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Remote maintenance support with the aid of cyber-physical systems and cloud technology
This article discusses how a business model based on traditional maintenance can evolve to generate servitization strategies, with the help of remote maintenance support. The application of cyber-physical systems and cloud technologies play a key role for such maintenance purposes. In fact, the utilization of large quantities of data collected on machines and their processing by means of advanced techniques such as machine learning enable novel techniques for condition-based maintenance. New sensor solutions that could be used in maintenance and interaction with cyber-physical systems are also presented. Here, data models are an important part of these techniques because of the huge amounts of data that are produced and should be processed. These data models have been used in a real case, supported by the Machinery Information Management Open System Alliance Open System Architecture for Condition-Based Maintenance standard architecture, for streamlining the modeling of collected data. In this context, an industrial use case is described, to enlighten the application of the presented concepts in a working pilot. Finally, current and future directions for application of cyber-physical systems and cloud technologies to maintenance are discussed
Security aspects in cloud based condition monitoring of machine tools
In the modern competitive environments companies must have rapid production systems that are able to deliver parts that satisfy highest quality standards. Companies have also an increased need for advanced machines equipped with the latest technologies in maintenance to avoid any reduction or interruption of production. Eminent therefore is the need to monitor the health status of the manufacturing equipment in real time and thus try to develop diagnostic technologies for machine tools. This paper lays the foundation for the creation of a safe remote monitoring system for machine tools using a Cloud environment for communication between the customer and the maintenance service company. Cloud technology provides a convenient means for accessing maintenance data anywhere in the world accessible through simple devices such as PC, tablets or smartphones. In this context the safety aspects of a Cloud system for remote monitoring of machine tools becomes crucial and is, thus the focus of this pape
Continuous maintenance and the future â Foundations and technological challenges
High value and long life products require continuous maintenance throughout their life cycle to achieve required performance with optimum through-life cost. This paper presents foundations and technologies required to offer the maintenance service. Component and system level degradation science, assessment and modelling along with life cycle âbig dataâ analytics are the two most important knowledge and skill base required for the continuous maintenance. Advanced computing and visualisation technologies will improve efficiency of the maintenance and reduce through-life cost of the product. Future of continuous maintenance within the Industry 4.0 context also identifies the role of IoT, standards and cyber security
Securing the Participation of Safety-Critical SCADA Systems in the Industrial Internet of Things
In the past, industrial control systems were âair gappedâ and
isolated from more conventional networks. They used
specialist protocols, such as Modbus, that are very different
from TCP/IP. Individual devices used proprietary operating
systems rather than the more familiar Linux or Windows.
However, things are changing. There is a move for greater
connectivity â for instance so that higher-level enterprise
management systems can exchange information that helps
optimise production processes. At the same time, industrial
systems have been influenced by concepts from the Internet
of Things; where the information derived from sensors and
actuators in domestic and industrial components can be
addressed through network interfaces. This paper identifies a
range of cyber security and safety concerns that arise from
these developments. The closing sections introduce potential
solutions and identify areas for future research
Blockchain Technology Helps Maintenance to Stop Climate Change
The development and interest in Industry 4.0
together with rapid development of Cyber Physical Systems has
created magnificent opportunities to develop maintenance to a
totally new level. The Maintenance 4.0 vision considers massive
exploitation of information regarding factories and machines to
improve maintenance efficiency and efficacy, for example by
facilitating logistics of spare parts, but on the other hand this
creates other logistics issues on the data itself, which only
exacerbate data management issues that emerge when distributed
maintenance platforms scale up. In fact, factories can be
delocalized with respect to the data centers, where data has to be
transferred to be processed. Moreover, any transaction needs
communication, be it related to purchase of spare parts, sales
contract, and decisions making in general, and it has to be verified
by remote parties. Keeping in mind the current average level of
Overall Equipment Efficiency (50%) i.e. there is a hidden factory
behind every factory, the potential is huge. It is expected that most
of this potential can be realised based on the use of the above
named technologies, and relying on a new approach called
blockchain technology, the latter aimed at facilitating data and
transactions management. Blockchain supports logistics by a
distributed ledger to record transactions in a verifiable and
permanent way, thus removing the need for multiple remote
parties to verify and store every transaction made, in agreement
with the first ârâ of maintenance (reduce, repair, reuse, recycle).
Keeping in mind the total industrial influence on the climate
change, we can expect that with the aid of the new advancements
the climate change can be if not totally stopped at least reduced,
and contribute to the green economy that Europe aims for. The
paper introduces the novel technologies that can support
sustainability of manufacturing and industry at large, and
proposes an architecture to bind together said technologies to
realise the vision of Maintenance 4.0.info:eu-repo/semantics/publishedVersio
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Intelligent decision support for maintenance: an overview and future trends
The changing nature of manufacturing, in recent years, is evident in industryâs willingness to adopt network-connected intelligent machines in their factory development plans. A number of joint corporate/government initiatives also describe and encourage the adoption of Artificial Intelligence (AI) in the operation and management of production lines. Machine learning will have a significant role to play in the delivery of automated and intelligently supported maintenance decision-making systems. While e-maintenance practice provides aframework for internet-connected operation of maintenance practice the advent of IoT has changed the scale of internetworking and new architectures and tools are needed. While advances in sensors and sensor fusion techniques have been significant in recent years, the possibilities brought by IoT create new challenges in the scale of data and its analysis. The development of audit trail style practice for the collection of data and the provision of acomprehensive framework for its processing, analysis and use should be avaluable contribution in addressing the new data analytics challenges for maintenance created by internet connected devices. This paper proposes that further research should be conducted into audit trail collection of maintenance data, allowing future systems to enable âHuman in the loopâ interactions
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent âdevicesâ, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew âcognitive devicesâ are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
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