KR100210232B1 - Working scheduling method of a shifter for welding - Google Patents

Abstract

The disclosed subject matter relates to a method for optimal scheduling of a moving apparatus for welding that welds a structure to members disposed on a platen. The optimal job scheduling method of the mobile device for welding according to the present invention optimizes the work area and the work order while avoiding collision between the mobile devices through a multi-step process. Therefore, there is an advantage that productivity of automation of welding process is improved and spleen is reduced.

Description

Optimal Job Scheduling Method for Welding Mobile Devices

The present invention relates to a method and apparatus for optimizing the operation of a mobile device for welding predetermined installations to members arranged on a table, and more particularly, to a mobile device for minimizing the cost of collision To an optimal task scheduling method.

Generally, the welding mobile device performs work while moving to the corresponding plate position in accordance with a work procedure plan only within a predetermined work area.

Conventional methods for job scheduling of mobile devices use gantry, robots and AGV as mobile devices. To perform this task, one mobile device is used or a plurality of mobile devices are used. In the case of using a plurality of mobile devices, a conventional work method is a method in which a work area for each mobile device is defined in advance according to a mobile device to be used and a work area, Has been implemented.

However, in the conventional work scheduling method of the mobile device, the work area must be defined in advance in order to perform work using a plurality of mobile devices. Therefore, there is a problem that a collision occurs between mobile devices when a work area is allocated to mobile devices and an operation is performed without defining a detailed work order according to work area allocation.

Accordingly, it is an object of the present invention to solve the above problems and to provide a method for scheduling an optimum operation of a mobile device for welding, which can prevent the mutual impetus during work of the mobile device and schedule an optimal work order.

FIG. 1 is a flowchart illustrating an optimal task scheduling process according to the present invention; FIG.

FIG. 2 is a flow chart for the second clustering phase of the clustering phase of FIG.

According to another aspect of the present invention, there is provided a method for scheduling a welding mobile device for welding members disposed on a base, the method comprising: inputting condition information for inputting information and conditions of the members and each mobile device; A weld line classification and work area setting step of classifying a workable weld line for each of the mobile devices using the information and conditions and setting a work area; A clustering step of distributing the entire work to be performed equally to each mobile device; And a routing step of determining a work order of the jobs distributed in the clustering step so as to avoid the collision of the respective mobile devices.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the embodiments of the present invention.

FIG. 1 is a flowchart illustrating an optimal task scheduling process according to the present invention, and FIG. 2 is a flowchart of a secondary clustering process in a clustering process of FIG.

As shown in FIG. 1, the first step of the optimal task scheduling process according to the present invention is a condition information input step (step 100). In this step (step 100), for optimal scheduling of the mobile device, data is inputted and basic resources are analyzed and processed into information necessary for scheduling. The conditions and information input at this stage include member and weld line information D101, mobile device status information D102, surface information D103, and constraint conditions D104. The double member and weld line information D101 is composed of information on the member and information on the weld line, and this member and weld line information D101 is stored in the member and weld line information storage location M101. The mobile device status information D102 informs the current operating status of whether the mobile feast is down or operating normally, and stores it in the mobile device status information storage location M102. The surface information D103 comprises the size of the surface to which the member is to be placed, the structural information of the mobile device, and the operation time information, and this information D103 is stored in the surface information storage location M103.

In addition to the information D101, D102, and D103, a constraint condition D101 at the time of scheduling according to the provided resources and strategies is also input. By using the information thus stored, the workable weld line is classified and the work area of the base is set. The work weld line classifying step (step 200) for classifying the workable weld lines reflects the member obtained from the information storage sites M101 and M102 and the weld line information D101 and the respective mobile device status information D102, Extract and classify workable seams to avoid collisions. The work area setting step (step 300) of the base is provided with the mobile device status information D102 and the surface information D103 from the information storage locations M101 and M102 to set the workable area of the base. In this step 300, each of the mobile devices has an area to be basically operated. However, if a mobile device is down because a plurality of mobile devices perform an operation, Change. Therefore, the operating states of the respective mobile devices should be considered.

As described above, the weld line is classified by using such information, and the work area of the base is set, and then the clustering step (step 400) is performed in consideration of the constraint D104 according to the predetermined resource or strategy. This step (step 400) is a step of evenly distributing the work amount of the member without considering the collision for each mobile device. The basic direction of the clustering step (step 400) is to allocate predefined works to a predetermined mobile device, and to assign a weld line that should not be divided according to a condition or an instruction, . In addition, it is also possible to allocate such work members within the segmentation range (minimum range that should not be divided), which are likely to be divided due to the work area division, to the mobile apparatuses included in the work area without dividing them .

This clustering step (step 400) is performed in a primary and a secondary order for more accurate clustering. In the primary clustering step, all the workpieces are arranged on the X axis, and each workpiece is separated into a predetermined segmentation region and made small. Then, the estimated work time for each separated work is obtained, and the work time and the total work expected time for each work area are obtained. Then, based on the estimated total operation time, the operation time for the mobile device on the X axis is determined by the number of mobile devices.

In this embodiment, the order of determining the work section goes from the center to the left to the right section, and the work that spans the two divided work areas is assigned to the center of the work. In addition, assigned work and non-dividable work are assigned according to conditions. Then, the total work time allocated to each mobile device is obtained.

In the second clustering step, the work time of each mobile device as a result of the first clustering is compared and the work completion times are adjusted to be the same while changing the operations of the mobile devices within the allowable range of conditions. At this time, the condition is such as minimizing the possibility of collision between mobile devices, and reducing the work time allocated to each mobile device. This second clustering step will be described with reference to FIG. 2 shows a flow chart for the sub-steps of the secondary clustering step in the clustering step of FIG. 1, and the flowchart shown in FIG. 2 shows the steps for minimizing the possibility of collision of each mobile device among a plurality of conditions .

First, a mobile device with the maximum working time is selected (step 421). Thereafter, it is checked whether there is a work over the boundary line of the work area allocated to the mobile device having the maximum work time (step 422). Thus, if it does not exist, the detailed clustering in this condition is finished, and if it exists, the work which is the most out of the work of this boundary line is selected. That is, the weld line having the greatest possibility of collision is selected (step 423). Then, when the selected work is moved to the adjacent area, it is determined whether the maximum working time can be reduced between the working areas (step 424). If the work can not be reduced, the work is clustered again from step 422. If the work can be reduced, the selected work is moved to the adjacent area (step 425). Thereafter, it is determined whether such an operation needs to be continued (step 426). If so, the process starts again from step 421, otherwise the clustering process is terminated.

After the clustering step (step 1, step 400) is performed, the work order of the work items allocated to each mobile device is determined through the routing step (step 500) and the imprubbing step (step 600). The routing step (step 500) schedules the work order of the works while avoiding each collision in consideration of possible collision situations between the mobile devices. For example, the procedure for area-specific scheduling is executed from the left area to the right area, and for the area, the routing is classified into five types of work allocated to collision. Five types are divided into A type work, B type work, C type work, D type work and E type work. Type A work is a work that may collide with the left area, type B work is a work that may collide with the right area, work that has a type C work that both types are likely to collide, and type D work A workpiece and an E type workpiece that are unlikely represent a workpiece assigned to the mobile device by the user's instruction. In the present embodiment, routing is performed in the order of E type work, A type work, C type work, B type work, and D type work. The work order of each workpiece according to each type is selected so that the farther weld line of the adjacent workpiece is selected and the algorithm is operated so as to fit into the routing phase of the position where the minimum cost is reached. In addition, the routing step (step 500) proceeds with minimal cost, and work latency to prevent collisions between mobile devices is also permitted. If such work waiting time occurs during the assignment of E, C, and B workpieces for Type B work and Type B work, the work proceeds to find the optimal Type B, Type D work .

After this routing step (step 500), the Impouring step (step 600) is followed. The imprubbing step (step 600) is a process for determining a work order for each mobile device selected to avoid collision between mobile devices in the routing step (step 500) so that the work order becomes optimal. In this step (step 600), job exchange for each work area is prevented. In this improuting step (step 600), two workpieces are successively selected according to a predetermined work order, and then the existing work costs and the resulting costs are compared with each other by changing the order of the two newly selected workpieces, A work order and a work direction for each mobile device are determined at a minimum cost.

Therefore, the optimal work scheduling method of the moving apparatus for welding according to the present invention is advantageous in that productivity can be improved by improving the efficiency of the welding process automation and reducing the cost by optimizing the work area and the work order through a multi-step process have.

Claims (4)

A work scheduling method for a welding mobile apparatus for welding members disposed on a base, the system comprising: a condition information input step of inputting information and conditions of the members and each mobile apparatus; A sorting line and a work area setting step of classifying a workable work line for each mobile device using the information and conditions and setting a work area; A clustering step of distributing the entire work to be performed equally to each mobile device; And a routing step of determining a work order of the jobs distributed in the clustering step so as to avoid the collision of each of the mobile devices. The method according to claim 1, characterized in that the step of routing further includes an improving step in the rear stage of the routing step of adjusting the work order so that the distributed work of each mobile device for which the work order is determined has an optimal order Wherein the optimal scheduling method of the moving device for welding is performed. 2. The method of claim 1, wherein the clustering step comprises: a primary clustering step of classifying the entire work into a predetermined area according to the conditions of the members and allocating the classified work to each mobile device, ; And a secondary clustering step of comparing the working time of each of the mobile devices allocated in the primary clustering step and adjusting the work completion time of each mobile device so that they substantially coincide with each other, A method of scheduling a job. The method according to claim 1, wherein the routing step determines a work order in consideration of characteristics of jobs distributed to each mobile device.