Mathematische Optimierung Grafischer Modelle Mit Der Software AURELIE

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Mathematische Optimierung Grafischer Modelle Mit Der Software AURELIE Strategische Planung technischer Kapazität in komplexen Produktionssystemen: mathematische Optimierung grafischer Modelle mit der Software AURELIE Dissertation zur Erlangung des akademischen Grades Doktoringenieur (Dr.-Ing.) Herr Dipl.-Inf. Christian Andreas Hochmuth, MBA geboren am 18. Mai 1984 in Chemnitz Fakultät für Informatik an der Technischen Universität Chemnitz Gutachter: Prof. Dr.-Ing. Martin Gaedke Prof. em. Dr. oec. Dr. rer. nat. habil. Peter Köchel Prof. Dr.-Ing. Jörg Lässig Tag der Verteidigung: 27. Februar 2020 Bibliografische Information Hochmuth, Christian Andreas. 2020. »Strategische Planung technischer Kapazität in komplexen Produktionssystemen: mathematische Optimierung grafischer Modelle mit der Software AURELIE« Dissertation, Technische Universität Chemnitz, Fakultät für Informatik. 231 Seiten, 70 Abbildungen, 12 Tabellen, 19 Algorithmen, 216 Quellen. Für Alexandra und Lasse Vorwort Die vorliegende Dissertation ist an der Fakultät für Informatik der Technischen Universität Chemnitz entstanden. Im Mittelpunkt dieser Arbeit steht das Grundkonzept der Software AURELIE, die im Zuge der Promotion bei der Bosch Rexroth AG entwickelt und eingeführt wurde. Die Veröffentlichung markiert den Schlusspunkt eines langen Prozesses und bietet Gelegenheit für einen Rückblick. Der Natur einer externen Promotion entsprechend haben mich Personen aus Forschung und Praxis auf diesem Weg begleitet. Zunächst möchte ich meine Förderer aus dem universitären Umfeld hervorheben. Ihre wissenschaftliche Anleitung half mir, die in der Dissertation vorgestellten Ideen und Konzep- te in publikationsgerechter Form zu strukturieren. Ich danke Prof. Dr.-Ing. Martin Gaedke für wertvolle Hinweise und für die Bereitschaft, die Betreuung der Arbeit zu übernehmen. Ebenso gilt mein Dank Prof. em. Dr. oec. Dr. rer. nat. habil. Peter Köchel, der mein Promoti- onsvorhaben von Beginn an fachlich und persönlich unterstützt hat. Des Weiteren danke ich Prof. Dr.-Ing. Jörg Lässig für die Begutachtung und für die lehrreiche Zusammenarbeit bei der Erstellung von Veröffentlichungen. Ein wichtiges Merkmal dieser Arbeit ist, dass der entwickelte Lösungsansatz erfolgreich in der Praxis umgesetzt werden konnte. Hieran haben meine Betreuer auf der Seite der Bosch Rexroth AG sowie die Fachexperten im Kollegenkreis großen Anteil. In diesem Zusammen- hang danke ich Dr.-Ing. Michael Sauter und Dr.-Ing. Bernd A. Müller für ihre Mentorenschaft und das Öffnen vieler verschlossener Türen. Alessandro Battino und Torsten Wassum danke ich für ihre Unterstützung bei der Spezifikation, dem Test und der Einführung der Software. Lukas Hahmann gilt mein Dank für seinen Einsatz im Rahmen von Anwenderschulungen und der technischen Dokumentation der Algorithmen. Darüber hinaus sei allen in der gebotenen Kürze nicht genannten Kollegen, Familienmit- gliedern und Freunden mein tiefer Dank versichert. Düsseldorf, im Mai 2020 Christian A. Hochmuth v Referat Aktuelle Entwicklungen erfordern die Flexibilisierung von Produktionssystemen, wodurch die Komplexität insbesondere in der variantenreichen Serienfertigung steigt. Als Folge beste- hen erhebliche Herausforderungen darin, die technische Kapazität in solchen komplexen Produktionssystemen effizient, transparent und flexibel zu planen. Um diese Herausforde- rungen zu bewältigen, wurde im Zusammenhang mit dieser Arbeit die Software AURELIE entwickelt und erfolgreich an den Standorten der Bosch Rexroth AG eingeführt. Im Folgen- den wird das Grundkonzept der Software dargelegt, welches sich aus den kalkulatorischen Grundlagen und den entwickelten Kernalgorithmen zusammensetzt. Im Fokus stehen aus strategischer Sicht die maximalen Kapazitäten, die minimalen In- vestitionen zur Herstellung der geplanten Stückzahlen und die optimale Auslastung der Produktionsanlagen. Den Rahmen für die Optimierung der Planungsziele bildet ein System von Wertströmen, welches alle Prozesse zur Fertigung und Montage von Produkten an einem Standort umfasst. Die Komplexität resultiert aus der Struktur solcher Systeme, beruhend auf der rekursiven Verknüpfung von Prozessschritten und der mehrfachen Belegung von Produk- tionsanlagen. Diese Verknüpfungen und die begrenzte Auslastung der Produktionsanlagen führen in der Planung zu wechselseitigen Abhängigkeiten. Um die angesprochenen Abhängigkeiten zu berücksichtigen, werden in Unternehmen Ansätze verfolgt, die sich in ein Spektrum zwischen zwei unterschiedlichen Fällen einordnen lassen: Im ersten Fall werden einfache Modelle erstellt, die nur sehr begrenzt die Komple- xität abbilden, jedoch von allen Beteiligten im Planungsprozess verstanden werden. Im zweiten, gegenteiligen Fall werden in aufwändiger Arbeit umfangreiche Modelle entwickelt, die zwar der Komplexität Rechnung tragen, allerdings nicht verständlich sind. Der Grund dafür ist, dass dem Planer die Aufgabe aufgebürdet wird, die Abhängigkeiten in mathemati- sche Ausdrücke zu überführen. Als Konsequenz ist in der Praxis zu beobachten, dass sich Vollständigkeit und Verständlichkeit der Modelle ausschließen. Zur Lösung dieses Zielkonflikts wird ein softwaregestützter Workflow vorgeschlagen, wel- cher auf der neuen Software AURELIE beruht. Im ersten Schritt erstellt der Planer mit Hilfe der Software ein grafisches Modell, das nicht nur verständlich ist, sondern auch das Sys- tem in seiner Komplexität vollständig widerspiegelt. Im zweiten, automatisch ablaufenden Schritt validiert die Software das grafische Modell und transformiert dieses in ein mathe- matisches Modell. Im dritten, ebenso automatisierten Schritt optimiert die Software das mathematische Modell, worauf der Planer das Modell anpasst und der Workflow von Neu- em beginnt. Das Ergebnis dieser Teilautomatisierung ist eine signifikante Steigerung der Effizienz, Transparenz und Flexibilität im Planungsprozess. Im Zuge einer Systemanalyse werden zuerst Struktur und Schnittstelle eines Systems von Wertströmen beschrieben, wofür ein spezifischer mathematischer Formalismus erarbeitet wird. Im Anschluss werden die kalkulatorischen Grundlagen dargelegt und die Anforde- rungen an eine Software abgeleitet, welche sich zur Modellierung und Optimierung eines solchen Systems eignet. Mit der Bewertung des Stands der Technik folgt der Beleg, dass zum Zeitpunkt der Betrachtung keine geeignete Software existierte. Als ein wesentlicher Beitrag neben der Systemanalyse werden danach die Kernalgorithmen zur grafischen Modellierung, Modelltransformation und mathematischen Optimierung beschrieben. vii Abstract Recent developments require a transition to more flexible production systems, which causes higher complexity, especially in the case of series production with a great number of variants. As a result, the efficient, transparent and flexible planning of the technical capacity in such complex production systems represents considerable challenges. In order to overcome these challenges, the software AURELIE was developed in the context of writing this dissertation and successfully implemented at the locations of Bosch Rexroth AG. In the following, the fundamental concept of the software is described, which comprises the foundations with respect to calculations and the developed core algorithms. From a strategic perspective, the focus lies on the maximal capacities, the minimal invest- ments which are required to produce the planned quantities and the optimal utilization of the production facilities. The scope for optimizing the planning objectives is defined by a system of value streams, which encompasses all processes for the manufacturing and assembly of products at a specific location. The complexity results from the structure of such systems, which is based on the recursive combination of process steps and the multiple allocation of production facilities. These combinations and the limited utilization of the production facilities lead to interdependencies in the planning. To account for the aforementioned interdependencies, companies follow approaches which can be classified along a spectrum between two distinct cases: In the first case, simple models are being created, which are very limited regarding the mapping of the complexity, but which are understood by all participants involved in the planning process. In the second, contrary case, extensive efforts are made to develop comprehensive models, which take the complexity into account, but which are not understandable. The underlying reason is that the task to transform the interdependencies into mathematical expressions is imposed upon the planner. As a consequence, it can be observed in practice that completeness and understandability of the models are mutually exclusive. With the aim to solve this conflict of objectives, a software-based workflow is proposed, which is supported by the newly developed software AURELIE. In the first step, the planner is aided by the software in creating a graphical model, which is not only understandable, but also reflects the system completely with respect to its complexity. In the second step, which is executed automatically, the software validates the graphical model and transforms it into a mathematical model. In the third step, which is automated as well, the software optimizes the mathematical model, whereupon the planner adjusts the model and the workflow starts from the beginning. The outcome of this partial automation is a significant improvement of efficiency, transparency and flexibility in the planning process. In the course of a system analysis, firstly the structure and the interface of a system of value streams are described, utilizing a specifically
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