cloud service evaluation and selection. In this paper, we discuss an alternative classification of metrics used for ranking cloud services based on their level of fuzziness and present an approach that allows cloud service evaluation based on a heterogeneous model of service characteristics. Our approach allows the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics. We use fuzzy numbers to model the imprecise service characteristics and vague user preferences and we validate a fuzzy AHP approach that solves the problem of service ranking.

Review, analysis and synthesis of prognostic-based decision support methods for condition based maintenance

In manufacturing enterprises, maintenance is a significant contributor to the total company’s cost. Condition based maintenance (CBM) relies on prognostic models and uses them to support maintenance decisions based on the predicted condition of equipment. Although prognostic-based decision support for CBM is not an extensively explored area, there exist methods which have been developed in order to deal with specific challenges such as the need to cope with real-time information, to predict the health state of equipment and to continuously update maintenance-related recommendations. The current work aims at providing a literature review for prognostic-based decision support methods for CBM. We analyse the literature in order to identify combinations of methods for prognostic-based decision support for CBM, propose a practical technique for selecting suitable combinations of methods and set the guidelines for future research.

A Real-Time Architecture for Proactive Decision Making in Manufacturing Enterprises

We outline a new architecture for supporting proactive decision making in manufacturing enterprises. We argue that event monitoring and data processing technologies can be coupled with decision methods effectively providing capabilities for proactive decision-making. We present the main conceptual blocks of the architecture and their role in the realization of the proactive enterprise. We illustrate how the proposed architecture supports decision-making ahead of time on the basis of real-time observations and anticipation of future undesired events by presenting a practical condition-based maintenance scenario in the oil and gas industry. The presented approach provides the technological foundation and can be taken as a blueprint for the further development of a reference architecture for proactive applications.

Context-aware Security Models for PaaS-enabled Access Control

Enterprises are embracing cloud computing in order to reduce costs and increase agility in their everyday business operations. Nevertheless, due mainly to confidentiality, privacy and integrity concerns, many are still reluctant to migrate their sensitive data to the cloud. In this paper, firstly, we outline the construction of a suitable Context-aware Security Model, for enhancing security in cloud applications. Secondly, we outline the construction of an extensible and declarative formalism for representing policy-related knowledge, one which disentangles the definition of a policy from the code employed for enforcing it. Both of them will be employed for supporting innovative PaaS-enabled access control mechanisms.

Advanced service brokerage capabilities as the catalyst for future cloud service ecosystems

Market analysts have foreseen the emergence of cloud brokers in the mediation of cloud services. But rather than focus on current kinds of intermediary role, it is more constructive to consider the kinds of brokerage capability that could be offered in the future, which go far beyond the integration, aggregation and customization services available today. This paper identifies advanced capabilities for cloud service governance, quality assurance and optimization that will be critical in catalyzing the emergence of cloud service ecosystems, environments in which all parties will find their symbiotic niches. It shows the path whereby a platform provider could evolve to become the hub of a cloud service ecosystem, through gradually taking on more of these advanced brokerage capabilities. The paper provides an overview of work conducted by the EU FP7 Broker@Cloud project towards realizing these advanced brokerage capabilities.

Supporting the Selection of Prognostic-based Decision Support Methods in Manufacturing

In manufacturing enterprises, maintenance is a significant contributor to the total companyâx80x99s cost. Condition n nBased Maintenance (CBM) relies on prognostic models and uses them to support maintenance decisions n nbased on the current and predicted health state of equipment. Although decision support for CBM is not an n nextensively explored area, there exist methods which have been developed in order to deal with specific n nchallenges such as the need to cope with real-time information, to prognose the health state of equipment n nand to continually update decision recommendations. We propose an approach for supporting analysts n nselecting the most suitable combination(s) of methods for prognostic-based maintenance decision support n naccording to the requirements of a given maintenance application. Our approach is based on the ID3 n ndecision tree learning algorithm and is applied in a maintenance scenario in the oil and gas industry.

Preference-based cloud service recommendation as a brokerage service

As the multitude and complexity of cloud services increases, the role of cloud brokers in the cloud service ecosystems becomes increasingly important. In particular, the lack of standard mechanisms that allow for the comparison of cloud service specifications against user requirements taking into account the implicit uncertainty and vagueness is a major hindrance during the cloud service evaluation and selection. In this paper, we discuss the Preference-based cLoud Service Recommender (PuLSaR) that uses a holistic multi-criteria decision making (MCDM) approach for offering optimisation as brokerage service. The specification and implementation details of this dedicated software are thoroughly discussed while the background method used is summarised. Both method and brokerage service allow for the multi-objective assessment of cloud services in a unified way, taking into account precise and imprecise metrics and dealing with their fuzziness.

Data Distribution and Encryption Modelling for PaaS-enabled Cloud Security

Some of the most valuable business benefits that accompany the cloud adoption cannot be exploited without addressing, first, new data security challenges posed by cloud computing distributed nature. A promising approach for alleviating these risks is to provide a security-by-design framework that will assist cloud application developers in defining appropriate context-driven policies that enhance cloud security at design-time and enforce access control at run-time. This paper discusses a generic and extensible formalism, called Context-aware Security Policy Model that can be tailored to the particular needs of different cloud applications for enhancing the privacy and confidentiality of sensitive data.

A survey on context security policies in the cloud

With the pervasion of cloud computing new security risks are created. A promising approach to alleviating these risks is to provide a security-by-design framework that will assist cloud application developers in defining appropriate context-driven access control policies. This paper surveys different approaches to context-driven access control, as well as different modelling formalisms for representing access control policies. The aim of this survey is to assess the appropriateness of existing approaches for the construction of a generic security-by-design framework, in particular one which is exposed as a PaaS offering.