CN113421065A - Semiconductor production intelligence letter sorting system based on thing networking - Google Patents
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Abstract
The invention relates to an intelligent sorting system for semiconductor production based on the Internet of things, which comprises a processor, a semiconductor module, a detection module, a processing and counting module, a calculation and analysis module and a sorting module, wherein the semiconductor module is used for processing and counting the semiconductor module; the semiconductor module collects data information of the semiconductor, wherein the data information comprises type data, size data and processing data of the semiconductor; cleaning data information; the detection module is used for detecting the sorted semiconductors to obtain detection information, and the detection information comprises crack data and duration data; cleaning the detection information; the processing and counting module is used for calculating the cleaned data information and the cleaned detection information to obtain a body value and a detection value; the invention solves the technical problems that the processing condition and the detection condition of the semiconductor can not be comprehensively analyzed in the prior scheme, and the semiconductor which does not meet the quality standard is sorted and transported in the transportation process.
Description
Technical Field
The invention relates to the technical field of semiconductor production, in particular to an intelligent sorting system for semiconductor production based on the Internet of things.
Background
The semiconductor refers to a material with electric conductivity between a conductor and an insulator at normal temperature, and is applied to the fields of integrated circuits, consumer electronics, communication systems, photovoltaic power generation, illumination, high-power conversion and the like.
In the existing semiconductor production process, the processing condition and the detection condition of the semiconductor cannot be comprehensively analyzed, and the semiconductor which does not meet the quality standard is sorted and transported in the transportation process.
Disclosure of Invention
The invention aims to provide an intelligent sorting system for semiconductor production based on the Internet of things, and mainly aims to solve the technical problems that the processing condition and the detection condition of a semiconductor cannot be comprehensively analyzed, and the semiconductor which does not meet the quality standard is sorted and transported in the transportation process in the existing scheme.
The purpose of the invention can be realized by the following technical method:
an intelligent sorting system for semiconductor production based on the Internet of things comprises a processor, a semiconductor module, a detection module, a processing and counting module, a calculation and analysis module and a sorting module;
the semiconductor module collects data information of the semiconductor, wherein the data information comprises type data, size data and processing data of the semiconductor; cleaning the data information to obtain type processing data, size processing data and processing data;
the detection module is used for detecting the sorted semiconductors to obtain detection information, and the detection information comprises crack data and duration data; cleaning the detection information to obtain detection cleaning information;
the processing and counting module is used for calculating the cleaned data information and the cleaned detection information to obtain a body value and a detection value;
the calculation analysis module is used for performing calculation analysis according to the body value and the detection value to obtain sorting data of the semiconductor;
the sorting module sorts the semiconductor according to the sorting data; the processor is used for processing the data in each module.
Further, the data information is cleaned, and the method comprises the following steps:
receiving data information and acquiring type data, size data and processing data of a semiconductor;
marking the semiconductor type in the type data and acquiring a corresponding semi-class correlation value;
respectively taking values and marking the semiconductor area and the semiconductor thickness in the size data;
and marking the machining type in the machining data and acquiring a corresponding class adding preset value.
Further, the cleaning of the detection information comprises:
receiving detection information and acquiring detected crack data and duration data;
respectively carrying out value taking and marking on the number and the area of the cracks in the crack data;
and carrying out value taking and marking on the detection duration in the time duration data.
Further, the processing statistic module is used for calculating the cleaned data information and the detected information to obtain a body value and a detected value, and comprises:
normalizing and valuing various items of data marked in the data information by using a formula
Calculating to obtain a body value BT of the semiconductor; wherein a1, a2, a3 and a4 are expressed as different proportionality coefficients, BLGi is expressed as a semi-class correlation value corresponding to a semiconductor type, JLYi is expressed as an added class preset value corresponding to a processing type, BMi is expressed as a semiconductor area, BHi is expressed as a semiconductor thickness, and i is 1, 2, 3.. n;
normalizing and taking values of various items of data marked in the detection information by using a formula
Calculating to obtain a detection value JC of the semiconductor; where b1 and b2 represent different proportionality coefficients, LSi represents the number of cracks, LMi represents the area of cracks, JSi represents the length of inspection time, and i is 1, 2, 3.
Further, the calculation and analysis module is configured to perform calculation and analysis according to the body value and the detection value to obtain sorting data of the semiconductor, and includes:
obtaining a body value BT and a detection value JC corresponding to different semiconductors by using formulas
Calculating to obtain a sorting value FJ of the semiconductor; wherein c1 and c2 represent different scaling factors;
calculating the ratio between the sorting value and the sorting threshold value, acquiring an integer part of the ratio, marking the integer part as K, and analyzing the K; if K is less than G, generating a first sorting signal; if G +1 is larger than K and is larger than or equal to G, generating a second sorting signal; if K is larger than or equal to G +1, generating a third sorting signal; wherein G represents a preset sorting integer;
the sort value is combined with the first, second, and third sort signals to obtain sort data.
Further, the sorting module sorts the semiconductor according to the sorting data, including:
and acquiring sorting signals corresponding to the semiconductors in the sorting data, and sorting and transferring the semiconductors by using the sorting signals.
The invention has the beneficial effects that:
acquiring data information of a semiconductor through a semiconductor module, and cleaning the data information; by collecting and processing type data, size data and processing data of the semiconductor, effective data support is provided for the detection of the semiconductor, and the detection accuracy can be improved;
detecting the sorted semiconductors through a detection module to obtain detection information, and cleaning the detection information; the semiconductor is detected and processed, so that effective data support is provided for sorting of the semiconductor, and different semiconductors are sorted in different modes;
calculating the cleaned data information and detection information through a processing and counting module to obtain a body value and a detection value; by calculating the collected and processed data, the data are linked, so that the overall analysis is facilitated, and the effectiveness of data analysis can be improved;
performing calculation analysis through a calculation analysis module according to the body value and the detection value to obtain sorting data of the semiconductor; sorting the semiconductor according to the sorting data by a sorting module; the processing condition and the detection condition of the semiconductor can be comprehensively analyzed, and the purpose of sorting and transferring the semiconductor which does not meet the quality standard in the transportation process is achieved.
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The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of an intelligent sorting system for semiconductor production based on the internet of things.
Detailed Description
To further illustrate the technical means and effects of the present invention adopted to achieve the predetermined objects, the following detailed description of the embodiments, structures, features and effects according to the present invention will be made with reference to the accompanying drawings and preferred embodiments.
Referring to fig. 1, the invention relates to an intelligent sorting system for semiconductor production based on the internet of things, which comprises a processor, a semiconductor module, a detection module, a processing and counting module, a calculation and analysis module and a sorting module;
in the semiconductor industry, infrared industrial cameras can be used to inspect the quality of pure semiconductor materials, and in addition, silicon ingots and finished wafers cut into wafers can also be used to detect defects or cracks in a similar manner, and then the wafers can be processed into optoelectronic devices or other semiconductor devices; in the processing process of cutting the wafer into single chips, for the calibration of the saw blade and the laser, the infrared industrial camera is still the mainstream scheme applied at present.
The semiconductor module collects data information of the semiconductor, wherein the data information comprises type data, size data and processing data of the semiconductor; cleaning the data information to obtain type processing data, size processing data and processing data; the method comprises the following steps:
receiving data information and acquiring type data, size data and processing data of a semiconductor;
marking the semiconductor type in the type data, acquiring a corresponding semi-class correlation value, and marking the semiconductor type as BLi, wherein i is 1, 2, 3.. n; setting different semiconductor types to correspond to a different semi-class correlation value, matching the semiconductor types in the type data with all the semiconductor types to obtain the corresponding semi-class correlation value, and marking the semi-class correlation value as BLGi; the marked semiconductor type and the corresponding semi-class correlation value form type processing data;
respectively carrying out value taking and marking on the semiconductor area and the semiconductor thickness in the size data, and marking the semiconductor area as BMi; marking the semiconductor thickness as BHi; the marked semiconductor area and semiconductor thickness constitute dimensional processing data;
marking the processing type in the processing data, acquiring a corresponding class adding preset value, and marking the processing type as JLi; setting different processing types to correspond to different adding preset values, matching the processing types in the processing data with all the processing types to obtain corresponding adding preset values, and marking the corresponding adding preset values as JLYi; the marked processing type and the corresponding class adding preset value form processing data; the processing type includes, but is not limited to, the growth technology, thin film deposition, photolithography, etching, doping technology, and process integration of the wafer; for example, if the sorted semiconductor has completed the photolithography step, the processing type corresponds to the photolithography type;
the detection module is used for detecting the sorted semiconductors to obtain detection information, and the detection information comprises crack data and duration data; cleaning the detection information to obtain detection cleaning information; the method comprises the following steps:
receiving detection information and acquiring detected crack data and duration data;
respectively carrying out value taking and marking on the number and the area of the cracks in the crack data, and marking the number of the cracks as LSi; mark the crack area as LMi;
taking and marking the detection duration in the time duration data, and marking the detection duration as JSi;
the processing and counting module is used for calculating the cleaned data information and the cleaned detection information to obtain a body value and a detection value; the method comprises the following steps:
normalizing and valuing various items of data marked in the data information by using a formula
Calculating to obtain a body value BT of the semiconductor; wherein a1, a2, a3 and a4 are expressed as different proportionality coefficients, BLGi is expressed as a semi-class correlation value corresponding to a semiconductor type, JLYi is expressed as an added class preset value corresponding to a processing type, BMi is expressed as a semiconductor area, BHi is expressed as a semiconductor thickness, and i is 1, 2, 3.. n;
normalizing and taking values of various items of data marked in the detection information by using a formula
Calculating to obtain a detection value JC of the semiconductor; wherein b1 and b2 are expressed as different proportionality coefficients, LSi is expressed as the number of cracks, LMi is expressed as the area of cracks, JSi is expressed as the length of inspection time, and i is 1, 2, 3.. n;
in the embodiment of the invention, the condition of the semiconductor is analyzed according to the type of the semiconductor and the corresponding semi-class correlation value, the area and the thickness of the semiconductor, the processing type and the corresponding class adding preset value, so that data support is provided for subsequent quality detection; and analyzing the detection condition of the semiconductor according to the number, area and detection time of the cracks, and providing data support for subsequent semiconductor sorting.
The calculation analysis module is used for performing calculation analysis according to the body value and the detection value to obtain sorting data of the semiconductor; the method comprises the following steps:
obtaining a body value BT and a detection value JC corresponding to different semiconductors by using formulas
Calculating to obtain a sorting value FJ of the semiconductor; wherein c1 and c2 represent different scaling factors;
calculating the ratio between the sorting value and the sorting threshold value, acquiring an integer part of the ratio, marking the integer part as K, and analyzing the K; if K is less than G, generating a first sorting signal; if G +1 is larger than K and is larger than or equal to G, generating a second sorting signal; if K is larger than or equal to G +1, generating a third sorting signal; wherein G is a preset sorting integer, G can be 1, for example, if the ratio of the sorting value to the sorting threshold is 2.5, K is 2, and K is equal to or greater than G +1, so as to generate a third sorting signal;
combining the sort value with the first, second, and third sort signals to obtain sort data;
in the embodiment of the invention, the detected semiconductors are sorted according to the first sorting signal, the second sorting signal and the third sorting signal, and the first sorting signal indicates that the corresponding semiconductor has no crack; the second sorting signal indicates that the corresponding semiconductor has a small amount of cracks meeting the quality standard; the third sorting signal indicates that the corresponding semiconductor has a small number of cracks which do not meet the quality standard; the quality standard is set based on the existing semiconductor quality inspection standard.
The sorting module sorts the semiconductor according to the sorting data; the processor is used for processing the data in each module; the method comprises the following steps:
acquiring sorting signals corresponding to the semiconductors in the sorting data, and sorting and transferring the semiconductors by using the sorting signals; sorting the corresponding semiconductor to a first conveying belt for conveying according to the first sorting signal; sorting the corresponding semiconductor to a second conveying belt for conveying according to the second sorting signal; sorting the corresponding semiconductor to a third conveyer belt for conveying according to the third sorting signal;
the formulas in the invention are all a formula which is obtained by removing dimensions and taking numerical value calculation, and software simulation is carried out by collecting a large amount of data to obtain the formula closest to the real condition, and the preset proportionality coefficient and the threshold value in the formula are set by the technical personnel in the field according to the actual condition or are obtained by simulating a large amount of data.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. The intelligent sorting system for semiconductor production based on the Internet of things is characterized by comprising a processor, a semiconductor module, a detection module, a processing and counting module, a calculation and analysis module and a sorting module;
the semiconductor module collects data information of the semiconductor, wherein the data information comprises type data, size data and processing data of the semiconductor; cleaning the data information to obtain type processing data, size processing data and processing data;
the detection module is used for detecting the sorted semiconductors to obtain detection information, and the detection information comprises crack data and duration data; cleaning the detection information to obtain detection cleaning information;
the processing and counting module is used for calculating the cleaned data information and the cleaned detection information to obtain a body value and a detection value;
the calculation analysis module is used for performing calculation analysis according to the body value and the detection value to obtain sorting data of the semiconductor;
the sorting module sorts the semiconductor according to the sorting data; the processor is used for processing the data in each module.
2. The intelligent sorting system for semiconductor production based on internet of things as claimed in claim 1, wherein the cleaning of data information comprises:
receiving data information and acquiring type data, size data and processing data of a semiconductor;
marking the semiconductor type in the type data and acquiring a corresponding semi-class correlation value;
respectively taking values and marking the semiconductor area and the semiconductor thickness in the size data;
and marking the machining type in the machining data and acquiring a corresponding class adding preset value.
3. The intelligent sorting system for semiconductor production based on the internet of things as claimed in claim 1, wherein the cleaning of the detection information comprises:
receiving detection information and acquiring detected crack data and duration data;
respectively carrying out value taking and marking on the number and the area of the cracks in the crack data;
and carrying out value taking and marking on the detection duration in the time duration data.
4. The intelligent sorting system for semiconductor production based on the internet of things as claimed in claim 1, wherein the processing statistic module is configured to calculate the cleaned data information and detection information to obtain an ontology value and a detection value, and comprises:
normalizing and valuing various items of data marked in the data information by using a formula
Calculating to obtain a body value BT of the semiconductor; wherein a1, a2, a3 and a4 are expressed as different proportionality coefficients, BLGi is expressed as a semi-class correlation value corresponding to a semiconductor type, JLYi is expressed as an added class preset value corresponding to a processing type, BMi is expressed as a semiconductor area, BHi is expressed as a semiconductor thickness, and i is 1, 2, 3.. n;
normalizing and taking values of various items of data marked in the detection information by using a formula
Calculating to obtain a detection value JC of the semiconductor; where b1 and b2 represent different proportionality coefficients, LSi represents the number of cracks, LMi represents the area of cracks, JSi represents the length of inspection time, and i is 1, 2, 3.
5. The intelligent semiconductor production sorting system based on the internet of things as claimed in claim 1, wherein the calculation and analysis module is configured to perform calculation and analysis according to the ontology value and the detection value to obtain sorting data of the semiconductor, and the system comprises:
obtaining a body value BT and a detection value JC corresponding to different semiconductors by using formulas
Calculating to obtain a sorting value FJ of the semiconductor; wherein c1 and c2 represent different scaling factors;
calculating the ratio between the sorting value and the sorting threshold value, acquiring an integer part of the ratio, marking the integer part as K, and analyzing the K; if K is less than G, generating a first sorting signal; if G +1 is larger than K and is larger than or equal to G, generating a second sorting signal; if K is larger than or equal to G +1, generating a third sorting signal; wherein G represents a preset sorting integer;
the sort value is combined with the first, second, and third sort signals to obtain sort data.
6. The intelligent sorting system for semiconductor production based on internet of things as claimed in claim 1, wherein the sorting module sorts the semiconductor according to the sorting data, comprising:
and acquiring sorting signals corresponding to the semiconductors in the sorting data, and sorting and transferring the semiconductors by using the sorting signals.
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| CN114894132A (en) * | 2022-05-08 | 2022-08-12 | 三河建华高科有限责任公司 | Semiconductor wafer thickness detection control system |
| CN117269731A (en) * | 2023-11-07 | 2023-12-22 | 千思跃智能科技(苏州)股份有限公司 | PCBA performance automatic test system based on Internet of things |
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