CN116681386A - Server scheduling control method, system, terminal and storage medium - Google Patents
Server scheduling control method, system, terminal and storage medium Download PDFInfo
- Publication number
- CN116681386A CN116681386A CN202310530262.8A CN202310530262A CN116681386A CN 116681386 A CN116681386 A CN 116681386A CN 202310530262 A CN202310530262 A CN 202310530262A CN 116681386 A CN116681386 A CN 116681386A
- Authority
- CN
- China
- Prior art keywords
- time
- production
- abnormal
- server
- scheduling
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000004519 manufacturing process Methods 0.000 claims abstract description 187
- 238000012545 processing Methods 0.000 claims abstract description 148
- 230000002159 abnormal effect Effects 0.000 claims abstract description 141
- 238000012360 testing method Methods 0.000 claims abstract description 83
- 238000012216 screening Methods 0.000 claims abstract description 67
- 238000012795 verification Methods 0.000 claims abstract description 47
- 230000005856 abnormality Effects 0.000 claims description 33
- 238000003745 diagnosis Methods 0.000 claims description 32
- 238000012423 maintenance Methods 0.000 claims description 28
- 238000012552 review Methods 0.000 claims description 9
- 238000012163 sequencing technique Methods 0.000 claims description 9
- 238000004590 computer program Methods 0.000 claims description 6
- 230000006978 adaptation Effects 0.000 claims description 2
- 238000007726 management method Methods 0.000 abstract description 8
- 238000013523 data management Methods 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 10
- 230000008859 change Effects 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 5
- 238000004891 communication Methods 0.000 description 5
- 238000012790 confirmation Methods 0.000 description 5
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000001360 synchronised effect Effects 0.000 description 3
- 238000000605 extraction Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- 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]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06316—Sequencing of tasks or work
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Quality & Reliability (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Data Mining & Analysis (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Automation & Control Theory (AREA)
- General Factory Administration (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of server production, and particularly provides a server production scheduling control method, a system, a terminal and a storage medium, wherein the method comprises the following steps: confirming that the material configuration of the base line of the server fails the matching verification, and acquiring an abnormal event which causes the matching verification to fail; acquiring average processing time of an abnormal event; extracting the shortest test time and the screening abnormal time from the historical order processing data of the same configuration server; calculating a scheduling time based on the average processing time, the shortest test time, and the screening anomaly time; comparing the production scheduling time with the original expected production time of the factory intelligent manufacturing system, and granting the factory intelligent manufacturing system permission to schedule production if the production scheduling time does not exceed the original expected production time. The invention can manage the server scheduling right limit based on the checking result, avoids the loss caused by server misoperation, has scientific and reasonable management flow, and improves the data management quality before server scheduling.
Description
Technical Field
The invention belongs to the technical field of server production, and particularly relates to a server production scheduling control method, a system, a terminal and a storage medium.
Background
In the production process of the server, after business ordering, maintenance personnel maintain corresponding production instructions to a diagnosis system, and after confirming that maintenance is finished, the maintenance personnel can take materials for formal online production. In addition, in the server production process, the client can join in own test program, mainly perform configuration check and performance pressure test of the server, so as to confirm that the produced server meets the expectations of the client. The configuration checking part of the client test program has a severe requirement on various configuration details of the server, and often when the client test program is used for configuration checking of the server, the operation failure of the whole client test program is often caused due to inaccuracy and incompleteness of a program configuration checking file, so that the test efficiency is influenced, and the productivity and the shipment progress are influenced. It is necessary to check and screen the configuration checking portion of the customer test program before it is put into use to ensure its accuracy and completeness.
The existing server scheduling control method is to compare and screen according to BOM information of orders, maintained instruction information and configuration files of client test programs, after screening fails, mail reminds corresponding diagnosis test persons, after confirming that abnormality exists, the diagnosis test persons send mails to corresponding front-end interface persons for confirmation and processing, and mail reminds scheduling staff of corresponding factories to pause scheduling.
The existing method has management loopholes, has no limit on the production scheduling authority, and can easily schedule orders for production by mistake if production scheduling staff cannot synchronously mark the information that the orders are not scheduled temporarily in an MES system, so that production loss is caused. And even if the MES system is synchronously marked, the scheduling staff cannot schedule the suspended orders for prediction, and schedule the scheduling after the abnormality is relieved.
Disclosure of Invention
The invention provides a server scheduling control method, a system, a terminal and a storage medium for solving the technical problems.
In a first aspect, the present invention provides a server scheduling control method, including:
confirming that the material configuration of the base line of the server fails the matching verification, and acquiring an abnormal event which causes the matching verification to fail;
acquiring average processing time of an abnormal event;
extracting the shortest test time and the screening abnormal time from the historical order processing data of the same configuration server;
calculating a scheduling time based on the average processing time, the shortest test time, and the screening anomaly time;
comparing the production scheduling time with the original expected production time of the factory intelligent manufacturing system, and granting the factory intelligent manufacturing system permission to schedule production if the production scheduling time does not exceed the original expected production time.
In an alternative embodiment, confirming that the server baseline material configuration fails the matchability check, acquiring an exception event that results in the matchability check failing, includes:
acquiring a bill of materials, instruction maintenance information and a baseline configuration file based on the server order information;
carrying out matching verification on the bill of materials, the instruction maintenance information and the baseline configuration file;
if the verification is not passed, diagnosis processing is carried out on the abnormal event which causes the verification result.
In an alternative embodiment, obtaining the average processing time of the exception event includes:
counting screening abnormal time and rechecking passing time of historical abnormal events, wherein the abnormal events comprise baseline abnormal events, instruction abnormal events, material abnormal allocation events and physical abnormal removal events;
the method for calculating the average processing duration Tb of the abnormal event comprises the following steps:
screening of the ith abnormal event abnormal time t 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of the abnormal event histories of the client test program, T bi Processing time length sigma for ith abnormal event<=5%, then the abnormal event history average processing time length T b ＝T b1
If sigma>5, processing all abnormal events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th integer of the total number n of the abnormal events tested by the client, T bj Is T bi And (5) the j-th abnormal event processing time length after the sorting from big to small.
In an alternative embodiment, extracting the shortest test time and screening for anomaly time from historical order processing data of the same configuration server includes:
acquiring historical flow record data of a specified number of server orders configured in the same way;
the method comprises the steps of extracting test time from production test starting to test item of a client test program from historical flow record data, and screening the shortest test time with the shortest duration from a plurality of test times;
and generating screening abnormal time in an average mode based on the time used for screening abnormal events in the historical flow record data of the orders.
In an alternative embodiment, calculating the production time based on the average processing time, the shortest test time, and the screening anomaly time includes:
calculating a difference value between the average processing time and the shortest testing time, and outputting the sum of the difference value and the screening abnormal time as the fastest online testing time;
And outputting the difference value between the fastest online test time and a preset fixed parameter as the scheduling time.
In an alternative embodiment, before calculating the difference between the average processing time and the shortest test time, the method further comprises:
judging whether the abnormal event is abnormal material:
if yes, selecting a smaller value from the average processing time of the material abnormality adaptation event and the average processing time of the physical abnormality removal event as the average processing time.
In an alternative embodiment, comparing the production schedule with an original estimated production time of the factory intelligent manufacturing system, granting the factory intelligent manufacturing system permission to schedule production if the production schedule does not exceed the original estimated production time, comprising:
extracting an original estimated production time from a factory intelligent manufacturing system;
judging whether the production time does not exceed the original predicted production time:
if yes, granting the factory intelligent manufacturing system with the authority to arrange the production, and displaying and outputting the production time;
if not, the factory intelligent manufacturing system is not granted the authority to schedule production.
In a second aspect, the present invention provides a server scheduling control system, including:
the abnormality checking module is used for confirming that the material configuration of the server baseline fails the matching verification and acquiring an abnormal event which causes the matching verification to fail;
The first acquisition module is used for acquiring the average processing time of the abnormal event;
the second acquisition module is used for extracting the shortest test time and screening abnormal time from the historical order processing data of the same configuration server;
the scheduling prediction module is used for calculating scheduling time based on the average processing time, the shortest testing time and the screening abnormal time;
and the permission control module is used for comparing the production scheduling time with the original expected production time of the intelligent factory manufacturing system, and granting permission for the intelligent factory manufacturing system to schedule production scheduling if the production scheduling time does not exceed the original expected production time.
In an alternative embodiment, the anomaly checking module includes:
the object acquisition unit is used for acquiring a bill of materials, instruction maintenance information and a baseline configuration file based on the server order information;
the matching verification unit is used for carrying out matching verification on the bill of materials, the instruction maintenance information and the baseline configuration file;
and the abnormality diagnosis unit is used for diagnosing and processing the abnormality factors which cause the verification result if the verification is not passed.
In an alternative embodiment, the first obtaining module is specifically configured to:
counting screening abnormal time and rechecking passing time of historical abnormal events, wherein the abnormal events comprise baseline abnormal events, instruction abnormal events, material abnormal allocation events and physical abnormal removal events;
The method for calculating the average processing duration Tb of the abnormal event comprises the following steps:
screening of the ith abnormal event abnormal time t 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of the abnormal event histories of the client test program, T bi Processing time length sigma for ith abnormal event<=5%, then the abnormal event history average processing time length T b ＝T b1
If sigma>5, processing all abnormal events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th integer of the total number n of the abnormal events tested by the client, T bj Is T bi And (5) the j-th abnormal event processing time length after the sorting from big to small.
In an alternative embodiment, the second acquisition module includes:
the historical data acquisition unit is used for acquiring the historical flow record data of the designated number of the same-configuration server orders;
the test time acquisition unit is used for extracting the test time from the production test to the test item of the client test program from the historical flow record data and screening the shortest test time with the shortest duration from the plurality of test times;
the screening time acquisition unit is used for generating screening abnormal time in an average mode based on the time used for screening the abnormal event in the historical flow record data of the orders.
In an alternative embodiment, the scheduling prediction module includes:
the first calculation unit is used for calculating the difference value between the average processing time and the shortest test time and outputting the sum of the difference value and the screening abnormal time as the fastest online test time;
the second calculation unit is used for outputting the difference value between the fastest online test time and a preset fixed parameter as the scheduling time.
In an alternative embodiment, the scheduling prediction module further comprises:
the event type judging unit is used for judging whether the abnormal event is abnormal material or not;
and the processing time determining unit is used for selecting a smaller value from the average processing time of the material abnormality change event and the average processing time of the physical abnormality removing event as the average processing time if the abnormal event is the material abnormality.
In an alternative embodiment, the rights control module includes:
an original extraction unit for extracting an original predicted production time from the factory intelligent manufacturing system;
the time judging unit is used for judging whether the production scheduling time does not exceed the original expected production time;
the authority granting unit is used for granting the authority of the factory intelligent manufacturing system for scheduling the production scheduling if the production scheduling time does not exceed the original expected production time, and displaying and outputting the production scheduling time;
And the refusal granting unit is used for not granting the authority of the factory intelligent manufacturing system to arrange the production scheduling if the production scheduling time exceeds the original expected production time.
In a third aspect, a terminal is provided, including:
a processor, a memory, wherein,
the memory is used for storing a computer program,
the processor is configured to call and run the computer program from the memory, so that the terminal performs the method of the terminal as described above.
In a fourth aspect, there is provided a computer storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the method of the above aspects.
The server scheduling control method, the system, the terminal and the storage medium have the advantages that the server material configuration is checked before server scheduling, the scheduling time is calculated based on the checking result, the scheduling time is compared with the original estimated production time, the server scheduling property limit is managed based on the comparison result, loss caused by server misoperation is avoided, the management flow is scientific and reasonable, and the data management quality before server scheduling is improved.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a schematic flow chart of a method of one embodiment of the invention.
Fig. 2 is another schematic flow chart of a method of one embodiment of the invention.
FIG. 3 is a schematic block diagram of a system of one embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make the technical solution of the present invention better understood by those skilled in the art, the technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
The following explains key terms appearing in the present invention.
Business ordering: the business person places a production order.
Production instructions: a series of software and hardware requirements to be followed in the production process.
Diagnostic system: an automated test system in a production process.
Base line control system: a system for screening configuration information for a production order.
Order BOM: material information used in the production order.
Instruction problem: the content of the production instruction does not meet the actual requirements of customers.
The material consumption problem: the material in the order BOM does not meet the actual needs of the customer.
Baseline problem: the benchmark set in the configuration file of the client test program is incorrect.
MES system: factory intelligent manufacturing system, business order, maintenance confirmation, arrangement production (scheduling) and the like.
The server scheduling control method provided by the embodiment of the invention is executed by the computer equipment, and correspondingly, the server scheduling control system is operated in the computer equipment.
FIG. 1 is a schematic flow chart of a method of one embodiment of the invention. The execution body of fig. 1 may be a server scheduling control system. The order of the steps in the flow chart may be changed and some may be omitted according to different needs.
As shown in fig. 1, the method includes:
step 110, confirming that the server baseline material configuration fails the matching verification, and acquiring an abnormal event which causes the matching verification to fail;
step 120, obtaining the average processing time of the abnormal event;
step 130, extracting the shortest test time and the screening abnormal time from the historical order processing data of the same configuration server;
step 140, calculating the production time based on the average processing time, the shortest test time and the screening abnormal time;
and step 150, comparing the production scheduling time with the original expected production time of the intelligent manufacturing system of the factory, and granting the intelligent manufacturing system of the factory the authority to schedule production scheduling if the production scheduling time does not exceed the original expected production time.
In order to facilitate understanding of the present invention, the following describes the server scheduling control method according to the present invention in conjunction with the process of performing authority management on server scheduling in the embodiment.
Specifically, referring to fig. 2, the server scheduling control method includes:
s1, acquiring a bill of materials, instruction maintenance information and a baseline configuration file based on server order information.
Querying a bill of materials from the factory intelligent manufacturing system based on the server order information; the method comprises the steps of maintaining instruction information to a record database in advance according to production instructions of orders, and calling corresponding instruction maintenance information from the record database according to the order information; and calling the baseline configuration file of the corresponding client test program from the configuration storage database based on the order information.
Specifically, after business ordering, the order BOM is automatically transferred to a diagnosis system database, and maintenance personnel maintain instruction information to the diagnosis system database according to production instructions in the order. At this point the scheduling function option remains in the no open-authority state (gray non-clickable state 0).
S2, carrying out matching verification on the bill of materials, the instruction maintenance information and the baseline configuration file.
And after receiving the instruction maintenance completion information, comparing and screening BOM information (bill of materials) transmitted by the MES system, instruction maintenance information in the diagnosis system and a baseline configuration file of the client test program.
And S3, if the verification is passed, first information is sent to the factory intelligent manufacturing system, and the first information is used for granting the factory intelligent manufacturing system with the limit of the intellectual property.
Specifically, the bill of materials, the instruction maintenance information and the baseline configuration file are subjected to matching verification, a verification result is synchronized to the MES system, the state of the scheduling function option in the MES system is switched to a blue clickable state 1, and scheduling personnel is allowed to click into scheduling production.
And S4, if the verification is not passed, diagnosing and processing abnormal factors which cause the verification result.
S401, confirming a verification result.
Sending the verification result to a verification terminal, and sending verification prompt information to an address bound by the verification terminal; receiving a confirmation result returned by the verification terminal; if the verification result is that the neglect is abnormal, updating the verification result to pass the verification, and generating first information to the factory intelligent manufacturing system; if the confirmation result is that the abnormality exists, diagnosing and processing the abnormality factor which leads to the verification result.
Specifically, the system processing node flows to the corresponding diagnosis test responsible person and reminds the mail, the diagnosis test responsible person confirms that the problem is negligible, misjudgment and the like, and clicks a pass button to change the screening result into pass, information is synchronized to the MES system, and a scheduling button in the MES system is set to be in a blue clickable state 1 to allow scheduling personnel to click to enter scheduling production. The diagnosis test responsible person confirms that the abnormality exists, clicks an abnormality button, the system processing node flows to the corresponding front-end interface personnel and reminds the mail, the abnormality information is simultaneously transmitted to the MES system, the order state of the MES system is displayed as baseline screening abnormality, and the scheduling button keeps a gray non-clickable state 0 and reminds the corresponding factory scheduling personnel by the mail.
S402, performing abnormality diagnosis.
Searching a target diagnosis terminal based on the server order information; the bill of materials, the instruction maintenance information, the baseline configuration file and unmatched abnormal data are sent to a target diagnosis terminal; sending diagnosis prompt information to an address bound by a target diagnosis terminal; and receiving a diagnosis result returned by the target diagnosis terminal, and analyzing the diagnosis result.
Specifically, the target diagnostic terminal refers to the terminal of the front-end interface personnel responsible for this order. The diagnostic result may be an empirically determined by the front-end interface personnel.
In other embodiments of the present invention, the target diagnostic terminal may analyze and determine, based on the diagnostic rule, the bill of materials, the instruction maintenance information, and the mismatch data of the baseline configuration file, so as to obtain the diagnostic result.
S403 performs exception handling based on the diagnosis result.
(1) If the diagnosis result is an instruction problem, based on the instruction problem solution extracted from the diagnosis result, an instruction update request is sent to the corresponding instruction problem processing terminal, and after a new version instruction returned by the instruction problem processing terminal is received, the new version instruction is updated to the instruction maintenance information, so that a processing completion mark is generated.
The exception is an instruction problem, a button of the instruction problem is clicked and notes describe detailed problems and solutions, tasks are assigned to corresponding instruction responsible persons, a system processing node flows to the assigned instruction responsible persons and email is reminded, the instruction responsible persons update the instructions according to requirements, the button of the instruction update is clicked after the instruction update, the system processing node flows to corresponding business responsible persons and email is reminded, the instruction corresponding to a business update order is clicked to be completed, the system flows to corresponding factory maintenance personnel and email is reminded, the maintenance personnel re-maintains the order instruction, click confirmation is carried out after maintenance is completed, and S2 re-screening is returned.
(2) If the diagnosis result is a material problem, sending the diagnosis result to a corresponding material problem processing terminal, and receiving a material processing scheme fed back by the material problem processing terminal; analyzing the material treatment scheme; if the material processing scheme is to cancel the order, all data related to the server order information are moved to an order canceling database, and cancel notification information is sent to the factory intelligent manufacturing system, so that the factory intelligent manufacturing system changes the state of the server order information into a cancel state; if the material processing scheme is to change the material configuration, after receiving the material configuration change completion prompt information sent by the material problem processing terminal, generating a processing completion mark.
The anomaly is a material problem, the material problem is clicked and detailed problems and solutions are described by remarks, tasks are assigned to corresponding business responsible persons, the system processing nodes flow to the assigned business responsible persons and mail is reminded, and the business responsible persons change or withdraw orders according to requirements. The order needs to be changed, the business responsible person clicks 'change complete' after updating the BOM, the system flows to corresponding plant maintenance personnel and reminds the mail, the maintenance personnel re-maintains the order instruction, clicks 'review' after maintenance is completed, and the S2 re-screening is returned. If the order needs to be cancelled, after the business responsible person confirms, clicking the order removing, synchronizing information to the MES system, displaying the order state in the MES system as the order removing, and no longer allocating production.
(3) If the diagnosis result is the baseline problem, sending the diagnosis result to the corresponding baseline problem processing terminal, and generating a processing completion mark after receiving a new baseline file fed back by the baseline problem processing terminal.
The abnormality is a baseline problem, the baseline problem is clicked and detailed problems and solutions are described by remarks, the problems and solutions are assigned to corresponding diagnosis test responsible persons, the system processing nodes flow to the assigned diagnosis test responsible persons and prompt the mail, after the diagnosis test responsible persons receive new baseline files provided by front-end interface persons, the baseline files are updated to the diagnosis system and the baseline management and control system, the review is clicked, and the step S2 is returned to for rescreening.
S4, special treatment.
Receiving an online application request and an authority certification file sent by an upper management terminal; verifying the permission proving file based on a preset key information verification rule; if the authority identification file passes the verification, first information is sent to a factory intelligent manufacturing system, the first information is used for granting the factory intelligent manufacturing system with the production scheduling authority, and a process file is recorded; and if the authority identification file fails to pass the verification, returning prompt information for failing to pass the request to the upper management terminal.
Specifically, if special treatment is needed to be performed on line in advance, detailed problems and solutions are described in remarks, a button for applying for on line is clicked, a system processing node flows to a corresponding factory production manager and email reminding is performed, after the corresponding factory production manager clicks 'consent', information is synchronized to an MES system, a production scheduling button is changed into a blue clickable state 1 and email reminding corresponding factory production scheduling personnel is performed, and production scheduling is allowed; if the corresponding factory production manager clicks the reject, the system processing node re-flows to the corresponding front-end interface person, and the flow returns to 2.2.1.6/2.2.1.8 for continuous processing.
S5, acquiring average processing time of the abnormal event.
Counting screening abnormal time and rechecking passing time of historical abnormal events, wherein the abnormal events comprise baseline abnormal events, instruction abnormal events, material abnormal allocation events and physical abnormal removal events;
the method for calculating the average processing duration Tb of the abnormal event comprises the following steps:
screening of the ith abnormal event abnormal time t 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of the abnormal event histories of the client test program, T bi Processing time length sigma for ith abnormal event<=5%, then the abnormal event history average processing time length T b ＝T b1
If sigma>5, processing all abnormal events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th integer of the total number n of the abnormal events tested by the client, T bj Is T bi And (5) the j-th abnormal event processing time length after the sorting from big to small.
For example, a baseline question average processing duration T b Instruction issue average processing duration T c Material problem improvement and average treatment duration T m Material problem single-removing average processing time length T r The calculation formula is as follows:
1)T b screening abnormal time t of ith baseline event in historical events of client test program 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of baseline event histories, T bi And processing the time length for the ith event.
If sigma<=5%, then the baseline event history averages the processing duration T b ＝T b1
If sigma>5, processing all baseline events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th of the total number of baseline events n of the client test program, T bj Is T bi The j-th event processing time length after sorting from big to small
2)T c In the history event of the client test program, the ith instruction event screens abnormal time t 1 Review the transit time t 2 Processing duration T ci ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the guest test program instruction eventTotal history, T ci For the ith event processing duration
If sigma<=5%, then the instruction event history averages the processing time period T c ＝T c1
If sigma>5, processing all instruction event processing time periods T ci Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again c ＝T c2
Wherein m is the 1/3 th of the total number of instruction events n of the client test program, T cj Is T ci The j-th event processing time length after sorting from big to small
3)T m In the history event of the client test program, the ith material change event is screened for abnormal time t 1 Rechecking the passing time t after the matching 2 Change the processing time length T mi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all processing durations of the events is as follows:
wherein n is the total number of instruction event histories of the client test program, T mi For the ith event processing duration
If sigma<=5%, then the instruction event history averages the processing time period T m ＝T m1
If sigma>5, processing all instruction event processing time periods T mi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again m ＝T m2
Wherein m is the 1/3 th of the total number of instruction events n of the client test program, T mj Is T mi And (5) the j-th event processing time length after the sorting from big to small.
4)T r In the history event of the client test program, the ith material withdrawal event is used for screening abnormal time t 1 Time T2 for removing the bill, and time period T for removing the bill ri ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of instruction event histories of the client test program, T ri For the ith event processing duration
If sigma<=5%, then the instruction event history averages the processing time period T r ＝T r1
If sigma>5, processing all instruction event processing time periods T ri Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again r ＝T r2
Wherein m is the 1/3 th of the total number of instruction events n of the client test program, T rj Is T ri And (5) the j-th event processing time length after the sorting from big to small.
And S6, extracting the shortest test time and the abnormal screening time from the historical order processing data of the same configuration server.
Acquiring historical flow record data of a specified number of server orders configured in the same way; the method comprises the steps of extracting test time from production test starting to test item of a client test program from historical flow record data, and screening the shortest test time with the shortest duration from a plurality of test times; and generating screening abnormal time in an average mode based on the time used for screening abnormal events in the historical flow record data of the orders.
For example, the shortest time period T1 from the start of the production test to the running of the test item of the customer test program for the same configuration of the near 5 historical orders is obtained, for example, the time period from the start of the test ts to the running of the test item tc of the customer test program for the machine n in the order a is tn=tc-ts, tn of all machines in the near 5 historical orders is sequentially obtained, and the minimum value is taken as the shortest time period T1.
And S7, calculating the production scheduling time based on the average processing time, the shortest testing time and the abnormal screening time.
Calculating a difference value between the average processing time and the shortest testing time, and outputting the sum of the difference value and the screening abnormal time as the fastest online testing time; and outputting the difference value between the fastest online test time and a preset fixed parameter as the scheduling time.
For example, when the screening abnormality is a baseline abnormality: MES original predicted production time to, confirmed screening abnormal time te, and the fastest online test time is ts=T b -t1+te, recommended production time ta=ts-4;
when the screening abnormality is an instruction abnormality, the following steps are performed: MES original predicted production time to, confirmed screening abnormal time te, and the fastest online test time is ts=T c -t1+te, recommended production time ta=ts-4;
when the screening abnormality is a material abnormality, the following steps are: MES original predicted production time to, confirm screening abnormality time te, T as described above m And T r Take the minimum value T mr The fastest online test time is ts=t mr T1+te, recommended production time ta=ts-4.
S8, comparing the production scheduling time with the original expected production time of the intelligent factory manufacturing system, and granting the intelligent factory manufacturing system with the authority to schedule production scheduling if the production scheduling time does not exceed the original expected production time.
Extracting an original estimated production time from a factory intelligent manufacturing system; judging whether the production time does not exceed the original predicted production time: if yes, granting the factory intelligent manufacturing system with the authority to arrange the production, and displaying and outputting the production time; if not, the factory intelligent manufacturing system is not granted the authority to schedule production.
For example, if ts > to, then the scheduling button remains in gray non-clickable state 0 and shows the suggested scheduling time ta; if ts < to, the scheduling button is displayed as an orange clickable state 2, prompting the scheduling personnel not to schedule in advance, and displaying the recommended scheduling time ta.
In some embodiments, the server production control system 300 may include a plurality of functional modules comprised of computer program segments. The computer program of each program segment in the server production control system 300 may be stored in a memory of a computer device and executed by at least one processor to perform (see fig. 1 for details) the functions of server production control.
In this embodiment, the server production control system 300 may be divided into a plurality of functional modules according to the functions performed by the system, as shown in fig. 3. The functional module may include: an anomaly checking module 310, a first acquisition module 320, a second acquisition module 330, a production prediction module 340, and a rights control module 350. The module referred to in the present invention refers to a series of computer program segments capable of being executed by at least one processor and of performing a fixed function, stored in a memory. In the present embodiment, the functions of the respective modules will be described in detail in the following embodiments.
An anomaly checking module 310, configured to confirm that the server baseline material configuration fails the matching verification, and obtain an anomaly event that causes the matching verification to fail;
a first obtaining module 320, configured to obtain an average processing time of the abnormal event;
a second obtaining module 330, configured to extract a shortest test time and a screening abnormal time from the historical order processing data of the same configuration server;
a scheduling prediction module 340 for calculating scheduling time based on the average processing time, the shortest test time, and the screening anomaly time;
and the authority control module 350 is used for comparing the production scheduling time with the original expected production time of the factory intelligent manufacturing system, and granting the factory intelligent manufacturing system with the authority of scheduling production if the production scheduling time does not exceed the original expected production time.
Alternatively, as one embodiment of the present invention, the anomaly checking module includes:
the object acquisition unit is used for acquiring a bill of materials, instruction maintenance information and a baseline configuration file based on the server order information;
the matching verification unit is used for carrying out matching verification on the bill of materials, the instruction maintenance information and the baseline configuration file;
and the abnormality diagnosis unit is used for diagnosing and processing the abnormality factors which cause the verification result if the verification is not passed.
Optionally, as an embodiment of the present invention, the first obtaining module is specifically configured to:
counting screening abnormal time and rechecking passing time of historical abnormal events, wherein the abnormal events comprise baseline abnormal events, instruction abnormal events, material abnormal allocation events and physical abnormal removal events;
the method for calculating the average processing duration Tb of the abnormal event comprises the following steps:
screening of the ith abnormal event abnormal time t 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the guestUser test program abnormal event history total number, T bi Processing time length sigma for ith abnormal event<=5%, then the abnormal event history average processing time length T b ＝T b1
If sigma>5, processing all abnormal events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th integer of the total number n of the abnormal events tested by the client, T bj Is T bi And (5) the j-th abnormal event processing time length after the sorting from big to small.
Optionally, as an embodiment of the present invention, the second obtaining module includes:
the historical data acquisition unit is used for acquiring the historical flow record data of the designated number of the same-configuration server orders;
The test time acquisition unit is used for extracting the test time from the production test to the test item of the client test program from the historical flow record data and screening the shortest test time with the shortest duration from the plurality of test times;
the screening time acquisition unit is used for generating screening abnormal time in an average mode based on the time used for screening the abnormal event in the historical flow record data of the orders.
Optionally, as an embodiment of the present invention, the scheduling prediction module includes:
the first calculation unit is used for calculating the difference value between the average processing time and the shortest test time and outputting the sum of the difference value and the screening abnormal time as the fastest online test time;
the second calculation unit is used for outputting the difference value between the fastest online test time and a preset fixed parameter as the scheduling time.
Optionally, as an embodiment of the present invention, the scheduling prediction module further includes:
the event type judging unit is used for judging whether the abnormal event is abnormal material or not;
and the processing time determining unit is used for selecting a smaller value from the average processing time of the material abnormality change event and the average processing time of the physical abnormality removing event as the average processing time if the abnormal event is the material abnormality.
Optionally, as an embodiment of the present invention, the rights control module includes:
an original extraction unit for extracting an original predicted production time from the factory intelligent manufacturing system;
the time judging unit is used for judging whether the production scheduling time does not exceed the original expected production time;
the authority granting unit is used for granting the authority of the factory intelligent manufacturing system for scheduling the production scheduling if the production scheduling time does not exceed the original expected production time, and displaying and outputting the production scheduling time;
and the refusal granting unit is used for not granting the authority of the factory intelligent manufacturing system to arrange the production scheduling if the production scheduling time exceeds the original expected production time.
Fig. 4 is a schematic structural diagram of a terminal 400 according to an embodiment of the present invention, where the terminal 400 may be used to execute the server scheduling control method according to the embodiment of the present invention.
The terminal 400 may include: processor 410, memory 420, and communication module 430. The components may communicate via one or more buses, and it will be appreciated by those skilled in the art that the configuration of the server as shown in the drawings is not limiting of the invention, as it may be a bus-like structure, a star-like structure, or include more or fewer components than shown, or may be a combination of certain components or a different arrangement of components.
The memory 420 may be used to store instructions for execution by the processor 410, and the memory 420 may be implemented by any type of volatile or nonvolatile memory terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk. The execution of the instructions in memory 420, when executed by processor 410, enables terminal 400 to perform some or all of the steps in the method embodiments described below.
The processor 410 is a control center of the storage terminal, connects various parts of the entire electronic terminal using various interfaces and lines, and performs various functions of the electronic terminal and/or processes data by running or executing software programs and/or modules stored in the memory 420, and invoking data stored in the memory. The processor may be comprised of an integrated circuit (Integrated Circuit, simply referred to as an IC), for example, a single packaged IC, or may be comprised of a plurality of packaged ICs connected to the same function or different functions. For example, the processor 410 may include only a central processing unit (Central Processing Unit, simply CPU). In the embodiment of the invention, the CPU can be a single operation core or can comprise multiple operation cores.
And a communication module 430, configured to establish a communication channel, so that the storage terminal can communicate with other terminals. Receiving user data sent by other terminals or sending the user data to other terminals.
The present invention also provides a computer storage medium in which a program may be stored, which program may include some or all of the steps in the embodiments provided by the present invention when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), a random-access memory (random access memory, RAM), or the like.
Therefore, the invention checks the material configuration of the server before the server is arranged, calculates the arrangement time based on the checking result, compares the arrangement time with the original expected production time, manages the server arrangement property limit based on the comparison result, avoids the loss caused by the server misoperation arrangement, has scientific and reasonable management flow, improves the data management quality before the server arrangement, and can achieve the technical effects which are not repeated herein.
It will be apparent to those skilled in the art that the techniques of embodiments of the present invention may be implemented in software plus a necessary general purpose hardware platform. Based on such understanding, the technical solution in the embodiments of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium such as a U-disc, a mobile hard disc, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, etc. various media capable of storing program codes, including several instructions for causing a computer terminal (which may be a personal computer, a server, or a second terminal, a network terminal, etc.) to execute all or part of the steps of the method described in the embodiments of the present invention.
The same or similar parts between the various embodiments in this specification are referred to each other. In particular, for the terminal embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference should be made to the description in the method embodiment for relevant points.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods may be implemented in other ways. For example, the system embodiments described above are merely illustrative, e.g., the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with respect to each other may be through some interface, indirect coupling or communication connection of systems or modules, electrical, mechanical, or other form.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
Although the present invention has been described in detail by way of preferred embodiments with reference to the accompanying drawings, the present invention is not limited thereto. Various equivalent modifications and substitutions may be made in the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and it is intended that all such modifications and substitutions be within the scope of the present invention/be within the scope of the present invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A server scheduling control method, comprising:
confirming that the material configuration of the base line of the server fails the matching verification, and acquiring an abnormal event which causes the matching verification to fail;
acquiring average processing time of an abnormal event;
extracting the shortest test time and the screening abnormal time from the historical order processing data of the same configuration server;
Calculating a scheduling time based on the average processing time, the shortest test time, and the screening anomaly time;
comparing the production scheduling time with the original expected production time of the factory intelligent manufacturing system, and granting the factory intelligent manufacturing system permission to schedule production if the production scheduling time does not exceed the original expected production time.
2. The method of claim 1, wherein confirming that the server baseline material configuration fails the matchability check, acquiring an exception event that caused the matchability check to fail, comprises:
acquiring a bill of materials, instruction maintenance information and a baseline configuration file based on the server order information;
carrying out matching verification on the bill of materials, the instruction maintenance information and the baseline configuration file;
if the verification is not passed, diagnosis processing is carried out on the abnormal event which causes the verification result.
3. The method of claim 1, wherein obtaining the average processing time of the exception event comprises:
counting screening abnormal time and rechecking passing time of historical abnormal events, wherein the abnormal events comprise baseline abnormal events, instruction abnormal events, material abnormal allocation events and physical abnormal removal events;
the method for calculating the average processing duration Tb of the abnormal event comprises the following steps:
Screening of the ith abnormal event abnormal time t 1 Review the transit time t 2 Processing duration T bi ＝t 2 -t 1 The average processing time length is as follows:
the standard deviation of all treatment durations was:
wherein n is the total number of the abnormal event histories of the client test program, T bi For the ith exception event processing duration
If sigma<=5%, then the abnormal event history average processing time length T b ＝T b1
If sigma>5, processing all abnormal events for a period of time T bi Sequencing, taking the numerical value of the first 1/3 from big to small, and taking the average value T again b ＝T b2
Wherein m is the 1/3 th integer of the total number n of the abnormal events tested by the client, T bj Is T bi And (5) the j-th abnormal event processing time length after the sorting from big to small.
4. The method of claim 1, wherein extracting the shortest test time and screening for anomaly time from historical order processing data of the same configuration server comprises:
acquiring historical flow record data of a specified number of server orders configured in the same way;
the method comprises the steps of extracting test time from production test starting to test item of a client test program from historical flow record data, and screening the shortest test time with the shortest duration from a plurality of test times;
and generating screening abnormal time in an average mode based on the time used for screening abnormal events in the historical flow record data of the orders.
5. The method of claim 1, wherein calculating the production time based on the average processing time, the shortest test time, and the screening anomaly time comprises:
calculating a difference value between the average processing time and the shortest testing time, and outputting the sum of the difference value and the screening abnormal time as the fastest online testing time;
and outputting the difference value between the fastest online test time and a preset fixed parameter as the scheduling time.
6. The method of claim 5, wherein prior to calculating the difference between the average processing time and the shortest test time, the method further comprises:
judging whether the abnormal event is abnormal material:
if yes, selecting a smaller value from the average processing time of the material abnormality adaptation event and the average processing time of the physical abnormality removal event as the average processing time.
7. The method of claim 1, wherein comparing the production schedule to an original projected production time for the factory intelligent manufacturing system and granting the factory intelligent manufacturing system permission to schedule production if the production schedule does not exceed the original projected production time comprises:
extracting an original estimated production time from a factory intelligent manufacturing system;
Judging whether the production time does not exceed the original predicted production time:
if yes, granting the factory intelligent manufacturing system with the authority to arrange the production, and displaying and outputting the production time;
if not, the factory intelligent manufacturing system is not granted the authority to schedule production.
8. A server scheduling control system, comprising:
the abnormality checking module is used for confirming that the material configuration of the server baseline fails the matching verification and acquiring an abnormal event which causes the matching verification to fail;
the first acquisition module is used for acquiring the average processing time of the abnormal event;
the second acquisition module is used for extracting the shortest test time and screening abnormal time from the historical order processing data of the same configuration server;
the scheduling prediction module is used for calculating scheduling time based on the average processing time, the shortest testing time and the screening abnormal time;
and the permission control module is used for comparing the production scheduling time with the original expected production time of the intelligent factory manufacturing system, and granting permission for the intelligent factory manufacturing system to schedule production scheduling if the production scheduling time does not exceed the original expected production time.
9. A terminal, comprising:
a memory for storing a server scheduling control program;
A processor for implementing the steps of the server scheduling control method according to any one of claims 1-7 when executing the server scheduling control program.
10. A computer readable storage medium storing a computer program, characterized in that the readable storage medium has stored thereon a server scheduling control program which, when executed by a processor, implements the steps of the server scheduling control method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310530262.8A CN116681386A (en) | 2023-05-11 | 2023-05-11 | Server scheduling control method, system, terminal and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310530262.8A CN116681386A (en) | 2023-05-11 | 2023-05-11 | Server scheduling control method, system, terminal and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116681386A true CN116681386A (en) | 2023-09-01 |
Family
ID=87781549
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310530262.8A Pending CN116681386A (en) | 2023-05-11 | 2023-05-11 | Server scheduling control method, system, terminal and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116681386A (en) |
-
2023
- 2023-05-11 CN CN202310530262.8A patent/CN116681386A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Bose et al. | Wanna improve process mining results? | |
| US7054699B2 (en) | Process management system and production management system | |
| CN105699760B (en) | The operating condition analysis method of electric energy measuring equipment and power information collecting device | |
| US20050071032A1 (en) | Quality control sytem, method, and program | |
| EP1897828A1 (en) | Sharing traceability management system | |
| US20050203789A1 (en) | Activity management system and method of using | |
| US8219541B2 (en) | System and method for automatically detecting, reporting, and tracking conflicts in a change management system | |
| CN107908548A (en) | A kind of method and apparatus for generating test case | |
| CN103631713A (en) | ERP software automated testing system and method | |
| Monteiro et al. | Defining a catalog of indicators to support process performance analysis | |
| CN111815099A (en) | Assembly line production management method and system | |
| CN113342939B (en) | Data quality monitoring method and device and related equipment | |
| CN116089220A (en) | Index inspection method and device based on operating system and electronic equipment | |
| CN115964272A (en) | Transaction data automatic testing method, device, equipment and readable storage medium | |
| US7225106B2 (en) | Data processing system and method for processing test orders | |
| US20090049394A1 (en) | Quantifying and analyzing back office and field service processes | |
| CN109213729A (en) | As a result the case management driven | |
| EP2453395A1 (en) | Method and system to analyze processes | |
| CN116681386A (en) | Server scheduling control method, system, terminal and storage medium | |
| Thaler et al. | Itil process and impact analysis at rabobank ict | |
| US20070233584A1 (en) | Logistics auditing system and method | |
| JP2016045819A (en) | Business result management system and computer program | |
| Rozum | Defining and understanding software measurement data | |
| CN112256594A (en) | Project information processing method and device and electronic equipment | |
| KR101903530B1 (en) | Optimization diagnostic system of business and IT system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |