Towards autonomy, self-organisation and learning in holonic manufacturing

This paper intends to discuss self-organisation and learning capabilities in autonomous and cooperative holons that are part of a holonic manufacturing control system. These capabilities will support the dynamic adaptation of the manufacturing control to the manufacturing evolution and emergency, specially the agile reaction to unexpected disturbances

A Combination of Workforce Sizing Plan and Worker Selection Guide with the Holonic Control Paradigm

The Holonic Workforce Allocation Model (HWM) is a dual-level advisory model using the concepts of Holonic Manufacturing Systems (HMS). The quantitative and pre-active level is termed as Workforce Sizing Plan (WOZIP), whereby the number of workers required for a production period can be forecasted. The resultant group of workers, in a case-by-case fashion, are continually assigned to parallel series of production tasks considering the individual skill and task urgency factors, at the qualitative and reactive level called Worker Selection Guide (WOSEG). When developing such an integrated model, four holonic control attributes need to be observed, namely real-time control, event-driven control, intelligent control, and distributed control. These control attributes help ensure the effective and sustainable improvement of factory processes, for which the strengths of and the interactions between holonic elements are discussed in this paper. Keywords: Holonic control, workforce sizing, worker selectio

An agile and adaptive holonic architecture for manufacturing control

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

A formal validation approach for holonic control system specifications

The holonic manufacturing paradigm allows a new approach to the emergent requirements faced by the manufacturing world, through the concepts of modularity, decentralisation, autonomy, re-use of control software components. The formal modelling and validation of the structural and behavioural specifications of holonic control systems assumes a critical role. This paper discusses the formal validation of the Petri Net models designed to represent the behaviour and specifications of the holon classes defined at ADACOR architecture

Skill-based reconfiguration of industrial mobile robots

Caused by a rising mass customisation and the high variety of equipment versions, the exibility of manufacturing systems in car productions has to be increased. In addition to a exible handling of production load changes or hardware breakdowns that are established research areas in literature, this thesis presents a skill-based recon guration mechanism for industrial mobile robots to enhance functional recon gurability. The proposed holonic multi-agent system is able to react to functional process changes while missing functionalities are created by self-organisation. Applied to a mobile commissioning system that is provided by AUDI AG, the suggested mechanism is validated in a real-world environment including the on-line veri cation of the recon gured robot functionality in a Validity Check. The present thesis includes an original contribution in three aspects: First, a recon - guration mechanism is presented that reacts in a self-organised way to functional process changes. The application layer of a hardware system converts a semantic description into functional requirements for a new robot skill. The result of this mechanism is the on-line integration of a new functionality into the running process. Second, the proposed system allows maintaining the productivity of the running process and exibly changing the robot hardware through provision of a hardware-abstraction layer. An encapsulated Recon guration Holon dynamically includes the actual con guration each time a recon guration is started. This allows reacting to changed environment settings. As the resulting agent that contains the new functionality, is identical in shape and behaviour to the existing skills, its integration into the running process is conducted without a considerable loss of productivity. Third, the suggested mechanism is composed of a novel agent design that allows implementing self-organisation during the encapsulated recon guration and dependability for standard process executions. The selective assignment of behaviour-based and cognitive agents is the basis for the exibility and e ectiveness of the proposed recon guration mechanism

Pollux: a dynamic hybrid control architecture for flexible job shop systems

Nowadays, manufacturing control systems can respond more effectively to exigent market requirements and real-time demands. Indeed, they take advantage of changing their structural and behavioural arrangements to tailor the control solution from a diverse set of feasible configurations. However, the challenge of this approach is to determine efficient mechanisms that dynamically optimise the configuration between different architectures. This paper presents a dynamic hybrid control architecture that integrates a switching mechanism to control changes at both structural and behavioural level. The switching mechanism is based on a genetic algorithm and strives to find the most suitable operating mode of the architecture with regard to optimality and reactivity. The proposed approach was tested in a real flexible job shop to demonstrate the applicability and efficiency of including an optimisation algorithm in the switching process of a dynamic hybrid control architecture.This work was supported by the Colombian scholarship programme of department of science – COLCIENCIAS under grant ‘Convocatoria 568 – Doctorados en el exterior’ and the Pontificia Universidad Javeriana under grant ‘Programa de Formacion de posgrados del Profesor Javeriano’.info:eu-repo/semantics/publishedVersio

Self-organising multi-agent control for distribution networks with distributed energy resources

Recent years have seen an increase in the connection of dispersed distributed energy resources (DERs) and advanced control and operational components to the distribution network. These DERs can come in various forms, including distributed generation (DG), electric vehicles (EV), energy storage, etc. The conditions of these DERs can be varying and unpredictably intermittent. The integration of these distributed components adds more complexity and uncertainty to the operation of future power networks, such as voltage, frequency, and active/reactive power control. The stochastic and distributed nature of DGs and the difficulty in predicting EV charging patterns presents problems to the control and management of the distribution network. This adds more challenges to the planning and operation of such systems. Traditional methods for dealing with network problems such as voltage and power control could therefore be inadequate. In addition, conventional optimisation techniques will be difficult to apply successfully and will be accompanied with a large computational load. There is therefore a need for new control techniques that break the problem into smaller subsets and one that uses a multi-agent system (MAS) to implement distributed solutions. These groups of agents would coordinate amongst themselves, to regulate local resources and voltage levels in a distributed and adaptive manner considering varying conditions of the network. This thesis investigates the use of self-organising systems, presenting suitable approaches and identifying the challenges of implementing such techniques. It presents the development of fully functioning self-organising multi-agent control algorithms that can perform as effectively as full optimization techniques. It also demonstrates these new control algorithms on models of large and complex networks with DERs. Simulation results validate the autonomy of the system to control the voltage independently using only local DERs and proves the robustness and adaptability of the system by maintaining stable voltage control in response to network conditions over time.Recent years have seen an increase in the connection of dispersed distributed energy resources (DERs) and advanced control and operational components to the distribution network. These DERs can come in various forms, including distributed generation (DG), electric vehicles (EV), energy storage, etc. The conditions of these DERs can be varying and unpredictably intermittent. The integration of these distributed components adds more complexity and uncertainty to the operation of future power networks, such as voltage, frequency, and active/reactive power control. The stochastic and distributed nature of DGs and the difficulty in predicting EV charging patterns presents problems to the control and management of the distribution network. This adds more challenges to the planning and operation of such systems. Traditional methods for dealing with network problems such as voltage and power control could therefore be inadequate. In addition, conventional optimisation techniques will be difficult to apply successfully and will be accompanied with a large computational load. There is therefore a need for new control techniques that break the problem into smaller subsets and one that uses a multi-agent system (MAS) to implement distributed solutions. These groups of agents would coordinate amongst themselves, to regulate local resources and voltage levels in a distributed and adaptive manner considering varying conditions of the network. This thesis investigates the use of self-organising systems, presenting suitable approaches and identifying the challenges of implementing such techniques. It presents the development of fully functioning self-organising multi-agent control algorithms that can perform as effectively as full optimization techniques. It also demonstrates these new control algorithms on models of large and complex networks with DERs. Simulation results validate the autonomy of the system to control the voltage independently using only local DERs and proves the robustness and adaptability of the system by maintaining stable voltage control in response to network conditions over time

A new approach for the validation of conceptual holonic constructions

The concepts of holon and holarchy were first applied in the manufacturing world to develop Holonic Manufacturing Systems. Since then, they have been used in many fields and have proved to be applicable concepts for developing applications in any business area. Resulting applications are based on conceptual holonic constructions. Like any model, a holarchy needs to be validated under real circumstances. Such validation assures the quality of the holarchy before it is implemented. In general, validation research tends to target: 1) the specific types of holons handled in each proposal and/or the selected development paradigms; and 2) algorithm performance rather than architecture quality. This paper proposes and evaluates a methodology that focuses on the quality of the architecture. This methodology is able to validate any holonic architecture built to meet trade requirements. Moreover, this is a general-purpose methodology. Therefore, the methodology would be valid for any domain and would not be invalidated by holon types and/or implementation paradigms emerging, changing or falling into disuse. For this purpose, we consider holonic architectures as conceptual models, using the pure holon and holarchy concepts and passing up not only any specific implementation paradigm but also any set of specific holon types

An agile and adaptive holonic architecture for manufacturing control

In the last decades significant changes in the manufacturing environment have been noticed: moving from a local economy towards a global economy, with markets asking for products with high quality at lower costs, highly customised and with short life cycle. In this environment, the manufacturing enterprises, to avoid the risk to lose competitiveness, search to answer more closely to the customer demands, by improving their flexibility and agility, while maintaining their productivity and quality. Actually, the dynamic response to emergence is becoming a key issue, due to the weak response of the traditional manufacturing control systems to unexpected disturbances, mainly because of the rigidity of their control architectures. In these circumstances, the challenge is to develop manufacturing control systems with autonomy and intelligence capabilities, fast adaptation to the environment changes, more robustness against the occurrence of disturbances, and easier integration of manufacturing resources and legacy systems. Several architectures using emergent concepts and technologies have been proposed, in particular those based in the holonic manufacturing paradigm. Holonic manufacturing is a paradigm based in the ideas of the philosopher Arthur Koestler, who proposed the word holon to describe a basic unit of organisation in biological and social systems. A holon, as Koestler devised the term, is an identifiable part of a (manufacturing) system that has a unique identity, yet is made up of sub-ordinate parts and in turn is part of a larger whole. The introduction of the holonic manufacturing paradigm allows a new approach to the manufacturing problem, bringing the advantages of modularity, decentralisation, autonomy, scalability, and re-use of software components. This dissertation intends to develop an agile and adaptive manufacturing control architecture to face the current requirements imposed to the manufacturing enterprises. The architecture proposed in this dissertation addresses the need for the fast reaction to disturbances at the shop floor level, increasing the agility and flexibility of the enterprise, when it works in volatile environments, characterised by the frequent occurrence of unexpected disturbances. The proposed architecture, designated by ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), is based in the holonic manufacturing paradigm, build upon autonomous and cooperative holons, allowing the development of manufacturing control applications that present all the features of decentralised and holonic systems. ADACOR holonic architecture introduces an adaptive control that balances dynamically between a more centralised structure and a more decentralised one, allowing to combine the global production optimisation with agile reaction to unexpected disturbances. Nas últimas décadas têm-se assistido a mudanças significativas no ambiente de fabrico: evoluindo de uma economia local para um economia global, com os mercados a procurar produtos com elevada qualidade a baixos preços, altamente customizados e com um ciclo de vida curto. Neste ambiente, as empresas de manufactura, para evitar o risco de perda de competitividade, procuram responder às solicitações dos clientes, melhorando a sua flexibilidade e agilidade, mantendo os mesmos índices de produtividade e qualidade. Na verdade, a resposta dinâmica à emergência está a tornar-se num assunto chave, devido `a fraca resposta a perturbações que os sistemas de controlo de fabrico tradicionais apresentam, principalmente devido à rigidez das suas arquitecturas de controlo. Nestas circunstâncias, é fundamental o desenvolvimento de sistemas de controlo de fabrico com capacidades de autonomia e inteligência, rápida adaptação às mudanças, maior robustez à ocorrência de perturbações e fácil integração de recursos físicos e sistemas legados. Diversas arquitecturas usando conceitos e tecnologias emergentes têm sido propostas, em particular algumas baseadas no paradigma da produção holónica. O paradigma da produção holónica é inspirado nas ideias de Arthur Koestler, que propôs a palavra holon para descrever uma unidade básica de organização de sistemas biológicos e sociais. Um holon, de acordo com a definição de Koestler, é uma parte identificável do sistema com identidade única, composta por sub-partes e fazendo simultaneamente parte do todo. A introdução do paradigma da produção holónica permite uma nova abordagem aos sistemas de controlo de fabrico, trazendo vantagens de modularidade, descentralização, autonomia, escalabilidade e reutilização de componentes. Esta dissertação pretende desenvolver uma arquitectura de controlo ágil e adaptativa que suporte os requisitos actuais impostos `as empresas de manufactura. A arquitectura proposta visa a necessidade de uma reacção rápida a perturbações, ao nível da planta fabril, melhorando a flexibilidade e agilidade da empresa quando esta opera em ambientes voláteis, caracterizados pela ocorrência frequente de perturbações inesperadas. A arquitectura proposta, designada por ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems), é baseada no paradigma da produção holónica e construída sobre holons autónomos e cooperativos, permitindo o desenvolvimento de aplicações de controlo de fabrico que apresentem todas as características dos sistemas descentralizados e holónicos. A arquitectura holónica ADACOR introduz um controlo adaptativo que balança dinamicamente entre uma estrutura de controlo mais centralizada e uma mais descentralizada, permitindo combinar a optimização da produção com a ágil reacção a perturbações

Knowledge and agent-based system for decentralised scheduling in manufacturing

The aim of the research paper is to develop algorithms for manufacturers’ agents that would allow them to sequence their own operation plans and to develop a multi-agent infrastructure to allow operation pair agents to cooperatively adjust the timing of manufacturing operations. The scheduling problem consisted of jobs with fixed process plans and of manufacturers collectively offering the necessary operations for the jobs. Manufacturer agents sequenced and pair agents timed each operation as and when required. Timing an operation triggered a cascade of conflicts along the job process plan that other pair agents would pick up on and would take action accordingly. The conventional approach performs conflict resolution in series and manufacturer agents as well as pair agents wait until they are allowed to sequence and time the next operation. The limiting assumption behind that approach was systematically removed, and the proposed approach allowed manufacturers to perform operation scheduling in parallel, cutting down tenfold on the computation time. The multi-agent infrastructure consists of the Protégé knowledge base, the Pellet semantic reasoner and the Workflows and Agent Development Environment (WADE). The case studies used were the MT6, MT10 and LA19 job shop scheduling problems; and an industrial use case was provided to give context to the manufacturing environment investigated. Although there were benefits from the decentralised manufacturing system, we noted an optimality loss of 34% on the makespans. However, for scalability, our approach showed good promise