CN106600154A - Method and system for precise personnel allocation of server product - Google Patents

Method and system for precise personnel allocation of server product Download PDF

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Publication number
CN106600154A
CN106600154A CN201611192730.1A CN201611192730A CN106600154A CN 106600154 A CN106600154 A CN 106600154A CN 201611192730 A CN201611192730 A CN 201611192730A CN 106600154 A CN106600154 A CN 106600154A
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delimited
organizational structure
line
lean
during
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罗希望
高阳
马志强
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Zhengzhou Yunhai Information Technology Co Ltd
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    • 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
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    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
    • G06Q10/06313—Resource planning in a project environment
    • 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • 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

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Abstract

The invention discloses a method and a system for precise personnel allocation of a server product, wherein the method and the system belong to the field of server production technology. According to the method for precise personnel allocation of the server product, big data analysis is utilized; a starting and stopping statistics module algorithm are introduced through an MES; a time utilization rate is evaluated according to accumulated historical data; product straight-through rate and linear balance rate of a production line are integrally utilized; a weighted working hour is established through a product proportion weight; and furthermore precise personnel allocation is obtained through the starting and stopping statistics module algorithm and market orders in introducing the MES. The method for precise personnel allocation of the server product has advantages of reducing personnel cost, more reasonably planning manpower, improving personnel utilization efficiency, reducing personnel cost, realizing rationality and scientizing in personnel utilization, and realizing high popularization value and high application value.

Description

The method and system that a kind of server product lean is delimited the organizational structure
Technical field
The present invention relates to server production technical field, method and be that a kind of server product lean delimits the organizational structure specifically are provided System.
Background technology
Computer has information memory capacity big, and user's acquisition information is convenient and swift, and information reliability height of acquisition etc. is excellent Point, is widely applied.In recent years, developing rapidly with social and economy, computer application field has further Extension, the application in production field receives extensive concern, can realize the increasingly automated of process of producing product, in a large number Manpower is saved, improve production efficiency brings bigger benefit to enterprise.The own characteristic of server product, customers, just determine Its many batches a small amount of, configuration variation, the operation mode of customization, equally during production is realized, in the face of various types Number, various configurations, different clients customize require order, quick response, it is ensured that carry out JIT（Just In Time）JIT During the mode of production, the excessive problem of personnel planning will not be produced again.Under the background of customization, to the flexibility of production line with Quick response is put forward higher requirement.But in manufacturing industry, in order to the needs for meeting customization are planned in manpower demand During change, often lack data foundation and algorithm, rely solely on experience and technique is planned, it is impossible to which the lean that calculates of science is determined Employment is compiled, so as to cause the waste of manpower, increases entreprise cost, be further improved.
The content of the invention
The technical assignment of the present invention is to be directed to above-mentioned problem, there is provided one kind can reduce employment cost, more reasonably Planning manpower, improves employment efficiency, reduces recruitment cost, so as to realize the reasonability and scientific server product essence of employment The method that benefit is delimited the organizational structure.
Further technical assignment of the invention is to provide a kind of system that can realize said method.
For achieving the above object, the invention provides following technical scheme：
A kind of method that server product lean is delimited the organizational structure, methods described is analyzed with big data, is imported by MES when starting shooting and is stopped Statistical module algorithm during machine, according to the historical data of accumulation time mobility is evaluated, and the product of integrated use production line leads directly to Rate and line balance rate, are set up weighting man-hour by product proportioning weight, and then are counted with the when of shutdown during the start of foundation MES importings Modular algorithm and market order show that lean is delimited the organizational structure number.
MES is the abbreviation of manufacturing execution system, i.e. manufacturing execution system.
Preferably, methods described specifically includes following steps：
S1：Statistical module algorithm when MES is imported when starting shooting and shut down：
1）K=end times-beginning activity duration when going into operation；
2）Code when shutting down is imported, containing line and multiple line code is stopped, stops being scanned during multiple line,
S=∑s n i during shutdown（It is m- during multiple line to stop the line time）i(i=1.2···n)；
3）Time mobility=(K-S)/K；
4）The weighting man-hour S of stationi=(Ai*Pi+Bi*Pi+···)/∑n iPi, line balance rate LOB=averge（Si）/max （Si）, T=∑s n i during the weighting chief engineer of single line（Pi*∑n iAi/∑n iPi）,
Wherein, each station man-hour of A products is A1···AN, yield is P1, each station man-hour of B products is B1···BN, Yield is P2, by that analogy, SiFor the station man-hour of letter definition in order；
S2：Market order quantity is MP, and demand delivery work number of days is N, and single day work hours were H, market beat T/T=3600* N*H/MP；
S3：Show that lean is delimited the organizational structure L=T/ (T/T* time mobility * Y*LOB), Y is product first-pass yield.
Preferably, in step S1, station is scanned as foundation with mainboard, the same day, first piece of mainboard making time on duty started As the activity duration is started, an appointment codes are scanned as the end time during take-up in mainboard.
Preferably, the time mobility a reference value is with 80% as starting point, line balance rate LOB is less than 12 stations with 85% For starting point, higher than 12 stations with 80% as starting point, brought into actual value higher than threshold value.
The system that a kind of server product lean is delimited the organizational structure, including：
MES modules：Statistical module algorithm during for importing during start and shut down；
Time mobility computing module：For calculating time mobility according to the historical data of accumulation；
Computing module during weighting chief engineer：During for the weighting chief engineer for calculating single line；
Lean is delimited the organizational structure computing module：Delimit the organizational structure number for calculating lean.
Preferably, statistical module algorithm when the MES modules are used to import when starting shooting and shut down, when going into operation at the end of K= The m- beginning activity duration, code when shutting down is imported, containing line and multiple line code is stopped, stop being scanned during multiple line, S=∑s n i during shutdown（It is multiple It is m- during line to stop the line time）i(i=1.2···n)。
Preferably, the time mobility computing module is：Time mobility=(K-S)/K.
Preferably, computing module is during the weighting chief engineer：T=∑n i（Pi*∑n iAi/∑n iPi）, wherein, A is produced Each station man-hour of product is A1···AN, yield is P1, each station man-hour of B products is B1···BN, yield is P2, with this Analogize, SiFor the station man-hour of letter definition in order.
The weighting man-hour S of each stationi=(Ai*Pi+Bi*Pi+···)/∑n iPi, line balance rate LOB=averge （Si）/max（Si）.
Preferably, the lean is delimited the organizational structure, computing module is：L=T/ (T/T* time mobility * Y*LOB), wherein, Y is product Product first-pass yield, market beat T/T=3600*N*H/MP, N are demand delivery work number of days, and H is single day work hours, and MP is market Quantity on order.
Compared with prior art, the method that server product lean of the invention is delimited the organizational structure has beneficial effect following prominent Really：The method delimited the organizational structure of server product lean of the present invention is set up an extending type lean and is delimited the organizational structure pattern, can section by the method Prediction production line is delimited the organizational structure manpower, reduces employment cost, more reasonably plans manpower, improves employment efficiency, reduce recruitment into This, with good practicality.
Specific embodiment
Below in conjunction with embodiment, the method and system that the server product lean of the present invention is delimited the organizational structure are made further in detail Explanation.
Embodiment 1
The method that the server product lean of the present invention is delimited the organizational structure, methods described is analyzed with big data, when importing start by MES With statistical module algorithm when shutting down, time mobility, the product of integrated use production line are evaluated according to the historical data of accumulation First-pass yield and line balance rate, by product proportioning weight set up weighting man-hour, and then according to MES import start when and shut down when Statistical module algorithm and market order show that lean is delimited the organizational structure number.
Embodiment 2
On the basis of embodiment 1, the present embodiment methods described specifically includes following steps：
S1：Statistical module algorithm when MES is imported when starting shooting and shut down：
1）K=end times-beginning activity duration when going into operation, station is scanned as foundation with mainboard, the same day, first piece of mainboard on duty was thrown The angle of incidence scans an appointment codes as the end time during take-up initially as the activity duration is started in mainboard.
2）Code when shutting down is imported, containing line and multiple line code is stopped, stops being scanned during multiple line,
S=∑s n i during shutdown（It is m- during multiple line to stop the line time）i(i=1.2···n)。
3）Time mobility=(K-S)/K.
4）The weighting man-hour S of stationi=(Ai*Pi+Bi*Pi+···)/∑n iPi, line balance rate LOB=averge（Si）/ max（Si）, T=∑s n i during the weighting chief engineer of single line（Pi*∑n iAi/∑n iPi）,
Wherein, each station man-hour of A products is A1···AN, yield is P1, each station man-hour of B products is B1···BN, Yield is P2, by that analogy, SiFor the station man-hour of letter definition in order.
S2：Market order quantity is MP, and demand delivery work number of days is N, and single day work hours were H, market beat T/T= 3600*N*H/MP。
S3：Show that lean is delimited the organizational structure L=T/ (T/T* time mobility * Y*LOB), Y is product first-pass yield.Time mobility base With 80% as starting point, line balance rate LOB is less than 12 stations with 85% as starting point to quasi- value, high higher than 12 stations with 80% as starting point Brought into actual value in threshold value.
Embodiment 3
The system that the server product lean of the present invention is delimited the organizational structure, including：
MES modules：Statistical module algorithm during for importing during start and shut down.
K=end times-beginning activity duration when going into operation.
Code when shutting down is imported, containing line and multiple line code is stopped, stops being scanned during multiple line,
S=∑s n i during shutdown（It is m- during multiple line to stop the line time）i(i=1.2···n)。
Time mobility computing module：For calculating time mobility according to the historical data of accumulation, time mobility= (K-S)/K。
Computing module during weighting chief engineer：During for the weighting chief engineer for calculating single line.
The weighting man-hour S of stationi=(Ai*Pi+Bi*Pi+···)/∑n iPi, line balance rate LOB=averge（Si）/ max（Si）, T=∑ n i during weighting chief engineer（Pi*∑n iAi/∑n iPi）.Wherein, each station man-hour of A products is A1··· AN, yield is P1, each station man-hour of B products is B1···BN, yield is P2, by that analogy, SiFor letter definition in order Station man-hour.
Lean is delimited the organizational structure computing module：Delimit the organizational structure number for calculating lean.
Lean is delimited the organizational structure L=T/ (T/T* time mobility * Y*LOB), and Y is product first-pass yield, market beat T/T=3600*N* H/MP, MP are market order quantity, and N is demand delivery work number of days, and H is single day work hours.
Embodiment described above, the simply present invention more preferably specific embodiment, those skilled in the art is at this The usual variations and alternatives carried out in the range of inventive technique scheme all should be comprising within the scope of the present invention.

Claims (9)

1. a kind of method that server product lean is delimited the organizational structure, it is characterised in that：Methods described is analyzed with big data, by MES Statistical module algorithm when importing when starting shooting and shutting down, according to the historical data of accumulation time mobility, integrated use life are evaluated The product first-pass yield and line balance rate of producing line, is set up weighting man-hour by product proportioning weight, and then the start imported according to MES When and the when of shutdown statistical module algorithm and market order show that lean is delimited the organizational structure number.
2. the method that server product lean according to claim 1 is delimited the organizational structure, it is characterised in that：Methods described is specifically included Following steps：
S1：Statistical module algorithm when MES is imported when starting shooting and shut down：
1）K=end times-beginning activity duration when going into operation；
2）Code when shutting down is imported, containing line and multiple line code is stopped, stops being scanned during multiple line,
S=∑s n i during shutdown（It is m- during multiple line to stop the line time）i(i=1.2···n)；
3）Time mobility=(K-S)/K；
4）The weighting man-hour S of stationi=(Ai*Pi+Bi*Pi+···)/∑n iPi, line balance rate LOB=averge（Si）/max （Si）, T=∑s n i during the weighting chief engineer of single line（Pi*∑n iAi/∑n iPi）,
Wherein, each station man-hour of A products is A1···AN, yield is P1, each station man-hour of B products is B1···BN, Yield is P2, by that analogy, SiFor the station man-hour of letter definition in order；
S2：Market order quantity is MP, and demand delivery work number of days is N, and single day work hours were H, market beat T/T=3600* N*H/MP；
S3：Show that lean is delimited the organizational structure L=T/ (T/T* time mobility * Y*LOB), Y is product first-pass yield.
3. the method that server product lean according to claim 2 is delimited the organizational structure, it is characterised in that：In step S1, with mainboard Scanning station is foundation, and the same day first piece of mainboard making time on duty is swept during take-up initially as the activity duration is started in mainboard An appointment codes are retouched as the end time.
4. the method that the server product lean according to Claims 2 or 3 is delimited the organizational structure, it is characterised in that：The time sows Rate a reference value with 80% as starting point, line balance rate LOB less than 12 stations with 85% as starting point, higher than 12 stations with 80% for Point, is brought into higher than threshold value with actual value.
5. the system that a kind of server product lean is delimited the organizational structure, it is characterised in that：Including：
MES modules：Statistical module algorithm during for importing during start and shut down；
Time mobility computing module：For calculating time mobility according to the historical data of accumulation；
Computing module during weighting chief engineer：During for the weighting chief engineer for calculating single line；
Lean is delimited the organizational structure computing module：Delimit the organizational structure number for calculating lean.
6. the system that server product lean according to claim 5 is delimited the organizational structure, it is characterised in that：The MES modules are used for Statistical module algorithm when importing when starting shooting and shutting down, K=end times-beginning activity duration when going into operation, imports code when shutting down, Containing line and multiple line code is stopped, stop being scanned during multiple line, S=∑s n i during shutdown（It is m- during multiple line to stop the line time）i(i=1.2··· n)。
7. the system that the server product lean according to claim 5 or 6 is delimited the organizational structure, it is characterised in that：The time sows Rate computing module is：Time mobility=(K-S)/K.
8. the system that server product lean according to claim 7 is delimited the organizational structure, it is characterised in that：It is described to weight total working hour meter Calculating module is：T=∑n i（Pi*∑n iAi/∑n iPi）, wherein, each station man-hour of A products is A1···AN, yield is P1, each station man-hour of B products is B1···BN, yield is P2, by that analogy, SiFor the station work of letter definition in order When.
9. the system that server product lean according to claim 8 is delimited the organizational structure, it is characterised in that：The lean is delimited the organizational structure calculating Module is：L=T/ (T/T* time mobility * Y*LOB), wherein, Y be product first-pass yield, market beat T/T=3600*N*H/MP, N is demand delivery work number of days, and H is single day work hours, and MP is market order quantity.
CN201611192730.1A 2016-12-21 2016-12-21 Method and system for precise personnel allocation of server product Pending CN106600154A (en)

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Cited By (4)

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Publication number Priority date Publication date Assignee Title
CN108009682A (en) * 2017-12-01 2018-05-08 郑州云海信息技术有限公司 A kind of station technique DYNAMIC DISTRIBUTION method and system under the big data based on MES
CN109556898A (en) * 2018-11-22 2019-04-02 京东方科技集团股份有限公司 A kind of method and storage medium of the performance mobility of determining equipment
CN110599018A (en) * 2019-08-30 2019-12-20 苏州浪潮智能科技有限公司 Production task configuration system and method based on MES system
CN111627189A (en) * 2019-02-12 2020-09-04 珠海格力电器股份有限公司 Equipment exception handling method, system and storage medium

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108009682A (en) * 2017-12-01 2018-05-08 郑州云海信息技术有限公司 A kind of station technique DYNAMIC DISTRIBUTION method and system under the big data based on MES
CN109556898A (en) * 2018-11-22 2019-04-02 京东方科技集团股份有限公司 A kind of method and storage medium of the performance mobility of determining equipment
CN111627189A (en) * 2019-02-12 2020-09-04 珠海格力电器股份有限公司 Equipment exception handling method, system and storage medium
CN111627189B (en) * 2019-02-12 2022-04-22 珠海格力电器股份有限公司 Equipment exception handling method, system and storage medium
CN110599018A (en) * 2019-08-30 2019-12-20 苏州浪潮智能科技有限公司 Production task configuration system and method based on MES system
CN110599018B (en) * 2019-08-30 2022-06-03 苏州浪潮智能科技有限公司 Production task configuration system and method based on MES system

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