@misc{12719, abstract = {{A human digital twin (HDT) is a virtual representation of a worker in cyberspace. Nevertheless, current research focusses mainly on HDTs for motoric work types, such as assembly. To fully integrate an HDT for workers in production, it is necessary that an HDT also displays cognitive processes like memorizing, thinking or reasoning. Such a concept can be used in information-based work, for example monitoring highly automated production systems, and contribute to the planning and control of production. Due to the high proportion of planning and decision-making processes, the efficiency of information-based work is determined in particular by the inner processes of the worker. An HDT can therefore help to describe current and future states of socio-technical work systems. Therefore, this paper presents a systematic literature review to explicitly derive the relevant components of an HDT for information-based work types. The elements of such an HDT and its environment are defined. Further, the current gaps in literature are identified. There are currently no real-world applications of such an HDT. Additionally, the value of multi-HDT systems must be evaluated more extensively.}}, author = {{Mordaschew, Viktoria and Latos, Benedikt and Tackenberg, Sven}}, booktitle = {{Procedia Computer Science}}, issn = {{1877-0509}}, keywords = {{Human-centric Production, Digital Twin, Systematic Literature Review}}, pages = {{2137--2146}}, publisher = {{Elsevier}}, title = {{{A Human Digital Twin for Worker-Centric Production}}}, doi = {{https://doi.org/10.1016/j.procs.2025.01.274}}, volume = {{253}}, year = {{2025}}, } @misc{13349, abstract = {{In weakly-structured work processes, workers are free to decide in which sequence to process their tasks. Predicting their decision-making helps plan production more accurately while preserving workers’ autonomy. The factors that influence workers’ decision-making depend on the manufacturing process and person considered, and they must be newly collected for each use case. This paper identifies the factors influencing workers when deciding in which sequence to process manufacturing tasks in a medium-sized hydraulic cylinder manufacturer. Five workers and two lead workers were observed and interviewed during several work shifts about influencing factors. The authors propose a new interview technique called indifference testing to overcome subjects’ difficulty articulating their decision-making process. Collected factors were categorized using inductive category formation and context analysis. The analyses identified 75 influencing factors comprising 37 decision attributes and 38 decision rules. The identified decision attributes indicate that worker preferences are influenced by attributes from the classical scheduling literature and attributes related to worker well-being, circadian rhythms, and ergonomics. The identified decision rules are useful constituents of more complex preference functions. The decision attributes and rules enable the construction of machine learning models to predict workers’ task sequencing decisions in job shops. Potential applications include systematically eliminating or controlling influencing factors through workplace design measures to increase worker well-being and optimality of their decisions.}}, author = {{Herrmann, Jan-Phillip and Tackenberg, Sven and Burgert, Florens and Nitsch, Verena}}, booktitle = {{Procedia Computer Science}}, issn = {{1877-0509}}, keywords = {{Task Sequencing, Manufacturing, Learning To Rank, Scheduling Human Factors, Case Study}}, pages = {{1820--1829}}, publisher = {{Elsevier BV}}, title = {{{Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer}}}, doi = {{10.1016/j.procs.2025.01.244}}, volume = {{253}}, year = {{2025}}, } @misc{12788, abstract = {{The product environmental footprint (PEF) is one of two life cycle assessment methods from the European Commission. With their published recommendation on environmental footprint methods, the European Commission provides a framework to assess the PEF for every product in a company. Since there is a high probability that the PEF will be mandatory for companies shortly, it is crucial that this recommendation guides companies and mainly technical employees through all phases of the PEF and enables them to execute a PEF study correctly. Therefore, this paper aims to analyze the process of calculating a PEF for a product critically. A PEF study is conducted on a smart luminaire with the software program OpenLCA. The use case concludes that many aspects of the PEF still need to be clarified. Especially the calculation methods behind every impact category need to be more transparent. Further, a comparison of the use case with a provided tutorial from OpenLCA is made. The comparison shows that no information is available on how to model the end-of-life and the use stages, which are mandatory in a PEF study. (c) 2023 The Authors. Published by ELSEVIER B.V.}}, author = {{Mordaschew, Viktoria and Tackenberg, Sven}}, booktitle = {{5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)}}, editor = {{Longo, F. and Shen, W. and Padovano, A.}}, issn = {{1877-0509}}, keywords = {{Product Environmental Footprint, Life Cycle Assessment, Sustainability, Cyber-physical Systems}}, location = {{Lisbon, PORTUGAL}}, pages = {{493--503}}, publisher = {{Elsevier BV}}, title = {{{The Product Environmental Footprint – A Critical Review}}}, doi = {{10.1016/j.procs.2024.01.049}}, volume = {{232}}, year = {{2024}}, } @misc{12795, abstract = {{Including disabled workers in value-creating work processes is a fundamental and guaranteed human right and is, therefore, an essential goal of society. In Germany, sheltered workshops create the conditions for this inclusion since they are essential to companies' value chains. A central challenge is the inclusion of disabled workers in the value-creation processes, such as in manufacturing or assembly areas. The skills of disabled workers vary since they have individual impairments. Therefore, this paper presents a digital human model, a Human Digital Twin (HDT), for disabled workers. The model maps their skills and supports the production planning and assembly processes. (C) 2024 The Authors. Published by Elsevier B.V.}}, author = {{Mordaschew, Viktoria and Duckwitz, Sönke and Tackenberg, Sven}}, booktitle = {{5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)}}, editor = {{Longo, F. and Shen, W. and Padovano, A.}}, issn = {{1877-0509}}, keywords = {{Human Digital Twin, Industry 4.0, Sheltered Workshops, Production Planning}}, location = {{Lisbon, PORTUGAL}}, pages = {{745--751}}, publisher = {{Elsevier BV}}, title = {{{A Human Digital Twin of Disabled Workers for Production Planning}}}, doi = {{10.1016/j.procs.2024.01.074}}, volume = {{232}}, year = {{2024}}, } @misc{12797, abstract = {{Sheltered workshops face the challenge of meeting their manufacturing objectives while considering the individual competenciesand assistance needs of persons with disabilities. Moreover, work processes in sheltered workshops are weakly structured, allowing for frequent task interruptions and changes based on the preferences of impaired work persons. While the Industry 4.0 literature provides many real-time scheduling algorithms for incorporating multiple objectives and constraints, these algorithms fall short of the characteristics of sheltered workshops. The resource-constrained project scheduling problem (RCPSP) is an optimization problem for computing manufacturing plans considering multiple objectives and resource constraints. Among many different RCPSP variants proposed in the literature, the multi-skill RCPSP (MSRCPSP) variant considers the individual skills of work persons when generating manufacturing plans. With the ongoing digital transformation of enterprises, new assistance systems enter the market, providing individual support to impaired work persons and compensating for lacking skills and abilities. This paper proposes an MSRCPSP variant that incorporates assistance systems and learning tasks compensating for competence gaps in the skill matrix of impaired work persons. Furthermore, it decomposes tasks into individual work objects, which accounts for frequent task interruptions and task preferences of work persons. The algorithm is described and demonstrated using a manufacturing data set from an actual sheltered workshop. In a small evaluation study, the algorithm is tested by scheduling two impaired work persons in the assembly department of a medium-sized manufacturing company in the primary labor market. The evaluation study proves its real-world applicability and the suitability of scheduling algorithms for participation and inclusive work. }}, author = {{Herrmann, Jan-Phillip and Mordaschew, Viktoria and Tackenberg, Sven}}, booktitle = {{5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)}}, editor = {{Longo, F. and Shen, W. and Padovano, A.}}, issn = {{1877-0509}}, keywords = {{Scheduling, Sheltered Workshops, Assistance System, Persons with Disabilities}}, location = {{Lisbon, PORTUGAL}}, pages = {{1329--1338}}, publisher = {{Elsevier BV}}, title = {{{A multi-skill RCPSP variant for persons with disabilities in sheltered workshops}}}, doi = {{10.1016/j.procs.2024.01.131}}, volume = {{232}}, year = {{2024}}, } @misc{12813, abstract = {{Autonomous Mobile Robots, as the advanced version of Automated Guided Vehicles have received a lot of interest and recognition in recent years. Simultaneous Localization and Mapping (SLAM) techniques enable the vehicles to independently navigate and map their surroundings so that they can drive autonomously in changing and uncharted areas. Due to the increasing importance and contributive development of SLAMs for automated guided vehicles and autonomous mobile robots, this study seeks to provide an in-depth analysis of well-known SLAM techniques developed and applied during the previous ten years. Well-known SLAM algorithms considered in this paper include GMapping, Cartographer, LIO-SAM, and so on. They are mainly examined and compared from the viewpoints of basic principles, sensor requirements, computing complexity, and performance. The aim of this paper is to offer insights into various SLAM approaches to researchers, practitioners, and developers in the field of automated guided vehicles and autonomous mobile robots, facilitating the selection of suitable SLAM methods for specific applications and fostering innovation in autonomous navigation and mapping.}}, author = {{Li, Li and Schulze, Lothar and Kalavadia, Kunal Satish}}, booktitle = {{5th International Conference on Industry 4.0 and Smart Manufacturing (ISM)}}, editor = {{Longo, F. and Shen, W. and Padovano, A.}}, issn = {{1877-0509}}, keywords = {{Automated Guided Vehicle, Autonomous Mobile Robot, Simultaneous Localization and Mapping, Robot Operating System}}, location = {{Lisbon, PORTUGAL}}, pages = {{2867--2874}}, publisher = {{Elsevier BV}}, title = {{{Promising SLAM Methods for Automated Guided Vehicles and Autonomous Mobile Robots}}}, doi = {{10.1016/j.procs.2024.02.103}}, volume = {{232}}, year = {{2024}}, } @misc{13351, abstract = {{Sheltered workshops face the challenge of meeting their manufacturing objectives while considering the individual competencies and assistance needs of persons with disabilities. Moreover, work processes in sheltered workshops are weakly structured, allowing for frequent task interruptions and changes based on the preferences of impaired work persons. While the Industry 4.0 literature provides many real-time scheduling algorithms for incorporating multiple objectives and constraints, these algorithms fall short of the characteristics of sheltered workshops. The resource-constrained project scheduling problem (RCPSP) is an optimization problem for computing manufacturing plans considering multiple objectives and resource constraints. Among many different RCPSP variants proposed in the literature, the multi-skill RCPSP (MSRCPSP) variant considers the individual skills of work persons when generating manufacturing plans. With the ongoing digital transformation of enterprises, new assistance systems enter the market, providing individual support to impaired work persons and compensating for lacking skills and abilities. This paper proposes an MSRCPSP variant that incorporates assistance systems and learning tasks compensating for competence gaps in the skill matrix of impaired work persons. Furthermore, it decomposes tasks into individual work objects, which accounts for frequent task interruptions and task preferences of work persons. The algorithm is described and demonstrated using a manufacturing data set from an actual sheltered workshop. In a small evaluation study, the algorithm is tested by scheduling two impaired work persons in the assembly department of a medium-sized manufacturing company in the primary labor market. The evaluation study proves its real-world applicability and the suitability of scheduling algorithms for participation and inclusive work.}}, author = {{Herrmann, Jan-Phillip and Mordaschew, Viktoria and Tackenberg, Sven}}, booktitle = {{Procedia Computer Science}}, issn = {{1877-0509}}, keywords = {{Scheduling, Sheltered Workshops, Assistance System, Persons with Disabilities}}, pages = {{1329--1338}}, publisher = {{Elsevier BV}}, title = {{{A multi-skill RCPSP variant for persons with disabilities in sheltered workshops}}}, doi = {{10.1016/j.procs.2024.01.131}}, volume = {{232}}, year = {{2024}}, } @misc{9358, abstract = {{Real-time human-centered assistance in industrial processes depends on the individual history of the work person’s activities in the work system and requires adequate methods for tracking the person’s actions. Most research in human activity recognition is based on recognizing actions from video data using computer vision methods. Digital equipment, standardized machine data interfaces, and smart wearable devices extend the possibilities to describe the current state of the work system. Petri nets have already been applied to human activity recognition, however, without the requirement of detecting actions in real-time. This paper proposes a Petri net architecture that enables hierarchical description-based human activity recognition in industrial work processes. We present an extension, a Partitioned Colored Petri Net, based on the colored Petri net formalism that infers activities from state transitions of the work system in real-time. In a case study, we demonstrate the Petri net’s application for an error-based learning system that visualizes error consequences in augmented reality using experimentable digital twins.}}, author = {{Herrmann, Jan-Phillip and Atanasyan, Alexander and Casser, Felix and Tackenberg, Sven}}, booktitle = {{Procedia Computer Science}}, issn = {{1877-0509}}, keywords = {{Colored Petri net, Human-centered Assistance, Experimentable Digital Twins}}, location = {{Österreich}}, pages = {{1188--199}}, publisher = {{Elsevier}}, title = {{{A Petri Net Architecture for Real-Time Human Activity Recognition in Work Systems}}}, doi = {{https://doi.org/10.1016/j.procs.2022.12.317}}, volume = {{217}}, year = {{2023}}, } @article{7033, abstract = {{Industry 4.0 technologies influence how production is planned, scheduled, and controlled. In literature, different classifications of the tasks and functions of production planning and control (PPC) exist, of which one is the German Aachen PPC model. This paper conducts an exploratory literature review by reviewing 48 publications on a full-text basis. Based on the review, a cyber-physical PPC architecture is proposed, which incorporates current Industry 4.0 technologies, current optimisation methods, optimisation objectives, and disturbances, relevant for the realisation of a PPC system in a smart factory. A classification scheme is developed as a basis for two cluster analyses that reveal researched and unexplored tasks and functions of the Aachen PPC model. Current approaches focus on the in-house PPC, particularly on the control using real-time information from the shop floor. Future research directions are proposed for the unexplored tasks and functions of the Aachen PPC model.}}, author = {{Herrmann, Jan-Phillip and Tackenberg, Sven and Padoano, Elio and Gamber, Thilo}}, issn = {{1877-0509}}, journal = {{Procedia Computer Science}}, keywords = {{Production planning, control, Industry 4.0, Industrial Internet of Things, Exploratory literature review}}, pages = {{208--218}}, publisher = {{Elsevier}}, title = {{{A literature review and cluster analysis of the Aachen production planning and control model under Industry 4.0}}}, doi = {{10.1016/j.procs.2021.01.158}}, volume = {{180}}, year = {{2021}}, }