Advanced soft-sensor systems for process monitoring, control, optimisation, and fault diagnosis. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 56 (2023), 2, S. 11768-11777
As processes become more complex and the need to measure each and every variable becomes more critical, the ability of physical sensors to always provide the sufficient accuracy and sampling time can be difficult. For many complex systems, such as nonideal mixtures, multiphase fluids, and solid-based systems, it may not be possible to even use a physical sensor to measure the key variables. For example, in a multiphase fluid, the concentration or density may only be able to be accurately estimated using a laboratory procedure that can only produce a limited number of samples. Similarly, the quality variables of steel may only be determinable once the final steel product has been produced, which limits the ability to effectively control the process with small time delays. In such cases, recourse has to be made to soft sensors, or mathematical models of the system that can be used to forecast the difficult-to-measure variables and allow for real-time process monitoring, control, and optimisation. Although the development of the soft-sensor model is well-established, the various applications and use cases have not been often considered and the key challenges examined. It can be seen that soft sensors have been applied to a wide range of processes from simple, chemical engineering systems to complex mining processes. In all cases, major improvements in the process operations have been observed. However, key challenges remain in updating the soft-sensor models over time, combining laboratory measurements, especially when they are infrequent or of uncertain quality, and the development of soft sensors for new conditions or processes.
https://doi.org/10.1016/j.ifacol.2023.10.565
Developing a computer programme for data quality assessment. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 56 (2023), 2, S. 11784-11789
With the increase in the available data, it becomes increasingly important to develop automatic methods that can extract valuable nuggets of information from the dregs of uninformative and useless information for use in system identification. This paper presents an overview and summary of this field's current state of the art. A MATLAB programme is presented that can implement data quality assessment. A brief tutorial is presented using industrial kerosene freeze-point data to partition the data set into good and bad regions for system identification. A model is developed using the partitioned data. It is shown that the resulting four models can accurately predict the kerosene freeze point in their respective regions and across the data set.
https://doi.org/10.1016/j.ifacol.2023.10.568
Concurrent monitoring and isolation of static deviations and dynamic anomalies with a sparsity constraint. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 56 (2023), 2, S. 11790-11795
In modern process industries, elaborate monitoring and isolation of various disturbances and faults are needed for reliable and efficient system operation. The classic process-monitoring and fault-diagnosis methods can grasp the correlation between variables, and thus, only take care of abnormal situations caused by the corruption of the correlation relationship. However, dynamics anomalies are even more noteworthy as they reflect more internal details of the system dynamic behaviour under specific situations, and more importantly, can cause severe failures and spread to a broader range of areas while evolving over time. In this paper, a monitoring-and-isolation strategy is proposed to concurrently detect and isolate faults of static deviations and dynamic anomalies. The natural sparsity of the faulty variables is used to overcome the limitations of unknown fault directions and insufficient erroneous measurements, thereby translating the isolation problem into a quadratic programming problem with a sparsity constraint and solved by the least absolute shrinkage and selection operator (LASSO). The case study shows the advantages of the proposed method in monitoring and isolating static deviations and dynamic anomalies.
https://doi.org/10.1016/j.ifacol.2023.10.570
Ruling the operational boundaries: a survey on operational design domains of autonomous driving systems. - In: IFAC-PapersOnLine, ISSN 2405-8963, Bd. 56 (2023), 2, S. 2202-2213
Automated driving systems (ADS) have the potential to offer a safe and efficient future for mobility. At the beginning of the design process of an ADS, the operational limits have to be defined using the operational design domain (ODD). Nonetheless, the field of ODD has only become popular recently, and the necessary regulations, standards, and development approaches are still emerging. Current research contributions in the domain of ODD have fragmented in recent years and have not followed a concrete direction. This survey examines a large proportion of the recent research in the domain of ODD by systematically identifying subject areas and categorising relevant publications, thereby integrating the approaches and showing an overview of the emerging topic area. Furthermore, it identifies existing gaps in the ODD research that need to be considered. Finally, the paper suggest relevant future development of ODD.
https://doi.org/10.1016/j.ifacol.2023.10.1128
Aggregated production planning for engineer-to-order products using reference curves. - In: Production at the leading edge of technology, (2023), S. 642-651
The production of highly individualized engineer-to-order products has special characteristics that lead to a significant increase in the complexity of production planning and control. Therefore, aggregate resource planning is a dynamic and complex process that must always deliver reliable results. But without appropriate tools, these predictions can only be achieved with significant manual effort. Therefore, this paper presents a holistic method that predicts and schedules the required manufacturing resources for new customer orders based on a type representative by means of product modularization and data preparation of approximately identical historical manufacturing orders. This allows the actual processing status of the current customer project to be derived from the preplanning by means of a concurrent calculation in order to be able to initiate countermeasures at an early stage in the event of project delays and also to reduce the lead time of the customer order by preallocating the required production resources.
https://doi.org/10.1007/978-3-031-18318-8_64
An AI-driven design method as basis for teaming. - In: Engineering for a changing world, (2023), 5.4.138, S. 1-9
The product development process could benefit from a synergistic human-machine teaming, potentially shortening product development cycles and improving product performance and sustainability. However, there is a lack of available methods to achieve this goal. A technical product has to satisfy numerous requirements. Due to the variety and complexity of these requirements, the design process is challenging for human engineers. While engineers are supported by various tools (e.g. FEM) for analyzing product properties, tools for computer-aided synthesis of product properties considering the corresponding requirements are still only available in exceptional cases. However, such synthesis capabilities are necessary to qualify a computer-aided tool for productive teaming with engineers. Special methods based on artificial intelligence show a high potential for general computer-aided synthesis methods. This contribution presents an innovative approach in this direction based on topology optimization techniques.
https://doi.org/10.22032/dbt.58937
Synergy of nanocomposite force myography and optical fiber-based wrist angle sensing for ambiguous sign classification. - In: Engineering for a changing world, (2023), 5.2.142, S. 1-2
This paper aims at understanding the capabilities and limitation of combining Nanocomposite Force myography sensors (FMG) and optical fiber sensors in standalone systems and their synergy influence on the classification of ambiguous hand gestures. A set of 10 highly similar hand signs from the fingerspelling of the American sign language is adopted in this study. Force myography (FMG) signals are collected from one healthy subject performing the selected set of gestures with 40 repetitions for each gesture. The K-Tournament Grasshopper Extreme Learner (KTGEL) classifier has been implemented to perform an automated feature selection and hand sign classification with an efficient network size and a high accuracy.
https://doi.org/10.22032/dbt.58941
Characterization of plastic-metal hybrid composites joined by means of reactive Al/Ni multilayers - evaluation of occurring thermal regime. - In: Engineering for a changing world, (2023), 4.3.056, S. 1-16
Present challenges in material science and joining technology are ever more subject to the desire for lightweight construction and engineering. Plastic-metal composites are suitable material combinations but also require the development and investigation of appropriate joining technologies. A particularly promising approach is the application of reactive multilayer foils. As an innovative method, these foils provide the possibility of flexible and low-distortion joining of dissimilar materials. The underlying reaction mechanism offers fast exothermic reaction propagation with well-known exothermic power output while the energy source is introduced directly into the joining zone. In this work, hybrid lap joints between semi-crystalline polyamide 6 and structured austenitic stainless steel X5CrNi18-10 were joined using reactive Al/Ni multilayer foils. The self-propagating reaction provides immediate temperatures that are well above the melting point of used plastic but decays rapidly after only a few milliseconds. To support ongoing investigations regarding composite formation, analysis of occurring thermal regime is in the focus of this work. Conducted experiments are supported by accompanying thermal simulation in ANSYS Workbench. Besides the estimation regarding sensitivity of thermal material parameters the evaluation of formed melting zone and resulting thermally influenced area is a central topic.
https://doi.org/10.22032/dbt.58913
Sustainability strategies and their influence on the product development of machine tools and special machines. - In: Engineering for a changing world, (2023), 4.2.125, S. 1-19
In the context of product development, the goal of developers is to design products based on a variety of stakeholder needs so that they sufficiently satisfy a wide range of required characteristics. The required properties relate to function, safety, manufacturability, cost, usability, etc. In recent years, sustainability has gained importance as an additional and now indispensable guiding principle in product development due to the rapidly growing global environmental, social and economic challenges. The focus of this paper is on sustainability, which takes into account resource consumption, environmental protection and ecology. The same applies to the circular economy as an essential component of sustainability strategies when it comes to product or material cycles, as well as the targeted repair, reuse, modification, waste prevention and upgrading of products, etc. A product category that is rarely in the public eye is machine tools and special machines. In order to consistently consider sustainability and the associated circular economy in the development of these machines, product developers need practice-oriented and methodically validated decision-making means. The paper discusses and systematizes possible sustainability strategies and their implications from different perspectives, such as business models or applicability.
https://doi.org/10.22032/dbt.58896
Improving system of objectives maturity through systematic reuse of knowledge using ontology-based knowledge representations. - In: Engineering for a changing world, (2023), 4.2.087, S. 1-16
Technical products are developed to meet the needs of different stakeholders. In addition, various constraints from all phases of the product life cycle have to be considered. In existing work, this information and its dependencies are systematically represented in the so-called system of objectives. A major challenge in modeling the system of objectives is that the necessary information in the system of objectives is often incomplete and uncertain. In addition, this uncertainty and the maturity of the system of objectives cannot be directly quantified because the target state of the system of objectives often cannot be unambiguously described. This research investigates a methodical approach to assess and improve the maturity of the system of objectives. Two means to reduce uncertainty and thus increase the maturity of the system of objectives are the systematic reuse of knowledge and the systematic building of knowledge through verification and validation activities.
https://doi.org/10.22032/dbt.58908