The goal of this paper is to describe the research on Evolvable Production Systems (EPS) in the context of Reconfigurable Manufacturing Systems (RMS), and to briefly describe a multiagent based control solution. RMS, Holonic and EPS concepts are briefly described and compared. Novel inspiration areas and concepts to solve the demanding requirements set by RMS, such as artificial life and complexity theory, are described. Finally, the multiagent based control solution is described as the underlying infrastructure to support all future development in EPS, using concepts such as emergence and self-organisation.
The work presented in this paper intends to clarify how multiagents can be an adequate paradigm to solve the challenges imposed by Evolvable Assembly Systems (EAS). The article will therefore show that a multiagent architecture based on coalitions of assembly modules (CoBASA) can be successfully used to implement the control architecture for EAS.
This paper details the recent development within evolvable assembly systems, including ontological, methodological, and application developments. This paradigm was recently proposed as an answer to the requirements faced by assembly companies in the current world of business and technological changes. EAS, as with other similar approaches, offers great opportunities for attaining true agility and cost- effective, stepwise automation. EAS does imply that the manner in which we develop and create projects for the development of assembly systems are radically changed, assuming a more synthesis-based approach.
A new paradigm, the Evolvable Assembly Systems (EAS), was recently proposed. This paradigm provides a complete new view on how assembly systems should be designed and developed. Because the control system is one of the key aspects for a successful implementation of EAS this paper proposes a development roadmap to pinpoint directions of research on how control systems should be developed. It is expected that with this information the industry can envision the potential benefits in terms of competitiveness of this approach; still, this paper is especially targeted to motivate researchers from self-organisation and distributed assembly systems to engage in this endeavour together. In particular, topics on self-organisation, emergence, dynamical systems, and distributed artificial intelligence can be the backbone of truly self-adapting assembly systems. In fact EAS seems to be a really demanding and grounded case-study for the referred research communities.
Simulation has played an important role along the years to predict systems' behaviour before their deployment. In the case of self-organising mechatronic systems simulation tools can help researchers and practitioners understanding the full potential of the solution as well as its underlying limitations. Self-organising mechatronic systems have passed a feasibility study and presented promising results. However they are rarely explored in industry in part due to the lack of methods to support their design and configuration and the difficulty to predict the systems' behaviour before their deployment. Given the cost and development time associated with building self-organising mechatronic systems this research problem has been left quite unattended. In this article we present a tool that enables the creation and simulation of Evolvable Production Systems and their self-organising behaviour. The generated operational results can posteriorly be used to analyse the suitability of different design and configuration alternatives for different product types and volumes.
Current major roadmapping efforts have all clearly underlined that true industrialsustainability will require far higher levels of systems’ autonomy and adaptability. In accordance withthese recommendations, the Evolvable Production Systems (EPS) has aimed at developing suchtechnological solutions and support mechanisms. Since its inception in 2002 as a next generation ofproduction systems, the concept is being further developed and tested to emerge as a production systemparadigm. The essence of evolvability resides not only in the ability of system components to adapt to thechanging conditions of operation, but also to assist in the evolution of these components in time such thatprocesses may become self-evolvable, self-reconfigurable, self-tuning, self-diagnosing, etc.Characteristically, Evolvable systems have distributed control, and are composed of intelligent moduleswith embedded control. To assist the development and life cycle issues, a comprehensive methodologicalframework is being developed. A concerted effort is being exerted through European research projects incollaboration with European manufacturers, technology/equipment suppliers, and universities. Afterbriefly stating the fundamental concepts of EPS, this paper presents current developments and applications.
This paper addresses the underlying principles of Evolvable Assembly Systems. This paradigm was recently proposed as an answer to the requirements faced by assembly companies in the current world of business and technological changes. The basis for this new approach lies in a multi-disciplinary study of the needs and requirements, and shifts the technological focus from complex, flexible, multi-purpose systems to simpler, process-oriented, dedicated swarms of machine modules.