Engineering methods and tools enabling reconfigurable and adaptive robotic deburring

Centrifugal pump is widely used in various fields of the national economy. Pumps, of which 70% are centrifugal pumps, consume 20.9% of the total electricity generation nationwide in China in 2009, according to the statistics. In this paper, the research advances in design methods and characteristics of internal flow fields for centrifugal pumps, carried out by the Research Center of Fluid Machinery Engineering and Technology of Jiangsu University, is introduced. First of all, the Greater Flow Design method, Non-Overload Design method and Splitter Blade Offset Design method are fully discussed through systematically studies. In addition, three methods of performance prediction for centrifugal pumps are adopted, and a CAD/CFD software for hydraulic design and analysis is initially developed. Secondly, to deepen the understanding of characteristics of internal flow in centrifugal pumps, the numerical simulation and PIV measurement investigation have been done. Then the unsteady flow induced vibration and noise are studied considering fluid-structure interaction and fluid-sound interaction. The control of the unsteady flow in centrifugal pumps is also attempted to optimize the design method for centrifugal pumps. In addition, the pressure pulsation and vibration behaviors under both cavitation and non-cavitation conditions are obtained and analyzed. Finally, some detecting methods and criterion for cavitation incipiency and development are put forward.

Most industrial robots are designed to operate as position servo-controlled manipulators, which is appropriate if the robot is to simply follow a predefined trajectory in free space. However, if the robot’s end-effector comes into contact with the environment, then position control generally will not suffice. Stability becomes a major issue when the robot end-effector becomes highly constrained, and the success of the operation is largely dependent upon the correct selection of the gains in the force control algorithm. These gains are themselves dependent upon the compliance at the task interface, and another major difficulty occurs when this is unknown or varying. This paper describes the application of fuzzy logic in the development of an industrial robot force controller, primarily used for robotic deburring operations. Experimental results illustrate the effectiveness of the controller’s self-adjusting gain strategy, and the ability of the robot to successfully carry out a deburring operation.

The rapid growth of robotics and automation, especially during the last few years, its current positive impact and future projections for impact on the United States economy are very promising. This rapid growth of robotic automation in all sectors of industry will require an enormous number of technically sound specialists with the skills in industrial robotics and automation to maintain and monitor existing robots, enhance development of future technologies, and educate users on implementation and applications. It is critical, therefore, that educational institutions adequately respond to this high demand for robotics specialists by developing and offering appropriate courses geared towards professional certification in robotics and automation. In order to effectively teach concepts of industrial robotics, the curriculum needs to be supported by the hands on activities utilizing industrial robots or providing training on robotic simulation software. Nowadays, there is no robotic simulation software available to the academic institution at no cost which limits educational opportunities. As part of the NSF sponsored project, team of faculty members and students from Michigan Tech are developing new, open source RobotRun robotic simulation software which will be available at no cost for adaptation by the other institutions. This will allow current concepts related to industrial robotics to be taught even in locations without access to current robotics hardware. In addition, to teach emerging concepts of robotics, automation, and controls, authors present the design and development the state-of-the-art robotic workcell consisting of 3 FANUC industrial robots equipped with robotic vision system, programmable logic controller, a conveyer and various sensors. The workcell enables the development and programing of various industry-oriented scenerious and therefore provide students with the opportunity of gaining skills that are relevant to current industry needs.

Trajectory optimization of a robotic work cell plays a fundamental role in productivity improvement. However, in some specific applications, such as robotic deburring, it is also possible to reduce cycle time by finding the best task order. In this paper, the well known Travelling Salesman Problem has been provided by additional constraints in order to solve the problem mentioned above. Moreover, such an approach has been applied to a specific industrial task.

One of the fundamental problems in simulating the motion of sharp interfaces between immiscible fluids is a description of the transition that occurs when the interfaces merge and reconnect. It is well known that classical methods involving sharp interfaces fail to describe this type of phenomena. Following some previous work in this area, we suggest a physically motivated regularization of the Euler equations which allows topological transitions to occur smoothly. In this model, the sharp interface is replaced by a narrow transition layer across which the fluids may mix. The model describes a flow of a binary mixture, and the internal structure of the interface is determined by both diffusion and motion. An advantage of our regularization is that it automatically yields a continuous description of surface tension, which can play an important role in topological transitions. An additional scalar field is introduced to describe the concentration of one of the fluid components and the resulting system of equations couples the Euler (or Navier–Stokes) and the Cahn–Hilliard equations. The model takes into account weak non–locality (dispersion) associated with an internal length scale and localized dissipation due to mixing. The non–locality introduces a dimensional surface energy; dissipation is added to handle the loss of regularity of solutions to the sharp interface equations and to provide a mechanism for topological changes. In particular, we study a non–trivial limit when both components are incompressible, the pressure is kinematic but the velocity field is non–solenoidal (quasi–incompressibility). To demonstrate the effects of quasi–incompressibility, we analyse the linear stage of spinodal decomposition in one dimension. We show that when the densities of the fluids are not perfectly matched, the evolution of the concentration field causes fluid motion even if the fluids are inviscid. In the limit of infinitely thin and well–separated interfacial layers, an appropriately scaled quasi–incompressible Euler–Cahn–Hilliard system converges to the classical sharp interface model. In order to investigate the behaviour of the model outside the range of parameters where the sharp interface approximation is sufficient, we consider a simple example of a change of topology and show that the model permits the transition to occur without an associated singularity.

Recent developments for the design of moment end-plate connections

Evaluation of cutting force and surface roughness in the dry turning of Al–Mg2Si in-situ metal matrix composite inoculated with bismuth using DOE approach

PurposeThis paper aims to describe the development and testing of a system for the automated deburring of aero‐engine components.Design/methodology/approachThe system described in this paper uses an in‐process measurement sensor to determine the component's exact location prior to the deburring operation. The core of the system is a set of algorithms capable of fitting and generating the required robot path relative to the feature to be profiled.FindingsThe paper demonstrates that with a combination of non‐contact metrology and mathematical processing standard industrial robot can be used to deburr aero engine components.Originality/valueThe paper introduces an efficient robotic deburring method, which is developed based on generating real‐time robotic deburring path. Reducing the reliance on part holding fixtures and the use of a laser‐guided robot ensures the developed deburring system is highly flexible and re‐configurable.

The use of robotics in the modern food industry has increased over recent years because of many advantages. However, the industry has not taken to the technology with the same pace as the automotive and other industries due to technical and some other reasons. The high investment rate, variable nature of food products, fragile and perishable characteristics of food items, hygienic and sterilization requirements, high production volume rates are making hindrance in usage of robotics in industry but the opportunity still exists to deliver significant benefits in terms of increased food shelf life, cost reductions and flexibility. The challenge is to develop low-cost, flexible, hygienic and intelligent machines for the food industry. This is a not tough as the technologies now exist to achieve it. The benefits that could be gained if systems are designed, installed and operated well could decide who will be the major food manufacturers of convenience foods in the future.

Redundant robotic manipulators under kinematic control may exhibit unpredictable behaviors at the joint level. When the end effector describes a closed trajectory, the joint angles may not return to their initial values. Likewise, final configuration in the joint space may depend on the trajectory that is followed by the end effector. In this paper, a complete parameterization of holonomic redundancy resolution techniques that avoid these problems is proposed. The flexibility of the proposed approach is discussed. In particular, it is shown that the selection of the redundancy resolution criterion is totally decoupled from the implementation of a closed-loop inverse kinematics (CLIK) algorithm. Any user-defined redundancy resolution criterion can, thus, be enforced. Potentialities of this new methodology are experimentally verified on an industrial robot in a case study where functional redundancy occurs and is applied in simulation on a 7-degree-of-freedom (7-DOF) anthropomorphic manipulator.

Neuro-evolution is an appealing approach to generating collective behaviors for robot swarms. In its typical application, known as off-line automatic design, the neural networks controlling the robots are optimized in simulation. It is understood that the so-called reality gap, the unavoidable differences between simulation and reality, typically causes neural network to be less effective on real robots than what is predicted by simulation. In this paper, we present an empirical study on the extent to which the reality gap impacts the most popular and advanced neuro-evolutionary methods for the off-line design of robot swarms. The results show that the neural networks produced by the methods under analysis performed well in simulation, but not in real-robot experiments. Further, the ranking that could be observed in simulation between the methods eventually disappeared. We find compelling evidence that real-robot experiments are needed to reliably assess the performance of neuro-evolutionary methods and that the robustness to the reality gap is the main issue to be addressed to advance the application of neuro-evolution to robot swarms.

The electromagnetic interference (EMI) problem of extra-high speed electronic devices and systems is becoming more complex with an increase of operating frequency. The conventional analysis and design methods could not cope with the current EMI problems. Advanced analysis and design methods are desired. Deep neural network (DNN) and Bayesian optimization algorithm (BOA) based on machine learning are utilized in prediction of EMI radiation, optimization of design parameters and localization of EMI sources. The feasibility of DNN and BOA is investigated and validated. The steps of using DNN and BOA are proposed in the paper.

Sustainable manufacturing focuses on increasing productivity by regulating process parameters through resource optimization. Industries are attempting to use fewer resources in machining of any material in order to improve productivity and sustainability. It can be accomplished by higher Material Removal Rate (MRR) and decreased defective components since enhanced MRR requires less energy usage and material waste can be reduced by manufacturing high-quality products. In the drilling operation of rotary ultrasonic machining (RUSM), this study intends to investigate the effects on material removal rate (MRR) by varying the process parameters and overcut, in order to reduce overcut error, which increased the number of faulty parts (RUSM). For this investigation, the Six Sigma (DMAIC) technique was used. Gauge R&R study was conducted to check the accuracy of measuring instrument by ensuring its measurements are repeatable and reproducible followed by cause and effect analysis to find out possible causes for a specific problem. More specifically, the current study focusses on determining the relative effect of process parameters on overcut and MRR by using a full factorial design. Ultrasonic power control factors and feed rate were chosen as the study's control variables. According to the study's findings, the total gauge R&R was 1.78%, which shows that the part-to-part variance is significant for an overcut error. The results revealed that at 0.6 mm/min feed rate and 75% ultrasonic power, the MRR achieved was maximum. With an ultrasonic power of 50% and 0.6mm/min feed rate, the overcut error was reduced. When using the revised machining conditions, the mean overcut error was reduced by 34.18%, which was a significant reduction. It can be concluded that machining with optimized process parameters leads to economically sound processes and solves persistent problems in terms of improved MRR, reduced overcut defects and increased productivity.

Industries frequently encounter several difficulties during milling operations, especially with cutting forces. Slot milling involves the machining of slots in materials using a milling cutter, and the challenges related to cutting forces can significantly impact the efficiency and quality of the milling process. CNC milling is widely used for machining of different types of materials in the manufacturing industry. Therefore, it is required to study process parameters and its behavior on materials which is not only to enhance the process but also make an effective and efficient path in metal cutting process. This research includes the effect of three input parameters i.e. feed rate, cutting speed and depth of cut on cutting force for Mild Steel. An empirical study gives the significant behavior of process or input parameter on machining properties. A mathematical study viz. ANOVA (Analysis of variance) gives the correlation in-between input or process parameters and machining or output properties for Mild Steel. It is also developed an equation for cutting force using a Regression model for the prediction of feed, speed and depth of cut. Values obtained from the mathematical models and Regression model was found to be very close to the data obtained from the experimental studies. The lowest cutting forces were obtained at high cutting speed and low feed rate and depth of cut.

Battling serious injuries and long-term consequences in road traffic remains one important issue in the overall goal of resilient future road transport and its Vision Zero. Challenges of increasing personal transport in urban areas coupled with autonomous vehicles and shuttles, new mobility devices and the overall need to ensure the safety of vulnerable road users as well as all types of vehicle occupants’ require solid medical background knowledge paired with innovative engineering approaches. EU Horizon Europe is currently funding the ProtAct-Us consortium (2024-2027) that aims at protecting all Road User Groups from serious injury and long-term physical, cognitive and mental health consequences related to road crashes through innovatively interlinked research action between medical and engineering methods and approaches. ProtAct-Us works on the following goals and challenges: i) Medical data correlation, standardisation and classification of long-term consequences of road crashes; ii) Robust and reliable medical, epidemiological and engineering tools like agreed methods to collect information on long-term consequences, upgraded Human Body Models and virtual assessment methods for the extremities, head, neck and face allowing for effective countermeasure development for all road users; iii) Reduction of long-term consequences and related socio-economic cost of road crash related injuries for all road users. The ProtAct-Us solutions will influence new standards in respect of extending current injury codification system with relevant long-term aspects, allowing new physical as well as virtual safety assessment procedures and adaption of rules and regulations to be implemented. Finally, scientifically well-founded suggestion for future implementation into policy, regulatory, and standardization guidelines for an inclusive safety improvement approach for in- as well as post-crash will be provided.