Concept for Context-Aware Manufacturing Dashboard Applications

Nadoveza, Dražen; Kiritsis, Dimitris

doi:10.3182/20130619-3-ru-3018.00103

Cited by 9 publications

(7 citation statements)

References 7 publications

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“…The motivation for this work (Nadoveza and Kiritsis 2013) is the fact that in certain situations not all information provided by an information system is important and relevant to the end user. Modern manufacturing information systems, such as production and logistic dashboards, provide huge amounts of information and, in those large volumes, very often the user cannot find appropriate and important information at the right time.…”

Section: Context Aware Technologiesmentioning

confidence: 99%

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Semantic technologies for engineering asset life cycle management

Kiritsis

2013

International Journal of Production Research

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The use of semantic technologies and ontologies is becoming more and more popular in engineering applications and particularly in product modelling. Still, the use is limited in academia and applications are of a small scale. In this paper we present the research work done by the closed-loop life cycle management (CL2M) team of the Laboratory for Computer-Aided Design and Production (LICP) at the Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland, on the use of ontology-based technologies for the life cycle management of products and engineering assets. This research has been performed through a number of PhD works partially financed by the European Framework Program for research. It aims at providing both a wider understanding of the benefits of applying such technologies in the complex environment of asset life cycle management (ALM) and at providing a platform for implementing ontology models in industrial environments.

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Section: Context Aware Technologiesmentioning

confidence: 99%

“…• Asset optimisation (Koukias et al 2012;Nadoveza and Kiritsis 2013) with developments in the framework of the FP7 project PLANTCockpit (www.plantcockpit.eu).…”

mentioning

confidence: 99%

Semantic technologies for engineering asset life cycle management

Kiritsis

2013

International Journal of Production Research

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“…The actual value of data can be enhanced by providing the right information and services to the right persons at the right place and time in a certain business process instance (Lee and Martinez Lastra, 2013). Effective adaptation of services is sought via context-adaptive computing (Perera et al , 2014; Nadoveza and Kiritsis, 2013). When contextualised with the support of informatics tools and organisational factors, this process can positively affect the adoption of knowledge management solutions by personnel (Lin, 2014).…”

Section: Current State and Research Driversmentioning

confidence: 99%

Management of linked knowledge in industrial maintenance

Pistofidis

Emmanouilidis

Papadopoulos³

et al. 2016

IMDS

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Purpose Field expertise in industry is often poorly recorded and unexploited. The purpose of this paper is to introduce a methodology and tool that incorporates a knowledge validation loop to leverage upon human-contributed field observations in industrial maintenance management. Starting from a failure mode, effects and criticality analysis (FMECA) model, it defines a collaborative process that links FMECA knowledge with field maintenance practice. Design/methodology/approach A metadata management system is designed to encourage staff involvement in enriching knowledge with field observations. The process supports easy feedback and collaborative annotation and is pilot tested via an industrial case study. Findings Streamlining FMECA validation is welcomed by maintenance staff, empowering them to exert more control over the management, usage and versioning of reference knowledge. Research limitations/implications The methodology for metadata management in industrial maintenance enables staff participation in a collaborative knowledge enrichment process. Metadata management is a pre-cursor and therefore an important step to drive future analytics. Practical implications Industry personnel are more inclined to contribute to organisational knowledge if the process is based on reference knowledge and requires minimal interaction. Social implications Facilitating individual contribution to collective knowledge strengthens the sense that each staff member can have organisational impact. Originality/value The paper introduces a methodology and tool to stimulate human-contributed knowledge in industrial maintenance, strengthening collaborative organisation knowledge flows.

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“…429 Context awareness is the ability of the system to sense, interpret, adapt, dis-431 cover resources, and associate digital data with the system's environment to 432 better understand the situation the system is in and how data should be best 433 used [80,81].…”

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confidence: 99%

An Evaluation Model of Autonomy Levels in Manufacturing and its Features

Monetti²,

Torayev³

et al. 2022

Preprint

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Modern manufacturing has to cope with dynamic and changing circumstances. Market fluctuations, the effects caused by unpredictable material shortages, highly variable product demand, and worker availability all require system robustness, flexibility, and resilience. To adapt to these new requirements, manufacturers should consider investigating, investing in, and implementing system autonomy. Autonomy is being adopted in multiple industrial contexts, but divergences arise when formalising the concept of autonomous systems. To develop an implementation of autonomous manufacturing systems it is essential to specify what autonomy means, how autonomous manufacturing systems are different from other autonomous systems, and how autonomous manufacturing systems are identified and achieved through the main features and enabling technologies. With a comprehensive literature review, this paper provides a definition of autonomy in the manufacturing context, infers the features of autonomy from different engineering domains, and presents a five-level model of autonomy -- associated with maturity levels for the features -- to ensure the complete identification and evaluation of autonomous manufacturing systems. The paper also presents the evaluation of a real autonomous system that serves as a use-case and a validation of the model.

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Concept for Context-Aware Manufacturing Dashboard Applications

Cited by 9 publications

References 7 publications

Semantic technologies for engineering asset life cycle management

Semantic technologies for engineering asset life cycle management

Management of linked knowledge in industrial maintenance

An Evaluation Model of Autonomy Levels in Manufacturing and its Features

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