BIOSOARM: a bio-inspired self-organising architecture for manufacturing cyber-physical shopfloors

Abstract

Biological collective systems have been an important source of inspiration for the design of production systems, due to their intrinsic characteristics. In this sense, several high level engineering design principles have been distilled and proposed on a wide number of reference system architectures for production systems. However, the application of bio-inspired concepts is often lost due to design and implementation choices or are simply used as heuristic approaches that solve specific hard optimization problems. This paper proposes a bio-inspired reference architecture for production systems, focused on highly dynamic environments, denominated BIO-inspired Self-Organising Architecture for Manufacturing (BIOSOARM). BIOSOARM aims to strictly adhere to bio-inspired principles. For this purpose, both shopfloor components and product parts are individualized and extended into the virtual environment as fully decoupled autonomous entities, where they interact and cooperate towards the emergence of a self-organising behaviour that leads to the emergence of the necessary production flows. BIOSOARM therefore introduces a fundamentally novel approach to production that decouples the system’s operation from eventual changes, uncertainty or even critical failures, while simultaneously ensures the performance levels and simplifies the deployment and reconfiguration procedures. BIOSOARM was tested into both flow-line and “job shop”-like scenarios to prove its applicability, robustness and performance, both under normal and highly dynamic conditions

Social Production System: A Three-Layer Smart Framework for Implementing Autonomous Human-Machine Collaborations in a Shop Floor

“…proposed a bio-inspired reference architecture for the cyberphysical production system to achieve the self-organization of the production system [48]. Chen et al proposed a reinforcement learning-based task-assigning policy to support multi-projects scheduling in the CMfg system [49].…”

Transitioning From Standard Automation Solutions to Cyber-Physical Production Systems: An Assessment of Critical Conceptual and Technical Challenges

“…Fully flat solutions are rarely encountered in the literature with wide application in industry. A complete survey and an application example can be found in [42] that shows that most of the approaches considered along these lines rely in bioinspired concepts. Typical interaction patterns would include [43]: direct cooperation by pre-establishing cooperation rules, stigmergy by making sure that the interactions are mediated by the environment, direct interactions with access to global information or reinforcement whereby a CPPM would base future decisions on previous experiences.…”

“…; have been applied in different mixes and with different meanings across the technical literature (see [44], [42], [45] for a comprehensive set of definitions).…”

“…The more strongly bio-inspired approaches have attempted to do so in the scope of distributed problem solving as well [42], [47], [48], [49], [50], [51], either by embedding the distributed problems solving semantics at the component level (Fully Heterarchical Bio-Inspired Control), or by combining local and global optimization (Semi-Heterarchical Bio-Inspired Control). Cloud abstractions are also increasingly being considered in this scope with the characteristic of hiding the network dimension from the implementation.…”

Application of a Simulation-Based Digital Twin for Predicting Distributed Manufacturing Control System Performance

“…Whenever applied for manufacturing purposes, CPSs are referred to as Cyber-Physical Production Systems (CPPSs) [9]. Most of the proposed CPPSs aim to bring dynamic and flexible solutions using adaptable and reconfigurable distributed control systems [10,11]. Usually, these distributed control systems are modelled as modular components and designed using Multi-Agent Systems (MASs) approaches [12].…”