Automatic control method for water boiling, rinsing and dewatering of injection molded parts

Abstract

The application discloses the technical fields of injection molding part cleaning and relates to an automatic water boiling, rinsing and dehydration control method for injection molding parts, which comprises the following steps: being applied to an automatic processing system composed of a conveying line, a material bucket, a mechanical arm, a water boiling closed area, a water boiling pool, an ultrasonic wave rinsing pool, a dehydration machine, a blanking slide table turnover device and a blanking streamline; the material bucket passes through water boiling, rinsing and dehydration stations and is provided with a frame cover which can be covered; the method comprises the following steps: injection molding parts are transferred to the material bucket through the conveying line, the frame cover is covered after the material bucket is filled, and then the material bucket is moved to the water boiling closed area; and the material bucket is grabbed to the water boiling pool by the mechanical arm after the material bucket is connected and identified. According to the formula control of multi-parameter coupling, the water boiling parameters are self-adaptively adjusted according to the material quality and wall thickness, the transfer rhythm of the mechanical arm is dynamically sorted according to the congestion degree of the station, and the dehydration time is real-timely converged according to the water content, so that the stress elimination consistency and cleanliness are improved, the manual intervention is reduced, the energy consumption is reduced, and the operation safety is ensured.

Description

Technical Field

[0001] This invention relates to an automated method for controlling the boiling, rinsing, and dehydration of injection molded parts, belonging to the field of injection molded part cleaning technology. Background Technology

[0002] After injection molded parts are demolded, they often retain a certain amount of internal stress, and mold release agent, oil, and fine particles may adhere to the surface and pores of the parts. To eliminate internal stress and improve dimensional stability and surface cleanliness, the industry commonly uses a post-treatment process that combines boiling, rinsing, and dehydration.

[0003] In existing technologies, the above-mentioned processes are mostly completed in stages by manual labor or semi-automated equipment: the operator pours the injection molded parts from the material frame into the boiling container, sets the boiling time and water temperature based on experience, and after boiling, the material bucket is manually transferred to the rinsing station, and after rinsing, it is transferred to the dewatering equipment. The entire process involves a large amount of manual intervention, and the connection rhythm of each station lacks uniform coordination. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide an automated boiling, rinsing and dehydration control method for injection molded parts. This method overcomes the defects of the prior art, such as low automation of the boiling, rinsing and dehydration process, parameter dependence on experience, fragmented workstation cycle time and difficulty in ensuring quality consistency. The invention provides an automated boiling, rinsing and dehydration control method and system for injection molded parts, realizing automatic connection of the entire process and collaborative optimization of multiple parameters.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides an automated boiling, rinsing, and dehydration control method for injection molded parts, comprising: an automated processing system consisting of a conveyor line, a material tank, a robotic arm, a closed boiling area, a boiling tank, an ultrasonic rinsing tank, a dehydrator, a material feeding slide tilting device, and a material feeding flow line, wherein the material tank passes through the boiling, rinsing, and dehydration stations and has a coverable frame, the method comprising:

[0007] The injection molded parts are transferred into the material barrel via the conveyor line. After the material barrel is full, the frame cover is closed and the parts are transferred to the boiling closed area. The robotic arm docks and identifies the material barrel and grabs it into the boiling tank. The parts are boiled at a constant temperature and timed according to the target boiling time determined by the adaptive formula. The lid is automatically closed during the boiling process. After the timer is completed, the lid is automatically opened and an alarm is issued.

[0008] The robotic arm grabs the bucket after boiling and places it into the ultrasonic rinsing tank, where it is ultrasonically rinsed for the set rinsing time.

[0009] The robotic arm grabs the rinsed material buckets and transfers them to the dewatering machine. After closing the frame cover, the buckets are centrifuged and dewatered. Once dewatered, they are transferred to the unloading slide tilting device, where the injection molded parts are poured into the unloading flow line and transferred to the material frame. The target boiling time is determined by an adaptive formula that comprehensively considers the material, wall thickness, filling amount, and water temperature deviation of the injection molded parts. The grabbing order of the material buckets to be transferred is dynamically scheduled based on the transfer priority score that comprehensively considers the retention degree, rinsing urgency, process completion degree, and transfer energy consumption. The target dewatering time is determined by a convergence formula based on the moisture content exponential decay model. The target boiling time is used as a known parameter in priority ranking, and the target dewatering time is fed back to congestion assessment, so that the boiling tank, ultrasonic rinsing tank, and dewatering machine form a parameter-coupled collaborative optimization closed loop.

[0010] Furthermore, the target boiling time is calculated using the following formula:

[0011] T_b=T_0×[1+α·(δ / δ_ref)+β·(w / w_ref)+γ·(ρ / ρ_ref)]×exp[-λ·(ΔT / T_ref)]

[0012] In the formula, T_b is the target boiling time, T_0 is the baseline boiling time, δ is the wall thickness of the current batch of injection molded parts, δ_ref is the reference wall thickness, w is the actual filling mass of the injection molded parts in the barrel, w_ref is the reference filling mass, ρ is the density of the injection molded part material, ρ_ref is the reference material density, ΔT is the absolute value of the difference between the set water temperature and the actual water temperature, T_ref is the reference water temperature, α, β, and γ are the weighting coefficients of wall thickness, filling mass, and material density, respectively, and λ is the exponential decay coefficient of water temperature deviation.

[0013] Furthermore, the transfer priority score of the material hopper is calculated using the following formula:

[0014] P_k=ω_1·(t_wk / T_bk)+ω_2·(C_us / C_us,max)+ω_3·(1-Q_k / Q_max)+ω_4·(1-E_k / E_max)

[0015] In the formula, P_k is the transfer priority score of the k-th bucket, t_wk is the dwell time of the k-th bucket in the boiling tank or ultrasonic rinsing tank, T_bk is the target boiling time corresponding to the k-th bucket, C_us is the current occupied capacity of the ultrasonic rinsing tank, C_us,max is the maximum capacity of the ultrasonic rinsing tank, Q_k is the stress relief completion degree of the k-th bucket in the boiling process, Q_max is the upper limit of the stress relief completion degree, E_k is the estimated energy consumption of the robotic arm to transport the k-th bucket to the next station, E_max is the upper limit reference value of energy consumption, and ω_1, ω_2, ω_3, and ω_4 are the weight coefficients of each item; the robotic arm grabs the transfer buckets in descending order of P_k.

[0016] Furthermore, the target dehydration time is calculated using the following formula:

[0017] T_d=(1 / κ)·ln[M_0·(ω_r)^2·J / (η·M_th)]

[0018] In the formula, T_d is the target dehydration time, M_0 is the initial moisture content of the injection molded parts in the barrel after rinsing, ω_r is the centrifugal angular velocity of the dehydrator, J is the equivalent moment of inertia of the barrel and the internal injection molded parts about the dehydrator shaft, η is the energy efficiency coefficient, M_th is the target residual moisture content threshold, and κ is the moisture content decay constant.

[0019] Furthermore, the target boiling time is used as a known parameter in the calculation of the priority score, and the dehydration time is fed back to the execution scheduling layer to estimate the occupancy time of the dehydrator and fill it back into the congestion assessment item of the priority formula, so as to realize the dynamic coupling of the cycle of the three workstations: the boiling tank, the ultrasonic rinsing tank and the dehydrator.

[0020] Furthermore, the automated processing system also includes a sensor acquisition layer, comprising a moisture content sensor and a temperature sensor in the boiling tank, a liquid level sensor and a turbidity sensor in the ultrasonic rinsing tank, a vibration sensor and a current sensor in the dewatering machine, and an RFID tag in the material tank; the wall thickness of the current batch of injection molded parts is acquired by an online laser thickness sensor, the actual filling mass of the injection molded parts in the material tank is acquired by a weighing sensor at the bottom of the material tank, the absolute value of the difference between the set water temperature and the actual water temperature is calculated from the difference between the measured value and the set value of the temperature sensor, and the initial moisture content of the injection molded parts in the material tank after rinsing is obtained from the difference between the two weighings before and after rinsing.

[0021] Furthermore, the method also includes a parameter calculation layer and an execution scheduling layer. The parameter calculation layer runs the calculation formulas for the target boiling time, transfer priority score, and target dehydration time. The execution scheduling layer includes a programmable logic controller and a controller for the robotic arm. The outputs of the calculation formulas for the target boiling time, transfer priority score, and target dehydration time are respectively converted into control instructions for the heating valve and timer of the boiling tank, the gripping sequence of the robotic arm, and the frequency converter and timer of the dehydrator.

[0022] Furthermore, the target boiling time is sent to the heating valve and timer of the boiling tank as its actual set value, and triggers the opening of the lid and alarm signal after the timer is completed; the transfer priority score is sent to the controller of the robotic arm as the basis for the decision of the grasping order; the target dehydration time is sent to the frequency converter and timer of the dehydrator as the dehydration running time, and together with the filling quality of the material bucket, it participates in the load and energy efficiency optimization of the dehydrator.

[0023] Furthermore, the equivalent moment of inertia of the material bucket and the internal injection molded parts around the dehydrator shaft is obtained by real-time calculation of the structural parameters of the material bucket and the filling mass. The stress relief completion degree of the k-th material bucket in the boiling process is estimated by the process model based on the boiling temperature and the processing time. The estimated energy consumption of the robotic arm to transport the k-th material bucket to the next station is obtained by the energy model estimated by the gripping path length and the load.

[0024] Furthermore, the robotic arm uses RFID tags on the material bins to identify and grasp materials between workstations.

[0025] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0026] I. The boiling parameters have been upgraded from experience-based settings to formulaic adaptive settings. The first formula comprehensively considers the material, wall thickness, filling amount, and water temperature deviation, so that the boiling time is dynamically adjusted according to batch characteristics, eliminating the subjective fluctuations of human experience and significantly improving the consistency and stability of stress relief effect;

[0027] Second, the transfer cycle has been upgraded from a fixed sequence to a priority dynamic scheduling. The second formula incorporates the degree of retention, the urgency of rinsing, the degree of process completion, and the energy consumption of transfer into a unified evaluation, so that the gripping sequence of the robotic arm always serves the overall efficiency of the system, effectively alleviating the structural contradiction of the coexistence of water boiling tank congestion and dewatering machine idleness, and improving the continuity and cycle balance of the entire process;

[0028] Third, the dehydration control has been upgraded from a fixed duration to a convergent calculation based on a moisture content decay model. The third formula reverses the dehydration time according to the exponential decay law of centrifugal dehydration, which not only ensures that the residual moisture content meets the standard, but also avoids ineffective overtime operation, thus balancing dehydration quality and energy economy.

[0029] IV. Significantly improved automation and safety throughout the entire process. The robotic arm automatically docks and identifies components, automatically closes the cover, and uses timing to trigger alarms and determine when the cover is closed. This reduces the need for direct human contact with high-temperature and humid work areas, lowering the risk of parts being thrown out and personnel being burned.

[0030] Fifth, the three formulas form a parameter coupling closed loop. The output of the first formula serves as the input of the second formula, and the output of the third formula is fed back to the scheduling evaluation. This integrates the three originally separate processes of boiling, rinsing, and dehydration into a collaborative optimization framework, thereby achieving efficient, low-consumption, and stable operation of the overall process while ensuring product quality. Attached Figure Description

[0031] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0032] Figure 1 This is a schematic diagram of the overall architecture of an automated boiling, rinsing and dehydration control method for injection molded parts provided in an embodiment of the present invention;

[0033] 1. Conveyor line; 2. Material hopper; 3. Robotic arm; 4. Boiling enclosed area; 5. Boiling tank; 6. Ultrasonic rinsing tank; 7. Dewatering machine; 8. Feeding slide tilting device; 9. Feeding flow line. Detailed Implementation

[0034] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0035] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0036] Example:

[0037] This embodiment proposes an automated method for controlling the boiling, rinsing, and dehydration of injection molded parts, as detailed below:

[0038] I. System Composition and Overall Process

[0039] Please see Figure 1This solution is applied to an automated processing system consisting of a conveyor line 1, a material hopper 2, a robotic arm 3, a closed boiling area 4, a boiling tank 5, an ultrasonic rinsing tank 6, a dewatering machine 7, a material unloading slide tilting device 8, and a material unloading flow line 9. Specifically: Conveyor line 1 transfers injection molded parts from the feeding end to the material hopper; material hopper 2 carries the injection molded parts, passing through the boiling, rinsing, and dewatering stations, and has a cover that can be closed; robotic arm 3 identifies and grabs the material hopper between stations; the closed boiling area 4 and the boiling tank 5 perform constant-temperature, timed boiling of the injection molded parts; the ultrasonic rinsing tank 6 performs ultrasonic rinsing of the boiled injection molded parts; the dewatering machine 7 performs centrifugal dewatering of the rinsed injection molded parts; and the material unloading slide tilting device 8 and the material unloading flow line 9 unload the processed injection molded parts and transfer them into a material frame.

[0040] The overall process is as follows: The operator pours the injection molded parts from the material frame into conveyor line 1, which then transfers them to the material tank 2. Once the material tank 2 is full, the operator manually closes it and presses a button to start the sliding table, which moves from the enclosed outer partition area to the boiling enclosed area 4. The robotic arm 3, controlled by a robot signal, docks with and identifies the material tank 2, grabbing it and placing it in the designated boiling tank 5. Boiling is then performed according to the product's specific boiling time and temperature settings. The lid is automatically closed during boiling to prevent the product from floating and affecting the boiling effect. When the set boiling time is automatically completed, the lid is opened and an alarm sounds. The robotic arm 3 then removes the material from the tank. Bucket 2 is picked up by the ultrasonic rinsing tank 6, and the rinsing time is set for automatic rinsing. The robotic arm 3 is controlled to pick up the bucket 2 after ultrasonic rinsing and put it into the dewatering machine 7 for dewatering. During dewatering, care should be taken to close the frame cover of bucket 2 to prevent the product from being thrown out. The robotic arm 3 is controlled to pick up the dewatered bucket 2 and put it into the unloading slide tilting device 8. The unloading slide tilting device 8 is manually moved to the position area of ​​the outer unloading flow line 9. The tilting angle of bucket 2 is manually controlled by the button to pour the injection molded product into the unloading flow line 9. The injection molded product is transferred into the material frame through the unloading flow line 9 to complete the boiling rinsing and dewatering process.

[0041] Based on the above process, this solution adds a sensor acquisition layer, a parameter calculation layer, and an execution scheduling layer. The sensor acquisition layer includes online moisture content / temperature sensors installed in the boiling tank, level and turbidity sensors installed in the rinsing tank, vibration and current sensors installed in the dewatering machine, and RFID tags on the feed hopper; the parameter calculation layer runs three control formulas; the execution scheduling layer includes a programmable logic controller and a robotic arm controller. The calculation results of the three formulas are ultimately converted into control commands for the heating valve in the boiling tank, the timer, the robotic arm's gripping sequence, and the dewatering machine's speed and runtime.

[0042] II. Boiling Time Setting Calculation

[0043] To overcome the shortcomings of existing technologies where boiling time relies entirely on human experience, this invention proposes a formula for setting the target boiling time. The physical meaning of this formula is: considering the material, wall thickness, filling density, and water temperature deviation of the injection molded part, normalization is used to unify all factors to the same dimensional scale, ultimately outputting a boiling time constrained by an upper limit. The normalization operation (i.e., dividing the physical quantity by its reference value) is based on the fact that different parameters have different dimensions and cannot be directly added. Therefore, they must be converted into dimensionless relative deviations before linear superposition. This is a direct application of the principle of dimensional homogeneity. The formula for setting the boiling time is:

[0044] T_b=T_0×[1+α·(δ / δ_ref)+β·(w / w_ref)+γ·(ρ / ρ_ref)]×exp[-λ·(ΔT / T_ref)]

[0045] The meanings of each parameter in the formula are as follows:

[0046] T_b represents the target boiling time, measured in minutes (min), and is the output of the formula;

[0047] T_0 is the baseline boiling time, measured in minutes (min). The data source is the reference value determined by process tests for standard samples (standard material, standard wall thickness, standard filling amount, and standard water temperature), stored in the system's process parameter library, and read by the parameter calculation layer.

[0048] δ represents the wall thickness of the current batch of injection molded parts, in millimeters (mm). The data source is the product's 3D model or an online laser thickness sensor, which is collected and uploaded by the sensor acquisition layer.

[0049] δ_ref is the reference wall thickness, with the dimension of millimeters (mm). The data source is the wall thickness of the standard sample. It is a preset constant and stored in the process parameter library.

[0050] w represents the actual mass of the injection molded parts inside the barrel, measured in kilograms (kg). The data source is the weighing sensor at the bottom of the barrel, collected by the sensor acquisition layer.

[0051] w_ref is the reference filling mass, with the dimension of kilograms (kg). The data source is the rated filling capacity of the hopper, which is a preset constant.

[0052] ρ is the density of the material used in the injection molded part, with the dimension of kilograms per cubic meter (kg / m³). The data source is obtained by looking up the corresponding material grade in the bill of materials (BOM) for this batch, and is obtained by querying the local database by the parameter calculation layer.

[0053] ρ_ref is the reference material density, in units of kilograms per cubic meter (kg / m³), and the data source is the material density of the standard sample, which is a preset constant;

[0054] ΔT is the absolute value of the difference between the set water temperature and the actual water temperature, with the dimension of degrees Celsius (°C). The data source is the difference between the measured value and the set value of the online temperature sensor of the water boiling tank, which is calculated by the sensor acquisition layer and then uploaded.

[0055] T_ref is the reference water temperature, with the dimension of degrees Celsius (°C). The data source is the standard boiling temperature specified in the process, and it is a preset constant.

[0056] α, β, and γ are the weighting coefficients for wall thickness, filling mass, and material density, respectively. The data are derived from the regression calibration results of process experiments and stored in the process parameter library.

[0057] λ is the exponential decay coefficient of the water temperature deviation, and the data source is the calibration constant;

[0058] III. Priority Calculation for Material Bucket Transfer

[0059] After boiling and rinsing, multiple buckets may simultaneously await grabbing and transfer by the robotic arm. If a simple first-come, first-served rule is applied, it can easily lead to congestion in the boiling tank or idleness in the dewatering machine. Therefore, this invention proposes a bucket transfer priority formula. Its physical meaning is: considering the bucket's existing residence time in the boiling tank, the target boiling time, the urgency of ultrasonic rinsing, the current congestion level of the dewatering machine, and energy consumption penalties, a dimensionless priority score is calculated for each bucket awaiting transfer. The higher the score, the more preferentially the bucket will be grabbed by the robotic arm. The bucket transfer priority formula is as follows:

[0060] P_k=ω_1·(t_wk / T_bk)+ω_2·(C_us / C_us,max)+ω_3·(1-Q_k / Q_max)+ω_4·(1-E_k / E_max)

[0061] The meanings of each parameter in the formula are as follows:

[0062] P_k is the transfer priority score of the k-th hopper, which is the output of the formula;

[0063] t_wk is the duration of the kth material bucket in the boiling tank or floating tank, measured in minutes (min). The data source is the system's timestamp of the moment each material bucket enters the tank, which is calculated in real time by the execution scheduling layer.

[0064] T_bk is the target boiling time corresponding to the kth material bucket, in minutes (min), which is the result calculated by the first formula, output and cached by the parameter calculation layer;

[0065] C_us represents the current occupied capacity of the ultrasonic floating pool, measured in cubic meters (m³). The data source is the liquid level sensor of the floating pool, collected by the sensor acquisition layer.

[0066] C_us,max is the maximum capacity of the ultrasonic floating pool, in cubic meters (m³), and is an inherent constant of the equipment, preset in the system;

[0067] Q_k represents the stress relief completion rate of the k-th bucket during the boiling process. The data source is the output of the process model estimated by the boiling temperature and the processing time, and is estimated by the parameter calculation layer.

[0068] Q_max is the upper limit of stress relief completion, which is a constant (standard upper limit).

[0069] E_k is the estimated energy consumption of the robotic arm to transport the k-th bucket to the next workstation. The unit is joule (J). The data source is the energy model estimated by the grasping path length and load, and the estimation is performed by the parameter calculation layer.

[0070] E_max is the upper limit reference value for energy consumption, with the dimension of joule (J), and is a preset constant;

[0071] ω_1, ω_2, ω_3, and ω_4 are the weight coefficients of each item, and the data comes from the scheduling strategy calibration results and is stored in the process parameter library.

[0072] IV. Dehydration Time Setting

[0073] If the dehydration process is insufficient, the moisture content will be too high; if it is too long, energy consumption will be wasted and the risk of parts being thrown out will increase. Therefore, this invention proposes a formula for setting the dehydration time. Its physical meaning is that, based on the initial moisture content to be dehydrated, and combined with centrifugal speed, load inertia, moisture content convergence threshold, and energy efficiency coefficient, the required dehydration time is obtained through an inverse solution of the exponential decay model of moisture content.

[0074] T_d=(1 / κ)·ln[M_0·(ω_r)²·J / (η·M_th)]

[0075] The meanings of each parameter in the formula are as follows:

[0076] T_d represents the target dehydration time, measured in minutes (min), and is the output of the formula;

[0077] M_0 represents the initial moisture content of the injection molded part in the hopper after rinsing, with the dimension of kilograms (kg). The data source is the value estimated based on the rinsing time and the material's water absorption model, or obtained by the difference between two weighings before and after rinsing by an online weighing sensor, and collected by the sensor acquisition layer.

[0078] ω_r is the centrifugal angular velocity of the dehydrator, with the dimension of radians per second (rad / s). The data source is the real-time speed conversion value fed back by the frequency converter of the dehydrator, which is collected by the sensor acquisition layer.

[0079] J is the equivalent moment of inertia of the hopper and internal injection molded parts around the dehydrator shaft, with the dimension of kilogram-square meter (kg·m²). The data source is the geometric calculation value of the hopper structural parameters and filling mass, which is calculated in real time by the parameter calculation layer based on the weighing results.

[0080] η is the energy efficiency coefficient, which characterizes the efficiency of water removal during the dehydration process. The data is obtained from process calibration tests and stored in the process parameter library.

[0081] M_th is the target residual moisture content threshold after dehydration is completed, with the dimension of kilogram (kg). The data source is the upper limit value specified by the product quality standard, and it is a preset constant.

[0082] κ is the moisture content decay constant, with dimensions in minutes (min). -1 The data source is the centrifugal drying kinetic calibration results, which are stored in the process parameter library.

[0083] During centrifugal dewatering, the residual moisture content in the container decreases approximately exponentially with the dewatering time, i.e., the moisture content and time satisfy M(t) = M_0·exp(-κt). Let M(t) = M_th and solve for t to obtain the above formula for dewatering time.

[0084] V. Application of the output results of the three formulas in practical processes

[0085] The three formulas are calculated by the system's parameter calculation layer (the arithmetic module within the programmable logic controller), and their outputs are sent to the corresponding execution entities, thereby driving the entire process to run automatically. The specific correspondence is as follows:

[0086] The output T_b of the first formula is sent to the heating valve and timer of the boiling tank as the actual set value for this batch of boiling; the system starts the countdown based on T_b, and triggers the opening of the lid and alarm signal after the countdown is completed. The execution subject is the control unit of the boiling tank (including the heating valve and timer); the output P_k of the second formula is sent to the robotic arm controller as the decision basis for the robotic arm's grasping order; the controller grasps the material buckets in order from high to low P_k and transfers them to the next work station. The execution subject is the robotic arm (3) and its controller; the output T_d of the third formula is sent to the frequency converter and timer of the dewatering machine as the set duration of the dewatering operation; at the same time, T_d and the filling mass in the material bucket are used together to judge the load of the dewatering machine and indirectly participate in energy efficiency optimization. The execution subject is the control unit of the dewatering machine (7).

[0087] The following example uses a specific application scenario to illustrate how the three formulas are actually invoked and output results. For ease of explanation, the calculations will use symbols that conform to the aforementioned parameter definitions, and each input value will be a specific batch of actual measurements or preset values.

[0088] For a specific batch of injection molded parts, the input parameters read or collected from the process parameter library are as follows: the baseline boiling time T_0 is a preset reference value; the wall thickness δ of the current batch of injection molded parts is collected by an online laser thickness sensor, and the reference wall thickness δ_ref is the process standard value; the actual filling mass w in the hopper is collected by a weighing sensor, and the reference filling mass w_ref is the rated filling amount of the hopper; the material density ρ is obtained from the bill of materials table, and the reference density ρ_ref is the process standard value; the difference ΔT between the set water temperature and the actual water temperature is measured by a temperature sensor and the absolute value is taken, and the reference water temperature T_ref is the process specified value; the weighting coefficients α, β, γ and the exponential decay coefficient λ are all calibration constants stored in the process parameter library.

[0089] Substituting the above parameters into the first formula yields the target boiling time T_b for this batch. The calculation result represents the required boiling duration to fully eliminate internal stress in the injection-molded part, considering deviations in wall thickness, filling amount, and material compared to the standard sample, as well as the impact of water temperature deviation on heat transfer efficiency. The parameter calculation layer writes T_b into the timer setting register of the boiling tank control unit and caches this value for use in the second formula. The parameter calculation layer is responsible for the calculation, while the boiling tank control unit is responsible for executing the "boiling at T_b" action.

[0090] Suppose there are multiple buckets in the boiling tank waiting to be transferred. For the k-th bucket, the parameter calculation layer reads the following parameters: the time the bucket has been in the boiling tank, t_wk, is obtained by timestamp timing, and its target boiling time, T_bk, is the result calculated and cached by the first formula; the current occupied capacity, C_us, of the ultrasonic rinsing tank is collected by the liquid level sensor, and its maximum capacity, C_us,max, is a device constant; the stress relief completion degree, Q_k, of the bucket is estimated by the process model, and the upper limit, Q_max, is a constant; the estimated energy consumption, E_k, of the robotic arm to transport it to the next station is estimated by the path and load energy model, and the upper limit, E_max, is a constant; the weights ω_1, ω_2, ω_3, and ω_4 are scheduling strategy calibration constants.

[0091] Substituting the above parameters into the second formula, we obtain the priority score P_k of the k-th bucket. The physical meaning of P_k is the degree to which this bucket "should be transferred with priority" compared to other buckets—the deeper the stagnation, the more congested the floating pool, the closer the stress relief is to completion, and the lower the transfer energy consumption, the higher the score. The parameter calculation layer calculates P_k for each bucket to be transferred, generates a grasping queue sorted in descending order of score, and sends this queue to the robotic arm controller. The main entity performing the calculation is the parameter calculation layer, while the main entity performing the "priority-based grasping and transfer" action is robotic arm 3 and its controller.

[0092] Suppose a material barrel has completed rinsing and is ready for dewatering. The parameter calculation layer reads the following parameters: the initial moisture content M_0 of the injection molded parts in the barrel after rinsing is obtained by the difference between two weighings before and after rinsing from the online weighing sensor; the centrifugal angular velocity ω_r of the dewatering machine is obtained by converting the rotational speed fed back by the frequency converter; the equivalent rotational inertia J of the barrel and the internal injection molded parts is calculated from the weighing results and the geometry of the barrel; the energy efficiency coefficient η is the process calibration constant; the target residual moisture content threshold M_th is the value specified by the quality standard; and the moisture content decay constant κ is the kinetic calibration constant.

[0093] Substituting the above parameters into the third formula, the target dewatering time T_d of the material bucket is obtained. The physical meaning of T_d is: the time required for the moisture content to decrease from the initial moisture content M_0 to the target threshold M_th under the exponential decay law of centrifugal dewatering. The parameter calculation layer writes T_d into the timer setting register of the dewatering machine control unit, and the dewatering machine runs for the corresponding time and then automatically stops. The main body performing the calculation is the parameter calculation layer, and the main body performing the "dewatering by T_d" action is the dewatering machine (7) control unit.

[0094] In a complete batch, the collaborative process of the three is as follows: the parameter calculation layer first determines T_b for each bucket according to the first formula, and the boiling tank completes the boiling and triggers the transfer request accordingly; the scheduling layer calls the second formula to sort all buckets to be transferred, and the robotic arm transfers the buckets sequentially to the rinsing tank and then to the dewatering machine; in the dewatering stage, the parameter calculation layer calls the third formula to determine T_d, and the dewatering machine completes the dewatering accordingly; after dewatering, the robotic arm transfers the buckets to the unloading slide tilting device, and the operator manually moves the slide to the outer unloading flow line position area, controls the bucket tilting angle with a button, pours the injection molded part into the unloading flow line, and finally transfers it into the material frame through the unloading flow line. In this way, the output results of the three formulas run through and drive the automatic control of the entire process of boiling, transferring, dewatering, and unloading.

[0095] As is known from common technical knowledge, this invention can be implemented through other embodiments that do not depart from its spirit or essential characteristics. Therefore, the disclosed embodiments described above are merely illustrative and not exhaustive. All modifications within the scope of this invention or its equivalents are included in this invention.

[0096] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An automated method for controlling the boiling, rinsing, and dehydration of injection molded parts, characterized in that, include: The method is applied to an automated processing system consisting of a conveyor line (1), a material hopper (2), a robotic arm (3), a closed boiling area (4), a boiling tank (5), an ultrasonic rinsing tank (6), a dewatering machine (7), a material feeding slide tilting device (8), and a material feeding flow line (9), wherein the material hopper (2) passes through the boiling, rinsing, and dewatering stations and has a coverable frame. The injection molded parts are transferred into the material bucket (2) via the conveyor line (1). After the material bucket (2) is full, the lid is closed and the parts are transferred to the boiling closed area (4). The robotic arm (3) docks with and identifies the material bucket (2) and then grabs it to the boiling tank (5). The parts are boiled at a constant temperature and timed according to the target boiling time determined by the adaptive formula. The lid is automatically closed during the boiling process. After the timer is completed, the lid is automatically opened and an alarm is issued. The robotic arm (3) grabs the material bucket (2) after boiling and places it into the ultrasonic rinsing tank (6) for ultrasonic rinsing according to the set rinsing time. The robotic arm (3) grabs the rinsed material bucket (2) to the dewatering machine (7), closes the frame cover and centrifuges it for dewatering. After dewatering, it is transferred to the unloading slide turning device (8). After turning, the injection molded parts are poured into the unloading flow line (9) and transferred into the material frame. The target boiling time is determined by an adaptive formula that takes into account the material, wall thickness, filling amount and water temperature deviation of the injection molded parts. The grabbing order of the material bucket (2) to be transferred is dynamically scheduled by the transfer priority score that takes into account the retention degree, rinsing urgency, process completion degree and transfer energy consumption. The target dewatering time of centrifugation is determined by a convergence formula based on the moisture content exponential decay model. The target boiling time is used as a known parameter to participate in priority ranking and the target dewatering time is fed back to the congestion assessment, so that the boiling tank (5), the ultrasonic rinsing tank (6) and the dewatering machine (7) form a parameter-coupled collaborative optimization closed loop.

2. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 1, characterized in that, The target boiling time is calculated using the following formula: T_b=T_0×[1+α·(δ / δ_ref)+β·(w / w_ref)+γ·(ρ / ρ_ref)]×exp[-λ·(ΔT / T_ref)]; In the formula, T_b is the target boiling time, T_0 is the baseline boiling time, δ is the wall thickness of the current batch of injection molded parts, δ_ref is the reference wall thickness, w is the actual filling mass of the injection molded parts in the barrel (2), w_ref is the reference filling mass, ρ is the density of the injection molded part material, ρ_ref is the reference material density, ΔT is the absolute value of the difference between the set water temperature and the actual water temperature, T_ref is the reference water temperature, α, β, and γ are the weighting coefficients of wall thickness, filling mass, and material density, respectively, and λ is the exponential decay coefficient of water temperature deviation.

3. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 2, characterized in that, The transfer priority score of the material hopper (2) is calculated by the following formula: P_k=ω_1·(t_wk / T_bk)+ω_2·(C_us / C_us,max)+ω_3·(1-Q_k / Q_max)+ω_4·(1-E_k / E_max); In the formula, P_k is the transfer priority score of the kth bucket (2), t_wk is the dwell time of the kth bucket in the boiling tank (5) or the ultrasonic rinsing tank (6), T_bk is the target boiling time corresponding to the kth bucket, C_us is the current occupied capacity of the ultrasonic rinsing tank (6), C_us,max is the maximum capacity of the ultrasonic rinsing tank (6), Q_k is the stress relief completion degree of the kth bucket in the boiling process, Q_max is the upper limit value of stress relief completion degree, E_k is the estimated energy consumption of the robotic arm (3) to transport the kth bucket to the next station, E_max is the upper limit reference value of energy consumption, ω_1, ω_2, ω_3, and ω_4 are the weight coefficients of each item; the robotic arm (3) grabs the transfer buckets (2) in order from high to low P_k.

4. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 3, characterized in that, The target dehydration time is calculated using the following formula: T_d=(1 / κ)·ln[M_0·(ω_r)^2·J / (η·M_th)]; In the formula, T_d is the target dehydration time, M_0 is the initial moisture content of the injection molded parts in the rinsing bucket (2), ω_r is the centrifugal angular velocity of the dehydrator (7), J is the equivalent rotational inertia of the rinsing bucket (2) and the internal injection molded parts around the axis of the dehydrator (7), η is the energy efficiency coefficient, M_th is the target residual moisture content threshold, and κ is the moisture content decay constant.

5. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 4, characterized in that, The target boiling time is used as a known parameter in the calculation of the priority score. The dehydration time is fed back to the execution scheduling layer to estimate the occupancy time of the dehydrator (7) and fill it back into the congestion assessment item of the priority formula, so as to realize the dynamic coupling of the cycle of the three stations of boiling pool (5), ultrasonic rinsing pool (6) and dehydrator (7).

6. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 4, characterized in that, The automated processing system is also equipped with a sensor acquisition layer, including a moisture content sensor and a temperature sensor in the boiling tank (5), a liquid level sensor and a turbidity sensor in the ultrasonic rinsing tank (6), a vibration sensor and a current sensor in the dehydrator (7), and an RFID tag in the material tank (2); the wall thickness of the current batch of injection molded parts is acquired by an online laser thickness sensor, the actual filling mass of the injection molded parts in the material tank (2) is acquired by a weighing sensor at the bottom of the material tank (2), the absolute value of the difference between the set water temperature and the actual water temperature is calculated by the difference between the measured value and the set value of the temperature sensor, and the initial moisture content of the injection molded parts in the material tank (2) after rinsing is obtained by the difference between the two weighings before and after rinsing.

7. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 1, characterized in that, The method also includes a parameter calculation layer and an execution scheduling layer. The parameter calculation layer runs the calculation formulas for the target boiling time, transfer priority score and target dehydration time. The execution scheduling layer includes a programmable logic controller and a controller for the robotic arm (3). The outputs of the calculation formulas for the target boiling time, transfer priority score and target dehydration time are respectively converted into control instructions for the heating valve and timer of the boiling tank (5), the grasping sequence of the robotic arm (3) and the frequency converter and timer of the dehydrator (7).

8. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 1, characterized in that, The target boiling time is sent to the heating valve and timer of the boiling tank (5) as its actual set value. After the timer is completed, the lid is opened and an alarm signal is triggered. The transfer priority score is sent to the controller of the robotic arm (3) as the basis for the grabbing order. The target dehydration time is sent to the frequency converter and timer of the dehydrator (7) as the dehydration running time, and together with the filling quality of the material bucket (2), it participates in the load and energy efficiency optimization of the dehydrator (7).

9. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 4, characterized in that, The equivalent rotational inertia of the material bucket (2) and the internal injection molded parts around the dehydrator (7) shaft is obtained by real-time calculation of the structural parameters and filling mass of the material bucket (2). The stress relief completion degree of the kth material bucket in the boiling process is estimated by the process model based on the boiling temperature and the processing time. The estimated energy consumption of the robotic arm (3) to transport the kth material bucket to the next station is obtained by the energy model estimated by the gripping path length and load.

10. The automated boiling, rinsing, and dehydration control method for injection molded parts according to claim 1, characterized in that, The robotic arm (3) uses the radio frequency identification tag on the material bucket (2) to identify and grab the workstations.

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