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

Maintenance Knowledge Management with Fusion of CMMS and CM

Abstract- Maintenance can be considered as an information, knowledge processing and management system. The management of knowledge resources in maintenance is a relatively new issue compared to Computerized Maintenance Management Systems (CMMS) and Condition Monitoring (CM) approaches and systems. Information Communication technologies (ICT) systems including CMMS, CM and enterprise administrative systems amongst others are effective in supplying data and in some cases information. In order to be effective the availability of high-quality knowledge, skills and expertise are needed for effective analysis and decision-making based on the supplied information and data. Information and data are not by themselves enough, knowledge, experience and skills are the key factors when maximizing the usability of the collected data and information. Thus, effective knowledge management (KM) is growing in importance, especially in advanced processes and management of advanced and expensive assets. Therefore efforts to successfully integrate maintenance knowledge management processes with accurate information from CMMSs and CM systems will be vital due to the increasing complexities of the overall systems. Low maintenance effectiveness costs money and resources since normal and stable production cannot be upheld and maintained over time, lowered maintenance effectiveness can have a substantial impact on the organizations ability to obtain stable flows of income and control costs in the overall process. Ineffective maintenance is often dependent on faulty decisions, mistakes due to lack of experience and lack of functional systems for effective information exchange [10]. Thus, access to knowledge, experience and skills resources in combination with functional collaboration structures can be regarded as vital components for a high maintenance effectiveness solution. Maintenance effectiveness depends in part on the quality, timeliness, accuracy and completeness of information related to machine degradation state, based on which decisions are made. Maintenance effectiveness, to a large extent, also depends on the quality of the knowledge of the managers and maintenance operators and the effectiveness of the internal & external collaborative environments. With emergence of intelligent sensors to measure and monitor the health state of the component and gradual implementation of ICT) in organizations, the conceptualization and implementation of E-Maintenance is turning into a reality. Unfortunately, even though knowledge management aspects are important in maintenance, the integration of KM aspects has still to find its place in E-Maintenance and in the overall information flows of larger-scale maintenance solutions. Nowadays, two main systems are implemented in most maintenance departments: Firstly, Computer Maintenance Management Systems (CMMS), the core of traditional maintenance record-keeping practices that often facilitate the usage of textual descriptions of faults and actions performed on an asset. Secondly, condition monitoring systems (CMS). Recently developed (CMS) are capable of directly monitoring asset components parameters; however, attempts to link observed CMMS events to CM sensor measurements have been limited in their approach and scalability. In this article we present one approach for addressing this challenge. We argue that understanding the requirements and constraints in conjunction - from maintenance, knowledge management and ICT perspectives - is necessary. We identify the issues that need be addressed for achieving successful integration of such disparate data types and processes (also integrating knowledge management into the “data types” and processes)

New Shop Floor Control Approaches for Virtual Enterprises

The virtual enterprise paradigm seems a fit response to face market instability and the volatile nature of business opportunities increasing enterprise’s interest in similar forms of networked organisations. The dynamic environment of a virtual enterprise requires that partners in the consortium own reconfigurable shop floors. This paper presents new approaches to shop floor control that meet the requirements of the new industrial paradigms and argues on work re-organization at shop floor level.virtual enterprise; networked organisations

A methodology for integrating asset administration shells and multi-agent systems

Industry 4.0 (I4.0) is promoting the digitization of industrial environments towards intelligent and distributed industrial automation systems based on Cyber-physical Systems (CPS). Currently, this digitization process is being leveraged by the Asset Administration Shell (AAS), which digitally describes an asset in a standardized and semantically unambiguous form throughout its lifecycle. However, more robust solutions based on autonomous AASs endowed with collaborative and intelligent capabilities, also called proactive AASs, are still in the early stages. In this context, Multi-agent Systems (MAS) are a key enabler to provide the required autonomy, intelligence and collaborative capabilities for the AASs. With this in mind, this paper presents a methodology positioned with respect to the Reference Architecture Model Industrie 4.0 (RAMI4.0) layers, which provides guidelines for integrating AASs and MAS, aiming to support the development of proactive AASs. The applicability of the proposed methodology was tested through the integration of AASs and MAS for a smallscale CPS demonstrator.The authors are grateful to the Foundation for Science and Technology (FCT), Portugal, for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021). The author Lucas Sakurada thanks the FCT for the PhD Grant 2020.09234.BD.info:eu-repo/semantics/publishedVersio

Meter Scoping Study

This report presents a summary of metering technology and cost information from past studies in an attempt to identify key barriers to more widespread implementation

EXTENDED ENTERPRISE AND INFORMATION SYSTEMS GOVERNANCE IN AN INTER-ORGANIZATIONAL CONTEXT

Flexibility, openness, and cooperation are fundamental tendencies that positively mark the ensemble of private and public sector organizations. For a sustainable development in a more and more complex globalized and competitive business environment, the ee-business, extended enterprise, inter-enterprise cooperative information systems, workflow, corporate governance, IS governance

Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges

Cyber-Physical Systems (CPS) is an emergent approach that focuses on the integration of computational applications with physical devices, being designed as a network of interacting cyber and physical elements. CPS control and monitor real-world physical infrastructures and thus is starting having a high impact in industrial automation. As such design, implementation and operation of CPS and management of the resulting automation infrastructure is of key importance for the industry. In this work, an overview of key aspects of industrial CPS, their technologies and emerging directions, as well as challenges for their implementation is presented. Based on the hands-on experiences gathered from four European innovation projects over the last decade (i.e. SOCRADES, IMC-AESOP, GRACE and ARUM), a key challenges have been identified and a prioritization and timeline are pointed out with the aim to increase Technology Readiness Levels and lead to their usage in industrial automation environments.The authors would like to thank for their support the European Commission, and the partners of the EU FP6 SOCRADES (www.socrades.net), EU FP7 GRACE (www.grace-project.org), EU FP7 IMC-AESOP (www.imc-aesop.eu) and EU FP7 ARUM (www.arum-project.eu) projects, for their fruitful support and discussions.info:eu-repo/semantics/publishedVersio

HOMEBOTS: Intelligent Decentralized Services for Energy Management

The deregulation of the European energy market, combined with emerging advanced capabilities of information technology, provides strategic opportunities for new knowledge-oriented services on the power grid. HOMEBOTS is the namewe have coined for one of these innovative services: decentralized power load management at the customer side, automatically carried out by a `society' of interactive household, industrial and utility equipment. They act as independent intelligent agents that communicate and negotiate in a computational market economy. The knowledge and competence aspects of this application are discussed, using an improved \ud version of task analysis according to the COMMONKADS knowledge methodology. Illustrated by simulation results, we indicate how customer knowledge can be mobilized to achieve joint goals of cost and energy savings. General implications for knowledge creation and its management are discussed

Multi-agent systems to implement industry 4.0 components

The fast-changing market conditions, the increased global competition and the rapid technological developments demand flexible, adaptable and reconfigurable manufacturing systems based on Cyber-Physical Systems (CPS). Aligned with CPS, the adoption of production system architectures is suitable to reduce complexity and achieve interoperability in the industrial applications. In this context, the Reference Architecture Model for Industry 4.0 (RAMI4.0) provides the guidelines to develop Industry 4.0 (I4.0) compliant solutions, considering the existing industrial standards. The so-called I4.0 components implement this model in practice, combining the physical asset with its digital representation, named Asset Administration Shell (AAS). This paper explores the use of Multi-Agent Systems (MAS) to implement the AAS functionalities, taking advantage of their inherits characteristics, e.g., autonomy, intelligence, decentralization and reconfigurability. In this context, the mapping between AAS functionalities and MAS characteristics is provided, as well as the challenges for this implementation. The applicability is illustrated by digitalizing an inspection cell comprising an UR3 robot and several console products by using MAS technology.info:eu-repo/semantics/publishedVersio