Context Awareness in Predictive Maintenance

Aesthetic defects are a violation of quality attributes that are symptoms of bad interface design programming decisions. They lead to deteriorating the perceived usability of mobile user interfaces and negatively impact the Users eXperience (UX) with the mobile app. Most existing studies relied on a subjective evaluation of aesthetic defects depending on end-users feedback, which makes the manual evaluation of mobile user interfaces human-centric, time-consuming, and error-prone. Therefore, recent studies have dedicated their effort to focus on the definition of mathematical formulas that each targets a specific structural quality of the interface. As the UX is tightly dependent on the user profile, the combination and calibration of quality attributes, formulas, and users characteristics, when defining a defect, is not straightforward. In this context, we propose a fully automated framework which combines literature quality attributes with the users profile to identify aesthetic defects of MUI. More precisely, we consider the mobile user interface evaluation as a multi-objective optimization problem where the goal is to maximize the number of detected violations while minimizing the detection complexity of detection rules and enhancing the interfaces overall quality in means

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“…-Software: which is the set of applications installed on the platform including an operating system, virtual machine,. [81,90,75].…”

Section: Context Modelingmentioning

confidence: 99%

“…-Geographical element: GPS coordinates or the type of space like a station or a store,... [31,71,43]. -Physical environment or environment condition like luminosity, noise, weather, ... [80,55,92,81,75]. For example, the luminosity which is a measurement of brightness or light can involve a change at the level of the used colors.…”

Section: Context Modelingmentioning

confidence: 99%

Assessing the quality of mobile graphical user interfaces using multi-objective optimization

et al. 2019

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“…In literature, several works have been established which attempt to consolidate the concept of context-aware with asset management such as context-awareness predictive maintenance [11], context-aware e-maintenance [12] and context-aware condition monitoring [10]. Two limitations are drawn from previous works: (1) the scope of applicability of proposed concept is limited given the fact that it only concerns partial aspect of the supervision process, For instance, the work of [11] concerns predictive maintenance, it lacks details regards how context been modeled and processed. (2) most works stay on a conceptual level which lacks sufficient technical details on how to put the concept into practice.…”

Section: Context-aware Supervision Systemmentioning

confidence: 99%

An Intelligent Context-aware System for Logistics Asset Supervision Service

Feng

Pang

Lodewijks

2016

Annals of Computer Science and Information Systems

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Abstract-The use of Information and Communication Technology (ICT) has touched various aspects in the domain of transport engineering and logistics (TEL). As the development of TEL tends to be more complex in operation and large in scale, recent practices start to pay more attentions on improving system robustness and reliability. In addition, current ICT innovations (such as WSN and IOT) could record and deliver system descriptors (physical measurements, virtual resources, operational configurations) in real time. Such large-stream and heterogeneous data requires an integrated framework to process and management. To address such challenges, in this paper, a novel concept of context-aware supervision is proposed. An intelligent system with integration of semantic web and agent technology is proposed to support the concept realization, which aims at providing condition-monitoring and maintenance service to relevant user. A generic ontology-agent based framework will be illustrated. Finally, it will be applied for the supervision of a large-scale material handling system-belt conveying system as a proof-of-concept.

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“…An entity is a person, place, or object that is considered relevant to the interaction between a user and an application, including the user and applications themselves" (Perera et al, 2014). Context-aware systems are adaptable to the existing and future possible environments without the interactions of users and process the context models based on the context lifecycle steps: acquisition, modelling, reasoning and dissemination (Perera et al, 2014;Schmidt et al, 2016).…”

Section: State-of-the-art Analysismentioning

confidence: 99%

“…Context-aware systems are adaptable to the existing and future possible environments without the interactions of users and process the context models based on the context lifecycle steps: acquisition, modelling, reasoning and dissemination (Perera et al, 2014;Schmidt et al, 2016). However, research on con-text-aware systems has focused on reactive applications rather than proactive ones that could enrich proactive event-driven decision making.…”

Section: State-of-the-art Analysismentioning

confidence: 99%

Proactive computing in industrial maintenance decision making

Bousdekis¹,

Μπουσδέκης²

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Η προδραστική πληροφορική οδηγούμενη από γεγονότα αφορά τη χρήση πληροφοριακών συστημάτων οδηγούμενων από γεγονότα που έχουν την ικανότητα να εξαλείφουν ή να αμβλύνουν την επίδραση μελλοντικών ανεπιθύμητων γεγονότων ή να αξιοποιούν μελλοντικές ευκαιρίες με βάση δεδομένα αισθητήρων πραγματικού χρόνου και τεχνολογίες λήψης αποφάσεων. Η διοίκηση συντήρησης μπορεί να επωφεληθεί από την προδραστική πληροφορική για να αντιμετωπίσει τις προκλήσεις στο πλαίσιο της Βιομηχανίας 4.0 (Industry 4.0).Για το σκοπό αυτό, η παρούσα διατριβή συνδυάζει τους ερευνητικούς τομείς της Βιομηχανίας 4.0, της Διοίκησης Συντήρησης και της Προδραστικής Πληροφορικής. Με αυτό τον τρόπο, ανοίγει το δρόμο για την επόμενη γενιά διοίκησης συντήρησης στο πλαίσιο της Βιομηχανίας 4.0, την Προδραστική Συντήρηση (Proactive Maintenance). Το επίκεντρο της διατριβής είναι η λήψη προδραστικών αποφάσεων. Συνεπώς, προτείνει μεθόδους προδραστικών αποφάσεων για βιομηχανική συντήρηση, αλγόριθμους για συνεχή βελτίωση της λήψης προδραστικών αποφάσεων μέσω της προτεινόμενης προσέγγισης Ανατροφοδότηση Υποβοηθούμενη από Αισθητήρες (Sensor-Enabled Feedback - SEF) και αλγόριθμους για την επίγνωση πλαισίου. Για να γίνει αυτό, αξιοποιεί μεθόδους και τεχνικές επιχειρησιακής έρευνας, ανάλυσης δεδομένων και μηχανικής μάθησης.Οι προαναφερθέντες αλγόριθμοι έχουν ενσωματωθεί σε ένα προδραστικό πληροφοριακό σύστημα για τη λήψη αποφάσεων το οποίο ολοκληρώθηκε με άλλα εργαλεία για την υλοποίηση όλων των βημάτων του πλαισίου της Προδραστικής Συντήρησης. Το σύστημα εγκαταστάθηκε και αξιολογήθηκε σε πραγματικό βιομηχανικό περιβάλλον, ενώ πραγματοποιήθηκε περαιτέρω αξιολόγηση με εκτεταμένα πειράματα προσομοίωσης.

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Context Awareness in Predictive Maintenance

Cited by 13 publications

References 24 publications

Assessing the quality of mobile graphical user interfaces using multi-objective optimization

Assessing the quality of mobile graphical user interfaces using multi-objective optimization

An Intelligent Context-aware System for Logistics Asset Supervision Service

Proactive computing in industrial maintenance decision making

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