Describing Structure and Complex Interactions in Multi-Agent-Based Industrial Cyber-Physical Systems

The description of structure and complex interactions in Multi-agent-based Industrial Cyber-physical (MAS-ICPS) systems has been elusively addressed in the literature. Existing works, grounded on model-based engineering, have been successful at characterizing and solving system integration problems. However, they fail to describe accurately the collective and dynamic execution behaviour of large and complex industrial systems, particularly in more discrete production domains, such as: automotive, home appliances, aerospace, food and beverages, etc. In these domains, the execution flow diverts dynamically due to production disturbances, custom orders, fluctuations in demand in mixed model production, faults, quality-control and product rework, etc. These dynamic conditions require re-allocation and reconfiguration of production resources, redirection of production flows, re-scheduling of orders, etc. A meta-model for describing the structure and complex interactions in MAS-ICPS is defined in this paper. This contribution goes beyond the State-Of-The-Art (SOTA) as the proposed meta-model describes structure, as many other literature contributions, but also describes the execution behaviour of arbitrarily complex interactions. The previous is achieved with the introduction of general execution flow control operators in the meta-model. These operators cover, among other aspects, delegation of the execution flow and dynamic decision making. Additionally, the contribution also goes beyond the SOTA by including validation mechanisms for the models generated by the meta-model. Finally, the contribution adds to the current literature by providing a meta-model focusing on production execution and not just on describing the structural connectivity aspects of ICPSs.publishersversionpublishe

Safe-Guarded Agent Design Pattern for Mechatronic Systems

To support the application of real-time Multi-Agent Control Systems (MACS) for mechatronic systems, a combination between the MACS design approach and OROCOS framework has been implemented: the OROCOS-based Implementation Framework for MACS (OROMACS). This paper presents our research results to make the OROMACS framework be easily applicable to develop realtime safe-guarded controller-agents and to maximize the reusability of safe-guarded MACS designs for various types of mechatronic systems. The approach that we advocate is a combination between OROMACS framework and pattern-based design method. Eleven control system design patterns are formed in which the Safe-Guarded Agent, one of the core design patterns, aims at providing a generic and flexible safe-guarded control solution for mechatronic systems. The design patterns are well organized into two reusable generalized safe-guarded control solutions, one for simple mechatronic systems and one for complex mechatronic systems

Safe-guarded multi-agent control for mechatronic systems: implementation framework and design patterns

This thesis addresses two issues: (i) developing an implementation framework for Multi-Agent Control Systems (MACS); and (ii) developing a pattern-based safe-guarded MACS design method.\ud \ud The Multi-Agent Controller Implementation Framework (MACIF), developed by Van Breemen (2001), is selected as the starting point because of its capability to produce MACS for solving complex control problems with two useful features:\ud • MACS is hierarchically structured in terms of a coordinated group of elementary and/or composite controller-agents;\ud • MACS has an open architecture such that controller-agents can be added, modified or removed without redesigning and/or reprogramming the remaining part of the MACS

Assessing self-organization and emergence in Evolvable Assembly Systems (EAS)

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThere is a growing interest from industry in the applications of distributed IT. Currently, most modern plants use distributed controllers either to control production processes, monitor them or both. Despite the efforts on the last years to improve the implementation of the new manufacturing paradigms, the industry is still mainly using traditional controllers. Now, more than ever, with an economic crisis the costumers are searching for cheap and customized products, which represents a great opportunity for the new paradigms to claim their space in the market. Most of the research on distributed manufacturing is regarding the control and communication infrastructure. They are key aspects for self-organization and there is a lack of study on the metrics that regulate the self-organization and autonomous response of modern production paradigms. This thesis presents a probabilistic framework that promotes self-organization on a multiagent system based on a new manufacturing concept, the Evolvable Assembly Systems/Evolvable Production Systems. A methodology is proposed to assess the impact of self-organization on the system behavior, by the application of the probabilistic framework that has the dual purpose of controlling and explaining the system dynamics. The probabilistic framework shows the likelihood of some resources being allocated to the production process. This information is constantly updated and exchanged by the agents that compose the system. The emergent effect of this self-organization dynamic is an even load balancing across the system without any centralized controller. The target systems of this work are therefore small systems with small production batches but with a high variability of production conditions and products. The agents that compose the system originated in the agent based architecture of the FP7-IDEAS proejct. This work has extended these agents and the outcome has been tested in the IDEAS demonstrators, as the changes have been incorporated in the latest version of the architecture, and in a simulation and more controlled environment were the proposed metric and its influence were assessed

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime

Improve the Performance of Industrial Agents using Fog Computing

In the last decade, the market requirements have been increasing by demanding numerous different products being highly customizable. Given this need, the necessity for dynamic and flexible production lines are a high priority to meet this change. A traditional approach is not enough to meet the market demand and due to this, several paradigms have been coined out to try and solve this problem. The proposed approach is related to communication between the shop-floor modules in order to create different products. This work proposes an architecture where an integration layer will join a Multiagent System capable of the more recent production paradigms with legacy hardware that is present in the more traditional factories in order to have different products being produced in the same production line. This architecture that revolves an interface that can be used by the agents in the factory in order to use the hardware modules to create a different product if need be. The main features of this project is the fact that by using datamodels and an interface created, it can be easily plugged new stations with different tools to modify the product thus increasing the amount of products that can be created

A multi-agent architecture for plug and produce on an industrial assembly platform

YesModern manufacturing companies face increased pressures to adapt to shorter product life cycles and the need to reconfigure more frequently their production systems to offer new product variants. This paper proposes a new multi-agent architecture utilising “plug and produce” principles for configuration and reconfiguration of production systems with minimum human intervention. A new decision-making approach for system reconfiguration based on tasks re-allocation is presented using goal driven methods. The application of the proposed architecture is described with a number of architectural views and its deployment is illustrated using a validation scenario implemented on an industrial assembly platform. The proposed methodology provides an innovative application of a multi-agent control environment and architecture with the objective of significantly reducing the time for deployment and ramp-up of small footprint assembly systems.The reported research has been part of the EU FP7 research project “PRIME

Service-oriented agents for collaborative industrial automation and production systems

Service-oriented Multi-Agent Systems (SoMAS) is an approach to combine the fundamental characteristics of service-oriented and multi-agent methods into a new platform for industrial automation. Several research works already targeted the connection of these technologies, presenting different perspectives in how and why to join them. This research focuses on available efforts and solutions in the area of SoMAS and explains the idea behind the service-oriented agents in industrial automation. A SoMAS system is mainly composed by shared resources in form of services and their providing/requesting agents. The paper also discusses the required engineering aspects of these systems, from the internal anatomy to the interaction patterns. Parameters of flexibility, reconfiguration, autonomy and reduced development efforts were considered and they should be the trademark of SoMAS. Aiming to illustrate the proposed approach, an example of service-oriented automation agents is given.The authors would like to thank the European Commission and the partners of the EU IST FP6 project “Service-Oriented Cross-layer infrastructure for Distributed smart Embedded devices” (SOCRADES), the EU FP6 "Network of Excellence for Innovative Production Machines and Systems” (I*PROMS), and the EC ICT FP7 project “Cooperating Objects Network of Excellence” (CONET) for their support

Towards the integration of process and quality control using multi-agent technology

The paper introduces a vision on the design of distributed manufacturing control systems using the multi-agent principles to enhance the integration of the production and quality control processes. It is highlighted how agent technology may enforce interaction of manufacturing execution system and distributed control system, enhancing the exploitation of the available information at the quality control and process control levels. A specific focus is made on a suitable engineering methodology for the design and realization of such concept. Innovation is also presented at the level of adaptive process control and self-optimizing quality control, with examples related to a home appliance production line