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  • nft幕后推手>ַ:mxsty.cc<>-m1x1s1t1y1-20221007

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    nft开发教学>ַ:mxsty.cc<>-m1x1s1t1y1-20221007

    ʱ䣺2021/11/02 Դδ֪ ߣַ
    ҵгԽԽңΪĵҵʼƷ̻֡滯ķչ
    Ϊƪģ

    ժҪ

    ҵгԽԽңΪĵҵʼƷ̻֡滯ķչͳ˸÷ʽȱѧϵΪʶӰ죬˲ܾáЧʵ£ͳŲʽ˹ޣԻöԼ¸ģʽŲʱԹ̻еװ䳵MESϵͳж༼ԱȺŲΪҪо󣬶Чѧģʵ֤Ҫо£

    һ װߴͳԱ÷ʽΪʶӰ죬Ұ鳤Ա֪ޣ޷ʵ˸Ż⣬Զ༼ԱװеʱЧʡϸʺʵȼӹΪָꡣÿ͹۸ȨеĵֵȷָȨϵ༼Աʤָ¼㷽װʤֵָΪĿ꣬˸ùϵΪԼĶ༼ԱŻģͣһָĽ㷨ԱŻģͣʵװ߶༼Ա빤λ֮˸ŻM˾ͺMCVװ˸ΪʵĽ㷨Чװ߶༼Ա˸Ż⣬ЧԴ˷ѣЧ10.95%-12 86%.

    Թ̻еͺŲƷװԼӣ˹ŲޣԻŲ⣬ͨԻװߵŲйԶͺŲƷװѭ깤СΪŻĿ꣬װߵŲŻģͣŴ㷨ĿԺģ˻㷨Mtopois ж׼γֲŵԣһŴģ˻㷨װߵĽӲŻģͣʵֶͺŲƷװߵŲŻM˾̻еװ䳵жͺMCVװߵŲΪʵŴģ˻㷨ЧװŲŻ⣬װѭ3.min-43.min,Ч18.2%6-23%.

    ̻еװ䳵MESϵͳϵͳ¶ϷΪݿ㡢㡢ݷʲ㡢ҵ߼㡢ûǰu1㡣ݿҪϵͳĸݽж̬ʵʱ£ΪϵͳԼϵͳӲĽṩ˶㣬֧֣ݷʲͨҵ廯֣ʵϲҵ²ݿ֮Ϣҵ߼Ҫϵͳ幦ܽ߼ĴʱӦǰûָûǰUIҪ豸ͻݹģ飬ûֻѡӦģеĹܽвҵ߼㽫ʱӦ

    ؼʣװߣʤָ༼ ԱȣŲȣ MESϵͳ

    Abstract

    With the increasingly fierce competition in the manufactural market, manufactural  companies with production orders as the core have gradually begun to develop in the drction of  multi-variety, variable batch size, cycle shortening, lean production. Due to the lack of a scientifie  evaluation system and sbjective avareness, the tadional way of manning job llocationo results  in people unable to make the most of their work and low production eficiency. Traditional  scheduling mcthods are dificult to obtain optimal scheduling plans under muliple constraints  due to limited manual computing apbilie. Therefore, this paper takes the mulisilled  personnel scheduling and scheduling method in the MES system of the construction machinery  assembly workshop as the main research objeet and conducts mathematical modeling and  example simulation to verify is benefit maximization. The main rescarch contents are as follows:

    Firstly, Aiming at the problem that the traditional stffing method of the assembly line is  casily ffccted by subjective consciousness and the team leader has limited awareness of  personnel capbilties, it is dificult to oplimize the deployment of personnel and posts. The  procssing data such as time eficiency, pass rate, and completion rate of mouli-skilled personnel  in the assembly process are used as evaluaion indicators, and the entropy method in the objective  weighing method is adopted to detemine the weigh cofficient of ceach evaluation index. This  paper proposes a calculaion method for the competence index of cach skill of muliskilled  personnel. To maximize the total competency index value of the assembly line, the opimizaion  model of muliskilled personnel scheduling is constructed with the constaint of the relationship  of prsonnel and post configuraion. An improved Hungarian algoritm to solve the opimization  model of personnel scheduling is proposed, which realizes the optimization of the deployment of  muli-killed personnel and workstations on the assembly line, Taking the man-post configuration  of the multi-model MCV mie-low assembly line of M company as an example, the simulation  resuls show that the improved Hungary algorithm can ellivcl solve the opimizaion problem of the mut-skilled personnel configurat ion of the assembly line, effectively avoid the waste of  resources, and increase the production fficiency by 10.95%~ 12.86%.

    Secondly, Because of the complex constraints of the mixed-flow assembly line for multi-  model products of construction mac hinery, the limited calculation capac ity of manual production,  it is dificult to obtain the optimal scheduling plan, Through the general description of the  scheduling problem of the mixed-flow assembly line, the optimization goal is to minimize the  maximum cycle completion period of mixed-flow assembly of multi-model products, and the  production scheduling and scheduling optimization model of the mixed-flow assembly line is  constructed. Combining the rapid convergence characteristics of genetic algorithm and the  feature that the Metropolis criterion of simulated annealing algorithm overflows with local  optimality, a genetic simulated annealing algorithm is proposed to solve the scheduling  optimization model of the mixed-flow assembly line, and realize the optimization of production  scheduling of mixed-flow assembly line of multi-model products. Taking the scheduling  arrangement of the muti-model MCV mixe-low assembly line in the construction machinery  assembly workshop of M company as an example, the simulation results show that the genetic  simulated anneal ing algorithm can efetively solve the optimization problem of the mixsed-flow  assembly line scheduling arrangement, and the mixed-flow assembly cycle period is shortened  by 31. 1min~43.7min. The production eficiency is increased by 18.2%~-23%.

    Thirdly, This paper develops the MES system of construction machinery assembly  workshop. From bottom to top, the system is pided into database layer, server layer, data access  layer, business logic layer, user interface layer, and front-end Ul layer. The database layer mainly  conducts dynamic management and real-time update of various data of the system; the server  layer provides top-level support for the normal operation of the system and the interaction of  system software and hardware; the data access layer real izes the informat ion interaction between  the upper-layer business and the lower-layer database by concretizing the business; the business  logic layer mainly processes logic calculation examples for specific functions of the system, and  responds to front-end user instructions promptly; the user interface layer and the front-end UI  layer mainly include modules such as production management, quality management, inventory  management, equipment management, and basic data management. Users only need to select the  functions in the corresponding modules to operate according to their needs, and the business logic  layer will respond in time.

    Key words: Assembly line: competency index; multi-skilled personnel schedul ing; production  scheduling: MES system

    Ŀ ¼

    1

    1.1 оĿļ

    ҵĿٷչͳģʽ쳵ϲƻ²ƲϵܵĴͳģʽ޷ҵٲϷչ󡣿ͻԽԽСơƷԽԽӻҪԽԽ̻ҵԽ滯ʹͳģʽ򼯳ɻܻתҵ4.0 ijֽݡƼ㡢˼빤ҵںϣΪҵǻ۹תӵһιҵĹҵ 4.0,¼۵ijֲƶҵ±ƽҵǻۻǻ۹ؽδҵչķĿ꣬Ҫպùҵ 4.0,ӿķչԹҵ MES ϵͳоͿԵΪҪ

    ҵǽ IOT Internet ںϵ켼¼㷺Ӧڹҵ[1],ṹͿɽֽɸ֪㡢Ӧò[2],ͼ 1-1 ʾ

    ֪Ƶʶ𡢴ȸ֪豸ʵʱض̬ȡĿݣҪƶͨʻʹȣͨ罫֪ĸϢʵʱ䣻ӦòͨԶյĸݡڽҵҵʵںϴܻʱֶһΪֳ㡢Ʋ㡢㡢ҵ[3],ͼ 1-2 ʾֳҵֳ豸ƲҪֿHMI ԼԴȣҪ DCS SCADAȣҪ MES ͹̬ҵҪָ ERP PLM,ͨҵ磨ֳߡҵ̫ȣɴϲײƵӣﵽҵֳ̡ҵɼҵֳݵҵ

    ҵΪҵ 4.0 ĺģƶҪãΪҵϲƻײƲ֮"蹵"Լ"µ"˽[4],ڹҵ MES ϵͳĿ

    MES ϵͳҪְǶԳĸݽͳһϼƻ¼Ʋ֮䡣Ϊṩƻʵʩ׷ݣԴʵʱ״ݣǹͨϼƻ¼Ʋ֮мŦҵϲײ֮"հ"[5],ͼ 1-3 ʾ

    MES ֮ǰҵ൥һͬɹƩ豸桢ݲɼԱϢȹЭͬڵһ֮伯Բ㣬ݹʵ֣޷ʹ̴ﵽŻ[6, 7],ŹҵˮƽĸٲϵطչͻҪԽСƣԽӻͳijģʽ޷[8],磺ϲƻ޷ֻײƲÿҵֳײƲͻϢ޷ʱϲƻ㣻豸֮ʵЧļɺݹΪһ"µ";ҪϢݹҾӳԣ޷ԭʼݽмʱЧھ͹⣬Ϊ˽[9-12],ִϵͳMESӦ˶MES ijں̶ܴ϶ԳŻ̡

    MES һԴú״̬⣬Ĺ̡ȡ豸ĵƷٵȹֳݲɼܷȹģ[13],ͼ 1-4 ʾһҵʵѡȡеļģϲϹҵɴһܹܡ

    ڹҵ MES ϵͳij֣ҵܻ̣ʵӦʵ֣ҵʵʱȡֳϢҵֳĶ̬ܿءϢĿӻҪϢݵھãҵ̵ĿɻԣƻƲ㡢䡢豸֮ϵ빵ͨӿҵǻۻIJǿԲƷܿ 1.2 о״ִϵͳMESΪҵǻ۹֮һҪ̶ȲɺӣѱҵΪصзĿرڵ¹"ҵ 4.0""й 2025"˫սƶ£ֽ MES Ȼָʽ[14].ͬʱMES ϵͳһֱǹѧоĿ֮һڱͳΪҹϢ빤ҵںϣʼʵ"й 2025"սԣҵͿԺУƽ MES ķչ[15, 16].ȹģΪ MES ϵͳĺ֮һ䱾ԱȺŲΪĵŻ⣬ǺܻˮƽҪָ֮һ˶оΪҪ

    1.2.1 MES ϵͳо״

    ŴݡƼ㡢ͼھ򿪷רѧ߶MES ϵͳоԽ룬MES ϵͳҲԽԽܻϢ

    ףڡʦѵԴͳ ERP ޷"滯""ܻ"󣬲 DIS OPC ȼϢµ ERP ϵͳɣٽ˳"滯""ܻ"չ[17-21];»ҡȡŰ˵Դͳ MES ϵͳ޷㾺г仯ҵܻת͵ķչͨϢ˹ҵ˼ںϼ뵽̵ĹܿУʵִͳ MES ϵͳҵ̶ܻ[22-25];̸Ϣˮƽ⣬ʹ"+"ʽгIJ𣬲ִϢʵֳ MES ϢϢˮƽ[26];ŵڶгкǻ۹ʵ MES ܸϸͷΪ MES ʵṩ˿з[27, 28];Ӱ⡢ɢҵϢ̶ȵ£Чʵµ⣬ùҵ̫ʵݵĿٽԼ̿ƣڴ˻Ͽ MES IJֹģ飬Ϣˮƽ[29-32];Ф·Թҵݱ¹ҵϢȫͨ MES µĹҵݰȫƣҵȫ[33].

    Zwoliska B Դͳ MES ϵͳڸ߶ԶˮƽлԺԲ⣬ñҶ˹򣬿 MES 㷨 MES ϵͳԺ[34];Babak Shirazi Դͳ ERP MES ЧЧʵ£޷ҵ⣬һֻƼERPMESSPXɵϵṹҵЧ[35];AlmadaLobo FMithun Mukherjee ΪͻƻƷ󣬽Ƽ㡢ƶ豸ʹݵȼϣܻ MES ϵͳٽҵܻת[36, 37].

    MES Ŀ C/S ΪϵͳܣϵͳԿͻǿάɱϸߣⴴʹ B/S ΪϵͳܣѶԿͻǿϵͳչԡ

    1.2.2 Ա㷨о״

    "Դ" 1954 Peter Drucker[38] ԴԴ߱ܶԣܹãͬʱз˸Żƥ 1980꣬ǶԴЧھ򡢺䡢˷ѵЧ;ҵвɻȱIJ[39],һֱܺѧע

    ·Աȹȱѧϵ⣬龰ַϣɳԱʤƳԱȹ[40];ƷõԱòЧʵµ⣬ WitnesseM-PlantԳԱŻнģͷһ̶ϸԱ[41-43];ʵ쳵˸ƥ䲻⣬˸÷ҵŻΪĿ꺯˸ģͣͨһֶĿ㷨һָĽŴ㷨ģͣҵɱЧ[44-46];÷㲿ӳ䣬ԱӹݲɼʱԱ׷ݲԱ׼ȷ⣬ RFID ʵʱɼӹݣͳƷԱˮƽ˳Աǿ˲ƷĹܿ[47, 48];ά깤СΪĿ꣬"һ˶"IJйģͣͨһָĽ˹ȺŻ㷨ģ̻ͣӳ깤ʱ䣬Լɱ[49, 50];ܵԱʷӹΪݣʱΪָԱֵԱֵΪ쳵ԱŻģͣû PSO 㷨ģͣʵ쳵ԱȺ[51];ֵװԱòװЧʵµ⣬ԱˮƽۼڸҵʱΪݣ˸Ӧܺ󻯡ƥӦȲСΪĿ꺯˸ģͣһֻڸλӦȾʽ㷨ģͣŻԱ빤λ֮ƥ⣬˲ߵЧ[52].

    X Cai ϼԱĹЧʵ⣬ԵԱɱСΪĿ꣬˸ŻģͣһָĽĶ׼Ŵ㷨[53]ģͣ˳ϼԱЧʣAlbert CorominasKoichi Nakade װ䳵Աò²װڹ⣬ֱװ̻ԱԱԱɱСΪĿ꺯˸ŻģֱͣöԹ滮[54] һڼԱŷŻ㷨[55]ģͣŻ˳˸⣬ĺɱCristobal Miralles[56]װˮԱ䲻ƽ⣬ ԱӦλװʱ䣬ЧԱʶȾΪĿ꣬˸Żģͣһֻڷ֧ͱ߽ʽ㷨ģͣЧԱʶȣYiyo Kuo[57]նװԱڶ֮ϵ⣬ԱȼߵͱţԱϵƵͻΪĿ꣬滮ģͣģģͽ⣬Ż༼Աڶ߼Ļϵ⡣

    ԳԱҪڻӳоװ䳵һԱоȱ⽫װնװԱΪо󣬲øĽ㷨װ˸ƥתΪϵѧ⣬ЧŻװնװԱ⣬װ䳵һԱоIJ㡣

    1.2.3 Ų㷨о״

    Ųȸ 1954 ꣬Ӣѧ Johnson о̨֮Ų[58],˺ŲⱻоչӦõҵСҵŲⰴҪΪ࣬һǻӳŲȣһװ䳵Ųȡ

    ڶԻӳŲоУԻӳҡ޷ʱ⣬СҵʱΪĿ꣬˸ָĽŴ㷨Ż˻ӳŲ[59-63];ڡɵԻӳ˹Ų⣬ֱ˻Լ۵Ų[64]ͻڹʽ㷨[65],ЧŻ˴ͳŲʽ

    ڶװ䳵ŲоУƻ½ѩ Patrick װ䳵Ĵͳ˹Ų⣬ֱ˻ԼŲģ[66]ԴȼŲģ[67, 68]ԼڶԵŲģ[69, 70],ģģͣŻװ䳵Ų⣻ܸM.Omkumar Զ༶װ䳵⣬³ִ⣬װΪĿ꺯ֱģͷԼԻ[71]һµĻȺ㷨ʽ㷨[72],Żװ䳵ŲʵֳRoberto Dominguez ԶͺŲƷװ䳵ŲŲڹ⣬Сװ깤ʱΪĿ꺯Ⱥ˹ۣһֻ͵Ⱥ㷨ڿܶȵѡԱӶԵʧֲŵ⣬Żװ䳵Ų[73];ͯСӢԶͺŲƷװ䳵Ʒӻ̻װѭʱ[74-77]װɱ[78]ΪĿ꺯ָĽŴ㷨ͺŲƷװˮŲģͣŻ˶ͺŲƷװˮŲ⡣

    ڳŲовƷͺŵһͺ٣ڶԼ¶ͺŲƷװŲоȱ⽫ԶԼ¶ͺŲƷװΪо󣬴һָĽŴģ˻㷨ŻԼ¶ͺŲƷװˮߵŲ⣬Ϊоṩһֿеķ

    1.3 Ҫо

    ĸݹ̻еװ䳵װߵص㣬ʵװԱЧߺװѭʱСΪĿ꣬ͨԱʤָۿϵĹԼԱȺŲģ͵ĽøĽĵ㷨ģͽ⣬ֲͳԱ÷ʹͳ˹ŲIJ㣬ʵֻװԱŲܵȣ󣬱ĽĽԱ㷨ԼŲ㷨Ӧõ̻еװ䳵 MES ϵͳĿСҪоУ

    1ȷװԱָָ꣬ٻһ»ֵȷָռϵԴ˻װԱʤ㷽װԱװ似ܵʤˮƽΪݣװߵЧΪĿ꺯װԱŻģͣøĽ㷨ģͣʵװԱŻͨʵ֤

    2ԱȵõĸλʵװʱΪݣԶͺŲƷװѭ깤ΪĿ꣬ͺŻװˮŲŻģͣһŴģ˻㷨ģͣʵֶͺŲƷװˮŲȵŻͨʵ֤

    3Ա㷨Ų㷨ںϵ MES ϵͳУӦģ飬ʵֹ̻еװ䳵˸Ųŵܻʵʱ

    1.4 ĵ֯ṹ

    ķ¶Թ̻еװ䳵 MES ϵͳеԱȺŲоԼ MES ϵͳֹģĿ֯ṹͼ 1-5 ʾ

    ½ھ尲£

    һ£ȷָоĿĺ壬Ȼȫۺ MESϵͳԱȺŲȵоԱĵҪоݽиڶ£ͨװԱõص⣬װ߶༼ԱʤĶ;ģͽиԱʷӹеʱЧʡϸʺΪֵָ꣬ö༼Աʤָ㷽װ˸ƥŻģͣһָĽ㷨ģͣͨʵ֤

    £ͨԶͺŻװˮߵŲзϲߵص㣬ͺŻװˮߵŲģͣһŴģ˻㷨ģͣͨʵ֤

    £ȸݹ̻еװ䳵ʵ󣬶Թ̻еװ䳵 MES ϵͳܹƺͼѡͣȻϵͳݿģͽƣ IntelliJ IDEAMySQL Workbench ȿɹ̻еװ䳵 MES ϵͳĿ

    £оɹܽᣬҪԱȺŲȵоɹMES ϵͳĿɹодڵIJԼδչ˼

    2 ڸĽ㷨װԱŻо

    2.1 װԱȵص

    2.2 װ߶༼Աʤ

    2.2.1 ʤĶģ

    2.2.2 ༼Աʤָ

    2.3 װԱŻģ

    2.3.1 ԱŻģ͸

    2.3.2 ԱŻģ

    2.3.3 ԱŻģ͹

    2.4 Ľ㷨

    2.5 ʵ֤

    2.6 С

    3 ͺŻװŲŻо

    3.1 װŲ

    3.2 װŲŻģ

    3.3 Ŵģ˻㷨

    3.3.1 ȾɫʼȺ

    3.3.2 ӦȺ

    3.3.3 Ŵ

    3.3.4 ģ˻

    3.4 ʵ֤

    3.5 С

    4 ̻еװ䳵 MES ϵͳ

    4.1 ϵͳ

    4.2 ݿ

    4.2.1 ݿӦó

    4.2.2 ݿṹ

    4.2.3 ݱ

    4.3 MES ϵͳģ뼼ʵ

    4.3.1 ϵͳԭ

    4.3.2 ģ

    4.3.3 ģ

    4.3.4 ģ

    4.3.5 豸ģ

    4.3.6 ݹģ

    4.4 С

    5 չ

    5.1

    빤̻еװ䳵ͻƷӻ̻󣬷װˮߵص⣬һָĽ㷨װԱŻȣһŴģ˻㷨װŲŻȣ B/S ܹƺͿ̻еװ䳵 MES ϵͳƽҵǻ۹Ľ̡Ҫоɹ£

    1װߴͳ˸÷ʽȱѧϵ鳤԰Աװ֪㡢ΪʶӰ졢˹ޣԱȲ˲ܾáװЧʵԼƷӵ⡣ĻʤԭʱЧʡϸԼʵȶװЧӰ죬ÿ͹۸ȨеֵΪָ긳ȨʱЧʡϸԼʵΪָװ߶༼Աʤϵƥԭʤָ뾭Ч֮ĹϵʤָΪĿ꺯װ߶༼ԱŻģͣһָĽ㷨ģͽ⣬Żװ߶༼Աȣ˲Ч档

    2ԴԼĶͺŻװˮߵ Flowshop ģʽͳ˹ŲʽΪʶӰ졢ԼⲻȫӰ죬»װˮЧʵºӳ⡣ķ˶ͺŻװˮFlowshop ģʽص㣬ƽƶʱ֯ʽҵϳȴ֣ԶͺŲƷװѭ깤ʱСΪĿ꺯˶ͺŻװŲŻģͣһŴģ˻㷨ŲģͣŻ˻װˮߵŲȣŲںڡ

    3 IntelliJ IDEA ƽ̨˹̻еװ䳵 MES ϵͳĿ Javaϵͳܴ CSSHTMLJavaScriptBootstrapJSPJSTL ȼϵͳǰҳĿ ServletJQueryJDBCTemplateDuirdBeanUtilsTomcatMySQL ȼϵͳ˹ܵĿ MySQL Workbench ϵͳݽж̬ϵͳҪ桢豸ͻݵ 5 ģ顣ʵ˹̻еװ䳵ԱȡƻŲءݹ豸״̬ȹܡ M ˾Ĺ̻еװ䳵ϵͳвԺ֤ͨԺ֤ĵ MES ϵͳ˳װԱȺͼƻŲ񣬲Чõ

    ĵоΪҵ MES ϵͳĿӦṩ˿еļҵǻ۹תҪ塣

    5.2 չ

    Թ̻еװ䳵 MES ϵͳеĵоһоɹԴһЩ֮費ϵĽѧϰʵ֤δչ£

    1Զ༼Աʤ۹УԱʤо迼ǸӰӣӦְԱʷӹݵ

    2ԱȹУȻǵԱ١ΪߺʱԱͲԱǼ뻯ʵҵҵԱʶӰҵЧʣҵԱijЩ;뿪ЩضϵͳԱӰ졣һϵͳԱӦԴ

    3ŲȹУûпǹתʱ䣬ʵʹ£תʱ佫ŲһӰ졣һģͽһƣʹϵͳʵʹ

    4Ĺ̻еװ䳵 MES ϵͳԼ򵥣ϵͳܽһ

    л

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    ȣԵظлҵĵʦ߷ڣʦҵľָ࣬ڿѧ̬ȡѧϽľ񣬶ڹ󾫵һֱؼ͸ȾҡҲڸʦϤָɵģѡٵĵ׫дÿһڶע˸ʦѪܹȡõijɼͽ벻ʦ׻׻̻塣ڴ˱ҵ֮ʣʦߵľĵĸллѧҵϵϤָϵ

    лʦҿйʱΪṩ˼·ʦѧʶԨѧϽɼҵĿѡ⡢оչУṩ˹ؼӱͼ⣬Ϊо˳չṩָʦԹ桢ѧϽԿеСѧչԼص˸Ӱңѧϰİ

    лʦμ̺ʦ˰ʦĿÿܵĹչ㱨мʱ飬·л¸ոڡʷ㸱ڡڡǺʦʦʦʦʦʦŶʦԪʦĿճоиͽ顣

    лΰΡ۱֡׷塢눐ʦֺΡٳܰŽࡢʦ㣬ҳʱҹذмӣҿ뵽ҵĿзΧлͬΡǿ͢㡢Ԫۡ쾡ΰ½˸˸ǿ֣ڼѧϰиҵİиҴĻ֡

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