Digitalisation of maintenance

Jantunen, Erkki; Campos, Jaime; Sharma, Pankaj; Baglee, David

doi:10.1109/icsrs.2017.8272846

Cited by 14 publications

(14 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The reliability of a complete system of sensors and cloud resources according to the importance of assets is high risk. Another problem is caused by the high heterogeneity of devices, which can cause a conflict with interoperability [41]. Although both Bluetooth and WLAN (wireless local area networks) are developing low-cost structures, so far, there are only very limited mechanisms to solve problems such as anti-interference, information security, and response times [42].…”

Section: Sme Challengesmentioning

confidence: 99%

Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

Dolatabadi

Budinská

2021

Machines

View full text Add to dashboard Cite

Today, small- and medium-sized enterprises (SMEs) play an important role in the economy of societies. Although environmental factors, such as COVID-19, as well as non-environmental factors, such as equipment failure, make these industries more vulnerable, they can be minimized by better understanding the concerns and threats these industries face. Only a few SMEs have the capacity to implement the innovative manufacturing technologies of Industry 4.0. The system must be highly adaptable to any equipment, have low costs, avoid the need of doing complex integrations and setups, and have future reliability due to the rapid growth of technology. The goal of this study was to provide an overview of past articles (2010–2020), highlighting the major expectations, requirements, and challenges for SMEs regarding the implementation of predictive maintenance (PdM). The proposed solutions to meet these expectations, requirements, and challenges are discussed. In general, in this study, we attempted to overcome the challenges and limitations of using smart manufacturing—PdM, in particular—in small- and medium-sized enterprises by summarizing the solutions offered in different industries and with various conditions. Moreover, this literature review enables managers and stakeholders of organizations to find solutions from previous studies for a specific category, with consideration for their expectations and needs. This can be significantly helpful for small- and medium-sized organizations to save time due to time-consuming maintenance processes.

show abstract

Section: Sme Challengesmentioning

confidence: 99%

Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

Dolatabadi

Budinská

2021

Machines

View full text Add to dashboard Cite

show abstract

“…The data generation begins in the data acquisition process. This step consists of using a transducer to convert and physical quantity into an electrical signal, after some filtering and amplification, the signal is digitalized using and Analog-to-Digital Converter (ADC) [8].…”

Section: Digitalization Of Assets Operation and Maintenancementioning

confidence: 99%

“…The predictive maintenance also can take advantage of these large amount of data to create indicators, and keep the Overall Equipment Efficiency (OEE) as highly as possible and reduce downtime due to unplanned shutdowns [8].…”

Section: Digitalization Of Assets Operation and Maintenancementioning

confidence: 99%

Proposal of a Augmented Operator for a Hydroelectric Power Plant

Silva

Barbosa

Santos

et al. 2019

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

There is a trend in the industry in the digitalization of assets for generating large amounts of information and greater control and supervision over the production. With this digitalization, the possibility arises to include new technologies that can facilitate the life of the maintenance team and the operator, such as the concept of augmented operator. In this concept, the operator using mobile devices can access information in real time of the desired equipment, saving time in the acquisition of this information and allowing a greater time to analyze this data. Thus, this work aims to propose an augmented operator system for an hydroelectric power generation industry, as an example there is the possibility of visualizing information of vibration, temperature and rotation of recirculating motor pumps of the cooling system from generation units. Preliminary results indicate a wide possibility of using this concept. In addition to the actual monitoring of the asset in real time, there is the possibility of obtaining the list of spare parts and materials that help in the communication to the purchasing sector and quick replacement of failed components.

show abstract

“…There have been many attempts to resolve these issues with the help of different kinds of ICTs over time, such as artificial intelligence, distributed intelligence, etc. [6][7][8]. Currently, with the emerging technologies such as the IoT, big data and analytics, open source solutions as well as open platforms, the entrance barrier to advanced maintenance solutions has been lowered considerably.…”

Section: Introductionmentioning

confidence: 99%

An Open Source Framework Approach to Support Condition Monitoring and Maintenance

et al. 2020

Self Cite

View full text Add to dashboard Cite

This paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.

show abstract

Digitalisation of maintenance

Cited by 14 publications

References 12 publications

Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

Systematic Literature Review Predictive Maintenance Solutions for SMEs from the Last Decade

Proposal of a Augmented Operator for a Hydroelectric Power Plant

An Open Source Framework Approach to Support Condition Monitoring and Maintenance

Contact Info

Product

Resources

About