This paper presents the theoretical and practical fundamentals of using physiology sensors to capture human emotion reactivity in a products or systems engineering context. We aim to underline the complexity of regulating (internal and external) effects on the human body and highly individual physiological (emotion) responses and provide a starting point for engineering researchers entering the field. Although great advances have been made in scenarios involving human-machine interactions, the critical elements—the actions and responses of the human—remain far beyond automatic control, because of the irrational behavior of human subjects. These (re)actions, which cannot be satisfactorily modeled, stem mostly from the fact that human behavior is regulated by emotions. The physiological measurement of the latter can thus be a potential door to future advances for the community. In this paper, following a brief overview of the foundations and ongoing discussions in psychology and neuroscience, various emotion-related physiological responses are explained on the basis of a systematic review of the autonomic nervous system and its regulation of the human body. Based on sympathetic and parasympathetic nervous system responses, various sensor measurements that are relevant in an engineering context, such as electrocardiography, electroencephalography, electromyography, pulse oximetry, blood pressure measurements, respiratory transducer, body temperature measurements, galvanic skin response measurements, and others, are explained. After providing an overview of ongoing engineering and human-computer interaction projects, we discuss engineering-specific challenges and experiment setups in terms of their usability and appropriateness for data analysis. We identify current limitations associated with the use of physiology sensors and discuss developments in this area, such as software-based facial affect coding and near-infrared spectroscopy. The key to truly understanding user experience and designing systems and products that integrate emotional states dynamically lies in understanding and measuring physiology. This paper serves as a call for the advancement of affective engineering research.

The use of digital twins to represent a product or process digitally is trending in many engineering disciplines. This term has also been recently introduced in the medical field. In arthroscopic surgery education, the paradigm shift from apprenticeship to simulation training has driven the need for better simulators, and the current focus is on improving simulators with respect to computational efficiency and system accuracy. However, expanding surgical simulations towards digital twins has not yet been explored. This paper introduces the digital twin concept for arthroscopic surgery, and explores its potential in light of the existing scientific literature. Thus, a systematic review was conducted to summarize and analyze the literature with respect to fast and robust design of an arthroscopic digital twin using patient-specific information, and methods for interactive surgical soft tissue simulation. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol with three reliable scientific search engines: IEEE Xplore, ScienceDirect and PubMed. Eighty papers were included in the review, and the extracted data included modeling methods, tissue types, constitutive behavior, computational efficiency or accuracy, hardware configuration, haptic device description, software tools, and system architectures. Considering the review, a novel macro-level conceptual arthroscopic digital twin system is presented, and the applicability of the review findings for the identified subsystems are discussed. The proposed system integrates patient-specific images, diagnostic data, intraoperative sensor data, and surgical practice as inputs, and conceptually enables surgical skills training, preoperative planning, and a database of virtual surgeries.

The idea of remote controlling ships for operational and commercial uses has developed beyond concepts. Controlling and monitoring vessels from a distant location requires updating the concept and requirements of shore control centers (SCCs), where human operators control the fleet via cameras, GPS, and many other types of sensors. While remote ship operation promises to reduce operational and maintenance costs, while increasing loading capacity and safety, it also brings significant uncertainty related to both the human-machine and human-human interactions which will affect operations. Achieving safe, reliable, and efficient remote ship operations requires consideration of both technological, cultural, social and human factor aspects of the system. Indeed, operators will act as captain and crew remotely, from the SCC, introducing new types of hardware and software interactions. This paper provides an overview of human factor issues that may affect human-machine and human-human interactions in the course of remote ship operations. In doing so, the literature related to remote operations in the domains of shipping, aerial vehicles, cranes, train transportation, automobiles, and mining is reviewed. Findings revealed that human factor issues are likely to fall into 13 distinct groups based on the type of human interactions that take place in SCCs.

Topology optimization (TO) has been a popular design method among CAD designers in the last decades. This method optimizes the given design domain by minimizing/maximizing one or more objective functions, such as the structure’s stiffness, and at the same time, respecting the given constraints like the volume or the weight reduction. For this reason, the companies providing the commercial CAD/FEM platforms have taken this design trend into account and, thus, have included TO in their products over the last years. However, it is not clear which features, algorithms, or, in other words, possibilities the CAD designers do have using these software platforms. A comparative study among the most applied topology optimization software was conducted for this research paper. First, the authors developed an online database of the identified TO software in the form of a table. Interested CAD designers can access and edit its content, contributing in this way to the creation of an updated library of the available TO software. In addition, a deeper comparison among three commercial software platforms—SolidWorks, ANSYS Mechanical, and ABAQUS—was implemented using three common case studies—(1) a bell crank lever, (2) a pillow bracket, and (3) a small bridge. These models were designed, optimized, and validated numerically, as well as compared for their strength. Finally, the above software was evaluated with respect to optimization time, optimized designs, and TO possibilities and features.

The weight optimization of a structure can be conducted by using fewer and downsized components, applying lighter materials in production, and removing unwanted material. Topology optimization (TO) is one of the most implemented material removal processes. In addition, when it is oriented towards additive manufacturing (AM), it increases design flexibility. The traditional optimization approach is the compliance optimization, where the material layout of a structure is optimized by minimizing its overall compliance. However, TO, in its current state of the art, is mainly used for design inspiration and not for manufacturing due to design complexities and lack of accuracy of its design solutions. The authors, in this research paper, explore the benefits and the limitations of the TO using as a case study the housings of a front and a rear brake caliper. The calipers were optimized for weight reduction by implementing the aforementioned optimization procedure. Their housings were topologically optimized, partially redesigned, prepared for 3D printing, validated, and 3D printed in titanium using selective laser melting (SLM). The weight of the optimized calipers reduced by 41.6% compared to commercial calipers. Designers interested in either TO or in automotive engineering can exploit the findings in this paper.

Topology and Parametric Optimization are two of the most implemented material optimization approaches. However, it is not clear in the literature which optimization procedure, or possible combination of them, can lead to the best results based on material reduction and optimization time. In this paper, a quantitative comparison of different topology and parametric optimization design processes is conducted using three benchmark examples: A Hollow Plate, an L-Bracket, and a Messerschmitt–Bölkow–Blohm Beam (MBB-Beam). Ten different design processes that were developed in each case study resulted in 30 simulations in total. The design processes were clustered in three main design workflows: The Topology Optimization, the Parametric Optimization, and the Simultaneous Parametric and Topology Optimization. Their results were compared with respect to mass, stress, and time. The Simultaneous Parametric and Topology Optimization approach gave the lightest design solutions without compromising their initial strength but also increased the optimization time. The findings of this paper will help the designers in the pursuit of lightweight structures and will create the basis for the identification of the ideal material optimization procedure.