Search Results (4)

Effective environmental monitoring is critical for preventing microbial and allergenic cross-contamination. However, manual swabbing methods, commonly used to verify hygienic conditions, are prone to inconsistent results because of variability in pressure, coverage, and techniques. Two novel solutions will be explored to address these challenges: a robotic swabbing system with tactile sensing control, and a fluorescence/absorbance spectrometer for non-contact, protein-based residue detection. The robotic system was evaluated against trained and untrained humans, measuring water pickup, surface coverage, and pressure consistency. Concurrently, the fluorescence system analyzed model poultry protein soil to correlate spectral patterns with contamination levels. The robotic system demonstrated statistically superior performance, achieving consistent force application and near-complete surface coverage, overcoming key limitations of manual sampling. The fluorescence system distinguished contamination with high sensitivity, validating its use as a rapid, non-contact assessment tool. Together, the robotic sample acquisition and the spectrometer’s sensitive analysis provide a dual-modality framework for enhancing hygiene monitoring in manufacturing facilities. Full article

The aim of the study is a multi-criteria comparative evaluation of robots cooperating with humans in single- and dual-arm variants used for the process of precise assembly of complex parts. RobotStudio simulation software with the Signal Analyzer add-on was used for comparative analyses. These studies were conducted as case studies. A robotic station was designed for the assembly of a computer motherboard and two robot variants were programmed to perform the assembly task while maintaining the same motion parameters and functions for both. Then, the TCP motion trajectories associated with the robot were analyzed, as well as monitoring signals from the robot controller during simulation, such as time, speed, acceleration and energy consumption. The costs and profitability of the robot variants were also calculated. The percentage share of tasks performed in the process was also analyzed, divided into assembly tasks and free movements. The differences between the robots in this process include time, 21 s single-arm versus 14 s dual-arm robots. The main influence on achieving the programmed speed was the length of the robot’s TCP motion path. In most cases, the maximum programmed speed of 200 mm/s was achieved. The single-arm robot proved to be more energy-efficient, but the dual-arm robot proved to be 20% faster, which in the long run proved to be a more profitable robot. The profitability of the dual-arm robot paid off after eight months of operation. The case study presented in this paper, assembling a computer motherboard using single- and dual-arm collaborative robots, provides a guide for conducting similar comparative analyses of different robotic stations. Simulations enabled reliable verification of collaborative robots in technological processes, supporting the design of production processes and the analysis of several variants of robotic solutions. Full article

The construction industry has traditionally relied on labor-intensive methods, often resulting in inefficiencies, cost overruns, and extended project timelines. Despite advancements in automation and robotics, the potential of programmable construction to address these challenges remains underexplored, particularly in the context of small to medium-scale projects. This study investigates the impact of programmable construction on time, cost, and sustainability, using a detailed case study of a residential project in Italy. This research adopts a comparative approach, analyzing traditional construction techniques versus automated construction systems. Production rates from previous research and real-world applications are used to develop alternative schedules that reflect the efficiencies of these advanced technologies. The findings demonstrate that programmable construction can reduce project timelines by up to 82.6% and achieve cost savings of approximately 40.6%. Automated systems also offer significant environmental advantages, including a 70.25% reduction in carbon emissions and a 70% decrease in energy consumption in several tasks such as soil treatment. This study suggested that programmable construction sites can significantly shorten project timelines and reduce costs. The precision and speed of AI and robotics minimize reliance on human labor, streamline construction processes, and enhance project performance and work quality by reducing human error while promoting sustainability through reduced resource consumption and lower environmental impact. Full article

Wearable sensor systems with transmitting capabilities are currently employed for the biometric screening of exercise activities and other performance data. Such technology is generally wireless and enables the non-invasive monitoring of signals to track and trace user behaviors in real time. Examples include signals relative to hand and finger movements or force control reflected by individual grip force data. As will be shown here, these signals directly translate into task, skill, and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. The present study draws from thousands of such sensor data recorded from multiple spatial locations. The individual grip force profiles of a highly proficient left-hander (expert), a right-handed dominant-hand-trained user, and a right-handed novice performing an image-guided, robot-assisted precision task with the dominant or the non-dominant hand are analyzed. The step-by-step statistical approach follows Tukey’s “detective work” principle, guided by explicit functional assumptions relating to somatosensory receptive field organization in the human brain. Correlation analyses (Person’s product moment) reveal skill-specific differences in co-variation patterns in the individual grip force profiles. These can be functionally mapped to from-global-to-local coding principles in the brain networks that govern grip force control and its optimization with a specific task expertise. Implications for the real-time monitoring of grip forces and performance training in complex task-user systems are brought forward. Full article