CN114801050A

CN114801050A - Feeding device of injection molding machine and operation method thereof

Info

Publication number: CN114801050A
Application number: CN202210444757.4A
Authority: CN
Inventors: 裴士轻; 蔡峻峰; 姜冬升
Original assignee: Kenta Enterprise Co ltd
Current assignee: Kenta Enterprise Co ltd
Priority date: 2022-04-26
Filing date: 2022-04-26
Publication date: 2022-07-29
Anticipated expiration: 2042-04-26
Also published as: CN114801050B

Abstract

The embodiment of the specification provides an injection molding machine feedway, and the device includes: the container is used for containing injection molding materials; the feeding pipe is used for conveying the injection molding material in the container to an injection molding machine; a controller to: determining a first feeding speed of a feeding pipe for feeding the injection molding machine; and controlling the feeding pipe to feed the injection molding machine at a first feeding speed.

Description

Feeding device of injection molding machine and operation method thereof

Technical Field

The specification relates to the field of injection molding machines, in particular to a feeding device of an injection molding machine and an operation method thereof.

Background

An injection molding machine is a main molding device for molding thermoplastic plastics or thermosetting plastics into plastic products of various shapes by using a plastic molding die, and is widely used in industrial production and manufacturing. The intellectualization of injection molding production plays an important role in promoting the improvement of production efficiency and product performance.

It is therefore desirable to provide a feeder apparatus for an injection molding machine and a method of operating the same to optimize injection molding production.

Disclosure of Invention

One or more embodiments of the present disclosure provide a feeder device for an injection molding machine, the feeder device including: the container is used for containing injection molding materials; the feeding pipe is used for conveying the injection molding material in the container to an injection molding machine; a controller to: determining a first feeding speed of a feeding pipe for feeding the injection molding machine; and controlling the feeding pipe to feed the injection molding machine at a first feeding speed.

One or more embodiments of the present disclosure provide a method of operating a feeding device of an injection molding machine, the feeding device including a container, a feeding pipe, and a controller, the method including: determining a first feeding speed of a feeding pipe for feeding the injection molding machine; and controlling the feeding pipe to feed the injection molding machine at a first feeding speed.

One or more embodiments of the present description provide a computer-readable storage medium storing computer instructions that, when read by a computer, are executed by the computer to implement a method of operating a feeder of an injection molding machine as described in any one of the above embodiments.

Drawings

The present description will be further explained by way of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not intended to be limiting, and in these embodiments like numerals are used to indicate like structures, wherein:

FIG. 1 is a schematic diagram of an application scenario of a feeding device according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram of a feed device according to some embodiments of the present disclosure;

FIG. 3 is an exemplary flow diagram of a method of operating a feed device according to some embodiments herein;

FIG. 4 is an exemplary flow chart illustrating feeding an injection molding machine at a second feed rate according to some embodiments of the present description;

FIG. 5 is an exemplary flow chart illustrating feeding an injection molding machine at a third feed rate according to some embodiments of the present description;

FIG. 6 is a schematic illustration of determining a target product material mix and a target product production rate based on a second performance prediction model in accordance with some embodiments of the present description;

fig. 7 is an exemplary flow chart illustrating feeding an injection molding machine at a fourth feed rate according to some embodiments of the present disclosure.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

It should be understood that "system", "apparatus", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.

As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.

Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.

Fig. 1 is a schematic view of an application scenario of a feeding device according to some embodiments of the present disclosure.

In some embodiments, an application scenario 100 of an injection molding machine feeder may include a controller 110, a network 120, a storage device 130, a terminal device 140, a feeder 150, and an injection molding machine 160. The application scenario 100 can ensure the normal operation of the injection molding production process by determining the feeding speed of the feeding device and controlling the feeding device to feed the injection molding machine at the determined feeding speed by implementing the method and/or process disclosed in the specification.

The controller 110 may be used to process data and/or information from at least one component of the application scenario 100 or an external data source (e.g., a cloud data center). Controller 110 may be connected to storage device 130, terminal device 140, injection molding machine supply 150, and/or injection molding machine 160 via network 120 to access and/or receive data and information. For example, the controller 110 may receive information related to the supply device 150 (e.g., feed rate, material detection results, etc.) and/or information related to the injection molding machine 160 (e.g., material consumption rate, product detection results) via the network 120. In other embodiments, the controller 110 may send information related to the supply device 150 (e.g., feed rate, material detection results, etc.) and/or information related to the injection molding machine 160 (e.g., material consumption rate, product detection results) to the terminal device 140 via the network 120. In some embodiments, the controller 110 may be a single controller or a group of controllers. The set of servers can be centralized or distributed (e.g., the servers 110 can be a distributed system), can be dedicated, or can be serviced by other devices or systems at the same time. In some embodiments, controller 110 may be connected locally to network 120 or remotely from network 120. In some embodiments, the controller 110 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-tiered cloud, and the like, or any combination thereof. In some embodiments, the controller 110 may be part of the feed device 150 and disposed on the feed device 150.

Network 120 may facilitate the exchange of information and/or data. In some embodiments, one or more components in the application scenario 100 (e.g., the storage device 130, the terminal device 140, the feed device 150, and the injection molding machine 160) may send information and/or data to another component in the application scenario 100 via the network 120. Network 120 may include a Local Area Network (LAN), a Wide Area Network (WAN), a wired network, a wireless network, and the like, or any combination thereof. In some embodiments, the network 120 may be any one or more of a wired network or a wireless network. In some embodiments, network 120 may include one or more network access points. For example, the network 120 may include wired or wireless network access points, such as base stations and/or network switching points, through which one or more components of the application scenario 100 may connect to the network 120 to exchange data and/or information.

Storage device 130 may be used to store data and/or instructions. The data may include data related to the user, the terminal device 140, the data acquisition apparatus 140, and the like. In some embodiments, storage device 130 may store data and/or instructions that controller 110 uses to perform or use to perform the exemplary methods described in this specification. For example, the memory device 130 may store production information (e.g., feed rates corresponding to historical time periods) for the feeder devices of the injection molding machine. As another example, storage 130 may store one or more machine learning models. In some embodiments, the storage device 130 may be part of the controller 110. In some embodiments, storage device 130 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), and the like, or any combination thereof. In some embodiments, storage device 130 may be implemented on a cloud platform. In some embodiments, a storage device 130 may be connected to the network 120 to communicate with one or more components of the application scenario 100 (e.g., the controller 110, the terminal device 140, the feed device 150, and the injection molding machine 160).

Terminal device 140 may refer to one or more terminal devices or software used by a user. In some embodiments, the user (e.g., an injection molding production operator, an injection molding production manager, etc.) may be the owner of the terminal device 140. In some embodiments, the end device 140 may include a mobile device 140-1, a tablet computer 140-2, a laptop computer 140-3, a vehicle mounted device, or the like, or any combination thereof. In some embodiments, terminal equipment 140 may include a signal transmitter and a signal receiver configured to communicate with feed device 150 and injection molding machine 160 to obtain information related to injection molding production. In some embodiments, the terminal device 140 may be fixed and/or mobile. For example, the terminal device 140 may be mounted directly on the controller 110 and/or the feeding device 150 as part of the controller 110 and/or the feeding device 150. As another example, terminal device 140 may be a mobile device, and an injection molding production worker may carry terminal device 140 at a remote location with respect to controller 110, feed device 150, and injection molding machine 160, and terminal device 140 may be connected to and/or in communication with controller 110, feed device 150, and/or injection molding machine 160 via network 120. In some embodiments, end device 140 may receive a user request and send information related to the request to controller 110 via network 120. For example, terminal equipment 140 may receive a request from a user to transmit information relating to the supply of the injection molding machine and transmit information relating to the request to controller 110 via, for example, network 120. Terminal device 140 may also receive information from controller 110 via network 120. For example, the terminal device 140 may receive information related to the feed device 150 and/or the injection molding machine 160 from the controller 110, and the determined one or more related information may be displayed on the terminal device 140.

The supply device 150 refers to a device for supplying a material for injection molding production to the injection molding machine 160. In some examples, the supply device 150 may include a container, a feed tube, and a controller. It should be understood that the controller of the feed device 150 may be the controller 110 in the scenario 100. For further description of the structure of the feeding device 150, reference is made to fig. 2, and further description is omitted here. In some embodiments, the feed device 150 may determine a feed rate for delivering injection molding material to the injection molding machine 160 based on information related to the feed device 150 (e.g., material detection results) and information related to the injection molding machine 160 (e.g., material consumption rate, injection molding parameters, product detection results, volume sensing results, etc.). Further details regarding the determination of the feed rate can be found in fig. 3-7 and will not be described here.

The injection molding machine 160 refers to a machine for injection molding production. The injection molding production refers to a process flow of melting materials (such as polyethylene, resin and the like) at high temperature, injecting the materials into a mold (such as a mobile phone shell mold, a plastic box mold and the like), cooling, solidifying, molding and demolding. In some embodiments, for some composite articles, it may be desirable to sequentially inject different materials into the mold. For example, when polyethylene, ethylene-vinyl acetate copolymer (EVA), and toner are used as materials required for some plastic parts, the materials are sequentially injected into a mold. In some embodiments, the injection molding machine 160 may include a charging bucket, an injection molding process unit, a product inspection unit, and the like. For more description of the structure of the injection molding machine 160, reference is made to fig. 2, and further description is omitted here. In some embodiments, the injection molding machine 160 may transmit its related information (e.g., the material consumption rate, injection molding parameters, product detection results, volume sensing results, etc.) to the feeding device 150 via a network to determine the feeding rate.

FIG. 2 is a schematic diagram of a feed device according to some embodiments of the present disclosure.

The supply device 200 refers to a device for supplying injection material to a mold of an injection molding machine. In some embodiments, the feeder device of the injection molding machine may include a container 210, a feed pipe 220, a controller 230, a first communication unit (not shown), a material detection unit 240, a second communication unit (not shown), a charging bucket (not shown), a transfer pump (not shown), and the like.

The container 210 may be used to contain injection molding material. In some embodiments, the supply device 200 may include one or more containers 210. The container 210 is connected to an injection molding machine, in particular, a charging barrel in the injection molding machine, through a feeding pipe 220. Different containers can contain different injection molding materials so that the injection molding machine can produce.

The feed tube 220 may be used to deliver the injection molding material in the container 210 to an injection molding machine. In some embodiments, the receptacle 210 is connected to one or more feed tubes 220.

The controller 230 may control the feeding of the feeding pipe 220 based on the set feeding speed of the feeding pipe 220 in the container 210, and control the feeding pipe 220 to supply the injection molding material according to the consumption of the injection molding machine. In some embodiments, the controller 230 may determine a first feed rate at which the feed tube 220 feeds the injection molding machine; the feeding pipe 220 is controlled to feed the injection molding machine at a first feeding speed. In some embodiments, the controller 230 may also determine a first depletion rate of the injection molding machine based on the initial product material mix and the initial product production rate; based on the first depletion rate, a first feed rate is determined. In some embodiments, the controller 230 may further adjust the first material consumption speed of the injection molding machine based on the material detection result to obtain a second material consumption speed; adjusting the first feeding speed based on the second material consumption speed to obtain a second feeding speed of the feeding pipe 220; and controlling the feeding pipe 220 to feed the injection molding machine at a second feeding speed. In some embodiments, the controller 230 may further adjust the initial product material ratio and the initial product production speed to obtain a target product material ratio and a target product production speed when the product detection result is unqualified; determining a third material consumption speed of the injection molding machine based on the material ratio of the target product and the production speed of the target product; determining a third feed rate for the feed tube 220 based on the third depletion rate; and controlling the feeding pipe 220 to feed the injection molding machine at a third feeding speed. In some embodiments, the controller 230 may also determine whether the first feeding speed needs to be adjusted based on the volume sensing result; when the first feeding speed needs to be adjusted, adjusting the first feeding speed based on a volume induction result to obtain a fourth feeding speed; and controlling the feeding pipe 220 to feed the injection molding machine at a fourth feeding speed. For details regarding the controller 230, reference is made to fig. 3-7 and related descriptions, which are not repeated herein.

The first communication unit may be used to acquire injection molding parameters of the injection molding machine. The injection molding parameters may include the material ratio of the initial product and the production speed of the initial product. In some embodiments, the first communication unit may acquire a product detection result of a product produced by the injection molding machine. The product detection result can be detected and determined by a product detection unit in the injection molding machine. For the detailed description of the above-mentioned contents of the first communication unit, refer to fig. 3 and its related description, which are not repeated herein.

The material detection unit 240 may be configured to detect the injection molding material in the container 210 and determine a material detection result of the injection molding material. For details of the above-mentioned content of the material detection unit 240, refer to fig. 4 and its related description, which are not repeated herein.

The second communication unit may be adapted to obtain a volume sensing result of a charging bucket of the injection molding machine. For the details of the above-mentioned contents of the second communication unit, refer to fig. 7 and the related description thereof, which are not repeated herein. In some embodiments, the first communication unit and the second communication unit may be the same communication unit. In some embodiments, the first communication unit and the second communication unit may be different communication units.

A delivery pump may be used to power the feed tube 220.

The feeding device of the injection molding machine can be applied to injection molding of various injection molding raw materials, injection molding parameters are dynamically adjusted, production automation is improved, and labor consumption is reduced.

It should be noted that the above description of the feeding device of the injection molding machine is merely for convenience of description and should not be construed as limiting the present disclosure to the illustrated embodiments. It will be appreciated by those skilled in the art that, given the teachings of the present system, any combination of the various structures or connections to other structures may be made without departing from such teachings. Such variations are within the scope of the present disclosure.

Fig. 3 is an exemplary flow diagram illustrating feeding an injection molding machine according to some embodiments of the present disclosure. As shown in fig. 3, the process 300 includes the following steps:

step 310, a first feeding speed of the feeding pipe for feeding the injection molding machine is determined. In some embodiments, step 310 may be performed by a controller.

By a container is meant a container which can be used for containing injection moulding material. In some embodiments, the container has at least two openings, one opening for loading and the other opening for connection to an injection molding machine through a feed tube. The container can be filled with injection molding materials to be subjected to injection molding processing. Such as polyethylene.

The injection molding material means a material used for injection molding production processing, for example, resin, polyethylene, polypropylene, phenolics, aminoplasts, and the like.

The feeding pipe is a pipeline which can be used for conveying the injection molding material in the container to an injection molding machine. Such as plastic tubing, metal tubing, etc. In some embodiments, the container is connected to at least one feed tube. One end of the feeding pipe is connected with the material container, and the other end of the feeding pipe is connected with the injection molding machine. Specifically, one end of the feeding pipe is connected with the material container, and the other end of the feeding pipe is connected with a charging barrel of the injection molding machine.

In some embodiments, the feed tube can deliver the molding material in the container to the injection molding machine based on power provided by the delivery pump.

The first feed rate is an initial amount of injection molding material per unit time in the feed tube to the injection molding machine. For example, 1m ³ Min, 0.5 kg/sec. In some embodiments, the first feed rate may be predetermined manually or determined by automatic analysis. In some embodiments, a user (e.g., an injection molding production operator, an injection molding production manager) may determine the first feed rate based on manual experience. For example, an injection molding production operator may determine empirically that the first feed rate is 0.8 kg/sec. In some embodiments, the controller can determine the first feed speed based on historical data. Wherein the historical data may include at least one injection molding material and a corresponding feed rate. It is to be understood that the controller may set a feeding speed corresponding to the same injection material as the currently fed injection material in the history data as the first feeding speed.

In some cases, the injection molding machine may perform production based on the injection material in the cartridge, and the first communication unit may acquire injection parameters of the injection molding machine. For example, the first communication unit may be communicatively connected to a control and/or memory unit of the injection molding machine to obtain the injection molding parameters. As another example, the first communication unit may obtain the injection molding parameters from a terminal, a network, and/or a database. In some embodiments, the controller may determine the first feed speed based on injection molding parameters of the injection molding machine.

The injection molding parameters refer to the process parameters for injection molding production. In some embodiments, the injection molding parameters may include initial product material proportions and initial product production speeds. In some embodiments, the controller may determine a first depletion speed of the injection molding machine based on the initial product material mix and the initial product production speed; based on the first depletion rate, a first feed rate is determined.

The initial product material ratio refers to the type and content of injection molding materials required in the product produced by the injection molding machine. For example, the material composition of the initial product of a certain plastic part is as follows: the initial product material mixture ratio of 2 g of polyethylene, 1 g of ethylene-vinyl acetate copolymer (EVA) and 0.5 g of toner is as follows: 20 g of polypropylene, 5 g of heat stabilizer and 10 g of antioxidant. In some embodiments, the initial product material mix ratio may be preset by a human or a controller.

The initial product production rate refers to the amount of product produced per unit time (e.g., within 1 minute, within 1 hour, etc.). E.g., 10 pieces/minute, 300 pieces/hour, etc.

In some embodiments, the initial product production speed may be obtained by a sensing unit (e.g., a photosensor, a camera) disposed on the injection molding machine. For example, a photoelectric sensor at the product outlet of the injection molding machine can identify and count the products in unit time; the camera at the product outlet of the injection molding machine can collect images of products in unit time to identify and count the products.

The first material consumption speed refers to the amount of various injection molding materials required by the injection molding machine to produce in unit time. For example, the first depletion rate for polyethylene is 20 grams per minute; the first consumption rate of polypropylene was 60 kg/h.

In some embodiments, the first depletion rate may be determined based on the initial product material mix and the initial product production rate. For example, the material composition of the initial product of a certain plastic part is as follows: 2 g/piece of polyethylene, 1 g/piece of ethylene-vinyl acetate copolymer (EVA), 0.5 g/piece of toner, and 15 pieces/min of initial product production rate, the first consumption rate of polyethylene is 2 × 15 to 30 g/min, the first consumption rate of EVA is 1 × 15 to 15 g/min, and the first consumption rate of toner is 0.5 × 15 to 7.5 g/min.

In some embodiments, the controller may directly use the first depletion rate as the first feed rate. For example, a first depletion rate of 10 kg/hr, then a first feed rate of 10 kg/hr.

In some embodiments, the controller may also adjust the first feed rate based on other relevant parameters (e.g., material detection results, product detection results, volume sensing results) to ensure that the amount of material in the cartridge of the injection molding machine is within a threshold range. By way of example only, the threshold range may be determined based on a ratio of injection material in a barrel of the injection molding machine to a total volume of the barrel, such as 0.8 to 0.9. When the ratio of the material in the charging barrel of the injection molding machine to the total volume of the charging barrel is less than 0.8, the controller can increase the first feeding speed to increase the material amount in the charging barrel of the injection molding machine; when the calculated ratio is larger than 0.9, the controller can reduce the first feeding speed to avoid the overflow of the injection molding material. For more details on adjusting the first feeding speed, reference is made to fig. 4-7, which are not described herein again.

The method according to some embodiments of the present description can determine the first feeding speed according to the actual injection molding production condition, and ensure the normal operation of the injection molding machine production.

And 320, controlling the feeding pipe to feed materials to the injection molding machine at a first feeding speed. In some embodiments, step 320 may be performed by a controller.

In some embodiments, the controller may control the feed tube to feed the injection molding machine at a first feed rate. For example, the controller may control the first feed rate by controlling the power level of the transfer pump such that the feed line feeds the injection molding machine at a first feed rate (e.g., 50 grams/minute, 3 liters/hour).

According to the method provided by some embodiments of the specification, the injection molding machine is automatically fed by the feeding device, so that the labor is saved, and the injection molding production efficiency of the injection molding machine is improved.

Fig. 4 is an exemplary flow chart illustrating feeding an injection molding machine at a second feed rate according to some embodiments of the present disclosure. As shown in fig. 4, the process 400 includes the following steps:

and step 410, detecting the injection molding material in the container, and determining the material detection result of the injection molding material. In some embodiments, step 410 may be performed by a material detection unit.

The material detection result refers to a result obtained by analyzing the injection molding material after the injection molding material is detected under the current parameter setting of the injection molding machine. The current parameter settings of the injection molding machine may include, but are not limited to, injection temperature, injection pressure, mold temperature, etc. of the injection molding machine.

In some embodiments, the material detection results may include, but are not limited to, injection molding material flowability, viscosity, and the like. The material detection unit can carry out sampling inspection on the injection molding material in the container and determine the material detection result of the injection molding material. For example, the material detection unit (e.g., composition detector) can sample and detect the injection molding material in the container, and detect that the material is polyethylene, the injection temperature of the injection molding machine is 125 ℃, the injection pressure is 140 bar (bar), and the viscosity of the polyethylene is 95-110 Pa seconds at the mold temperature of 120 ℃.

And step 420, adjusting the first material consumption speed of the injection molding machine based on the material detection result to obtain a second material consumption speed. In some embodiments, step 420 may be performed by a controller.

The second material consumption speed refers to the amount of various injection molding materials produced by the injection molding machine in unit time after the injection molding machine is adjusted on the basis of the first material consumption speed based on the material detection result. For example, several phone shells were produced with a first polycarbonate depletion rate of 1500 g/min and a second polycarbonate depletion rate of 1620 g/min after adjustment.

In some embodiments, the controller may adjust the first depletion rate of the injection molding machine to obtain a second depletion rate. In some embodiments, the controller may determine an initial product performance based on the material detection and the first depletion rate; when the performance of the initial product is lower than the performance threshold, the controller can adjust the first material consumption speed to obtain a second material consumption speed.

The initial product performance refers to the product performance obtained by processing the injection molding material by the injection molding machine at the first material consumption speed. The product performance includes, but is not limited to, high hardness, impact resistance, corrosion resistance, etc. For example, the Rockwell hardness of the produced mobile phone shell is 68, and the density of the produced plastic box is 1.38-1.41 g/cm ³ 。

In some embodiments, the controller may determine the corresponding historical product property by querying the historical material detection result and the historical first material consumption rate stored in the database, where the historical material detection result and the historical first material consumption rate are the same as the current material detection result and the current first material consumption rate, and the historical product property is the current product property.

In some embodiments, the first depletion rate is adjusted to obtain the second depletion rate when the initial product performance is below the performance threshold.

The performance threshold refers to the lowest value that is required to achieve one or more properties of a qualified product. For example, the threshold for performance of the cell phone case is Rockwell hardness 62 and the threshold for performance of the plastic case is density 1.38 grams/cm ³ . In some embodiments, the performance threshold may be set based on historical data. Wherein the historical data may include performance parameters for the qualified product over a number of historical time periods. The controller may obtain the performance parameter with the lowest value as the performance threshold. For example, a threshold performance value for a batch of qualified plastic boxes is a density of 1.42 grams/cm ³ 1.39 g/cm ³ 1.43 g/cm ³ 1.38 g/cm ³ Then, the minimum value is 1.38 g/cm ³ As a performance threshold for plastic boxes.

In some embodiments, the controller may query the material consumption speed corresponding to the performance threshold stored in the database, where a difference between the material consumption speed and the current first material consumption speed is an adjustment value of the first material consumption speed, and the adjusted material consumption speed is the second material consumption speed. For example, a density of 1.38 g/cm is found ³ The material consumption speed of the plastic box is 160 g/min, the current first material consumption speed is 130 g/min, the adjustment value is 160-G/min, the second depletion rate is 160 g/min.

The method according to some embodiments of the present description avoids that the injection molding amount of the material required by the product is insufficient at the original feeding speed of the injection molding machine due to insufficient flowability, viscosity and the like of the material, so that the product quality does not meet the requirement, and therefore, the first material consumption speed is adjusted according to different sampling conditions of different materials, so that the method can be used for subsequent adjustment of the first feeding speed, ensure normal injection molding production, improve the product quality, and reduce the defective rate.

In some embodiments, the controller may obtain a plurality of candidate second material consumption speeds, and determine the second material consumption speed based on the product performance corresponding to the candidate second material consumption speeds.

The candidate second depletion speed is the depletion speed value used for determining the second depletion speed. E.g., 130 g/min, 123 g/min, etc. In some embodiments, the candidate second depletion rate may be determined by manually relying on historical experience. In some embodiments, the candidate second depletion rates may also be obtained from a database and/or a website.

The product performance refers to the corresponding product performance obtained by processing the injection molding material by the injection molding machine at the candidate second material consumption speed. For example, the plastic case has rockwell hardness of 78, 80, 81, etc.

In some embodiments, the controller may process the candidate second material consumption speed and the material detection result based on the first performance prediction model, and determine the product performance corresponding to the candidate second material consumption speed.

The first performance prediction model can analyze and process the input candidate second material consumption speed and the material detection result and output the product performance corresponding to the candidate second material consumption speed.

In some embodiments, the first performance prediction model may include, but is not limited to, a combination of one or more of a 3D Convolutional Neural network (3D CNN), a Decision Tree (DT), a Linear Regression (LR), and the like.

In some embodiments, for each candidate second material consumption speed, the candidate second material consumption speed and the material detection result may be used as inputs of the first performance prediction model, and the product performance corresponding to the candidate second material consumption speed may be used as an output of the first performance prediction model.

The parameters of the first performance prediction model may be obtained by training. In some embodiments, multiple sets of training samples may be obtained based on a large volume of injection molding production data, and each set of training samples may include multiple training data and labels corresponding to the training data. The training data may include the historical candidate second material consumption speed and the historical material detection result, and the label may be the product performance of a product produced based on the historical candidate second material consumption speed under the historical material detection result. For example, the controller may collect candidate second material consumption speeds and material detection results at multiple time points within a historical period of time (e.g., a day, a week, a month, etc.) as training data, and obtain a determination result (e.g., a determination result manually made according to actual product performance of the product) of the product produced based on the second material consumption speeds under the material detection results at the multiple time points.

In some embodiments, the initial first performance prediction model may be trained based on a plurality of labeled training samples, and parameters of the initial first performance prediction model may be updated through training so that a loss function of the model satisfies a preset condition. For example, the loss function converges, or the loss function value is smaller than a preset value. And completing model training when the loss function meets the preset condition to obtain a trained first performance prediction model.

In some embodiments, the controller may determine the second material consumption speed based on the product performance corresponding to each candidate second material consumption speed obtained by the first performance prediction model.

In some embodiments, the controller may select the corresponding candidate second material consumption speed as the second material consumption speed according to a preset product performance requirement. For example, the preset product performance requirement is that the plastic box with the highest hardness is selected, the product performance is rockwell hardness 82, 79, 83 and 78, and the controller may select a candidate second material consumption speed 1350 g/min corresponding to the rockwell hardness 83 as the second material consumption speed.

The method according to some embodiments of the present disclosure can further improve the product quality and reduce the defective rate by adjusting the second consumption rate according to the product performance.

And 430, adjusting the first feeding speed based on the second material consumption speed to obtain a second feeding speed of the feeding pipe. In some embodiments, step 430 may be performed by a controller.

The second feeding speed is the amount of the injection molding material which is fed to the injection molding machine in a unit time in the feeding pipe adjusted on the basis of the first feeding speed. For example, several phone shells were produced with a first feed rate of 700 g/min resin and a second feed rate of 720 g/min after adjustment.

In some embodiments, the controller may directly use the second depletion rate as the second feed rate. For example, if the second consumption rate is 700 g/min, the second feed rate is also 700 g/min.

And step 440, controlling the feeding pipe to feed the injection molding machine at a second feeding speed. In some embodiments, step 440 may be performed by a controller.

In some embodiments, the controller may control the feed tube to feed the injection molding machine at a second feed rate. For example, the controller may control the feeding speed to be adjusted to a second feeding speed (e.g., 100 g/min) by controlling the power of the delivery pump, so that the feeding pipe feeds the injection molding machine at the second feeding speed.

The method of some embodiments of the specification can adjust the feeding speed according to the actual condition of the material and the performance of the product, optimize the quality of the injection molding product and improve the injection molding production efficiency.

Fig. 5 is an exemplary flow chart illustrating feeding an injection molding machine at a third feed rate according to some embodiments of the present disclosure. In some embodiments, the process 500 may be performed by a controller. As shown in fig. 5, the process 500 includes the following steps:

and 510, acquiring a product detection result of the product produced by the injection molding machine, wherein the product detection result is determined by detecting the product through a product detection unit in the injection molding machine. In some embodiments, step 510 may be performed by the first pass unit.

The product detection result refers to a detection result capable of reflecting the quality of the injection molding product according to different requirement indexes. The product test results may include excellent, qualified, unqualified, and the like. The product detection content can comprise aging detection, bending detection, hardness detection, weight detection, image detection and the like, and correspondingly, the product detection method can comprise a combustion test method, a density test method, a thermal deformation test method and the like. For example, the actual finished product to be detected is slightly whitened compared with the standard sample, and the detection result of the product can be qualified; for another example, when the actual finished product to be detected has dents, cracks and deformation compared with the standard sample, the detection result of the product can show that the product is not qualified.

In some embodiments, the product detection result may be acquired by the first communication unit, and the product is detected and determined by a product detection unit in the injection molding machine.

The product detection unit refers to a unit capable of checking and verifying a product, wherein the injection molding machine may include a plurality of product detection units. The product detection unit detection content may include a ratio detection unit, a speed detection unit, a weight detection unit, an image detection unit, and the like.

In some embodiments, the product detection unit may detect the weight of the product produced by the injection molding machine to determine the product detection result. In some embodiments, the product detection result can be determined by comparing whether the weight of the product meets a preset weight requirement, and when the weight of the product meets the preset weight requirement, the product detection result is determined to be qualified; and when the preset weight requirement is not met, determining that the product detection result is unqualified. Correspondingly, the product detection unit may comprise a conveying pipe and a weighing machine. The conveying pipeline is used for obtaining an actual finished product produced by the injection molding machine; the weighing machine is used for weighing the actual finished product. For example, when a teapot product is produced, the weight of a standard sample of the teapot is 500g, and the preset weight range is 400g-500g, when the actual finished product weight of a certain injection-molded teapot to be detected is 450g, although the actual finished product weight does not meet the weight of the standard sample, the actual finished product weight meets the preset weight range, and therefore the product detection result of the product can be displayed to be qualified; when the weight of the actual finished product of the other injection molding teapot to be detected is 350g, the preset weight range is not met, and the product detection result of the product can be displayed to be unqualified. In some embodiments, a single product weight may be preset according to business requirements, and the finished product weight may be determined based on the single product weight. For example, in the production of teapot products, the finished weight of the teapot is determined according to the individual weights of the spout, the body, the lid and the handle.

Some embodiments of this description can confirm more conveniently, directly perceivedly whether the volume of actual finished product injection molding is enough through detecting the weight of actual finished product, practices thrift product detection cost.

In some embodiments, the product inspection unit may inspect an image of a product produced by the injection molding machine to determine a product inspection result. In some embodiments, the product detection result can be determined by comparing whether the image of the product meets the preset image requirement, and when the image meets the preset image requirement, the product detection result is determined to be qualified; and when the preset image requirement is not met, determining that the product detection result is unqualified. Correspondingly, the product detection unit may include a camera, wherein the camera is configured to acquire a product image. For example, when a teapot product is produced, the preset image of the teapot is required to be one spout and two teapots, and when the image of an actual finished product of a certain injection-molded teapot to be detected meets the preset image requirement, the product detection result of the product can be displayed to be qualified; when the image of the actual finished product of the other injection molding teapot to be detected is a spout and a handle, the requirement of the preset image is not met, and the product detection result of the product can be displayed as unqualified.

In some embodiments, image recognition may be performed on the product image to determine the product detection result. The image recognition may include image acquisition, image preprocessing, image feature extraction, image matching recognition, and the like.

In some embodiments, the product image may be processed based on the first image recognition model to determine a product detection result.

In some embodiments, the first image recognition model input is a product image; and outputting the first image recognition model as a product detection result. The first image recognition model can extract the image characteristics of the product, recognize the image characteristics, judge whether the image of the product is qualified or not and determine the detection result of the product. The product image features may include, among other things, product shape, product color, product size, etc.

In some embodiments, the first image recognition model may be a Convolutional Neural Networks (CNN) model.

In some embodiments, the first image recognition model may be acquired based on historical product image training. In some embodiments, the training module may use historical product images corresponding to the plurality of samples as training samples. The identification of the training sample can be a historical product detection result of a product corresponding to the historical product image. In some embodiments, the labels of the training samples may be obtained by manually identifying and labeling historical product image determinations. Specifically, a training sample with an identifier is input into an initial first image recognition model, parameters of the initial first image recognition model are updated through training, when the trained model meets a preset condition, the training is finished, and the trained first image recognition model is obtained.

Some embodiments of the present description detect the product image through the first image recognition model, so as to more conveniently and effectively determine whether the appearance of the product meets the requirements, and save the product detection cost.

In some embodiments, the product image and the standard sample image may be processed based on the second image recognition model to determine the product detection result. The standard sample image may be a standard image of a product set in advance.

In some embodiments, the second image recognition model may be a twin network model. Inputting a second image recognition model into a product image and a standard sample image; and outputting the second image recognition model as a product detection result. The second image recognition model can respectively extract product image features and standard sample image features of the product image and the standard sample image, compare the product image features with the standard sample image features, determine product detection vectors, and determine product detection results based on the product detection vectors. The product detection vector may be represented as (X, Y), wherein elements in the vector represent unqualified and qualified from left to right, respectively, and a specific value in the product detection vector may be represented as a probability value of a corresponding element. Based on the magnitude of the probability value, a product detection result may be determined. For example, the product detection vector output by the second image recognition model is (0.2, 0.8), where 0.2 may represent a non-qualification, 0.8 may represent a qualification, and it is known that the probability of qualification is 0.8, which is greater than the probability of non-qualification 0.2, so the final product detection result is a qualification.

In some embodiments, the output of the second image recognition model further includes a confidence level of the product detection result. The controller may directly take the probability values of the elements in the vector as the confidence levels of the corresponding product detection results. For example, the product detection vector output by the second image recognition model is (0.2, 0.8), and when the final product detection result is qualified, the confidence of the product detection result is 0.8.

In some embodiments, the second image recognition model may be trained based on historical product images and historical standard sample images. The historical product image includes historical product image features and the standard sample image includes historical standard sample image features. In some embodiments, the training module may use the historical product image features and the historical standard sample image features corresponding to the plurality of samples as training samples. The identification of the training sample may be historical product test results. In some embodiments, the labels of the training samples may be obtained in a manner that is manually labeled. In some embodiments, historical product detection results may be determined based on historical product image features and historical standard sample image features corresponding to the plurality of samples. Specifically, a training sample with an identifier is input into the initial second image recognition model, parameters of the initial second image recognition model are updated through training, when the trained model meets preset conditions, the training is finished, and the trained second image recognition model is obtained.

Some embodiments of the present description may compare the product image with the standard sample image through the second image recognition model, so as to determine whether the appearance of the real product meets the requirement more conveniently and efficiently.

And step 520, when the product detection result is unqualified, adjusting the material ratio of the initial product and the production speed of the initial product to obtain the material ratio of the target product and the production speed of the target product. In some embodiments, step 520 may be performed by a controller.

The material ratio of the target product refers to the ratio of each injection molding material in the product obtained after adjustment. The production speed of the target product is the production speed of the product in the injection molding machine after adjustment. For example, in the case of producing a plastic gear, the initial product material ratio may be 20% by weight and 40g of Polyoxymethylene (POM), 50% by weight and 100g of nylon (PA66), and 30% by weight and 60g of polyparaphthalein-p-phenylenediamine (PPA), the initial product production speed may be 300 pieces/hour, and when the product detection result of the plastic gear is failed, the initial product material ratio and the initial product production speed are adjusted to obtain a target product material ratio of 50% by weight and 40% by weight of nylon (PA66), and 10% by weight of polyparaphthalein-p-phenylenediamine (PPA), and the target product production speed may be 200 pieces/hour.

In some embodiments, the injection molding parameters may be adjusted according to the injection molding parameter adjustment value, that is, the material ratio of the initial product and the production speed of the initial product are correspondingly adjusted according to the product material ratio adjustment value and the product production speed adjustment value, so as to obtain the material ratio of the target product and the production speed of the target product.

The injection molding parameter adjustment value may refer to an adjustment value for adjusting an injection molding parameter, and may include a product material ratio adjustment value and a product production speed adjustment value. The product material ratio adjustment value may refer to an adjustment value for adjusting the initial product material ratio to the target product material ratio, and the product production speed adjustment value may refer to an adjustment value for adjusting the initial product production speed to the target product production speed. In some embodiments, the initial product material ratio and the initial product production speed may be adjusted according to a preset rule, so as to obtain a product material ratio adjustment value and a product production speed adjustment value. For example, when the product detection result is unqualified, the product material ratio adjustment value and/or the product production speed adjustment value can be determined according to a preset product qualification relation table. When only one of the material ratio adjustment value and the production speed adjustment value of the product is adjusted, the adjustment value of the other parameter may be represented by 0.

In some embodiments, the controller may obtain a plurality of sets of candidate product material proportioning adjustment values and candidate product production speed adjustment values; and aiming at each group of candidate product material ratio adjusting values and candidate product production speed adjusting values, determining the product performance of the product which is obtained by adjusting the injection molding parameters based on the group of candidate product material ratio adjusting values and the candidate product production speed adjusting values based on the injection molding parameters of the second performance prediction model, the candidate product material ratio adjusting values and the candidate product production speed adjusting values. In some embodiments, a target product material ratio adjustment value and a target product production speed adjustment value are determined based on the candidate product material ratio adjustment values of each group and the product performance and preset product performance requirements corresponding to the candidate product production speed adjustment values; and determining the material ratio of the target product and the production speed of the target product based on the material ratio of the initial product, the production speed of the initial product, the material ratio adjustment value of the target product and the production speed adjustment value of the target product. Product properties include, but are not limited to, impact resistance, corrosion resistance, etc. of the product. The preset product performance requirement may refer to a preset product performance requirement. For example, the predetermined product performance requirement may be the strongest corrosion resistance.

It should be understood that after the initial product material ratio and the initial product production speed are adjusted based on each set of candidate product material ratio adjustment values and candidate product production speed adjustment values, the product detection results of the products produced by the injection molding machine are all qualified. Product performance can be related to product material mix and/or product production speed of the product. For example, due to insufficient material proportion of the product, the product performance may only have impact resistance under the condition that the production speed of the product is not changed; for another example, due to the slow production speed of the product, the product may have only corrosion resistance without changing the material ratio of the product. Therefore, the controller can determine the product performance of each group of candidate product material ratio adjustment values and candidate product production speed adjustment values, so that the target product material ratio adjustment values and the target product production speed adjustment values can be determined as required from the plurality of groups of candidate product material ratio adjustment values and candidate product production speed adjustment values.

As shown in FIG. 6, one of the injection molding parameter 610 and the candidate injection molding parameter adjustment value 620 may be input into a second performance prediction model 630, and the output of the second performance prediction model 630 is the product performance 640 corresponding to the candidate injection molding parameter adjustment value. For example, the first candidate product material ratio adjustment value, the first candidate product production speed adjustment value, the initial product material ratio, and the initial product production speed may be input into a second performance prediction model, and the output of the second performance prediction model is the first product performance.

For the product performance 640 and the preset product performance requirement 670 corresponding to each set of candidate injection molding parameter adjustment values, a target product material ratio adjustment value and a target product production speed adjustment value 650 can be determined. Based on the injection molding parameter 610, the target product material ratio adjustment value and the target product production speed adjustment value 650, the target product material ratio and the target product production speed 660 can be determined.

The candidate injection molding parameter adjustment values 620 may include multiple sets of injection molding parameter adjustment values. For example, the candidate injection parameter adjustment values 620 may include a first candidate product material ratio adjustment value and a first candidate product production speed adjustment value, a second candidate product material ratio adjustment value and a second candidate product production speed adjustment value … nth candidate product material ratio adjustment value and nth candidate product production speed adjustment value.

In some embodiments, the second performance prediction model may include, but is not limited to, a deep learning model, a deep belief network, and the like, or a combination thereof.

In some embodiments, the second performance prediction model may be trained based on historical injection molding parameters and historical injection molding parameter adjustment values. Historical injection molding parameters and historical injection molding parameter adjustment values corresponding to the plurality of samples can be used as training samples. The identification of the training sample can be the historical product performance of a product obtained by the injection molding machine based on the historical injection molding parameter adjustment value. A plurality of training samples with identifications can be input into the initial second performance prediction model, parameters of the initial second performance prediction model are updated through training, and when the trained model meets preset conditions, the training is finished to obtain the trained second performance prediction model.

In some embodiments of the present description, a best product performance is determined according to different candidate adjustment values through a second performance prediction model, and a target product material ratio adjustment value and a target product production speed adjustment value corresponding to preset product performance requirements are selected. Compared with a manual adjustment value determining mode, the efficiency can be better improved for different products, and the production automation is improved.

At step 530, a third material consumption rate of the injection molding machine is determined based on the target product material ratio and the target product production rate. In some embodiments, step 530 may be performed by a controller.

The third material consumption speed refers to the material consumption speed of the injection molding machine for each injection molding material, which is obtained by adjusting the injection molding parameters based on the material ratio of the target product and the production speed of the target product. The third depletion rate may be determined based on the target product material mix and the target product production rate. For example, the initial product material ratio of polyoxymethylene is 20 wt% and 40g, the initial product production rate is 200 pieces/hour, and correspondingly, the first consumption rate may be 8000 g/hour. And determining that the product is unqualified after detection, wherein the weight of the polyformaldehyde accounts for 30% and 60g in the material ratio of the target product, the production speed of the target product is 150 pieces/hour, and correspondingly, the third material consumption speed can be 9000 g/hour.

And 540, determining a third feeding speed of the feeding pipe based on the third material consumption speed. In some embodiments, step 540 may be performed by a controller.

The third feeding speed is the feeding speed obtained by adjusting the first feeding speed of the feeding pipe in the feeding device based on the third material consumption speed.

In some embodiments, the third depletion rate may be determined directly as the third feed rate. For example, the third consumption rate of polyoxymethylene in the injection molding machine may be 200 tons/hour, and correspondingly, the third feeding rate of the feeding pipe for feeding polyoxymethylene may be 200 tons/hour.

In some embodiments, the third feed rate may also be determined based on preset rules. For example, the third feed rate is a third consumption rate adjustment value, wherein the adjustment value can be predetermined.

And step 550, controlling the feeding pipe to feed the injection molding machine at a third feeding speed. In some embodiments, step 550 may be performed by a controller.

Some embodiments of the present description may obtain a material ratio of a target product and a production speed of the target product by obtaining a product detection result, thereby determining a third material consumption speed of the injection molding machine, and may implement continuous automatic feeding production, save labor and time, and improve production efficiency.

In some embodiments, when the feeding speed of the feeding pipe needs to be adjusted based on the material detection result and the product detection result, the second feeding speed and the third feeding speed may be fused to obtain a fifth feeding speed. Wherein the fifth feed rate may be determined based on equation (1):

wherein S is ₅ At a fifth feed rate, S ₂ At a second feed rate, S ₃ At the third feed rate, R ₁ As confidence of material detection result, R ₂ And the confidence of the product detection result. For example, if the controller determines that the second feeding speed of polyoxymethylene is 30 tons/hr, the confidence of the material detection unit is 0.6, the third feeding speed of polyoxymethylene is 40 tons/hr, and the confidence of the product detection unit is 0.9, then this may be the caseTo determine a fifth feed rate of 30 × 0.4+40 × 0.6-36 tons/hour.

In some embodiments, the controller may control the feed tube to feed the injection molding machine at a fifth feed speed.

Fig. 7 is an exemplary flow chart illustrating feeding an injection molding machine at a fourth feed speed according to some embodiments of the present description. In some embodiments, the flow 700 may be performed by a controller. As shown in fig. 7, the process 700 includes the following steps:

step 710, obtaining a volume sensing result of a charging barrel of the injection molding machine. In some embodiments, step 710 may be performed by the second communication unit.

The charging bucket is a structure used for containing injection molding materials in the injection molding machine. Each injection molding machine may include a plurality of charging barrels.

The volume sensing result is a result capable of reflecting the volume of the injection molding material in the charging barrel of the injection molding machine. For example, the volume sensing result may be "sufficient", "standard", "insufficient", etc. In some embodiments, the volume sensing result may be a specific value. For example, the volume of the molding material in the charging barrel of the injection molding machine is 50m ³ The total volume of the charging bucket is 100m ³ The volume sensing result can be expressed as 0.5, etc.

In some embodiments, the volume sensing result can be obtained by a volume sensor, wherein the volume sensor refers to a device capable of converting the volume of the injection molding material in the charging barrel into a corresponding output in other forms. For example, the volume sensor may be a radar sensor, an electromagnetic sensor, a pressure sensor, or the like. In some embodiments, the volume sensing result may be transmitted to the feeding device via a second communication unit.

And 720, judging whether to adjust the first feeding speed or not based on the volume sensing result. In some embodiments, step 720 may be performed by a controller.

In some embodiments, whether the first feeding speed needs to be adjusted may be determined based on a magnitude relationship between the volume sensing result and a preset threshold. The preset threshold value can refer to the preset ratio of the volume of the injection molding material in the charging barrel of the injection molding machine to the total volume of the charging barrel. In some embodiments, the preset threshold may include a first threshold, a second threshold, a third threshold, and the like.

The first threshold may be a maximum value of a ratio of a volume of injection material in a barrel of the injection molding machine to a total volume of the barrel. In some embodiments, when the volume sensing result is greater than or equal to the first threshold value, indicating that the injection molding machine includes a large amount of injection molding material in the barrel, the injection molding machine feeder adjusts the first feed rate to prevent the injection molding material from overflowing the barrel.

The second threshold may be a median value of the ratio of the volume of injection material in the barrel of the injection molding machine to the total volume of the barrel. The second threshold is less than the first threshold. When the volume sensing result is smaller than the first threshold value and larger than or equal to the second threshold value, the first feeding speed is over fast, the consumption speed of the injection molding material is smaller than the feeding speed, if the injection molding material is fed at the first feeding speed for a long time, the injection molding material is gradually accumulated in the charging barrel of the injection molding machine, and the first consumption speed needs to be adjusted.

The third threshold may be a minimum value of a ratio of a volume of injection material in a barrel of the injection molding machine to a total volume of the barrel. The third threshold is less than the second threshold. When the volume induction result is smaller than the second threshold value and larger than or equal to the third threshold value, the first feeding speed is normal, the consumption speed of the injection molding material is approximately equal to the feeding speed, and the first consumption speed is not required to be adjusted. When the volume sensing result is smaller than the third threshold value, the first feeding speed is characterized to be too low, the consumption speed of the injection molding material is higher than the feeding speed, the injection molding material in the charging barrel of the molding machine is not enough to meet the production requirement of the injection molding material for a long time, and the first consumption speed needs to be adjusted.

And 730, when the first feeding speed needs to be adjusted, adjusting the first feeding speed based on the volume sensing result to obtain a fourth feeding speed. In some embodiments, the flow 730 may be performed by a controller.

The fourth feeding speed is the feeding speed obtained by adjusting the first feeding speed of the feeding pipe based on the volume induction result.

In some embodiments, when the volume sensing result is greater than or equal to the first threshold, the feeding may be stopped, and the four feeding speeds are determined to be 0; when the volume induction result is smaller than the first threshold and larger than or equal to the second threshold, the first feeding speed can be reduced to obtain a fourth feeding speed; when the volume induction result is smaller than the second threshold value and larger than or equal to the third threshold value, the first feeding speed is not adjusted; when the volume sensing result is smaller than the third threshold, the first feeding speed can be increased to obtain a fourth feeding speed.

In some embodiments, the fourth feed speed may be determined by a preset rule. For example, the fourth feed speed may be determined based on equation (2):

S ₄ ＝S ₁ *T (2)

wherein S is ₄ At a fourth feed speed, S ₁ And T is an adjusting coefficient determined according to the volume induction result and a preset threshold value.

Illustratively, the first threshold value may be set to 0.8, the second threshold value may be set to 0.6, and the third threshold value may be set to 0.4, and if the volume induction result of a certain cartridge is greater than 0.8, the adjustment coefficient may be determined to be 0, and if the volume induction result of a certain cartridge is between 0.6 and 0.8, the adjustment coefficient may be determined to be 0.8; if the volume induction result is between 0.4 and 0.6, the adjustment coefficient can be determined to be 1, and the adjustment coefficient can be determined to be 1.2.

In some embodiments, the magnitude by which the first feed speed needs to be decreased may be determined based on the first ratio when the volume sensing result is less than the first threshold and greater than or equal to the second threshold. The first ratio is a ratio of a consumption speed of the injection molding material to a conveying speed which is set in advance according to production requirements. In some embodiments, the fourth feed rate may be determined such that the first ratio is less than (fourth feed rate-first depletion rate)/first depletion rate.

It should be understood that the fourth feed rate has a value not less than the first consumption rate to avoid the injection material in the cartridge being unable to support the injection molding machine for production for a long period of time.

For example, when the volume sensing result is less than the first threshold and greater than or equal to the second threshold, the first feeding speed is 30 tons/hour, the first material consumption speed is 20 tons/hour, and according to the preset first ratio 0.3, the fourth feeding speed is determined to have a value ranging from 24 tons/hour to 20 tons/hour.

In some embodiments, the magnitude of the increase in the first feed speed may be determined based on the first depletion speed when the volume sensing result is less than the third threshold.

In some embodiments, the magnitude by which the first feed speed needs to be increased may be determined based on the second ratio. The second ratio is a ratio of the consumption speed to the conveying speed of the other injection molding material which is preset according to the production requirement. In some embodiments, the fourth feed speed may be determined such that the second ratio is greater than (fourth feed speed-first feed speed)/first depletion speed.

Illustratively, when the volume sensing result is smaller than the third threshold, the first feeding speed is 15 tons/h, the first material consumption speed is 20 tons/h, and the preset second ratio is 0.5, the value range of the fourth feeding speed is determined to be 25 tons/h-20 tons/h.

In some embodiments of the present disclosure, by setting the first ratio and the second ratio, an excessive or small amount of injection molding material in a cartridge of an injection molding machine can be avoided, and production stability can be maintained.

In some embodiments, when the volume sensing result is less than the first threshold and greater than or equal to the second threshold, the material conveying process may be controlled based on a proportional-integral-derivative (PID) control method to determine the magnitude of decreasing the first feeding speed. The PID control method is a method that can make the current first feeding speed accurately reach the set first feeding speed and finally keep stable, wherein, the PID controller can calculate the amplitude by using the proportional (P) control, the integral (I) control and the derivative (D) control according to the error between the current first feeding speed and the fourth feeding speed, and dynamically control the adjustment of the fourth feeding speed.

In some embodiments, the parameter values of the PID control method can be obtained by simulation tests of actual production conditions. In some embodiments, a simulation test may be performed on a plurality of sets of parameter values of the PID control method, and the parameter values may be adjusted by simulating the effect of the curve to determine the final parameter values of the PID control method. Wherein the predetermined PID parameter values may be based on the actual production run or obtained in advance. For example, when the current first feeding speed is 30 tons/hour, the PID parameter values are selected to be 0.5, 0.3, and 0.2 respectively to observe the effect of the simulation curve, if the set PID parameter values are not satisfied, the set PID parameter values are adjusted, and then whether the adjusted parameter values satisfy the effect is observed until the effect is satisfied (if the final PID parameter is determined to be 0.9, 0.3, and 0.2).

In some embodiments, the PID controller can be a material PID controller, and the output of the material can be adjusted by the material PID controller, i.e., the first feed rate of the material can be adjusted by the material PID controller. The material PID controller can adjust the first feeding speed and determine the fourth feeding speed through preset PID parameter values.

In some embodiments, when the volume sensing result is less than the third threshold, the material conveying process may also be controlled based on a PID control method to determine the magnitude of the increase in the first feeding speed. For a detailed description of the PID control method, reference is made to the above description, which is not repeated herein.

Some embodiments of this specification can reduce or raise the feeding speed of the injection molding material dynamically through the relationship between the volume sensing result and the preset threshold value, ensure the normal operation of production, improve the production efficiency remarkably, and save manpower and material resources.

And step 740, controlling the feeding pipe to feed the injection molding machine at a fourth feeding speed. In some embodiments, step 740 may be performed by a controller.

Some embodiments of the present description determine whether to adjust the first feeding speed by obtaining the volume sensing result, thereby determining the fourth feeding speed of the injection molding machine, and thus, continuous automatic feeding production can be realized, and production efficiency can be improved.

The present specification also provides a computer-readable storage medium storing computer instructions, wherein when the computer instructions in the storage medium are read by a computer, the computer executes the method for operating the feeding device of the injection molding machine according to any one of the embodiments of the present specification.

It should be noted that the above description of the respective flows is only for illustration and description, and does not limit the applicable scope of the present specification. Various modifications and changes to the procedures described herein will be apparent to those skilled in the art in light of the disclosure. However, such modifications and variations are intended to be within the scope of the present description.

Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.

Also, the description uses specific words to describe embodiments of the description. Reference throughout this specification to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.

Additionally, the order in which the elements and sequences of the process are recited in the specification, the use of alphanumeric characters, or other designations, is not intended to limit the order in which the processes and methods of the specification occur, unless otherwise specified in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it is to be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware devices, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the present specification, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to imply that more features than are expressly recited in a claim. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Numerals describing the number of components, attributes, etc. are used in some embodiments, it being understood that such numerals used in the description of the embodiments are modified in some instances by the use of the modifier "about", "approximately" or "substantially". Unless otherwise indicated, "about", "approximately" or "substantially" indicates that the number allows a variation of ± 20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximations that may vary depending upon the desired properties of the individual embodiments. In some embodiments, the numerical parameter should take into account the specified significant digits and employ a general digit preserving approach. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the range are approximations, in the specific examples, such numerical values are set forth as precisely as possible within the scope of the application.

For each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., cited in this specification, the entire contents of each are hereby incorporated by reference into this specification. Except where the application history document does not conform to or conflict with the contents of the present specification, it is to be understood that the application history document, as used herein in the present specification or appended claims, is intended to define the broadest scope of the present specification (whether presently or later in the specification) rather than the broadest scope of the present specification. It is to be understood that the descriptions, definitions and/or uses of terms in the accompanying materials of this specification shall control if they are inconsistent or contrary to the descriptions and/or uses of terms in this specification.

Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims

1. A feeder device for an injection molding machine, the feeder device comprising:

the container is used for containing injection molding materials;

the feeding pipe is used for conveying the injection molding material in the container to an injection molding machine;

a controller to:

determining a first feeding speed of the feeding pipe for feeding the injection molding machine; and

and controlling the feeding pipe to feed the injection molding machine at the first feeding speed.

2. The feeder apparatus of claim 1, further comprising:

the injection molding machine comprises a first communication unit, a second communication unit and a control unit, wherein the first communication unit is used for acquiring injection molding parameters of the injection molding machine, and the injection molding parameters comprise an initial product material ratio and an initial product production speed;

the controller is further configured to:

determining a first material consumption speed of the injection molding machine based on the initial product material ratio and the initial product production speed; and

determining the first feed rate based on the first depletion rate.

3. The feeder apparatus of claim 2, further comprising:

the material detection unit is used for detecting the injection molding material in the container and determining the material detection result of the injection molding material;

the controller is further configured to:

adjusting the first material consumption speed of the injection molding machine based on the material detection result to obtain a second material consumption speed;

adjusting the first feeding speed based on the second material consumption speed to obtain a second feeding speed of the feeding pipe; and

and controlling the feeding pipe to feed the injection molding machine at the second feeding speed.

4. The feeder apparatus of claim 2, wherein the first communication unit is further configured to:

obtaining a product detection result of a product produced by the injection molding machine, wherein the product detection result is determined by detecting the product through a product detection unit in the injection molding machine;

the controller is further configured to:

when the product detection result is unqualified, adjusting the material ratio of the initial product and the production speed of the initial product to obtain the material ratio of a target product and the production speed of the target product;

determining a third material consumption speed of the injection molding machine based on the target product material ratio and the target product production speed;

determining a third feed speed of the feed tube based on the third depletion speed; and

and controlling the feeding pipe to feed the injection molding machine at the third feeding speed.

5. The feeder apparatus of claim 1, further comprising:

the second communication unit is used for acquiring a volume sensing result of a charging barrel of the injection molding machine;

the controller is further configured to:

judging whether the first feeding speed needs to be adjusted or not based on the volume sensing result;

when the first feeding speed needs to be adjusted, adjusting the first feeding speed based on the volume sensing result to obtain a fourth feeding speed; and

and controlling the feeding pipe to feed the injection molding machine at the fourth feeding speed.

6. An operation method of a feeding device of an injection molding machine, which is characterized in that the feeding device comprises a container, a feeding pipe and a controller, and the method comprises the following steps:

7. The method of claim 6, wherein said controlling said feed tube to feed said injection molding machine at said first feed rate comprises:

acquiring injection molding parameters of the injection molding machine, wherein the injection molding parameters comprise an initial product material ratio and an initial product production speed;

determining the first feed rate based on the first depletion rate.

8. The method of claim 7, further comprising:

detecting the injection molding material in the container, and determining a material detection result of the injection molding material;

9. The method of claim 7, further comprising:

10. A computer-readable storage medium storing computer instructions which, when read by a computer, cause the computer to perform the method of operating the feeder apparatus of an injection molding machine according to any one of claims 6 to 9.