Condition Monitoring of Rollers in Belt Conveyor Systems

Al-Kahwati, Kammal; Saari, Esi; Birk, Wolfgang; Atta, Khalid Tourkey

doi:10.1109/systol52990.2021.9595269

Cited by 5 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In process industries, the roll-out of component-level strategies is still in its infancy and the organizational challenges associated with it need to be first overcome. That being the case, Al-Kahwati et. al.…”

Section: Introductionmentioning

confidence: 92%

“…Data tags from the asset site are needed to form the model for calculating the degradation of remaining useful life. The minimum requirement of data tags for the condition monitoring of the solution are the feed rate, belt speed and the belt tension as described in (Al-Kahwati et al, 2021). The data points are provided to the online cloud solution through a data lake.…”

Section: Component Condition Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems

Al-Kahwati¹,

Birk

Nilsfors³

et al. 2022

PHME_CONF

Self Cite

View full text Add to dashboard Cite

Availability of belt conveyor systems is essential in production and logistic lines to safeguard production and delivery targets to customers. In this paper, experiences from commissioning, validation, and operation of an interactive predictive maintenance solution are reported. The solution and its development is formerly presented in Al-Kahwati et.al. (Al-Kahwati, Saari, Birk, & Atta, 2021), where the principles to derive a digital twin of a typical belt conveyor system comprising component-level degradation models,estimation schemes for the remaining useful life and the degradation rate, and vision-based hazardous object detection. Furthermore, the validation approach of modifying the belt conveyor and thus exploiting the idler misalignment load (IML) for the degradation predictions for individual components (including long-lasting ones) together with the actionable insights for the decision support is presented and assessed. Moreover, the approach to testing and validation of the object detection and its performance is assessed and presented in the same manner. An overall system assessment is then given and concludes the paper together with lessons learned. As pilot site for the study a belt conveyor system at LKAB Narvik in northern Norway is used.

show abstract

Section: Introductionmentioning

confidence: 92%

Section: Component Condition Monitoringmentioning

confidence: 99%

Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems

Al-Kahwati¹,

Birk

Nilsfors³

et al. 2022

PHME_CONF

Self Cite

View full text Add to dashboard Cite

show abstract

Hazardous Object Detection in Bulk Material Transport Using Video Stream Processing

Meulenberg,

Moloukbashi Al-Kahwati,

Öhman

et al. 2024

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

A conceptual framework proposal for the implementation of Prognostic and Health Management in production systems

Abbate,

Franciosi,

Voisin

et al. 2024

IET Collab Intel Manufact

View full text Add to dashboard Cite

Prognostic and Health Management (PHM) is an emerging maintenance concept that is highly regarded by the scientific community and practitioners, as its adoption can bring economic, technical and environmental benefits to a company. PHM fully reflects the smart maintenance paradigm encompassing data collection, data manipulation, state detection, health assessment, prognostic assessment and advisory generation. Despite the undeniable benefits, there is still a large gap between the scientific and the real world. Several authors have investigated on the barriers to PHM implementation for companies, highlighting among them the lack of systematic approaches to its design and implementation. As a first contribution to this topic, the authors conducted a systematic literature review (SLR) to investigate the use of Decision Support Systems (DSSs) to support the PHM implementation. The SLR highlighted that few DSS had been developed and were limited to critical unit identification, maintenance strategy selection and data acquisition phase of PHM. Therefore, a conceptual framework for PHM implementation was provided as a second contribution. This framework summarises the decisions that should be addressed by a practitioner wishing to implement PHM services; moreover, it could lay the foundations for the development/improvement of the missing/existing DSSs for PHM implementation.

show abstract

Condition Monitoring of Rollers in Belt Conveyor Systems

Cited by 5 publications

References 1 publication

Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems

Experiences of a Digital Twin Based Predictive Maintenance Solution for Belt Conveyor Systems

Hazardous Object Detection in Bulk Material Transport Using Video Stream Processing

A conceptual framework proposal for the implementation of Prognostic and Health Management in production systems

Contact Info

Product

Resources

About