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 “devices”, 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 “cognitive devices” 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

A high level e-maintenance architecture to support on-site teams

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent modules to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. Further this paradigm shift towards “embedded intelligence”, supported by cross platform technologies, induces relevant organizational and functional changes on local maintenance teams. On the one hand, the possibility of outsourcing maintenance activities, with the warranty of a timely response, through the use of pervasive networking technologies and, on the other hand, the optimization of local maintenance staff are some examples of how IT is changing the scenario in maintenance. The concept of e-maintenance is, in this context, emerging as a new discipline with defined socio-economic challenges. This paper proposes a high level maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action.manufacturing systems, platform technologies, maintenance

Intelligent decision support for maintenance: an overview and future trends

The changing nature of manufacturing, in recent years, is evident in industry’s 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 ‘Human in the loop’ interactions

A review of e-maintenance capabilities and challenges

Within the era of e-manufacturing and e-business, e-maintenance provides the opportunity for a new maintenance generation. E-maintenance integrates existing telemaintenance principles, with web-services and modern e-collaboration principles. Collaboration allows not only to share and exchange information but also knowledge and (e)-intelligence. This paper outlines the basic capabilities provided by e-maintenance to companies as well as describes emerging challenges to benefit from these new operational improvement opportunitie

Exploring the Scope of Prognosis Agent Technology in Digital Manufacturing

It is an established fact that the last decade is evident for the advancement in manufacturing sector by the use of various digital manufacturing (DM) techniques. Agent technology has contributed far in the DM by simplifying and adding synergy to the various functionaries in form of static and mobile agents. The agents contribute in the paradigms of designing, diagnosis, production, marketing etc. In the international business market, the agent technology has increased the competence by providing fast, error free, customized services. The paper first reviews the work done in the field of applications of agent technology in digital manufacturing including the role of agent technology in prognosis and then the research object is to develop a framework for the prognosis of digital data feeded to the manufacturing facilities of DM system. The paper focus on the introduction and brief description of the manufacturing prognosis agent in context to Digital manufacturing. Key words: manufacturing prognosis agent, digital manufacturing, prognosis, agent technology, digital dat

A high level e-maintenance architecture to support on-site teams

Emergent architectures and paradigms targeting reconfigurable manufacturing systems increasingly rely on intelligent modules to maximize the robustness and responsiveness of modern installations. Although intelligent behaviour significantly minimizes the occurrence of faults and breakdowns it does not exclude them nor can prevent equipment’s normal wear. Adequate maintenance is fundamental to extend equipments’ life cycle. It is of major importance the ability of each intelligent device to take an active role in maintenance support. Further this paradigm shift towards “embedded intelligence”, supported by cross platform technologies, induces relevant organizational and functional changes on local maintenance teams. On the one hand, the possibility of outsourcing maintenance activities, with the warranty of a timely response, through the use of pervasive networking technologies and, on the other hand, the optimization of local maintenance staff are some examples of how IT is changing the scenario in maintenance. The concept of e-maintenance is, in this context, emerging as a new discipline with defined socio-economic challenges. This paper proposes a high level maintenance architecture supporting maintenance teams’ management and offering contextualized operational support. All the functionalities hosted by the architecture are offered to the remaining system as network services. Any intelligent module, implementing the services’ interface, can report diagnostic, prognostic and maintenance recommendations that enable the core of the platform to decide on the best course of action

Mobile Maintenance Management

The paper gives a short overview of the enabling tools and technology available to the maintenance engineer in manufacturing industry, in relation to the emergence of e-maintenance practices and the introduction of mobile computing devices. An analysis of the main characteristics of the e- maintenance concepts and the associated challenges is provided, highlighting the lack of use of condition-based maintenance strategies. The potential of using ubiquitous computing in industrial maintenance practice is then examined, followed by an original vision for the adoption of mobile maintenance management solutions, which can facilitate the implementation of condition-based- maintenance. This vision is supported today by the European Integrated Project DYNAMITE 017498 (Dynamic Decisions in Maintenance)

Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System

During the recent years, development of information technology caused to develop a new industrial system which is called e-Manufacturing system. Thanks to the webenabled manufacturing technologies, the lead times are being minimized to their extreme level, and the minimum amount of inventory is kept, though the products are being made-to order. Under these circumstances, achieving near-zero downtime of the plant floor’s equipments is a crucial factor which mitigates the risk of facing unmet demands. Many researches carried out to schedule maintenance actions in short term, but none of them have utilized all of planning horizon to spread maintenance actions along available time. In this research a method of enhanced maintenance scheduling of multi-component e-Manufacturing systems has been developed. In this multi-component system, importance of all machines is considered and the benefit of the entire system in term of produced parts is taken into account (versus benefits of single machine). In proposed system, the predicted machines degradation information, online information about work in process (WIP) inventory (at inventory buffer of each work station) as well as production line’s dynamism are taken into account. All of makespans of planning horizon have been utilized to improve scheduling efficiency and operational productivity by maximizing the system throughputs. A state-of-the-art method which is called simulation optimization has been utilized to implement the proposed scheduling method. The production system is simulated by ProModel software. It plays the role of objective function of the maintenance scheduling optimization problem. Using a production related heuristic method which is called system value method, the value of each workstation is determined. These values are used to define the objective function’s parameters. Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. This process is carried out for nine generated scenarios. At the end, the results are benchmarked by two commonly used maintenance scheduling methods to magnify the importance of proposed intelligent maintenance scheduling in the multi-component e-Manufacturing systems. The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. Furthermore, it indicates that when the mean time to repairs are longer, this method is more efficient. The results in the simulated testbed indicate that the developed scheduling method using simulation optimization functions properly and can be applied in other cases