Manufacturing Handling Research Articles

Genetic Algorithm-Based Trajectory Optimization for Digital Twin Robots.

Mobile robots have an important role in material handling in manufacturing and can be used for a variety of automated tasks. The accuracy of the robot’s moving trajectory has become a key issue affecting its work efficiency. This paper presents a method for optimizing the trajectory of the mobile robot based on the digital twin of the robot. The digital twin of the mobile robot is created by Unity, and the trajectory of the mobile robot is trained in the virtual environment and applied to the physical space. The simulation training in the virtual environment provides schemes for the actual movement of the robot. Based on the actual movement data returned by the physical robot, the preset trajectory of the virtual robot is dynamically adjusted, which in turn enables the correction of the movement trajectory of the physical robot. The contribution of this work is the use of genetic algorithms for path planning of robots, which enables trajectory optimization of mobile robots by reducing the error in the movement trajectory of physical robots through the interaction of virtual and real data. It provides a method to map learning in the virtual domain to the physical robot.

Magnetocuring of temperature failsafe epoxy adhesives

Adhesive technology is of high and increasing interest in a wide variety of conventional and emerging applications. One-component adhesives typically cure using moisture, heat and light. These approaches limit applications to specific substrates, inefficient handling in manufacturing, and can only be indirectly activated. Hence, we developed a method for remote, wireless, contactless curing of adhesives using alternating magnetic fields (AMF). This approach (“magnetocuring”) offers energy efficient, on-demand adhesion. Exposure of MnxZn1-xFe2O4 Curie temperature tuned magnetic nanoparticles (CNP) additives within commercial epoxy adhesives to an AMF cured thermoset resins within min with minimal rise in substrate temperature. The heating of the CNP “switches off” above its Curie temperature offering failsafe heating. The in-situ heating of the CNP can be controlled by CNP composition, CNP loading, and AMF strength. Internal temperatures of 160 °C could be reached in 5 min, allowing curing of most commercial epoxy adhesives without resin scorching. The maximum lap shear adhesion strength exceeded 6.5 MPa. Magnetocuring is demonstrated on wood, ceramics, and plastics, which is of considerable interest in sports, automotive, and aerospace industries.

Composite Microposts with High Dry Adhesion Strength.

Interfaces with enhanced and tunable adhesion have applications in a broad range of fields, including microtransfer printing of semiconductors, grippers on robots, and component handling in manufacturing. Here, a composite post structure with a stiff core and a compliant shell is used to achieve an enhanced adhesion under normal loading. Loading the composite structure in shear significantly reduces the effective adhesion strength, thus providing tunability. The composite posts can be used as stamps in microtransfer printing processes or as building blocks of large-area tunable surfaces composed of arrays of posts. Experimental measurements on composite posts with diameters of 200 μm show a peak adhesion strength of 1.5 MPa, a 9 times enhancement in adhesion relative to a homogeneous post under normal loading, and also that the adhesion can be reduced by nearly a factor of 7 through the application of shear. The adhesion behavior of these composite structures was also examined using finite element analysis, which provides an understanding of the mechanics of detachment. Finally, the composite adhesive posts were used as stamps in a microtransfer printing process in which 5 μm thick silicon membranes were retrieved and subsequently printed.

Achieving enhanced and tunable adhesion via composite posts

Surfaces with enhanced and tunable adhesion have a variety of applications, including microtransfer printing of semiconductor elements, material handling in manufacturing, and gripping surfaces on climbing robots. Traditionally, schemes to achieve tunable adhesion have relied on fabricating arrays of posts or fibers with complex geometries, such as angled posts terminated by wider caps. Here, we describe an alternative to post structures with complex geometries through the use of composite posts that consist of a stiff core and a compliant shell. Posts consisting of a stiff core and compliant shell have enhanced adhesion under normal loading, and the pull-off can be reduced via the application of shear. The adhesion mechanics of composite posts are demonstrated here through a combination of finite element simulations and experimental measurements on individual millimeter-scale posts.

Optimum workforce strategy for production handling

The optimum workforce assignment for chip handling in computer–based manufacturing has been rebellious and crucial to industrial management. However, through OWS, Optimum Workforce Strategy, model proposed in this paper, this issue becomes realistically and concretely solvable. This study not only meditates the conception of balancing machine productivity and human ability into the objective, but also develops the step–by–step algorithm for optimizing the combinatorial problem to accomplish maximum profit. In addition, to extend the applicability of OWS model, the computerized decision tool written in VISUAL BASIC is comprehensively prepared in approaching the optimum solution of workforce allocation efficiently. Moreover, the versatility of OWS model is exemplified through a numerical study. This paper definitely contributes the applicable scheme of workforce allocation for production handling in manufacturing, and provides the valuable tool to conclusively optimize the profit of a machining project for operations research in today's machining industry with profound insight.

A model of optimal manpower allocation for chiphandling in manufacturing

The optimal workforce assignment for chip handling in computer-based manufacturing has been rebellious and crucial to industrial management. However, through the OMP, Optimal Manpower, model proposed in this paper, this issue becomes realistically and concretely solvable. This study not only meditates the conception of balancing machine productivity and human ability into the objective, but also develops the step-by-step algorithm for optimising the combinatorial problem to accomplish maximum profit. In addition, to extend the applicability of OMP model, the computerised decision tool written in Visual Basic is comprehensively prepared in approaching the optimal solution of manpower allocation efficiently. Moreover, the versatility of OMP model is exemplified through a numerical study. This paper definitely contributes the applicable scheme of manpower allocation for chip handling in manufacturing, and provides the valuable tool to conclusively optimise the profit of a machining project for operations research in today's machining industry with profound insight.