CN113110362A - Injection molding equipment state monitoring system based on industry 4.0 - Google Patents
Injection molding equipment state monitoring system based on industry 4.0 Download PDFInfo
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- 238000001746 injection moulding Methods 0.000 title claims abstract description 151
- 238000012544 monitoring process Methods 0.000 title claims abstract description 20
- 238000012423 maintenance Methods 0.000 claims abstract description 96
- 238000004519 manufacturing process Methods 0.000 claims abstract description 16
- 238000003745 diagnosis Methods 0.000 claims abstract description 15
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- 239000002994 raw material Substances 0.000 claims description 73
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4185—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by the network communication
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- G—PHYSICS
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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Abstract
The invention discloses an industrial 4.0-based injection molding equipment state monitoring system, which relates to the technical field of injection molding machine production and comprises a monitoring center, an information input module, a data acquisition module, a data analysis module, a logistics distribution module, a fault diagnosis module, a loss estimation module, a maintenance module and an information push module; by arranging the fault diagnosis module, when the service life of the injection molding equipment or the service life of a mold reaches a system preset value, early warning information can be automatically sent out, and a maintenance task list is generated, so that the condition that batch finished products are poor after the injection molding equipment breaks down is avoided; through setting up the failure diagnosis module to make in the finished product of production, unqualified finished product's quantity exceeds standard, can automatic investigation lead to the reason that the unqualified quantity of finished product exceeds standard, and generate the maintenance task list, thereby can help the maintenance personal to solve the problem fast.
Description
Technical Field
The invention belongs to the technical field of injection molding machine production, and particularly relates to an industrial 4.0-based injection molding equipment state monitoring system.
Background
The industry is the division made based on different stages of industrial development. According to the current consensus, the industry 1.0 is a steam engine era, the industry 2.0 is an electrification era, the industry 3.0 is an information era, and the industry 4.0 is an era of promoting industrial transformation by using an information technology, namely, an intelligent era.
The patent document with the publication number of CN206048736U discloses a monitoring system for injection molding equipment, injection molding equipment includes material loading machine, injection molding machine and mould temperature machine, the material loading machine with the injection molding machine is connected, and for the injection molding machine provides the raw materials of moulding plastics, be connected with the mould on the injection molding machine, the mould temperature machine is used for controlling the temperature of mould, wherein, monitoring system includes a control panel, the control panel can monitor the behavior of material loading machine, injection molding machine and mould temperature machine simultaneously. In the application, the running condition of the whole injection molding equipment is uniformly monitored by the monitoring panel, so that centralized viewing and management are facilitated, and a better monitoring effect is achieved; simultaneously, the setting of pressure display element of intaking can in time remind the user to handle the incrustation scale in the mould temperature controller, has ensured that the control by temperature change circulating water of mould temperature controller moves under reasonable pressure and flow.
In the prior art, the running state of the injection molding equipment still needs to be checked manually, and the running state cannot be found in time when the injection molding equipment is abnormal, so that batch unqualified products are easily caused; in order to solve the above problems, an industrial 4.0-based injection molding equipment status monitoring system is provided.
Disclosure of Invention
The invention aims to provide an industrial 4.0-based injection molding equipment state monitoring system.
The technical problem to be solved by the invention is as follows: 1. how to automatically monitor whether the injection molding equipment is abnormal or not through the process production information of the injection molding equipment; 2. how to quickly search the reason when the injection molding equipment fails or the quantity of unqualified finished products exceeds the standard.
The purpose of the invention can be realized by the following technical scheme: an injection molding equipment state monitoring system based on industry 4.0 comprises a monitoring center, an information input module, a data acquisition module, a data analysis module, a logistics distribution module, a fault diagnosis module, a loss estimation module, a maintenance module and an information push module;
the fault diagnosis module is used for diagnosing the fault reason of the injection molding equipment when the injection molding equipment has faults, and the specific diagnosis process comprises the following steps:
step G1: when the injection molding equipment is marked as suspected fault equipment, acquiring a mould loss coefficient MSX, when the MSX is not less than MS0 and not more than MS1, indicating that the mould is in an early warning state, sending mould loss early warning information to a monitoring center, and simultaneously marking the mould as a primary suspected fault point; when MSX is larger than MS1, judging that the mold is in an overload state, sending mold overload state early warning information to a monitoring center, and marking the mold as a secondary suspected fault point; when the mould loss coefficient MSX is less than MS0, the mould is in a normal state, and then the next step is carried out;
step G2: when the mould is in a normal state, acquiring the initial weight CZ of each raw materialiAnd the remaining weight SZiTo obtain the used mass YZ of each raw materiali，YZi＝CZi-SZi(ii) a By the formula
Obtaining the ratio value ZB of each raw materiali(ii) a The obtained ratio value ZB of each raw materialiMatching with the raw material ratio required by the model of the product being produced;
step G3: when the deviation value of the ratio of certain raw materials to the raw material ratio required by the model of the product being produced is larger than PiIf so, marking the raw materials as fault sources; and determines that the cause of the failure of the injection molding apparatus is caused by the source of the failure.
Further, the information input module is used for inputting injection molding equipment information and personnel information, and sending the injection molding equipment information and the personnel information to the monitoring center for storage, wherein the injection molding equipment information comprises an injection molding equipment number, an injection molding equipment name, time for the injection molding equipment to start to be put into use and a specific position of the injection molding equipment; the personnel information comprises names, sexes, working ages, departments to which the personnel belong, positions and mobile phone numbers authenticated by real names;
further, the data acquisition module comprises a raw material information acquisition unit, an equipment information acquisition unit and a finished product information acquisition unit, and is used for acquiring the production information of the injection molding equipment, and the specific acquisition process comprises the following steps:
step S1: the method comprises the steps of obtaining a product model of injection molding equipment through a raw material information acquisition unit, obtaining the type and proportion of raw materials required by the product model, numbering each raw material, sequencing each raw material from large to small according to the occupied proportion, and marking each raw material as i, wherein i is 1,2, … …, n is an integer;
step S2: acquiring the initial weight of each raw material in the injection molding equipment through a raw material information acquisition unit, and marking the initial weight of each raw material as CZi(ii) a The remaining weight of each material in the injection molding apparatus is obtained and labeled as SZi；
Step S3: the method comprises the steps that starting time of the injection molding equipment is obtained through an equipment information acquisition unit, running time of the injection molding equipment is recorded, the starting time of the injection molding equipment is marked as KS, the total running time of the injection molding equipment is marked as KT, and the starting time and the total running time of the injection molding equipment are sent to a monitoring center;
step S4: acquiring the mold use duration of the injection molding equipment and the number of assembly products produced by the mold through an equipment information acquisition unit, marking the mold use duration as MT, and marking the number of the assembly products produced by the mold as ZS;
step S5: acquiring the quantity of qualified finished products and the quantity of unqualified finished products through a finished product information acquisition unit, and respectively marking the qualified finished products and the unqualified finished products as YS and NS;
step S6: and sending the data acquired in the steps S1-S5 to a data analysis module in real time.
Further, the data analysis module is used for analyzing the production information of the injection molding equipment, and the specific analysis process comprises the following steps:
step F1: by the formula
Obtaining consumption coefficient PX of each raw materialiWhen PX isiSatisfy PXiIf the content of the raw materials is more than 0, indicating that the raw materials are sufficient, otherwise indicating that the content of the raw materials is insufficient, marking the raw materials with insufficient content, sending early warning information to a logistics distribution module, and recording the moment YT of sending the early warning information; wherein a is a system preset consumption threshold value and a is more than 0;
step F2: when the injection molding equipment stops operating, recording the time t1 when the injection molding equipment stops operating, and recording the time t2 when the injection molding equipment starts operating;
step F3: when T1-YT is less than or equal to T0 and T2-T1 is less than or equal to T1, judging the suspended operation of the injection molding equipment as normal suspension; when T1-YT is more than T1, the suspended operation of the injection molding equipment is judged to be abnormal suspension, then a suspension event is generated, and the generated suspension event is sent to a monitoring center, wherein the content of the suspension event comprises a suspended injection molding equipment number, a suspension starting time, a suspension ending time, a suspension reason, a responsibility department and a responsibility department person, T0 is system preset logistics response time, and T0 is more than 0; t1 is the preset feeding time of the system, and T1 is more than 0;
step F4: by the formula
Obtaining a mould loss coefficient MSX, and when the mould loss coefficient MSX is less than MS0, indicating that the mould is in a normal state; when MSX is not less than MS0 and not more than MS1, the mold is in an early warning state, mold loss early warning information is sent to a monitoring center, when MSX is more than MS1, the mold is judged to be in an overload state, the mold overload state early warning information is sent to the monitoring center, the injection molding equipment is forcibly stopped, and a maintenance task list is generated, wherein the maintenance task list comprises the number of the injection molding equipment, the fault reason, the position of the injection molding equipment and the predicted time required for completing maintenance; sending a maintenance task list to a maintenance module, wherein M0 and Z0 are the theoretical use duration and the theoretical production times of the injection molding equipment respectively, MS0 and MS1 preset loss thresholds for the system,and MS0 is less than MS 1;
step F5: by the formula
Obtaining a finished product rejection coefficient GF, judging that the yield of unqualified finished products of the injection molding equipment exceeds the standard when GF is more than 0, marking the injection molding equipment as suspected fault equipment, sending information of the suspected fault equipment to a monitoring center, and generating an overhaul task list, wherein the overhaul task list comprises the number of the injection molding equipment, the fault reason, the position of the injection molding equipment and the expected time required for completing maintenance; and sending the maintenance task list to a maintenance module, wherein beta is a system correction coefficient, G0 is a system preset unqualified product standard exceeding rate, Ts is a system preset acquisition time period, and TN is the number of unqualified products in the system preset acquisition time period.
Further, when receiving the early warning information of insufficient raw material content, the logistics distribution module responds to the received early warning information, and the early warning information includes the serial number of the injection molding equipment with insufficient raw material, the position of the injection molding equipment, the name of the raw material to be distributed and the content of the raw material.
Further, the loss estimation module is used for estimating theoretical loss caused by the injection molding equipment, and the specific estimation process comprises the following steps:
step D1: acquiring the time spent by each injection molding device for producing a single finished product, and marking the time as DJT; acquiring the cost required by each single finished product, and marking the cost as DJC;
step D2: by the formula
And obtaining a production theoretical loss value SG, wherein ZT is total downtime of the injection molding equipment, theta is a system correction coefficient, and theta is larger than 0.
Further, the maintenance module is used for distributing a maintenance task list or a maintenance task list, and the specific distribution mode comprises the following steps:
step W1: acquiring all maintenance task lists and maintenance task lists, wherein the maintenance task lists have priorities;
step W2: acquiring information of maintenance personnel who attendance on the day, marking the state of the maintenance personnel who are performing maintenance work as working, and marking the state of the maintenance personnel who are not performing maintenance work as waiting;
step W3: preferentially distributing a maintenance task list or a maintenance task list to maintenance personnel in a waiting state; when a plurality of maintenance personnel in the waiting state exist, the maintenance personnel in the waiting state with the longest time are preferentially allocated;
step W4: when all maintenance personnel are in a working state, acquiring the information of the maintenance personnel who are executing the maintenance task list, and distributing the maintenance task list to the maintenance personnel who are executing the maintenance task list;
step W5: when all maintenance personnel execute the maintenance task list, acquiring the predicted residual completion time of each maintenance task list, and distributing the maintenance task list to the maintenance personnel with the shortest predicted residual completion time;
step W6: and sending the maintenance task list or the maintenance task list information to a mobile phone of a maintenance worker through an information pushing module.
The invention has the beneficial effects that: 1. by arranging the fault diagnosis module, when the service life of the injection molding equipment or the service life of a mold reaches a system preset value, early warning information can be automatically sent out, and a maintenance task list is generated, so that the condition that batch finished products are poor after the injection molding equipment breaks down is avoided;
2. through setting up the failure diagnosis module to make in the finished product of production, unqualified finished product's quantity exceeds standard, can automatic investigation lead to the reason that the unqualified quantity of finished product exceeds standard, and generate the maintenance task list, thereby can help the maintenance personal to solve the problem fast.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic block diagram of an industrial 4.0 based injection molding apparatus condition monitoring system.
Detailed Description
As shown in fig. 1, an injection molding equipment state monitoring system based on industry 4.0 includes a monitoring center, an information input module, a data acquisition module, a data analysis module, a logistics distribution module, a fault diagnosis module, a loss estimation module, a maintenance module, and an information push module;
the information input module is used for inputting injection molding equipment information and personnel information, and sending the injection molding equipment information and the personnel information to the monitoring center for storage, wherein the injection molding equipment information comprises an injection molding equipment number, an injection molding equipment name, the time for the injection molding equipment to start to be put into use and the specific position of the injection molding equipment; the personnel information comprises names, sexes, working ages, departments to which the personnel belong, positions and mobile phone numbers authenticated by real names;
the data acquisition module comprises a raw material information acquisition unit, an equipment information acquisition unit and a finished product information acquisition unit and is used for acquiring the production information of the injection molding equipment, and the specific acquisition process comprises the following steps:
step S1: the method comprises the steps of obtaining a product model of injection molding equipment through a raw material information acquisition unit, obtaining the type and proportion of raw materials required by the product model, numbering each raw material, sequencing each raw material from large to small according to the occupied proportion, and marking each raw material as i, wherein i is 1,2, … …, n is an integer;
step S2: acquiring the initial weight of each raw material in the injection molding equipment through a raw material information acquisition unit, and marking the initial weight of each raw material as CZi(ii) a The remaining weight of each material in the injection molding apparatus is obtained and labeled as SZi；
Step S3: the method comprises the steps that starting time of the injection molding equipment is obtained through an equipment information acquisition unit, running time of the injection molding equipment is recorded, the starting time of the injection molding equipment is marked as KS, the total running time of the injection molding equipment is marked as KT, and the starting time and the total running time of the injection molding equipment are sent to a monitoring center;
step S4: acquiring the mold use duration of the injection molding equipment and the number of assembly products produced by the mold through an equipment information acquisition unit, marking the mold use duration as MT, and marking the number of the assembly products produced by the mold as ZS;
step S5: acquiring the quantity of qualified finished products and the quantity of unqualified finished products through a finished product information acquisition unit, and respectively marking the qualified finished products and the unqualified finished products as YS and NS;
step S6: and sending the data acquired in the steps S1-S5 to a data analysis module in real time.
The data analysis module is used for analyzing the production information of the injection molding equipment, and the specific analysis process comprises the following steps:
step F1: by the formula
Obtaining consumption coefficient PX of each raw materialiWhen PX isiSatisfy PXiIf the content of the raw materials is more than 0, indicating that the raw materials are sufficient, otherwise indicating that the content of the raw materials is insufficient, marking the raw materials with insufficient content, sending early warning information to a logistics distribution module, and recording the moment YT of sending the early warning information; wherein a is a system preset consumption threshold value and a is more than 0;
step F2: when the injection molding equipment stops operating, recording the time t1 when the injection molding equipment stops operating, and recording the time t2 when the injection molding equipment starts operating;
step F3: when T1-YT is less than or equal to T0 and T2-T1 is less than or equal to T1, judging the suspended operation of the injection molding equipment as normal suspension; when T1-YT is more than T1, the suspended operation of the injection molding equipment is judged to be abnormal suspension, then a suspension event is generated, and the generated suspension event is sent to a monitoring center, wherein the content of the suspension event comprises a suspended injection molding equipment number, a suspension starting time, a suspension ending time, a suspension reason, a responsibility department and a responsibility department person, T0 is system preset logistics response time, and T0 is more than 0; t1 is the preset feeding time of the system, and T1 is more than 0;
step F4: by the formula
Obtaining a mould loss coefficient MSX, and when the mould loss coefficient MSX is less than MS0, indicating that the mould is in a normal state; when MSX is not less than MS0 and not more than MS1, the mold is in an early warning state, mold loss early warning information is sent to a monitoring center, when MSX is more than MS1, the mold is judged to be in an overload state, the mold overload state early warning information is sent to the monitoring center, the injection molding equipment is forcibly stopped, and a maintenance task list is generated, wherein the maintenance task list comprises the number of the injection molding equipment, the fault reason, the position of the injection molding equipment and the predicted time required for completing maintenance; sending a maintenance task list to a maintenance module, wherein M0 and Z0 are the theoretical use duration of the injection molding equipment and the theoretical production times of the injection molding equipment respectively, MS0 and MS1 preset loss thresholds for the system, and MS0 is less than MS 1;
step F5: by the formula
Obtaining a finished product rejection coefficient GF, judging that the yield of unqualified finished products of the injection molding equipment exceeds the standard when GF is more than 0, marking the injection molding equipment as suspected fault equipment, sending information of the suspected fault equipment to a monitoring center, and generating an overhaul task list, wherein the overhaul task list comprises the number of the injection molding equipment, the fault reason, the position of the injection molding equipment and the expected time required for completing maintenance; and sending the maintenance task list to a maintenance module, wherein beta is a system correction coefficient, G0 is a system preset unqualified product standard exceeding rate, Ts is a system preset acquisition time period, and TN is the number of unqualified products in the system preset acquisition time period.
The logistics distribution module responds to the received early warning information when receiving the early warning information with insufficient raw material content, wherein the early warning information comprises the serial number of the injection molding equipment with insufficient raw material, the position of the injection molding equipment, the name of the raw material to be distributed and the content of the raw material.
The fault diagnosis module is used for diagnosing the fault reason of the injection molding equipment when the injection molding equipment has faults, and the specific diagnosis process comprises the following steps:
step G1: when the injection molding equipment is marked as suspected fault equipment, acquiring a mould loss coefficient MSX, when the MSX is not less than MS0 and not more than MS1, indicating that the mould is in an early warning state, sending mould loss early warning information to a monitoring center, and simultaneously marking the mould as a primary suspected fault point; when MSX is larger than MS1, judging that the mold is in an overload state, sending mold overload state early warning information to a monitoring center, and marking the mold as a secondary suspected fault point; when the mould loss coefficient MSX is less than MS0, the mould is in a normal state, and then the next step is carried out;
step G2: when the mould is in a normal state, acquiring the initial weight CZ of each raw materialiAnd the remaining weight SZiTo obtain the used mass YZ of each raw materiali，YZi＝CZi-SZi(ii) a By the formula
Obtaining the ratio value ZB of each raw materiali(ii) a The obtained ratio value ZB of each raw materialiMatching with the raw material ratio required by the model of the product being produced;
step G3: when the deviation value of the ratio of certain raw materials to the raw material ratio required by the model of the product being produced is larger than PiIf so, marking the raw materials as fault sources; and determines that the cause of the failure of the injection molding apparatus is caused by the source of the failure.
The loss estimation module is used for estimating theoretical loss caused by injection molding equipment, and the specific estimation process comprises the following steps:
step D1: acquiring the time spent by each injection molding device for producing a single finished product, and marking the time as DJT; acquiring the cost required by each single finished product, and marking the cost as DJC;
step D2: by the formula
And obtaining a production theoretical loss value SG, wherein ZT is total downtime of the injection molding equipment, theta is a system correction coefficient, and theta is larger than 0.
The maintenance module is used for distributing a maintenance task list or a maintenance task list, and the specific distribution mode comprises the following steps:
step W1: acquiring all maintenance task lists and maintenance task lists, wherein the maintenance task lists have priorities;
step W2: acquiring information of maintenance personnel who attendance on the day, marking the state of the maintenance personnel who are performing maintenance work as working, and marking the state of the maintenance personnel who are not performing maintenance work as waiting;
step W3: preferentially distributing a maintenance task list or a maintenance task list to maintenance personnel in a waiting state; when a plurality of maintenance personnel in the waiting state exist, the maintenance personnel in the waiting state with the longest time are preferentially allocated;
step W4: when all maintenance personnel are in a working state, acquiring the information of the maintenance personnel who are executing the maintenance task list, and distributing the maintenance task list to the maintenance personnel who are executing the maintenance task list;
step W5: when all maintenance personnel execute the maintenance task list, acquiring the predicted residual completion time of each maintenance task list, and distributing the maintenance task list to the maintenance personnel with the shortest predicted residual completion time;
step W6: and sending the maintenance task list or the maintenance task list information to a mobile phone of a maintenance worker through an information pushing module.
The working principle of the invention is as follows: inputting injection molding equipment information and personnel information through an information input module, and sending the injection molding equipment information and the personnel information to a monitoring center for storage; then, data information is acquired through a raw material information acquisition unit, an equipment information acquisition unit and a finished product information acquisition unit in the data acquisition module, the model of a product being produced by the injection molding equipment is acquired through the raw material information acquisition unit, and the type and the ratio of raw materials required by the model of the product being produced are acquired; the starting time of the injection molding equipment is obtained through the equipment information acquisition unit, the using time of a mold of the injection molding equipment and the number of assembly products produced by the mold are obtained through the equipment information acquisition unit, the number of qualified finished products and the number of unqualified finished products are obtained through the finished product information acquisition unit, when the number of the unqualified finished products exceeds the standard, the reasons causing the unqualified number of the finished products to exceed the standard can be automatically checked, and a maintenance task list is generated, so that maintenance personnel can be helped to quickly solve the problem; then, data acquired by the data acquisition module are sent to the data analysis module in real time; the data analysis module analyzes the production information of the injection molding equipment, sends early warning information to the logistics distribution module when the raw materials are insufficient, and the logistics distribution module responds to the received early warning information when receiving the early warning information with insufficient raw material content; when the injection molding equipment has faults, the fault diagnosis module diagnoses the fault reasons of the injection molding equipment, inspects the use conditions of the injection molding equipment and a mold, and then inspects the use conditions of raw materials so as to determine a fault source; therefore, when the service life of the injection molding equipment or the service life of the mold reaches a system preset value, early warning information can be automatically sent out, and a maintenance task list is generated, so that the condition that batch finished products are poor after the injection molding equipment breaks down is avoided; estimating theoretical loss caused by injection molding equipment by arranging a loss estimation module, and acquiring a theoretical loss value by acquiring the number of unqualified finished products and the total pause time of the injection molding equipment; and distributing the maintenance task list or the overhaul task list through the maintenance module, and executing the maintenance task by the maintenance personnel according to the information on the maintenance task list or the overhaul task list.
The above formulas are all quantitative calculation, the formula is a formula obtained by acquiring a large amount of data and performing software simulation to obtain the latest real situation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is illustrative and explanatory of the structure of the invention, and various modifications, additions or substitutions in a similar manner to the specific embodiments described may be made by those skilled in the art without departing from the structure or scope of the invention as defined in the claims. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Claims (7)
1. An injection molding equipment state monitoring system based on industry 4.0 is characterized by comprising a monitoring center, an information input module, a data acquisition module, a data analysis module, a logistics distribution module, a fault diagnosis module, a loss estimation module, a maintenance module and an information pushing module;
the fault diagnosis module is used for diagnosing the fault reason of the injection molding equipment when the injection molding equipment has faults, and the specific diagnosis process comprises the following steps:
step G1: when the injection molding equipment is marked as suspected fault equipment, acquiring a mould loss coefficient MSX, when the MSX is not less than MS0 and not more than MS1, indicating that the mould is in an early warning state, sending mould loss early warning information to a monitoring center, and simultaneously marking the mould as a primary suspected fault point; when MSX is larger than MS1, judging that the mold is in an overload state, sending mold overload state early warning information to a monitoring center, and marking the mold as a secondary suspected fault point; when the mould loss coefficient MSX is less than MS0, the mould is in a normal state, and then the next step is carried out;
step G2: when the mould is in a normal state, acquiring the initial weight CZ of each raw materialiAnd the remaining weight SZiTo obtain the used mass YZ of each raw materiali，YZi＝CZi-SZi(ii) a By the formula
Obtaining the ratio value ZB of each raw materiali(ii) a Mixing each obtained raw materialMaterial ratio ZBiMatching with the raw material ratio required by the model of the product being produced;
step G3: when the deviation value of the ratio of certain raw materials to the raw material ratio required by the model of the product being produced is larger than PiIf so, marking the raw materials as fault sources; and determines that the cause of the failure of the injection molding apparatus is caused by the source of the failure.
2. The industrial 4.0-based injection molding equipment state monitoring system of claim 1, wherein the data acquisition module is used for acquiring production information of injection molding equipment, and comprises a raw material information acquisition unit, an equipment information acquisition unit and a finished product information acquisition unit, and the raw material information acquisition unit is used for acquiring a product model of the injection molding equipment and acquiring a required raw material type and a required mixture ratio of the product model; acquiring the initial weight of each raw material in the injection molding equipment and the residual weight of each raw material in the injection molding equipment through a raw material information acquisition unit; the method comprises the steps that starting time of the injection molding equipment is obtained through an equipment information acquisition unit, and the running time of the injection molding equipment is recorded; acquiring the use duration of a mold of the injection molding equipment and the number of assembly products produced by the mold through an equipment information acquisition unit; and acquiring the quantity of qualified finished products and the quantity of unqualified finished products through a finished product information acquisition unit.
3. An industrial 4.0-based injection molding apparatus condition monitoring system as claimed in claim 1 wherein said data analysis module is configured to analyze production information of the injection molding apparatus.
4. The industrial 4.0-based injection molding equipment condition monitoring system of claim 1, wherein the logistics distribution module is responsive to the received early warning information when receiving early warning information of insufficient raw material content.
5. An industrial 4.0-based injection molding apparatus condition monitoring system as claimed in claim 1 wherein said loss estimation module is configured to estimate a theoretical loss incurred by the injection molding apparatus.
6. An industrial 4.0-based injection molding apparatus condition monitoring system as claimed in claim 1 wherein said maintenance module is configured to assign a maintenance order or service order.
7. The industrial 4.0-based injection molding equipment state monitoring system of claim 1, wherein the information entry module is used for entering injection molding equipment information and personnel information, and sending the injection molding equipment information and the personnel information to the monitoring center for storage, wherein the injection molding equipment information comprises an injection molding equipment number, an injection molding equipment name, time for the injection molding equipment to start to be put into use, and a specific position of the injection molding equipment; the personnel information comprises name, gender, working age, affiliated department, position and mobile phone number of real-name authentication.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113469560A (en) * | 2021-07-19 | 2021-10-01 | 北京东华博泰科技有限公司 | Cloud platform data management system based on industrial big data |
| CN114035466A (en) * | 2021-11-05 | 2022-02-11 | 肇庆高峰机械科技有限公司 | Control system of duplex position magnetic sheet arrangement machine |
| CN114527718A (en) * | 2022-02-25 | 2022-05-24 | 江苏鑫亿鼎石英科技股份有限公司 | Quartz sand datamation intelligent production control system |
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Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114415613B (en) * | 2022-01-07 | 2022-09-09 | 深圳市微特精密科技股份有限公司 | Automatic production management system |
| JP7287528B1 (en) | 2022-03-30 | 2023-06-06 | 凸版印刷株式会社 | Materials management system, materials management method, materials management device, and program |
Family Cites Families (25)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS63296102A (en) * | 1987-05-28 | 1988-12-02 | Toshiba Corp | Plant control system |
| JPH01291918A (en) * | 1988-05-20 | 1989-11-24 | Komatsu Ltd | Trouble diagnosis device for injection molding machine |
| JP2693858B2 (en) * | 1990-09-26 | 1997-12-24 | 東洋機械金属株式会社 | Injection molding machine |
| JPH0752219A (en) * | 1993-08-18 | 1995-02-28 | Japan Steel Works Ltd:The | Memory system for content of generated abnormality of injection molding machine |
| JP2002308232A (en) * | 2001-04-19 | 2002-10-23 | Nihon Tetra Pak Kk | Method and apparatus for monitoring liquid food packaging and filling machine |
| JP3705583B2 (en) * | 2001-09-25 | 2005-10-12 | 住友重機械工業株式会社 | Mold management system for molding machine |
| TWI236418B (en) * | 2002-08-27 | 2005-07-21 | Sumitomo Heavy Industries | Molding machine managing system, molding machine managing apparatus, portable information terminal, recording medium where program for molding machine managing apparatus is installed, and recording medium where program for portable information terminal.. |
| JP3962672B2 (en) * | 2002-11-08 | 2007-08-22 | 東芝機械株式会社 | MANAGEMENT SUPPORT DEVICE, ITS SYSTEM, ITS METHOD, ITS PROGRAM, AND RECORDING MEDIUM CONTAINING THE PROGRAM |
| DE102004041891B3 (en) * | 2004-08-31 | 2006-04-13 | Krauss-Maffei Kunststofftechnik Gmbh | IT-technical integration of all operational processes in production machines |
| CN101582790B (en) * | 2008-05-15 | 2011-12-07 | 华为技术有限公司 | Method, device and system for dynamic data audit and service entity fault detection |
| US8855804B2 (en) * | 2010-11-16 | 2014-10-07 | Mks Instruments, Inc. | Controlling a discrete-type manufacturing process with a multivariate model |
| CN104935481B (en) * | 2015-06-24 | 2018-03-09 | 华中科技大学 | Data reconstruction method based on redundancy scheme under a kind of distributed storage |
| CN107239064A (en) * | 2016-03-27 | 2017-10-10 | 中国食品发酵工业研究院 | A kind of method for assessing filling production lines efficiency and board state |
| CN205562161U (en) * | 2016-05-04 | 2016-09-07 | 漳州东利光学科技有限公司 | Glasses mould operating condition monitoring devices |
| CN106952033B (en) * | 2017-03-16 | 2020-11-17 | 沈阳新一代信息技术有限公司 | Multi-data-source-based stirring equipment production quality monitoring system and method |
| CN106986155A (en) * | 2017-05-10 | 2017-07-28 | 安徽江淮汽车集团股份有限公司 | A kind of feeding control method and system for combining material |
| CN108092847B (en) * | 2017-11-28 | 2019-03-08 | 南瑞集团有限公司 | A kind of electric power LTE wireless terminal remote on-line monitoring method |
| JP6852811B2 (en) * | 2017-12-26 | 2021-03-31 | 日産自動車株式会社 | Abnormality judgment method and abnormality judgment device |
| CN108197813A (en) * | 2018-01-12 | 2018-06-22 | 北京上格云技术有限公司 | Work order distribution method based on internet |
| CN108845544A (en) * | 2018-06-15 | 2018-11-20 | 合肥齐信信息技术有限公司 | A kind of scarce material intelligent alarm method of production line based on surplus monitoring |
| CN111098463A (en) * | 2018-10-27 | 2020-05-05 | 泰瑞机器股份有限公司 | Injection molding machine fault diagnosis system and diagnosis method |
| CN109870966A (en) * | 2019-01-09 | 2019-06-11 | 深圳先进技术研究院 | A kind of industry internet control system |
| CN110497604A (en) * | 2019-08-15 | 2019-11-26 | 长虹美菱股份有限公司 | A kind of fault verification and alarm set of Packing Machine |
| CN110991834A (en) * | 2019-11-20 | 2020-04-10 | 黑龙江电力调度实业有限公司 | Scheduling system of electric power overhaul task |
| CN112464628B (en) * | 2020-12-05 | 2024-03-26 | 勇气模具塑胶(苏州)有限公司 | Automatic material preparation method, system, terminal and storage medium for injection molding machine |
-
2021
- 2021-05-24 CN CN202110565036.4A patent/CN113110362A/en active Pending
- 2021-08-10 CN CN202110914263.3A patent/CN113504769A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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