Electronic device manufacturing system

Abstract

The invention provides a manufacturing system of an electronic device. The manufacturing system includes a manufacturing apparatus, a calculation unit, and a comparison unit. The manufacturing equipment provides an existing data string and an instant data string. The calculation unit receives an existing data string and outputs a control upper limit value and a control lower limit value according to the existing data string. The comparison unit is used for generating an exponentially weighted moving average slope (EWMA) value according to the instant data string, and comparing the exponentially weighted moving average slope value with a control upper limit value and a control lower limit value to generate a comparison result.

Description

Technical Field

[0001] The present disclosure relates to a manufacturing system, and more particularly to a manufacturing system for electronic devices and / or electronic components. Background Art

[0002] A manufacturing system may include manufacturing equipment. When the manufacturing equipment is operating to manufacture electronic devices and / or electronic components, it is necessary to keep track of the data values of the process parameters of the manufacturing equipment at all times and control the data values. When the data value approaches or exceeds a control limit value, the manufacturing system will generate a warning message to reduce the production of electronic devices and / or electronic components with abnormal specifications by the manufacturing equipment. However, when the data values of the process parameters of the manufacturing equipment gradually increase or decrease over time and show a trend-like cyclic fluctuation, it is not applicable to use a fixed control limit value to control the manufacturing equipment. Therefore, how to provide an appropriate management method and manufacturing system is one of the research focuses of those skilled in the art. Summary of the Invention

[0003] The present disclosure is directed to a manufacturing system for an electronic device that can control data values showing a trend-like cyclic fluctuation.

[0004] According to an embodiment of the present disclosure, the manufacturing system includes a manufacturing device, a computing unit, and a comparison unit. The manufacturing device provides an existing data string and an instant data string. The computing unit receives the existing data string and outputs a control upper limit value and a control lower limit value based thereon. The comparison unit generates an exponentially weighted moving average (EWMA) slope value based on the instant data string, and compares the exponentially weighted moving average slope value with the control upper limit value and the control lower limit value to generate a comparison result.

[0005] Based on the above, the manufacturing system can calculate the EWMA slope value of the data value, and compare the EWMA slope value with the control upper limit value and the control lower limit value to generate a comparison result. In this way, the manufacturing system can control data values with cyclic fluctuations. Brief Description of the Drawings

[0006] Figure 1 is a schematic diagram of a manufacturing system shown according to an embodiment of the present disclosure;

[0007] Figure 2 is a flowchart of a management method shown according to an embodiment of the present disclosure;

[0008] Figure 3 is a schematic diagram of a data string and data values shown according to an embodiment of the present disclosure;

[0009] Figure 4is a flowchart of a management method shown in an embodiment of the present disclosure;

[0010] Figure 5 is a flowchart of a management method shown in an embodiment of the present disclosure;

[0011] Figure 6 is a schematic diagram of an EWMA slope value shown in an embodiment of the present disclosure;

[0012] Figure 7 is a schematic diagram of data values for a single period shown in an embodiment of the present disclosure.

[0013] Description of Reference Numerals

[0014] 100: Manufacturing system

[0015] 110: Manufacturing equipment

[0016] 120: Computing unit

[0017] 130: Comparison unit

[0018] DB1, DB2, DB3: Database

[0019] EVS: Exponentially Weighted Moving Average (EWMA) slope value

[0020] LD: Lower control limit value

[0021] LU: Upper control limit value

[0022] PDT: Existing data string

[0023] RDT: Real-time data string

[0024] S100, S200, S300: Management method

[0025] S210: System control establishment method

[0026] S110~S130, S220~S240, S211, S212, S310~S340: Steps

[0027] SDT1: First data string

[0028] SDT2: Second data string

[0029] SG1~SG7: Segments

[0030] SR: Comparison result Detailed Implementation Manner

[0031] This disclosure can be understood by referring to the following detailed description in conjunction with the accompanying drawings as described below. It should be noted that for the purpose of clear illustration and easy understanding by the reader, each of the accompanying drawings of this disclosure shows a part of the electronic device, and some components in each of the accompanying drawings may not be drawn to scale. In addition, the number and size of each device shown in the accompanying drawings are only illustrative and are not intended to limit the scope of this disclosure.

[0032] Certain terms are used throughout the description and the following claims to refer to specific components. As those skilled in the art will understand, electronic device manufacturers may use different names to refer to components. This document does not intend to distinguish between components with different names but the same functions. In the following description and in the claims, the terms "comprise," "include," and "have" are used in an open-ended manner and should therefore be interpreted to mean "including but not limited to..." Thus, when the terms "comprise," "include," and / or "have" are used in the description of this disclosure, it will indicate the presence of corresponding features, regions, steps, operations, and / or components, but not limited to the presence of one or more corresponding features, regions, steps, operations, and / or components.

[0033] It should be understood that when a component is referred to as being "coupled to," "electrically connected to," or "conducted to" another component, the component can be directly electrically connected to the other component and can directly establish an electrical connection, or there may be intermediate components between these components for relaying the electrical connection (indirect electrical connection). In contrast, when a component is referred to as being "directly coupled to," "directly conducted to," or "directly electrically connected to" another component, there are no intermediate components.

[0034] Although terms such as first, second, third, etc. may be used to describe different component parts, such component parts are not limited by these terms. The terms are only used to distinguish the component parts in the specification from other component parts. The claims may not use the same terms, but may use terms such as first, second, third, etc. relative to the order required for the components. Thus, in the following description, the first component part may be the second component part in the claims.

[0035] The electronic device disclosed herein may include a display device, an antenna device, a sensing device, a light-emitting device, a touch display, a curved display, or a free-shaped display, but is not limited thereto. The electronic device may include a foldable or flexible electronic device. The electronic device may, for example, include electronic components, liquid crystal, light-emitting diodes, quantum dots (QDs), fluorescence, phosphor, other suitable display media, or a combination of the above materials, but is not limited thereto. The electronic components may include passive components and active components, such as capacitors, resistors, inductors, diodes, transistors, etc. The diodes may include light-emitting diodes or photodiodes. The light-emitting diodes may, for example, include organic light-emitting diodes (OLEDs), mini light-emitting diodes (mini LEDs), micro light-emitting diodes (micro LEDs), or quantum dot light-emitting diodes (QLEDs, QDLEDs), or other suitable materials, or a combination of the above, but is not limited thereto. The display device may, for example, include a tiled display device, but is not limited thereto. The antenna device may, for example, be a liquid crystal antenna, but is not limited thereto. The antenna device may, for example, include an antenna tiling device, but is not limited thereto. It should be noted that the electronic device may be any permutation and combination of the foregoing, but is not limited thereto. In addition, the shape of the electronic device may be rectangular, circular, polygonal, a shape with curved edges, or other suitable shapes. The electronic device may have peripheral systems such as a driving system, a control system, a light source system, etc. to support the display device, the antenna device, or the tiling device, but the disclosure is not limited thereto. The sensing device may include a camera, an infrared sensor, a fingerprint sensor, etc., and the disclosure is not limited thereto. In some embodiments, the sensing device may further include a flash, an infrared (IR) light source, other sensors, electronic components, or a combination of the above, but is not limited thereto.

[0036] It should be noted that the technical features in the following different embodiments may be replaced, reorganized, or mixed with each other without departing from the spirit of the disclosure to form another embodiment.

[0037] Please also refer to Figure 1 and Figure 2 , Figure 1 which is a schematic diagram of a manufacturing system shown in an embodiment of the disclosure. Figure 2It is a flowchart of a management method shown in an embodiment of the present disclosure. In this embodiment, the manufacturing system 100 includes a manufacturing device 110, a computing unit 120, and a comparison unit 130. The manufacturing system 100 may further include databases DB1, DB2, DB3 (however, the present disclosure is not limited thereto) to store process parameter data required by the manufacturing system 100, including historical parameter data (i.e., existing data string PDT) and real-time parameter data (i.e., real-time data string RDT) and other data strings.

[0038] In this embodiment, the management method S100 is applicable to the manufacturing system 100. The management method S100 includes steps S110 to S130. In this embodiment, the manufacturing device 110 can provide the existing data string (i.e., historical parameter data) PDT generated during past production of electronic devices to the computing unit 120 to establish the upper control limit value LU and the lower control limit value LD of the manufacturing system 100. The existing data string PDT may include a first data string SDT1 and a second data string SDT2. The computing unit 120 receives the first data string SDT1 and the second data string SDT2 of the existing data string PDT, and establishes the upper control limit value LU and the lower control limit value LD based on the first data string SDT1 and the second data string SDT2.

[0039] In another embodiment, the existing data string PDT may also be provided to the database DB1 for use by the computing unit 120 first, or the database DB1 may transmit the first data string SDT1 and the second data string SDT2 in the existing data string PDT to the database DB2 for use by the computing unit 120.

[0040] In the manufacturing system 100 of this embodiment, the comparison unit 130 is coupled to the computing unit 120 and the manufacturing device 110. In step S110 of the management method S100, the comparison unit 130 receives the upper control limit value LU and the lower control limit value LD. In step S120, the comparison unit 130 calculates the exponentially weighted moving average (EWMA) slope value EVS of the real-time data string (i.e., real-time parameter data) RDT from the manufacturing device 110. In step S130, the comparison unit 130 compares the EWMA slope value EVS of the real-time data string RDT with the upper control limit value LU and the lower control limit value LD and generates a comparison result SR.

[0041] It is worth mentioning here that the manufacturing system 100 can calculate the EWMA slope value EVS of the real-time data string RDT, and compare the EWMA slope value EVS with the upper control limit value LU and the lower control limit value LD to generate a comparison result SR. In this way, the comparison unit 130 can control the real-time data string RDT with cyclic fluctuations.

[0042] In this embodiment, when the EWMA slope value EVS of the real-time data string RDT is greater than the upper control limit value LU or less than the lower control limit value LD, this indicates that the real-time data string RDT at this time does not meet the specifications of the manufacturing parameters, and it is easy to produce electronic devices with poor quality. Therefore, the comparison unit 130 can output a comparison result SR. In addition, the comparison unit 130 can report the real-time data string RDT that does not meet the manufacturing parameter specifications to the database DB3. The comparison result SR representing non-compliance with the manufacturing parameter specifications can be a warning light, warning text, or a warning sound, and the present disclosure is not limited thereto.

[0043] On the other hand, when the EWMA slope value EVS of the real-time data string RDT is less than or equal to the upper control limit value LU and greater than or equal to the lower control limit value LD, this indicates that the real-time data string RDT at this time meets the specifications of the manufacturing parameters. Therefore, the comparison unit 130 may not output a comparison result SR. In other words, in one embodiment, the comparison unit 130 may only output a comparison result SR when the real-time data string RDT does not meet the manufacturing parameter specifications, while in another embodiment, the comparison unit 130 may output a comparison result SR when the real-time data string RDT does not meet the manufacturing parameter specifications and when it meets the manufacturing parameter specifications, and distinguish whether the real-time data string RDT meets the manufacturing parameter specifications through the content of the comparison result SR. In addition, the comparison unit 130 can transfer the real-time data string RDT that meets the manufacturing parameter specifications back to the database DB1.

[0044] In this embodiment, the existing data string PDT and the real-time data string RDT may be, for example, monitored values such as the flow rate value, temperature value, and pressure value of the fluid used by the manufacturing equipment 110, but the present disclosure is not limited thereto. In this embodiment, the calculation unit 120 and the comparison unit 130 can be implemented by a device respectively, but the present disclosure is not limited thereto.

[0045] Please refer to Figure 1 and Figure 3 , Figure 3 is a schematic diagram of the existing data string PDT shown according to an embodiment of the present disclosure. In this embodiment, Figure 3 shows a first data string SDT1 and a second data string SDT2 corresponding to different time intervals. Both the first data string SDT1 and the second data string SDT2 exhibit periodic cyclic fluctuations. Therefore, both the first data string SDT1 and the second data string SDT2 can be used as comparison models.

[0046] For example, the existing data string PDT can be the flow value of the solution passing through the filter element of the manufacturing device 110. As time goes by, when the solution passes through the filter element of the manufacturing device 110, the filter element will gradually become blocked. Therefore, as the usage time of the filter element increases, the degree of blockage of the filter element becomes increasingly serious, resulting in a decrease in the flow value with the usage time. Therefore, when the flow valve of the manufacturing device 110 is adjusted to increase the flow value or the filter element is replaced, the flow value will become larger, and a new cycle will start. In other words, the existing data string PDT before the flow valve of the manufacturing device 110 is adjusted to increase the flow value or the filter element is replaced can be divided into the first data string SDT1, and the subsequent existing data string PDT can be divided into the second data string SDT2.

[0047] In this embodiment, the control upper limit value LU and the control lower limit value LD can be obtained by the calculation unit 120.

[0048] Please refer to Figure 1 、 Figure 3 and Figure 4 , Figure 4 is a flowchart of the management method shown in an embodiment of the present disclosure. In this embodiment, the management method S200 includes a system control establishment method S210 and steps S220 to S240. In this embodiment, the calculation unit 120 executes the system control establishment method S210 to obtain the control upper limit value LU and the control lower limit value LD. The system control establishment method S210 includes steps S211 and S212. In step S211, the calculation unit 120 receives the first data string SDT1 and the second data string SDT2. In step S212, the calculation unit 120 divides the first data string SDT1 and the second data string SDT2 into multiple segments respectively, and calculates the control upper limit value LU and the control lower limit value LD of one of the multiple segments.

[0049] In this embodiment, the calculation unit 120 refers to the cumulative fitting regression line slope of one of the multiple segments of the first data string SDT1 and the second data string SDT2 and the segment before the one segment and the average standard deviation value of each of the multiple segments to output the control upper limit value LU. The calculation unit 120 calculates and outputs the control lower limit value LD by referring to the cumulative fitting regression line slope of one of the multiple segments of the first data string SDT1 and the second data string SDT2 and the segment before the one segment and the average standard deviation value of each of the multiple segments.

[0050] To further illustrate the implementation example of step S212, please refer to Table 1. Table 1 is a generation table of the control upper limit value LU and the control lower limit value LD shown according to an embodiment of the present disclosure. In this embodiment, the data volume of the first data string SDT1 is greater than the data volume of the second data string SDT2. Therefore, the first data string SDT1 can be divided into segments SG1 to SG7, and the second data string SDT2 can be divided into segments SG1 to SG6.

[0051] Table 1:

[0052] SDT1 SDT2 SAV SIG LU LD SG1 S1_1 S2_1 SA1 SIG1 SA1 + 3×SIGA SA1 - 3×SIGA SG2 S1_2 S2_2 SA2 SIG2 SA2 + 3×SIGA SA2 - 3×SIGA SG3 S1_3 S2_3 SA3 SIG3 SA3 + 3×SIGA SA3 - 3×SIGA SG4 S1_4 S2_4 SA4 SIG4 SA4 + 3×SIGA SA4 - 3×SIGA SG5 S1_5 S2_5 SA5 SIG5 SA5 + 3×SIGA SA5 - 3×SIGA SG6 S1_6 S2_6 SA6 SIG6 SA6 + 3×SIGA SA6 - 3×SIGA SG7 S1_7 SA7 SA7 + 3×SIGA SA7 - 3×SIGA SIGA

[0053] The number of segments of the first data string SDT1 and the number of segments of the second data string SDT2 can be determined by formula (1). In formula (1), "SG" is the number of segments. "B" is a constant. "N" is the number of working times or the time of the manufacturing equipment. For example, "B" is equal to "2.5". "N" is equal to "10000". Therefore, the number of segments is equal to "10". For example, "B" is equal to "2". "N" is equal to "10000". Therefore, the number of segments is equal to "8". For example, "B" is equal to "2.5". "N" is equal to "1000". Therefore, based on the rounding method, the number of segments is equal to "8". Based on the unconditional truncation method, the number of segments is equal to "7".

[0054] SG = B × log(N) … formula (1)

[0055] After obtaining the number of segments, the number of working times of the manufacturing equipment in each segment can be determined by formula (2).

[0056] PC = N / SG … formula (2)

[0057] In formula (2), "PC" is the number of working times of the manufacturing equipment 110 in each segment.

[0058] In this embodiment, the more the number of segments, the closer the cyclic fluctuation trend of each segment can approach linearity. The more the number of segments helps to monitor and / or control the non-linear trend of a single cycle.

[0059] In this embodiment, the calculation unit 120 calculates the cumulative fitting regression line slope S1_1 of the segment SG1 of the first data string SDT1, the cumulative fitting regression line slope S1_2 of the segment SG1 of the first data string SDT1 to the whole segment SG2, the cumulative fitting regression line slope S1_3 of the segment SG1 of the first data string SDT1 to the whole segment SG3 (including segment 2), the cumulative fitting regression line slope S1_4 of the segment SG1 of the first data string SDT1 to the whole segment SG4, the cumulative fitting regression line slope S1_5 of the segment SG1 of the first data string SDT1 to the whole segment SG5, the cumulative fitting regression line slope S1_6 of the segment SG1 of the first data string SDT1 to the whole segment SG6, and the cumulative fitting regression line slope S1_7 of the segment SG1 of the first data string SDT1 to the whole segment SG7.

[0060] Similarly, the calculation unit 120 calculates the cumulative fitting regression line slope S2_1 of the segment SG1 of the second data string SDT2, the cumulative fitting regression line slope S2_2 of the segment SG1 of the second data string SDT2 to the whole segment SG2, the cumulative fitting regression line slope S2_3 of the segment SG1 of the second data string SDT2 to the whole segment SG3, the cumulative fitting regression line slope S2_4 of the segment SG1 of the second data string SDT2 to the whole segment SG4, the cumulative fitting regression line slope S2_5 of the segment SG1 of the second data string SDT2 to the whole segment SG5, and the cumulative fitting regression line slope S2_6 of the segment SG1 of the second data string SDT2 to the whole segment SG6.

[0061] The calculation unit 120 calculates the average value SA1 and the standard deviation value SIG1 of the cumulative fitting regression line slope S1_1 of the segment SG1 of the first data string SDT1 and the cumulative fitting regression line slope S2_1 of the segment SG1 of the second data string SDT2. Similarly, the calculation unit 120 calculates the average value SA2 and the standard deviation value SIG2 of the cumulative fitting regression line slope S1_2 of the first data string SDT1 and the cumulative fitting regression line slope S2_2 of the second data string SDT2, and so on. Therefore, the calculation unit 120 calculates the average values SA1 to SA7 and the standard deviation values SIG1 to SIG6.

[0062] The calculation unit 120 calculates the average standard deviation value SIGA of the standard deviation values SIG1 to SIG6.

[0063] In this embodiment, the calculation unit 120 adds the average values SA1 to SA7 of the cumulative fitting regression line slopes corresponding to the segments SG1 to SG7 to three times the average standard deviation value SIGA respectively to output the upper control limit values LU corresponding to the segments SG1 to SG7. The calculation unit 120 subtracts three times the average standard deviation value SIGA from the average values SA1 to SA7 of the cumulative fitting regression line slopes corresponding to the segments SG1 to SG7 respectively to output the lower control limit values LD, but is not limited thereto. In other embodiments, the calculation unit 120 adds N times the average standard deviation value SIGA to the average values SA1 to SA7 of the cumulative fitting regression line slopes respectively to output the upper control limit values LU. The calculation unit 120 subtracts N times the average standard deviation value SIGA from the average values SA1 to SA7 of the cumulative fitting regression line slopes respectively to output the lower control limit values LD. When N is greater than 3, the control procedure for the manufacturing equipment 110 can be relaxed. Similarly, when N is less than 3, the control procedure for the manufacturing equipment 110 can be tightened.

[0064] For example, the calculation unit 120 adds three times the average standard deviation value SIGA to the average value SA1 (i.e., LU = SA1 + 3 × SIGA) to output the upper control limit value LU corresponding to the segment SG1. The calculation unit 120 adds three times the average standard deviation value SIGA to the average value SA2 (i.e., LU = SA2 + 3 × SIGA) to output the upper control limit value LU corresponding to the segment SG2, and so on.

[0065] For example, the calculation unit 120 subtracts three times the average standard deviation value SIGA from the average value SA1 (i.e., LD = SA1 - 3 × SIGA) to output the lower control limit value LD corresponding to the segment SG1. The calculation unit 120 subtracts three times the average standard deviation value SIGA from the average value SA2 (i.e., LD = SA2 - 3 × SIGA) to output the lower control limit value LD corresponding to the segment SG2, and so on.

[0066] It should be noted that in this embodiment, the calculation unit 120 establishes the slope specification for the real-time data string RDT based on the fluctuations of the existing data string PDT. The central value of the slope specification is determined by the average values SA1 to SA7 of the segments SG1 to SG7 of the existing data string PDT. In addition, the upper control limit value LU and the lower control limit value LD of the slope specification are determined by the average standard deviation value SIGA. Therefore, the slope difference between the upper control limit value LU and the lower control limit value LD can be fixed.

[0067] In this embodiment, steps S220 to S240 are Figure 2 similar to steps S110 to S130 of

[0068] Please refer to Figure 1 as well as Figure 5 , Figure 5 which is a flowchart of a management method shown according to an embodiment of the present disclosure. In this embodiment, the management method S300 includes steps S310 to S340. In step S310, the comparison unit 130 receives the control upper limit value LU and the control lower limit value LD. In step S320, the comparison unit 130 calculates the EWMA value of the instantaneous data string RDT using EWMA.

[0069] For example, the comparison device 130 can obtain the EWMA value according to formula (3).

[0070] C k = λ × A (k-1) +(1 - λ) × C (k-1) … Formula (3)

[0071] In formula (3), "Ck" is the EWMA value of the instantaneous data string RDT at the current time (i.e., the k-th moment). "λ" is the weight value. "Ck-1" is the EWMA value of the instantaneous data string RDT at the previous time (i.e., the (k - 1)-th moment). "Ak-1" is the actual value of the instantaneous data string RDT at the previous time (i.e., the (k - 1)-th moment).

[0072] In this embodiment, the weight value λ can be between "0.05" and "1". The weight value λ can be adjusted. For example, when the weight value λ is smaller, the curve of the EWMA value is smoother. When the weight value λ is larger, the curve of the EWMA value is rougher. In some embodiments, the weight value λ can be between "0.85" and "0.95". The present disclosure is not limited to the range of the weight value λ.

[0073] In step S330, the comparison unit 130 calculates the EWMA slope value EVS based on the initial EWMA value and the EWMA value of the instantaneous data string RDT at the current time (i.e., the k-th moment).

[0074] For example, the comparison unit 130 can calculate the EWMA slope value EVS of the current period according to formula (4).

[0075] EVS = (C k - C1) / k… Formula (4)

[0076] In formula (4), "C1" is the initial EWMA value of the current period. The initial EWMA value "C1" is approximately equal to the initial actual value "A0".

[0077] It is worth mentioning here that in steps S320 and S330, the comparison unit 130 only needs the actual value at the previous time (i.e., "Ak-1"), the EWMA value of the immediate data string RDT at the previous time (i.e., "Ck-1"), the EWMA value at the current time (i.e., "Ck"), and the initial EWMA value of the current period (i.e., "C1") to calculate the immediate EWMA slope value EVS of the current period. Therefore, the amount of data that the comparison unit 130 needs to store can be reduced. Accordingly, the computing resources required by the comparison unit 130 can also be saved to save costs and / or energy consumption.

[0078] In step S340, the comparison unit 130 monitors the EWMA slope value EVS based on the control upper limit value LU and the control lower limit value LD. The comparison unit 130 can compare the EWMA slope value EVS of the immediate data string RDT with the control upper limit value LU and the control lower limit value LD in step S340 and generate a comparison result SR.

[0079] Please also refer to Figure 1 、 Figure 6 and Figure 7 , Figure 6 is a schematic diagram of the EWMA slope value shown according to an embodiment of the present disclosure. Figure 7 is a schematic diagram of the data values of a single period shown according to an embodiment of the present disclosure. In this embodiment, Figure 6 shows the EWMA slope values of different periods. It should be noted that based on formula (4), since the "k" value of the initial segment (such as segment SG1) of each period is small, this makes the EWMA slope value of the initial segment of each period have large fluctuations. The initial segment can be regarded as the unstable period of each period. Therefore, in step S340, the comparison unit 130 may not monitor the EWMA slope value EVS of the initial segment of each period based on the control upper limit value LU and the control lower limit value LD.

[0080] An embodiment of the present application also provides a calculator-readable storage medium, on which a calculator program is stored, and the calculator program can be used to cause the calculator to execute the management method of any one of the above embodiments.

[0081] An embodiment of the present application also provides a calculator non-volatile readable storage medium, in which one or more program modules are stored, and when the one or more program modules are used in the device, the device can be caused to execute the instructions of the steps included in any one of the above embodiments.

[0082] The above-described computer-readable storage medium may, for example, be (but is not limited to) an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor device or apparatus, or any combination of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an optical fiber, a read-only optical disc (CD-ROM), an optical storage device, a magnetic storage device, or a suitable combination of any of the foregoing.

[0083] In summary, the manufacturing system calculates the EWMA slope value of the data value and compares the EWMA slope value with the upper control limit value and the lower control limit value to generate a comparison result. In this way, the manufacturing system can control the data value with cyclic fluctuations. In addition, the first data string is divided into multiple segments. The second data string is divided into multiple segments. The more the number of segments, the more the cyclic fluctuation trend of each segment can approach linearity. The more the number of segments helps to monitor and control the non-linear trend of a single cycle.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure, and are not intended to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A manufacturing system for an electronic device, characterized in that, The manufacturing system includes: Manufacturing equipment for providing an existing data string and an instant data string; A calculation unit for receiving the existing data string and outputting a control upper limit value and a control lower limit value based thereon; and A comparison unit for generating an exponentially weighted moving average slope value based on the instant data string, and comparing the exponentially weighted moving average slope value with the control upper limit value and the control lower limit value to generate a comparison result.

2. The manufacturing system according to claim 1, characterized in that When the exponentially weighted moving average slope value is greater than the control upper limit value or less than the control lower limit value, the comparison unit generates a warning result.

3. The manufacturing system according to claim 1, characterized in that The calculation unit obtains the control upper limit value and the control lower limit value through a system control establishment method.

4. The manufacturing system according to claim 3, characterized in that, The system control establishment method includes: The calculation unit receives a first data string and a second data string; and The calculation unit divides the first data string and the second data string into multiple segments respectively, and calculates the control upper limit value and the control lower limit value of one of the multiple segments.

5. The manufacturing system according to claim 4, characterized in that, The calculation unit refers to the cumulative fitting regression line slope between one of the multiple segments and the segment before it and the average standard deviation value of each of the multiple segments to output the control upper limit value.

6. The manufacturing system according to claim 5, characterized in that, The calculation unit adds three times the average standard deviation value to the average value of the cumulative fitting regression line slopes to output the control upper limit value.

7. The manufacturing system according to claim 5, wherein: The calculation unit calculates a first average value and a first standard deviation value of the cumulative fitting regression line slope of the first segment of the first data string and the cumulative fitting regression line slope of the first segment of the second data string; The calculation unit calculates a second average value and a second standard deviation value of the cumulative fitting regression line slope of the second segment of the first data string and the cumulative fitting regression line slope of the second segment of the second data string; And The calculation unit calculates the average standard deviation value of the first standard deviation value and the second standard deviation value.

8. The manufacturing system according to claim 7, characterized in that, The calculation unit outputs the control upper limit value corresponding to the first segment according to the first average value plus three times the average standard deviation value.

9. The manufacturing system according to claim 4, wherein The calculation unit outputs the control lower limit value by referring to the cumulative fitting regression line slope between one of the multiple segments and the segment before it and the average standard deviation value of each of the multiple segments.

10. The manufacturing system according to claim 9, characterized in that, The calculation unit subtracts three times the average standard deviation value from the average value of the cumulative fitting regression line slopes to output the control lower limit value.

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