摘 要
随着多品种小批量生产模式的逐步兴起,多品种小批量生产模式的工时定额管理还不够成熟.在批量产品的定额中与生产实际工时偏差较大,无法预期产品交货期,影响了企业产品在市场的竞争力.如何制定更加准确的工时定额,是多品种小批量生产企业亟待解决的问题.
强大泵业主轴车间生产的主轴为多品种小批量产品,现行工时定额管理存在很大问题.本文以主轴工时定额为研究对象,对车间现行工时定额现状进行分析,找出存在的主要问题.以秒表法对定额时间中的准备结束时间、布置场地时间、休息时间和作业时间中的手动时间与机手并动时间进行实测与制定,运用 SPSS 软件拟合作业时间中不同参数主轴机动加工时间实测数据,构造机加工工时模型,最终得出主轴产品的标准工时定额;再通过对批量新产品中作业时间随着产量的累加工时逐渐减小的规律,运用 SPSS 软件拟合学习曲线幂函数,构造计划修正系数,对主轴标准工时定额中作业时间进行修正,得到最终批量产品的计划工时定额.通过引入的学习曲线理论对标准工时定额中作业时间修正得到批量产品的计划工时定额更加符合生产实际,在主轴车间实施计划工时定额编制生产计划,缩短了产品的安全期,实现了按期交货的目的,提高了企业竞争力.
关键词 多品种小批量,学习曲线,SPSS 拟合工时模型,计划工时定额
Abstract
With the gradual rise of multi-variety and small-batch production modes, the man-hourquota management for multi-variety and small-batch production models are not matureenough. In the quota of batch products, there is a large deviation from the actual productionoperation time so that the product delivery date cannot be expected, which affects thecompetitiveness of the enterprise products in the market. How to formulate more accuratetime quotas is an urgent problem to be solved by multi-variety small-batch productionenterprises.
The Spindle Workshop in Qiangda Pump Industry are multi-variety and small-batchproducts, and there are great problems in the current man-hour quota management. In thispaper, taking the spindle man-hour quota as the research object, the present situation of thecurrent man-hour quota in the workshop is analyzed so as to find out the main problems.The time for preparation and end, allowed time for organization, allowed time for individualneeds and relaxation, hand time and overlap time of machine and hand are measured anddetermined by the stopwatch method. Using SPSS software to fit the measured data of thespindle machine time of different parameters in the Time quota, to construct the machinetime model, and finally obtain the standard time quota of the spindle product; Then, byadopting the law that the operation time of batch new products is gradually reduced withthe processing of production, the SPSS software is used to fit the power function of thelearning curve, the plan correction coefficient is constructed, and the operation time in thestandard time quota of the spindle is corrected to obtain the final Planned time quota forbulk products. By introducing the learning curve theory, the work time in the standard worktime quota is modified, and the planned work time quota of batch products is moreconsistent with the actual production.The production plan is prepared in the main shaftworkshop, and the safety period of the product is shortened, the purpose of delivery onschedule is realized, and the competitiveness of the enterprise is improved.
Key words Multi-variety small batch; Learning curve; SPSS fitting mathematical model;Planned time quota
目 录
摘 要 ·································································································· I
Abstract ······························································································· III
第 1 章 绪 论 ····················································································· 1
1.1 研究背景及意义 ········································································ 1
1.1.1 研究背景 ········································································· 1
1.1.2 研究意义 ········································································· 1
1.2 国内外研究现状 ········································································ 2
1.2.1 国外研究现状 ··································································· 2
1.2.2 国内研究现状 ··································································· 2
1.3 研究内容 ················································································· 3
1.4 研究方法及技术路线 ·································································· 4
1.4.1 研究方法 ········································································· 4
1.4.2 技术路线 ········································································· 4
第 2 章 相关理论与方法 ········································································· 7
2.1 工时定额理论基础 ····································································· 7
2.1.1 工时定额概念 ··································································· 7
2.1.2 工时定额的组成 ································································ 4
2.1.3 工时定额的组成分析 ·························································· 7
2.1.4 工时定额制定额依据 ·························································· 7
2.1.5 工时定额制定的方法 ·························································· 8
2.1.6 工时定额理论的应用 ·························································· 8
2.2 工业工程工作研究 ····································································· 8
2.2.1 工作研究概述 ··································································· 8
2.2.2 方法研究概述 ··································································· 9
2.2.3 作业测定概述 ··································································· 9
2.3 学习曲线理论 ·········································································· 10
2.4 本章小结 ················································································ 10
第 3 章 主轴车间工时定额管理现状 ························································· 13
3.1 强大泵业公司概况 ···································································· 13
3.2 主轴车间概况 ·········································································· 14
3.3 主轴车间现行工时定额现状 ························································ 16
3.4 主轴车间现行工时定额管理存在的问题 ········································· 16
3.5 本章小结 ················································································ 18
第 4 章 主轴车间计划工时定额制定 ························································· 19
4.1 计划工时定额制定的思路和方法 ·················································· 19
4.2 计划工时定额的主要技术路线 ····················································· 19
4.3 准备与结束时间制定 ································································· 20
4.4 作业时间的制定 ······································································· 23
4.4.1 手动时间与机手并动时间的制定 ·········································· 24
4.4.2 机动加工时间的制定 ························································· 30
4.5 宽放时间的制定 ······································································· 36
4.6 主轴标准工时的确定 ································································· 37
4.7 主轴计划工时的制定 ································································· 38
4.7.1 学习系数的确定 ······························································· 38
4.7.2 标准批量的确定 ······························································· 39
4.7.3 计划修正系数的确定 ························································· 40
4.7.4 计划工时定额的制定 ························································· 40
4.8 主轴计划工时数据库的建立 ························································ 41
4.9 主轴车间计划工时定额实施与效果评价 ········································· 42
4.9.1 主轴计划工时定额实施应用 ················································ 42
4.9.2 主轴计划工时定额效果评价 ················································ 44
4.10 本章小结 ··············································································· 45
第 5 章 结论与展望 ·············································································· 47
5.1 研究结论 ················································································ 47
5.2 展望 ······················································································ 47
参考文献 ····························································································· 49
攻读硕士学位期间发表的论文 ·································································· 53
致 谢 ································································································ 55
第 1 章 绪 论
1.1 研究背景及意义
1.1.1 研究背景
随着市场的需求多样化,制造业的生产模式逐步转化为多品种小批量生产,该生产模式下产品品类众多、批量小且生产周期短[1].但由于该生产模式下品类众多,产品交互性强,造成产品在生产管理过程中难以进行控制,不能够有效的保证产品的交货期.产品交货期的有效保证,才是在日趋竞争激烈的市场环境中生存的关键.多品种小批量的生产模式下,产品的生产还未达到生产稳定期便已加工完成,难以获得大量的重复生产数据,这使得传统定额方法在多品种小批量生产的应用中与生产实际产生较大的偏差,无法实现对产品加工时间和加工过程的有效控制.
多品种小批量机械加工企业在进行生产管理过程中运用现行工时定额进行核算生产设备和人员的工时时,由于生产产品的新旧不同、批量大小不同和工人操作熟练度不同等原因,制定的工时定额与工人生产前期过程的实作工时误差较大,造成企业生产作业计划与生产能力产生不平衡的现象.目前大多数多品种小批量生产企业直接使用固定周期法进行编制生产计划,生产作业计划的完成率仅在 40%~90%之间,严重影响了企业产品的交货期和资金占用周期.因此需要实施计划工时定额对多品种小批量产品进行定额.实施计划工时定额以满足生产实际,把制定的生产作业计划控制在较小的安全期内[2].
以强大泵业主轴车间为研究背景进行计划工时定额的研究,基于工业工程作业测定技术,运用秒表法和数学模型法对新产品进行标准工时的测定后再通过 SPSS 软件拟合学习曲线构造合适的计划修正系数对标准工时中作业时间进行修正,得到计划工时定额;对于老产品通过对历史数据的分析以适当的计划修正系数进行修正得到计划工时定额.计划工时定额更加符合多品种小批量产品的生产特点,从而提高编制生产计划的准确率,建立的主轴计划工时定额,能够预期产品交货期,提高主轴车间的生产管理水平.
1.1.2 研究意义
要想本企业在竞争激烈的市场环境中生存,需要不断的去改善车间的生产管理方法来应对需求不断变化的市场.本文以多品种小批量生产模式的主轴为研究对象,运用工业工程作业测定技术,结合产品加工工艺和产品特点,首先对多品种小批量产品主轴进行进行时间模型研究,制定出标准工时[3].再引入学习曲线理论对标准工时中作业时间进行修正,得到适合多品种小批量产品的计划工时定额.通过实施计划工时定额优化主轴车间工时定额管理水平、降低成本,以期能为多品种小批量制造企业解决因工时定额管理落后而带来生产和管理问题提供有效思想,为企业准确制定诸多生产计划、科学排产和高效管理提供合理基础[4].
对主轴进行计划工时定额研究,完善主轴车间的的生产管理制度,能够准确的核算主轴车间的生产能力,预期产品的交货期,提高主轴车间的生产效率,优化车间工时定额管理水平.通过主轴计划工时定额的实施,使主轴车间工时定额管理更加符合多品种小批量产品的生产实际,将生产偏差控制在合理的范围内,从而有效的保证产品的交货期[5].同时可以将计划工时定额用于工人的绩效考核,预期工人的生产数量,设置激励以提高工人的生产积极性和工作热情,从而促进生产技术水平的提升和劳动效率的提升,最终提高经济效益.计划工时的实施,不但可以统计出工人的劳动总量,也能分析出车间生产工作强度、工人操作方法和劳动状况,科学合理的准确评定工人的劳动贡献,并进行分配劳动所得,平衡工人间的分配尺度等,保证主轴车间按劳分配制度实施[6].
1.2 国内外研究现状
1.2.1 国外研究现状
泰勒的作业测定是目前大多数制造企业制定工时定额常用的方法.作业测定通过秒表法和影像分析等方法对生产现场工人的生产过程和生产数据进行观察、测定和记录,再通过对生产数据的统计和分析得到标准作业时间和宽放时间.在生产周期重复性较强的工序中应用作业测定和方法研究进行结合,制定出有效合理的标准工时,提高车间的生产效率[7].1920 年,西格秉承经济最大化原则,通过对每一项操作动作进行研究,科学划分动作要素,提出了动作时间分析法,并发表了《动作时间分析》一书,提出了方法时间衡量、基本动作时间研究等预定时间标准法.罗亚和多赛特等学者对工时的消耗时间进行研究,发现工人熟练程度、作业时间长短、作业空间大小和作业类型以及作业的多样性等等均对工时产生了显着影响,并基于这些测定作业时间[8].澳大利亚博士哈依德在 1966 年基于人类工效学原理基础上建立了模特排时法,对于工时定额的制定又提出了一重大创新理论,并在多个制造企业中取得了显着的效果,明显的提升了经济效益,得到各制造行业的认可[9].
1.2.2 国内研究现状
相比于国外,我国国内对标准时间的研究起步较晚,并且对于标准工时的应用不够重视[10].国内大多数制造企业没有科学的理论和方法制定工时定额,不能够符合生产实际,目前车间的生产管理中加班赶工已经称为制造行业的常态,使制造企业的工时定额管理水平处于落后状态[11].随着市场经济的不断发展,我国制造业也越来越重视车间工时定额的管理.学者们通过利用各种工业工程技术并结合其它各种学科先进的技术在工时定额管理方面不断进行深入研究.
随着各学科技术理论的不断发展与创新,学者们都在进行着交叉学科研究,把其它学科理论研究引入到工时定额管理中,有效的改善了工时定额管理的水平.刘刚等学者引入数学等理论对工时定额标准进行研究,在整个研究过程中量化工时定额标准的工作路线,通过制定工时模型来确定产品的工时定额;陈国钧在统计计算方法的基础之上,把概率论中数理统计方法引入到工时定额的制定过程中来,进行统计分析实际发生工时,并对工时定额进行估算,有效的提高了工时定额的准确性;付斌通过定额量测算和置信度分析等方法进行工时定额的深入研究,提高了工时定额的准确性,并提出了对定额方法的合理性评价[12];李淑娟等学者采用神经网络算法技术对生产实例进行分解详细研究,构建生产工时预测模型;钟宏才分类归纳了影响工时定额的各种要素,并确定主要影响工时要素,将其代入神经网络算法中,最终得到加工工时模型[13].
随着科技的不断发展,计算机信息技术不断在工时定额管理和研究中得到广泛的应用[13].Sharafeev 通过计算机技术研究设计了工时计算方法;张吉楠开发出计算机辅助工时定额测算系统,大大的提高了工时定额制定的效率;祁光威开发出专门的工时定额管理系统,将工时定额管理工作更加高效化和信息化;董晓宇利用 ERP 技术将工时定额管理与日常生产管理 ERP 系统有效结合,实现了生产管理与工时管理的快速衔接,提高了工时定额管理的水平[14].
目前学者们虽然在工时定额管理上不断进行着大量科学有效的研究,但是针对多品种小批量制造企业的产品特点的工时定额研究还处于起步阶段,还有待进一步深入研究.
1.3 研究内容
本文通过主轴车间现行工时定额管理现状,引出机械加工多品种小批量产品工时定额存在的问题,并以主轴车间主轴的工时定额为研究对象,从发现问题、提出方案、解决问题到实施效果评价的全过程的计划工时定额制定.
具体研究内容如下:
首先,指出现阶段下多品种小批量生产企业现行工时定额管理状况,明确现阶段多品种小批量生产企业在工时定额管理中的需求,引出为何要制定计划工时定额以满足生产实际,进行合理排产,保证产品的交货期.
其次,具体说明强大泵业主轴车间现行工时定额管理中存在的问题,并分析问题,为接下来的具体问题的解决提供依据.
最后,结合主轴的生产流程,提出对多品种小批量产品的定额方法改善方案,对主轴进行标准工时的测定,再通过构建计划修正系数对标准工时中作业时间加以修正,得到主轴产品的计划工时定额,使之更加符合产品的生产实际.并进行实践,对实施效果进行评价与总结,发现不足,并进行展望.
1.4 研究方法及技术路线
1.4.1 研究方法
本文主要通过文献分析法、数学建模法、秒表法和 SPSS 软件与具体案例分析结合的方法来制定计划工时定额.
(1)文献研究法
以已有研究成果为基础,学习多品种小批量产品工时定额相关理论方法,广泛吸收有益于本论文研究的思路、观点和方法,查阅国内外相关的理论文献,从相关课题研究实践中吸收与发展这些研究成果,为本文制定计划工时定额提供研究技术和方法.
(2)数学建模法
对作业时间中机动加工时间数据利用 SPSS 软件拟合数学模型,构建机加工工时模型.
(3)秒表法
运用工业工程作业测定技术中秒表法对主轴生产过程中手动时间和机手并动时间划分的各操作单元进行实测,并进行数据的记录.
(4)学习曲线
引入学习曲线理论,将批量生产的主轴工时数据运用 SPSS 软件拟合学习曲线幂函数,得到学习系数.
…………由于本文篇幅较长,部分内容省略,详细全文见文末附件
第 5 章 结论与展望
5.1 研究结论
本文通过多主轴车间计划工时定额的研究,现行工时定额管理中存在不科学、不规范、定额效率低等问题.进一步分析主轴车间现行工时定额管理现状发现,现行工时定额与生产实际过程中工人的实作工时偏差较大,编制出的生产计划不合理,不能够预期产品的交货期.现行工时定额不符合多品种小批量产品,因此需要制定主轴生产计划工时定额的方法和手段来解决当前主轴工时定额存在的问题.本文结合工业工程经典作业测定技术,并运用 SPSS 软件拟合数据构造加工时间模型,确定符合多品种小批量产品的标准工时定额方法,同时引入学习曲线理论,对生产初期零件生产数据拟合学习曲线幂函数,构造计划修正系数,对标准工时中的作业时间加以修正,得到批量主轴产品的计划工时定额.通过计划修正系数对标准工时中作业时间的加以修正,能够有效提高多品种小批量产品工时定额的准确性和提高生产计划的准确性,有效的预期产品交货期.从而对产品生产过程进行有效的把控,对生产管理过程进行有效的改善.
本文主要通过对工时定额相关理论方法的研究,结合主轴现行工时定额现状进行分析,指出目前多品种小批量生产企业工时定额面临的普遍问题.以主轴生产为研究对象,分析主轴现行工时定额存在问题,并对问题进行分析,发现批量较小的主轴生产定额中作业时间比实作工时要短,与生产实际产生较大的偏差.先对主轴进行标准工时的测定,根据主轴的工特点采用秒表法和构造加工时间模型的方法将定额时间分类进行测定.然后从主轴作业时间下手,引入学习曲线理论,对主轴标准工时中作业时间进行修正,最终得到批量产品的计划工时定额,更加符合生产实际,用计划工时定额编制的生产计划更加准确.
5.2 展望
本文制定的主轴计划工时定额方法同样适用于其它多品种小批量生产企业.通过计划工时定额的实施,可以对车间现行工时定额管理进行改善,提高车间工时定额的管理水平,能够有效的控制产品的生产过程,更加准确的预期产品的交货期.计划工时定额制定的过程中任务量大,过程复杂,需要长期的积累和众多员工的参与,计划工时定额的目标是为了不断提高工时定额的准确性.在不同的生产环境中,计划工时定额制定的方法不同.计划工时定额的制定需要多方法、多目标的不断的去进行优化,需要更加深入详细的去研究.
对于多品种小批量生产模式的制造企业来说,只有从最基础的制造车间下手,优化车间内的生产管理,提高车间内的工时定额管理水平,降低成本,提高劳动生产率,才能够应在激烈的市场环境中生存.在企业内部制造车间需要不断去学习并制定每个工艺流程的计划工时制定方法,进一步把计划工时定额系统整合到企业的成本控制、劳动定员、生产计划的编制中,将计划工时定额更加细化并通过计算机辅助开发设计适合多品种小批量生产企业的计划工时系统,才能不断去提高企业的生产管理效率,才能在竞争日趋激烈的市场中发展下去.
参考文献
[1] 张毕西, 周艳, 刘鑫. 离散生产系统车间布局优化[J]. 工业工程, 2004, (02): 8-11.
[2] 薛伟,蒋祖华. 工业工程概论. 北京: 机械工业出版社, 2015, 7-9
[3] 刘伟亮. 机械加工车间动态生产计划于监控系统研究. [河北科技大学硕士论文]. 河北: 河北科技大学, 2010
[4] 王娜. 汽车焊装生产线工时定额研究. [天津大学硕士论文]. 天津: 天津大学, 2012
[5] 涂迪思. 基于计划行为理论的人格特质对社会责任消费意向的影响研究. [杭州科技大学硕士论文]. 杭州: 杭州科技大学, 2014
[6] 汪应洛. 系统工程方法论. 西安: 机械工业出版社, 2016, 13-15
[7] 郭伏,钱省三. 人因工程学. 北京: 机械工业出版社, 2017, 17-19
[8] 孙绍文. 中小型单件制造企业 CAPP 系统中工时定额编制子系统的开发. [华中农业大学硕士论文]. 湖北: 华中农业大学, 2008
[9] 贾丽秀. 工时定额在某制造型企业的应用研究. 北京: 机械工业出版社, 2013, 6-9
[10] 潘春荣. 秒表法在工时定额中的应用. 北京: 机械工业出版社, 2012, 23(2): 62-65
[11] 周惠民. 单件小批量生产的工时定额方法及其系统开发研究. [重庆大学硕士论文]. 重庆:重庆大学, 2014
[12] 孔造杰. 运筹学理论. 北京: 机械工业出版社, 2017, 10-13
[13] 程朗. UP 公司叶片生产作业测定及效率提升. [南京理工大学硕士学位论文]. 南京: 南京理工大学, 2016
[14] 王亚婷. 平准化在一汽轿车生产组织中的应用研究与创新. [天津大学硕士论文]. 天津: 天津大学, 2012
[15] 易树平, 郭伏. 基础工业工程. 北京: 机械工业出版社, 2006, 35(3): 34-35
[16] 朱耀祥, 朱立强. 设施规划与物流. 北京: 机械工业出版社, 2004
[17] 王家善, 吴清一, 周家平. 设施规划与物流. 北京: 机械工业出版社, 1995
[18] 刘勇. 四平鼓风机厂的动态生产计划管理方法研究. [大连理工大学硕士论文]. 大连: 大连理工大学, 2011
[19] 郝云宏, 向荣. 管理学. 北京: 机械工业出版社, 2019, 17-23
[20] 曹智安. 多品种小批量生产计划与控制优化技术研究. [沈阳工业大学硕士论文]. 沈阳: 沈阳工业大学, 2005
[21] 胡洲. L 公司车间布局优化与生产物流仿真研究[D]. 广西大学, 2016.
[22] 张迪. 大规模定制环境下基于工艺相似性的工时模块化方法研究. [重庆大学硕士论文]. 重 庆: 重庆大学, 2014
[23] J. H. Holland. Adaptation in National and Artificial System. The Univ. Michigan Press, Ann Arbor,MI, 1975.
[24] J. D. Bagley. The Behavior of Adaptive System Which Employ Genetic and Correlation Algorithm.Dissertation Abstracts International, 1967, 28(12)
[25] D. E. Goldberg. Genetic Algorithms in Search, Optimization and Machine Learning. AdaptationWesley Publishing, 1989
[26] Liang He, Wan Lin Guo. A Logistics Model of Total Life Cycle of Mechanical Products. AppliedMechanics and Materials, 2013, 2141(248)
[27] Akhilesh, Kumar, Prakash, M.K. Tiwari, Ravi Shankar and Alok Baveja. Solving Machine-loadingProblem of a Flexible Manufacturing System with Constraint-based Genetic Algorithm. EuropeanJournal of Operational Research, 2006, 175: 1043-1069
[28] M. Adel, El-Baz. A Genetic Algorithm for Facility Layout Problems of Different ManufacturingEnvironments. Computers & Industrial Engineering, 2004, 47: 233-246
[29] Housni Djellab, Gourgand. A new heuristic procedure for the single-row facility layout problem[J].Computers & IndustrialEngineering, 2001, 14(3): 270-280.
[30] E. Zouein, H. Harmanani. A. najat. Genetic Algorithm for Solving Site Layout Problem withUnequal-Size and Constrained Facilities[J]. Journal of Computing in Civil Engineering, 2002, 4:143-151.
[31] 陈友玲, 阮键, 王尧. 大规模定制环境下基于产品结构复杂度的工时定额制定研究. 计算机应用, 2016, (34):
[32] 王慧聪, 陈友玲, 张树梁. 大规模定制下误差修正系数的工时算法研究. 计算机工程与应用,2013, (12): 33-34
[33] 邮韶妮. 基于成组技术的工时定额方法研究. [武汉理工大学硕士论文]. 武汉: 武汉理工大学,2010.
[34] 钟卉, 廖兰芳. 企业标准工时定额管理的实践与思考. 经营管理, 2017, (11): 118-119
[35] 麦毅成. 电火花线切割火花参数分析研究. [广东工业大学硕士论文]. 广东: 广东工业大学,2015.
[36] 李春杰, 肖素梅. 成组技术的产生与发展. 黑龙江史志, 2006, (4): 10-11
[37] 潘全科, 孙志俊, 朱剑英. 基于遗传算法的作业车间调度优化阴. 信息与控制, 2002, (3): 216-218.
[38] Tengku Nurul Aishah Tengku Aziz, Harlina Suzana Jaafar, Ramlah Mohd Tajuddin. Green SupplyChain: Awareness of Logistics Industry in Malaysia. Procedia - Social and Behavioral Sciences,2016, 219
[39] Saurabh Agrawal, Rajesh K. Singh, Qasim Murtaza. Disposition decisions in reverse logistics:Graph theory and matrix approach. Journal of Cleaner Production, 2016
[40] Vladimír Vavrík, Milan Gregor, Patrik Grznár. Computer Simulation as a Tool for the Optimizationof Logistics Using Automated Guided Vehicles. Procedia Engineering, 2017, 192
[41] Helena Fidlerová, Miroslava M?kva. Improving the Reverse Logistics Respecting Principles ofSustainable Development in an Industrial Company. Research Papers Faculty of Materials Scienceand Technology Slovak University of Technology, 2016, 24(37)
[42] Liang He, Wan Lin Guo. A Logistics Model of Total Life Cycle of Mechanical Products. AppliedMechanics and Materials, 2013, 2141(248)
[43] 王海涛. 现威数控机床公司客户关系管理研究. [燕山大学硕士论文]. 秦皇岛: 燕山大学,2018
[44] 李海军. 浅谈纺织机械公司工时定额管理. 机电信息报, 2014, (11): 153-161
[45] 李闯. 多品种小批量制造企业工时定额方法研究.[大连理工大学硕士论文]. 大连: 大连理工大学, 2017
[46] 孙绍文.中小型单件制造企业 CAPP 系统中工时定额编制子系统开发.[华中农业大学]. 湖北:华中农业大学, 2017
[47] E.Zouein, H.Harmanani. A.najat.Genetic Algorithm for Solving Site Layout Problem with UnequalSize and Constrained Facilities[J]. Journal of Computing in Civil Engineering, 2002, 4: 143-151.
[48] Yunbo Bi, Weimiao Yan, Yinglin Ke. Multi load-transmitting device based support layoutoptimization for large fuselage panels in digital assembly. Proceedings of the Institution ofMechanical Engineers, Part C: Journal of Mechanical Engineering Science, 2015, 229(10)
[49] Heng Li, E.D.Peter, L.Site-Level. Facilities Layout Using Genetic Algorithms[J]. Journal ofComputing in Civil Engineering, 1998, 10:227-231.
[50] D. Elilraja, Sundaravel Vijayan. Particle Swarm Optimization for Integrated Fixture Layout.Applied Mechanics and Materials, 2015, 4123(787)
[51] Meller R D, Bozer Y A. A new simulated annealing algorithm for the facility layout problem[J].International Journal of Production Research, 1996, 34(6): 1675 一 1692.
[52] 刘太平. A 公司电动工具圆锯片生产精益优化研究. [江西理工大学硕士论文]. 江西: 江西大学, 2017
[53] 潘磊. 四川理工学院校园宽带运维管理系统的设计与实现. 计算机技术, 2016, (08): 85-88
[54] Rosenblatt M J. The dynamics of plant layout[J]. Management Science, 1986, 32(1): 76-86
[55] Mohd Azrin bin Mohd Said, Napsiah Binti Ismail. Virtual Production Line Layout Modeling UsingArena Simulation Software. Applied Mechanics and Materials, 2013, 2622(393)
[56] I. El Mouayni, A. Etienne, A. Siadat, J-Y. Dantan, A. Lux. A simulation based approach forenhancing health aspects in production systems by integrating work margins. IFAC PapersOnLine,2016, 49(12)
[57] E.Zouein, H.Harmanani. A.najat.Genetic Algorithm for Solving Site Layout Problem with UnequalSize and Constrained Facilities[J]. Journal of Computing in Civil Engineering, 2002, 4: 143-151.
[58] Dominika Jurovata, Pavel Vazan, Lukas Hrcka, Julia Kurnatova. Input Control in ProductionSystem by Simulation Optimization. Applied Mechanics and Materials, 2014, 3592(693)
[59] J.D. Bagley. The Behavior of Adaptive System Which Employ Genetic and Correlation Algorithm.Dissertation Abstracts International, 1967, 28(12)
[60] L.Zhang, L.Wang. Genetic Ordinal Optimization for Stochastic Traveling Salesman Problem.Proceedings of the World Congress on Intelligent Control and Automation (WCICA), 2006,13(8):2086-2090
[61] Scheffer, Tobias Rahm, Markus K?nig, Markus Thewes. Simulation-Based Analysis of IntegratedProduction and Jobsite Logistics in Mechanized Tunneling. Journal of Computing in CivilEngineering, 2016
