阅读说明：本技术 用于流水线太阳能电池生产工厂的光电太阳能电池测试系统以及用于使用这种类型的光电太阳能电池测试系统来优化太阳能电池流水线生产的方法 (Photovoltaic solar cell testing system for a pipeline solar cell production plant and method for optimizing a solar cell pipeline production using a photovoltaic solar cell testing system of this type) 是由 M·斯凯尔福 于 2019-08-07 设计创作，主要内容包括：本发明涉及一种用于流水线太阳能电池生产工厂的光电太阳能电池测试系统,该太阳能电池测试系统具有：用于太阳能电池的流水线测量的曝光和测量设备(10),和耦合到该曝光和测量设备(10)的控制和评估单元(20),该曝光和测量设备(10)被设计和配置为在太阳能电池(SC)上执行一个或多个测试测量(TM)以用于生成测试测量数据。根据本发明,该控制和评估单元(20)被配置和设计为使用来自由该曝光和测量设备(10)对流水线生产的多个太阳能电池(SC)实施的相同测试测量(TM)的测试测量数据来执行统计分析(200),并且将来自不同测试测量(TM)的测试测量数据的统计分析相互相关,和/或将测试测量数据的统计分析(TMstat)与生产测量数据的统计分析(PMstat)相关,和/或将测试测量数据的统计分析(TMstat)和/或生产测量数据的统计分析(PMstat)与生产输入数据(PED)相关,以便生成相关结果(201),并在导出规则(202)的基础上从相关结果(201)中导出被指派给负责太阳能电池的流水线生产的至少一个人员组(PG1、PG2、PGn)的至少一个处理建议(203)和/或至少一个处理指令(204),其中控制和评估单元(20)具有通信设备(21),其将至少一个处理建议(203)和/或至少一个处理指令(204)传输给至少一个指派的人员组(PG1、PG2、PGn)。本发明还涉及一种用于使用这种类型的太阳能电池测试系统借助于流水线太阳能电池生产工厂来优化太阳能电池生产的方法。(The invention relates to a photovoltaic solar cell test system for a production line solar cell production plant, comprising: an exposure and measurement device (10) for inline measurement of solar cells, and a control and evaluation unit (20) coupled to the exposure and measurement device (10), the exposure and measurement device (10) being designed and configured to perform one or more Test Measurements (TM) on a Solar Cell (SC) for generating test measurement data. According to the invention, the control and evaluation unit (20) is configured and designed to carry out a statistical analysis (200) using test measurement data from the same Test Measurement (TM) carried out by the exposure and measurement device (10) on a plurality of Solar Cells (SC) produced in a pipeline and to correlate statistical analyses of test measurement data from different Test Measurements (TM) with each other and/or to correlate statistical analyses of test measurement data (TMstat) with statistical analyses of production measurement data (PMstat) and/or to correlate statistical analyses of test measurement data (TMstat) and/or statistical analyses of production measurement data (PMstat) with production input data (PED) in order to generate a correlation result (201) and to derive from the correlation result (201) on the basis of a derivation rule (202) at least one group of persons (PG1, G32, G) assigned to the pipeline production responsible for solar cells, PG2, PGn), wherein the control and evaluation unit (20) has a communication device (21) which transmits the at least one processing proposal (203) and/or the at least one processing instruction (204) to the at least one assigned group of persons (PG1, PG2, PGn). The invention also relates to a method for optimizing solar cell production by means of a flow-line solar cell production plant using a solar cell test system of this type.)

1. A photovoltaic solar cell testing system for a streamlined solar cell production plant, the solar cell testing system comprising:

-an exposure and measurement device (10) for inline measurement of solar cells, and

a control and evaluation unit (20) coupled to the exposure and measurement device (10),

the exposure and measurement device (10) being configured and adapted to perform one or more Test Measurements (TM) on a Solar Cell (SC) in order to generate test measurement data,

the Test Measurement (TM) is selected from the group consisting of:

-infrared image measurement of a reverse energized solar cell in order to determine a local short circuit in the solar cell,

-a flash exposure with an exposure spectrum for measuring at least one current-voltage characteristic of the solar cell,

a plurality of spectrally differentiated flash exposures in order to measure a spectrally resolved current characteristic of the solar cell and/or in order to measure a quasi-external quantum efficiency of the solar cell,

-electroluminescence measurements of the solar cell, in particular in order to determine micro-cracks in the solar cell material and/or in order to determine electrode structure interruptions and/or contact problems between electrode structure and substrate and/or in order to determine electrically inactive areas and/or local short-circuits,

-a measurement of a bright characteristic curve and a measurement of a dark characteristic curve of the solar cell in order to calculate a series resistance of the solar cell,

measuring the resistance of the electrode structure comprising the electrode fingers in order to determine the mass of the metal electrode structure,

the method is characterized in that:

the control and evaluation unit (20) is adapted and configured to perform a statistical analysis (200) on test measurement data of the same Test Measurements (TM) performed on in-line produced Solar Cells (SC) by means of the exposure and measurement device (10), and

-correlating (200) the statistical analysis of the test measurement data of different Test Measurements (TM) with each other, and/or

-correlating the statistical analysis of the test measurement data (TMstat) with the statistical analysis of the production measurement data (PMstat), and/or

-correlating the statistical analysis of the test measurement data (TMstat) and/or the statistical analysis of the production measurement data (PMstat) with the production input data (PED),

in order to generate a correlation result (201) and to derive from the correlation result (201) at least one processing proposal (203) and/or at least one processing instruction (204) assigned to at least one group of people (PG1, PG2, PGn) participating in the pipeline production of the solar cell with the aid of a derivation rule (202), the control and evaluation unit (20) comprising a communication device (21), the communication device (21) transmitting the at least one processing proposal (203) and/or the at least one processing instruction (204) to the at least one assigned group of people (PG1, PG2, PGn).

2. Optoelectronic solar cell testing system according to claim 1, characterized in that the communication device (21) is adapted and configured such that

-a display device (12) arranged on the exposure and measurement apparatus (10) and/or

-a display device (22) arranged on the control and evaluation unit (20) and/or

-display devices (PD1, PD2, PDn) and/or arranged on process equipment (PE1, PE2, PEn) of the in-line solar cell production plant

Mobile digital terminals (M1, M2, Mn)

Communicating the at least one processing suggestion (203) and/or the at least one processing instruction (204) to the at least one assigned group of people (PG1, PG2, PGn).

3. The photovoltaic solar cell testing system according to claim 2, characterized in that the communication device (21) is adapted and configured such that the communication device (21) selects at least one specifically assigned group of people (PG1, PG2, PGn) according to at least one derived processing recommendation (203) and/or at least one derived processing instruction (204).

4. Photovoltaic solar cell testing system according to one of claims 2 and 3, characterized in that the control and evaluation unit (20) is adapted and configured to

-performing a statistical analysis (PMstat) of production measurement data by means of received Production Measurements (PM) of production measurement devices (PM1, PM2, PMn), and/or

-receiving from the production measurement device (PM1, PM2, PMn) a statistical analysis (PMstat) of the production measurement data generated in the production measurement device (PM1, PM2, PMn).

5. Photovoltaic solar cell testing system according to one of the claims 2 to 4, characterized in that the derivation rules (202) are stored in a digital memory (23) of the control and evaluation unit (20).

6. The photovoltaic solar cell testing system according to claim 5, characterized in that the derived rules (202) are stored in the digital memory (23) of the control and evaluation unit (20) in such a way that they can be modified via a digital interface (24).

7. Photovoltaic solar cell test system according to one of the claims 2 to 6, characterized in that the display device (12) of the exposure and measurement apparatus (10) and/or the display device (22) of the control and evaluation process apparatus (20) and/or the display device (PD1, PD2, PDn) of the process apparatus (PE1, PE2, PEn) and/or the mobile digital terminal (M1, M2, Mn) is configured and adapted to receive a reception confirmation signal (EQ1, EQ2, EQn) generated by the at least one specifically assigned group of people (PG1, PG2, PGn).

8. Photovoltaic solar cell testing system according to one of the claims 2 to 7, characterized in that at least one of the display means (12) of the exposure and measurement apparatus (10) and/or the display means (22) configuration of the control and evaluation unit (20) and/or the display means (PD1, PD2, PDn) of the process equipment (PE1, PE2, PEN) and/or the mobile digital terminal (M1, M2, Mn) is configured and adapted to receive evaluation signals (F1, F2, Fn), which evaluation signals (F1, F2, Fn) are conveyed on a part of the at least one assigned group of people (PG1, PG2, PGn): whether the processing proposal (203) generated by the control and evaluation unit (20) and/or the processing instruction (204) generated by the control and evaluation unit (20) is appropriate in view of the assigned group of persons (PG1, PG2, PGn).

9. The photovoltaic solar cell testing system according to claim 8, characterized in that the control and evaluation unit (20) is adapted and configured to perform statistical analyses between the generated processing recommendations (203) and processing instructions (204) and the evaluation signals (F1, F2, Fn) obtained in response thereto, and to validate and adapt the derived rules (202) based on these statistical analyses.

10. Method for optimizing solar cell production by means of a pipeline solar cell production plant by using a photovoltaic solar cell testing system according to any of the preceding claims, wherein the pipeline solar cell production plant comprises a plurality of process equipment (PE1, PE2, PEn) with process measurement equipment (PM1, PM2, PMn) for generating production measurement data (PM).

11. The method for optimizing the in-line production of solar cells of claim 10,

-correlating the statistical analysis (TMstat) of the test measurement data of different test measurements with each other, and/or

-correlating a statistical analysis of the test measurement data (TMstat) of a test measurement with a statistical analysis of the production measurement data (PMstat) of a production measurement, and/or

-correlating the statistical analysis (TMstat) of the test measurement data with the production input data (PED), and/or

Correlating the statistical analysis of production measurement data (PMstat) with the production input data (PED),

in order to generate a correlation result (201) and to derive from the correlation result (201) at least one processing proposal (203) and/or at least one processing instruction (204) assigned to at least one group of people (PG1, PG2, PGn) participating in the pipeline production of the solar cell with the aid of a derivation rule (202), and the at least one processing proposal (203) and/or the at least one processing instruction (204) are transmitted to the at least one assigned group of people (PG1, PG2, PGn).

12. Method for optimizing the in-line production of solar cells according to claim 11, characterized in that the derived rules (202) of the photovoltaic solar cell test system are checked and adapted by a feedback system aiming at producing solar cells with the best quality, the feedback system (205) supplying feedback information (F1, F2, Fn) by at least one group of people (PG1, PG2, PGn) participating in the in-line production of the solar cells.

13. Method for optimizing the in-line production of solar cells according to claim 12, characterized in that the derivation rules (202) are checked and adapted by an automatic optimization program.

14. Method for optimizing the production line of solar cells according to one of claims 10 to 13, characterized in that processing recommendations (203) and/or processing instructions (204) to which a part of the assigned personnel groups (PG1, PG2, PGn) is not responsive are communicated and/or communicated to other personnel groups (PG1, PG2, PGn) with a higher degree of attention or a higher relevance level after the confirmation time has elapsed.

15. Method for optimizing the in-line production of solar cells according to one of claims 10 to 14, characterized in that a data pattern indicating the maintenance requirements and/or signs of wear of the process equipment (PE1, PE2, PEn) is determined from the generated correlation results (201).

Technical Field

The invention relates to a photovoltaic solar cell test system for a pipeline solar cell production plant according to the pre-characterized clause of claim 1. The invention also relates to a method for optimizing the production line of solar cells using such a photovoltaic solar cell testing system.

Background

Photovoltaic solar cell test systems include systems with exposure and measurement devices, which are referred to in technical terms as "flash lamps". The exposure and measurement device is coupled to the control and evaluation unit and is conventionally located at the end of a production line plant for quality measurement of the produced solar cells. Such a system is known, for example, from DE112012006365T 5.

The exposure and measurement device is configured and adapted to perform one or more test measurements on the solar cell to generate test measurement data, the test measurements selected from the group consisting of:

-infrared image measurement of the reversely energized solar cells in order to determine local short circuits in the solar cells,

a flash exposure with an exposure spectrum, in particular a simulated solar spectrum, in order to measure at least one current-voltage characteristic of the solar cell,

a plurality of spectrally differentiated flash exposures in order to measure the spectrally resolved current characteristic of the solar cell and/or in order to measure the quasi-external quantum efficiency of the solar cell,

electroluminescence measurement of the solar cell, in particular in order to determine micro-cracks in the solar cell material and/or in order to determine electrode structure interruptions and/or contact problems between the electrode structure and the substrate and/or in order to determine electrically inactive areas and/or local short circuits,

-measurement of the bright and dark characteristic curves of the solar cell in order to calculate the series resistance of the solar cell, and

-resistance measurements of the electrode structure of the solar cell comprising the electrode fingers in order to determine the quality of the metal electrode structure.

The quasi-external quantum efficiency of the solar cell is obtained by spectrally differentiated flash exposure. For flash exposures in the blue spectral range, a deficiency in the measurements of the wafer solar cell indicates a problem with the nitride layer or emitter. For flash exposures in the red spectral range, poor bulk material of the wafer or poor quality of the backside passivation layer can be identified.

The interruption and/or contact problems between the electrode structure and the substrate identified by the electroluminescence measurement may occur on both its front and back sides, depending on the structural design of the solar cell. Electrically inactive areas are caused in wafer solar cells by damaged or poor quality substrate material. Local shorting of the p-n junction may occur in a wafer solar cell due to the pn junction being shorted, for example, by so-called etch wrap-around at the edge of the solar cell.

Along a solar cell production line plant consisting of a plurality of sequential process equipment, there are conventionally different process measurement equipment that monitor or document the production operation. For the production of wafer-based solar cells, these include, inter alia, process measurement equipment for registering the wafer resistivity, the wafer thickness, the wafer weight, the wafer TTV (total thickness variation), the wet chemical etch removal, the composition of the wet chemistry, the minority carrier lifetime of the wafer, the electrical conductivity and homogeneity of the diffusion layer, the layer thickness and refractive index of the antireflective and/or passivation layer, the homogeneity of the antireflective and/or passivation layer, the etch wrap-around in the case of a single-sided etching step, the amount and location of the gold plating paste, errors in the printed image of the paste, etc., depending on the level of automation and the layout of the production line. With the aid of production measurements, these process measurement devices determine and typically store production measurement data. Alternatively, an alarm is triggered in case the deviation between the production measurement data and the defined set value is too large. With the aid of further production measurements, production measurement data are generated which represent parameters of the processing methods respectively taking place in the process plant. These are in particular data relating to the temporal and/or spatial distribution of temperature, pressure, processing time, etc. Production measurement data is created in the process plant by production measurements on partially manufactured solar cells or by production measurements on parameters of the processing methods taking place in the process plant.

In addition to further activities, employees of the pipeline solar cell production plant may and should observe these characteristic values obtained from production measurement data, when they have time to do so, and make corrections to the corresponding processing methods of the process equipment based on their knowledge and capabilities as necessary, or report exceptions to other employees to take further action. Typically, even in the case of relatively large problems, the pipeline production will continue without diminishing until the responsible technician arrives and begins the fault tracing. It may take several hours before the technician arrives. It is even worse if the production personnel working at the process equipment of the in-line production plant do not notice the problem or they do not proceed with the problem. This may be due to insufficient training or the employee not being motivated to report the problem found for various reasons. It is also possible for the production personnel to have too many parallel tasks, so that the equipment of the process plant which subjectively considers the problem the most is prioritized. In such a scenario, for example, the same more relevant issues may not be brought to the attention of a more trained technician until the next shift change report. Since in-line solar cell production is conventionally operated all-weather, many of the problems that have occurred during the night often begin to be resolved only in the morning after the arrival of more advanced technicians.

Production personnel working at process equipment of a production line plant are typically relatively low-level of training and therefore do not have an in-depth knowledge of the process and/or solar cells. Furthermore, at many sites, the loss rate of such production personnel is as high as 50% per year. Accordingly, production expertise cannot be continuously built and maintained. This is contradictory to the fact that: solar cell production is a highly complex multidisciplinary process with a versatile impact on many different solar cell parameters. These solar cell parameters may influence each other, enhancing or even compensating for certain effects, which makes it more difficult to perform fault tracking to optimize production. Therefore, the actual cause of process variation is often difficult for the manufacturer to track. Furthermore, especially wafer solar cell structures are becoming more and more complex (PERC (passivated emitter and back cell), IBC (interdigitated back contact), HIT (heterojunction with intrinsic thin layer)), and thus more sensitive to reaction to process variations, which affects efficiency and sensitivity to PID (light induced degradation) or LeTID (light and high temperature degradation).

Solar cells suffer a loss of quality and/or efficiency if the in-line production plant is not operating optimally. In order to be particularly efficient, all process equipment and processes must be optimally adjusted, which is only possible with a large number of measuring techniques and a large number of trained staff. Both of which are expensive. Many measurement interpretation errors that can also occur with time delays of the battery are possible and common. Currently, no production line factory in the world can really realize the optimal operation for a long time.

Along and at the end of the solar cell production process, its cell parameters/characteristics will be measured and recorded. This is mainly done at so-called flash lamps, but can also be done at process measurement devices, which for example determine two-dimensional electroluminescent or photoluminescent or infrared images of the surface of partially manufactured solar cells. These process measurement devices may also indicate trends so that possible causes of quality problems are more easily tracked. However, the production personnel often lack the expertise and/or time and/or knowledge of current production modifications (different material lots for substrate components (e.g., wafers), the wet bench for texture etching has been refilled, etc.) to properly account for the deviation in results. The technician is required to be queried, which can result in time delays and thus reduced quality (efficiency) or reduced production quantities (in the event of a production stop).

The technician must be trained interdisciplinary or composed of several people who currently cover all relevant technical problem areas of the entire production process. Depending on the actual level of knowledge, the problem that has occurred cannot be solved optimally, or different solutions are proposed depending on who tries to solve the problem. The production line cannot run optimally until the actual cause is tracked.

Solar cell production suffers from performance loss, particularly when technicians are not immediately available. Often, only a few technicians are present, or they must resolve multiple problems simultaneously. This problem is exacerbated when multiple splits operating in parallel cause problems simultaneously. The plurality of partial lines then no longer operates optimally.

In order to save production costs, the maintenance intervals should also be chosen as long as possible. Thus, it can be seen that: the occurrence of performance losses that are no longer tolerable, or the individual process equipment that is subject to damage and therefore the entire in-line production plant waits. In case of an interruption, the reason is clear. In the case of a performance loss, it must first be assigned to the process equipment that incurs the performance loss. The loss of performance may occur much earlier than usual, or it may have many different causes or multiple causes combined together. Such assignment becomes difficult. During cause tracing, the in-line production plant is not operating optimally.

It is also possible to actually perfectly tune a production line plant, but to some extent deliberately cause performance losses, for example by using less expensive, lower quality raw materials or by recombining process parameters, but this is unknown to the producer-for example due to poor communication. In such cases, the observed performance loss may be misinterpreted and the manufacturer may draw erroneous conclusions and adjust the process parameters within or even beyond their range of motion. This will further impair performance. However, when the finally produced solar cell is measured at the flash lamp of the cell test device, depending on the location of the final intervention, such further damage can only be observed with a significant time delay (a production run may take several hours). This requires a large number of poor quality solar cells that are not optimally processed.

Conventionally, a pipeline solar cell production plant is organized as follows: to supervise a production line plant, the following groups of individuals are typically used:

production personnel, who attend to process equipment running around the clock during shift operations, while immediately addressing minor process interruptions (e.g., removal of broken wafers) and performing maintenance in the form of maintenance work, but, even in the case of relatively large interruptions of the process equipment, addressing these failures until the process equipment fails,

on-duty supervisors who attend to the tasks of the process plant and also organize the maintenance of the production personnel,

technical staff who have expertise in the individual process steps, but are not permanently located on site (e.g. during night shifts or night shifts), comprise relatively few staff and provide technical knowledge in case of process plant interruptions, and

production supervisors, who have a comprehensive understanding and responsibility for production.

Therefore, the systems known from the prior art for testing the produced solar cells have the following problems: defects in the treatment methods of the individual process apparatuses are not recognized, or are only recognized insufficiently or inadequately, and there is additionally a time delay.

Disclosure of Invention

It is therefore an object of the present invention to provide a photovoltaic solar cell test system for a pipeline solar cell production plant, which allows defects to be identified more reliably and more rapidly in the individual processes of the pipeline solar cell production plant and the countermeasures taken thereby lead to a faster and more reliable resolution of the process defects.

This object is achieved by a photovoltaic solar cell test system having the features of claim 1 and by a method for optimizing the in-line production of solar cells by using such a photovoltaic solar cell test system having the features of claim 10.

According to the invention, the control and evaluation unit (20) is adapted and configured to

Performing a statistical analysis on test measurement data of the same test measurement performed on a plurality of solar cells produced in-line by means of an exposure and measurement device, and

correlating the statistical analysis of the test measurement data of the different test measurements with each other, and/or

Correlating the statistical analysis of the test measurement data with the statistical analysis of the production measurement data, and/or

Correlating the statistical analysis of the test measurement data and/or the statistical analysis of the production measurement data with the production input data,

in order to generate a correlation result and to derive from the correlation result, with the aid of the derivation rule, at least one processing proposal and/or at least one processing instruction assigned to at least one group of persons participating in the pipeline production of solar cells, the control and evaluation unit comprising a communication device which transmits the at least one processing proposal and/or the at least one processing instruction to the at least one assigned group of persons. The warnings and opinions are also considered processing suggestions or processing instructions according to their content presentation. For example, the warning opinions mean suggestions or indications for improving attention, which are summarized in detail by the contents of the warning opinions.

In order to clearly distinguish between test measurements performed on the finally produced solar cell by means of the exposure and measuring device of the flash lamp, the production measurements and the production measurement data derived therefrom are such measurement data obtained from the partially produced solar cell after or during individual process steps in the process equipment of the in-line production plant. An in-line production plant for solar cells is formed by a series of these process equipment. Each of these process tools may include one or more process measurement tools. With the aid of these process measurement devices, process measurements are carried out on solar cells which have not yet been completed and are therefore only partially manufactured, and production measurement data are obtained in this way. Additionally or alternatively, the process measurement device may also be configured to obtain production measurement data which is not obtained by measurements of partially manufactured solar cells but by measurements of the processing methods occurring in the respective process device. This means the processing parameters of the respective processing method to which the partially manufactured solar cell is subjected at the respective process equipment.

In the terminology of the present patent application, therefore, the testing of the finally produced solar cells for generating the test measurement data is distinguished from the production measurements made for the purpose of producing the production measurement data on the partially produced solar cells or on the corresponding processing methods of the partial production steps. Furthermore, the term production input data is also used. The production input data are, for example, material parameters of substrate components initially introduced into the in-line production process in the form of semiconductor wafers. From the substrate elements, partially manufactured and finally manufactured solar cells are produced in an in-line production process in the order of the process equipment. Further, the production input data may be material properties of consumable materials used in the respective production equipment along a production line sequence for the processing methods occurring in the production equipment. These are, for example, liquids for cleaning or removing surfaces, gases for depositing thin layers or metal pastes for forming metallization layers.

With the aid of this photovoltaic solar cell test system, not only are test measurement data, production measurement data and production input data recorded, represented and documented as usual, but the solar cell test system also independently creates targeted messages configured as processing recommendations or as processing instructions. Depending on the respective content, these processing recommendations or processing instructions are communicated to the assigned group of people. The associated personnel group is one or more of the following personnel groups: production personnel, on-duty supervisors, technicians and production supervisors.

The processing advice or processing instructions may comprise a task that is directly executed or initiated, or a task that is executed or initiated by the associated group of people after they have examined other parameters themselves. The assignment of processing recommendations and/or processing instructions to groups of associated personnel is determined by information or level of responsibility specific to the respective pipeline production plant. By means of an adaptive selection of the communication medium and the communication time, communication can be performed for different assigned persons.

The test system allows for fully or partially automated analysis of many property values in the form of test measurement data, production measurement data and production input data (including whole data). Although these production data are not obtained from a pipeline production plant, they are still related to the solar cells produced. They are in particular the characteristic values of the starting materials treated and of the consumable materials used in the production plants of the pipeline.

Each loss of performance of the resulting solar cell, as determined by the solar cell testing system, has a clear "fingerprint" in the perspective of the overall data analyzed in the overall data space. By evaluating the overall data, the development of corresponding specific "fingerprints" in the overall data space and the superposition of multiple such "fingerprints" can be detected. As part of the evaluation, the test measurement data and the statistical analysis of the production measurement data and the production input data are preferably correlated. It is particularly advantageous to correlate the statistical analysis of the data of one or more imaging test and/or production measurement methods with non-imaging test and/or production measurement methods.

With this test system, the noticeability of production deviations and the resulting performance loss no longer depends on when the production staff again look at the test measurements and/or the results of the production measurements, and in fact notice the significant data and then interpret them correctly. Other sources of delay include human factors, i.e., when and where the technician is specifically patrolling, or when the production personnel will make the next routine report to the technician regarding performance loss. The test system immediately indicates the observed deviation and advises or guides the action by means of the generated message. This means that the test system can give direct indications to production line personnel that specific inspections or measurements are required and/or that the guidance of the production personnel is temporarily taken over, if necessary, until the technician arrives as usual or as required. With the message comprising an alarm and also being recorded, the staff belonging to the production staff may find it difficult to borrow that they have not noticed or taken into account at all that this or that measure is/are implemented because e.g. a fault is infrequent. By means of the messages generated by the test system, a timely handling of the resistance performance defect is initiated, thereby saving production costs considerably by avoiding long downtimes.

Furthermore, the newly added export rules can be used directly without first being interpreted by training to production line personnel.

Preferably, the photovoltaic solar cell testing system is characterized in that the communication device is adapted and configured such that:

-a display device arranged on the exposure and measurement apparatus; and/or

-display means arranged on the control and evaluation unit; and/or

-a display device arranged on process equipment of an in-line solar cell production plant; and/or

-a mobile digital terminal.

At least one processing recommendation and/or at least one processing instruction is communicated to at least one assigned group of people. In this case, the selection of the medium used for transmitting the processing proposal and the processing instruction is performed depending on the situation. If multiple personnel groups are assigned, communication may be performed using the same or different communication media.

Advantageously, the optoelectronic solar cell testing system is improved such that the communication device is adapted and configured such that the communication device selects at least one specifically assigned group of people according to at least one derived processing recommendation and/or at least one derived processing instruction.

Processing recommendations and processing instructions can be communicated in very different ways. For example, they may each be automatically sent to a working production person. The indication in the form of processing advice and processing instructions may be communicated by a specific indicator light, a specific alarm sound, a display indication in the form of text, or a combination thereof. Depending on the nature and severity of the process defect, the message may be delivered to a group of people assigned to a larger circle of people. In this case, the communication medium and the content of the messaging may be different. For example, minor process deviations are only shown as "caution" on the display screen and have no guidance on the production personnel responsible for the process equipment. Serious process defects can be communicated, for example, by means of special alarm sounds, requiring confirmation on a correspondingly configured interface and prompting the production personnel for predetermined measures in the form of an operator instruction. In this case, the report is made to the on-duty supervisor. In very severe cases, this may result in the need to stop production, which must be verified by production supervisors. This can also be done remotely online.

In severe cases, the system may be authorized to guide the production personnel and often there will be treatment recommendations. Depending on the severity, it must be confirmed and verified. If this does not occur, the message is passed to an alternate assigned personnel group in the same or a different manner. Depending on the relevance of the message, the technician and/or the higher-ranked circle of people can be notified directly, for which digital terminals and communication via text/voice messages are suitable. The correlation may, for example, be correlated with a threshold being exceeded, or may result from a report to a production person not being confirmed. As the duration of processing defects continues to increase, the manner of messaging may be escalated to a higher level of relevance — for example, by changing the processing recommendations to processing instructions.

Advantageously, the photovoltaic solar cell test system is characterized in that the control and evaluation unit is adapted and configured to:

performing a statistical analysis of the production measurement data by means of the received production measurement values of the production measurement device, and/or

-receiving from the production measurement device a statistical analysis of the production measurement data generated in the production measurement device. The statistical analysis includes conventional mean and variance analysis. For continuously executed test measurements and production measurements, these can either be executed centrally by the control and evaluation unit or these evaluations can already be carried out by correspondingly configured production measuring devices which continue to transmit the statistical evaluation results to the control and evaluation unit.

Preferably, the derived rules are stored in a digital memory of the control and evaluation unit. The derivation rules that can be used depend on the available test measurements and production measurements. The activatable export rule is selected by the technician.

Particularly preferably, the derived rules are stored in a digital memory of the control and evaluation unit in such a way that they can be modified via a digital interface. The advantage of this improvement is that the technician can write new supplementary export rules and the resulting messages in the form of processing recommendations and/or processing instructions. Likewise, through empirical observation of the system and its overall data in different relevant scenarios, the technician himself can determine further derived rules and the resulting messages.

According to an advantageous further development of the optoelectronic solar cell test system, the display device of the exposure and measurement device and/or the display device of the control and evaluation unit and/or the display device of the process plant and/or the mobile digital terminal is configured and adapted to receive a reception confirmation signal generated by at least one specifically assigned personnel group. These receipt confirmation signals are requested in the case of messages communicated in the form of processing advice and/or processing instructions. If the requested acknowledgment verification signal does not arrive, the request is repeated. Depending on the relevance level of the message, other groups of people may be assigned and notified if the reception confirmation signal has not yet arrived.

Preferably, the optoelectronic solar cell testing system is characterized in that at least one of the display means of the exposure and measurement device and/or the display means of the control and evaluation unit and/or the display means of the process device and/or the mobile digital terminal is configured and adapted to receive an evaluation signal which is communicated on a part of at least one assigned group of people: the processing recommendations generated by the control and evaluation unit and/or the processing instructions generated by the control and evaluation unit are appropriate from the point of view of the assigned group of people. These evaluation signals are preferably evaluated by a part of the technician and subsequently used to verify the derived rules to be used and adapted or even discarded if necessary.

Alternatively, the messages generated after the application of the correlation and derivation rules of the statistical analysis of the data can also be stored simply in the form of processing recommendations and/or processing instructions. The suitability of the message may then be checked and verified or rejected by a technician. With this feedback, the derived rules are then manually adapted and thus optimized.

In a preferred development of the above-described photovoltaic solar cell test system with evaluation signal, the control and evaluation unit is adapted and configured to carry out statistical analyses between the generated processing recommendations and processing instructions and the evaluation signals obtained in response thereto, and to validate and adapt the derivation rules used on the basis of these statistical analyses. In this variant, the above-described evaluation work of the technician is largely or completely automated in order to provide a self-learning system. For this purpose, systems with artificial intelligence can be used and trained, for example, by using neural networks.

The object of the invention is also achieved by a method for optimizing the production of solar cells by means of a flow-line solar cell production plant by using a photovoltaic solar cell testing system as described above. As explained above, the in-line solar cell production plant is composed of a plurality of process apparatuses having process measurement apparatuses for performing production measurements in order to generate production measurement data.

Preferably, the improvement of the method for optimizing the in-line production of solar cells consists in:

correlating the statistical analysis of the test measurement data of the different test measurements with each other, and/or

Correlating the statistical analysis of the test measurement data of the test measurements with the statistical analysis of the production measurement data, and/or

Correlating the statistical analysis of the test measurement data with the production input data, and/or

Correlating the statistical analysis of the production measurement data with the production input data,

in order to generate a correlation result and to derive from the correlation result, with the aid of the derivation rule, at least one processing proposal and/or at least one processing instruction assigned to at least one group of persons participating in the pipeline production of the solar cell, and the at least one processing proposal and/or the at least one processing instruction are transmitted to the at least one assigned group of persons. From the correlation of the various data sets in the overall data space and the resulting images, the urgency of performance loss can be predicted even if the partially fabricated solar cells in the in-line production sequence have not advanced the test measurements. In this way, this performance loss can be resisted earlier.

Preferably, the method for optimizing the in-line production of solar cells is improved in that the derived rules of the photovoltaic solar cell test system are checked and adapted by a feedback system aiming at producing solar cells with the best quality, which feedback system is supplied with feedback information by at least one staff member participating in the in-line production of solar cells. It is particularly preferred to assign this task to a technician who has a comprehensive understanding of the relationships and a great deal of experience gained from the production plant. A fully manual optimization or a partially automated optimization may be performed. In the case of partially automated optimization, the system has proposed certain modifications to the derived rules, which are verified, adapted or discarded by a part of the technician. In this case, systems with artificial intelligence are used and trained, for example, by using neural networks.

According to a further advantageous variant of the method for optimizing the production line of solar cells, the derivation rules are checked and adapted by an automatic optimization program. The responsible technician can still be used to perform authenticity monitoring on the checked and adapted derived rules.

A preferred refinement of the method for optimizing the line production of solar cells is characterized in that processing recommendations and/or processing instructions to which a part of the assigned staff group does not respond are communicated and/or communicated to other staff groups with a higher degree of attention or a higher relevance level after the confirmation time has elapsed. In this way, a fast response to messages generated by the test system is ensured. Therefore, the possibility of unintentional or intentional omission of the message is reduced, and the response time for initiating the countermeasure is also reduced in the case where the solar cell produced in the in-line production plant is about to occur or has started to degrade in performance.

Advantageously, the method for optimizing the in-line production of solar cells is improved such that a data pattern indicating maintenance requirements and/or signs of wear of the process equipment is determined from the generated correlation results. In the multidimensional consideration of the entire data space of test measurements and production measurements, the need for maintenance and/or signs of wear on the process equipment are noted earlier, so that production stoppages and long production stoppages can be avoided, since corresponding maintenance precautions or worn parts to be replaced are ready to be able to respond quickly when required. In this way, the down time of the in-line production plant can be further reduced, thereby reducing production costs.

Drawings

Further aspects of the invention will be explained with the aid of a test system and a purely exemplary embodiment of a method for optimizing the in-line production of solar cells by using such a test system and with the aid of the accompanying drawings, in which:

fig. 1 shows in a purely schematic representation an exemplary embodiment of a photovoltaic solar cell test system integrated into a pipeline solar cell production plant, an

Fig. 2 shows an exemplary embodiment of a method for optimizing the production of solar cells by means of a pipeline solar cell production plant by using a photovoltaic solar cell testing system as particularly represented in fig. 1.

Detailed Description

The in-line solar cell production plant is here represented schematically and by way of example by a linear sequence of a plurality of process apparatuses PE1, PE2, PEn. In such a flow-line production plant, for example, the solar cells SC may be produced on the basis of semiconductor wafers. The finally produced solar cell SC is measured by means of an exposure and measurement device 10 for determining its quality parameters. The exposure and measurement device 10 is part of a photovoltaic solar cell testing system, which is also referred to in technical terminology as a "flash lamp". In order to determine the quality parameter, a series of test measurements is typically performed in order to generate test measurement data TM.

The test measurement data TM determined by the respective solar cell SC is fed to a control and evaluation unit 20 assigned to the test system. The control and evaluation unit 20 furthermore receives production measurement data PM from each process plant PE1, PE2, PEn, which is equipped with at least one production measurement device PM1, PM2, PMn assigned to it. Each production measurement device PM1, PM2, PMn generates specific production measurement data PM, respectively. These production measurement data PM are in turn fed to the control and evaluation unit 20 of the test system.

In this case, a certain degree of evaluation of the production measurement data PM generated at the respective production measurement device PM1, PM2, PMn may already be performed on a part of the production measurement device PM1, PM2, PMn. The production measurement devices PM1, PM2, PMn are then configured such that they not only generate production measurement data PM, but also further process them by means of their own evaluation units. Furthermore, this leads to production measurement data PM, which, however, have been fed to the control and evaluation unit 20 in a fully or partially processed form. During all or part of the processing of the process measurement data PM, a statistical analysis PMstat of the process measurement data is created. This involves, for example, the formation of time-averaged and/or analysis of variance values. However, such an analysis can also be centrally performed in the control and evaluation unit 20 of the photovoltaic solar cell test system due to the lack of a corresponding evaluation unit of the production measuring devices PM1, PM2, PMn. The control and evaluation unit 20 can be structurally closely coupled to the exposure and measurement device 10. It is also conceivable that this functionality is spatially separated from the location where the test measurement data TM is generated. It is only necessary to ensure that the test measurement data TM is fed to the control and evaluation unit 20.

The production measurement data PM may be generated by various measurements in the area of the process equipment PE1, PE2, PEn. These are in particular measurements on partially treated solar cells SC in the respective process equipment PE1, PE2, PEn. Additionally or alternatively, the production measurement devices PM1, PM2, PMn of the process plants also generate production measurement data PM in the form of process parameters of the treatment methods occurring in the respective process plant PE1, PE2, PEn. In order to ensure quality, these process parameters must in any case be monitored by measurement. In this regard, the production measurement devices PM1, PM2, PMn of all embodiments of the photovoltaic solar cell testing system are configured and adapted such that they generate and provide multiple types of production measurement data of one variation or another.

As a further data stream, so-called production input data PED is fed to the control and evaluation unit 20. These are the material parameters of the raw materials used which are further processed to form the solar cell, as well as the material parameters of the consumable materials used in the individual processing methods of the respective process equipment PE1, PE2, PEn.

The control and evaluation unit 20 performs a statistical analysis and correlates them with each other in the entire data space available to the control and evaluation unit 20. Processing recommendations or processing instructions are generated with the help of derived rules based on analysis and/or correlation of the data. The method will be explained in more detail below in connection with fig. 2. These processing recommendations or processing commands are transmitted to the display devices PD1, PD2, PDn of the process installations PE1, PE2, PEn by means of the communication equipment 21 belonging to the test system and displayed there. In addition or alternatively, the processing proposal or the processing instruction can also be displayed on a display device 22 belonging to the control and evaluation unit 20 or on a display device 12 belonging to the exposure and measurement device 10.

In particular, the processing advice or the processing instructions draw attention to the various groups of people PG1, PG2, PGn along the pipeline solar cell production plant by means of the display devices of the process apparatuses PD1, PD2, PDn. In addition to or instead of the display devices of the process devices PD1, PD2, PDn, processing instructions can also be transmitted wirelessly by means of the communication device 21 to the mobile terminals M1, M2, Mn of the respectively assigned personnel groups PG1, PG2, PGn.

The control and evaluation unit 20 further comprises a digital memory 23 in which the derived rules are stored. In this embodiment, a digital interface 24 of the control and evaluation unit 20 is also provided, by means of which the derivation rules can be modified by the instrument to be connected.

Fig. 2 shows an exemplary embodiment of a method for optimizing the production of solar cells by means of a pipeline solar cell production plant by using a photovoltaic solar cell testing system as particularly represented in fig. 1. The method is functionally executed in a control and evaluation unit 20 of the solar cell test system. For this purpose, a statistical analysis of the test measurement data TM provided by the exposure and measurement device 10 of the solar cell test system, which is referred to as TMstat, is carried out in the control and evaluation unit 20. Such statistical analysis is performed using production measurement data PM generated on a part of the production measurement devices PM1, PM2, PMn. As described above, the production measurement devices PM1, PM2, PMn perform measurements within the scope of the processing methods occurring in the respective process devices PE1, PE2, PEn, and will provide the obtained measurement values as production measurement data PM. The statistical analysis of the production measurement data PMstat may have been generated by the corresponding evaluation unit of the production measurement devices PM1, PM2, PMn and/or by the control and evaluation unit 20 of the solar cell test system. Thus, there is a statistical analysis of test measurements TMstat, production measurements PMstat and the above-mentioned production input data PED. From these data, a correlation analysis 201 is performed in the control and evaluation unit 20 in order to generate correlation results. These correlation results are processed in a further method step by using the derivation rules 202. As a result, the application of the derived rules 202 delivers at least one processing proposal 203 and/or at least one processing instruction 204 and/or at least one other correlation selected from the statistical analysis of test measurements TMstat, production measurements PMstat and production input data PED is requested before a new application of the derived rules 202 to the correlation results 201 occurs. The generated processing recommendations 203 and processing instructions 204 are transmitted by means of the communication device 21 of the control and evaluation unit 20 to the various groups of staff PG1, PG2, PGn working in the various task areas within the pipeline solar cell production plant. These groups of persons PG1, PG2, PGn preferably generate the reception acknowledgement signals EQ1, EQ2, EQn which verify that the processing proposal 203 and/or the processing instruction 204 have been noticed. Preferably, the evaluation signals relating to the previously received processing recommendations 203 and processing instructions 204 are furthermore generated on a part of the various groups of persons PG1, PG2, PGn. In this way, by means of a feedback loop, it is intended that the control and evaluation unit 20 knows whether and to what extent the received processing proposal 203 and/or processing instruction 204 has been properly classified on a part of the various groups of persons PG1, PG2, PGn. The feedback loop may be used to equip the control and evaluation unit 20 with self-learning functionality.

List of references:

10 Exposure and measurement apparatus

12 display device of exposure and measurement equipment

20 control and evaluation unit

200 statistical analysis of test measurement data and production measurement data

201 correlation results obtained from statistical analysis of test measurement data and/or statistical analysis of production measurement data and/or correlation of production input data

202 application of derived rules to related results

203 processing recommendations

204 process the instruction

205 feedback system

21 communication device

22 display device of a control and evaluation unit

23 digital memory of a control and evaluation unit

24 digital interface for a control and evaluation unit

Process equipment of PE1, PE2 and PEN assembly line solar cell production factory

Production measuring equipment of PM1, PM2 and PMn process equipment

Display device of PD1, PD2 and PDn process equipment

TM test measurement data

Statistical analysis of TMstat test measurement data

PM production measurement data

Statistical analysis of PMstat production measurement data

PED production input data

PG1, PG2, PGn assigned group of people

Mobile terminal of M1, M2 and Mn assigned personnel group

EQ1, EQ2, EQn reception confirmation signals generated by the group of persons

F1, F2, Fn evaluation signals transmitted by the group of persons

SC solar cell