Search Results (8)

The degradation of the electronic properties of semiconductor materials and electronic devices under neutron irradiation is a critical issue for the development of electronic systems intended for use in nuclear and thermonuclear energy facilities. This study presents a methodology for real-time measurement of the electrical parameters of semiconductor structures during neutron irradiation in a high-flux reactor environment. A specially designed irradiation fixture with an electrical measurement system was developed and implemented at the WWR-K research reactor. The system enables simultaneous measurement of electrical conductivity and the Hall effect, with automatic temperature control and remote data acquisition. The sealed fixture, equipped with radiation-resistant wiring and a temperature control, allows for continuous measurement of remote material properties at neutron fluences exceeding 10¹⁸ cm⁻², eliminating the limitations associated with post-irradiation handling of radioactive samples. The technique was successfully applied to the two different InGaAs-based heterostructures, revealing distinct mechanisms of radiation-induced modification: degradation of mobility and carrier concentration in the InGaAs quantum well structure on GaAs substrate, and transmutation-induced doping effects in the heterostructure on InP substrate. The developed methodology provides a reliable platform for evaluating radiation resistance and optimizing materials for magnetic sensors and electronic components designed for high-radiation environments. Full article

This paper presents the design, construction, and implementation of a soft robotic system comprising a continuum manipulator arm equipped with a compliant gripper. Three main objectives were pursued: (1) developing a soft silicone gripper as an alternative to expensive and rigid steel grippers, enabling safe and precise handling of delicate or irregular objects such as fruits, glassware, and irregular shapes; (2) fabricating a continuum manipulator arm with robotic joints inspired by vertebrae, allowing for smooth, non-linear motion and more excellent maneuverability compared to traditional rigid arms, enabling access to hard-to-reach areas; and (3) integrating the compliant gripper with the continuum manipulator and implementing a control system for the soft gripper and remote bending arm using a microcontroller. The soft gripper, manipulator arm vertebrae, and other components were fabricated using 3D printing with PLA material for the molds. The gripper construct used hyperelastic silicone (Ecoflex 00.30). The continuum manipulator achieved a higher degree of freedom and mobility, while simulations and experiments validated the design’s effectiveness. The comparison shows that the close agreements differ by only 2.5%. In practical experiments involving lifting objects, the gripper was able to carry items with a greater mass. The proposed soft, integrated robotic system outperformed traditional rigid approaches, offering safe and flexible handling capabilities in unstructured environments. The nature-inspired design enabled a compliant grip and enhanced maneuverability, making it suitable for various applications requiring dexterous manipulation of delicate or irregularly shaped objects. Full article

In this paper, we will compare two solution options to determine whether the deployment of an autonomous mobile robot will be a beneficial investment for a company not only in terms of cost, time, and manpower savings, but also in terms of efficiency and reliability in the implementation of selected logistics processes to ensure the smooth running of production. In this paper, we would like to analyse the technology in terms of functions, carrying capacity, and interconnection within the infrastructure in the enterprise. The logistics processes from material order to export to the final customer will be analysed when an automatically controlled robot is deployed. One of the solutions discusses the use of personnel and material handling equipment (tractor with transport kit). The second solution discusses the deployment of the robot and selected logistics processes. The paper concludes with a summary of both options in terms of time, cost, and efficiency of the solution. Full article

Laser cutting is used in many industrial settings to achieve precise cuts of metal sheets. Laser operators may be exposed to particles formed during cutting when opening the cabinet or when metal sheets are exchanged. To characterise the potential exposure, particles formed during laser cutting were studied with scanning electron microscopy equipped with an energy dispersive X-ray detector and an energy backscatter diffraction detector. The total concentration of particles (11–615 nm) was determined online with a scanning mobility particle sizer. The chemical composition of the particles formed during the cutting of the different metal sheets was determined by inductively coupled plasma mass spectrometry (ICP-MS). X-ray diffraction was applied to determine the phase composition. The occupational exposure was assessed gravimetrically and by ICP-MS for five laser operators handling different laser cutters, and materials and were found to be low. Agglomerates and aggregates of condensation particles were formed during laser cutting, independent of the sheet type. Iron, present as both magnetite and α-Fe, was the main element found in the particles formed when cutting steel sheets. The size of the particles generated was mainly below 300 nm. Open laser cutters may lead to higher metal exposures, which is especially relevant when cutting metal sheets containing heavy metals. Full article

The lithium-ion battery (LIB) represents a useful lever for reducing material handling equipment’s (MHE) environmental impact. The exploitation of opportunity charging might improve LIB adoption, which is still prevented by the high investment cost. Since opportunity charging is affected by the system organization, the relationship between LIB and organizational variables is a meaningful work direction to reduce warehouses’ environmental impact, which is underrepresented by the current literature. The present paper aims at filling this gap by investigating the implications of organisational variables on LIB adoption in warehouses where handling activities are performed with forklift trucks. Based on an in-depth review of the literature and semi-structured interviews, the research presents an input-process-output model linking organisational variables and LIB forklift related costs with an application to a real case. This paper is original as it extends findings from the research fields of production and mobility to the warehouse arena, and it opens room for further research on warehouse sustainability. The paper also offers insights to warehouse managers making decisions about LIB adoption for their electric forklift fleets. This is particularly meaningful to reduce warehouse environmental impact, since MHE power source significantly contributes to greenhouse gases emissions. Full article

Mobile robots, such as Automated Guided Vehicles (AGVs), are increasingly employed in automated manufacturing systems or automated warehouses. They are used for many kinds of applications, such as goods and material handling. These robots may also share industrial areas and routes with humans. Other industrial equipment (i.e., forklifts) could also obstruct the outlined routes. With this in mind, in this article, a coloured Petri net-based traffic controller is proposed for collision-free AGV navigation, in which other elements moving throughout the industrial area, such as humans, are also taken into account for the trajectory planning and obstacle avoidance. For the optimal path and collision-free trajectory planning and traffic control, the D* Lite algorithm was used. Moreover, a case study and an experimental validation of the suggested solution in an industrial shop floor are presented. Full article

In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO₂ emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses’ energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e., forklifts) in labor-intensive warehouses from profit and sustainability perspectives. The resulting scheduling aims at minimizing the total cost, which is the sum of the penalty cost related to the makespan of the material handling activities and the total electricity cost of charging batteries. The approach ensures that jobs are executed in accordance with priority queuing and that the completion time of battery recharging is minimized. Realistic numerical experiments are conducted to evaluate the effects of integrating the scheduling of electric loads into the scheduling of material handling operations. The obtained results show the effectiveness of the model in identifying the optimal battery-charging schedule for a fleet of electric MMHEs from economic and environmental perspectives simultaneously. Full article

Construction sites are dangerous due to the complex interaction of workers with equipment, building materials, vehicles, etc. As a kind of protective gear, hardhats are crucial for the safety of people on construction sites. Therefore, it is necessary for administrators to identify the people that do not wear hardhats and send out alarms to them. As manual inspection is labor-intensive and expensive, it is ideal to handle this issue by a real-time automatic detector. As such, in this paper, we present an end-to-end convolutional neural network to solve the problem of detecting if workers are wearing hardhats. The proposed method focuses on localizing a person’s head and deciding whether they are wearing a hardhat. The MobileNet model is employed as the backbone network, which allows the detector to run in real time. A top-down module is leveraged to enhance the feature-extraction process. Finally, heads with and without hardhats are detected on multi-scale features using a residual-block-based prediction module. Experimental results on a dataset that we have established show that the proposed method could produce an average precision of 87.4%/89.4% at 62 frames per second for detecting people without/with a hardhat worn on the head. Full article