Increasing grasping efficiency is very important for the robots to grasp unknown objects especially subjected to unfamiliar environments. To achieve this, a new algorithm is proposed based on the C-shape configuration. Specifically, the geometric model of the used under-actuated gripper is approximated as a C-shape. To obtain an appropriate graspable position, this C-shape configuration is applied to fit geometric model of an unknown object. The geometric model of unknown object is constructed by using a single-view partial point cloud. To examine the algorithm using simulations, a comparison of the commonly used motion planners is made. The motion planner with the highest number of solved runs, lowest computing time and the shortest path length is chosen to execute grasps found by this grasping algorithm. The simulation results demonstrate that excellent grasping efficiency is achieved by adopting our algorithm. To validate this algorithm, experiment tests are carried out using a UR5 robot arm and an under-actuated gripper. The experimental results show that steady grasping actions are obtained. Hence, this research provides a novel algorithm for fast grasping of unknown objects.@en

Abrasive wear can cause surface damage of bulk solids handling equipment. Reducing the abrasive wear is beneficial to lower the maintenance cost. Previous research elaborated on the bionic design methodology to reduce surface wear of bulk solids handling equipment. To facilitate the application of the bionic design methodology in bulk solids handling, this research examines the effectiveness of a bionic model using discrete element method (DEM) simulations. A reference case of an abrasive wear scenario in bulk solids handling is simulated, and the wear volume of a smooth chute surface is predicted. By applying a bionic model to the chute surface and using the same simulation model, the wear volume of a bionic surface is predicted. By comparisons, it is identified that the bionic surfaces produce less wear than the smooth surface. In addition, the sensitivities of the geometrical parameters for the wear reduction are predicted. Therefore, the abrasive wear reduction effectiveness of the bionic model is demonstrated.@en

Purpose
Sliding wear is a common phenomenon in the iron ore handling industry. Large-scale handling of iron ore bulk-solids causes a high amount of volume loss from the surfaces of bulk-solids-handling equipment. Predicting the sliding wear volume from equipment surfaces is beneficial for efficient maintenance of worn equipment. Recently, the discrete element method (DEM) simulations have been utilised to predict the wear by bulk-solids. However, the sensitivity of wear prediction subjected to DEM parameters has not been systemically investigated at single particle level. To ensure the wear predictions by DEM are accurate and stable, this study aims to conduct the sensitivity analysis at the single particle level.

Design/methodology/approach
In this research, pin-on-disc wear tests are modelled to predict the sliding wear by individual iron ore particles. The Hertz–Mindlin (no slip) contact model is implemented to simulate interactions between particle (pin) and geometry (disc). To quantify the wear from geometry surface, a sliding wear equation derived from Archard’s wear model is adopted in the DEM simulations. The accuracy of the pin-on-disc wear test simulation is assessed by comparing the predicted wear volume with that of the theoretical calculation. The stability is evaluated by repetitive tests of a reference case. At the steady-state wear, the sensitivity analysis is done by predicting sliding wear volumes using the parameter values determined by iron ore-handling conditions. This research is carried out using the software EDEM® 2.7.1.

Findings
Numerical errors occur when a particle passes a joint side of geometry meshes. However, this influence is negligible compared to total wear volume of a wear revolution. A reference case study demonstrates that accurate and stable results of sliding wear volume can be achieved. For the sliding wear at steady state, increasing particle density or radius causes more wear, whereas, by contrast, particle Poisson’s ratio, particle shear modulus, geometry mesh size, rotating speed, coefficient of restitution and time step have no impact on wear volume. As expected, increasing indentation force results in a proportional increase. For maintaining wear characteristic and reducing simulation time, the geometry mesh size is recommended. To further reduce simulation time, it is inappropriate using lower particle shear modulus. However, the maximum time step can be increased to 187% TR without compromising simulation accuracy.

Research limitations/implications
The applied coefficient of sliding wear is determined based on theoretical and experimental studies of a spherical head of iron ore particle. To predict realistic volume loss in the iron ore-handling industry, this coefficient should be experimentally determined by taking into account the non-spherical shapes of iron ore particles.

Practical implications
The effects of DEM parameters on sliding wear are revealed, enabling the selections of adequate values to predict sliding wear in the iron ore-handling industry.

Originality/value
The accuracy and stability to predict sliding wear by using EDEM® 2.7.1 are verified. Besides, this research accelerates the calibration of sliding wear prediction by DEM.@en

Bulk solids handling continues to play an important role in a number of industries. One of the issues during bulk solids handling processes is equipment surface wear. Wear results in high economic loss and increases downtime. Current wear reduction methods such as optimizing transfer conditions or using wear-resistant materials, have brought notable progress. Nevertheless, the wear loss is still significant. Therefore, new solutions for reducing the surface wear must be investigated. Because wear also occurs to the surfaces of many biological organisms, inspirations for wear reduction can be obtained from biology. In this research, the bionic design method is explored to reduce the surface wear of bulk solids handling equipment. This thesis firstly illustrates the analytical wear models in bulks solids handling. Hence, the wear phenomena in biology are investigated. Based on the analogies between biology and bulk solids handling, a bionic design method for wear reduction of bulk solids handling equipment surfaces is developed. Furthermore, two bionic models for reducing abrasive and erosive wear respectively, are proposed for the applications of bulk solids handling equipment surfaces. To model the effects of applying bionic models on the surface wear of bulk solids handling equipment, the discrete element method (DEM) is utilized. Using the parameter values obtained from experiments, the wear of bionic surfaces and conventional smooth surfaces is successfully modeled. By comparing predicted wear loss from bionic surfaces and smooth surfaces, the effectiveness of reducing wear by application of bionic models are successfully demonstrated. Moreover, parametric studies on geometrical parameters of bionic models were also carried out. The results demonstrate that as biological wear reduction mechanisms are implemented, wear reduction of bulk solids handling equipment surfaces can be achieved. It is shown that abrasive wear loss can be reduced by up to 63% whilst erosive wear loss can be reduced by up to 26%.@en

Fast grasping of unknown objects has crucial impact on the efficiency of robot manipulation especially subjected to unfamiliar environments. In order to accelerate grasping speed of unknown objects, principal component analysis is utilized to direct the grasping process. In particular, a single-view partial point cloud is constructed and grasp candidates are allocated along the principal axis. Force balance optimization is employed to analyze possible graspable areas. The obtained graspable area with the minimal resultant force is the best zone for the final grasping execution. It is shown that an unknown object can be more quickly grasped provided that the component analysis principle axis is determined using single-view partial point cloud. To cope with the grasp uncertainty, robot motion is assisted to obtain a new viewpoint. Virtual exploration and experimental tests are carried out to verify this fast gasping algorithm. Both simulation and experimental tests demonstrated excellent performances based on the results of grasping a series of unknown objects. To minimize the grasping uncertainty, the merits of the robot hardware with two 3D cameras can be utilized to suffice the partial point cloud. As a result of utilizing the robot hardware, the grasping reliance is highly enhanced. Therefore, this research demonstrates practical significance for increasing grasping speed and thus increasing robot efficiency under unpredictable environments.

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The handling of iron ore bulk solids maintains an increasing trend due to economic development. Because iron ore particles have hard composites and irregular shapes, the bulk solids handling equipment surface can suffer from severe sliding wear. Prediction of equipment surface wear volume is beneficial to the efficient maintenance of worn areas. Archard’s equation provides a theoretical solution to predict wear volume. To use Archard’s equation, the coefficient of sliding wear must be determined. To our best knowledge, the coefficient of sliding wear for iron ore handling conditions has not yet been determined. In this research, using a pin-on-disk tribometer, the coefficients of sliding wear for both Sishen particles and mild steel are determined with regard to iron ore handling conditions. Both naturally irregular and spherical shapes of particles are used to estimate average values of wear rate. Moreover, the hardness and inner structures of Sishen particles are examined, which adds the evidence of the interpretation of wear results. It is concluded that the coefficients of sliding wear can vary largely for both Sishen particle and mild steel. The wear rate decreases from transient- to steady-state. The average coefficient of sliding wear is capable of predicting wear with respect to long distances at the steady-state. Two types of sliding friction are distinguished. In addition, it is found that the temperature rise of the friction pairs has negligible influence on wear rate.@en

Purpose – The tensile test is one of the fundamental experiments used to evaluate material properties. Simulating a tensile test can be a replacement of experiments to determine mechanical parameters of a continuous material. The paper aims to discuss these issues. Design/methodology/approach – This research uses a new approach to model a tensile test of a high-carbon steel on the basis of discrete element method (DEM). In this research, the tensile test specimen was created by using a DEM packing theory. The particle-particle bond model was used to establish the internal forces of the tensile test specimen. The particle-particle bond model was first tested by performing two-particle tensile test, then was adopted to simulate tensile tests of the high-carbon steel by using 3,678 particles. Findings – This research has successfully revealed the relationships between the DEM parameters and mechanical parameters by modelling a tensile test. The parametric study demonstrates that the particle physical radius, particle contact radius and bond disc radius can significantly influence ultimate stress and Young’s modulus of the specimen, whereas they slightly impact elongation at fracture. Increasing the normal and shear stiffness, the critical normal and shear stiffness can enable the increase of ultimate stress, however, up to maximum values. Research limitations/implications – To improve the particle-particle bond model to simulate a tensile test for high-carbon steel, the damping factors for compensating energy loss from transition of particle motions and failure of bonds are required. Practical implications – This work reinforces the knowledge of applying DEM to model continuous materials. Originality/value – This research illustrates a new approach to model a tensile test of a high-carbon steel on the basis of DEM.@en

Large-scale handling of particulate solids can cause severe wear on bulk solids handling equipment surfaces. Wear reduces equipment life span and increases maintenance cost. Examples of traditional methods to reduce wear of bulk solids handling equipment include optimizing transport operations and utilizing resistant materials. To our knowledge, the so-called bionic design has not been utilized. Bionic design is the application of biological models, systems, or elements to modern engineering. Bionic design has promoted significant progress on the development of engineering products and systems. In order to use bionic design for wear reduction of bulk solids handling equipment surfaces, this paper introduces bionic design to bulk solids handling on the basis of analogies between biology and bulk solids handling. In addition, a bionic design methodology for the wear reduction of bulk solids handling equipment surfaces is formulated. Based on the bionic design methodology, two bionic models used for abrasive and erosive wear reduction of bulk solids handling equipment surfaces are proposed.@en