WO2022102176A1

WO2022102176A1 - Sorting method for electronic component scraps and processing method for electronic component scraps

Info

Publication number: WO2022102176A1
Application number: PCT/JP2021/028211
Authority: WO
Inventors: 勝志青木; 弘河野
Original assignee: Ｊｘ金属株式会社
Priority date: 2020-11-13
Filing date: 2021-07-29
Publication date: 2022-05-19
Also published as: JP2022078835A; TWI807375B; TW202218757A

Abstract

Provided are: an electronic component scrap sorting method with which it is possible to appropriately determine a scrap mixture including multiple types of components; and an electronic component scrap processing method. This electronic component scrap sorting method comprises: a location/shape identification step for identifying the location and shape of each electronic component scrap from among multiple pieces of electronic component scraps having different shapes so as to obtain location/shape identification information that contains location information and shape information of the respective electronic component scraps; a feature analysis step for analyzing at least two features from each of the electronic component scraps so as to obtain feature analysis information; and a sorting step for, on the basis of the location/shape identification information and the feature analysis information, sorting the respective electronic component scraps by predetermined component types by using at least two features associated with one certain type of electronic component scraps that have the same shape and are at the same location.

Description

Classification method of electronic parts waste and disposal method of electronic parts waste

The present invention relates to a method for classifying electronic component scraps and a method for treating electronic component scraps, and the present invention relates to, for example, a method for classifying electronic component scraps and a method for treating electronic component scraps that can be used in a recycling processing process for used electronic / electrical equipment.

In recent years, from the viewpoint of resource protection, it has become more and more popular to recover valuable metals from electronic component scraps such as waste home appliances, PCs, and mobile phones, and efficient recovery methods have been studied and proposed. Has been done.

For example, in Japanese Patent Application Laid-Open No. 9-78151 (Patent Document 1), scraps containing valuable metals such as electronic parts scraps are charged into a self-melting furnace for copper ore smelting, and the valuable metals are retained in the furnace. It describes how to recycle valuable metals, including the process of collecting them on a mat.

According to JP-A-2018-123380 (Patent Document 2), as a method for recovering valuable metals from recycled raw materials containing aluminum, the recycled raw materials are charged into a melting furnace in a copper smelting process, and aluminum is oxidized to form a molten slag layer. A method for treating recycled raw materials is described in which the valuable metal is removed from the system by making it a component of the above, the valuable metal is dissolved in the metal layer or the mat layer, and the dissolved valuable metal is recovered.

Japanese Unexamined Patent Publication No. 9-78151 Japanese Unexamined Patent Publication No. 2018-123380

Ideally, the processing of electronic component scraps should be well separated by crushing into multiple component types suitable for recovery, such as substrates, plastics, metal pieces, copper wire scraps, capacitors, IC chips, and other component types. It is a target. Currently, many sorting processes are classified and processed on the premise that the crushed material is in a state suitable for recovery of valuable resources. For example, in the treatment of electronic component waste, one of the purposes may be to appropriately recover a substrate containing a relatively large amount of valuable metal.

However, at present, there are mixed scraps containing a plurality of types of scraps to be classified, such as scraps including substrates attached to parts such as capacitors and IC chips, and parts scraps including substrates attached to plastics. In the case of such mixed waste, it is difficult to sort by the conventional sorting method. For example, a substrate containing a relatively large amount of plastic in sorting using a metal sorter is relatively sorted as plastic even if the substrate contains a large amount of precious metal to be collected due to the detection sensitivity of the metal sorter or the like. Sometimes. Further, the capacitor to which the substrate is attached is also determined as a capacitor depending on the detection sensitivity of the sorter, so that the capacitor is not recovered as a substrate and the recovery efficiency of the substrate is lowered. As described above, since the content ratio of the valuable metal contained in the electronic component waste differs depending on the raw material, the mixed waste can be efficiently sorted by the conventional sorting method depending on the detection sensitivity of the sorter. The current situation is that there is no such thing.

In view of the above problems, the present disclosure provides a method for classifying electronic component waste and a method for treating electronic component waste, which can appropriately determine a mixed waste containing a plurality of component types from among electronic component waste.

As a result of diligent studies by the present inventor in order to solve the above problems, electronic component scraps are a mixture of two or more types of components such as plastic and metal, and among metals, metal to be recovered as a valuable metal and recovery. Since there are complicated circumstances such as some metals not being collected, it is necessary to detect the characteristics of two or more types of electronic component scraps to be collected. Then, the present inventors identify the position and shape of each electronic component scrap from the plurality of electronic component scraps by the identification means, and then, for each electronic component scrap whose position and shape are identified, each electronic component. It was found that it is effective to analyze two or more characteristics of the waste and classify the component waste using the two or more characteristics associated with the electronic component waste of the same shape and position. rice field.

The embodiment of the present invention completed based on the above findings identifies the position and shape of each electronic component scrap from a plurality of electronic component scraps having different shapes on one side, and position information of each electronic component scrap. In the position shape identification step of obtaining the position shape identification information including the shape information, the feature analysis step of analyzing at least two or more features of each electronic component waste and obtaining the feature analysis information, and the position shape identification information and the feature analysis information. Based on this, an electron including a classification step of classifying each electronic component scrap by a predetermined component type using two or more features associated with one electronic component scrap of the same shape and in the same position. This is a method for classifying component scraps.

In another aspect, the embodiment of the present invention identifies the position and shape of each electronic component scrap from a plurality of electronic component scraps having different shapes, and includes position information and shape information of each electronic component scrap. The position shape identification step for obtaining the position shape identification information, the feature analysis step for obtaining the feature analysis information associated with the position shape identification information by analyzing at least two characteristics of each electronic component waste, and the position shape identification information and the feature analysis information. Based on the above, a classification process for classifying each electronic component scrap by a predetermined component type and classification using two or more features associated with one electronic component scrap having the same shape and the same position. It is a method for processing electronic component waste including an extraction step of extracting electronic component waste to be extracted from a plurality of electronic component waste based on a process classification result and position shape identification information.

According to the present disclosure, it is possible to provide a method for classifying electronic component waste and a method for treating electronic component waste, which can appropriately determine mixed waste containing a plurality of component types from among electronic component waste.

It is a schematic diagram which shows an example of the sorting system which concerns on embodiment of this invention. It is a block diagram which shows an example of the image analysis means which concerns on embodiment of this invention. It is a flow diagram which shows an example of the image analysis processing which concerns on embodiment of this invention. It is a photograph which shows an example of the area detection data. It is a photograph showing an example of multispectral imaging data. It is a photograph which shows the example of the case where the inspection area is assigned to the data which binarized the area detection data of FIG. It is a table which shows the comparison result of the recognition accuracy when the conventional color camera and the camera equipped with the multispectral illumination which concerns on embodiment of this invention are used as an image pickup means. It is a top view which shows an example of the picking apparatus which concerns on embodiment of this invention. It is a perspective view of the robot hand provided in the picking apparatus which concerns on embodiment of this invention. It is a perspective view which concerns on the modification of the robot hand provided in the picking apparatus which concerns on embodiment of this invention. It is a flow diagram which shows an example of the processing method of the electronic component waste which concerns on embodiment of this invention. It is a photograph which shows the example of the simple substance waste (Al waste) of the electronic component waste. It is a photograph which shows the example of the simple substance waste (Fe waste) of the electronic component waste. It is a photograph which shows the example of the mixed waste (Al waste) of the electronic component waste. It is a photograph which shows the example of the mixed waste (Fe waste) of the electronic component waste.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that the embodiments shown below exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention describes the structure, arrangement, etc. of the components as follows. It is not specific to things.

(Sort system)
As shown in FIG. 1, the sorting system 100 according to the embodiment of the present invention has a transport unit 3 provided with a transport surface 30 for transporting electronic component scraps 5, and electronic component scraps 5 transported on the transport surface 30. It includes an image recognition unit 2 for image recognition, and a sorting unit 1 for transporting electronic component scraps 5 from a transport source to a transport destination using a picking robot 10.

Electronic component scrap 5 means scraps of crushed electronic and electrical equipment such as waste home appliances, PCs and mobile phones, and refers to those crushed to an appropriate size after being collected. The crushing for obtaining the electronic component waste 5 may be performed by the processor himself, or may be crushed in the city and purchased.

The crushing method is not limited to a specific device, and may be a shearing method or an impact method, but crushing that does not impair the shape of parts is desirable as much as possible. Therefore, equipment belonging to the category of crushers intended for fine crushing is not included. Although not limited to the following, the electronic component scrap 5 in the present embodiment typically uses scrap crushed to a particle size of 10 mm or more and 100 mm or less, and more typically 15 mm or more and 50 mm or less as a raw material. Is preferable.

As the electronic component waste 5, the electronic component scrap 5 after being sorted by using any of a magnetic force sorter, a color sorter, a metal sorter, an optical sorter including an infrared sensor, and a plastic sorter is preferable. Can be adopted for.

In particular, the electronic component waste 5 includes component waste (for example, substrate, plastic, metal piece, copper wire waste, capacitor, IC chip, etc.) or outside the system, which is a raw material for smelting suitable for recovery in the smelting process described later. The raw material scraps (heat sink, housing, iron (Fe) scraps, aluminum (Al) scraps, stainless steel (SUS) scraps, synthetic resins, etc.) are contained in a single state (that is, the main parts are contained in one component scrap). A single waste having a ratio of 90% or more by weight) and a mixed waste in which these plurality of component wastes are mixed are included.

The single waste is not limited to the following, but is, for example, Al waste including a silver-white heat sink or a housing as shown in FIG. 12 (a), and black as shown in FIG. 12 (b). Al scrap containing a heat sink or housing, as shown in FIG. 12 (c), a capacitor having a cylindrical shape and exhibiting black or blue, and an iron core exhibiting black or gray as shown in FIG. 13 (a). Fe scraps containing, screws and springs having a silver color as shown in FIG. 13 (b) are included.

Examples of the mixed waste include a heat sink with an IC as shown in FIG. 14 (a), a capacitor with a substrate as shown in FIG. 14 (b), and aluminum waste with a copper wire as shown in FIG. 14 (c). An iron core with a copper coil as shown in 15 (a), an iron scrap or iron core with a substrate as shown in FIG. 15 (b), a substrate with a lead wire as shown in FIG. 5 (c), and the like are included. The simple substance scraps as shown in FIGS. 12 (a) to 13 (b) can be appropriately sorted to some extent by appropriately adjusting the sorting accuracy of the smelter, but FIGS. 14 (a) to 14 (a) to FIG. As for the mixed waste as shown in 15 (c), it may be difficult to properly sort the mixed waste because the smelting raw material and the non-system raw material are mixed.

The electronic component waste 5 is transported on the transport surface 30 from the transport source along the transport direction, and the image analysis means 20 included in the image recognition unit 2 performs image analysis processing. As shown in FIG. 2, the image analysis means 20 includes an image pickup means 21 for capturing an image of electronic component scraps 5 in an image pickup area set on the transport surface 30, and a control means for controlling various operations of the image pickup means 21. The 200, a storage device 210 for storing information necessary for the operation of the control means 200, and an input means 120 and an output means 130 capable of inputting / outputting information necessary for the control means 200 can be provided.

The image pickup means 21 irradiates a plurality of electronic component scraps 5 in the imaging area with light having different wavelengths (multispectral light) to obtain two or more spectral information on the electronic component scraps 5. A unit (not shown) and a multi-spectral imaging unit (multi-camera unit: not shown) for imaging electronic component scraps 5 in an imaging area irradiated with light of different wavelengths are provided. The image pickup control means 201 extracts the multispectral image pickup data captured by the multispectral image pickup unit and stores it in the multispectral image pickup data storage means 211.

The image recognition unit 2 may include a region detection unit 23 that irradiates the electronic component waste 5 in the imaging area with region detection light to acquire region detection data. The area detection includes detecting the area (existing area) of the electronic component waste 5 existing in the image pickup area of the image recognition unit 2 by the image recognition process, whereby the contour of the object can be clearly recognized. .. Specifically, it is obtained by binarizing the area detection data which is an image of the imaging area including the electronic component scraps 5, whereby the position, the number, and the contour of the electronic component scraps 5 existing in the imaging area are obtained. (Shape) and area are clarified. For example, if the position of any electronic component scrap 5 in the sorting unit 1 matches the position of the specific electronic component scrap 5 in the area detection data obtained by the image recognition unit 2, they are the same. Can be identified.

The specific configuration of the region detection unit 23 is not particularly limited, but for example, a light source that irradiates an object in the imaging area with region detection light such as visible light, infrared light, or ultraviolet light, and region detection light. It can be provided with a detector or the like for detecting an object in the image pickup area illuminated by. The area detection data is stored in the area detection data storage means 212. If the area detection data can be produced in place of the area detection unit 23 by the multispectral illumination unit and the multispectral image pickup unit included in the image pickup means 21, the area detection unit 23 may be omitted.

The control means 200 identifies, for example, the position and shape of each electronic component scrap 5 from among a plurality of electronic component scraps 5 having different shapes from the image pickup control means 201 that controls the image pickup means 21 and the area detection unit 23. The position and shape identification means 202 that obtains the position and shape identification information including the position information and the shape information of each electronic component waste 5, and the feature analysis means 203 that analyzes at least two or more features of each electronic component scrap 5 and obtains the feature analysis information. And, based on the position shape identification information and the feature analysis information, each electronic component scrap 5 is predetermined by using two or more features associated with one electronic component scrap 5 having the same shape and the same position. It is provided with a classification means 204 for classifying by the type of parts, an identification information producing means 205 for producing identification information for each electronic component waste 5, and a movement following means 207.

In the storage device 210, the multispectral imaging data storage means 211 for storing the multispectral imaging data for the electronic component waste 5, the area detection data storage means 212 for storing the area detection data, and the image analysis means 20 are images. Identification information of each component scrap 5 based on the characteristics of the color characteristic information storage means 213, the classification information storage means 214, and the electronic component scrap 5 that store the color characteristic information based on the color included in the electronic component scrap 5 to be analyzed. The identification information storage means 215 for producing the above is provided.

The control means 200 is connected to the server 25 or another sorting system 24 via the network 22 so that the image analysis result of the electronic component waste 5 analyzed by the image analysis means 20 of FIG. 2 can be shared with each other. May be good.

The image analysis means 20 can proceed with the image analysis process according to, for example, the procedure shown in FIG. For example, as shown in step S100 of FIG. 3, the image pickup control means 201 controls the area detection unit 23 to irradiate the electronic component waste 5 conveyed in the image pickup area with the area detection light for area detection. An object in the image pickup area illuminated by light is detected, and the area detection data of the electronic component waste 5 conveyed in the image pickup area is imaged (see FIG. 4). The area detection data is stored in the area detection data storage means 212.

In step S101, the multispectral illumination unit included in the image pickup means 21 irradiates the electronic component scrap 5 in the image pickup area with multispectral illumination light having a different wavelength, and the multispectral image pickup unit performs a plurality of multispectral illuminations having different illumination colors. Obtain the imaging data (see FIGS. 5 (a) to 5 (h)). Here, for example, multispectral imaging data of eight colors of illumination light of white, ultraviolet (UV), blue, green, orange, red, far infrared color (FR), and infrared (IR) can be obtained. The multispectral imaging data is stored in the multispectral imaging data storage means 211.

In step S102, the position / shape identification means 202 of FIG. 2 detects the position and shape of the electronic component waste 5 existing in the imaging area based on the area detection data. For example, the position / shape identification means 202 binarizes the imaged data in FIG. 4 to clarify the shade between the outer diameter of the electronic component waste 5 and the background (see FIG. 5), and to create an image in which the shade is clarified. Based on this, the black figures that emerge on the white background are extracted as the electronic component scraps 5 to be detected. For example, in the example of FIG. 6, there are three lumps on a white background. Therefore, the position shape identification means 202 detects three electronic component scraps 5 in the image pickup data. By detecting the number of electronic component scraps 5 existing in the imaging area using the area detection data, the position and shape (area (number of pixels)) of the electronic component scraps 5 can be detected more appropriately.

In step S103, the feature analysis means 203 sets the first to

third inspection areas

51, 52, and 53 so that only one electronic component waste 5 is included in each inspection area. For example, in the example of FIG. 6, the feature analysis means 203 can set the first, second, and

third inspection areas

51, 52, and 53. Further, the feature analysis means 203 further sets the multispectral imaging data and the electronic component scraps 5 registered in advance in the color characteristic information storage means 213 for the electronic component scraps 5 in the first to third inspection areas 51 to 53. At least two or more features of each electronic component scrap 5 are analyzed based on the identification information for identifying a plurality of component types included in the above, and feature analysis information is obtained.

The feature analysis information for analyzing the features of the electronic component scrap 5 can include color characteristic information, and the color characteristic information can include at least the extracted color information and the extracted color area information. The extracted color information includes information including setting values of each value such as hue, saturation, and lightness of typical colors included in the smelting raw material or the extrasystem raw material. When the extracted color area information includes the "extracted color" preset by the user in the electronic component scrap 5 in the inspection area, the electronic component scrap 5 is determined to be a smelting raw material or a non-system raw material. Contains information on the area threshold (area ratio setting value). The feature analysis means 203 analyzes the ratio of the specific color of the electronic component scraps to the area occupied by the specific color with respect to the total area of the electronic component scraps 5 to determine the smelting raw material or the non-system raw material. By comparing with the threshold value, the characteristics of the smelting raw material or the extrasystem raw material can be analyzed. Information on the threshold value of the area for determining the smelting raw material or the non-system raw material can be input in advance.

As the color characteristic information, a material containing valuable resources contained in the smelting raw material to be collected, for example, wire scrap (copper color, gold color), metal waste such as brass (copper color, gold color), IC or LSI. (Black, gold, green), substrate containing valuable metal (green, brown, black, white), connector insertion slot containing copper wire (white), capacitor and heat sink containing a certain amount or more of valuable metal (silver, White, black) etc. are included. Non-system raw materials include metal scraps (glossy silver), plastics (white, black, brown) that are not suitable for recovery in the smelting process such as iron, aluminum, and stainless steel, capacitors that do not contain more than a certain amount of valuable metals, and Includes heat sinks, etc. (silver, white, black).

As the extraction color information for reducing the misrecognition of these smelting raw materials and non-system raw materials as much as possible and improving the recognition accuracy, at least the white, green, black, gold, and copper colors of the smelting raw materials and the non-system raw materials are used. It is preferable to include it as information of "extraction color" used for determining the extraction of the object to be sorted. In a more preferable embodiment, it is preferable to include white, green, black, gold, copper, brown, and silver as information of at least the "extraction color" used for determining the extraction of the selection target.

Among various extraction colors, black is a color that can be contained in both smelting raw materials and non-system raw materials, and is an extraction color that is particularly prone to misrecognition. Therefore, in the present embodiment, it is preferable that the extracted color area information used as the feature analysis information includes two or more threshold values for the black area. For example, when a first threshold value and a second threshold value larger than the first threshold value are set, among the electronic component scraps 5 having black color, those below the first threshold value are unevenness of the electronic component scraps 5. Since it is considered that it was only affected by the shadow that can be formed, it can be set as a "sorting target" to be extracted as a raw material for smelting. Those between the first and second threshold values are considered to detect the regulator (IC) attached to the heat sink, and therefore should be left on the transport surface 30 as an extrasystem raw material. ". Those having a value equal to or higher than the second threshold value are considered to be black-painted metal scraps, and therefore can be set as "sorting objects" as smelting raw materials. As described above, by providing the extraction color area information with a threshold value of the area ratio of black of 2 or more, erroneous recognition when selecting the smelting raw material and the non-system raw material from the electronic component waste 5 is reduced and recognized. The accuracy can be improved.

For example, when sorting "smelting raw materials" such as substrate scraps as sorting objects (those that are picked up (extracted) and removed from the transport surface 30), the classification means 204 is preset as "smelting raw materials". Based on the extracted color information and the extracted color area information, whether or not the electronic component waste 5 in the inspection area satisfies the condition of the "smelting raw material" is classified by collating with the multispectral imaging data. When the electronic component scrap 5 in the inspection area satisfies the condition of the "smelting raw material", the electronic component scrap 5 is classified as a "smelting raw material" to be removed by the sorting process described later.

As step S104, the classification means 204 identifies the multispectral imaging data and the smelting raw material and the non-system raw material registered in advance in the color characteristic information storage means 213 for the electronic component waste 5 in each inspection area. Based on the color characteristic information of, the object to be not sorted (selection exclusion: either smelting raw material or extrasystem raw material) is determined.

In step S105, the identification information creating means 205 creates the identification information based on the setting result of the selection target and the selection exclusion. The identification information includes information on whether the electronic component waste 5 in each inspection area is an object to be sorted or a non-target object to be sorted, and the position, color, area, major axis and minor axis of the object. Information such as the orientation and center of gravity is included. The identification information is stored in the identification information storage means 215.

According to the embodiment of the present invention, the imaging means 21 provided with multispectral illumination for imaging the electronic component scrap 5 in the imaging area to obtain multispectral imaging data, and the multispectral imaging data are registered in advance. The image analysis means 20 is provided with an image analysis means 20 for identifying a smelting raw material or a non-system raw material based on color characteristic information of a smelting raw material and a non-system raw material and obtaining identification information including position information of the smelting raw material or the non-system raw material. As a result, the recognition accuracy of the electronic component waste 5 can be improved as compared with the case where an image pickup means using a conventional color camera is provided.

For example, among the electronic component scraps 5 used as extrasystem raw materials, for example, metal scraps such as iron, aluminum, and stainless steel have a metallic luster, so that they look white due to halation in a conventional color camera and have a silver recognition area. It may become smaller and the recognition rate of the object may decrease. On the other hand, if the extraction color is expanded to white silver in an attempt to reduce the erroneous recognition rate, the white silver contained in the substrate waste of the smelting raw material is erroneously detected.

According to the present embodiment, the imaging means 21 provided with the multispectral illumination unit can obtain a plurality of multispectral imaging data in which the influence of halation is suppressed. Therefore, the electrons contained therein are used by using the multispectral imaging data. By comparing the component scrap 5 with the color characteristic information including the information of the extracted color registered in advance, the influence of halation can be reduced and the misrecognition of the color possessed by the electronic component scrap 5 can be suppressed.

In addition, in a conventional color camera, the uneven metal object looks black in a wide range in the darkened part due to the reflection of light, and the silver recognition area exhibited by the metal becomes small, so that the recognition rate may decrease. According to the present embodiment, since the image pickup means 21 provided with the multispectral illumination unit can recognize a subtle color difference, it is possible to suppress the influence of shadows and make the silver recognition area exhibited by the metal closer to reality. Can be done.

In addition, in a conventional color camera, since it is passed through a color filter, black silver such as stainless steel has a reduced spectral intensity of metal and looks black, and the recognition area of silver is reduced, so that the recognition rate may decrease. According to the present embodiment, the image pickup means 21 provided with the multispectral illumination unit makes it possible to recognize a black-silver metal such as stainless steel. Further, the metal scraps painted in black can be identified by ignoring the influence of painting by evaluating using the multispectral imaging data of the wavelength in the infrared region.

FIG. 7 shows a case where a conventional color camera is used as an image pickup means 21 when two types of metal scraps and two types of plastics are processed as the electronic component scraps 5 to be image-analyzed by the image recognition unit 2 of FIG. , An example of the comparison result when the camera irradiating the multispectral illumination light is used as the image pickup means 21 is shown.

In the case of metal scraps (1) that emit white reflected light by irradiation with conventional illumination light, in a color camera, it is confused with white plastic, which is an external raw material, and misrecognition occurs. On the other hand, when the image pickup means 21 that irradiates the multispectral illumination light is used, it can be recognized as substrate waste which is a raw material for smelting. Similarly, in the case of metal scrap (2) that emits green reflected light by irradiation with illumination light, it is confused with a green plastic substrate which is an external raw material in a color camera, and misrecognition occurs. On the other hand, when the image pickup means 21 that irradiates the multispectral illumination light is used, it can be recognized as substrate waste which is a raw material for smelting.

In the case of plastic (1) whose appearance is very dirty, it is confused with brown substrate waste, which is a raw material for smelting, in a color camera, and misrecognition occurs. On the other hand, when the image pickup means 21 that irradiates the multispectral illumination light is used, it can be recognized as a plastic as an external raw material. In the case of red plastic (2), in a color camera, it is confused with copper wire scrap which is a raw material for smelting, and misrecognition occurs. On the other hand, when the image pickup means 21 that irradiates the multispectral illumination light is used, it can be recognized as a plastic as an external raw material.

As shown in FIG. 2, the control means 200 may include the movement following means 207. When the transport unit 3 is continuously moved to continuously move the electronic component waste 5 on the transport surface 30, the position may be displaced between the first and last imaging data. In the present embodiment, when the electronic component scrap 5 continuously moving along the transport direction is identified by image analysis, as a step of identifying by image analysis, immediately before imaging the region detection light and the multispectral illumination light. Immediately after that, the reference light is applied to the electronic component scrap 5 in the imaging area. As the reference light, white light of multispectral illumination can be used. By correcting the positional deviation of the imaged data due to the movement of the electronic component scraps 5 based on the imaged data irradiated with the reference light, the transport unit 3 can be continuously operated, so that the processing efficiency is improved.

The electronic component waste 5 after the image analysis process is performed by the image recognition unit 2 is sent to the sorting unit 1 shown in FIG. The sorting unit 1 is not particularly limited as long as it has a device for sorting objects on the transport surface 30. For example, a sorting device using air injection, an electric paddle, a suction mechanism, a robot hand, or the like can be used. In one embodiment, the sorting unit 1 is connected to a picking robot 10 that transports an object on the transport surface 30 from the transport unit 3 to the transport unit 4, and the picking robot 10, and is connected to the picking robot 10 from among the electronic component scraps 5. It is provided with a robot hand 11 that grips a smelting raw material or a non-system raw material as an object. The picking robot 10 picks out an object based on the identification information generated by the image recognition unit 2.

The picking robot 10 is not particularly limited as long as it is an industrial robot having a function of grasping and transporting an object, and various types of industrial robots can be used. For example, as the picking robot 10, a robot having various methods such as a orthogonal type, an articulated type, and a parallel link type can be used. The orthogonal robot is a simple robot composed of two or three slide axes. Articulated robots can be either vertical or horizontal, and the vertical type has a wide range of motion due to the rotation of the pedestal and the movement of the arm, and is capable of three-dimensional movement with a high degree of freedom. The horizontal robot has all the axes of rotation of the joints vertically aligned, and has a simpler structure than the vertical articulated robot. The parallel link type robot is an industrial robot having a parallel link structure in which joints are arranged in parallel.

Among them, the parallel link type robot moves to the target position in the shortest distance by the parallel link mechanism, so it moves to the position of the object to be extracted with high speed and high accuracy, grips the substance, and moves to the predetermined position at high speed. Among various industrial robots that can be used as the picking robot 10, it can be particularly preferably used because it can be sent to.

Although not limited to the following aspects, as shown in FIG. 8, the picking robot 10 is typically in a direction perpendicular to the transport direction so as to cross the transport surface 30 of the transport unit 3. The object can be extracted from the transport unit 3 toward the transport destination of the transport unit 4 having a transport direction. The transport unit 4 can be configured by a conveyor or the like.

In this way, the transport unit 3 and the picking robot 10 are arranged close to each other, and the picking robot 10 is configured to discharge the object in a direction crossing the transport direction of the transport unit 3 to eject the object. It can be accurately removed from the electronic component waste 5 in a short time and transported.

(Robot hand)
As shown in FIG. 9A, the robot hand 11 included in the picking robot 10 is provided with a suction pad 13a for sucking an object and a vacuum generator 13b connected to the suction pad 13a in the central portion. 13, a holding portion 14 (first to fourth arm portions 14a to 14d) for sandwiching an object to be sucked by the suction pad 13a, and a fixing portion 12 for fixing the suction portion 13 and the holding portion 14. To prepare for. One end of the fixing portion 12 is fixed to the picking robot 10, and the holding portion 14 is fixed to the other end. The suction pad 13a is made of an elastic member such as rubber or silicon, and projects downward (on the transport surface 30 side).

The sandwiching portion 14 is not particularly limited as long as it can sandwich an object. The sandwiching portion 14 may include, for example, a first arm portion 14a, a second arm portion 14b, a third arm portion 14c, and a fourth arm portion 14d. The base end portions of the first to fourth arm portions 14a to 14d are connected to a drive mechanism (not shown) in the fixed portion 12, respectively.

As shown in FIG. 9B, the first arm portion 14a and the second arm portion 14b receive power transmitted from the drive mechanism, and the direction V toward or away from the central axis X of the suction pad 13a. It can be opened and closed in conjunction with W. The third arm portion 14c and the fourth arm portion 14d located in the depth direction of the paper surface in FIG. 9B are also from the air chucks (not shown) connected to the first to fourth arm portions 14a to 14d. Upon receiving the transmission of power, the suction pad 13a can be opened and closed in conjunction with the direction V approaching the central axis X and the direction W moving away from it. The first to fourth arm portions 14a to 14d can be opened and closed at the same timing, whereby the suctioned object is sandwiched or released by the tip portion of the suction pad 13a.

It is preferable that the tips of the first to fourth arm portions 14a to 14d are provided with claw portions 141a to 141d protruding toward the central portion where the suction pads 13a are arranged, respectively. Since the first to fourth arm portions 14a to 14d are provided with the claw portions 141a to 141d, respectively, it is possible to more accurately grip the object while suppressing the fall of the object.

It is preferable that the claw portions 141a to 141d are formed so as to have a tapered shape toward the suction pad 13a side. As a result, the claw portions 141a to 141d can come into contact with the bottom surface of the object to facilitate scooping up of the object.

As shown in FIG. 9B, the tip portions (lowermost end portions) of the claw portions 141a to 141d are arranged at a position relatively lower than the tip portion of the suction pad 13a, that is, a position closer to the transport surface 30. Is preferable. As a result, the object whose claws 141a to 141d are sucked by the suction pad 13a can be easily picked up from the transport surface 30 and pinched.

Further, as shown in FIG. 10, the claw portion 141a of the first arm portion 14a and the claw portion 141d of the fourth arm portion 14d are connected, and the claw portion 141b of the second arm portion 14b and the third arm portion are connected. The claw portion 141c of 14c may be connected. With this configuration, it is possible to more appropriately grip a long object including a substrate or the like in the electronic component waste 5.

Further, by changing the lengths of the claw portions 141a to 141d according to the shape of the object, a smaller object can be gripped more reliably. The length L (see FIG. 9A) of the claw portions 141a to 141d along the direction parallel to the opening / closing direction of the first to fourth arm portions 14a to 14d is the electronic component waste 5 according to the present embodiment. In the case of treatment, it is preferably 5 mm or more, more preferably 10 mm or more, and further preferably 15 mm or more. The upper limit depends on the dimensions of the robot hand 11, but can be, for example, 40 mm or less, further 30 mm or less. The length D (see FIG. 9B) of the claw portions 141a to 141d along the direction perpendicular to the opening / closing direction of the first to fourth arm portions 14a to 14d is the electronic component waste 5 according to the present embodiment. In the case of treatment, it is preferably 5 mm or more, more preferably 10 mm or more, and further preferably 20 mm or more. The upper limit depends on the dimensions of the robot hand 11, but can be, for example, 40 mm or less, further 30 mm or less.

According to the robot hand 11 included in the picking robot 10 according to the embodiment of the present invention, the suction pad 13a for sucking the object and the first to fourth arm portions 14a for sandwiching the object sucked by the suction pad 13a. A holding portion 14 including 14d is provided, and the object is first sucked by the suction pad 13a, and then the object is gripped by the first to fourth arm portions 14a to 14d (see FIG. 9C). As a result, even heavy objects that are difficult to pick with the suction force of the suction pad 13a can be sandwiched and carried by the holding portion 14, so that the electronic component scraps 5 having various shapes can be more reliably and appropriately conveyed. be able to.

In particular, the board scraps and the like have ICs and wiring laid on the board and are heavy, and when gripped by either the suction pad 13a or the first to fourth arm portions 14a to 14d, they fall during transportation. May occur. According to the picking apparatus according to the embodiment of the present invention, among the electronic component scraps 5 in which various raw materials are mixed, scraps such as substrate scraps having a large specific density and various sizes can be removed more reliably. Therefore, it is possible to appropriately select a target object in a large amount.

The opening / closing speed of the first to fourth arm portions 14a to 14d can be adjusted according to the transport speed of the transport surface 30. Further, it is preferable that the distance between the object to be picked and another adjacent object by the first to fourth arm portions 14a to 14d is 5 mm or more, more preferably 10 mm or more. Thereby, the object can be gripped more appropriately by using the first to fourth arm portions 14a to 14d.

(How to dispose of electronic component waste)
FIG. 11 shows an example of a method for treating electronic component waste 5 according to an embodiment of the present invention. The method for treating electronic component scraps according to an embodiment of the present invention is a step of treating electronic component scraps 5 by at least two-step wind sorting (S2, S4) and a metal sorting step (S6) using a metal sorter. At least the step of sorting the scraps can be included.

According to the processing method according to the embodiment of the present invention, in the initial stage of physical sorting, the wind power sorting is first divided into two stages (S2, S4), as compared with the case where the magnetic force sorting is performed at the initial stage. Therefore, the loss of valuable metal can be suppressed, and a large amount of electronic component waste 5 can be sorted and processed at once while concentrating more valuable metal. Then, after the two-step wind power sorting, the smelting inhibitor is removed while increasing the processing amount of the electronic component waste 5 by combining the sorting treatment (S6) using the metal sorter which takes time for the treatment. Valuable metals can be recovered efficiently.

In one embodiment, the method for treating the electronic component waste 5 according to the embodiment of the present invention includes a pre-sorting step (S1) for removing massive copper wire dust from the electronic component scrap 5, and an electronic component after pre-sorting. The wind sorting step (S2), in which the scrap 5 is wind-sorted to move the powdery and film-like scraps to the lightweight material side and removed, and the heavy material obtained by the wind-sorting are screened and linear (long). ) Valuable metals such as copper using a color sorter from the sieving step (S3) for removing copper wire scraps, the second stage wind sorting step (S4), and the electronic component scraps 5 after removing the linear copper wire scraps. Includes a color sorting step (S5) for removing substrate scraps containing the above, and a metal sorting step (S6) for further removing substrate scraps containing valuable metals such as copper from the electronic component scraps 5 after the color sorting step using a metal sorter. be able to.

By providing a sieving step (S3) between the first-stage wind sorting step (S2) and the second-stage wind sorting step (S4), the wire dust contained in the electronic component waste 5 can be removed. can. In the sieving step, it is preferable to use a sieving machine having a slit-shaped sieving. In the sieving step (S3), powdery substances can be removed in addition to wire chips by sieving. By sending the powdered material and copper wire waste after sieving to the smelting process via the pre-incinerator treatment process, the valuable metal in the component waste can be recovered more efficiently. Further, by carrying out the color sorting step (S5) after the wind sorting step (S4), the metal content ratio of the object to be processed sent to the metal sorting step (S6) can be reduced, so that the metal sorting step (S6) can be performed. The sorting step in S6) can be made higher.

Furthermore, some of the substrates to be processed in the copper smelting process may be mixed in the heavy material obtained in the second stage wind power sorting process (S4). Therefore, the heavy objects obtained in the second stage wind sorting step (S4) should be further classified by magnetic force sorting, eddy current sorting, color sorter, hand sorting, robots, etc., and processed in the copper smelting step. Since the substrate can be separated and sent to the smelting process, the recovery efficiency of valuable metals is improved.

For example, the heavy material obtained in the second stage wind power sorting step (S4) is sent to the magnetic force sorting step (S8) through the pre-sorting step (S7). In the magnetic force sorting step (S8), raw materials containing iron are removed from heavy objects as extrasystem raw materials in the smelting process. After the magnetic force sorting step (S8), an eddy current sorting step (S9) is performed, and further, a pre-sorting step (S10) is performed to remove aluminum, synthetic resins (plastics), debris containing SUS, etc., and the residue remains. Send the scraps of the substrate to the smelting process.

In the method for treating electronic component waste 5 according to the embodiment of the present invention, the sorting system 100 shown in FIG. 1 is subjected to a pre-smelting step (S1, S7) before or after the wind smelting step (S2, S4), or a vortex current. By introducing it into the pre-sorting step (S10) after the sorting step (S9), the smelting raw material containing the valuable metal that can be processed in the smelting step or the noble metal is not contained in the electronic parts waste 5 and , Iron, aluminum, stainless steel, synthetic resin, and other external raw materials can be processed efficiently and quickly. As a result, the electronic component waste 5 can be sorted more efficiently as compared with the case where manual sorting is applied, and a larger amount of the electronic component scrap 5 can be mechanically processed.

Further, the method for treating electronic component waste 5 according to the present embodiment is not limited to the above-mentioned pre-sorting steps (S1, S7, S10), and can be appropriately combined and used for each sorting process. .. For example, before or after processing the electronic component waste 5 in various sorting steps (S3 to S6, S8 to S9), the image recognition unit 2 performs image recognition when necessary, and FIGS. 9 (a) to 10 show. It is also preferable to perform a sorting process for extracting an object by using a sorting device including the robot hand 11 shown.

In particular, raw materials sorted as extrasystem raw materials in the pre-sorting step (S7), magnetic force sorting step (S8), eddy current sorting step (S9), and pre-sorting step (S10) include smelting as well as single raw materials. There are many mixed scraps in which raw materials and non-system raw materials are mixed. The composite waste is subjected to the image recognition process according to the present embodiment, and the sorting process for extracting the object using the sorting device provided with the robot hand 11 shown in FIGS. 9 (a) to 10 is performed. Since the work that was conventionally performed manually can be mechanized, the sorting process can be speeded up, and the mixed waste from the single waste in the non-system raw material and the mixed waste containing the smelting raw material can be used. Alternatively, it becomes possible to appropriately determine the single waste.

Further, for example, the component scraps containing Al in the heavy material sorted in the wind force sorting step (S4) are sorted as Al scraps on the external raw material side by the eddy current sorting step (S9). Includes not only simple substance of Al as shown in FIGS. 12 (a) to 12 (c) but also mixed waste containing Al as shown in FIGS. 14 (a) to 14 (c). Therefore, for the Al scraps sorted in the eddy current sorting step (S9), the characteristics of the parts scraps are analyzed by using the sorting method according to the present embodiment, and further, the robot hands shown in FIGS. 9A to 10A. By performing a sorting process for extracting an object using a sorting device provided with 11, the simple substance of Al as shown in FIGS. 12 (a) to 12 (c) and the single waste of Al and FIGS. 14 (a) to 14 (c) ) Can be sorted out from the mixed waste containing Al. Then, by putting the selected mixed waste into the smelting process as a smelting raw material containing valuable resources, the recovery efficiency of the valuable resources can be improved.

Parts scraps containing Fe in heavy objects sorted in the wind power sorting step (S4) are sorted as Fe scraps as an external raw material by the subsequent magnetic force sorting step (S8). The Fe scraps selected here include single iron scraps containing Fe as a single substance as shown in FIGS. 13 (a) and 13 (b), as well as those shown in FIGS. 15 (a) to 15 (c). This includes iron cores with copper coils, iron scraps with substrates or iron cores, or mixed iron scraps such as substrates with lead wires, to which other component scraps are attached to such Fe. Therefore, for the Fe waste treated in the magnetic force sorting step (S8), the treatment method according to the present embodiment is used, and by discriminating these for each characteristic of the component, Fe containing elemental iron waste and mixed iron waste is used. A predetermined mixed iron scrap can be extracted from the scrap. By sorting the iron scraps judged to be mixed iron scraps to the valuable resources side (smelting raw materials side) by picking or the like, the recovery efficiency of the valuable resources can be improved.

(Smelting process)
The method for treating electronic component waste 5 according to the embodiment of the present invention further includes a smelting step for smelting a processing raw material containing a valuable metal sorted in each physical sorting step (S1 to S10).

When recovering copper as a valuable metal, smelting is performed using a smelting furnace. The smelting step includes, for example, a step of incinerating the electronic component waste 5, a step of crushing and sieving the incinerated product, and a step of smelting the crushed and sieved processed product into copper. Depending on the processing capacity of the smelting process, the step of incinerating the electronic component waste 5 may be omitted.

In the smelting process, any method can be selected for the step of crushing and sieving the electronic component waste 5 as long as it is a process of molding the electronic component waste 5 into a size preferable for the smelting process. By performing the physical sorting step shown in FIG. 11 before the incineration step, the crushing and sieving step in the smelting step, iron, aluminum, which are smelting inhibitors while recovering valuable metals more efficiently, Raw materials containing either stainless steel or synthetic resin can be efficiently sent out of the system.

Although not limited to the following, the copper smelting process using the flash smelting furnace method can be preferably used as the smelting process according to the present embodiment. As a copper smelting process using the flash smelting method, for example, copper concentrate, a solvent, and electronic component waste 5 are charged from the ceiling of the shaft of the flash smelting furnace. The charged concentrate and electronic component waste 5 melts on the shaft of the flash smelting furnace, and in the setler of the flash smelting furnace, for example, a mat containing 50 to 68% copper and slag floating above the mat. Be separated. Valuable metals such as copper, gold, and silver in electronic / electrical equipment parts are absorbed by the mat that stays in the flash smelting furnace, so that the valuable metals can be recovered from the electronic parts waste 5.

In copper smelting, in order to produce copper and recover more precious metals such as gold and silver, as much as possible of electronic parts waste 5 containing a large amount of valuable metals such as copper, gold and silver is added as a raw material to be processed. It is important to process it. On the other hand, the electronic component waste 5 contains a substance that affects the quality of products and by-products in copper smelting and / or a smelting inhibitor that affects the process of copper smelting. For example, if the amount of a substance containing an element such as Sb or Ni as described above into a smelting furnace is large, the quality of electrolytic copper obtained by copper smelting may deteriorate.

Also, in non-ferrous metal smelting processes such as copper smelting, sulfuric acid is produced from sulfur dioxide generated by the oxidation of concentrates, but if sulfur dioxide is mixed with sulfur dioxide, the produced sulfuric acid may be colored. Examples of the mixing source of hydrocarbons include synthetic resins such as plastics, but depending on the composition of the electronic component waste 5 brought into copper smelting, such synthetic resins may be contained in large amounts. Synthetic resins may cause rapid combustion in the smelting furnace, smoke leakage, and equipment deterioration due to local heating.

Furthermore, if Al, Fe, etc. are present in the smelting furnace at a concentration above a certain level, for example, the slag composition may be changed in the copper smelting process, which may affect the loss of valuable metals to slag, so-called slag loss. .. Further, if a large amount of halogen elements such as Cl, Br, and F are contained in the electronic component waste 5 charged into the smelting furnace, it may cause corrosion of the exhaust gas treatment equipment for copper smelting and deterioration of the sulfuric acid catalyst. .. Such a problem of smelting inhibitory substances becomes apparent as the amount of electronic component waste 5 processed increases, and there is a problem that the smelting process is burdened.

According to the method for treating electronic component waste 5 according to the embodiment of the present invention, a physical sorting step for electronic component waste 5 as shown in FIG. 11 is provided before the smelting process. As a result, the ratio of smelting inhibitors brought into the smelting process is suppressed as much as possible, the amount of electronic parts waste 5 processed is increased, and the ratio of electronic parts waste 5 containing copper and valuable metals is increased to increase the ratio of copper and valuable metals. Can be efficiently recovered.

Although the present invention has been described in accordance with the above embodiments, the statements and drawings that form part of this disclosure should not be understood to limit the invention. That is, the present disclosure is not limited to the above embodiment, and the components can be modified and embodied without departing from the gist thereof.

1 ... Sorting unit 2 ... Image recognition unit 3 ... Transfer unit 4 ... Transfer unit 5 ... Electronic parts waste 10 ... Picking robot 11 ... Robot hand 12 ... Fixing unit 13 ... Suction unit 14 ... Holding unit 13a ... Suction pad 13b ... Vacuum generation Vessels 14a to 14d ... Arm unit 20 ... Image analysis means 21 ... Imaging means 22 ... Network 23 ... Area detection unit 24 ... Sorting system 25 ... Server 30 ...

Transport surface

51, 52, 53 ... Inspection area 100 ... Sorting system 120 ... Input Means 130 ... Output means 141a-141d ... Claw portion 200 ... Control means 201 ... Imaging control means 202 ... Position shape identification means 203 ... Feature analysis means 204 ... Classification means 205 ... Identification information production means 207 ... Movement tracking means 210 ... Storage device 211 ... Multispectral imaging data storage means 212 ... Area detection data storage means 213 ... Color characteristic information storage means 214 ... Classification information storage means 215 ... Identification information storage means

Claims

A position-shape identification step of identifying the position and shape of each electronic component waste from a plurality of electronic component scraps having different shapes and obtaining position-shape identification information including position information and shape information of each electronic component waste.
A feature analysis process that analyzes at least two features of each electronic component waste and obtains feature analysis information.
Based on the position shape identification information and the feature analysis information, each electronic component scrap is defined in advance by using two or more features associated with one electronic component scrap having the same shape and the same position. A method for classifying electronic component waste, including a classification process for classifying by product type.
The position shape identification step
The plurality of electronic component scraps in the imaging area are irradiated with region detection light to acquire region detection data, and the region detection data is used to obtain position information and shape information of each electronic component scrap. The method for classifying electronic component waste according to claim 1, which comprises producing position / shape identification information including.
The method for classifying electronic component scraps according to claim 1 or 2, wherein the feature analysis step obtains two or more spectral information for each electronic component scrap using a multispectral imaging means.
One of claims 1 to 3, wherein the feature analysis step includes analyzing the ratio of the specific color of the electronic component scraps to the area occupied by the specific color with respect to the total area of the electronic component scraps. The method for classifying electronic component scraps according to item 1.
The electrons after the plurality of electronic component scraps having different shapes are sorted by using any of a magnetic force sorter, a color sorter, a metal sorter, an optical sorter including an infrared sensor, and a plastic sorter. The method for classifying electronic component scraps according to any one of claims 1 to 4, which includes component scraps.
A position-shape identification step of identifying the position and shape of each electronic component waste from a plurality of electronic component scraps having different shapes and obtaining position-shape identification information including position information and shape information of each electronic component waste.
A feature analysis step of analyzing at least two features of each electronic component waste and obtaining feature analysis information associated with the position shape identification information.
Based on the position shape identification information and the feature analysis information, each electronic component scrap is defined in advance by using two or more features associated with one electronic component scrap having the same shape and the same position. Classification process to classify by type and
A method for treating electronic component scraps, which includes an extraction step of extracting electronic component scraps to be extracted from the plurality of electronic component scraps based on the classification result of the classification step and the position and shape identification information.