Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Sensor actor network modeling utilizing the holonic architectural framework

This paper discusses the results of utilizing advanced EKM modeling techniques to manage Sensor-Actor networks (SANETs) based upon the Holonic Architectural Framework. EKMs allow a quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize from a given input space to administer SANET routing and clustering functions with a control parameter space. Results demonstrate that in comparison to linear approximation techniques, indirect mapping with EKMs provide fluid control and feedback mechanisms by operating in a continuous sensory control space-thus enabling interactive detection and optimization of events in real-time environments

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Deployment of an agent-based SANET architecture for healthcare services

This paper describes the adaptation of a computational technique utilizing Extended Kohonen Maps (EKMs) and Rao-Blackwell-Kolmogorov (R-B) Filtering mechanisms for the administration of Sensor-Actuator networks (SANETs). Inspired by the BDI (Belief-Desire-Intention) Agent model from Rao and Georgeff, EKMs perform the quantitative analysis of an algorithmic artificial neural network process by using an indirect-mapping EKM to self-organize, while the Rao-Blackwell filtering mechanism reduces the external noise and interference in the problem set introduced through the self-organization process. Initial results demonstrate that a combinatorial approach to optimization with EKMs and Rao-Blackwell filtering provides an improvement in event trajectory approximation in comparison to standalone cooperative EKM processes to allow responsive event detection and optimization in patient healthcare

An Improvement to Trust Based Cross-Layer Security Protocol against Sybil Attacks (DAS)

The performance of distributed networks depends on collaboration among distributed entities. To enhance security in distributed networks, such as ad hoc networks, it is important to evaluate the trustworthiness of participating entities since trust is the major driving force for collaboration. The trust based security protocol based on a cross-layer approach attains confidentiality and authentication of packets in both routing and link layers of MANETs but it doesn’t address few attacks like Bad Mouthing Attack, On-off Attack, and Conflicting Behavior Attack, Sybil Attack and Newcomer Attack. In this paper we present DAS, a protocol for reducing of the corruptive/malicious influences of Sybil attacks. Malicious users in general may create multiple identities with few trust relationships. Hence there is a disproportionately small gap in the graph between the Sybil nodes and the honest nodes. DAS exploits this property so as to bind the number of identities a malicious user can create. We simulate the effectiveness of DAS both analytically and experimentally. Keywords: MANETs, Security Protocol, DAS, Malicious nodes, Cross Layer, Authenticatio

Is Ambient Intelligence a truly Human-Centric Paradigm in Industry? Current Research and Application Scenario

The use of pervasive networked devices is nowadays a reality in the service sector. It impacts almost all aspects of our daily lives, although most times we are not aware of its influence. This is a fundamental characteristic of the concept of Ambient Intelligence (AmI). Ambient Intelligence aims to change the form of human-computer interaction, focusing on the user needs so they can interact in a more seamless way, with emphasis on greater user-friendliness. The idea of recognizing people and their context situation is not new and has been successfully applied with limitations, for instance, in the health and military sectors. However its appearance in the manufacturing industry has been elusive. Could the concept of AmI turn the current shop floor into a truly human centric environment enabling comprehensive reaction to human presence and action? In this article an AmI scenario is presented and detailed with applications in human’s integrity and safety.Ambient Intelligence, networks, human-computer interaction

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

sWSN3: A simulation tool for reliability calculation in WSN

Knowledge about the reliability of a wireless sensor network is important in industry. Indeed, in holonic manufacturing, it is convenient to ensure that decisions are made with reliable data. However, experimental evaluation in a real environment is a task that consumes time and financial resources, it also depends on several factors such as the technical characteristics of the transceiver and the location of the nodes. Thus, the use of simulation and calculation software in Industry 4.0 can potentially reduce costs and implementation time significantly, nonetheless some simulators deal with power consumption and network reliability with theoretical models that have limitations for commercial devices. This paper presents the sWSN3 tool that, through an intuitive graphical interface allows placing sensor nodes on the virtual environment of a plant layout and calculates the reliability of a wireless sensor network using parameters such as signal to noise ratio, received packet rate, and battery life time. Results show that sWSN3 can accurately estimate the reliability of a virtual WSN