Decentralized Scheduling of Discrete Production Systems with Limited Buffers

Die Steuerung der Produktion ist eine der Kernaufgaben eines jeden produzierenden Unternehmens. Sie ist insbesondere wichtig, um auf die Anforderungen des Marktes und damit auf die Wünsche der Kunden reagieren zu können. Aktuelle Trends im Markt führen dabei zu einer hochindividualisierten Produktion bei gleichzeitiger Erhöhung der produzierten Stückzahlen. Eine Konsequenz daraus ist, dass Unternehmen über flexiblere und agilere Produktionssysteme verfügen müssen, um auf die sich ständig ändernden Kundenwünsche reagieren zu können. Da starre Fertigungslinien nicht mehr geeignet sind, werden zunehmend komplexere Strukturen wie die der Werkstattfertigung oder Matrixproduktion eingesetzt. Hierfür werden geeignete Steuerungsmethoden für die Produktion benötigt. Diese Arbeit beschäftigt sich mit eben jenen Steuerungsmethoden, genauer gesagt Methoden zur Planung von Produktionsaufträgen in diesen neuen Produktionssystemen. Zur Steuerung eignen sich echtzeitfähige und autonome Entscheidungssysteme, mit denen die Steuerung der neuen Organisationsstruktur der Produktion angepasst ist. Agentenbasierte Systeme bieten genau diese Eigenschaften und erlauben es, komplexe Planungsaufgaben in kleinere Teilprobleme zu zerlegen, die schneller und genauer gelöst werden können. Sie erfordern die Verfügbarkeit von Daten in Echtzeit und eine schnelle Kommunikation zwischen den Agenten, was heute dank der vierten industriellen Revolution zur Verfügung steht. Demgegenüber steht der erhöhte Koordinierungsbedarf, der in diesen Systemen beherrscht werden muss. Das Ziel dieser Arbeit ist es, einen dezentralen Produktionsplanungs-Algorithmus zu entwickeln, der in einem Multi-Agenten-System implementiert ist. Er berücksichtigt begrenzte Verfügbarkeit von Pufferplätzen an jedem Arbeitsplatz, ein Thema, das in der Literatur wenig erforscht ist. Der Algorithmus ist in einer flexiblen Werkstattfertigung anwendbar und zeigt eine große Zeiteffizienz bei der Einplanung größerer Mengen von Aufträgen. Um dieses Ziel zu erreichen, wird zunächst der Produktionsplanungs-Algorithmus ohne das Agentensystem entworfen. Er basiert auf der von \textcite{adams1988} veröffentlichten Shifting Bottleneck Heuristik. Da viele Änderungen notwendig sind, um die geforderten Eigenschaften berücksichtigen zu können, bleibt nur die grundlegende Vorgehensweise gleich, während alle Schritte der Heuristik von Grund auf neu modelliert werden. Anschließend wird ein Multi-Agenten-System entworfen, das die genannten Anforderungen abbildet und den Algorithmus zur Planung verwendet. In diesem System hat jeder Arbeitsplatz einen Arbeitsplatzagenten, der für die Planung und Steuerung seines zugeordneten Arbeitsplatzes zuständig ist, sowie einige zusätzliche Agenten für die Kommunikation, die Datenspeicherung und allgemeine Aufgaben. Der entworfene Algorithmus wird angepasst und in das Multi-Agenten-System implementiert. Da das System im praktischen Einsatz immer eine Lösung finden muss, stellen wir mögliche Fehlerfälle vor und wie mit ihnen umgegangen wird. Abschließend findet eine numerische Evaluierung mit zwei realen Produktionssystemen statt. Da sich diese Systeme in einem wichtigen Merkmal ähneln, werden weitere zufällig erzeugte Beispiele getestet und ausgewertet

Production control

This thesis analyzes important concepts in production control from the perspective of a typical manufacturing plant. The scope is further limited to include theory that is especially relevant for the case company. The case company is an electric motor manufacturer ABB Oy, Motors and Generators Vaasa. The purpose of the research is first to develop understanding of theoretical concepts regarding production control. Secondly the case company will be used as an example to show some applications of the concepts discussed. The goal is to find the most effective tools for the development of the case company’s production control. The research is divided into three parts: a theoretical part based on literature on production control, to the analysis of the case company’s production control and to a simulation study. The main focus will be given to principles that are directly applicable by the management of a manufacturing plant. The purpose of simulation will be to further increase the understanding of the theory discussed and to show the contrast of some varying production control configurations. The research problem is: How can theoretical frameworks regarding production control be used for significant improvement in a typical manufacturing plant such as the case company? By discussing and clarifying many of the practical activities and processes in production control with a theoretical framework, the research shows that understanding such a framework can give managers valuable insights and perspectives for the development of processes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Planning and Scheduling Optimization

Although planning and scheduling optimization have been explored in the literature for many years now, it still remains a hot topic in the current scientific research. The changing market trends, globalization, technical and technological progress, and sustainability considerations make it necessary to deal with new optimization challenges in modern manufacturing, engineering, and healthcare systems. This book provides an overview of the recent advances in different areas connected with operations research models and other applications of intelligent computing techniques used for planning and scheduling optimization. The wide range of theoretical and practical research findings reported in this book confirms that the planning and scheduling problem is a complex issue that is present in different industrial sectors and organizations and opens promising and dynamic perspectives of research and development

A Digital Twin Framework for Production Planning Optimization: Applications for Make-To-Order Manufacturers

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing the limitations in accurately representing production environments. The consequence has been a serious gap between theory advancement and industry practice. The major goal of this dissertation is to develop a framework that allows for practical testing, evaluation, and implementation of new approaches for seamless industry adoption. We develop this framework as a modular software package and emphasize the practicality and configurability of the framework, such that minimal modelling effort is required to apply the framework to a multitude of optimization problems and manufacturing systems. Throughout this dissertation, we emphasize the importance of the underlying scheduling problems which provide the basis for additional operational decision making. We focus on the computational evaluation and comparisons of various modeling choices within the developed frameworks, with the objective of identifying models which are both effective and computationally efficient. In Part 1 of this dissertation, we consider a class of Production Planning and Execution problems faced by job shop manufacturing systems. In Part 2 of this dissertation, we consider a class of scheduling problems faced by manufacturers whose production system is dominated by a single operation

Personal mobile grids with a honeybee inspired resource scheduler

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The overall aim of the thesis has been to introduce Personal Mobile Grids (PMGrids) as a novel paradigm in grid computing that scales grid infrastructures to mobile devices and extends grid entities to individual personal users. In this thesis, architectural designs as well as simulation models for PM-Grids are developed. The core of any grid system is its resource scheduler. However, virtually all current conventional grid schedulers do not address the non-clairvoyant scheduling problem, where job information is not available before the end of execution. Therefore, this thesis proposes a honeybee inspired resource scheduling heuristic for PM-Grids (HoPe) incorporating a radical approach to grid resource scheduling to tackle this problem. A detailed design and implementation of HoPe with a decentralised self-management and adaptive policy are initiated. Among the other main contributions are a comprehensive taxonomy of grid systems as well as a detailed analysis of the honeybee colony and its nectar acquisition process (NAP), from the resource scheduling perspective, which have not been presented in any previous work, to the best of our knowledge. PM-Grid designs and HoPe implementation were evaluated thoroughly through a strictly controlled empirical evaluation framework with a well-established heuristic in high throughput computing, the opportunistic scheduling heuristic (OSH), as a benchmark algorithm. Comparisons with optimal values and worst bounds are conducted to gain a clear insight into HoPe behaviour, in terms of stability, throughput, turnaround time and speedup, under different running conditions of number of jobs and grid scales. Experimental results demonstrate the superiority of HoPe performance where it has successfully maintained optimum stability and throughput in more than 95% of the experiments, with HoPe achieving three times better than the OSH under extremely heavy loads. Regarding the turnaround time and speedup, HoPe has effectively achieved less than 50% of the turnaround time incurred by the OSH, while doubling its speedup in more than 60% of the experiments. These results indicate the potential of both PM-Grids and HoPe in realising futuristic grid visions. Therefore considering the deployment of PM-Grids in real life scenarios and the utilisation of HoPe in other parallel processing and high throughput computing systems are recommended

A study of interactive control scheduling and economic assessment for robotic systems

A class of interactive control systems is derived by generalizing interactive manipulator control systems. Tasks of interactive control systems can be represented as a network of a finite set of actions which have specific operational characteristics and specific resource requirements, and which are of limited duration. This has enabled the decomposition of the overall control algorithm simultaneously and asynchronously. The performance benefits of sensor referenced and computer-aided control of manipulators in a complex environment is evaluated. The first phase of the CURV arm control system software development and the basic features of the control algorithms and their software implementation are presented. An optimal solution for a production scheduling problem that will be easy to implement in practical situations is investigated