Laboratory color matching intelligent management method and system

Abstract

The invention belongs to the technical field of laboratory color matching management, and particularly relates to an intelligent management method and system for laboratory color matching, and the method comprises the steps: calculating a color matching error index through receiving an ERP task and matching a preliminary color matching scheme, and judging whether to trigger adjustment or not according to the error index; if triggering is carried out, a target color matching source, an adjustment range and a single adjustment amplitude are determined in combination with historical records, color matching simulation is carried out, an adjustment scheme is output, small sample dyeing measurement is carried out based on the preliminary or adjustment scheme, chromatic aberration comparison is carried out, if yes, the scheme is executed, and the adjustment scheme and simulation records are pushed to an ERP historical color matching record log. According to the method, through the historical data driven advanced pre-judgment and virtual simulation adjustment, invalid sample making and blind trial and error are reduced, the color matching efficiency and precision are improved, the dependence on the experience of operators is reduced, and meanwhile, the intelligent level of color matching management is further enhanced through iterative optimization of a formula library through data feedback.

Description

Technical Field

[0001] This invention belongs to the field of laboratory color matching management technology, and more specifically, relates to a laboratory color matching intelligent management method and system. Background Technology

[0002] In the dyeing production process of products in industries such as textile printing and dyeing, coatings and chemicals, the product qualification rate is related to the accuracy of color matching. Therefore, it is necessary to achieve the matching of the original color ratio and the target color standard through accurate color matching. This matching process usually requires laboratory color matching to determine the target color standard matching and ratio scheme. In order to improve the accuracy of laboratory color matching and efficient management, laboratory color matching needs to be managed.

[0003] Existing laboratory color matching typically involves receiving a color matching task, directly selecting suitable colorants based on the task's color standards and substrate characteristics, designing an initial mixing scheme based on historical formula data, and then calculating color difference values ​​to determine whether it meets the requirements by producing standard samples. Upon receiving a color matching task, historical formula data is simply reused or slightly adjusted to generate an initial mixing scheme. This lacks objective quantitative analysis and proactive prediction of potential error patterns in historical color matching records, resulting in a lack of reliable pre-judgment basis for the adaptability of the initial scheme and an inability to identify and avoid color deviation risks in advance.

[0004] Furthermore, if the test finds that the color difference exceeds the standard requirements, it mainly relies on the operator's experience to analyze and judge, which involves multiple small sample production and testing processes. This can easily lead to over-adjustment or under-adjustment. Moreover, the entire color matching process often involves adjusting the direction of color deviation and adjusting the proportion or type of the original color based on experience after the small sample test. This causes the color matching process to fall into a cycle of blindly repeating operations and making mistakes, resulting in a large number of ineffective adjustment operations, which ultimately lengthens the color matching cycle. Summary of the Invention

[0005] In view of this, in order to solve the above problems, a smart management method for laboratory color matching is proposed.

[0006] The objective of this invention can be achieved through the following technical solution: This invention provides a laboratory color matching intelligent management method, which includes: receiving ERP tasks and matching preliminary color matching schemes.

[0007] Retrieve the color matching records of the same ERP task from the historical color matching log of the ERP system, and calculate the color matching error index.

[0008] Based on the color matching error index, determine whether to trigger color matching scheme adjustment. If not, proceed to the next step. Otherwise, based on the color matching record, determine the target color matching original, the adjustment range of the target color matching original, and the single adjustment range, and simultaneously perform color matching simulation, record the color matching simulation record, and output the adjusted color matching scheme.

[0009] Based on the preliminary color scheme or the adjusted color scheme, small samples are stained using a dispensing machine, and color measurements are taken. The measured data are then compared with the QTX standard data to determine whether the stained samples meet the preset requirements.

[0010] If the preset requirements are met, the color scheme will be matched according to the preliminary color scheme or the adjusted color scheme. The adjusted color scheme that triggered the scheme adjustment will be pushed back to the historical color scheme log of the ERP system along with the simulation record, and an updated historical color scheme log will be generated.

[0011] The present invention also provides a laboratory color matching intelligent management system, which includes: a color scheme matching module, an error index calculation module, a color scheme output module, a dyeing comparison module, and a formula update module.

[0012] The color scheme matching module receives ERP tasks and matches preliminary color schemes.

[0013] The error index calculation module retrieves the color matching records of the same ERP task from the historical color matching log of the ERP system and calculates the color matching error index.

[0014] The color scheme output module determines whether to trigger a color scheme adjustment based on the color scheme error index. If not triggered, it proceeds to the next step. Otherwise, it determines the target color scheme, the adjustment range of the target color scheme, and the single adjustment range based on the color scheme record. It then performs a color scheme simulation simultaneously, records the color scheme simulation record, and outputs the adjusted color scheme.

[0015] The staining comparison module stains small samples using a dispensing machine according to the preliminary or adjusted color scheme and measures the color. The measured data is then compared with the QTX standard data to determine whether the stained sample meets the preset requirements.

[0016] If the formula update module meets the preset requirements, it will perform color matching according to the preliminary color matching scheme or the adjusted color matching scheme, and push the adjusted color matching scheme that triggered the scheme adjustment and the simulation record back to the historical color matching record log of the ERP system to generate the updated historical color matching record log.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention retrieves historical color matching records consistent with ERP tasks and calculates the color matching error index to make an advance judgment on the adaptability of the initial color matching scheme. It can determine whether there is a potential color deviation risk in the initial scheme without making standard samples, thereby avoiding the ineffective consumption of experimental materials and manpower and improving the resource utilization rate of the color matching process.

[0018] (2) This invention accurately locks the target color source, adjustment range and single adjustment range by quantitatively analyzing historical color matching data, and completes virtual optimization by combining bidirectional successive color matching simulation. This effectively avoids the problem of over-adjustment or under-adjustment, thereby avoiding blind trial and error, greatly reducing ineffective adjustment operations, reducing the cost of color matching adjustment, and shortening the color matching cycle.

[0019] (3) This invention achieves dynamic updating and iterative optimization of formula data by synchronously pushing the adjusted color scheme and simulation record back to the historical color scheme record log, thereby continuously improving the initial scheme matching accuracy and adjustment efficiency of subsequent similar color scheme tasks, and improving the stability and consistency of color scheme results. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the overall implementation process of the present invention.

[0022] Figure 2 This is a schematic diagram illustrating the calculation process of the color matching error index of this invention.

[0023] Figure 3 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] For details, please refer to [link / reference]. Figure 1 As shown, the present invention provides a laboratory color matching intelligent management method, which includes: S1, receiving ERP tasks and matching preliminary color matching schemes.

[0026] The goal of laboratory color matching is to achieve quantitative matching of color mark requirements on different substrate types (such as fabric and metal). The final color effect is determined by the color matching ratio and the substrate type. The color rendering effect of the same color mark ratio on different substrates usually varies greatly. The color matching ratio corresponding to different color mark requirements is also completely different. In order to ensure that the initial color matching scheme is effective and accurate, it is necessary to select historical laboratory color matching formula data with the same color mark requirements and substrate type.

[0027] Specifically, the matching process of the preliminary color scheme includes: extracting the color mark requirements and substrate types of the ERP task, using the color mark requirements and substrate types as collaborative matching elements, and comparing the collaborative matching elements with the collaborative matching elements associated with the laboratory historical color formula data in the historical color matching record log.

[0028] Historical color matching formulas from laboratories with consistent matching elements were used as preliminary color matching schemes.

[0029] S2. Retrieve the color matching records of the same ERP task from the historical color matching log of the ERP system, and calculate the color matching error index.

[0030] Please see Figure 2 As shown, specifically, the calculation process of the color matching error index includes: S21, extracting from each color matching record the proportion of each original color matching before adjustment, the number of color matching adjustments, the end time of each color matching adjustment, the type of the original color matching to be adjusted, and the adjustment ratio of the corresponding type of original color matching, and calculating the overall adjustment coverage and the overall adjustment degree respectively.

[0031] The calculation process of the overall adjustment coverage includes: A1. For each color matching record, the original color matching types adjusted in each color matching adjustment are compared with each other, and the number of existing original color matching types is counted.

[0032] A2. Compare the number of existing color matching source types with the total number of preset color matching sources to obtain the color matching source adjustment coverage of a single color matching record. The color matching source adjustment coverage represents the proportion of the adjusted color matching source types in a single color matching record to the total number of preset color matching sources. The higher the value, the greater the initial scheme deviation of the single color matching record, the more color matching source types need to be adjusted, and therefore the greater the color matching error index.

[0033] The total number of preset color sources is set according to the ERP task. The total number of preset color sources for textile printing and dyeing tasks is 5 to 8, and the total number of preset color sources for coating and chemical tasks is 3 to 6. For example, taking the task of color matching red cotton fabric as an example, the total number of preset color sources is 5, which specifically includes: reactive red, reactive yellow, reactive blue, reactive white and reactive orange.

[0034] A3. Calculate the average of the original color adjustment coverage of a single color matching record, and use it as the overall adjustment coverage.

[0035] The calculation process of the overall adjustment degree includes: B1. For each color matching record, the adjustment ratios of the same original color matching type in each color matching adjustment are summed to obtain the total adjustment ratio corresponding to each original color matching type.

[0036] B2. Select the proportion of the corresponding color scheme type to be adjusted from the proportions of each color scheme original before adjustment, and use it as the initial proportion of the corresponding color scheme original type to be adjusted.

[0037] B3. Calculate the ratio of the total adjustment ratio to the initial ratio for each original color scheme type to obtain the degree of adjustment for each original color scheme type.

[0038] B4. Select the largest adjustment level from the adjustment levels of each original color scheme type as the adjustment level of the corresponding color scheme record.

[0039] B5. Extract the end time of the last color adjustment from each color matching record, and set the time weight based on the end time and the current time.

[0040] In practical applications, the production process and storage conditions of color matching materials may be adjusted over time. At the same time, the wear and tear of equipment and the calibration cycle will also affect the accuracy of the mixing ratio. Consequently, the degree of adjustment recorded in the early stages may not represent the actual situation of the current scenario. Based on this, the present invention needs to set time weights according to the end time and the current time.

[0041] As a preferred example, the specific process for setting time weights is as follows: Extract the end time of the last color adjustment from each color matching record, and denot it as... , Indicates the sequence number of the color matching record. From 1 to n, and record the end time of the last adjustment in the first color matching record as n. .

[0042] according to and Set time weights , In the formula, For the current time, Indicates the first The secondary color scheme records the time interval from the current time. This represents the total duration of all color scheme records. Indicates the first The ratio of the time interval between a color matching record and the current time to the total duration is given. The smaller the time interval between a color matching record and the current time, the smaller the ratio and the greater the time weight.

[0043] By setting time weights based on the end time of the last color adjustment in each color matching record and the current time, and by weighting and summing the time weights to obtain the overall adjustment degree, the recent adjustment degree can dominate the overall calculation, ensuring that the overall adjustment degree can truly reflect the adjustment risks that the current task may face.

[0044] B6. Based on the time weight of each color matching record, the adjustment degree of each color matching record is linearly weighted and summed to obtain the overall adjustment degree. The adjustment degree characterizes the severity of the deviation between the original color matching ratio and the target color matching ratio. The greater the severity of the deviation, the greater the adjustment error, that is, the greater the color matching error index.

[0045] The above-mentioned linear weighted summation is an existing formula and will not be shown or explained in detail in this invention.

[0046] S22. The overall adjustment coverage and the overall adjustment degree are linearly weighted and summed to obtain the color matching error index.

[0047] The overall adjustment coverage reflects the general range of color scheme types and adjustment scenarios that need adjustment in similar historical tasks, helping to determine the universality of the adjustment requirements. The overall adjustment degree, on the other hand, is directly related to the severity of deviation between historical color schemes and the target color scheme, serving as a necessary basis for determining whether the current preliminary scheme needs adjustment. Therefore, the weight of the overall adjustment degree is greater than that of the overall adjustment coverage. Preferably, the weight of the overall adjustment coverage is assigned to 0.4, and the weight of the overall adjustment degree is assigned to 0.6.

[0048] This invention retrieves historical color matching records that are completely consistent with the current ERP task color code requirements and substrate type. Based on the color matching error index obtained by quantitative calculation of historical data, it can make advance judgment on the adaptability of the initial color matching scheme. Moreover, it can accurately determine whether there is a potential color deviation risk in the initial scheme without preparing physical samples. It transforms the current lagging trial and error verification into accurate prediction in advance, which greatly improves the resource utilization and overall efficiency of the laboratory color matching process.

[0049] S3. Based on the color matching error index, determine whether the color matching scheme adjustment is triggered. If not, proceed to the next step. Otherwise, based on the color matching record, determine the target color matching original, the adjustment range of the target color matching original, and the single adjustment range, and simultaneously perform color matching simulation, record the color matching simulation record, and output the adjusted color matching scheme.

[0050] It should be added that the condition for triggering color scheme adjustment is that the color scheme error index is greater than the preset index threshold. That is, when the color scheme error index is greater than or equal to the preset index threshold, the color scheme adjustment is triggered; when the color scheme error index is less than the preset index threshold, the color scheme adjustment is not triggered.

[0051] The specific process for setting the preset index threshold is as follows: Extract all historical color matching records that are completely consistent with the color code requirements and substrate type of the current ERP task from the historical color matching record log. Records in the historical records that complete the qualified color matching by only adjusting the initial color matching scheme once are recorded as reference historical color matching records. Calculate the color matching error index of all reference historical color matching records and use the average value of the color matching error index as the preset index threshold.

[0052] Specifically, the process of determining the target color source includes: calculating the total adjustment ratio of each type of adjusted color source during each color adjustment, and calculating the average total adjustment ratio of each type of adjusted color source.

[0053] Count the total number of times the original color type of the color scheme appears in all color scheme records, and use the ratio of the total number of occurrences to the number of times the color scheme is recorded as the repeated color scheme adjustment ratio.

[0054] The adjustment importance of the corresponding original color scheme is obtained by multiplying the sum of the average adjustment ratios of each original color scheme type by the repeated adjustment ratio of the corresponding original color scheme type.

[0055] Count the number of times each color scheme original type appears, and record the color scheme original type with the most occurrences as the candidate color scheme original type.

[0056] The candidate color source type corresponding to the adjustment importance greater than the preset importance threshold is used as the target color source.

[0057] It should be noted that the specific setting process of the above-mentioned preset importance threshold is as follows: Extract all historical color matching records that are completely consistent with the color standard requirements and substrate type of the current ERP task from the historical color matching record log, remove invalid records caused by equipment failure, operation error, abnormal color source, etc., and calculate the adjustment importance of each color source according to the adjustment importance calculation method of the present invention based on the remaining historical color matching records after removal. After sorting them from smallest to largest, an adjustment importance sequence is constructed, and the adjustment importance value corresponding to the 90th percentile is used as the preset importance threshold.

[0058] Specifically, the process of determining the adjustment range includes: extracting the adjustment ratio of the target color original in each color matching record corresponding to each color matching adjustment, and constructing the adjustment ratio sequence of the target color original.

[0059] Outlier removal is performed on the adjustment ratio sequence, and the maximum and minimum adjustment ratios of each target color source are extracted from the removed adjustment ratio sequence.

[0060] It should be noted that, as a preferred embodiment of the present invention, the outlier removal method adopted above is the mean ratio range method. That is, the difference between the mean of the target color original adjustment ratio sequence and three times the standard deviation is used as the lower limit of the normal value range, and the sum of the mean of the target color original adjustment ratio sequence and three times the standard deviation is used as the upper limit of the normal value range. Adjustment ratios outside the normal value range are removed, thereby effectively eliminating extreme adjustment ratios caused by accidental anomalies in the color original batch, and ensuring that the maximum or minimum adjustment ratio extracted subsequently can accurately define the reasonable adjustment boundary of the target color original, avoiding the adjustment range being too wide or too narrow due to outlier interference.

[0061] The minimum adjustment ratio of the target color scheme is used as the lower limit of the adjustment range, and the maximum adjustment ratio of the target color scheme is used as the upper limit of the adjustment range, thus obtaining the adjustment range of the corresponding target color scheme.

[0062] Specifically, the process of determining the single adjustment range includes: obtaining the adjustment range of each adjustment color source in the same way as obtaining the adjustment range of the target color source.

[0063] Calculate the interval similarity between the adjustment interval of each target color scheme original and the adjustment interval of the adjusted color scheme original, and record the adjusted color scheme original with an interval similarity greater than a preset similarity threshold as the reference color scheme original.

[0064] In combination with the actual needs of laboratory color matching in industrial fields such as textile printing and dyeing, coatings and chemicals, the general range of the preset similarity threshold is 0.7 to 0.9. As a preferred embodiment of the present invention, the preset similarity threshold is assigned a value of 0.8. Implementers can make dynamic adjustments within the corresponding value range according to the color matching accuracy requirements.

[0065] It should be added that the interval similarity calculation process is as follows: the similarity between the upper limit of the adjustment interval of each target color scheme original and the upper limit of the adjustment interval of the original color scheme is calculated by using the cosine similarity algorithm. At the same time, the similarity between the lower limit of the adjustment interval of each target color scheme original and the lower limit of the adjustment interval of the original color scheme is calculated. Then, the minimum similarity is taken as the interval similarity. The cosine similarity algorithm is existing technology and will not be shown or explained in detail in this invention.

[0066] Count the number of times each reference color scheme appears, and compare it with the total number of color scheme records. Record the ratio as the reference weight.

[0067] The number of adjustments for each reference color scheme is counted, and the number of adjustments is sorted in ascending order to construct an adjustment number sequence. The quartiles and interquartile ranges of the adjustment number sequence are calculated, and a normal boundary interval is set based on the quartiles and interquartile ranges.

[0068] It should be noted that the quarter-digit of the adjustment sequence is denoted as... The third-quarter digit of the sequence of adjustment times is denoted as . ,Will and The difference is used as the interquartile range .

[0069] The formula for calculating the lower limit of the normal boundary interval is: , Indicates when If it is less than or equal to 1, then 1 is taken as the lower limit of the normal boundary interval. If it is greater than 1, then The result is used as the lower limit of the normal boundary interval.

[0070] The formula for calculating the upper limit of the normal boundary interval is: The upper limit of the normal boundary interval is .

[0071] For each reference color scheme, determine whether its number of adjustments is within the normal boundary range: if the number of adjustments is within the normal boundary range, then the number of adjustments and the reference weight are respectively used as the final number of adjustments and the final reference weight.

[0072] If the number of adjustments exceeds the upper limit of the normal boundary interval, the upper limit value of the interval is taken as the final number of adjustments, and a first reduction coefficient is calculated based on the degree to which it exceeds the upper limit. The reference weight is then multiplied by the first reduction coefficient to obtain the final reference weight.

[0073] The calculation process of the first reduction coefficient is as follows: First, calculate the absolute value of the difference between the number of adjustments and the final number of adjustments. Then, perform a linear transformation on the absolute value of the difference. Finally, subtract the linear transformation result from 1 to obtain the first reduction coefficient.

[0074] It should be added that, in the above linear transformation, the present invention can preferably use minimum-maximum linear normalization, wherein the maximum and minimum values ​​in the normalization process are respectively derived from the maximum and minimum number of adjustments recorded in the historical color matching records, and minimum-maximum linear normalization is a prior art and will not be shown or described in detail in the present invention.

[0075] If the number of adjustments is less than the lower limit of the normal boundary interval, the lower limit of the interval is taken as the final number of adjustments, and a second reduction coefficient is calculated based on the degree to which it is lower than the lower limit. The reference weight is then multiplied by the second reduction coefficient to obtain the final reference weight.

[0076] The calculation process for the second reduction factor is the same as that for the first reduction factor, and will not be repeated here.

[0077] Based on the final reference weights of each reference color source, the final number of adjustments is linearly weighted and summed, and the calculation result is rounded up to obtain the baseline number of adjustments.

[0078] The difference between the upper and lower limits of the adjustment range of the target color scheme is used to obtain the width of the corresponding adjustment range of the target color scheme.

[0079] Calculate the ratio of the adjustment range width of the target color scheme original to the baseline number of adjustments to obtain the single adjustment range of the target color scheme original.

[0080] Specifically, the process of determining the color scheme adjustment includes: using the target color scheme's original ratio as the starting point for simulation, retrieving its adjustment range, single adjustment range, and QTX standard data, while keeping the initial ratio settings of non-target color schemes.

[0081] The target color source's mixing ratio baseline value refers to the initial mixing ratio of the target color source in the preliminary color scheme.

[0082] Calculate the ratio of the adjustment interval width to the single adjustment amplitude, and round up to obtain the maximum number of simulation steps.

[0083] Starting from the simulated starting point, adjust the simulated color data bidirectionally and sequentially according to the single adjustment range. Compare the color difference between the adjusted simulated color data and the QTX standard data of the ERP task to obtain the color difference value, and record the adjusted ratio value simultaneously.

[0084] The bidirectional successive adjustment refers to taking the initial ratio of the target color source as the starting point of the simulation, and within its determined adjustment range, gradually increasing or decreasing the ratio in two directions, according to the preset single adjustment range.

[0085] The color difference value mentioned above is calculated using the CIE1976 ΔE*ab formula, which is as follows: In the formula, This is the color difference value. , To adjust the difference between the L value of the simulated color data and the L value of the target color scale in the QTX standard data, , To adjust the difference between the 'a' value of the simulated color data and the 'a' value of the target color scale in the QTX standard data, , To adjust the difference between the b-value of the simulated color data and the b-value of the target color scale in the QTX standard data, , , These are the L, a, and b values ​​of the adjusted simulated color data. , , These are the L, a, and b values ​​of the target color mark in the QTX standard data. The differences between the L, a, and b values ​​are all proportional to the color difference value. , , The larger the values ​​of all three, the greater the color difference.

[0086] As a preferred example, the color difference value can also be calculated using the CMC formula or CIE94 formula, etc. The CMC formula and CIE94 formula are existing formulas and will not be described in detail here.

[0087] The final ratio setting of the target color source is the adjustment ratio value that does not exceed the preset color difference threshold for the first time. The final ratio setting of the target color source and the initial ratio setting of the non-target color source are combined to form the adjustment color scheme.

[0088] The preset color difference threshold is set with reference to the general empirical value range of laboratory color matching. When using the CIE1976 ΔE×ab formula, the preset color difference threshold range is 1.5 to 2.5. If the CMC formula is used, the preset color difference threshold range is 0.5 to 1.5. If the CIE94 formula is used, the preset color difference threshold range is 0.8 to 1.8.

[0089] When the color matching accuracy requirement is low, the preset color difference threshold can be set to the upper limit of the above value range. When the color matching accuracy requirement is high, the preset color difference threshold can be set to the lower limit of the above value range. The higher the color matching accuracy requirement, the closer the preset color difference threshold is to the lower limit of the value range. Implementers can set it within this range according to the actual color matching accuracy requirements. This invention does not impose specific limitations.

[0090] S4. Based on the preliminary color scheme or the adjusted color scheme, complete the staining of the sample using a dispensing machine and measure the color. Compare the obtained measured data with the QTX standard data to determine whether the stained sample meets the preset requirements.

[0091] It should be noted that the condition for determining whether the dyed sample meets the preset requirements is that the color difference comparison result between the measured data of the dyed sample and the QTX standard data is less than or equal to the preset color difference threshold. That is, when the color difference comparison result is less than or equal to the preset color difference threshold, the dyed sample is determined to meet the preset requirements; when the color difference comparison result is greater than the preset color difference threshold, the dyed sample is determined to not meet the preset requirements.

[0092] S5. If the preset requirements are met, the color scheme is matched according to the preliminary color scheme or the adjusted color scheme, and the adjusted color scheme that triggers the scheme adjustment is pushed back to the historical color scheme log of the ERP system together with the simulation record to generate the updated historical color scheme log.

[0093] Please see Figure 3 As shown, the present invention also provides a laboratory color matching intelligent management system, which includes: a color scheme matching module, an error index calculation module, a color scheme output module, a dyeing comparison module, and a formula update module.

[0094] In the above, the error index calculation module is connected to the color scheme matching module and the color scheme output module, respectively. The dyeing comparison module is connected to the color scheme output module and the formula update module, respectively. The dyeing comparison module is also connected to the color scheme matching module.

[0095] The color scheme matching module receives ERP tasks and matches preliminary color schemes.

[0096] The error index calculation module retrieves the color matching records of the same ERP task from the historical color matching log of the ERP system and calculates the color matching error index.

[0097] The color scheme output module determines whether to trigger a color scheme adjustment based on the color scheme error index. If not triggered, it proceeds to the next step. Otherwise, it determines the target color scheme, the adjustment range of the target color scheme, and the single adjustment range based on the color scheme record. It then performs a color scheme simulation simultaneously, records the color scheme simulation record, and outputs the adjusted color scheme.

[0098] The staining comparison module stains small samples using a dispensing machine according to the preliminary or adjusted color scheme and measures the color. The measured data is then compared with the QTX standard data to determine whether the stained sample meets the preset requirements.

[0099] If the formula update module meets the preset requirements, it will perform color matching according to the preliminary color matching scheme or the adjusted color matching scheme, and push the adjusted color matching scheme that triggered the scheme adjustment and the simulation record back to the historical color matching record log of the ERP system to generate the updated historical color matching record log.

[0100] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A laboratory color matching intelligent management method, characterized in that, The method includes: Receive ERP tasks and match preliminary color schemes; Retrieve color matching records that are identical to the ERP task from the historical color matching log of the ERP system, and calculate the color matching error index; Based on the color matching error index, determine whether to trigger color matching scheme adjustment. If not triggered, proceed to the next step. Otherwise, based on the color matching record, determine the target color matching original, the adjustment range of the target color matching original, and the single adjustment range, and simultaneously perform color matching simulation, record the color matching simulation record, and output the adjusted color matching scheme. Based on the preliminary color scheme or the adjusted color scheme, small samples are stained using a dispensing machine, and color measurements are taken. The measured data are compared with the QTX standard data to determine whether the stained samples meet the preset requirements. If the preset requirements are met, the color scheme will be matched according to the preliminary color scheme or the adjusted color scheme. The adjusted color scheme that triggered the scheme adjustment will be pushed back to the historical color scheme log of the ERP system along with the simulation record, and an updated historical color scheme log will be generated.

2. The intelligent management method for laboratory color matching as described in claim 1, characterized in that: The matching process for the preliminary color scheme includes: Extract the color mark requirements and substrate types of the ERP task, use the color mark requirements and substrate types as collaborative matching elements, and compare the collaborative matching elements with the collaborative matching elements associated with the laboratory historical color matching formula data in the historical color matching record log. Historical color matching formulas from laboratories with consistent matching elements were used as preliminary color matching schemes.

3. The intelligent management method for laboratory color matching as described in claim 1, characterized in that: The calculation process for the color matching error index includes: Extract the proportion of each original color scheme before adjustment, the number of color scheme adjustments, the end time of each color scheme adjustment, the type of the original color scheme adjusted, and the adjustment proportion of the corresponding original color scheme type from the color scheme record, and calculate the overall adjustment coverage and the overall adjustment degree respectively. The color matching error index is obtained by linearly weighting and summing the overall adjustment coverage and the overall adjustment degree.

4. The intelligent management method for laboratory color matching as described in claim 3, characterized in that: The calculation process for the overall adjustment coverage includes: For each color scheme record, the original color scheme types adjusted during each color scheme adjustment are compared with each other, and the number of existing original color scheme types is counted. The number of existing color matching original types is compared with the total number of preset color matching originals to obtain the color matching original adjustment coverage of a single color matching record; Calculate the average original color adjustment coverage of a single color matching record, and use it as the overall adjustment coverage.

5. The intelligent management method for laboratory color matching as described in claim 3, characterized in that: The calculation process for the overall adjustment degree includes: For each color scheme record, the adjustment ratios of the same original color scheme type in each color scheme adjustment are summed to obtain the total adjustment ratio corresponding to each original color scheme type. Select the proportion of the corresponding color scheme type from the proportions of each color scheme original before adjustment, and use it as the initial proportion of the corresponding color scheme original type; Calculate the ratio of the total adjustment ratio to the initial ratio for each original color scheme type to obtain the degree of adjustment for each original color scheme type; The largest adjustment level is selected from the adjustment levels of each original color scheme type and used as the adjustment level for the corresponding color scheme record; Extract the end time of the last color adjustment from each color matching record, and set a time weight based on the end time and the current time; Based on the time weight of each color matching record, the adjustment degree of each color matching record is linearly weighted and summed to obtain the overall adjustment degree.

6. The intelligent management method for laboratory color matching as described in claim 3, characterized in that: The process of determining the target color source includes: The total adjustment ratio of each original color scheme type was calculated during each color scheme adjustment, and the average total adjustment ratio of each original color scheme type was also calculated. Count the total number of times the original color type of the color scheme is adjusted in all color scheme records, and use the ratio of the total number of occurrences to the number of color scheme records as the repeated color scheme adjustment ratio; The adjustment importance of the corresponding original color scheme is obtained by multiplying the sum of the average adjustment ratios of each original color scheme type by the repeated adjustment ratio of the corresponding original color scheme type. Count the number of times each color scheme original type appears, and record the color scheme original type with the most occurrences as the candidate color scheme original type; The candidate color source type corresponding to the adjustment importance greater than the preset importance threshold is used as the target color source.

7. The intelligent management method for laboratory color matching as described in claim 3, characterized in that: The process of determining the adjustment range includes: Extract the adjustment ratio of the target color original in each color matching record corresponding to each color matching adjustment, and construct the adjustment ratio sequence of the target color original. Outlier removal is performed on the adjustment ratio sequence, and the maximum and minimum adjustment ratios of each target color source are extracted from the removed adjustment ratio sequence. The minimum adjustment ratio of the target color scheme is used as the lower limit of the adjustment range, and the maximum adjustment ratio of the target color scheme is used as the upper limit of the adjustment range, thus obtaining the adjustment range of the corresponding target color scheme.

8. The intelligent management method for laboratory color matching as described in claim 7, characterized in that: The process of determining the magnitude of a single adjustment includes: Similarly, obtain the adjustment ranges for each original color scheme using the same method as obtaining the adjustment range for the original target color scheme; Calculate the interval similarity between the adjustment interval of each target color scheme original and the adjustment interval of the original color scheme. The original color scheme original with an interval similarity greater than a preset similarity threshold is recorded as the reference color scheme original. Count the number of times each reference color scheme appears, and compare it with the total number of color scheme records. Record the ratio as the reference weight. The number of adjustments for each reference color scheme is counted, and the number of adjustments is sorted in ascending order to construct an adjustment number sequence. The quartiles and interquartile ranges of the adjustment number sequence are calculated, and a normal boundary interval is set based on the quartiles and interquartile ranges. For each reference color scheme, determine whether the number of adjustments is within the normal boundary range: If the number of adjustments is within the normal boundary range, then the number of adjustments and the reference weight will be used as the final number of adjustments and the final reference weight, respectively. If the number of adjustments exceeds the upper limit of the normal boundary interval, the upper limit value of the interval is taken as the final number of adjustments, and a first reduction factor is calculated based on the degree to which it exceeds the upper limit. The reference weight is then multiplied by the first reduction factor to obtain the final reference weight. If the number of adjustments is less than the lower limit of the normal boundary interval, the lower limit value of the interval is taken as the final number of adjustments, and a second reduction coefficient is calculated based on the degree to which it is lower than the lower limit. The reference weight is then multiplied by the second reduction coefficient to obtain the final reference weight. Based on the final reference weights of each reference color scheme, the final number of adjustments is linearly weighted and summed, and the calculation result is rounded up to obtain the baseline number of adjustments. Calculate the ratio of the adjustment range width of the target color scheme original to the baseline number of adjustments to obtain the single adjustment range of the target color scheme original.

9. The intelligent management method for laboratory color matching as described in claim 5, characterized in that: The process of determining the adjusted color scheme includes: Starting from the target color source's ratio baseline, retrieve its adjustment range, single adjustment range, and QTX standard data. The ratios of non-target color sources are kept at their initial ratio settings. Calculate the ratio of the adjustment interval width to the single adjustment amplitude, and round up to obtain the maximum number of simulation steps; Starting from the simulated starting point, adjust the simulated color data bidirectionally and sequentially according to the single adjustment range. Compare the color difference between the adjusted simulated color data and the QTX standard data of the ERP task to obtain the color difference value, and record the adjusted ratio value simultaneously. The final ratio setting of the target color source is set when the color difference value does not exceed the preset color difference threshold for the first time. The final ratio setting of the target color source and the initial ratio setting of the non-target color source are combined to form the adjusted color scheme.

10. A laboratory color matching intelligent management system, characterized in that: The system includes: The color scheme matching module receives ERP tasks and matches preliminary color schemes. The error index calculation module retrieves color matching records that are the same as the ERP task from the historical color matching record log of the ERP system and calculates the color matching error index. The color scheme output module determines whether to trigger color scheme adjustment based on the color scheme error index. If not triggered, it proceeds to the next step. Otherwise, it determines the target color scheme, the adjustment range of the target color scheme, and the single adjustment range based on the color scheme record. It then performs color scheme simulation simultaneously, records the color scheme simulation record, and outputs the adjusted color scheme. The staining comparison module stains small samples using a dropper according to the preliminary or adjusted color scheme and measures the color. It then compares the measured data with the QTX standard data to determine whether the stained sample meets the preset requirements. If the formula update module meets the preset requirements, it will perform color matching according to the preliminary color matching scheme or the adjusted color matching scheme, and push the adjusted color matching scheme that triggered the scheme adjustment and the simulation record back to the historical color matching record log of the ERP system to generate the updated historical color matching record log.

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