CN121455053A - Automatic numerical control workshop transformation method and system - Google Patents

Abstract

This invention discloses an automated CNC workshop transformation method and system, comprising: acquiring machining process chains of several parts based on a part machining plan; determining the part to be machined; selecting a machining process chain based on the part to be machined; and matching a candidate machine tool dataset that meets the part machining type; filtering the candidate machine tool dataset in conjunction with a constructed production process database to determine a first executing machine tool; monitoring the machining status of the part to be machined in real time based on the production process database; if the machining status of the part to be machined is in a deviated state, triggering a machine tool reassignment mechanism and determining a second executing machine tool; and continuing to monitor the machining status of the part to be machined until the part to be machined is completed. Compared with the prior art, it can achieve adaptive selection and dynamic reassignment of machine tools based on the part machining plan and the production process database, effectively improving production efficiency and production quality.

Description

Automatic numerical control workshop transformation method and system

Technical Field

The application relates to the technical field of manufacturing automation, in particular to an automatic numerical control workshop transformation method and system.

Background

Along with the acceleration of the intelligent transformation of the manufacturing industry, a numerical control workshop is used as a core production unit, the automation level of the numerical control workshop directly determines the production efficiency and the product competitiveness of an enterprise, the number and the variety of numerical control machine tools in the enterprise are continuously increased at present, the processing requirement presents complex characteristics of multiple varieties and multiple procedures, the production organization and the equipment management of the numerical control workshop become the core challenges of the automatic upgrading of the manufacturing industry, the part processing is required to be matched with the performance of a specific process chain and a machine tool in the numerical control processing process, the running state, the processing precision and the service life cycle of the machine tool are different, the task issuing lag and the equipment coordination difference are easily caused by the manual intervention, the process suitability, the equipment scheduling flexibility and the abnormal response timeliness of the automatic transformation of the workshop are more stringent, and the main operation mode of the numerical control workshop in the industry is still mainly single-bed manual management control at present, and the partial transformation scheme only realizes the local automation of single equipment.

In the prior art, although schemes try to realize multi-machine tool cooperation through manual preset flow or select processing equipment by means of basic data statistics, in the prior art, a plurality of automatic numerical control workshops which cooperate and carry out terminal total control still do not exist, one person and one machine result in low equipment utilization rate, poor processing efficiency and high labor cost.

Therefore, how to provide an automatic numerical control workshop capable of implementing multiple collaboration and terminal general control has become a technical problem to be solved urgently by those skilled in the art.

Disclosure of Invention

In order to solve the technical problems, the application provides an automatic numerical control workshop transformation method which can realize machine tool self-adaptive screening and dynamic redistribution according to a part processing scheme and a production process database, and effectively improve the production efficiency and the production quality.

The first technical scheme provided by the application is as follows:

The application provides an automatic numerical control workshop transformation method which comprises the following steps of obtaining a part machining scheme, respectively obtaining machining process chains of a plurality of machined parts according to the part machining scheme, identifying and determining the parts to be machined, selecting the machining process chains according to the parts to be machined, matching candidate machine tool data sets meeting the part machining types according to the machining process chains, constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data sets in combination with the production process database, determining a first execution machine tool, sending the parts to be machined to the first execution machine tool, monitoring the machining state of the parts to be machined in real time based on the production process database, sending an alarm if the machining state of the parts to be machined is in a deviation state, triggering a machine tool reassigning mechanism to obtain idle second execution machine tool information, moving a workpiece to the second execution machine tool according to the idle second execution machine tool information, and continuing to monitor the machining state of the parts to be machined until the machining of the parts to be machined is completed.

Further, in a preferred mode of the present invention, the identifying and determining the part to be machined includes:

analyzing the part to be processed;

collecting processing indexes of the part to be processed, wherein the processing indexes comprise precision requirement information, processing time and processing yield;

wherein the processing index of the part to be processed is input by a user.

Further, in a preferred form of the invention, the adaptive screening of the candidate machine tool data set in conjunction with the production process database comprises:

Searching the production process database based on the precision requirement information as a search condition, and matching the precision requirement with the candidate machine tool data set according to a search result to obtain a first candidate machine tool subset;

Searching the production process database based on the processing time as a search condition, and matching the processing time with the candidate machine tool data set according to a search result to obtain a second candidate machine tool subset;

And searching the production process database based on the processing yield as a search condition, and according to a search result, performing processing yield matching with the candidate machine tool data set to determine a first execution machine tool.

Further, in a preferred form of the invention, the steps of constructing a production process database include:

Respectively collecting historical machine tool performance parameters, rated life cycle and historical service life of a plurality of numerical control machine tools and historical part performance requirements of the machined parts;

The historical machine tool performance parameters comprise historical machining time and historical machining yield of each machined part machined by each numerical control machine tool respectively, and the historical part performance requirements comprise historical precision requirements of the machined parts;

Acquiring the service life deviation of the machine tool according to the rated service life period and the historical service life of each numerical control machine tool;

and respectively establishing a combined index with each numerical control machine tool, the historical machine tool performance parameters, the historical part performance requirements, the rated life cycle, the historical service life and the machine tool life deviation, and constructing a production process database.

Further, in a preferred form of the invention, the step of iteratively optimizing the production process database comprises:

and recording part production data according to a real-time monitoring result, inputting the part production data into the production process database for database updating until the iteration times reach preset times, and completing the iterative optimization of the production process database.

Further, in a preferred form of the invention, the step of adaptively screening the candidate machine tool dataset in conjunction with the production process database comprises:

Determining historical machine tool performance parameters of each candidate machine tool according to the production process database, and dividing the historical machine tool performance parameters into a plurality of groups of performance data sets, wherein the performance data sets are data sets of each type of machining performance data;

And performing performance weight distribution on the performance requirements of the part to be processed, and screening a plurality of groups of performance data sets according to the performance weight distribution result as a reference to determine a first execution machine tool.

Further, in a preferred mode of the present invention, the step of performing performance weight allocation on the performance requirement of the part to be processed includes:

Extracting the historical part performance requirements of the part to be processed according to the production process database, and setting initial performance weights according to the historical part performance requirements;

Disassembling the processing technology chain of the part to be processed to obtain a rough processing stage and a finish processing stage, respectively setting main processing targets for the rough processing stage and the finish processing stage, respectively correcting the initial performance weights according to the main processing targets of different stages, and obtaining stage performance weights;

Acquiring equipment life cycle data of the candidate machine tool according to the production process database, judging whether the corresponding candidate machine tool is in a healthy state according to the life cycle data, if so, maintaining the stage performance weight, and if not, adjusting the stage performance weight to acquire a stage optimization weight;

And screening the candidate machine tool data set according to the phase optimization weight and the phase performance weight to obtain a first execution machine tool.

Further, in a preferred mode of the present invention, the step of triggering machine tool reassignment when the first execution machine tool is in an offset state includes:

determining a procedure deviation node according to the processing technology chain, and determining a subsequent processing machine tool and a processing procedure according to the procedure deviation node;

Searching the processing procedure according to the production process database, searching historical execution machine tools of the processing procedure, and obtaining a plurality of machine tools to be matched;

and performing procedure matching according to the plurality of machine tools to be matched, and determining a redistribution machine tool.

Further, in a preferred mode of the present invention, the step of performing process matching according to a plurality of machine tools to be matched includes:

Acquiring the working state of the machine tool to be matched in real time, and filtering the machine tool to be matched according to the working state to acquire an idle machine tool;

according to the production process database, the machining yield of the idle machine tool is called, and the machining yield is ordered to obtain a machining qualification sequence;

and matching the machine tools to be matched according to the processing qualified sequence, and completing process matching.

The application provides a second technical scheme as follows:

the application also provides an automatic numerical control workshop reconstruction method system, which comprises the following steps:

The processing chain acquisition module is used for acquiring a part processing scheme and respectively acquiring processing process chains of a plurality of processed parts according to the part processing scheme;

The candidate machine tool acquisition module is used for identifying and determining a part to be machined, selecting the machining process chain according to the part to be machined, and matching a candidate machine tool data set meeting the machining type of the part according to the machining process chain;

the database construction module is used for constructing a production process database, and carrying out self-adaptive screening on the candidate machine tool data set by combining the production process database to determine a first execution machine tool;

the machine tool redistribution module is used for sending the part to be processed to the first execution machine tool and monitoring the processing state of the part to be processed in real time based on the production process database;

If the machining state of the part to be machined is in a deviation state, an alarm is sent out, a machine tool reassignment mechanism is triggered, idle second execution machine tool information is obtained, and a workpiece is moved to a second execution machine tool according to the idle second execution machine tool information;

And continuously monitoring the processing state of the part to be processed until the part to be processed is processed.

The automatic numerical control workshop transformation method comprises the steps of S1 obtaining a part machining scheme, respectively obtaining machining process chains of a plurality of machined parts according to the part machining scheme, S2 identifying and determining the machined parts, selecting the machining process chains according to the machined parts, matching candidate machine tool data sets meeting the machining types of the parts according to the machining process chains, S3 constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data sets in combination with the production process database, determining a first execution machine tool, S4 sending the machined parts to the first execution machine tool, monitoring the machining state of the machined parts in real time based on the production process database, sending an alarm if the machining state of the machined parts is in a deviation state, triggering a machine tool reassigning mechanism to obtain idle second execution machine tool information, moving a workpiece to the second execution machine tool according to the idle second execution machine tool information, and continuing to monitor the machining state of the machined parts until the machining of the machined parts is completed. The method comprises the steps of acquiring a part machining scheme and respectively acquiring machining process chains of a plurality of machined parts, solving the problem that the prior art is disjointed due to the fact that a common process is used or a process is set up in a scattered manner, the problems that the process chains are different from the parts to be machined, and complex machining requirements of multiple varieties and multiple procedures are caused in the process chains are solved, selecting a candidate machine tool data set corresponding to the machining process chains and meeting the machining types of the parts according to matching of the process chains after identifying the parts to be machined, solving the problem that machining equipment is selected only by means of basic data statistics in the prior art, the performance of the machine tool is not related to the specific process chains of the parts, constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data set by combining the database to determine a first execution machine tool, solving the problem that the prior art ignores individual differences such as the running state, the machining precision, the service life cycle and the like of the machine tool, and mainly uses single-bed manual control, solving the problem that the equipment utilization rate is low due to one machine is solved, meanwhile, the limitation of local automation of single equipment is overcome, a data driving basis is provided for a plurality of equipment is broken through the database, and the machine tool redistribution mechanism can break through the main flow single-bed manual control, efficiency is improved, and the bottleneck loss caused by the dynamic equipment scheduling is avoided.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of steps of an automated numerical control plant transformation method provided by an embodiment of the invention;

FIG. 2 is a schematic diagram of adaptive screening of candidate machine tool data sets according to an embodiment of the present invention;

fig. 3 is a schematic diagram of machine tool redistribution according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the technical solutions of the present application, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

It will be understood that when an element is referred to as being "mounted" or "disposed" on another element, it can be directly on the other element or be indirectly on the other element, or be directly connected or indirectly connected to the other element.

It is to be understood that the terms "length," "width," "upper," "lower," "front," "rear," "first," "second," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are merely for convenience in describing and simplifying the description based on the orientation or positional relationship shown in the drawings, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus are not to be construed as limiting the application.

Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" or "a number" means two or more, unless specifically defined otherwise.

It should be understood that the structures, proportions, sizes, etc. shown in the drawings are for the purpose of understanding and reading the disclosure, and are not intended to limit the scope of the application, which is defined by the claims, but rather by the claims, unless otherwise indicated, and that any structural modifications, proportional changes, or dimensional adjustments, which would otherwise be apparent to those skilled in the art, would be made without departing from the spirit and scope of the application.

The automatic numerical control workshop transformation method comprises the steps of S1 obtaining a part machining scheme, respectively obtaining machining process chains of a plurality of machined parts according to the part machining scheme, S2 identifying and determining the parts to be machined, selecting the machining process chains according to the parts to be machined, matching candidate machine tool data sets meeting the part machining types according to the machining process chains, S3 constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data sets in combination with the production process database, determining a first execution machine tool, S4 sending the parts to be machined to the first execution machine tool, monitoring the machining state of the parts to be machined in real time based on the production process database, sending an alarm if the machining state of the parts to be machined is in a deviation state, triggering a machine tool redistribution mechanism, obtaining idle second execution machine tool information, moving a workpiece to the second execution machine tool according to the idle second execution machine tool information, and continuing to monitor the machining state of the parts to be machined until the parts to be machined are machined.

In this embodiment, firstly, a general part processing scheme is imported, the scheme needs to include core information such as part design drawing, processing precision requirement, surface quality standard, process sequence logic and the like, and then, materials, structural features and processing requirements of different processed parts in the scheme are automatically identified, and a complete processing process chain corresponding to each processed part is extracted; identifying and determining a machined part, automatically matching an extracted exclusive machining process chain of the part, screening a candidate machine tool data set matched with machining types based on machining types of all working procedures in the process chain, constructing a production process database, executing self-adaptive screening on the candidate machine tool data set based on the production process database, finally determining the first machine tool, transferring the part to be machined to the first machine tool through a workshop logistics conveying system, monitoring the machining state of the part to be machined in real time, acquiring machining data in real time through a built-in sensor (such as a temperature sensor, a vibration sensor and a displacement sensor) of the machine tool, comparing the machining data with monitoring parameters, judging whether the machining state is normal or not, immediately judging that the machining state is in a deviation state if the real-time acquired data exceeds a monitoring parameter threshold value, synchronously triggering an audible alarm, displaying the deviation parameter and possible reasons, starting a machine tool reassignment mechanism, inquiring machine tool information in the production process database, transferring the part to be machined from the first machine tool to the second machine tool through the workshop logistics conveying system, synchronously updating parameters until the whole machining process is completed by the system, and if the real-time acquired data does not exceed the monitoring parameter threshold value, the first executing machine tool is not replaced, and the part machining is normally completed.

The following describes the steps of an automated numerical control plant improvement method in detail with reference to specific embodiments.

Specifically, in a specific embodiment of the present invention, identifying and determining a part to be machined includes:

analyzing a part to be processed;

Collecting processing indexes of a part to be processed, wherein the processing indexes comprise precision requirement information, processing time and processing yield;

Wherein the processing index of the part to be processed is from user input.

In this embodiment, a part identification reading device is adopted, such as an industrial code scanning gun, an RFID reader and the like, for collecting information of a part to be processed, wherein in the embodiment, if a unique identification label (such as a two-dimensional code and a bar code) is attached to the surface of the part to be processed, the label information is read through the code scanning gun, basic properties of the part including a part name, a material type, a basic size, structural characteristics and the like are automatically analyzed, if the part to be processed has no identification label, an appearance image of the part to be processed is shot through a visual identification camera, edge feature matching, contour similarity calculation and the like of the part to be processed are identified through image comparison, and then the processing index of the part to be processed including precision requirement information, processing time and processing yield is input through a workshop worker or a production dispatcher.

Specifically, as shown in fig. 2, in the embodiment of the present invention, the step of adaptively screening the candidate machine tool data set in combination with the production process database includes:

Searching the production process database based on the precision requirement information as a search condition, and matching the precision requirement with the candidate machine tool data set according to a search result to obtain a first candidate machine tool subset;

Searching the production process database based on the processing time as a search condition, and matching the processing time with the candidate machine tool data set according to the search result to obtain a second candidate machine tool subset;

And searching the production process database based on the machining yield as a search condition, and matching the production process database with the candidate machine tool data set according to the search result to determine the first execution machine tool.

In this embodiment, firstly, precision requirement information (such as critical process dimension tolerance, form and position tolerance and surface roughness) is called as a search condition, a production process database is called for searching, a search result is compared with a candidate machine tool data set, machine tools with unsatisfied precision are removed, finally, a first candidate machine tool subset is formed, the subset is required to be marked with precision matching degree of each machine tool, then, processing time requirements (including a single piece total processing time length upper limit and a critical process time length upper limit) are extracted, the search is called for searching by taking the search result as a search condition, the search result is compared with the first candidate machine tool subset, machine tools with exceeding estimated time length are removed, a second candidate machine tool subset is formed, the estimated processing time length of each machine tool is marked by the subset, then, the search result is called for searching by taking the search condition, the search result is compared with the second candidate machine tool subset, if the second candidate machine tool subset has machine tools with precision matching degree, stability of processing yield is further compared, the comparison is carried out, and if the comparison is carried out by comparing the first candidate machine tools with the first candidate machine tool subset with the largest priority, and the best overall machine tool performance is determined to be 1, and the best overall machine tool performance is determined if the comparison is carried out.

Specifically, in a specific embodiment of the present invention, the steps of constructing a production process database include:

Respectively collecting historical machine tool performance parameters, rated life cycle and historical service life of a plurality of numerical control machine tools and historical part performance requirements of machined parts;

The historical machine tool performance parameters comprise the historical machining time and the historical machining yield of each numerical control machine tool for machining each machined part respectively, and the historical part performance requirements comprise the historical precision requirements of the machined parts;

Acquiring the service life deviation of the machine tool according to the rated service life period and the historical service life of each numerical control machine tool;

And respectively establishing a combined index with each numerical control machine tool, historical machine tool performance parameters, historical part performance requirements, rated life cycle, historical service life and machine tool life deviation, and constructing a production process database.

In the embodiment of the invention, firstly, the PLC control system of each numerical control machine tool is connected through OPC UA protocol, the history data of each machine tool for processing different parts is extracted, and the history data is stored according to the dimension classification of the machine tool and the parts, wherein the single processing time length of each machine tool for processing a single part is recorded, and the single processing time length comprises the complete time from the feeding to the discharging of a workpiece and is accurate to seconds; then, the qualification rate of each machine tool for processing a part is counted, and then, the rated life cycle of each machine tool is extracted, provided by a machine tool manufacturer, and the historical practical life from the time of the machine tool being put into use to the current actual operation time is obtained; the method comprises the steps of extracting historical precision requirements of machined parts, including dimensional tolerance, form and position tolerance, surface quality requirements and the like, calculating the service life deviation of the machine tool based on rated service life and historical service life of each numerical control machine tool, wherein the calculation method comprises the steps of setting up multi-dimensional combined indexes by taking a machine tool unique identifier and a machined part unique identifier as cores, and in the embodiment, the steps of associating each index with core data such as the machine tool unique identifier, the machined part unique identifier, historical machine tool performance parameters, the historical part performance requirements, the machine tool rated service life cycle, the machine tool historical service life, the machine tool service life deviation and the like, and adopting an industrial relational database to construct a production process database.

Specifically, in a specific embodiment of the present invention, the steps of iteratively optimizing a production process database include:

And recording the production data of the parts according to the real-time monitoring result, inputting the production data of the parts into a production process database for updating the database until the iteration times reach the preset times, and completing the iteration optimization of the production process database.

In the embodiment of the invention, based on the real-time data interface of the OPC UA industrial communication protocol direct connection numerical control machine tool, real-time data related to the machine tool are synchronously collected, the collected real-time data are bound with the corresponding machine tool and the part, and are directly updated into a production process database without replacing original historical data, meanwhile, the real-time service life data of the machine tool are updated, the service life deviation of the machine tool is recalculated, the combined index of the machine tool and the part is updated according to the updated data, the historical data and the latest data can be simultaneously called when the subsequent screening is ensured, the data stability and the instantaneity are considered, compared with the existing mode, the incremental updating can reduce a large amount of data writing time, the historical data is reserved to facilitate the analysis of production trend, the data support is provided for process optimization, and the problems of infinite iteration and incapability of landing of the database are avoided when the iteration updating is carried out according to preset iteration times, and the problems of machine tool mismatch, machining errors and the like caused by inaccurate data are remarkably reduced.

Specifically, in the embodiment of the present invention, the step of adaptively screening the candidate machine tool data set in combination with the production process database includes:

determining historical machine tool performance parameters of each candidate machine tool according to a production process database, and dividing the historical machine tool performance parameters into a plurality of groups of performance data sets, wherein the performance data sets are data sets of each type of machining performance data;

and performing performance weight distribution on the performance requirements of the part to be processed, and screening a plurality of groups of performance data sets according to the performance weight distribution result as a reference to determine a first execution machine tool.

In this embodiment, the historical data of each candidate machine tool for machining similar parts is obtained through the production process database, including machining quality parameters, stability parameters and the like, and the parameters are classified, for example, the parameters can be classified according to three major categories of machining efficiency, machining quality and stability, each group forms an independent performance data set, dynamic weight distribution is performed according to performance requirements (such as precision, efficiency and stability priority) of the part to be machined, and the first execution machine tool is determined by taking a weight distribution result as a reference.

Specifically, in a specific embodiment of the present invention, the step of performing performance weight allocation on performance requirements of a part to be processed includes:

Extracting the historical part performance requirements of the part to be processed according to the production process database, and setting initial performance weights according to the historical part performance requirements;

Disassembling a processing chain of a part to be processed, obtaining a rough processing stage and a finish processing stage, setting main processing targets for the rough processing stage and the finish processing stage respectively, and correcting initial performance weights according to the main processing targets of different stages respectively to obtain stage performance weights;

Acquiring equipment life cycle data of the candidate machine tool according to the production process database, judging whether the corresponding candidate machine tool is in a healthy state according to the life cycle data, if so, maintaining the stage performance weight, and if not, adjusting the stage performance weight to acquire the stage optimization weight;

and screening the candidate machine tool data set according to the phase optimization weight and the phase performance weight to obtain a first execution machine tool.

In this embodiment, the historical part performance requirements of the part to be processed are retrieved from the production process database, including the precision requirement, the efficiency requirement and the efficiency requirement of the part in the past processing, and according to the occurrence frequency of the historical requirements and the influence degree on the quality of the finished product, the initial performance weights (such as the precision, the efficiency and the yield ratio respectively account for 50%, 30% and 20%) are comprehensively determined; then, the processing process chain of the part to be processed is disassembled, a rough processing stage (such as blank removing allowance and a preliminary forming process) and a finish processing stage (such as precision size processing and surface treatment process) are clearly distinguished, main processing targets are set for core targets of the two stages, wherein the rough processing stage mainly comprises efficient removing allowance and guaranteeing uniformity of follow-up process allowance, the finish processing stage mainly comprises the steps of meeting final precision requirements and guaranteeing qualified surface quality, the initial weight is corrected according to the main processing targets, the weight proportion of the rough processing stage for improving efficiency and stability is reduced, the weight proportion of the precision and the yield is reduced, the weight of the finish processing stage for improving the precision and the yield is matched with the core requirements of each stage, the whole process is avoided, then, equipment life cycle data of candidate machine tools are extracted from a production process database, the equipment life cycle data of the candidate machine tools comprise rated life cycle, historical service life and life deviation, the machine tool health state is judged according to the data, the health state of the machine tools is judged if the machine tools are healthy, the performance weight of the stages is maintained, the non-health state is not well, the weight is improved, the weight of the stability is reduced, the weight is formed, the weight is optimized through the non-health risk avoidance of the machine tool is optimized, finally, comprehensively screening the performance data (such as accuracy standard rate, processing efficiency and yield stability) of the candidate machine tool according to the stage performance weight and the stage optimization weight to obtain a first execution machine tool,

Specifically, as shown in fig. 3, in a specific embodiment of the present invention, when the first execution machine is in a deviated state, the step of triggering machine redistribution includes:

S41, determining a procedure deviation node according to a processing technology chain, and determining a subsequent processing machine tool and a processing procedure according to the procedure deviation node;

s42, searching the processing procedure according to the production process database, searching historical execution machine tools of the processing procedure, and obtaining a plurality of machine tools to be matched;

S43, performing process matching according to a plurality of machine tools to be matched, and determining a redistribution machine tool.

In the embodiment of the invention, a first execution machine tool is monitored in real time, when the first execution machine tool triggers an alarm of a deviation state, a processing process chain of the part is immediately acquired, the processing process progress and a process chain node are compared, an unfinished part in the process chain is intercepted based on the deviation node by precisely positioning the process deviation node, a processing process to be executed subsequently and a corresponding machine tool type requirement are determined, processing parameters of the finished process are recorded at the same time and used as reference data of the subsequent process, machine tools which have successfully executed the same process historically are screened out according to a production process database to form a machine tool list to be matched, historical process adaptation parameters of each machine tool are marked, and a set of machine tools to be matched is aimed at.

Specifically, in the embodiment of the invention, the steps of performing process matching according to a plurality of machine tools to be matched include:

Acquiring the working state of a machine tool to be matched in real time, and filtering the machine tool to be matched according to the working state to acquire an idle machine tool;

according to the production process database, the machining yield of the idle machine tool is called, and the machining yield is ordered to obtain a machining qualification sequence;

and matching the machine tools to be matched according to the machining qualified sequence, and completing process matching.

In the embodiment, working state data of each machine tool to be matched is collected, wherein the working state data comprises whether the machine tool to be matched is in a machining state currently, a load rate, the residual duration of a currently executed task and the like, the process is completed through real-time communication between a terminal master control system and a machine tool PLC control system, working procedure waiting caused by misjudging the non-idle machine tools is effectively avoided, timeliness of subsequent working procedure connection is guaranteed, judging errors caused by manual intervention are reduced, the load rate is 0% and the idle machine tools without the currently executed task are fetched, then machining yield data of the same working procedure is historically executed by the idle machine tools are fetched from a production process database, the data comprises the data of batch yield, critical dimension standard reaching rate, surface quality standard reaching rate and the like of the working procedure within about 3 months, the batch yield is taken as a core index, the duty ratio is set to be 70%, the duty ratio is set to be 20% in combination with the critical dimension standard reaching rate, the surface quality standard reaching rate is set, the duty ratio is 10%, comprehensive yield score is calculated, and the working standard reaching sequence is formed according to the score from high to low order, and the working standard reaching sequence is matched, and working procedure matching is completed.

The application also provides an automatic numerical control workshop transformation system, which comprises:

the processing chain acquisition module acquires a part processing scheme, and respectively acquires processing process chains of a plurality of processed parts according to the part processing scheme;

the candidate machine tool acquisition module is used for identifying and determining a part to be machined, selecting a machining process chain according to the part to be machined, and matching a candidate machine tool data set meeting the machining type of the part according to the machining process chain;

The database construction module is used for constructing a production process database, and carrying out self-adaptive screening on the candidate machine tool data set by combining the production process database to determine a first execution machine tool;

The machine tool redistribution module is used for sending the part to be processed to the first execution machine tool and monitoring the processing state of the part to be processed in real time based on the production process database;

If the machining state of the part to be machined is in a deviation state, an alarm is sent out, a machine tool reassignment mechanism is triggered, idle second execution machine tool information is obtained, and a workpiece is moved to a second execution machine tool according to the idle second execution machine tool information;

and continuously monitoring the processing state of the part to be processed until the part to be processed is processed.

The automatic numerical control workshop transformation method comprises the steps of S1 obtaining a part machining scheme, respectively obtaining machining process chains of a plurality of machined parts according to the part machining scheme, S2 identifying and determining the parts to be machined, selecting the machining process chains according to the parts to be machined, matching candidate machine tool data sets meeting the part machining types according to the machining process chains, S3 constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data sets in combination with the production process database to determine a first execution machine tool, S4 sending the parts to be machined to the first execution machine tool, monitoring the machining state of the parts to be machined in real time based on the production process database, sending an alarm if the machining state of the parts to be machined is in a deviation state, triggering a machine tool redistribution mechanism to obtain idle second execution machine tool information, moving a workpiece to the second execution machine tool according to the idle second execution machine tool information, and continuing to monitor the machining state of the parts to be machined until the parts to be machined are machined. The method comprises the steps of acquiring a part machining scheme and respectively acquiring machining process chains of a plurality of machined parts, solving the problem that the prior art is disjointed due to the fact that a common process is used or a process is set up in a scattered manner, the problems that the process chains are different from the parts to be machined, and complex machining requirements of multiple varieties and multiple procedures are caused in the process chains are solved, selecting a candidate machine tool data set corresponding to the machining process chains and meeting the machining types of the parts according to matching of the process chains after identifying the parts to be machined, solving the problem that machining equipment is selected only by means of basic data statistics in the prior art, the performance of the machine tool is not related to the specific process chains of the parts, constructing a production process database, carrying out self-adaptive screening on the candidate machine tool data set by combining the database to determine a first execution machine tool, solving the problem that the prior art ignores individual differences such as the running state, the machining precision, the service life cycle and the like of the machine tool, and mainly uses single-bed manual control, solving the problem that the equipment utilization rate is low due to one machine is solved, meanwhile, the limitation of local automation of single equipment is overcome, a data driving basis is provided for a plurality of equipment is broken through the database, and the machine tool redistribution mechanism can break through the main flow single-bed manual control, efficiency is improved, and the bottleneck loss caused by the dynamic equipment scheduling is avoided.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. An automated numerical control plant retrofit method, comprising:

s1, acquiring a part machining scheme, and respectively acquiring machining process chains of a plurality of machined parts according to the part machining scheme;

S2, identifying and determining a part to be machined, selecting a machining process chain according to the part to be machined, and matching a candidate machine tool data set meeting the machining type of the part according to the machining process chain;

s3, constructing a production process database, and carrying out self-adaptive screening on the candidate machine tool data set by combining the production process database to determine a first execution machine tool;

s4, the part to be processed is sent to the first execution machine tool, and the processing state of the part to be processed is monitored in real time based on the production process database;

If the machining state of the part to be machined is in a deviation state, an alarm is sent out, a machine tool reassignment mechanism is triggered, idle second execution machine tool information is obtained, and a workpiece is moved to a second execution machine tool according to the idle second execution machine tool information;

And continuously monitoring the processing state of the part to be processed until the part to be processed is processed.

2. The automated numerically controlled shop adaptation method according to claim 1, wherein,

The identifying and determining the part to be machined comprises:

analyzing the part to be processed;

collecting processing indexes of the part to be processed, wherein the processing indexes comprise precision requirement information, processing time and processing yield;

wherein the processing index of the part to be processed is input by a user.

3. The automated numerically controlled shop adaptation method according to claim 2, wherein adaptively screening the candidate machine tool dataset in conjunction with the production process database comprises:

Searching the production process database based on the precision requirement information as a search condition, and matching the precision requirement with the candidate machine tool data set according to a search result to obtain a first candidate machine tool subset;

Searching the production process database based on the processing time as a search condition, and matching the processing time with the candidate machine tool data set according to a search result to obtain a second candidate machine tool subset;

And searching the production process database based on the processing yield as a search condition, and according to a search result, performing processing yield matching with the candidate machine tool data set to determine a first execution machine tool.

4. The automated numerically controlled shop adaptation method according to claim 1, wherein the step of constructing a production process database comprises:

Respectively collecting historical machine tool performance parameters, rated life cycle and historical service life of a plurality of numerical control machine tools and historical part performance requirements of the machined parts;

The historical machine tool performance parameters comprise historical machining time and historical machining yield of each machined part machined by each numerical control machine tool respectively, and the historical part performance requirements comprise historical precision requirements of the machined parts;

Acquiring the service life deviation of the machine tool according to the rated service life period and the historical service life of each numerical control machine tool;

and respectively establishing a combined index with each numerical control machine tool, the historical machine tool performance parameters, the historical part performance requirements, the rated life cycle, the historical service life and the machine tool life deviation, and constructing a production process database.

5. The automated numerically controlled shop adaptation method according to claim 4, wherein the iterative optimization of the production process database comprises:

and recording part production data according to a real-time monitoring result, inputting the part production data into the production process database for database updating until the iteration times reach preset times, and completing the iterative optimization of the production process database.

6. The automated numerically controlled shop adaptation method according to claim 1, wherein the step of adaptively screening the candidate machine tool dataset in conjunction with the production process database comprises:

Determining historical machine tool performance parameters of each candidate machine tool according to the production process database, and dividing the historical machine tool performance parameters into a plurality of groups of performance data sets, wherein the performance data sets are data sets of each type of machining performance data;

And performing performance weight distribution on the performance requirements of the part to be processed, and screening a plurality of groups of performance data sets according to the performance weight distribution result as a reference to determine a first execution machine tool.

7. The automated numerically controlled shop adaptation method according to claim 6, wherein the step of assigning a performance weight to the performance requirement of the part to be machined comprises:

Extracting the historical part performance requirements of the part to be processed according to the production process database, and setting initial performance weights according to the historical part performance requirements;

Disassembling the processing technology chain of the part to be processed to obtain a rough processing stage and a finish processing stage, respectively setting main processing targets for the rough processing stage and the finish processing stage, respectively correcting the initial performance weights according to the main processing targets of different stages, and obtaining stage performance weights;

Acquiring equipment life cycle data of the candidate machine tool according to the production process database, judging whether the corresponding candidate machine tool is in a healthy state according to the life cycle data, if so, maintaining the stage performance weight, and if not, adjusting the stage performance weight to acquire a stage optimization weight;

And screening the candidate machine tool data set according to the phase optimization weight and the phase performance weight to obtain a first execution machine tool.

8. The automated numerically controlled shop adaptation method according to claim 1, wherein the step of triggering machine tool reassignment when the first execution machine tool is in an off-set state comprises:

determining a procedure deviation node according to the processing technology chain, and determining a subsequent processing machine tool and a processing procedure according to the procedure deviation node;

Searching the processing procedure according to the production process database, searching historical execution machine tools of the processing procedure, and obtaining a plurality of machine tools to be matched;

and performing procedure matching according to the plurality of machine tools to be matched, and determining a redistribution machine tool.

9. The automated numerically controlled shop adaptation method according to claim 7, wherein the step of performing process matching according to a number of the machine tools to be matched comprises:

Acquiring the working state of the machine tool to be matched in real time, and filtering the machine tool to be matched according to the working state to acquire an idle machine tool;

according to the production process database, the machining yield of the idle machine tool is called, and the machining yield is ordered to obtain a machining qualification sequence;

and matching the machine tools to be matched according to the processing qualified sequence, and completing process matching.

10. An automated numerically controlled shop retrofit system, the system comprising:

The processing chain acquisition module is used for acquiring a part processing scheme and respectively acquiring processing process chains of a plurality of processed parts according to the part processing scheme;

The candidate machine tool acquisition module is used for identifying and determining a part to be machined, selecting the machining process chain according to the part to be machined, and matching a candidate machine tool data set meeting the machining type of the part according to the machining process chain;

the database construction module is used for constructing a production process database, and carrying out self-adaptive screening on the candidate machine tool data set by combining the production process database to determine a first execution machine tool;

the machine tool redistribution module is used for sending the part to be processed to the first execution machine tool and monitoring the processing state of the part to be processed in real time based on the production process database;

If the machining state of the part to be machined is in a deviation state, an alarm is sent out, a machine tool reassignment mechanism is triggered, idle second execution machine tool information is obtained, and a workpiece is moved to a second execution machine tool according to the idle second execution machine tool information;

And continuously monitoring the processing state of the part to be processed until the part to be processed is processed.