Christian Leyh, Wibke Kusturica, Sarah Neuschl, Christoph Laroque • Industrie 4.0 Management 2022(6)

Neue Wertschöpfungsprozesse und Geschäftsmodelle, die durch umfangreiche Datennutzung und überbetriebliches Datenteilen geprägt sind, werden für Unternehmen immer wichtiger. Viele Barrieren und Hemmnisse verlangsamen jedoch vor allem für den Mittelstand den Weg zu einer datenbasierten Wertschöpfung. Den Unternehmen fehlt es an konkreten Datennutzungs- und Umsetzungsideen und/oder an Digitalisierungs- und Datenanalysekompetenzen. Dadurch bestehen ungenutzte Wertschöpfungspotenziale in Unternehmen – selbst wenn bereits Daten vorhanden sind. Mit diesem Beitrag werden durch die Beschreibung eines Reallabors mit Realexperimenten Unterstützungsmöglichkeiten für Unternehmen aufgezeigt, um den eigenen „Datenschatz“ zu identifizieren und zu heben.

ResearchGate

Majsa Ammouriova, Madlene Leißau, Javier Panadero, Christin Schumacher, Christoph Laroque, Angel A. Juan • Winter Simulation Conference 2022, Singapore

Compared to other industries, production systems in semiconductor manufacturing have an above-average level of complexity. Developments in recent decades document increasing product diversity, smaller batch sizes, and a rapidly changing product range. At the same time, the interconnections between equipment groups increase due to rising automation, thus making production planning and control more difficult. This paper discusses a hybrid flow shop problem with realistic constraints, such as stochastic processing times and priority constraints. The primary goal of this paper is to find a solution set (permutation of jobs) that minimizes the production makespan. The proposed algorithm extends our previous work by combining biased-randomization techniques with a discrete-event simulation heuristic. This simulation-optimization approach allows us to efficiently model dependencies caused by batching and by the existence of different flow paths. As shown in a series of numerical experiments, our methodology can achieve promising results even when stochastic processing times are considered.

ResearchGate

Wibke Kusturica, Christoph Laroque • Innovation und Kooperation auf dem Weg zur All Electric Society

Der deutsche Maschinen- und Anlagenbau ist durch kleine und mittelständische Unternehmen geprägt und charakterisiert den Industriestandort Deutschland. Die Unternehmen befinden sich im Spannungsfeld zwischen kundenindividueller Einzelfertigung in höchster Qualität auf der einen Seite und der Effizienzeinhaltung in Bezug auf nachhaltig erfolgreiches Wirtschaften und ressourcenschonende Produktionsverfahren auf der anderen Seite. Zukünftig muss die Branche mehr noch als heute steigende Anforderungen an Ressourceneffizienz und Konnektivität ihrer Produkte realisieren, um wettbewerbsfähig zu bleiben und sich auf einem globalen Markt zu behaupten. Dieser Beitrag stellt Forschungsergebnisse aus dem Bereich des Projektmanagements im Maschinen- und Anlagenbau vor und zeigt die Potentiale durch datengestützte Werkzeuge zur Entscheidungsunterstützung auf. Mit Hilfe fortschrittlicher Business-Analytics-Methoden wird ein datenbasiertes Projektmanagement konzipiert, um die unternehmerischen Wertschöpfungsprozesse zu projektieren und zu terminieren. Die Ergebnisse werden genutzt, um die Prozesse planbarer und effizienter zu machen. In einem langfristigen Sinne bietet die digitale Verfügbarkeit der Informationen die Chance, Wissen aus vergangenen Projekten zur Verbesserung der Planung sowie der Geschäftsprozesse zu verwenden.

ResearchGate

Christoph Laroque, Madlene Leißau, Wolfgang Scholl, Germar Schneider, Patrick Preuß • 26. ASIM Symposium Simulationstechnik, Vienna (Austria)

Manufacturing companies are experiencing many chal-lenges regarding customer-oriented and on-time pro-duction, especially in the context of an intensified global business and while advancing the digital transfor-mation. Accordingly, the ongoing development and deployment of Industry 4.0 solutions for customisable products in small batch sizes, not only pose new prob-lems for work preparation, but also for operative pro-duction planning in connection with high cost, time, and quality pressure. Modern, complex, and highly auto-mated production systems (in this case from the semi-conductor domain) must be operated close to an opti-mal operating state to be economically reasonable. Promised delivery dates and throughput times specified in contracted service agreements must be ensured and require a permanent and effective adjustment of pro-duction planning and control in daily execution. All other general conditions of an economic production remain unchanged. Today, the question of whether the production target is realistic and whether all promised delivery dates are met are still answered with rather simple backward-oriented approaches, mostly without considering uncertainties, stochastic behaviour of the manufacturing system or alternatives that arise during operation. As shown in previous publications by the authors, these questions can be answered in more de-tail and more resilient using a backward-oriented dis-crete event-based simulation approach (SimBack). This article presents additional findings. The results show and deepen the impression, that the SimBack-approach can successfully solve scheduling questions for custom-er-specific orders in a real-world environment.

ResearchGate

Christoph Laroque, Madlene Leißau, Wolfgang Scholl, Germar Schneider • CIRP CMS 2022, Lugano (Switzerland)

Manufacturing companies are experiencing many challenges with regard to customer-oriented and on-time production, especially in the context of an intensified global business and while advancing the digital transformation. Accordingly, the ongoing development and deployment of Industry 4.0 solutions for customisable products in small batch sizes, not only pose new problems for work preparation, but also for operative production planning in connection with high cost, time and quality pressure. Modern, complex and highly automated production systems (in this case from the semiconductor domain) must be operated close to an optimal operating state in order to be economically reasonable. Promised delivery dates and throughput times specified in contracted service agreements must be ensured and require a permanent and effective adjustment of production planning and control in daily execution. All other general conditions of an economic production remain unchanged. Today, the question of whether the production target is realistic and whether all promised delivery dates are met are today still answered with rather simple backward-oriented approaches, mostly without taking into account uncertainties, stochastic behaviour of the manufacturing system or alternatives that arise during operation. As shown in previous publications, these questions can be answered in more detail and more resilient using a backward-oriented discrete event-based simulation approach (SimBack). This article presents additional findings. The results show and deepen the impression, that the SimBack-approach can be successfully solve scheduling questions for customer-specific orders in a real-world environment.

ResearchGate

Christoph Laroque, Madlene Leißau, Pedro Copado, Christin Schumacher, Javier Panadero, Angel A. Juan • 26. Algorithms 15(2)

Based on a real-world application in the semiconductor industry, this article models and discusses a hybrid flow shop problem with time dependencies and priority constraints. The analyzed problem considers a production where a large number of heterogeneous jobs are processed by a number of machines. The route that each job has to follow depends upon its type, and, in addition, some machines require that a number of jobs are combined in batches before starting their processing. The hybrid flow model is also subject to a global priority rule and a “same setup” rule. The primary goal of this study was to find a solution set (permutation of jobs) that minimizes the production makespan. While simulation models are frequently employed to model these time-dependent flow shop systems, an optimization component is needed in order to generate high-quality solution sets. In this study, a novel algorithm is proposed to deal with the complexity of the underlying system. Our algorithm combines biased-randomization techniques with a discrete-event heuristic, which allows us to model dependencies caused by batching and different paths of jobs efficiently in a near-natural way. As shown in a series of numerical experiments, the proposed simulation-optimization algorithm can find solutions that significantly outperform those provided by employing state-of-the-art simulation software.

ResearchGate

Sigrid Wenzel, Deike Gliem, Christoph Laroque, Wibke Kusturica • Industrie 4.0 Management 38(3)

Die Planung von Logistikprozessen und ihre effiziente Umsetzung sind für den kundenindividuellen Anlagenbau wettbewerbsentscheidend. Auf der Baustelle wird die Erfassung von Logistikdaten jedoch häufig vernachlässigt, sodass dem Projektplaner keine zuverlässige Datenbasis vorliegt. Damit einhergehende Informationslücken lassen sich mit Hilfe eines Digitalen Schattens schließen, der logistikrelevante Daten (teil-)automatisch sammelt, persistent speichert und dem Projektmanagement zur Verfügung stellt. In diesem Beitrag werden als erste wichtige Ergebnisse eines Forschungsvorhabens Informations- und Kommunikationsprozesse in der Baustellenlogistik beschrieben und deren Notwendigkeit für den Aufbau und die Nutzung dieses Digitalen Schattens erläutert.

ResearchGate

Deike Gliem, Ulrich Jessen, Sigrid Wenzel, Wibke Kusturica, Christoph Laroque • Logistics Research 15(5)

Due to severe global competition, the project management process for one-of-a-kind production must aim for better risk management and higher efficiency. Despite being critical in order to forecast the duration of logistics processes, intra-enterprise knowledge, historical data from past projects as well as simulation models are not sufficiently utilized in today´s practices. To improve the project planning for one-of-a-kind production, a systematic modeling concept and a technical solution approach are developed, which are based on logistics reference processes and an ontology, as a major part of the overall systematic. This paper focuses on the development of the basic structure of the ontology. A use case applies the ontology within a project management toolset to highlight the potentials for process duration forecasting in project management.

ResearchGate