Intelligent Product Agents for Multi-Agent Control of Manufacturing Systems

The current manufacturing paradigm is shifting toward more flexible manufacturing systems that produce highly personalized products, adapt to unexpected disturbances in the system, and readily integrate new manufacturing system technology. However, to achieve this type of flexibility, new system-level control strategies must be developed, tested, and integrated to coordinate the components on the shop floor. One strategy that has been previously proposed to coordinate the resources and parts in a manufacturing system is multi-agent control. The manufacturing multi-agent control strategy consists of agents that interface with the various components on the shop floor and continuously interact with each other to drive the behavior of the manufacturing system. Two of the most important decision-making agents for this type of control strategy are product agents and resource agents. A product agent represents a single product and a resource agent represents a single resource on the plant floor. The objective of a product agent is to make decisions for an individual product and request operations from the resource agents based on manufacturer and customer specifications. A resource agent is the high-level controller for a resource on the shop floor (e.g., machines, material-handling robots, etc.). A resource agent communicates with other product and resource agents in the system, fulfills product agent requests, and interfaces with the associated resource on the plant floor. While both product agents and resource agents are important to ensure effective performance of the manufacturing system, the work presented in this dissertation improves the intelligence and capabilities of product agents by providing a standardized product agent architecture, models to capture the dynamics and constraints of the manufacturing environment, and methods to make improved decisions in a dynamic system. New methods to explore the manufacturing system and cooperate with other agents in the system are provided. The proposed architecture, models, and methods are tested in a simulated manufacturing environment and in several manufacturing testbeds with physical components. The results of these experiments showcase the improved flexibility and adaptability of this approach. In these experiments, the model-based product agent effectively makes decisions to meet its production requirements, while responding to unexpected disturbances in the system, such as machine failures or new customer orders. The model-based product agent proposed in this dissertation pushes the fields of manufacturing and system-level control closer to realizing the goals of increased personalized production and improved manufacturing system flexibility.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162893/1/ikoval_1.pd

An extended process automation system : an approach based on a multi-agent system

This thesis describes studies on application of multi-agent systems (acronym: MAS) to enhance process automation systems. A specification of an extended process automation system is presented. According to this specification, MAS can be used to extend the functionality of ordinary process automation systems at higher levels of control. Anticipated benefits of the specification include enhanced reconfigurability, responsiveness and flexibility properties of process automation. Previous research concerning applications of MAS in process automation has been more limited than in other fields of automation. There has been more research about this topic for example in the area of discrete manufacturing. As goal-oriented distributed systems with coordination capabilities MAS have been found applicable to a part of automation functions, e.g. modification of control logic in abnormal situations. However, when applying MAS to process automation the particular characteristics of this application domain need to be taken into account. The important role of continuous control in process automation needs to be considered. In this thesis, a specification of an agent platform for process automation is presented as a basis for applying MAS in this application domain. The specification extends a FIPA-compliant agent platform with process automation specific functionality. It utilises a hierarchical agent organisation, a BDI-agent model and qualitative reasoning. It also presents a model for programming MAS applications for process automation with techniques of distributed planning and search. Two applications are specified using the platform. One of these shows how the techniques of distributed planning can be applied in sequential control. The other provides a design model for supervisory continuous control applications using the techniques of distributed search. Experiments performed with a laboratory test environment using prototype implementations of the applications are presented. The experiments are able to demonstrate the feasibility of the approach in limited test scenarios. They also provide information about in which ways MAS techniques are able enhance the properties of process automation. As a result of the work presented in this thesis more knowledge has been gained about application of MAS in process automation. The specification of the agent platform for process automation and its applications provide a basis for further studies of this topic.reviewe

Towards a new methodology for design, modelling, and verification of reconfigurable distributed control systems based on a new extension to the IEC 61499 standard

In order to meet user requirements and system environment changes, reconfigurable control systems must dynamically adapt their structure and behaviour without disrupting system operation. IEC 61499 standard provides limited support for the design and verification of such systems. In fact, handling different reconfiguration scenarios at runtime is difficult since function blocks in IEC 61499 cannot be changed at run-time. Hence, this thesis promotes an IEC 61499 extension called reconfigurable function block (RFB) that increases design readability and smoothly switches to the most appropriate behaviour when a reconfiguration event occurs. To ensure system feasibility after reconfiguration, in addition to the qualitative verification, quantitative verification based on probabilistic model checking is addressed in a new RFBA approach. The latter aims to transform the designed RFB model automatically into a generalised reconfigurable timed net condition/event system model (GRTNCES) using a newly developed environment called RFBTool. The GR-TNCES fits well with RFB and preserves its semantic. Using the probabilistic model checker PRISM, the generated GR-TNCES model is checked using defined properties specified in computation tree logic. As a result, an evaluation of system performance and an estimation of reconfiguration risks are obtained. The RFBA methodology is applied on a distributed power system case study.Dynamische Anforderungen und Umgebungen erfordern rekonfigurierbare Anlagen und Steuerungssysteme. Rekonfiguration ermöglicht es einem System, seine Struktur und sein Verhalten an interne oder externe Änderungen anzupassen. Die Norm IEC 61499 wurde entwickelt, um (verteilte) Steuerungssysteme auf Basis von Funktionsbausteinen zu entwickeln. Sie bietet jedoch wenig Unterstützung für Entwurf und Verifikation. Die Tatsache, dass eine Rekonfiguration das System-Ausführungsmodell verändert, erschwert die Entwicklung in IEC 61499 zusätzlich. Daher schlägt diese Dissertation rekonfigurierbare Funktionsbausteine (RFBs) als Erweiterung der Norm vor. Ein RFB verarbeitet über einen Master-Slave-Automaten Rekonfigurationsereignisse und löst das entsprechende Verhalten aus. Diese Hierarchie trennt das Rekonfigurationsmodell vom Steuerungsmodell und vereinfacht so den Entwurf. Die Funktionalität des Entwurfs muss verifiziert werden, damit die Ausführbarkeit des Systems nach einer Rekonfiguration gewährleistet ist. Hierzu wird das entworfene RFB-Modell automatisch in ein generalised reconfigurable timed net condition/event system übersetzt. Dieses wird mit dem Model-Checker PRISM auf qualitative und quantitative Eigenschaften überprüft. Somit wird eine Bewertung der Systemperformanz und eine Einschätzung der Rekonfigurationsrisiken erreicht. Die RFB-Methodik wurde in einem Softwarewerkzeug umgesetzt und in einer Fallstudie auf ein dezentrales Stromnetz angewendet

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Adapter module for self-learning production systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e ComputadoresThe dissertation presents the work done under the scope of the NP7 Self-Learning project regarding the design and development of the Adapter component as a foundation for the Self-Learning Production Systems (SLPS). This component is responsible to confer additional proprieties to production systems such as lifecycle learning, optimization of process parameters and, above all, adaptation to different production contexts. Therefore, the SLPS will be an evolvable system capable to self-adapt and learn in response to dynamic contextual changes in manufacturing production process in which it operates. The key assumption is that a deeper use of data mining and machine learning techniques to process the huge amount of data generated during the production activities will allow adaptation and enhancement of control and other manufacturing production activities such as energy use optimization and maintenance. In this scenario, the SLPS Adapter acts as a doer and is responsible for dynamically adapting the manufacturing production system parameters according to changing manufacturing production contexts and, most important, according to the history of the manufacturing production process acquired during SLPS run time.To do this, a Learning Module has been also developed and embedded into the SLPS Adapter. The SLPS Learning Module represents the processing unit of the SLPS Adapter and is responsible to deliver Self-learning capabilities relying on data mining and operator’s feedback to up-date the execution of adaptation and context extraction at run time. The designed and implemented SLPS Adapter architecture is assessed and validated into several application scenario provided by three industrial partners to assure industrial relevant self-learning production systems. Experimental results derived by the application of the SLPS prototype into real industrial environment are also presented

Distributed Planning for Self-Organizing Production Systems

Für automatisierte Produktionsanlagen gibt es einen fundamentalen Tradeoff zwischen Effizienz und Flexibilität. In den meisten Fällen sind die Abläufe nicht nur durch den physischen Aufbau der Produktionsanlage, sondern auch durch die spezielle zugeschnittene Programmierung der Anlagensteuerung fest vorgegeben. Änderungen müssen aufwändig in einer Vielzahl von Systemen nachgezogen werden. Das macht die Herstellung kleiner Stückzahlen unrentabel. In dieser Dissertation wird ein Ansatz entwickelt, um eine automatische Anpassung des Verhaltens von Produktionsanlagen an wechselnde Aufträge und Rahmenbedingungen zu erreichen. Dabei kommt das Prinzip der Selbstorganisation durch verteilte Planung zum Einsatz. Die aufeinander aufbauenden Ergebnisse der Dissertation sind wie folgt: 1. Es wird ein Modell von Produktionsanlagen entwickelt, dass nahtlos von der detaillierten Betrachtung physikalischer Produktionsprozesse bis hin zu Lieferbeziehungen zwischen Unternehmen skaliert. Im Vergleich zu existierenden Modellen von Produktionsanlagen werden weniger limitierende Annahmen gestellt. In diesem Sinne ist der Modellierungsansatz ein Kandidat für eine häufig geforderte "Theorie der Produktion". 2. Für die so modellierten Szenarien wird ein Algorithmus zur Optimierung der nebenläufigen Abläufe entwickelt. Der Algorithmus verbindet Techniken für die kombinatorische und die kontinuierliche Optimierung: Je nach Detailgrad und Ausgestaltung des modellierten Szenarios kann der identische Algorithmus kombinatorische Fertigungsfeinplanung (Scheduling) vornehmen, weltweite Lieferbeziehungen unter Einbezug von Unsicherheiten und Risiko optimieren und physikalische Prozesse prädiktiv regeln. Dafür werden Techniken der Monte-Carlo Baumsuche (die auch bei Deepminds Alpha Go zum Einsatz kommen) weiterentwickelt. Durch Ausnutzung zusätzlicher Struktur in den Modellen skaliert der Ansatz auch auf große Szenarien. 3. Der Planungsalgorithmus wird auf die verteilte Optimierung durch unabhängige Agenten übertragen. Dafür wird die sogenannte "Nutzen-Propagation" als Koordinations-Mechanismus entwickelt. Diese ist von der Belief-Propagation zur Inferenz in Probabilistischen Graphischen Modellen inspiriert. Jeder teilnehmende Agent hat einen lokalen Handlungsraum, in dem er den Systemzustand beobachten und handelnd eingreifen kann. Die Agenten sind an der Maximierung der Gesamtwohlfahrt über alle Agenten hinweg interessiert. Die dafür notwendige Kooperation entsteht über den Austausch von Nachrichten zwischen benachbarten Agenten. Die Nachrichten beschreiben den erwarteten Nutzen für ein angenommenes Verhalten im Handlungsraum beider Agenten. 4. Es wird eine Beschreibung der wiederverwendbaren Fähigkeiten von Maschinen und Anlagen auf Basis formaler Beschreibungslogiken entwickelt. Ausgehend von den beschriebenen Fähigkeiten, sowie der vorliegenden Aufträge mit ihren notwendigen Produktionsschritten, werden ausführbare Aktionen abgeleitet. Die ausführbaren Aktionen, mit wohldefinierten Vorbedingungen und Effekten, kapseln benötigte Parametrierungen, programmierte Abläufe und die Synchronisation von Maschinen zur Laufzeit. Die Ergebnisse zusammenfassend werden Grundlagen für flexible automatisierte Produktionssysteme geschaffen -- in einer Werkshalle, aber auch über Standorte und Organisationen verteilt -- welche die ihnen innewohnenden Freiheitsgrade durch Planung zur Laufzeit und agentenbasierte Koordination gezielt einsetzen können. Der Bezug zur Praxis wird durch Anwendungsbeispiele hergestellt. Die Machbarkeit des Ansatzes wurde mit realen Maschinen im Rahmen des EU-Projekts SkillPro und in einer Simulationsumgebung mit weiteren Szenarien demonstriert

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Towards semantics-driven modelling and simulation of context-aware manufacturing systems

Systems modelling and simulation are two important facets for thoroughly and effectively analysing manufacturing processes. The ever-growing complexity of the latter, the increasing amount of knowledge, and the use of Semantic Web techniques adhering meaning to data have led researchers to explore and combine together methodologies by exploiting their best features with the purpose of supporting manufacturing system's modelling and simulation applications. In the past two decades, the use of ontologies has proven to be highly effective for context modelling and knowledge management. Nevertheless, they are not meant for any kind of model simulations. The latter, instead, can be achieved by using a well-known workflow-oriented mathematical modelling language such as Petri Net (PN), which brings in modelling and analytical features suitable for creating a digital copy of an industrial system (also known as "digital twin"). The theoretical framework presented in this dissertation aims to exploit W3C standards, such as Semantic Web Rule Language (SWRL) and Web Ontology Language (OWL), to transform each piece of knowledge regarding a manufacturing system into Petri Net modelling primitives. In so doing, it supports the semantics-driven instantiation, analysis and simulation of what we call semantically-enriched PN-based manufacturing system digital twins. The approach proposed by this exploratory research is therefore based on the exploitation of the best features introduced by state-of-the-art developments in W3C standards for Linked Data, such as OWL and SWRL, together with a multipurpose graphical and mathematical modelling tool known as Petri Net. The former is used for gathering, classifying and properly storing industrial data and therefore enhances our PN-based digital copy of an industrial system with advanced reasoning features. This makes both the system modelling and analysis phases more effective and, above all, paves the way towards a completely new field, where semantically-enriched PN-based manufacturing system digital twins represent one of the drivers of the digital transformation already in place in all companies facing the industrial revolution. As a result, it has been possible to outline a list of indications that will help future efforts in the application of complex digital twin support oriented solutions, which in turn is based on semantically-enriched manufacturing information systems. Through the application cases, five key topics have been tackled, namely: (i) semantic enrichment of industrial data using the most recent ontological models in order to enhance its value and enable new uses; (ii) context-awareness, or context-adaptiveness, aiming to enable the system to capture and use information about the context of operations; (iii) reusability, which is a core concept through which we want to emphasize the importance of reusing existing assets in some form within the industrial modelling process, such as industrial process knowledge, process data, system modelling primitives, and the like; (iv) the ultimate goal of semantic Interoperability, which can be accomplished by adding data about the metadata, linking each data element to a controlled, shared vocabulary; finally, (v) the impact on modelling and simulation applications, which shows how we could automate the translation process of industrial knowledge into a digital manufacturing system and empower it with quantitative and qualitative analytical technics

A Review of Building Information Modeling and Simulation as Virtual Representations Under the Digital Twin Concept

Building Information Modeling (BIM) is a highly promising technique for achieving digitalization in the construction industry, widely used in modern construction projects for digitally representing facilities. Nevertheless, retains limitations in terms of representing construction operations. The digital twin concept may potentially overcome these limitations and initiate advanced digital transformation in the construction industry as it has revolutionized the product lifecycle management in the manufacturing industry. This research provides a critical review of applying digital twin in the construction industry. Altogether, 140 papers from related journals and databases were reviewed. The digital aspect of twinning consists of BIM and simulation modeling. These two techniques have been used to create virtual or digital representations of actual buildings and real-world construction processes. However, integrating and applying BIM and simulation modeling according to the digital twin concept remains to be fully studied. Comprehensive evaluations of BIM, simulation modeling, and digital twin will provide a well-defined framework for this research, to identify direction and potential for digital twin in the construction industry, thereby progressing to the next level of digitalization and improvement in construction management practice