There has been a rapid increase in the use of collaborative robots in manufacturing industries within the context of Industry 4.0 and smart factories. The existing human–robot interactions, ...simulations, and robot programming methods do not fit into these fast-paced technological advances as they are time-consuming, require engineering expertise, waste a lot of time in programming and the interaction is not trivial for non-expert operators. To tackle these challenges, we propose a digital twin (DT) approach for human–robot interactions (HRIs) in hybrid teams in this paper. We achieved this using Industry 4.0 enabling technologies, such as mixed reality, the Internet of Things, collaborative robots, and artificial intelligence. We present a use case scenario of the proposed method using Microsoft Hololens 2 and KUKA IIWA collaborative robot. The obtained results indicated that it is possible to achieve efficient human–robot interactions using these advanced technologies, even with operators who have not been trained in programming. The proposed method has further benefits, such as real-time simulation in natural environments and flexible system integration to incorporate new devices (e.g., robots or software capabilities).
Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it ...difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts.
The concept of the circular economy (CE) is receiving encouraging attention among scholars and practitioners, as a convenient solution to move away from the linear economy concept without neglecting ...the goals of sustainable development. The main goals of the CE are the closing of resource loops and the keeping of resources in the system for as long as possible at the highest utility level. However, as a result of the lack of internationally accepted definitions of the CE and several unsolved barriers, an excessive and inconsistent number of different CE applications exist. Most fields are mainly focusing on making a linear system circular instead of applying the CE principles in a holistic way. This paper presents a strategy to close the mentioned inconsistency gap, by contrasting currently discussed CE barriers and goals and thereof deriving two areas with a need for action (1. identifying the needed collection, sorting, and recovery infrastructure, and 2. developing circular product design guidelines). The strategy itself consists of connecting these two areas through an improved information exchange between the end-of-life (EOL) and beginning-of-life (BOL) of products. The result is CE design guidelines which are in accordance with the available or needed collection, sorting, and recovery infrastructure. The proposed strategy presents an innovative solution to apply CE principles in a holistic manner, based on EOL-driven product design.
This article addresses the problem of contact-state (CS) monitoring for peg-in-hole force-controlled robotic assembly tasks. In order to perform such a monitoring target, the wrench (Cartesian forces ...and torques) and pose (Cartesian position and orientation) signals of the manipulated object are firstly captured for different CS’s of the object (peg) with respect to the environment including the hole. The captured signals are employed in building a model (a recognizer) for each CS, and in the framework of pattern classification, the CS monitoring would be addressed. It will be shown that the captured signals are nonstationary, i.e., they have non-normal distribution that would result in performance degradation if using the available monitoring approaches. In this article, the concept of the Gaussian mixtures models (GMM) is used in building the likelihood of each signal and the expectation maximization (EM) algorithm is employed in finding the GMM parameters. The use of the GMM would accommodate the signals nonstationary behavior and the EM algorithm would guarantee the estimation of the optimal parameters set of the GMM for each signal, and hence the modeling accuracy would be significantly enhanced. In order to see the performance of the suggested CS monitoring scheme, we installed a test stand that is composed of a KUKA lightweight robot (LWR) doing peg-in-hole tasks. Two experiments are considered; in the first experiment, we use the EM-GMM in monitoring a typical peg-in-hole robotic assembly process, and in the second experiment, we consider the robotic assembly of camshaft caps assembly of an automotive powertrain and use the EM-GMM in monitoring its CS’s. For both experiments, the excellent monitoring performance will be shown. Furthermore, we compare the performance of the EM-GMM with that obtained when using available CS monitoring approaches. Classification success rate (CSR) and computational time will be considered as comparison indices, and the EM-GMM will be shown to have a superior CSR performance with reduced a computational time.
Laser beam welding of miscellaneous material combinations is an effective joining technology useful for diverse industrial applications because it can provide high speed, flexibility, and precision. ...However, welding defects like solidification cracking are some of the challenges in the joining process. The past decade has seen an extended effort to deal with this issue in many studies. However, there remains to be more comprehensive research regarding preventive procedures for solidification cracking by changing the grain structure. Following a thorough understanding of the solidification crack mechanism theories, we reviewed recent research on the critical role of metallurgical factors in the solidification cracks during laser welding. It considers the influence of the grain structure, intermetallic compounds, and laser welding parameters to propose preventive procedures to suppress the solidification cracks. Recent achievements show grain refiners, laser beam oscillation, ultrasonic vibration, and implementation of double laser sources are the main strategies that suppress or minimize solidification cracks. Furthermore, in laser beam welding of dissimilar materials, like steel-hard metal and copper-aluminum, brittle intermetallic compounds are recognized as one of the main reasons for the solidification crack susceptible increment. Recent approaches to overcome the formation or reduce the number of intermetallic compounds through various laser parameters and setups are discussed.
Laser Wire Additive Manufacturing (LWAM) is a flexible and fast manufacturing method used to produce variants of high metal geometric complexity. In this work, a physics-based model of the bead ...geometry including process parameters and material properties was developed for the LWAM process of large-scale products. The developed model aimed to include critical process parameters, material properties and thermal history to describe the relationship between the layer height with different process inputs (i.e., the power, the standoff distance, the temperature, the wire-feed rate, and the travel speed). Then, a Model Predictive Controller (MPC) was designed to keep the layer height trajectory constant taking into consideration the constraints faced in the LWAM technology. Experimental validation results were performed to check the accuracy of the proposed model and the results revealed that the developed model matches the experimental data. Finally, the designed MPC controller was able to track a predefined layer height reference signal by controlling the temperature input of the system.
Laser Wire-Feed Metal Additive Manufacturing (LWAM) is a process that utilizes a laser to heat and melt a metallic alloy wire, which is then precisely positioned on a substrate, or previous layer, to ...build a three-dimensional metal part. LWAM technology offers several advantages, such as high speed, cost effectiveness, precision control, and the ability to create complex geometries with near-net shape features and improved metallurgical properties. However, the technology is still in its early stages of development, and its integration into the industry is ongoing. To provide a comprehensive understanding of the LWAM technology, this review article emphasizes the importance of key aspects of LWAM, including parametric modeling, monitoring systems, control algorithms, and path-planning approaches. The study aims to identify potential gaps in the existing literature and highlight future research opportunities in the field of LWAM, with the goal of advancing its industrial application.
Many manufacturing industries especially small and medium size (SMEs) industries are reluctant to automatize their production using robots. This is due to the fact that mostly industrial robots are ...not properly equipped to recognize their surrounding and take intelligent decisions regarding path planning especially for low volume, flexible production with versatile production lines. The proposed idea is that a robot manipulator performing assembly or disassembly tasks should be able to predict potential collisions even with unknown obstacles and must be able to prevent i.e. react automatically for safe detour around obstacle. Currently, industrial robots have tactile sensing abilities, which detect collisions after a real contact but the existing proposals for its avoidance are either computationally expensive, need prior information about the obstacles or not very well adapted to the safety standards. Therefore, this paper introduces a ToF sensor based information collection and intelligent decision methodology in order to localize the un-known, un-programmed obstacles and propose a safe peg-in-hole automated assembly process. In the case of collisions, the proposed method will provide various solutions and decides for the best solution according to the scenario on-hand. The proposed solution is quick and robust and currently applied for static environment, whereas dynamic obstacles will be treated in future.
Laser joining of polymers to metals is a rising research subject due to the potential of considerably reducing the weight of structures. This article deals with the laser joining process between ...polypropylene and aluminum. Without pre-treatment, laser joining of these materials is not feasible, and the method applied in this study to circumvent this issue is a surface modification of aluminum with a pulsed laser to create mechanical interlocking for the heat conduction laser joining technique. Different patterns and various laser parameters are analyzed with the design of experiments to best understand the effects of each parameter along with microscopic observations. It is found that engraving weakens the mechanical properties of the aluminum samples. The compromise between the engraving depth and the mechanical properties of the samples is optimized, and the engraving process with a 0.28 mm line width, 27.3% density and 150 mm/s speed provides the highest mechanical performance of the assembly with minimum degradation of aluminum samples. Moreover, by adjusting the laser power and using power modulation below 300 W, the decomposition of polypropylene occurring at high temperatures is reduced to a minimum. After the final optimization, the joined samples reliably withstand a maximum force of 1500 N, which is, approximately, a shear strength of 20 MPa.
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