Andre Dionisio Rocha

An Agent Based Framework to Support Plug And Produce

The new market trends are very different, so it is crucial to the companies improve the tools and capabilities that allow themselves readjust rapidly and effectively to the news market changes and to the new requirements. In order to facilitate this process, it is proposed in this paper an agent based implementation that can provide to the existent systems the capacity to quickly adapt and reconfigure using standard technology. The proposed framework provides an intelligent tool to autonomously help the configuration when a production operator pretends to introduce a new variant of product in runtime and consult important information provided by the system to monitor execution.

An agent based monitoring architecture for plug and produce based manufacturing systems

In recent years a set of production paradigms were proposed in order to allow companies the possibility to face the new market requirements and needs, such as the new demand for highly customized products and the decrease of products life cycle. These new paradigms propose solutions capable of facing these requirements, giving manufacturing systems high capacity to adapt along with high flexibility and intelligence 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 to support pluggability and in this way allow the companies to add and / or remove components during execution without any programming effort and without wasting much valued time. Although these new systems give companies the capacity to be more flexible, they were not designed to perform monitoring as flexible as the control system itself, because the usual monitoring software, mostly based on SCADA systems, is not capable of re-adapting during execution to this new plugging and / or unplugging of devices and to changes in the characteristics of the entire systems topology. Considering these aspects, this article proposes a fully distributed agent based architecture, capable of performing monitoring at different levels while still supporting the addition and removal of monitoring entities, responsible for data extraction and analysis during runtime.

Collaborative routing of products using a self-organizing mechatronic agent framework-A simulation study

An innovative agent-based architecture for dynamic routing is detailed.The architecture is tested under simulation and the results are discussed.Results suggest that the fully distributed approach provides a feasible solution. Scheduling is a fundamental activity in modern shop floors. It is also known to be a highly complex problem which has motivated several sub-formulations and the subsequent models. Traditional approaches, typically enumerative or heuristic, struggle to contain the computation complexity and often present solutions for restricted cases that feature unrealistic assumptions in respect to the system size, flow of products and the system logistics/behaviour. The multiagent-based architecture presented in this paper is aligned with a set of emerging architectures that seek to explore more heterarchical decision and control models to circumvent the limitations of the traditional approaches. The main distinguishing factor of the proposed architecture is that it directly addresses (re)routing/local scheduling of products in plug and produce systems. It does not make any assumptions on the alignment of the orders and, instead, it dynamically handles the potential rescheduling of the orders already on the system based on the available resources, and their state, in a time efficient way. The architecture was tested under a simulation environment, that is geometrically accurate and that supports plug and produce in runtime, to characterize its performance under dynamic conditions.

A multi-agent framework for capability-based reconfiguration of industrial assembly systems

Rapidly changing market requirements and shorter product lifecycles demand assembly systems that are able to cope with frequently changing resources, resource capabilities and product specifications. This paper presents a multi-agent framework that can adapt an assembly system in order to cope with such changes. The focus of this work is on the ability to plug resources (such as PLCs) into and out of the system, and dynamically aggregate resource capabilities to form more complex ones as resources are plugged in. In addition, an implementation of the framework on an industrial assembly system is discussed, and some insights are provided into some of the key features that product specification languages ought to have to be useful in real world assembly systems, and into the added value of using the proposed framework.

Selection of a data exchange format for industry 4.0 manufacturing systems

With the emergence of the Industry 4.0 concept, or the fourth industrial revolution, the industry is bearing witness to the appearance of more and more complex systems, often requiring the integration of various new heterogeneous, modular and intelligent elements with pre-existing legacy devices. This challenge of interoperability is one of the main concerns taken into account when designing such systems-of-systems, commonly requiring the use of standard interfaces to ensure this seamless integration. To aid in tackling this challenge, a common format for data exchange should be adopted. Thus, a study to select the foundations for the development of such a format is hereby presented, taking into account the specific needs of four different use cases representing varied key European industry sectors.

A product handling technical architecture for multiagent-based mechatronic systems

In recent years a set of production paradigms has emerged to circumvent pressing production challenges. In particular the ability of composing lower order components to form higher order entities with more complex functionalities and reuse them to build yet more complex system has been widely explored. However material handling aspects have been tackled independently of the control/reconfiguration architecture. Traditionally transport resources have been assumed passive and the organization of the production has been treated as a scheduling problems that often ignores disturbances in the transport system. This renders most of the scheduling approaches too theoretical to be applied in real production scenarios and has motivated researchers to pursuit alternative approaches to this sort of production organization problems. In this paper a technical agent-based architecture that integrates control/reconfiguration aspects with material handling is detailed. The architecture supports the simultaneous usage of conveyor and AGV-based material handling systems and the addition of production or material handling resources is handled in a transparent way through careful generic interaction design. Overall the proposed architecture can be applied to any mechatronic system favouring re-configuration and minimizing reprogramming.In recent years a set of production paradigms has emerged to circumvent pressing production challenges. In particular the ability of composing lower order components to form higher order entities w ...

PRIME as a Generic Agent Based Framework to Support Pluggability and Reconfigurability Using Different Technologies

Presently the manufacturers are facing a challenging and important period. The markets are very different comparatively to the past, with constant changes and facing a big crisis. Hence, with these new characteristics is very important for the companies quick adaptations in order to take advantage of new business opportunities. However on the shop floor is not easy reconfigure the production lines to perform new tasks. The PRIME framework presents an agent based solution capable to rapidly reconfigure and readapt the production line using standard technology. In this paper is demonstrated the usability of this framework with three completely different technologies. With this flexibility, using PRIME it is possible perform plug and produce, reconfigurability and monitoring for all kind of technologies, not obligating the companies to reform all components in the line, avoiding external costs and stoppages.

Big Data Analysis to Ease Interconnectivity in Industry 4.0—A Smart Factory Perspective

Thriving and challenging market trends led to changes in the manufacturing industry. Production lines that need to adapt to customisable products on the fly emerged. By applying communication and sensors to the shop-floor, along with Industry 4.0 principles, this became a possibility. The growing amount of sensors led to an exponential boom of the amount of data available, creating the concept of Smart Factory. By applying Big Data Analysis to this data, it may be possible to optimise Smart Factories. There are technologies capable of doing this, even though only some are capable of guaranteeing Smart Factory requirements, such as real-time. A study of these technologies, based on SME’s experts’ opinion, is hereby presented to assess the most suitable ones to analyse Big Data in a Smart Factory environment.

A Highly Flexible, Distributed Data Analysis Framework for Industry 4.0 Manufacturing Systems

In modern manufacturing, high volumes of data are constantly being generated by the manufacturing processes. However, only a small percentage is actually used in a meaningful way. As part of the H2020 PERFoRM project, which follows the Industry 4.0 vision and targets the seamless reconfiguration of robots and machinery, this paper proposes a framework for the implementation of a highly flexible, pluggable and distributed data acquisition and analysis system, which can be used for both supporting run-time decision making and triggering self-adjustment methods, allowing corrections to be made before failures actually occur, therefore reducing the impact of such events in production.

A Cloud-Based Infrastructure to Support Manufacturing Resources Composition

Current development in emerging technologies, such as the Internet of Things (IoT), service-oriented and high-performance computing combined with the increasing advancement of manufacturing technologies and information systems, triggered a new manufacturing model. Modern industrial automation domain is characterized by heterogeneous equipment encompassing distinct functions, network interfaces and I/O specifications and controlled by distinct software/hardware platforms. To cope with such specificity, manufacturing enterprises are demanding for new service-oriented models that aimoc to abstract physical systems in terms of their functionalities/capabilities. In this scenario, Cloud Manufacturing (CMfg) arises as a new networked, service-oriented, customer centric and demand driven paradigm where manufacturing resources and capabilities are virtualized as services available in the cloud to users.