Moritz Glatt

Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau | TUK · Lehrstuhl für Fertigungstechnik und Betriebsorganisation

Noise monitoring is important in the context of manufacturing because it can help maintain a safe and healthy workspace for employees. Current approaches for noise monitoring in manufacturing are based on acoustic sensors, whose measured sound pressure levels (SPL) are shown as bar/curve charts and acoustic heat maps. In such a way, the noise emiss...

Studies affecting manufacturing system resilience have been of rising interest in recent years due to increased rates of naturally caused, and socio-economic disturbances. The non-linearity in modern manufacturing systems, attributed to a host of internal and external complexities in structure and operations cannot be properly modeled using convent...

An efficient production planning and control is inevitable for the economic operation of a manufacturing system. As an essential part of production planning and control, process scheduling aims to assign processes to the available resources of a manufacturing system under consideration of its objectives. This forms an optimization problem also know...

Flexible Job Shop Scheduling (FJSSP) is a challenging optimization problem with multiple conflicting objectives used to model and compute real-world process scheduling tasks. In order for a manufacturing system to remain competitive, it is necessary to compute such optimization problems quickly and efficiently. The limitations of conventional optim...

Hybrid models which combine data-driven and physics-based models have emerged as a trend in manufacturing for improving process efficiency, reducing costs, and enhancing product quality. Hybrid models can deliver greater performance benefits than either model by itself. As sustainability becomes an increasingly important issue for the manufacturing...

Flexible Job Shop Scheduling (FJSSP) is a challenging optimization problem with multiple conflicting objectives used to model and compute real-world process scheduling tasks. In order for a manufacturing system to remain competitive, it is necessary to compute such optimization problems quickly and efficiently. The limitations of conventional optim...

The 5G mobile communication standard can potentially meet the networking requirements for different industrial use cases simultaneously due to the promised low latency, high bandwidth, and high device density while providing a high quality of service. These capabilities enable the realization of digital twins (DTs) that are based on edge computing...

Die Elektromobilität ist ein wichtiger Baustein für eine klimafreundliche Mobilität. Elektrofahrzeuge, insbesondere in Verbindung mit regenerativ erzeugtem Strom, können deutlich zu einer Reduktion der CO 2 -Bilanz des Mobilitätssektors beitragen. Im Rahmen einer ganzheitlichen Betrachtung gilt es jedoch, nicht nur das Fahrzeug selbst, sondern auch...

The cellular network standard 5G meets the networking requirements for different industrial use cases due to the advantages of low latency, high bandwidth, and high device density while providing a very good quality of service. These capabilities enable the realization of wireless digital twins (DTs), a key element of future cyber-physical producti...

The automated tracking of objects in factories via real-time locating systems (RTLS) is gaining increased attention due to its improved availability, technical sophistication, and most of all, its plethora of applications. The tracking of workpieces through their production process, for example, unlocks a detailed understanding of timings, patterns...

Additive manufacturing (AM) is suitable for designing and producing complex components that are difficult or impossible to manufacture with conventional manufacturing processes. To ensure the design benefits of AM, novel design approaches such as structural topology optimization and cellular structure design are widely used and bring up the researc...

The generation of an optimized factory layout is a central element of the factory planning process. The generated factory layout predefines multiple characteristics of the future factory, such as the operational costs and proper resource allocations. However, manual layout planning is often time and resource-consuming and involves creative processe...

The need for energy-efficient manufacturing technologies is growing due to the increasing pressure from climate change, consumers, and regulations. Additive manufacturing is claimed to be a sustainable manufacturing technology, especially for individualized products and small batches. To include the energy demand in the decision-making process on w...

Gradient infill design (GID) is important in design for additive manufacturing (AM) because it can improve the strength of filled structures. Conventional GID methods aim at product design and use mathematics to formulate the infill geometry; thus, they are complex and require a high level of expertise from the designer. In this work, we propose a...

An efficient production planning and control is inevitable for the economic operation of a manufacturing system. As an essential part of production planning and control, process scheduling aims to assign processes to the available resources of a manufacturing system under consideration of its objectives. This forms an optimization problem also know...

The unit process life cycle inventory is a modeling approach to estimate the energy demand and resource requirements of a unit process. Thus, a model of the unit process life cycle inventory for a specific manufacturing process can be used for quantifying the environmental impacts of specific products manufactured by that process. Within the approa...

Factory layout planning aims at finding an optimized layout configuration under consideration of varying influences such as the material flow characteristics. Manual layout planning can be characterized as a complex decision-making process due to a large number of possible placement options. Automated planning approaches aim at reducing the manual...

Factory layout planning aims at finding an optimized layout configuration under consideration of varying influences such as the material flow characteristics. Manual layout planning can be characterized as a complex decision-making process due to a large number of possible placement options. Automated planning approaches aim at reducing the manual...

Especially in manufacturing systems with small batches or customized products, as well as in remanufacturing and recycling facilities, there is a wide variety of part types that may be previously unseen. It is crucial to accurately identify these parts based on their type for traceability or sorting purposes. One approach that has shown promising r...

Resilience describes the capability of manufacturing systems to resist disturbances while minimizing the loss of revenue or productivity. In order to achieve robustness against disturbances under consideration of operational costs, multiple planning parameters and strategies must be taken into account simultaneously. This leads combinatorial optimi...

The COVID-19 pandemic and crises like the Ukraine-Russia war have led to numerous restrictions for industrial manufacturing due to interrupted supply chains, staff absences due to illness or quarantine measures, and order situations that changed significantly at short notice. These influences have exposed that it is crucial to address the issue of...

Laser-based powder bed fusion of metals (PBF-LB/M) is an additive manufacturing (AM) process for producing metal components. In current works, the simulation of the temperature gradient (TG) of PBF-LB/M is done by solving partial differential equations (PDEs) that describe the heat transfer between a laser beam and a powder bed. However, solving PD...

Industrial robots are widely used in manufacturing systems. The places that humans share with robots are called human-robot collaboration (HRC) workspaces. To ensure the safety in HRC workspaces, a collision-avoidance system is required. In this paper, we regard the collision-avoidance as a problem during the robot action trajectory design and prop...

Reducing energy costs is an emerging aspect in the research on the economic and environmental dimensions of manufacturing systems. The share of electricity cost accounts for approximately 60 % of the total energy cost of a manufacturing system, whereas the share of oil, coal, and gas accounts for the remaining 40 %. The electricity cost is dependen...

Quantum Annealing (QA) is a metaheuristic for solving optimization problems in a time-efficient manner. Therefore, quantum mechanical effects are used to compute and evaluate many possible solutions of an optimization problem simultaneously. Recent studies have shown the potential of QA for solving such complex assignment problems within millisecon...

Human cyber-physical production systems (HCPS) - as an extension of cyber-physical production systems (CPPS) - focus on the human being in the system and the development of socio-technical systems. Humans and therefore anthropogenic behavior have to be integrated into the manufacturing system and its processes. Due to the shift towards customized p...

Abstract The value stream method is a widely used tool for reducing the costs and waste of a manufacturing company, which however requires substantial manual efforts. Due to the widespread implementation of digital technologies in the context of Industry 4.0 into production systems and the accompanying collection of data, a large amount of informat...

Factory layout planning is a recurring and important process since an inadequately planned layout can significantly impede the operation of a factory. A time-efficient and automated planning method is especially important as shortened product lifecycles, changing technologies, and market requirements lead to changes in the production program, which...

The new cellular network standard 5G meets the networking requirements for many industrial use cases due to the advantages of low latency, high bandwidth, and high device density while providing a very good quality of service. These capabilities enable the wireless realization of digital twins (DT), a key element of cyber-physical production system...

The stunning success of deep image classification approaches relies heavily on huge, labeled datasets based on real-world images. Nonetheless, the latest generation of neural network architectures provides pre-trained models that allow the training and classification of new classes with only minor example data. In most application use cases, the pr...

Inadequately planned factory layouts can lead to higher operational costs. The planning process is time-consuming and multiple planning parameters must be considered simultaneously, leading to large solution spaces. Automated planning approaches can support the planning team in the early phases of layout planning by generating layout variants that...

Abstract Tool wear and metal removal rate significantly determine the production costs of a machined component. Decision support for tool change based on machine learning (ML) offers great potential to use tools more efficiently. However, ML models are usually not readily applicable to real, variable machining processes. The use of transfer learnin...

Der neue Mobilfunkstandard der fünften Generation (5G) bietet weitreichende Potenziale für die deutsche Wirtschaft. Insbesondere die Industrie profitiert durch den Einsatz von 5G. Prozesse können leichter digitalisiert und flexibler gestaltet werden, das Arbeiten wird mobiler und durch den Einsatz von augmentierter und virtueller Realität effizient...

The new cellular network standard 5G is characterized by greater bandwidth, lower latencies, higher reliabilities, and a higher number of recipients per cell compared to industrial 4G or wireless networks. This makes 5G a promising technology in latency-critical applications in manufacturing, such as machine tool control systems. Today, machine too...

Manufacturing systems need to be highly adaptive and flexible to meet heterogeneous customer requirements and require fast and accurate object identification. This paper presents the implementation of deep learning for the object detection in a factory in which images of machines are used to train four models. For each model, three trials with diff...

Die computergestützte Erweiterung physischer Objekte durch zusätzliche Informationsdarstellung birgt große Potenziale im industriellen Kontext. Diese als Augmented Reality (AR) bezeichnete Technologie benötigt hohe Rechenleistungen zur Verarbeitung der zur Verfügung gestellten Informationen und eine geringe Latenz zur Vermeidung von bewegungsbe din...

Das auf quantenmechanischen Prozessen basierende Quanten-Annealing ist eine Technologie, die es erlaubt, Energieminimierungsprobleme effizient zu lösen. Durch die Formulierung von Reihenfolgeplanungsproblemen als Energieminimierungsprobleme bieten sich Potenziale einer zeiteffizienten Lösung mittels Quanten-Annealing. Gegenstand dieses Beitrags ist...

Additive manufacturing (AM) processes are characterized by a high degree of flexibility regarding the manufacture of complex geometries due to the tool-free layerwise build-up principle. A well-established AM method is Fused Deposition Modeling (FDM), in which the part is produced by melting thermoplastic material in an extrusion process. However,...

4D printing is a term for the additive manufacturing (AM) processes, in which shape-memory materials are used. A 4D printed component is capable of changing its shape to another, which implies that the transformation over time is regarded as the fourth dimension in addition to x, y, and z dimensions in AM. A common material type for 4D printing is...

Bei der Ermittlung von Vorgangsfolgen innerhalb der Arbeitsplanung wird auf Erfahrungswissen von Fachkräften und weitere Hilfsmittel wie Unterlagen, Richtlinien und Arbeitspläne ähnlicher Produkte zurückgegriffen. Demzufolge enthalten erstellte Arbeitspläne implizites Wissen, dessen Extraktion und Nutzung das Potenzial zur Beschleunigung der Vorgan...

The concept of digital twin is based on the linkage of a physical system with a digital model-based representation and shows numerous potentials in additive manufacturing (AM). The existing approaches related to digital twins of AM mainly focus on the process, machine, and factory levels to monitor and optimize the process and system performance of...

Mit der fortschreitenden Digitalisierung wachsen die Forderungen nach der Ausschöpfung des Potentials der dabei erhobenen Daten. Hierfür haben die Methoden des Maschinellen Lernens ihre Praxistauglichkeit bewiesen. Jedoch ergeben sich bei der Anwendung dieser Technologie in Produktionssystemen mit hohem Variantenreichtum und kleinen Se- rien, viels...

Factory layout planning is a recurring and time consuming process since multiple often conflicting planning objectives have to be considered simultaneously. Inadequately planned layouts however can significantly impede the operation of a factory. Recent studies from other disciplines have shown the potential of reinforcement learning to solve compl...

During cryogenic turning of metastable austenitic stainless steels, a deformation-induced phase transformation from γ-austenite to α’-martensite can be realized in the workpiece subsurface, which results in a higher microhardness as well as in improved fatigue strength and wear resistance. The α’-martensite content and resulting workpiece propertie...

Quantification and analysis of manufacturing costs in additive manufacturing (AM) are important research tasks, since materials and machines for AM are relatively expensive. To enable the cost estimation in AM, a number of studies have focused on the development of cost estimation software tools for AM. However, these studies mainly focused on sing...

Manufacturing companies aim at ensuring ecological sustainability within their value-adding processes and sustainability indicators like CO2 emissions associated to a product are becoming important selling points for customers. In consequence, manufacturers investigate and measure their manufacturing processes in order to be able to provide respect...

Additive manufacturing (AM) is seen as a promising technology to improve the resource efficiency and environmental performance in manufacturing systems. However, recent studies have shown that the ecological advantages of AM are dependent on the design of the manufactured parts. This leads to the requirement of the implementation of eco-design for...

Various triggers in manufacturing operations lead to engineering changes, such as the conversion of a machine or changes in the factory layout. In companies, the priority is often to avoid engineering changes as they are time-intensive and lead to change costs. If changes cannot be avoided, the implementation must be simplified and accelerated as m...

To ensure that technical products are traceable, they must be clearly identifiable. A novel concept for rendering components made of metastable austenitic stainless steel traceable and thus counterfeit-proof is presented. The characteristic deformation-induced phase transformation of this material group and the associated changes in permeability ar...

Within the Industry 4.0 perspective, this paper investigates the fusion of two theoretical models with different nature, in order to offer a better simulation tool for the industrial sector of polished stoneware tiles. A model based on physical principle, composed by the set of equations that rules the kinematics equations performed by the abrasive...

Kurzfassung Digitale Zwillinge bieten vielfältige Potenziale in Produktionssystemen. Die zielgerichtete Planung und Implementierung basieren auf dem jeweiligen Anwendungsfall und den dabei einzubeziehenden Informationen, Modellen und Systemen. Zur Vereinfachung dieser Prozesse wird in diesem Beitrag ein Rahmenwerk aufgezeigt, welches die eindeutige...

Kurzfassung Digitale Zwillinge bilden Eigenschaften und Zustände von realen Systemen digital ab. Dabei analysieren sie auf Basis relevanter Daten und Modelle das reale System und geben optimierte Daten an das reale System zurück. Grundlage hierfür sind physikalische und datengetriebene Modelle, welche jeweils charakteristische Vor- und Nachteile au...

Cyber-physical production systems enable adaptivity and flexibility when manufacturing customized products in small batches. Due to varying routes and a high variance of workpieces, material flows in cyber-physical production systems can get highly complex, which can lead to physically induced disturbances that can result in accidents or decreased...

Additive manufacturing (AM) technologies are providing promising solutions to production of unique parts at reduced material and energy consumptions. However, recent studies show that the sustainable advantage of AM is not always achieved. For ensuring the sustainability of the AM processes, quantification and assessment of the levels of resource c...

Additive manufacturing (AM) has been considered as a promising technology with higher resource efficiency and better ecological benefits in production systems. However, recent works have shown that the ecological benefits of AM are sensitive to the parameters in operation. If the parameters are not designed appropriately, the ecological performance...

Current machine learning techniques show a high degree of maturity and can be implemented for applications in manufacturing. In this context, using machine learning to investigate the relationship between process parameters and process performance allows an optimization of production systems. Conventional methods to analyze the life time of a manuf...