Jochen Deuse

• Professor
• TU Dortmund University

Increasingly complex products and production technology, as well as customer requirements, pose major challenges for the manufacturing industry. Data-based techniques offer new possibilities for problem-solving but also bring new demands on operational IT architectures as well as competences and procedures. The article addresses future challenges o...

The ergonomic configuration of processes is becoming increasingly important, especially considering the changing demographics and increasing shortage of skilled workers. Exoskeletons are widely discussed as a means of protecting employees from overstraining at the level of personal protective measures. The field of industrial exoskeletons research...

This paper presents a comprehensive study on anomaly detection in screw connections using supervised machine learning techniques. We introduce a novel, open-source dataset comprising 12,500 time series observations from screw tightening processes, including both normal operations and seven distinct error types related to surface properties. The dat...

The ongoing digitization of online learning resources has led to a proliferation of collaboration platforms for specific areas of application and disciplines. Simultaneously, especially manufacturing companies need to gain and secure knowledge in the field of Industrial Data Science (IDS) and to collaborate with partners to form a competitive value...

Delivery times represent a key factor influencing the competitive advantage, as manufacturing companies strive for timely and reliable deliveries. As companies face multiple challenges involved with meeting established delivery dates, research on the accurate estimation of delivery dates has been source of interest for decades. In recent years, the...

This paper investigates the application of Machine Learning (ML) approaches for anomaly detection in time series data from screw driving operations, a pivotal process in manufacturing. Leveraging a novel, open-access real-world dataset, we explore the efficacy of several unsupervised and supervised ML models. Among unsupervised models, DBSCAN demon...

Dieses Buch schlägt eine Brücke zwischen Theorie und Praxis für das produzierende Gewerbe im Zeitalter der Digitalisierung, der Industrie 4.0 und der Künstlichen Intelligenz. Es ist das Resultat eines vierjährigen Forschungsprojekts, das unter der Leitung des Instituts für Produktionssysteme der Technischen Universität Dortmund und der RapidMiner G...

In diesem Beitrag wird die Anwendung des parallelkinematischen Manipulators Hexaglide in der THT-Bestückung untersucht. Kostengünstige optische und taktile Sensoren ermöglichen präzises Referenzieren und Einstecken von Bauteilen. Eine kraft- und bildgeregelte heuristische Steuerungsstrategie sowie Reinforcement Learning wurden erprobt und die Taugl...

With digitalization and automation, today's economy is undergoing fundamental changes. Organizations are facing increasing complexity and dynamism, coupled with demographic shifts that require changing workforce skills and organizational flexibility. To ensure a sustainable competitive advantage, it is necessary to efficiently deploy employees base...

Das fachgerechte Recycling von ausgedienten Kühlgeräten spielt eine wichtige Rolle beim Schutz der Umwelt und des Klimas. Recyclinganlagen unterliegen regelmäßigen Audits, um die Einhaltung strenger Umweltvorschriften zu gewährleisten. Die Erhebung von prüfungsrelevanten Daten stellt jedoch eine anspruchsvolle und zeitaufwändige Aufgabe dar, da sie...

Zusammenfassung Das BMBF-Forschungsvorhaben AKKORD behandelt die vernetzte und integrierte Anwendung industrieller Datenanalysen für die wertschaffende und kompetenzorientierte Kollaboration in dynamischen Wertschöpfungsnetzwerken. In diesem Kapitel werden die wichtigsten Informationen zum Vorhaben eingeführt. Das übergeordnete Ziel im Forschungsvo...

Zusammenfassung Der Einsatz industrieller Datenanalysen zur Erzeugung von Wissen für eine Unterstützung der Entscheidungsfindung in produzierenden Unternehmen gewinnt zunehmend an Bedeutung. Bisher fehlen umfassende Lösungen, die die diversen Aufgaben zusammenführen und eine systematische sowie zielgerichtete Anwendung von Datenanalysen unterstütze...

Zusammenfassung Seit über einem Jahrzehnt erfährt die Forschungslandschaft in Deutschland einen umfassenden Wandel unter dem Einwirken des als Industrie 4.0 bezeichneten Paradigmenwechsels. In diesem Kapitel wird der Hintergrund der Einflussfaktoren und Maßnahmen vorgestellt, die zur Entstehung des Forschungsvorhaben AKKORD beigetragen haben. Das P...

Zusammenfassung Im BMBF-Forschungsvorhaben AKKORD wurden Werkzeuge entwickelt, die insbesondere kleine und mittelständische Unternehmen dazu befähigen industrielle Datenanalysen wertschöpfend einzusetzen. Im integrierten Referenzbaukasten werden bausteinartige Teillösungen zur Anwendung industrieller Datenanalysen bereitstellt. Entscheidend für die...

Zusammenfassung Methoden und Werkzeuge der industriellen Datenanalyse erweitern das bisherige Methoden- und Kompetenzportfolio des Industrial Engineerings. Der Einsatz von datengetriebenen Entscheidungsunterstützungen in einem Produktionsnetzwerk leistet einen vielversprechenden Beitrag für ein ganzheitliches Produktivitätsmanagement durch das Indu...

Zusammenfassung Dieses Kapitel beschreibt die konzeptionelle und technische Umsetzung eines anschaulichen Anwendungsszenarios für die AKKORD-Plattform. Ziel des umgesetzten Demonstrators ist es, den Nutzen der Plattform-Komponente AI-Toolbox für industrielle Datenanalysen zu veranschaulichen und die Akzeptanz bei Anwendern zu erhöhen. Der Demonstra...

Zusammenfassung Im Anwendungsfall zum datengetriebenen vernetzten Qualitätsmanagement im Forschungsprojekt AKKORD arbeiten Miele, IPS und RapidMiner an der Entwicklung eines modular erweiterbaren und ganzheitlichen Analysesystems auf Basis der im Projekt entwickelten Plattform. Inhaltlich wurden dafür Daten aus dem Bereich der Feldbeobachtung gewäh...

Zusammenfassung In diesem Kapitel wird mit der Prozesskette der industriellen Datenanalyse das zentrale Konzept des Forschungsprojekts AKKORD vorgestellt. Mithilfe der Prozesskette können im Kontext der Industrie 4.0 und der Digitalisierung die Potenziale von Datenanalysen in der industriellen Produktion erschlossen werden. Der AKKORD-Referenzbauka...

Zusammenfassung Datenanalysen müssen für die zielführende Anwendung im industriellen Kontext, insbesondere in kleinen und mittleren Unternehmen, entsprechend mehreren Anforderungen gestaltet sein. Dabei müssen sie vorrangig Wissen zu den jeweiligen Problemstellungen aus Daten generieren und gleichzeitig leicht für Anwender zugänglich sein, die aus...

Zusammenfassung Das Kapitel beschreibt die Umsetzung der Datenakquise am Beispiel des Heizelementschweißens von Kunststoffen an einer Laborschweißanlage sowie an einer industriellen Produktionsanlage. Die Identifizierung der relevanten Datenquellen und die Verknüpfung des Expertenwissens über den Prozess sind Kernbestandteile der Realisierung. Dazu...

The gap between production scheduling theory and practice still persists as theoretical scheduling models do not cover real-world characteristics such as the multidimensional nature of scheduling decisions appropriately. Moreover, the set of objectives used in classical scheduling does not fully capture multidimensional scheduling decisions. This w...

Although industrial robots are predetermined to overtake repetitive and physically demanding assembly tasks of human workforce while delivering constant product quality, their precision comes at high hardware costs. Efficient control strategies make lightweight robotic solutions more attractive to companies with limited resources. This is especiall...

Companies have been adopting lean management for decades to increase productivity, customer satisfaction and profitability. A foundational and powerful tool in lean management is value stream mapping (VSM). VSM is still widely used as a static pen and paper-based tool. However, as industrial processes have become more advanced and digitalized, stat...

Takt work represents a significant risk factor for the development of musculoskeletal complaints and diseases, especially in short-cycle processes. The increased risk results primarily from a permanent uniform load on the musculoskeletal system. Studies on motor variability suggest that an increase in load variation can have positive effects on red...

In recent times, learning by demonstration has seen tremendous progress in robotic assembly operations. One of the most prominent trajectory-level task models applied is Dynamic Movement Primitives (DMP). However, it lacks the ability to tackle complex operations as often encountered in industrial assembly. Augmenting low-level models with a high-l...

A variety of established approaches exist for the detection of dynamic bottlenecks. Furthermore, the prediction of bottlenecks is experiencing a growing scientific interest, quantifiable by the increasing number of publications in recent years. Neglected, on the other hand, is the diagnosis of occurring bottlenecks. Detection methods may determine...

p>The ergonomic configuration of processes is becoming increasingly important, especially considering the changing demographics and increasing shortage of skilled workers. Exoskeletons are widely discussed as a means of protecting employees from overstraining at the level of personal protective measures. The field of industrial exoskeletons researc...

p>The ergonomic configuration of processes is becoming increasingly important, especially considering the changing demographics and increasing shortage of skilled workers. Exoskeletons are widely discussed as a means of protecting employees from overstraining at the level of personal protective measures. The field of industrial exoskeletons researc...

Forgetting effects occur whenever production is interrupted and workers lose previously acquired routine. Existing forgetting models primarily focused on the impacts of production breaks in single-product production environments. Consequently, forgetting models neglected times during which a different product type is produced despite being an impor...

Over the past decades, the world has seen a continuous increase of globalisation and interconnectedness – in part supported by advances in digital communication and production technologies. In the case of industrial production, this trend has led to global, integrated supply chains in order to provide the most competitive and innovative products ut...

On the one hand, Industry 4.0 provides possibilities to address arising challenges such as globalisation, individualisation and shortening product lifecycles. On the other hand, it also increases changes and challenges in planning and operation processes of production systems. The paper discusses the changes in digital work in the areas of planning...

In highly automated manufacturing systems running 24/7, preventive maintenance activities need to be executed during production times. Flexible job shops with several identical machines generally bear the potential to compensate temporary machine unavailability times caused by preventive maintenance without a considerable increase of the makespan d...

Parts can be supplied from warehouses to assembly lines via several production-order-independent and -dependent parts supply strategies. Order-dependent parts supply strategies sequencing, kitting and batch supply share enough similarities that allow joint modelling in picking order planning and execution, whereas line stocking, just-in-time, just-...

In recent years, there has been an increasing interest in using industrial data science (IDS) in manufacturing companies. Structured IDS projects proceed according to process models such as the cross industry standard process for data mining (CRISP-DM), knowledge discovery in databases (KDD), or the process chain of industrial data science. Because...

The ongoing digitization of online learning resources has led to a proliferation of collaboration platforms for specific areas of application and disciplines. Simultaneously, the need for collaboration in the field of data analysis and knowledge management increases, especially for manufacturing companies. In this paper, collaborative and competenc...

Sustainability is the current global challenge. This is reflected in the demand for healthy food and CO neutrality. These challenges can be met with the industrial cultivation of algae: Algae can be used as food supplements, nutraceuticals, pharmaceuticals, fuel, CO sinks, and obtain high relative yield density per area. Current limitations in thei...

Learning from demonstration (LfD) has the potential to greatly increase the applicability of robotic manipulators in modern industrial applications. Recent progress in LfD methods have put more emphasis in learning robustness than in guiding the demonstration itself in order to improve robustness. The latter is particularly important to consider wh...

Besides the sequence itself also additional factors serving as moderator variables affect the value of scheduling objectives. For mixed-model assembly lines, especially number and heterogeneity of different products, their volume mix proportions, average workload of the jobs to process and the degree of grouping of identical jobs within the sequenc...

Neben der zeitökonomischen Gestaltung gewinnt die ergonomische Optimierung von Arbeitssystemen zunehmend an Bedeutung. Hohe Personalaufwände zur Erstellung bewegungsökonomischer Analysen sind jedoch Hemmnisse in deren industriellen Umsetzung. Markerloses Motion Capturing bietet Potenzial zur aufwandsreduzierten Erstellung entsprechender Analysen au...

This paper presents the application of a Natural Language Processing (NLP) pipeline, which automatically extracts procedural knowledge in a standardized way from assembly instructions. The developed pipeline is able to parse and process written German assembly instructions regardless of the language discourse. The pipeline helps resolve ambiguities...

Since bolted joints are ubiquitous in manufacturing, their effective and reliable quality assurance is particularly important. Most tightening processes rely on statistical methods to detect faulty screw connections already during assembly. In this paper, we address the detection of faulty tightening processes using a clustering based approach from...

Manufacturing companies are increasingly confronted with the challenges of market globalisation, a shortening of product life cycles and a growing diversity of variants. New and flexible approaches to optimizing production processes and their planning ability are therefore needed to secure competitiveness in a sustainable way. Manual assembly in pa...

Industrial management is facing many challenges, one need is to adopt sustainable practices. As climate change is becoming an increasingly urgent problem, industrial management must find ways to reduce waste and pollution, conserve natural resources, and protect the environment and employees. Industrial management also needs to embrace new technolo...

Interlinked manufacturing processes are characterized by the dependence of downstream process steps on the previous ones. If it can be predicted that a particular workpiece will not reach the desired quality, anticipatory measures can be taken early in the process. By its prediction, machine learning saves resources, both in processing and in the m...

Aktuelle Planungsprojekte zur Produktionssystemgestaltung erfordern die Integration zahlreicher Akteure. Zur erfolgreichen, verteilten Kollaboration ist eine geeignete digitale Plattform erforderlich. Die in diesem Beitrag vorgestellte Plattformarchitektur stellt eine aufgabenorientierte Bereitstellung der Planungsdaten vor und zeigt die Verknüpfun...

Prozessparameter von Bauteilreinigungsanlagen werden häufig manuell eingestellt und beruhen auf über Jahre gesammeltem Expertenwissen. Dieses Wissen gilt es, so zu erfassen, dass Modelle für maschinelles Lernen beziehungsweise künstliche Intelligenz trainiert und angewendet werden können. Das ptimierungskriterium ist der Ressourcenverbrauch, der du...

The importance of cross-process multivariate data analysis for improving products and processes is continuously increasing. Artificial intelligence and machine learning offer new possibilities to represent complex cause-effect relationships in models and to use them for optimisation. For consistent and scalable usage, unified data structures and re...

Sustainability is gaining importance and the economy is changing into a circular economy, especially with regard to climate change and the need to create more resilient value chains. The organization of work is meeting these challenges with, among other things, the digitalization of increasingly changeable production. Collecting and understanding d...

Recycling of refrigerating appliances plays a major role in protecting the Earth’s atmosphere from ozone depletion and emissions of greenhouse gases. The performance of refrigerator recycling plants in terms of material retention is the subject of strict environmental certifications, and is reviewed periodically through specialized audits. The cont...

The alarming progress of climate change requires immediate and rigorous action from our society. This also affects the manufacturing industry to a large extent. Many companies have recognised the situation and set themselves ambitious goals with regard to achieving CO2 neutrality. An important step is the detailed analysis of CO2 emissions across t...

Manually defined control limits remain a common strategy for quality control in manufacturing due to their ease of deployment on the shop floor compared to more advanced data analysis approaches. Despite their continued importance, there is no systematic method of defining these control limits. However, sub-optimal control limits can lead to undete...

Capacity-limiting bottlenecks in manufacturing systems form the ideal starting point for measures of improvement. However, the inherent variability of modern systems leads to dynamic bottleneck behavior, causing them to shift between stations. Numerous methods for the detection of shifting bottlenecks exist in literature. In this paper, we present...

Complex product and production systems often result in high variability in the production flow, prohibiting the sustainable implementation of lean practices. In this paper the authors introduce a PDCA cycle to analyse and reduce variability in value streams. The value stream is divided into zones, which are then qualified as stable or unstable. Lea...

p>Takt work represents a significant risk factor for the development of musculoskeletal complaints and diseases, especially in short-cycle processes. The increased risk results primarily from a permanent uniform load on the musculoskeletal system. Studies on motor variability suggest that an increase in load variation can have positive effects on r...

p>Takt work represents a significant risk factor for the development of musculoskeletal complaints and diseases, especially in short-cycle processes. The increased risk results primarily from a permanent uniform load on the musculoskeletal system. Studies on motor variability suggest that an increase in load variation can have positive effects on r...

In manufacturing systems, early quality prediction enables the execution of corrective measures as early as possible in the production chain, avoiding thus costly rework and waste of resources. The increasing development of Smart Factory Sensors and Industrial Internet of Things has offered wide opportunities for applying data-driven approaches for...

p>In recent times, learning by demonstration has seen tremendous progress in robotic assembly operations. One of the most prominent trajectory-level task models applied is Dynamic Movement Primitives (DMP). However, it lacks the ability to tackle complex operations as often encountered in industrial assembly. Augmenting low-level models with a high...

p>In recent times, learning by demonstration has seen tremendous progress in robotic assembly operations. One of the most prominent trajectory-level task models applied is Dynamic Movement Primitives (DMP). However, it lacks the ability to tackle complex operations as often encountered in industrial assembly. Augmenting low-level models with a high...

Eine erhöhte geplante und ungeplante Variabilität innerhalb der Produktion begünstigt das vermehrte Auftreten dynamischer Engpässe. Deren Beherrschung in Form eines zielgerichteten Engpassmanagements gelingt in der Unternehmenspraxis derzeit häufig nur sehr unzureichend und weitestgehend reaktiv. Dieser Beitrag stellt wesentliche Anwenderanforderun...

Improving the recall of information retrieval systems for similarity search in time series databases is of great practical importance. In the manufacturing domain, these systems are used to query large databases of manufacturing process data that contain terabytes of time series data from millions of parts. This allows domain experts to identify pa...

Purpose: Computer-aided production engineering simulation is a common approach in the search for improvements to real systems. They are used in various industrial sectors and are a basis for optimization. Such production simulations have found limited use in the wool industry. This study aims to compare the performance of different woolshed layouts...

Industrial Engineering, through its role as design, planning and organizational body of the industrial production, has been crucial for the success of manufacturing companies for decades. The potential, expected over the course of Industry 4.0 and through the application of Data Analytic tools and methods, requires a coupling to established methods...

Numerous methods for bottleneck detection, along novel approaches for bottleneck prediction, are available in literature. To facilitate the development and application of such methods, this paper proposes a holistic methodology for Bottleneck Analysis in dynamic value streams. Analogous to established data analytics levels, namely descriptive, diag...

Zusammenfassung Durch die fortschreitende Digitalisierung und Automatisierung sind Unternehmen einem stetigen Transformationsprozess ausgesetzt. Dadurch entfallen alte Berufsbilder und gleichzeitig entstehen völlig neue Berufe mit veränderlichen und digitalen Kompetenzanforderungen. Um zu verhindern, dass der technologische Wandel mit einem Talentm...

Product life cycles change, market developments and quantities are increasingly difficult to predict, as is the case in the production of charging stations. For these reasons, scalable assembly concepts with an adaptable degree of automation are becoming increasingly important. Currently, charging stations are still manufactured manually. With incr...

The linkage of machines in the context of Industry 4.0 through information and communication technology (ICT) to cyber-physical systems with the aim of monitoring, controlling, and optimizing complex production systems, enables real-time capable approaches for data acquisition, analysis, and process knowledge generation. In this context, surface mo...

In manufacturing systems, early quality prediction enables the execution of corrective measures as early as possible in the production chain, avoiding thus costly rework and waste of resources. The increasing development of Smart Factory Sensors and Industrial Internet of Things has offered wide opportunities for applying data-driven approaches for...

Digital tools such as enterprise resource planning systems (ERP) and project management offices (PMO) can support companies in digitalization and getting done common tasks. From an organizational standpoint, agile methods with their short-cycled and target-state-oriented way of working emerged as a promising opportunity to design complex projects e...

Anomaly detection in manufacturing systems has great potential for the prevention of critical quality faults. In recent years, unsupervised deep learning has shown to frequently outperform conventional methods for anomaly detection. However, tuning, deploying and debugging deep learning models is a time-consuming task, limiting their practical appl...

The continuous acquisition of new digital competences and the development of situational learning assistance systems will become more important than ever in the coming years, because the world of work is becoming more complex, more informative and all above more data-driven. Jobs are changing due to increasing digitalisation, whereby the use of mod...

The application of Reinforcement Learning (RL) methods offers a potential for improvement in operational Production Program Planning. Numerous influences and domain-specific practices characterize the multi-dimensional planning paradigm. RL can support human planning personnel in the determination of optimal production parameters. This requires a s...

The corresponding author worked for many years with Toyota coaches, supporting Bosch in the development of pilot value streams for the Bosch Production system. The coaches spent considerable time and effort to analyze and decouple production from customer fluctuations and to stabilize the flow of production with adequate inventory buffers and capac...

Ever since the First Industrial Revolution, optimization measures and operational decisions in the manufacturing industry rely on quantitative and fact-based assess-ments. New advancements during the on-going digitalization and globalization of nowadays world of work represent a logical and inevitable continuation of the ob-servable trends in scien...

The inspection of component surfaces for size, number and type of particulate contamination is carried out using the standard cleanliness analysis described in ISO 16232 and VDA 19.1. Currently, the detection, measurement, counting and classification of particles is performed by an analysis-system comprised of an incident light microscope and corre...

Special Machine Manufactures (SMM) assembling in project shops have to ensure a high delivery performance to be competitive, while the demographic change reinforces the importance of human ergonomics. Since the degree of standardization in project shops is low, the assembly and logistical processes are planned and controlled insufficiently. Particu...