Search results

This paper aims to propose an automated framework for agile development and simulation of robotic palletizing cells. An automatic offline programming tool, for a variety of robot brands, is also introduced.

This framework, named AdaptPack Studio, offers a custom-built library to assemble virtual models of palletizing cells, quick connect these models by drag and drop, and perform offline programming of robots and factory equipment in short steps.

Simulation and real tests performed showed an improvement in the design, development and operation of robotic palletizing systems. The AdaptPack Studio software was tested and evaluated in a pure simulation case and in a real-world scenario. Results have shown to be concise and accurate, with minor model displacement inaccuracies because of differences between the virtual and real models.

An intuitive drag and drop layout modeling accelerates the design and setup of robotic palletizing cells and automatic offline generation of robot programs. Furthermore, A* based algorithms generate collision-free trajectories, discretized both in the robot joints space and in the Cartesian space. As a consequence, industrial solutions are available for production in record time, increasing the competitiveness of companies using this tool.

The AdaptPack Studio framework includes, on a single package, the possibility to program, simulate and generate the robot code for four different brands of robots. Furthermore, the application is tailored for palletizing applications and specifically includes the components (Building Blocks) of a particular company, which allows a very fast development of new solutions. Furthermore, with the inclusion of the Trajectory Planner, it is possible to automatically develop robot trajectories without collisions.

The purpose of this paper is to provide a maximum speed algorithm for serial palletizing robots, which guarantees relatively low system modeling requirements and can be easily implemented in actual applications.

Operation speed is an important index of palletizing robots performance. In order to improve it, features of palletizing motions are analyzed, and a refined iterative learning control algorithm for maximum speed optimization is proposed. The refined algorithm learns to increase local speed when the following error does not exceed a predefined tolerance, unlike conventional applications which make actual output identical to its reference. Furthermore, experiments were developed to illustrate the new algorithm's ability to take full advantage of motor capacity, drive ability and repetitive link couplings to improve palletizing efficiency.

Experiments show that motion time decreases more than 20 percent after optimization.

The new iterative control algorithm can be easily applied to any repetitive handling operations where manipulating efficiency matters.

FlexPalletizer IRB 640 is the name of a new palletizing robot developed by ABB that meets the special needs of the consumer goods industry, and particularly those of the foodstuffs and beverage sector. A total of 1,200 palletizing cycles per hour and a handling capacity of 160kg are among the performance features that ensure fast pay‐back of the capital investment. Modern software tools not only increase productivity, but also lower the cost of operating the robot. PalletWizard, for example, allows users to create their own palletizing programs off‐line and requires no special knowledge of programming. It works in a PC environment and allows the robot to be kept in production while new work cycles, etc., are being created.

The purpose of this paper is to report on the innovative system developed to automatically palletize orders of cartons of candy for shipment to distribution centers.

Designers study the manual system employed by the customer and focused on dividing the workload across robotic and traditional palletizing equipment.

As many as 15 workers could be redistributed to other areas of the plant, as well as helping to prevent injuries, without increasing floor space needed.

Robotics can be very useful but are not always the correct answer for all aspects of every application.

Knowing what others have accomplished can be very useful in structuring an approach to a new automated assembly requirement.

Gives an example of the use of offline 3‐D graphical simulation to assist in program generation for a robot palletizing operation, a technique which is proving increasingly cost effective. Describes GRASP, the 3‐D graphical simulation tool for robotics applications whose special palletizing module was employed, and reports on the successful outcome. Claims that GRASP has enabled verified robot programs to be generated which can be produced in less than a day, saving more than two days over the manual programming approach and reducing cell downtime from three days to less than two hours.

This paper aims to propose a translation library capable of generating robots proprietary code after their offline programming has been performed in a software application, named AdaptPack Studio, running over a robot simulation and offline programming software package.

The translation library, named AdaptPack Studio Translator, is capable to generate proprietary code for the Asea Brown Boveri, FANUC, Keller und Knappich Augsburg and Yaskawa Motoman robot brands, after their offline programming has been performed in the AdaptPack Studio application.

Simulation and real tests were performed showing an improvement in the creation, operation, modularity and flexibility of new robotic palletizing systems. In particular, it was verified that the time needed to perform these tasks significantly decreased.

The design and setup of robotics palletizing systems are facilitated by an intuitive offline programming system and by a simple export command to the real robot, independent of its brand. In this way, industrial solutions can be developed faster, in this way, making companies more competitive.

The effort to build a robotic palletizing system is reduced by an intuitive offline programming system (AdaptPack Studio) and the capability to export command to the real robot using the AdaptPack Studio Translator. As a result, companies have an increase in competitiveness with a fast design framework. Furthermore, and to the best of the author’s knowledge, there is also no scientific publication formalizing and describing how to build the translators for industrial robot simulation and offline programming software packages, being this a pioneer publication in this area.

In this industrial case study paper the problem of handling production variations online, i.e. during actual production, is addressed. These variations may occur when it is not possible to exactly guarantee working conditions during a production cycle or between two consecutive cycles. These variations are common in some types of industries, like the glass and ceramic industry, where the products may change slightly during the production cycle. Since it is common to have two or more different model campaigns during a working day, it should be possible to easily parameterize the production system when a new campaign is started. This paper uses a highly‐efficient robotic palletizing system, developed for the partner company Sekurit Saint Gobain (Portugal), to introduce and explain how these problems may be addressed. The paper includes details about practical implementation, along with discussion of options and obtained operational results, showing it to be a good example of human‐machine co‐operation.