In the context of tolerance management, the consideration of manufacturing and assembly processes is becoming increasingly important. The main drivers for this are, above all, short development times and high-quality requirements, leading to tight tolerances. To overcome the resulting challenges, many publications address the process-oriented tolerance management. However, since multiple terms and definitions for describing activities that link tolerance management with the production process exist, it is hard to obtain a comprehensive overview on the topic. Therefore, this paper presents a review of existing approaches. The aim is to identify similarities and differences of existing approaches and present them with the help of a classification. For this purpose, among others, work from the areas of process-oriented tolerance management, stream of variation, state space modeling, and variation propagation in multistation manufacturing and assembly systems is considered. Based on the definition of the summarizing term “process-oriented tolerance and variation management”, a classification of this thematic area will be introduced.

The assembly of fuel cell stacks presents some unresolved engineering challenges. The aim of this work is to provide a comprehensive solution concept that addresses the identified issues. A product analysis was conducted, from which the assembly process chain could be derived. Subsequently, the problems encountered during assembly were structured and presented. Finally, a solution concept was developed that addresses both the overarching problem and the process-specific difficulties. The analysis shows the necessity of a cost degression of the stacks through full automation of the assembly systems. However, this represents a significant economic risk, which is why a scalable assembly in terms of automation level is proposed. The problem of process complexity and a generally low level of product knowledge is addressed by the introduction of cognitive and physical assistance systems in the low automation stages. To increase the speed of knowledge building in terms of product, process and equipment, algorithms for self-optimizing processes or for outputting action recommendations are used. The control complexity arises from high speed and accuracy requirements of the stacking process, which is addressed in a novel approach using continuous drive technology.

Challenges of the fourth industrial revolution such as shorter product life cycles and increasing product variance require the continuous use of digital technologies in production. Only through these solutions the use of adaptable systems is possible. In this context, the Digital Twin is of crucial importance. The Digital Twin is represented across multiple sectors to meet the technological change. In manufacturing companies its areas of application are versatile. The usage can range from production planning and production monitoring to production optimization. In order to be able to use the advantages of the Digital Twin in the mentioned areas, a targeted data aggregation is necessary. In this paper a cross-application workflow for the efficient planning and usage of Digital Twins is presented. The workflow covers the whole process from the goal and requirement definition up to the implementation and usage of the technology. Particular attention is paid to the aggregation and usage of data in Digital Twins. The developed workflow is evaluated based on an adaptable assembly system.

Fuel cell systems will play an important role in the achievement of global climate goals, particularly in the building and transportation sectors. However, manufacturers face several challenges in the production of these systems, arising primarily from the complexity of products, processes, and equipment as well as the associated data processing requirements. This paper briefly outlines the challenges in the assembly of fuel cell stacks and introduces a specific design of a Digital Twin that addresses them with the help of tailored data management, data evaluation and information utilization. This is followed by the presentation of two potential application scenarios: the use of the Digital Twin as the basis for an expert system that accelerates scaling from prototype to series assembly and as a tool for end-to-end quality monitoring to continuously optimize the products and processes.