Surface protecting and cleaning device for plastic mold transportation

Abstract

The invention relates to the field of mold transportation and cleaning, in particular to a surface protecting and cleaning device for plastic mold transportation. Comprising a packaging box, an environment recording module, a cleaning unit, a cleaning verification unit and a controller. The mold is bound with the environment recording module after being protected, and temperature, humidity, vibration and other data are collected during transportation and storage; after the mold reaches the cleaning end, the controller calculates environment exposure risk indexes based on the collected data and the mold process parameters, and matched cleaning parameters are generated according to the environment exposure risk indexes to control the spraying pressure, flow, temperature and time; and after cleaning is completed, the cleaning level is obtained through machine vision and / or surface energy detection, the cleaning level is compared with a preset target, cleaning parameters are fed back and adjusted, meanwhile, whole-process data are written into a file, and quantitative control and traceable management of surface protection and cleaning in the whole period of mold transportation are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of mold transportation and cleaning, in particular to a surface protection and cleaning device for plastic mold transportation. BACKGROUND

[0002] As the core tooling in injection molding production, plastic molds are extremely sensitive to surface roughness, geometric precision, and surface residual contamination, as their key parts such as mold cavity, parting surface, guide pillar, and guide sleeve are mostly made of high-smoothness quenched steel or pre-hardened steel. During the process of transportation and storage, the industry usually adopts protective coating and physical packaging methods to prevent rusting, contamination, and damage caused by handling. Before leaving the factory, the mold cavity and parting surface are sprayed with oil-based or wax-based rust inhibitors to form a temporary protective film. At the same time, wooden boxes, metal frames, or plastic turnover boxes are used to support and position the molds. Some enterprises also use rust-proof films or bags containing volatile rust inhibitors to seal the molds in a plastic film space, combining physical protection and chemical rust prevention.

[0003] In the cleaning process, most existing factories use a combination of manual and equipment methods. Before the molds are put into production at the destination, the operators remove the packaging and fixtures and use solvents or special cleaning agents with spray guns, brushes, or wipes to remove the rust-proof oil and protective wax. For higher cleanliness requirements, some enterprises may arrange for solvent spraying, ultrasonic cleaning, or water-based high-pressure cleaning, supplemented by hot air drying to improve cleaning consistency and environmental friendliness. However, such cleaning processes are often independent of the protective agent system selected at the front end, and the protective agent and cleaning agent suppliers optimize their formulations separately. On-site operators usually choose a cleaning program based on experience. The compatibility between different protective agents and different cleaning processes lacks quantitative evaluation, and whether the cleaning is sufficient depends on visual inspection of the oil sheen, feel, and a small amount of sampling, making it difficult to establish a standardized and traceable surface state archive.

[0004] From the perspective of transportation and storage, some enterprises in the existing technology pay attention to the temperature and humidity of the warehouse or transportation environment, but often only monitor the site roughly and rarely record the actual exposure process of individual molds. The time span from the completion of protective coating to the entry into the cleaning station may vary from a few days to a few months, and the environmental stresses such as humidity changes, storage time, and loading and unloading vibrations and impacts during this period are difficult to trace specifically. Therefore, the protective strategy usually adopts a conservative setting of "better safe than sorry", such as choosing a thicker oil film or a more difficult-to-clean wax film to offset the risk of high humidity or long storage time. This approach, while improving safety margins, increases the difficulty of subsequent film removal and cleaning load. Incomplete cleaning may cause mold cavity roughness, sticking, or surface defects, while attempting to solve the problem by increasing cleaning intensity may easily cause unnecessary microscopic erosion to the high-smoothness surface.

[0005] In addition, the existing automatic cleaning equipment usually adopts a preset fixed program or a small number of gear switching, and the control logic is mainly based on whether the mold size is heavily contaminated or not, instead of matching the real environmental exposure risk of the mold during the transportation and storage period. The cleaning equipment itself generally lacks quantitative description of the actual flushing intensity and corresponding decontamination capacity of the spray pressure, flow, time and temperature on the key surface of the mold, and also lacks a mechanism for closed-loop adjustment of the cleaning intensity and transportation exposure risk and cleaning detection results. Once the front-end environmental conditions change (such as long-time high-humidity storage or abnormal severe vibration), the existing cleaning program is difficult to automatically identify and make targeted strengthening, and can only rely on the operator to temporarily extend the time or repeat the cleaning, resulting in either insufficient cleaning or over-cleaning, which affects the production rhythm and the service life of the mold.

[0006] In summary, the existing technology in the surface protection and cleaning control of plastic mold transportation mainly has the following objective defects: first, the protection agent selection and cleaning process are disconnected, and there is a lack of linkage strategy based on the actual environmental exposure risk, which leads to conservative protection and increases the difficulty and uncertainty of cleaning; second, the environmental stress such as humidity, temperature, vibration and storage time of the mold during transportation and storage is lack of fine recording and quantitative evaluation based on single mold, which makes the subsequent cleaning parameters unable to match the actual risk level; third, the parameters such as spray pressure, flow, temperature and time in the cleaning process are mainly based on experience adjustment, and there is no model to establish a functional relationship between environmental exposure risk and cleaning load, making it difficult to realize the self-adaptive control of "matching intensity according to risk"; fourth, the cleaning effect is mainly judged by the naked eye and simple sampling inspection, and there is a lack of quantitative cleaning level based on visual detection or surface energy test, which cannot provide feedback data for parameter optimization, and it is also difficult to establish a traceable surface state archive for each mold. These problems together cause the surface protection and cleaning in the whole cycle of mold transportation to remain in the stage of experience management, and there is a lack of quantitative control means based on the coupling of environmental exposure, cleaning load and cleaning result. SUMMARY

[0007] The purpose of the present application is to provide a surface protection and cleaning device for plastic mold transportation to solve the technical problems raised in the background art.

[0008] Based on the above idea, the present application provides the following technical solutions: A surface protection and cleaning device for plastic mold transportation, comprising: a packaging box, an environmental recording module, a cleaning unit, a cleaning verification unit and a controller; The packaging box is used to accommodate the plastic mold after protection coating, and the environmental recording module is arranged inside. The environment recording module corresponds to the digital identification of the mold one by one, and is used for collecting and storing environmental data such as temperature, relative humidity, vibration acceleration and its duration during mold transportation and storage. The cleaning unit is used for performing spray cleaning on the mold arriving at the cleaning end. The cleaning verification unit is used for detecting the cleaning degree of the key surface of the mold after cleaning is completed. The controller is electrically connected with the environment recording module, the cleaning unit and the cleaning verification unit, and is configured to perform the following control process: S1, after the mold completes the protective coating, the mold identification and the protective agent type are obtained, the mold identification is written into the digital identification carrier, and the environment recording module is arranged in the packaging box and bound to the mold identification, so that the environment recording module continuously records the environmental data in the subsequent transportation and storage process; S2, when the mold arrives at the cleaning end, the environmental data corresponding to the mold identification is read, and the process reference parameters such as mold structure and cavity surface roughness level are combined to form a basic data set of the mold; S3, the environmental exposure risk index representing the corrosion, rust and pollution risk of the mold in the transportation and storage stage is calculated according to the basic data set; S4, based on the environmental exposure risk index and the preset cleaning medium type range, the cleaning program template is determined, and the cleaning load index representing the flushing amount and decontamination capacity of the cleaning process to the unit area of the mold surface is generated, and the target interval of the spray pressure, spray flow, cleaning temperature and cleaning time of the cleaning unit is determined; S5, after the cleaning program is executed, the residual oil area ratio, surface gloss deviation and contact angle of the key surface of the mold are detected by the cleaning verification unit, and the actual cleaning level is obtained; S6, the actual cleaning level is compared with the target cleaning level required by the corresponding process, the cleaning deviation is obtained, the set values of the spray pressure, spray flow, cleaning temperature and cleaning time are adaptively adjusted on the basis of the environmental exposure risk index and the cleaning load index, and the environmental data, cleaning parameters and cleaning results are written into the mold surface protection and cleaning file for subsequent batch strategy optimization.

[0009] By configuring the environment recording module in the packaging box and binding it one by one with the digital identification of each mold, the environmental information such as temperature, humidity and vibration of the mold from the protective coating to the cleaning station can be completely recorded, and the subsequent cleaning parameters and cleaning detection results are stored in the file, so that the traceable management of the mold surface state in the whole process of protection, transportation and cleaning is realized. The environmental record, cleaning control and cleaning verification are connected into a closed loop process, which no longer relies on the experience of workers to estimate whether to strengthen cleaning, but the system adjusts the cleaning intensity according to the actual exposure and detection results, which is beneficial to improve the cleaning consistency and reproducibility, reduce surface damage caused by insufficient or excessive cleaning, and provide data basis for subsequent optimization of protective agent selection and transportation scheme.

[0010] Preferably, the S4 further comprises, when calculating the environmental exposure risk index: Integrating the relative humidity time curve collected by the environmental record module during mold transportation and storage to obtain the equivalent humidity; Obtaining the storage time according to the duration from completing the protective coating to entering the cleaning unit; Calculating the equivalent vibration energy index according to the vibration acceleration and its action time; And combining the equivalent humidity, storage time and equivalent vibration energy index based on the humidity amplification coefficient, time amplification coefficient and vibration amplification coefficient to represent the environmental exposure risk.

[0011] By integrating the humidity time curve during the entire transportation and storage process, the equivalent humidity is obtained; the storage time is obtained according to the duration from completing the protection to starting cleaning; and the intensity and duration of multiple vibration impacts are converted into an equivalent vibration energy index, and different amplification weights are assigned to the three quantities to form a comprehensive index, which can objectively reflect the comprehensive risk degree of the mold in the entire turnover cycle under the combined action of humidity, long-term storage and vibration impact; This way can unify and quantify different exposure modes such as long-term moderate humidity, short-term high humidity, frequent small impact and occasional large impact, avoid underestimating the risk of hidden corrosion or overreacting to slight exposure, and thus provide more accurate risk classification basis for subsequent cleaning strategy matching.

[0012] Preferably, the environmental exposure risk index is calculated according to the following equation: ; Wherein, H ref is the relative humidity reference value, t ref is the storage time reference value, E ref is the vibration energy reference value, H eq is the equivalent humidity, t s is the storage time, E v is the equivalent vibration energy index, a is the humidity amplification coefficient, b is the time amplification coefficient, c is the vibration amplification coefficient, and X is closer to 1, indicating a higher environmental exposure risk.

[0013] The equivalent humidity, parking time and equivalent vibration energy are compressed mapped by using an increasing exponential function to weight combination, so that when the three are in the safe interval, the risk index is close to zero; once any of them significantly exceeds the benchmark, the comprehensive risk will rise rapidly and nonlinearly, highlighting the sensitivity to extreme conditions such as high humidity, long parking time and long-term high vibration; This nonlinear mapping method avoids the problem of misjudgment of high humidity but short time and low humidity but super-long parking as moderate risk in linear weighting, making the environmental exposure risk index closer to the physical mechanism of actual corrosion and rust occurrence, and facilitating significant increase in attention and automatic attenuation of neglect in cleaning strategy selection.

[0014] Preferably, the controller, when generating the cleaning load index, further comprises: Selecting a matching cleaning program template in the cleaning program library based on the environmental exposure risk index, limiting the value range of spray pressure, spray flow, cleaning temperature and cleaning time; Combined with the spray pressure, spray flow, cleaning time and key surface area of the mold, the unit area scouring amount is estimated to represent the average action strength of the liquid jet on the mold surface during cleaning; Combined with the deviation of the cleaning temperature relative to the temperature benchmark value, and the same equivalent vibration energy index as in the environmental exposure risk index, humidity amplification coefficient, time amplification coefficient and cleaning reinforcement coefficient are introduced to nonlinearly combine the above quantities to obtain the cleaning load index representing the matching degree of cleaning intensity and environmental exposure.

[0015] When generating the cleaning load index, it is not simply executed according to the established program, but first uses the environmental exposure risk index to screen the appropriate cleaning template in the program library, then estimates the unit area scouring amount based on the relationship between the spray pressure, flow, time and key surface area of the mold, and considers the deviation of the cleaning temperature relative to the benchmark temperature and the influence of the aforementioned vibration exposure degree in the cleaning stage, and quantifies the cleaning intensity required by the mold into an index that can be directly compared by giving different amplification weights and cleaning reinforcement factors; High-risk molds will be automatically matched to cleaning programs with high scouring amount, higher temperature and longer time, while low-risk molds can use milder, energy-saving and less damaging programs, achieving on-demand cleaning. Compared with traditional uniform programs or manual experience-based judgment, it can significantly reduce residual film and rust caused by insufficient cleaning, and avoid surface polishing layer loss and time waste caused by repeated and excessive cleaning of low-risk molds.

[0016] Preferably, the cleaning load index is calculated according to the following equation: ; Wherein, p sQ is the spray pressure s t is the spray flow rate c A is the cleaning time s T is the mold critical surface area c T is the cleaning temperature ref E is the cleaning temperature reference value v E is the equivalent vibration energy index ref a is the humidity amplification coefficient, b is the time amplification coefficient, d is the cleaning enhancement coefficient related to the nozzle structure and cleaning medium, and Y is closer to 1, indicating a higher cleaning load.

[0017] By combining the spray pressure, spray flow rate, cleaning time, and mold surface area into a unit area flushing intensity, while considering the degree of deviation of the cleaning temperature from the reference value as a thermodynamic factor affecting the oil stain dissolution speed and the softening degree of the protective film, and superimposing the energy index from the same source as the environmental vibration exposure, an incremental exponential function is used to combine the three parts into a cleaning load index, which can comprehensively reflect the mechanical flushing ability of the cleaning fluid, the promotion of temperature to decontamination, and the additional compensation of cleaning intensity under historical abnormal working conditions on a dimensionless value.

[0018] This structure makes the humidity and time weight representing environmental risk inherited and reused in the cleaning load index, on the one hand, ensuring that high-risk molds obtain sufficient cleaning load, and on the other hand, introducing device characteristics such as nozzle structure and spraying mode into the model through a special cleaning enhancement factor, realizing the coupling representation of risk dimension and equipment dimension, which is helpful to form a transferable cleaning strategy among different devices and different molds.

[0019] Preferably, the controller further comprises, when adaptively adjusting the cleaning parameters: obtaining the detection results of residual oil stain area ratio, surface gloss deviation, and / or contact angle of the critical surface of the mold from the cleaning verification unit, and normalizing them into actual cleaning grades; setting a target cleaning grade according to the process requirements of the corresponding mold and molded product, and taking the difference between the target cleaning grade and the actual cleaning grade as a cleaning deviation; inputting the environmental exposure risk index, the cleaning load index, and the cleaning deviation into an optimization model, searching and correcting the spray pressure, the spray flow rate, the cleaning temperature, and the cleaning time, and updating the surface protection and cleaning profile of the humidity amplification coefficient, the time amplification coefficient, the vibration amplification coefficient, and the cleaning enhancement coefficient related to the nozzle structure and the cleaning medium while obtaining updated parameters.

[0020] The residual oil stain area ratio, surface gloss deviation, contact angle, etc. are detected by the cleaning verification unit, and these detection quantities are normalized to the actual cleaning grade, and then compared with the target cleaning grade set for different molds and products to obtain the cleaning deviation, so that the cleaning effect is no longer based on the experience of looking at the approximate difference with the naked eye, but is evaluated by quantitative indicators to determine whether it meets the standard and how much deviation there is.

[0021] On this basis, the environmental exposure risk index, cleaning load index and cleaning deviation are input into the optimization model, the parameters such as spray pressure, flow rate, temperature and time are iteratively corrected, and the corresponding weight factors and archive records are updated synchronously, which can form a self-adaptive control similar to self-learning: when the system finds that the current cleaning program is too weak or too strong under a certain environmental exposure mode for many times, it will automatically tighten or loosen the corresponding parameter interval, so that subsequent molds of the same type can be closer to the expected state during the initial cleaning, reducing the number of re-cleaning and further stabilizing the surface quality.

[0022] Preferably, the target value Z of the joint optimization objective function is defined as: ; Wherein, X is the environmental exposure risk index, Y is the cleaning load index, ΔC(p s ,Q s ,T c ,t c )=C req -C meas (p s ,Q s ,T c ,t c ), C req is the target cleaning grade, C meas (p s ,Q s ,T c ,t c ) is the actual cleaning grade measured by the cleaning verification unit under the corresponding spray pressure, spray flow rate, cleaning temperature and cleaning time, and α, β, γ, η are non-negative weight coefficients. The controller adjusts the spray pressure p s , spray flow rate Q s , cleaning temperature T c and cleaning time t c so that the objective function F(p s ,Q s ,T c ,t c ) reaches a minimum value, and p s , Q s , T c , t cThe cleaning parameters of the final optimization are written into the mold surface protection and cleaning file for the subsequent cleaning strategy recommendation of the same mold.

[0023] By constructing a target function with environmental risk, cleaning load and cleaning deviation as core components, the punishment when the environmental exposure risk is increased, the punishment when the cleaning load is insufficient, the superimposed punishment when the risk and load are not matched, and the deviation punishment when the cleaning is not up to standard are mapped to a numerical value, and the spray pressure, flow, temperature and time are explicitly used as the optimized independent variables, and when the target function reaches the minimum value, a set of optimal cleaning parameters is determined, which can achieve the multi-objective balance of higher risk, lower load, higher load and lower cleaning deviation on the mathematical level.

[0024] Compared with simple rules or experience tables, this optimization method based on the target function can naturally reflect the three types of relationships in the algorithm: When the environmental risk is high but the cleaning load is low, the system will strongly tend to increase the cleaning parameters; When the environmental risk is low and the cleaning load is too high, the system will tend to reduce the cleaning intensity to protect the mold surface and save resources; When the cleaning deviation is large for a long time, the system will gradually strengthen the constraint force of the corresponding component through weight adjustment; Finally, the molds of different sources and different transportation conditions can automatically converge to a set of parameter combinations that take into account safety, cleanliness and surface life after entering the cleaning line, providing a surface protection and cleaning control strategy that can be implemented and optimized for long-term use for the cross-factory turnover of plastic molds.

[0025] The technical solution of the application can include the following beneficial effects: The application integrates the environment recording module, the cleaning unit, the cleaning verification unit and the controller into one, realizes the closed-loop management of the surface state information of the plastic mold from the protection coating, packaging and transportation to the whole process of washing and production, and binds the temperature, humidity, vibration during transportation and storage of each mold, subsequent cleaning parameters and cleaning detection results to the digital identifier and forms a file, changes the situation that the protection and cleaning links are managed separately in the prior art, and lacks data transmission and traceability, so that the mold surface protection strategy is no longer a one-time on-site experience decision, but a whole cycle management scheme that can be continuously evaluated and optimized based on historical data, which is beneficial to improve the quality consistency and traceability in the cross-factory and cross-regional turnover process; By introducing the environmental exposure risk index and the cleaning load index, the environmental factors such as moisture exposure, parking time, vibration impact of the mold during transportation and storage are quantitatively corresponding to the process parameters such as spray pressure, flow, temperature, time and the like in the cleaning stage, realizing the self-adaptive control of "matching the cleaning strength according to the risk". For the mold with high humidity and long storage time or poor vibration working condition, the system can automatically match higher flushing amount and intensive program to reduce the risk of rust and residual film; for the low-risk mold, the mild and efficient cleaning parameters are selected to avoid excessive cleaning, which can cause damage to the polishing layer of the mold cavity and unnecessary energy consumption and chemical consumption. Compared with the traditional method which depends on the subjective judgment of the operator, the present application can balance the cleaning strength and the service life of the mold surface under the premise of ensuring the cleanliness, and significantly improve the reliability and economy of the cleaning link; By introducing the cleaning verification station based on machine vision and / or surface energy test after cleaning, the residual oil stain, surface gloss deviation, contact angle and the like are quantified as cleaning grades, and compared with the preset target grade. The cleaning deviation, environmental risk and cleaning load are used as optimization targets for parameter correction and archive update, forming an optimization mechanism with self-learning ability. With the accumulation of batch data, the system can automatically identify the advantages and disadvantages of the combination of certain protective agent, certain transportation working condition and certain cleaning parameter group, and gradually solidify it into a recommended strategy and issue a warning for abnormal combination, thereby reducing re-cleaning and rework, improving mold turnover efficiency, reducing dependence on personal experience, and providing an engineeringable technical path for enterprises to establish a standardized, data-driven mold surface protection and cleaning control system in multiple factory, multiple customer and multiple mold type scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0026] Figure 1 A flowchart of a surface protection and cleaning device for plastic mold transportation according to the present application. DETAILED DESCRIPTION

[0027] Example 1 As Figure 1 , A surface protection and cleaning device for plastic mold transportation, comprising: a packaging box, an environmental recording module, a cleaning unit, a cleaning verification unit and a controller; The packaging box is used to accommodate the plastic mold after protective coating, and the environmental recording module is arranged inside the packaging box; The environmental recording module corresponds to the digital identification of the mold one by one, and is used to collect and store environmental data such as temperature, relative humidity, vibration acceleration and its duration during mold transportation and storage; The cleaning unit is used to perform spray cleaning on the mold arriving at the cleaning end; The cleaning verification unit is used for detecting the cleaning degree of the key surface of the mold after cleaning is completed. The controller is electrically connected with the environment recording module, the cleaning unit and the cleaning verification unit, and is configured to perform the following control process: S1, after the mold is completed with protective coating, the mold identification and the type of protective agent are obtained, the mold identification is written into the digital identification carrier, and the environment recording module is arranged inside the packaging box and bound with the mold identification, so that the environment recording module continuously records environment data in the subsequent transportation and storage process; A special packaging station is arranged at the mold delivery end, a spray gun for spraying protective agent, a mold turntable and a digital identification printing / writing device are arranged; after the mold is completed with protective coating, the mold number is read by a code scanning gun, a corresponding two-dimensional code label is generated by an industrial tablet computer or an RFID electronic tag is written, and is pasted or fixed on a non-key position of the mold frame; an environment recording module installation slot is reserved in the packaging box, and the recording module with temperature, humidity and three-axis acceleration sensors is placed in the slot by an operator, and is bound with the corresponding mold identification through near field communication (such as NFC) or Bluetooth; the binding information is written into the internal storage of the module and the database of the upper computer; the packaging box adopts a wooden box or a metal frame plus a lining structure, and the position of the environment recording module is marked on the lining to ensure that it does not move violently during transportation.

[0028] S2, when the mold reaches the cleaning end, the environment data corresponding to the mold identification is read, and the process reference parameters such as the mold structure and the cavity surface roughness level are combined to form a basic data set of the mold; A low-power microcontroller is arranged inside the environment recording module, and is connected with a temperature sensor (such as PT1000 or a digital temperature chip), a capacitive humidity sensor and a three-axis MEMS accelerometer. The sampling period can be set to 1-5 minutes, the microcontroller collects the current temperature, relative humidity and three-axis acceleration at fixed time intervals, records the data with a time stamp in a ring buffer, and fills the storage space until it is full. For vibration data, a threshold can be set, and only when the acceleration exceeds the preset threshold, the data is recorded at a higher frequency, so as to calculate the equivalent energy of vibration impact in the subsequent calculation. The module is powered by a lithium battery, has a low power alarm function, and the power state can be uploaded together with the binding information.

[0029] S3, according to the basic data set, the environmental exposure risk index representing the corrosion, rust and pollution risk of the mold in the transportation and storage stage is calculated; When the mold reaches the entrance of the cleaning line, a code scanner or RFID reader is arranged at the entrance station to read the mold identification and associate it with the order information in the host computer. The operator confirms the mold type, cavity surface roughness, mold cavity material, and other process reference parameters on the HMI, which can also automatically retrieve typical values from the existing database. The environmental recording module is removed and placed on the data reading seat, and the stored temperature, humidity, acceleration, and time stamp records are exported through wired or wireless methods. The host computer automatically matches the corresponding mold number based on the exported time series. The host computer generates humidity time curves, temperature time curves, and acceleration time curves based on the exported time series, and combines them with the mold's geometric characteristics, sensitive surface area, and other factors to form a basic data set, which provides input for subsequent calculations of environmental exposure risk index and cleaning load.

[0030] S4, based on the environmental exposure risk index and the preset cleaning medium type range, determine the cleaning program template, and generate a cleaning load index representing the amount of flushing and decontamination capacity applied to the unit area of the mold surface during the cleaning process, and determine the target range of spray pressure, spray flow, cleaning temperature, and cleaning time of the cleaning unit; S5, after executing the cleaning program, the residual oil area ratio, surface gloss deviation, and contact angle of the key surface of the mold are detected by the cleaning verification unit to obtain the actual cleaning level; S6, compare the actual cleaning level with the target cleaning level required by the corresponding process to obtain the cleaning deviation, and based on the environmental exposure risk index and the cleaning load index, adaptively adjust the set values of spray pressure, spray flow, cleaning temperature, and cleaning time, and write the environmental data, cleaning parameters, and cleaning results into the mold surface protection and cleaning file for subsequent batch strategy optimization.

[0031] A cleaning verification station is set up at the exit of the cleaning line, equipped with an industrial camera, a multi-angle high-color-rendering-index light source, and a micro-droplet assembly for contact angle measurement. The mold automatically stops at the verification position after leaving the cleaning line. The visual system takes pictures of the mold cavity, parting surface, and other areas, extracts the brightness and area distribution of residual oil light through software, calculates the residual pollution area ratio and surface gloss deviation, and drops standard droplets at typical positions to calculate the static contact angle through image processing.

[0032] By configuring an environmental recording module in the packaging box and binding it one-to-one with the digital identification of each mold, the temperature, humidity, vibration, and other environmental information of the mold during the protection coating and entering the cleaning station can be recorded completely, and the subsequent cleaning parameters and cleaning detection results are stored in the file, realizing traceable management of the mold surface state during the protection, transportation, and cleaning processes; The environmental record, cleaning control and cleaning verification are connected in series into a closed loop process, which no longer relies on the experience of workers to estimate whether to strengthen cleaning, but the system adjusts the cleaning intensity according to the actual exposure and detection results, which is beneficial to improve the cleaning consistency and reproducibility, reduce the surface damage caused by insufficient or excessive cleaning, and provide data basis for subsequent optimization of protective agent selection and transportation scheme.

[0033] Specifically, the S4 further comprises the following when calculating the environmental exposure risk index: Integrating the relative humidity time curve collected by the environmental record module during mold transportation and storage to obtain the equivalent humidity; According to the duration from completing the protective coating to entering the cleaning unit to obtain the storage time; According to the vibration acceleration and its action time, the equivalent vibration energy index is calculated; And based on the humidity amplification coefficient, the time amplification coefficient and the vibration amplification coefficient, the equivalent humidity, the storage time and the equivalent vibration energy index are combined to represent the environmental exposure risk.

[0034] The storage time is obtained by subtracting the time stamp of the cleaning entry time from the time stamp of the completion of the environmental protection, and the time stamp can be provided by the MES or a simplified mold management software. In order to prevent the packaging station and the cleaning station from being in the same system, the time can be written into the environmental record module when packaging, and then read by the reading seat at the cleaning end, and then compared with the current time. The vibration acceleration signal uses a threshold event recording method, and when the absolute value of any axis acceleration exceeds the preset threshold, the acceleration waveform of this period of time is recorded. For each event, the product of the acceleration square and the duration is calculated, and the sum of all events is equivalent to using "acceleration mean square value x time" to estimate the vibration energy, which reflects the potential risk of cracking and detachment of the wax film or protective film during transportation; the humidity weight reflects the dominant role of high humidity environment in the corrosion process, and usually takes a larger value when the protective agent is sensitive to moisture; the time weight reflects the influence of exposure time on rust accumulation, and can be appropriately amplified when long-term storage is more prone to problems; the vibration weight is used to consider the influence of frequent impact on the integrity of the film layer, which is particularly important for long-distance transportation with multiple drops and poor road conditions.

[0035] In actual implementation, enterprises can compare the actual rust conditions of multiple batches of molds, use logistic regression or simple fitting method to empirically calibrate a, b and c, so that the risk index X calculated has good correlation with the actual defect occurrence probability. The equivalent humidity is obtained by integrating the humidity-time curve during the whole transportation and storage process, the parking time is obtained by integrating the duration from the completion of protection to the beginning of cleaning, and the strength and duration of multiple vibration impacts are converted into an equivalent vibration energy index, and then the three quantities are given different amplification weights to form a comprehensive index, which can objectively reflect the comprehensive risk degree of the mold in the whole turnover cycle under the conditions of humidity, long parking time and vibration impact; This method can unify different exposure modes such as long-term moderate humidity, short-term high humidity, frequent small impact and occasional large impact, avoid underestimating the risk of hidden corrosion or overreacting to slight exposure, and thus provide more accurate risk classification basis for subsequent cleaning strategy matching.

[0036] Specifically, the environmental exposure risk index is calculated according to the following equation: ; Wherein, H ref is the relative humidity reference value, t ref is the parking time reference value, E ref is the vibration energy reference value, H eq is the equivalent humidity, t s is the parking time, E v is the equivalent vibration energy index, a is the humidity amplification coefficient, b is the time amplification coefficient, c is the vibration amplification coefficient, and X is closer to 1, indicating that the environmental exposure risk is higher.

[0037] The bracket part in the index is the weighted sum of the equivalent humidity, parking time and vibration energy, representing the total stress; when the total stress is much lower than the reference, the value in the bracket tends to 0, the value of the exponential function is close to 1, and finally X≈0, indicating that the risk is very small; when the total stress is significantly higher than the reference, the value in the bracket becomes larger, the exponential function rapidly decays to close to 0, and at this time X is close to 1, indicating that the risk is close to the highest level.

[0038] This non-linear characteristic of low flatness in low area and high steepness in high area is consistent with the actual law of corrosion and rust in material science, that is, almost no corrosion occurs below a certain threshold, and rapid deterioration occurs when the exposure condition is aggravated after exceeding the threshold; the humidity reference value H ref The upper limit humidity recommended in the protective agent specification can be selected, for example, 60% or 65%; the time reference value t ref The standard turnover time that the enterprise wants to ensure can be selected, such as 7 days or 14 days; the vibration energy reference value E ref The vibration energy reference value E vAs a reference unit; the humidity coefficient a is generally adjusted between 0.5-2, which can be increased to 3-4 when high humidity is very sensitive to some fine polishing molds; the time coefficient b is usually between 0.3-1, which can also be appropriately increased when long-term storage is more deadly than high humidity; the vibration coefficient c is set according to the packaging method and route characteristics, and a relatively large value can be taken for wooden boxes, sea transportation, and multiple handling scenes. Through parameter adjustment, the sensitivity of X to different risk sources can be matched with actual experience.

[0039] By using an incremental exponential function to compress the weighted combination of equivalent humidity, storage time and equivalent vibration energy, when the three are in the safe interval, the risk index is close to zero; once any of them is significantly beyond the benchmark, the comprehensive risk will rise rapidly and nonlinearly, highlighting the sensitivity to extreme conditions such as high humidity, long-term storage, and long-term high vibration; This nonlinear mapping method avoids the problem of misjudgment of high humidity but short time and low humidity but super-long storage as medium risk in linear weighting, making the environmental exposure risk index closer to the physical mechanism of actual corrosion and rust occurrence, and facilitating the significant increase of attention and automatic attenuation of neglect in cleaning strategy selection.

[0040] Specifically, the controller, when generating the cleaning load index, further comprises: Selecting a matching cleaning program template in the cleaning program library based on the environmental exposure risk index, limiting the value range of spray pressure, spray flow, cleaning temperature and cleaning time; Combining the spray pressure, spray flow, cleaning time and key surface area of the mold to estimate the unit area flushing volume, which is used to represent the average action strength of the liquid jet on the mold surface in the cleaning process; Combining the deviation of the cleaning temperature from the temperature benchmark value, and the same equivalent vibration energy index as in the environmental exposure risk index, introducing humidity amplification coefficient, time amplification coefficient and cleaning strengthening coefficient, nonlinearly combining the above quantities to obtain the cleaning load index for representing the matching degree of cleaning strength and environmental exposure.

[0041] For a certain cleaning section, the pump outlet pressure corresponds to the spray pressure p s , the flow Q s , the cleaning time t c , and the key surface area A s of the mold that the section acts on, the flushing strength is proportional to the flow and pressure acting on unit area per unit time, which is simplified as p s Q s t c / A s .

[0042] This quantity can be physically understood as the total liquid momentum flux per unit area, indirectly reflecting the shear stress and the solvent's ability to remove oil stains; cleaning temperature T c Above the reference temperature T ref At this time, the viscosity of oil-based and wax-based protective agents will decrease and the dissolution rate will increase, thus promoting cleaning. However, excessively high temperatures may adversely affect certain surface treatment layers or inserts of the mold, therefore... The square form of the equation controls the contribution of temperature deviation to the cleaning load index within an adjustable range, and its weight is limited by the coefficient b. The equivalent vibrational energy E is the same as that during the environmental exposure phase. v / Eref The introduction of a cleaning load index reflects the potential risks of localized cracking of the protective film and rust formation if transportation vibration is severe. In such cases, it is necessary to appropriately increase the cleaning intensity. Even if the environmental risk index has already indicated the risk, the cleaning load is given an additional weight amplification. The cleaning enhancement coefficient d can be adjusted according to the degree of difficulty in cleaning batches with severe vibrations found in actual tests; the above three components are combined in an exponential form to obtain Y; During the cleaning program selection phase, the system can perform verification based on the relative magnitudes of X and Y: If X is high and Y is low, it means that the current cleaning intensity is insufficient, and the spray pressure, time or temperature needs to be increased. If X is low and Y is too high, the cleaning intensity can be appropriately reduced to decrease surface wear and save energy.

[0043] When generating the cleaning load index, it is not simply executed according to the established procedure. Instead, the environmental exposure risk index is first used to select a suitable cleaning template from the program library. Then, the scouring amount per unit area is estimated by combining the relationship between spray pressure, flow rate, time and the key surface area of ​​the mold. At the same time, the deviation of the cleaning temperature from the reference temperature and the influence of the aforementioned vibration exposure degree in the cleaning stage are considered. By assigning different amplification weights and cleaning enhancement factors, the required cleaning intensity of the mold is quantified into an index that can be directly compared. High-risk molds are automatically assigned to cleaning programs with high flushing volume, high temperature, and long duration, while low-risk molds can be cleaned using gentler, more energy-efficient programs that cause less damage to the cavity, achieving on-demand cleaning. Compared to traditional uniform programs or manual judgment based on experience, this significantly reduces the risk of residual film and rust spots caused by insufficient cleaning, and also avoids the loss of surface polishing layer and wasted time caused by repeated or excessive cleaning of low-risk molds.

[0044] Specifically, the cleaning load index is calculated according to the following equation: ; wherein, p s is the spray pressure, Q s is the spray flow rate, t c is the cleaning time, A s is the critical surface area of the mold, T c is the cleaning temperature, T ref is the cleaning temperature reference value, E v is the equivalent vibration energy index, E ref is the vibration energy reference value, a is a humidity amplification coefficient, b is a time amplification coefficient, d is a cleaning intensification coefficient related to the nozzle structure and cleaning medium, and Y is closer to 1, indicating a higher cleaning load.

[0045] A typical mold was selected and cleaned under different combinations of spray pressure (e.g., 0.5, 1.0, 1.5 MPa), flow rate, time, and temperature. The cleaning level C meas was measured using a cleaning verification station. By comparing the results with manual strict inspection, it was determined which combinations belonged to sufficient cleaning, barely sufficient cleaning, and insufficient cleaning.

[0046] The unit area flushing volume, temperature deviation term, and vibration energy term (which can be represented by a typical E v ) were calculated for each combination. These independent variables were fitted with samples of sufficient cleaning, so that Y was roughly concentrated in the interval of 0.7-0.9 when cleaning was sufficient, and less than 0.5 when cleaning was insufficient, thereby determining the value range of a, b, and d.

[0047] For a mold with high environmental risk, it was calculated that X was close to 0.8. The upper computer selected a relatively high intensity template, and the initial parameters were set as a spray pressure of 1.2 MPa, a flow rate of 80 L / min, a time of 600 s, a critical surface area of 2 m², and a cleaning temperature that was 10°C higher than the reference temperature.

[0048] By substituting the numerical values into the formula, the cleaning load index Y ≈ 0.85 was obtained. If actual cleaning verification still found local oil stains, the system would slightly increase the pressure or extend the time according to the deviation ΔC, so that the next Y would be increased to approximately 0.9. For molds with low environmental risk, the initial parameters given by the template may be 0.6 MPa, 50 L / min, 300 s, and the same temperature as the reference. Calculated Y ≈ 0.5-0.6, which meets the normal demand and does not cause excessive flushing of the mold.

[0049] By combining the spray pressure, spray flow rate, cleaning time and mold surface area into a unit area flushing intensity, while considering the degree of deviation of the cleaning temperature from the reference value as a thermodynamic factor affecting the oil stain dissolution speed and the protective film softening degree, and superimposing the energy index of the same source as the environmental vibration exposure, the three parts are synthesized into a cleaning load index using an increasing exponential function, which can comprehensively reflect the mechanical flushing ability of the cleaning fluid and the promotion of temperature to decontamination, and the additional compensation of cleaning intensity under historical abnormal working conditions on a dimensionless value.

[0050] This structure makes the humidity and time weight of environmental risk characterization inherited and reused in the cleaning load index, on the one hand to ensure that high-risk molds obtain sufficient cleaning load, and on the other hand to introduce device characteristics such as nozzle structure and spray mode into the model through a special cleaning reinforcement factor, realizing the coupling representation of risk dimension and equipment dimension, which helps to form a transferable cleaning strategy among different devices and different molds.

[0051] Specifically, the controller further comprises, when adaptively adjusting the cleaning parameters: Obtain the detection results of residual oil stain area ratio, surface gloss deviation and / or contact angle of the key surface of the mold from the cleaning verification unit, and normalize them to the actual cleaning level; Set a target cleaning level according to the process requirements of the corresponding mold and molded product, and take the difference between the target cleaning level and the actual cleaning level as the cleaning deviation; Input the environmental exposure risk index, the cleaning load index and the cleaning deviation into the optimization model, search and correct the spray pressure, the spray flow rate, the cleaning temperature and the cleaning time, and update the surface protection and cleaning file of the humidity amplification coefficient, the time amplification coefficient, the vibration amplification coefficient and the cleaning reinforcement coefficient related to the nozzle structure and the cleaning medium while obtaining the updated parameters.

[0052] The visual system maps the residual oil stain area ratio to a value between 0 and 1 (0 means no residual stain, and 1 means severe residual stain), and the surface gloss deviation and the contact angle deviation from the standard value are also normalized to 0-1; By pre-set weights, the above three quantities are linearly or nonlinearly combined into a cleaning level index; For molds used for high-gloss appearance parts, set C req to 0.9 or higher; For molds with slightly lower surface finish requirements, it can be set to about 0.8; When ΔC=C req -C measWhen positive and large (e.g. more than 0.1), it indicates that the cleaning intensity is insufficient, and the controller increases the flushing volume per unit area or the temperature appropriately while keeping the risk index X and the cleaning load index Y unchanged until ΔC is reduced to a certain allowable range.

[0053] When ΔC has approached 0, the system records the current parameter combination as the "empirical optimal value"; If ΔC is always positive or negative for a certain type of environmental exposure mode in multiple batches, the system adjusts the coefficients a, b, c, d in the risk index X or the cleaning load index Y simultaneously to make the model gradually fit the actual situation.

[0054] As the cleaning record increases, for the same type of protective agent, similar environmental exposure mode and mold type combination, the system can directly recommend the parameters that have performed stably in history, reducing the debugging time; At the same time, combinations with large cleaning deviations are prompted to suggest that the process engineer change the protective agent or the transportation method.

[0055] The cleaning verification unit detects the residual oil area ratio, surface gloss deviation, contact angle, etc., normalizes these detection quantities to the actual cleaning level, and compares them with the target cleaning level set for different molds and products to obtain the cleaning deviation. The cleaning effect is no longer based on the experience of looking at the approximate difference with the naked eye, but on the quantitative index to evaluate whether it meets the standard and how much the deviation is.

[0056] On this basis, the environmental exposure risk index, the cleaning load index and the cleaning deviation are input into the optimization model to iteratively correct the parameters such as spray pressure, flow, temperature and time, and update the corresponding weight factors and archive records simultaneously, which can form a self-adaptive control similar to self-learning: when the system finds that the current cleaning program is too weak or too strong for a certain type of environmental exposure mode multiple times, it will automatically tighten or loosen the corresponding parameter interval, so that subsequent molds of the same type can be closer to the expected state during the initial cleaning, reducing the number of re-cleaning and further stabilizing the surface quality.

[0057] Specifically, the target value Z of the joint optimization objective function is defined as: ; Where X is the environmental exposure risk index, Y is the cleaning load index, ΔC(p s ,Q s ,T c ,t c )=C req -C meas (p s ,Q s ,T c ,t c ),Creq Target cleaning level, C meas (p s , Q s , T c , t c ) are actual cleaning levels measured by the cleaning verification unit under corresponding spray pressure, spray flow, cleaning temperature and cleaning time, and α, β, γ, η are non-negative weight coefficients; The controller adjusts the spray pressure p s , spray flow Q s , cleaning temperature T c and cleaning time t c so that the target function F(p s , Q s , T c , t c ) reaches a minimum value, and the p s , Q s , T c , t c at this time are written as the final optimized cleaning parameters in the mold surface protection and cleaning file for subsequent cleaning strategy recommendation for similar molds.

[0058] The first component coefficient is multiplied by the environmental risk index, which reflects that the higher the environmental risk, the less tolerance for the constraint of low cleaning load; The second component 1 - cleaning load index represents the gap between the current set cleaning intensity and high load, and when the cleaning load is insufficient, this item is larger, which promotes the system to improve the cleaning intensity; The third component is the product of the environmental risk and the cleaning load gap, which highlights the particularly dangerous combination of high risk and low load; The fourth component is the square of the cleaning deviation, which ensures that the cleanliness of the final result is as close to the target level as possible.

[0059] The controller can use a hierarchical search method: first, take the current template parameters as the center, and perform incremental / decremental trials within the allowed interval for spray pressure, time and temperature with limited steps, update the cleaning load index and the predicted cleaning level after each trial, and calculate the target function value.

[0060] Compare the target function values of several groups of candidate parameters, and select the parameter combination corresponding to the minimum value as the recommended parameters this time. For high-risk molds, the amplitude of reducing the cleaning intensity can be limited to ensure the safety boundary.

[0061] Under the condition of ensuring safety, energy consumption and chemical consumption can also be indirectly reflected in the target function by adjusting the weight, so that the optimization result not only meets the cleaning requirement, but also takes into account the economy.

[0062] When a certain type of mold is repeatedly cleaned under a specific environmental exposure mode, and the objective function converges to a similar parameter combination, the host computer can solidify this combination as a standard cleaning scheme; When a new mold enters the cleaning line under similar conditions, the system can directly retrieve the scheme as the initial setting, significantly shortening the debugging period.

[0063] If subsequent observations show changes in product appearance defects or mold corrosion, process engineers can adjust the weight coefficients in the objective function to moderately change the balance between risk priority and economic priority.

[0064] By constructing an objective function with environmental risk, cleaning load, and cleaning deviation as core components, the penalties for increasing environmental exposure risk, insufficient cleaning load, and the superimposed penalties for risk and load mismatch, as well as the deviation penalties for cleaning failure are unified into a numerical value. The spray pressure, flow, temperature, and time are explicitly optimized as independent variables. When the objective function reaches a minimum value, a set of optimal cleaning parameters is determined, which can achieve a multi-objective balance of higher risk, lower load, and lower cleaning deviation on a mathematical level.

[0065] Compared with simple rules or experience tables, this optimization method based on the objective function can naturally reflect the three types of relationships in the algorithm: When the environmental risk is high but the cleaning load is low, the system will strongly prefer to increase the cleaning parameters; When the environmental risk is low but the cleaning load is too high, the system will tend to reduce the cleaning intensity to protect the mold surface and save resources; When the cleaning deviation is large for a long time, the system will gradually strengthen the constraint force of the corresponding component through weight adjustment; Finally, molds of different sources and different transportation conditions can automatically converge to a parameter combination that considers safety, cleanliness, and surface life after entering the cleaning line, providing a surface protection and cleaning control strategy that can be engineered and optimized for long-term use for cross-factory turnover of plastic molds.

[0066] Through the above embodiments, those skilled in the art can correspond the parameters in the formula to specific sensors, actuators, and process conditions based on standard industrial hardware and software frameworks, thereby specifically implementing a surface protection and cleaning device for plastic mold transportation.

Claims

1. A surface protection cleaning device for plastic mold transportation, characterized by, The device comprises a packaging box, an environmental recording module, a cleaning unit, a cleaning verification unit, and a controller. The packaging box is used to accommodate the plastic mold after protective coating and is internally provided with the environmental recording module. The environmental recording module corresponds to the digital identification of the mold, and is used to collect and store environmental data such as temperature, relative humidity, vibration acceleration, and their duration during mold transportation and storage. The cleaning unit is used to perform spray cleaning on the mold arriving at the cleaning end. The cleaning verification unit is used to detect the cleaning degree of the key surface of the mold after cleaning. The controller is electrically connected with the environmental recording module, the cleaning unit, and the cleaning verification unit, and is configured to perform the following control process: S1, after the mold completes protective coating, the mold identification and the type of protective agent are obtained, the mold identification is written into the digital identification carrier, and the environmental recording module is arranged inside the packaging box and bound to the mold identification, so that the environmental recording module continuously records environmental data in the subsequent transportation and storage process; S2, when the mold arrives at the cleaning end, the environmental data corresponding to the mold identification is read, and the process reference parameters such as mold structure and cavity surface roughness level are combined to form a basic data set of the mold; S3, the environmental exposure risk index representing the corrosion, rust, and pollution risk of the mold in the transportation and storage stage is calculated according to the basic data set; S4, based on the environmental exposure risk index and the preset cleaning medium type range, a cleaning program template is determined, and a cleaning load index representing the flushing amount and decontamination capacity per unit area of the mold surface during the cleaning process is generated, and the target interval of the spray pressure, spray flow, cleaning temperature, and cleaning time of the cleaning unit is determined; S5, after the cleaning program is executed, the residual oil area ratio, surface gloss deviation, and contact angle of the key surface of the mold are detected by the cleaning verification unit, and the actual cleaning level is obtained; S6, the actual cleaning level is compared with the target cleaning level required by the corresponding process, the cleaning deviation is obtained, the set values of the spray pressure, spray flow, cleaning temperature, and cleaning time are adaptively adjusted based on the environmental exposure risk index and the cleaning load index, and the environmental data, cleaning parameters, and cleaning results are written into the mold surface protection and cleaning file for subsequent batch strategy optimization.

2. The surface protection and cleaning device for plastic mold transportation according to claim 1, wherein when calculating the environmental exposure risk index, the S4 further comprises: integrating the relative humidity time curve collected by the environmental recording module during mold transportation and storage to obtain equivalent humidity; obtaining the storage time according to the duration from the completion of protective coating of the mold to the entry into the cleaning unit; calculating the equivalent vibration energy index according to the vibration acceleration and its action time; and combining the equivalent humidity, the storage time, and the equivalent vibration energy index based on the humidity amplification coefficient, the time amplification coefficient, and the vibration amplification coefficient to represent the environmental exposure risk. The environmental exposure risk index is calculated according to the following equation: ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ 3. The surface protection and cleaning device for plastic mold transportation according to claim 2, wherein, ​ ； where H ref is the relative humidity reference value, t ref is the parking time reference value, E ref is the vibration energy reference value, H eq is the equivalent humidity, t s is the parking time, E v is the equivalent vibration energy index, a is the humidity amplification coefficient, b is the time amplification coefficient, c is the vibration amplification coefficient, and X is closer to 1, indicating a higher environmental exposure risk.

4. The surface protection and cleaning device for plastic mold transportation according to claim 3, wherein the controller, when generating the cleaning load index, further comprises: selecting a matching cleaning program template from a cleaning program library based on the environmental exposure risk index, and limiting the value range of the spray pressure, the spray flow, the cleaning temperature and the cleaning time; combining the spray pressure, the spray flow, the cleaning time and the key surface area of the mold to estimate the unit area flushing volume, which is used to represent the average action strength of the liquid jet on the mold surface during the cleaning process; combining the deviation of the cleaning temperature relative to the temperature reference value, and the same equivalent vibration energy index in the environmental exposure risk index, introducing the humidity amplification coefficient, the time amplification coefficient and the cleaning enhancement coefficient, and nonlinearly combining the above quantities to obtain the cleaning load index for representing the matching degree of the cleaning strength and the environmental exposure. The cleaning load index is calculated according to the following equation:

5. The surface protection and cleaning device for plastic mold transportation according to claim 4, wherein, 6. The surface protection and cleaning device for plastic mold transportation according to claim 5, wherein the controller, when performing adaptive adjustment on the cleaning parameters, further comprises: ； wherein p s is the spray pressure, Q s is the spray flow rate, t c is the cleaning time, A s is the area of the critical surface of the mold, T c is the cleaning temperature, T ref is the reference value of the cleaning temperature, E v is the equivalent vibration energy index, E ref is the reference value of the vibration energy, a is a humidity amplification coefficient, b is a time amplification coefficient, d is a cleaning intensification coefficient related to the nozzle structure and the cleaning medium, and the closer Y is to 1, the higher the cleaning load. obtaining the detection results of the residual oil area proportion, the surface gloss deviation and / or the contact angle of the key surface of the mold from the cleaning verification unit, and normalizing them into the actual cleaning level; setting the target cleaning level according to the process requirements of the corresponding mold and molded product, and taking the difference between the target cleaning level and the actual cleaning level as the cleaning deviation; inputting the environmental exposure risk index, the cleaning load index and the cleaning deviation into the optimization model to perform parameter search and correction on the spray pressure, the spray flow, the cleaning temperature and the cleaning time, and updating the surface protection and cleaning file related to the humidity amplification coefficient, the time amplification coefficient, the vibration amplification coefficient and the cleaning enhancement coefficient of the nozzle structure and the cleaning medium at the same time as obtaining the updated parameters.

7. The surface protection and cleaning device for plastic mold transportation according to claim 6, wherein the target value Z of the joint optimization objective function is defined as: ​ ​ ​ ； wherein X is the environmental exposure risk index, Y is the cleaning load index, ΔC(p s Q s T c t c ) = C req - C meas (p s , Q s , T c , t c ), C req is a target cleaning level, C meas (p s , Q s , T c , t c ) is an actual cleaning level measured by the cleaning verification unit under corresponding spray pressure, spray flow rate, cleaning temperature, and cleaning time, and α, β, γ, and η are non-negative weight coefficients. The controller adjusts the spray pressure p s , the spray flow rate Q s , the cleaning temperature T c , and the cleaning time t c , so that the target function F(p s , Q s , T c , t c ) reaches a minimum value, and the p s , Q s , T c , t c at this time are written as the final optimized cleaning parameters of the mold surface protection and cleaning file, for subsequent cleaning strategy recommendation for similar molds.

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