From a10af6314659fc9c76f9ff3371e4eeefe0c4d9c8 Mon Sep 17 00:00:00 2001 From: BogdaLD Date: Thu, 30 Nov 2023 23:55:54 +0800 Subject: [PATCH] Site updated: 2023-11-30 23:55:53 --- .../index.html" | 386 +++++++++++ .../index.html" | 419 ++++++++++++ about/index.html | 287 ++++++++ archives/2023/11/index.html | 132 +++- archives/2023/index.html | 132 +++- archives/index.html | 132 +++- atom.xml | 56 ++ categories/index.html | 286 ++++++++ css/main.css | 616 ++++++++++++------ images/Bogda Peak of Tian shan Mountain.jpeg | Bin 0 -> 226546 bytes images/avatar of LD.jpg | Bin 0 -> 288101 bytes .../index.html => images/hello-world.html | 186 +++--- index.html | 303 ++++++++- search.xml | 67 ++ tags/index.html | 293 +++++++++ .../index.html" | 297 +++++++++ .../index.html" | 297 +++++++++ 17 files changed, 3500 insertions(+), 389 deletions(-) create mode 100644 "2023/11/29/\345\217\221\345\210\212\346\204\237\346\203\263/index.html" create mode 100644 "2023/11/30/\345\246\202\344\275\225\346\224\271\351\200\240\346\210\220\344\270\272\346\231\272\350\203\275\345\210\266\351\200\240\345\267\245\345\216\202\357\274\237\350\256\251\346\210\221\344\273\254\344\273\216OEE\345\274\200\345\247\213/index.html" create mode 100644 about/index.html create mode 100644 atom.xml create mode 100644 categories/index.html create mode 100644 images/Bogda Peak of Tian shan Mountain.jpeg create mode 100644 images/avatar of LD.jpg rename 2023/11/28/hello-world/index.html => images/hello-world.html (54%) create mode 100644 search.xml create mode 100644 tags/index.html create mode 100644 "tags/\345\217\221\345\210\212\350\257\215/index.html" create mode 100644 "tags/\346\231\272\350\203\275\345\210\266\351\200\240-OEE/index.html" diff --git "a/2023/11/29/\345\217\221\345\210\212\346\204\237\346\203\263/index.html" "b/2023/11/29/\345\217\221\345\210\212\346\204\237\346\203\263/index.html" new file mode 100644 index 0000000..6c32bd3 --- /dev/null +++ "b/2023/11/29/\345\217\221\345\210\212\346\204\237\346\203\263/index.html" @@ -0,0 +1,386 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +发刊感想 | 博格达峰下的赶路人 + + + + + + + + + + + + + + +
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博格达峰下的赶路人

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对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考

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+ 发刊感想 +

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参加工作以来我就认为,只有终身学习才是职业发展的根本动力,为此不断的工作和生活中参加各种学习活动,自己电脑中的各种材料(电子书、白皮书……)加起来也几十个G了,但是后来发现自己沉迷于“厚积”,却忘了“博发”。

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博客的动机

记得有一个理论说,最好的学习方式是将自己的学习成果进行展示,教会别人。在教会给别人的同时自己的也得到了学习的深化。很有道理,所以我想对自己的知识进行“博发”深度学习是这个博客的第一动机吧。
从机械专业毕业却进入到工业自动化企业工作,本想做个技术宅,但是“阴差阳错”下做了销售工程师、产品经理和项目经理。在职业的成长中,对工业企业中“产品管理”、“项目管理”和其它管理给自己带了很多的感谢,与看客分享自己的“博闻”,得到认可或讨论,也许是博客的第二动机。
虽然离开了技术的专深,但确始终在工业自动化这个“大圈子”中游弋,随着工业信息化的发展,工业技术也进入了全新的阶段,有幸在自动化的工业信息技术的工作经历,自己也算是OT于IT都有所专擅的“广博”之辈,很想把这个博采与同道一起分享,这算是博客的第三动机。
其实搭建这个博客实际上还是花了一些时间,由于不想在传统的CMD中进行写作,所以在学习了几篇帖子以后,决心自己搭建这个博客,到底是岁数大了,还是有些费劲。不过总算折腾出来了。

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一点期望

我其实写作的能力一般,而且也不知道会什么时候突然就不想写了,但是我的另外一个习惯是,只要去做就想办法做到精致,所以博客中的文章会有很多的别人的文章,但一定会有自己的思考。这些思考或许不一定正确,但是如果有看客能给我提出指正,那我会诚挚感谢,并进行在学习和研究。
或许,也有看客可以通过我的文章后,想和我合作一些项目,那也许会成为我以后发博的第四动机和成长动力吧。

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hello http://example.com/2023/11/29/发刊感想/ bye

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博格达峰下的赶路人

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+ 如何改造成为智能制造工厂?让我们从OEE开始 +

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#智能制造的回顾与困惑
从德国政府宣布的工业4.0开始算起,新一代工业设施建设也已近10年了。而从计算机集成制造技术进入工厂实践开始,数字化制造或者智能制造的理念的推广可能还要更早,对中国的工厂管理者来说已经不是什么新鲜的概念了。就中国开工建设的“灯塔工厂”数量也是世界之最。所谓“数字孪生”“工业互联网”“IIoT”“人工智能”“SaaS”“PaaS”这些热词,即便是车间的班组长也都有所听闻并不陌生。

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然而在实践中,除少数行业头部和大型企业以外,更多的中小型企业恐怕并没有真正去考虑建设或者升级成智能制造工厂。
成为智能制造企业,可以提高工厂的竞争力,提高生产柔性、降低运营成本,为企业带来更多的收益,难道这些听起来“不香”嘛?香或许是香,但是这些新建和升级并不是没有代价的,甚至在等来可见的“收益”前,前期投资已经让不少中小企业不堪重负了。

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面对UNCA时代的挑战,特别是疫情后全球供应链挑战,制造业转移和回流,过去以性价比见长的中国制造业特别是中小型制造企业,必须要拥抱数字化与智能化来确保未来的竞争力。

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这样就出现了“进则担负升级改造的高投入风险,退则抱残守缺逐渐丧失竞争力”的两难局面;如何破局?小步快跑,边走边跑或许是一个中小企业可取的办法。具体说就先从简单的、可见的、可迅速与提高制造效率和收益的项目开始,比如,就可以从实践OEE的自动可视化开始……

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#什么是OEE?其历史与对制造工厂的提高?
OEE是Overall Equpment Efficiency的缩写,翻译为综合设备效率,也有会翻译成设备稼动率;其意义是通过考量设备的运行时间、性能和质量来评估设备在生产过程中的效率和利用率。

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简而言之就是观测设备的有效运行状况判断当前设备的“赚钱”的能力。这就好比很多出租车运营者会考虑让两个或三个司机轮换开车来提高车辆的运营,通过多跑载客时间或里程,减少空闲,提高收益。

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OEE的概念进入最早是在以精益制造而闻名的丰田的TPS系统中,在TPS中其中一个重要的内容就是TPM,即全员生产性维护,通过提供现场操作人员对设备进行即时与定时的保养,是设备始终保持在一个良好的作业状态,从而提供制造的效率和质量,减少如设备停机,不良品返工等浪费现象(六大损失),其中OEE就是度量当个设备的运行状态的重要指标KPI
OEE的计算公式是:

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OEE = 设备的可用率X设备的效能率X产品良品率,
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这其中:

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  1. 设备的可用率,是指设备的实际工作时间与设备计划工作时间的比率,
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  3. 设备的效能率,是指设备无故障工作时间和折算的全速工作时间与实际工作时间的比率
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  5. 设备的良品率,就如字面意思一样就是设备生产的合格品与所有产出品的比率
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在逻辑上,只要我们提高的OEE,也就意味着可以提高设备的可用时间,提高产品的质量,从而为企业创造了更高的价值。

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如此好的工具,但实施起来并不是那么容易的,特别是对中小企业而言。原因如下:

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  • OEE本身和企业的收益联系并不是直接可显的,特别是通过公式我们可以看到这个OEE实际上是一个时间窗口的计算值,而且还是一个滞后指标。通过OEE来分析其提高的途径,或许可以间接的提高企业的综合收益,但是这也绝非一朝一夕就可以实现的。
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  • 最初的OEE都是通过人工手动来完成的,在大型制造企业中,这些数据的收集都是有车间的价值流经理、精益专员来完成,少数有设备的操作员来完成,使用人工测量和计算对数据的准确性提出挑战,而如果对操作员来完成相关测量,有可能降低操作员工作效率,更不用说人力资源紧张的中小型企业;
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  • 或许有的自动化设备提供了可以在线实施测量设备工作状态的数据接口,但是也会有设备数据的转换、数据通讯协议的转换等相关问题,对现场的OT和IT工程师提出了挑战;
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  • 特别是不同数据如何获取、从什么渠道获取,并且让数据可以建立相关联系并展现出来,不仅是对中小企业,即便是拥有_数据科学家和数据工程师_的大企业也需要仔细面对。
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  • 特别是对于一些重要生产设备但非自动化设备,如果不考虑用专门的人员来测量和计算其设备相关设备,如何通过适当的改造,最好是不停机改造来实现设备数据采集,又不至于对现下的生产产生中断和大影响,这对缺少自动化与数字化工程师和相关经验的中小企业都是挑战;
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另外还有现场设备太多,设备协议太多……等问题,也是阻碍OEE实施的一些原因。

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#智能化与数字化制造,从OEE开始
虽然有上述很多困难阻碍OEE的实施,但借助工业物联网(IIoT)的技术发展普及,OEE的项目实施依旧是中小企业开始数字化和智能制造升级的最重要与最合适的第一步,这就是OEE自动化数据获取;

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数字化转型与精益生产的思想是一致的,就是从客户的需求出发进行制造,与其无目标的收集数据,又或者目标太多需要大量大范围数据,OEE的KPI需求是明确的且可以明显反映设备生产状况的,可以拉动相关设备数据采集和改进方向;

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通过OEE的数据,中小企业迅速判断当前的设备投资状况,比如,与其购买添置新设备,是否可以通过提高设备OEE来发掘潜力,减少重复投资;又或者通过OEE比较,寻找整个生产流程的瓶颈,并加以改善;

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相对于复杂的商业智能BI或者其它数字辅助决策,OEE所需要的数据量是非常有限的,这样对升级所需的投资规模也是合理与可控的,如果是自动化设备且具有相应数据开放的接口,或许仅需要一些软件的升级与修改就可以完成,而对于性能良好的“哑巴”设备,部署有限的传感器和数采设备就可以完成升级,对中小型企业而言是“惠而不费”的。

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据调查,尽管欧美制造企业对诸如“物理升级制造技术以与IT基础设施连接”,“变得更具有成本效益和资源效率”“优化能源管理”,“优化设备性能”等数字化企业KPI更加看重,但这些都是以OEE流程自动化为基础。特别是对于计划采购数字孪生技术的企业,OEE自动建设更不是不可或缺的,它现实与虚拟设备结果的重要比较的数据,为企业优化运营提供支持
#那企业如何实施部署OEE,也许仅仅需要三部就可以:

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  1. OEE数据采集自动化:如前面所提到的,如果设备继续使用人工方式来收集OEE数据,不仅浪费巨大的人工,降低操作员的工作效率,同时数据采集的准确性和可靠性都会大打折扣,降低其可用性;通过使用自动化设备的控制器数据接口获取数据,或者在老旧设备中增设如“安灯”数据采集,设备电流互感器等传感器自动收集设备信息。有些设备可以改造为在线检测的,可及时获取质量数据,而对于加工后检测的就需要在IT系统中自动获取产品的质量信息;
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  3. 设备运行的事件记录:尽管自动化和AI程度的很高,但是我们依旧无法离开“人”在制造流程中的参与,特别是还处于半自动化半手工状态的众多小型制造企业,比如对设备突发的状况人工干预。这些状况坑定会对OEE产品印象。如果我们仅知道设备OEE水平低,但是并不知什么原因导致如此表现,则就无法找到改进的方向。将操作人员的事件类记录(非结构数据)与OEE对比才是数字化改造的重要目的;
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  5. 最后将生产调度中的数据拉入OEE的计算公式中,自动获得不同角度的OEE,为制造运营改善提供洞察insight;比如有文章建议,可以测量三种不同的时间窗的OEE:最后一小时OEE,最近换班OEE,和开机后OEE。通过观察不同时段的OEE,可以获取更多有关生产的见解,比如,不同班次的OEE的差别原因是什么?如辅具更换速度,准备时间长短,环境数据等。又比如企业在工艺调整后,观察对OEE的提高判断改善的有效性。
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但是在使用OEE时,也需要企业特比小型和谨慎,比如:

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  1. OEE数据为经营改善提供了改善,但是如果将OEE数据作为考核指标,则有可能诱发运营人员操弄数据,虚假提升的问题。就比如,当前的OEE是 OEE=0.7X0.6X0.9=0.378,而通过提供运营可用性,而降低产品质量,可能的数据就是OEE=0.85X0.6X0.8=0.408. 这样看似OEE提升了,但是产品次品率提升,对企业声誉产生影响,并非可取之策
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  3. OEE一定要结合特定的生产环境中,制造企业中的生产环境不一样,产品不同,工艺不同,即便是同样的设备也有可能是不同的OEE,不能一概而论,或者强行比较,特别是将设备OEE与最终产品价值进行比较。比如,虽然同样的机床,但是加工工件所需工艺和时间不同,但产品的价值就完全不同。OEE作为改善指引,最后是用其与同一个设备的历史值(或者数字孪生同设备的虚拟值)进行比较。
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  5. OEE仅仅是数字化运营升级的第一步,但绝对不是仅此一步或就此一步,正如精益管理核心理念之一的持续改善一样,数字化与智能化升级也无法“毕其功于一役”,持续的发现需求,发现瓶颈,挖掘潜力才是数字化制造企业长期追求目标;
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  7. OEE的目标仅仅与时考察单台设备的运行指标,且如前文所讲还是一个滞后指标,随着AI技术的发展和IIoT技术的进步,特别是预测性维护技术的发展,正如有的文章指出的那样,OEE的重要作用将让位于设备健康值,即在数字化运营特别是MES(MOM)的优化后,设备“借故偷懒”的机会已经不多了,只要设备健康就可以持续产生收益。此时OEE可能仅成为一项设备是否需要投资的参考最低阀值。
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#总结:
虽然OEE是个单一的指标,但是对计划进行数字化建设和升级的企业,特别是中小型制造企业,是个非常合适的发起和实现的项目,通过当前IIoT的技术,特别是通过设备互联做到数据自动采集,仅需要有限的投资和部署,就可以为企业带来数字化提升制造效率和运营水平的初期效果。

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hello http://example.com/2023/11/30/如何改造成为智能制造工厂?让我们从OEE开始/ bye

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博格达峰下的赶路人

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#关于作者
学机械专业,但毕业就进入工业自动化企业工作;原本想做个技术宅就好,却没想到转入了销售职业。人生总是充满不可预料啊。
时光蹉跎,自己职业从销售工程师、产品BD,到产品经理,距离工程师范儿原来越远,接触的管理方法越来越多。也许是在外企工作所染的危机感和焦虑症,总想学习更多的知识,增长更多的见识。对“stay hungry stay foolish” 深以为然。
#关于博客
在几家自动化头部企业兜兜转转后,虽然还在这个“圈子”中,但视野以及早非当年的工程师宅男了。除了对I3.0的工业自动化技术熟知,也持续学习和研究I4.0的工业物联网、工业信息化相关问题。知识只有在分享中,才能获得更多的成长和增长。
在这里我会就我所了解的技术和管理方法,发表自己的文章,希望对这个博客的观众有所帮助和收获。如果可以就具体的项目的问题开展研究和合作,那就

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博格达峰下的赶路人

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对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考

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- 嗯..! 目前共计 1 篇日志。 继续努力。 + 嗯..! 目前共计 2 篇日志。 继续努力。
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Hexo & NexT.Muse 强力驱动 +
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Hexo & NexT.Pisces 强力驱动
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博格达峰下的赶路人

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博格达峰下的赶路人

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博格达峰下的赶路人

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Hexo & NexT.Muse 强力驱动 +
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Hexo & NexT.Pisces 强力驱动
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博格达峰下的赶路人

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博格达峰下的赶路人

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Hexo & NexT.Muse 强力驱动 +
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Hexo & NexT.Pisces 强力驱动
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博格达峰下的赶路人

- + + + + - + + + diff --git a/atom.xml b/atom.xml new file mode 100644 index 0000000..0fef4c8 --- /dev/null +++ b/atom.xml @@ -0,0 +1,56 @@ + + + 博格达峰下的赶路人 + + 对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考 + + + + 2023-11-30T15:23:32.109Z + http://example.com/ + + + 刘 栋 + + + + Hexo + + + 如何改造成为智能制造工厂?让我们从OEE开始 + + http://example.com/2023/11/30/%E5%A6%82%E4%BD%95%E6%94%B9%E9%80%A0%E6%88%90%E4%B8%BA%E6%99%BA%E8%83%BD%E5%88%B6%E9%80%A0%E5%B7%A5%E5%8E%82%EF%BC%9F%E8%AE%A9%E6%88%91%E4%BB%AC%E4%BB%8EOEE%E5%BC%80%E5%A7%8B/ + 2023-11-30T08:05:47.000Z + 2023-11-30T15:23:32.109Z + + + + + <p>#智能制造的回顾与困惑<br>从德国政府宣布的工业4.0开始算起,新一代工业设施建设也已近10年了。而从计算机集成制造技术进入工厂实践开始,数字化制造或者智能制造的理念的推广可能还要更早,对中国的工厂管理者来说已经不是什么新鲜的概念了。就中国开工建设的“灯塔工厂”数量也是世 + + + + + + + + + + + 发刊感想 + + http://example.com/2023/11/29/%E5%8F%91%E5%88%8A%E6%84%9F%E6%83%B3/ + 2023-11-29T09:59:06.000Z + 2023-11-30T03:43:50.542Z + + + <p>参加工作以来我就认为,只有终身学习才是职业发展的根本动力,为此不断的工作和生活中参加各种学习活动,自己电脑中的各种材料(电子书、白皮书……)加起来也几十个G了,但是后来发现自己沉迷于“厚积”,却忘了“博发”。 + + + + + + + + + diff --git a/categories/index.html b/categories/index.html new file mode 100644 index 0000000..1a6c017 --- /dev/null +++ b/categories/index.html @@ -0,0 +1,286 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Categories | 博格达峰下的赶路人 + + + + + + + + + + + + + + + +
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博格达峰下的赶路人

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对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考

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--content-bg-color: #333; + --card-bg-color: #555; + --text-color: #ccc; + --blockquote-color: #bbb; + --link-color: #ccc; + --link-hover-color: #eee; + --brand-color: #ddd; + --brand-hover-color: #ddd; + --table-row-odd-bg-color: #282828; + --table-row-hover-bg-color: #363636; + --menu-item-bg-color: #555; + --theme-color: #222; + --btn-default-bg: #222; + --btn-default-color: #ccc; + --btn-default-border-color: #555; + --btn-default-hover-bg: #666; + --btn-default-hover-color: #ccc; + --btn-default-hover-border-color: #666; + --highlight-background: #1c1b1b; + --highlight-foreground: #fff; + --highlight-gutter-background: #323131; + --highlight-gutter-foreground: #e8e8e8; + color-scheme: dark; + } + img { + opacity: 0.75; + } + img:hover { + opacity: 0.9; + } + iframe { + color-scheme: light; + } +} html { line-height: 1.15; /* 1 */ -webkit-text-size-adjust: 100%; /* 2 */ @@ -303,7 +340,7 @@ td { .btn { background: var(--btn-default-bg); border: 2px solid var(--btn-default-border-color); - border-radius: 0; + border-radius: 2px; color: var(--btn-default-color); display: inline-block; font-size: 0.875em; @@ -739,7 +776,7 @@ pre code { } .post-body .tabs ul.nav-tabs, .tabs-comment ul.nav-tabs { - background: var(--body-bg-color); + background: var(--content-bg-color); display: flex; display: flex; flex-wrap: wrap; @@ -968,7 +1005,7 @@ pre code { border-bottom: 0; color: var(--brand-color); display: inline-block; - padding: 0 40px; + padding: 0; } .brand:hover { color: var(--brand-hover-color); @@ -981,9 +1018,9 @@ pre code { margin: 0; } .site-subtitle { - color: #999; + color: #ddd; font-size: 0.8125em; - margin: 10px 0; + margin: 10px 10px 0; } .use-motion .site-title, .use-motion .site-subtitle, @@ -1101,19 +1138,20 @@ pre code { display: inline-block; } .site-author-image { - border: 2px solid #333; - max-width: 96px; + border: 1px solid #eee; + max-width: 120px; padding: 2px; + border-radius: 50%; } .site-author-name { - color: #f5f5f5; - font-weight: normal; - margin: 5px 0 0; + color: var(--text-color); + font-weight: 600; + margin: 0; } .site-description { color: #999; - font-size: 1em; - margin-top: 5px; + font-size: 0.8125em; + margin-top: 0; } .links-of-author a { font-size: 0.8125em; @@ -1170,7 +1208,7 @@ pre code { } .sidebar-nav li { border-bottom: 1px solid transparent; - color: #666; + color: var(--text-color); cursor: pointer; display: inline-block; transition: 0.2s ease-in-out; @@ -1180,17 +1218,17 @@ pre code { margin-left: 10px; } .sidebar-nav li:hover { - color: #f5f5f5; + color: #fc6423; } .sidebar-toc-active .sidebar-nav-toc, .sidebar-overview-active .sidebar-nav-overview { - border-bottom-color: #87daff; - color: #87daff; + border-bottom-color: #fc6423; + color: #fc6423; transition-delay: 0.2s; } .sidebar-toc-active .sidebar-nav-toc:hover, .sidebar-overview-active .sidebar-nav-overview:hover { - color: #87daff; + color: #fc6423; } .sidebar-panel-container { align-items: start; @@ -1264,26 +1302,26 @@ pre code { width: 16px; background: #222; cursor: pointer; - opacity: 0.8; + opacity: 0.6; position: fixed; z-index: 30; - left: 30px; + right: 30px; } @media (max-width: 991px) { .sidebar-toggle { - left: 20px; + right: 20px; } } .sidebar-toggle:hover { - opacity: 1; + opacity: 0.8; } @media (max-width: 991px) { .sidebar-toggle { - opacity: 1; + opacity: 0.8; } } .sidebar-toggle:hover .toggle-line { - background: #87daff; + background: #fc6423; } @media (any-hover: hover) { body:not(.sidebar-active) .sidebar-toggle:hover :first-child { @@ -1332,7 +1370,6 @@ pre code { line-height: 1.8; overflow: hidden; text-overflow: ellipsis; - white-space: nowrap; } .post-toc .nav .nav-child { --height: 0; @@ -1349,14 +1386,14 @@ pre code { visibility: unset; } .post-toc .nav .active > a { - border-bottom-color: #87daff; - color: #87daff; + border-bottom-color: #fc6423; + color: #fc6423; } .post-toc .nav .active-current > a { - color: #87daff; + color: #fc6423; } .post-toc .nav .active-current > a:hover { - color: #87daff; + color: #fc6423; } .site-state { display: flex; @@ -1373,12 +1410,12 @@ pre code { } .site-state-item-count { display: block; - font-size: 1.25em; + font-size: 1em; font-weight: 600; } .site-state-item-name { - color: inherit; - font-size: 0.875em; + color: #999; + font-size: 0.8125em; } .footer { color: #999; @@ -1400,7 +1437,7 @@ pre code { flex-direction: column; justify-content: center; margin: 0 auto; - width: 700px; + width: calc(100% - 20px); } @media (max-width: 767px) { .footer-inner { @@ -1409,12 +1446,12 @@ pre code { } @media (min-width: 1200px) { .footer-inner { - width: 800px; + width: 1160px; } } @media (min-width: 1600px) { .footer-inner { - width: 900px; + width: 73%; } } .use-motion .footer { @@ -1465,10 +1502,10 @@ pre code { transition: bottom 0.2s ease-in-out; background: #222; cursor: pointer; - opacity: 0.8; + opacity: 0.6; position: fixed; z-index: 30; - left: 30px; + right: 30px; } .back-to-top span { margin-right: 8px; @@ -1480,19 +1517,19 @@ pre code { } @media (max-width: 991px) { .back-to-top { - left: 20px; + right: 20px; } } .back-to-top:hover { - opacity: 1; + opacity: 0.8; } @media (max-width: 991px) { .back-to-top { - opacity: 1; + opacity: 0.8; } } .back-to-top:hover { - color: #87daff; + color: #fc6423; } .back-to-top.back-to-top-on { bottom: 30px; @@ -1925,18 +1962,18 @@ pre code { } .reward-container button { background: transparent; - color: #87daff; + color: #fc6423; cursor: pointer; line-height: 2; padding: 0 15px; - border: 2px solid #87daff; + border: 2px solid #fc6423; border-radius: 2px; outline: 0; transition: all 0.2s ease-in-out; vertical-align: text-top; } .reward-container button:hover { - background: #87daff; + background: #fc6423; color: #fff; } .post-reward { @@ -2150,228 +2187,411 @@ ul.breadcrumb li:last-child { border-bottom-color: #111; color: #111; } -.use-motion .animated { - animation-fill-mode: none; - visibility: inherit; +@media (prefers-color-scheme: dark) { + .tag-cloud-0 { + border-bottom-color: #555; + color: #555; + } + .tag-cloud-1 { + border-bottom-color: #646464; + color: #646464; + } + .tag-cloud-2 { + border-bottom-color: #737373; + color: #737373; + } + .tag-cloud-3 { + border-bottom-color: #828282; + color: #828282; + } + .tag-cloud-4 { + border-bottom-color: #929292; + color: #929292; + } + .tag-cloud-5 { + border-bottom-color: #a1a1a1; + color: #a1a1a1; + } + .tag-cloud-6 { + border-bottom-color: #b0b0b0; + color: #b0b0b0; + } + .tag-cloud-7 { + border-bottom-color: #c0c0c0; + color: #c0c0c0; + } + .tag-cloud-8 { + border-bottom-color: #cfcfcf; + color: #cfcfcf; + } + .tag-cloud-9 { + border-bottom-color: #dedede; + color: #dedede; + } + .tag-cloud-10 { + border-bottom-color: #eee; + color: #eee; + } } -.use-motion .sidebar .animated { - animation-fill-mode: both; +.search-active { + overflow: hidden; } -header.header { - margin: 0 auto; +.search-pop-overlay { + background: rgba(0,0,0,0); + display: flex; + height: 100%; + left: 0; + position: fixed; + top: 0; + transition: visibility 0.4s, background 0.4s; + visibility: hidden; + width: 100%; + z-index: 40; +} +.search-active .search-pop-overlay { + background: rgba(0,0,0,0.3); + visibility: visible; +} +.search-popup { + background: var(--card-bg-color); + border-radius: 5px; + height: 80%; + margin: auto; + transform: scale(0); + transition: transform 0.4s; width: 700px; } +.search-active .search-popup { + transform: scale(1); +} @media (max-width: 767px) { - header.header { - width: auto; + .search-popup { + border-radius: 0; + height: 100%; + width: 100%; } } -@media (min-width: 1200px) { - header.header { - width: 800px; +.search-popup .search-icon, +.search-popup .popup-btn-close { + color: #999; + font-size: 18px; + padding: 0 10px; +} +.search-popup .popup-btn-close { + cursor: pointer; +} +.search-popup .popup-btn-close:hover .fa { + color: #222; +} +.search-popup .search-header { + background: #eee; + border-top-left-radius: 5px; + border-top-right-radius: 5px; + display: flex; + padding: 5px; +} +@media (prefers-color-scheme: dark) { + .search-popup .search-header { + background: #666; } } -@media (min-width: 1600px) { +.search-popup input.search-input { + background: transparent; + border: 0; + outline: 0; + width: 100%; +} +.search-popup input.search-input::-webkit-search-cancel-button { + display: none; +} +.search-popup .search-result-container { + height: calc(100% - 55px); + overflow: auto; + padding: 5px 25px; +} +.search-popup .search-result-container hr { + margin: 5px 0 10px; +} +.search-popup .search-result-container hr:first-child { + display: none; +} +.search-popup .search-result-list { + margin: 0 5px; + padding: 0; +} +.search-popup a.search-result-title { + font-weight: bold; +} +.search-popup p.search-result { + border-bottom: 1px dashed #ccc; + padding: 5px 0; +} +.search-popup .search-input-container { + flex-grow: 1; + padding: 2px; +} +.search-popup .no-result { + display: flex; +} +.search-popup .search-result-list { + width: 100%; +} +.search-popup .search-result-icon { + color: #ccc; + margin: auto; +} +mark.search-keyword { + background: transparent; + border-bottom: 1px dashed #ff2a2a; + color: #ff2a2a; + font-weight: bold; +} +.use-motion .animated { + animation-fill-mode: none; + visibility: inherit; +} +.use-motion .sidebar .animated { + animation-fill-mode: both; +} +header.header { + background: var(--content-bg-color); + border-radius: initial; + box-shadow: initial; +} +@media (max-width: 991px) { header.header { - width: 900px; + border-radius: initial; } } -.main-inner { +.main { + align-items: stretch; + display: flex; + justify-content: space-between; margin: 0 auto; - width: 700px; - padding-bottom: 60px; + width: calc(100% - 20px); } @media (max-width: 767px) { - .main-inner { + .main { width: auto; } } @media (min-width: 1200px) { - .main-inner { - width: 800px; + .main { + width: 1160px; } } @media (min-width: 1600px) { - .main-inner { - width: 900px; + .main { + width: 73%; } } -@media (max-width: 767px) { - .main-inner { - padding-left: 20px; - padding-right: 20px; +@media (max-width: 991px) { + .main { + display: block; + width: auto; } } -.post-block:first-of-type { - padding-top: 70px; +.main-inner { + border-radius: initial; + box-sizing: border-box; + width: calc(100% - 312px); } -@media (max-width: 767px) { - .post-block:first-of-type { - padding-top: 35px; +@media (max-width: 991px) { + .main-inner { + border-radius: initial; + width: 100%; } } -.custom-logo-image { - background: #fff; - margin: 0 auto 10px; - max-width: 150px; - padding: 5px; +.footer-inner { + padding-left: 312px; } -.brand { - background: var(--btn-default-bg); +@media (max-width: 991px) { + .footer-inner { + padding-left: 0; + padding-right: 0; + width: auto; + } } -header.header { - padding-top: 100px; +.column { + width: 300px; } -@media (max-width: 767px) { - header.header { - padding-top: 50px; +@media (max-width: 991px) { + .column { + width: auto; } } -@media (max-width: 767px) { - .site-nav { - padding-top: 30px; - } +.site-brand-container { + background: var(--theme-color); } -@media (max-width: 767px) { - .main-menu { - border-bottom: 1px solid #ddd; - border-top: 1px solid #ddd; +@media (max-width: 991px) { + .site-nav-on .site-brand-container { + box-shadow: 0 0 16px rgba(0,0,0,0.5); } } -@media (max-width: 767px) { - .menu { - text-align: left; - } +.site-meta { + padding: 20px 0; } -@media (max-width: 767px) { - .menu .menu-item { - margin: 0 10px; +@media (min-width: 768px) and (max-width: 991px) { + .site-nav-toggle, + .site-nav-right { + display: flex; + flex-direction: column; + justify-content: center; } } -.menu .menu-item a { - border-bottom: 1px solid transparent; +.site-nav-toggle .toggle, +.site-nav-right .toggle { + color: #fff; } -@media (max-width: 767px) { - .menu .menu-item a { - padding: 5px 10px; +.site-nav-toggle .toggle .toggle-line, +.site-nav-right .toggle .toggle-line { + background: #fff; +} +@media (min-width: 768px) and (max-width: 991px) { + .site-nav { + --scroll-height: 0; + height: 0; + overflow: hidden; + transition: 0.2s ease-in-out; + transition-property: height, visibility; + visibility: hidden; + } + body:not(.site-nav-on) .site-nav .animated { + animation: none; + } + body.site-nav-on .site-nav { + height: var(--scroll-height); + visibility: unset; } } -.menu .menu-item a:hover, -.menu .menu-item a.menu-item-active { - background: transparent; - border-bottom: 1px solid var(--link-hover-color); +.menu .menu-item { + display: block; + margin: 0; } -@media (max-width: 767px) { - .menu .menu-item a:hover, - .menu .menu-item a.menu-item-active { - border-bottom: 1px dotted #ddd; - } +.menu .menu-item a { + padding: 5px 20px; + position: relative; + text-align: left; + transition-property: background-color; } -@media (min-width: 768px) { - .menu .menu-item i[class^='fa'] { - display: block; - line-height: 2; - margin-right: 0; - width: 100%; +@media (max-width: 991px) { + .menu .menu-item.menu-item-search { + display: none; } } .menu .menu-item .badge { - background: #eee; - color: #555; - padding: 1px 4px; + background: #ccc; + border-radius: 10px; + color: var(--content-bg-color); + float: right; + padding: 2px 5px; + text-shadow: 1px 1px 0 rgba(0,0,0,0.1); } .sub-menu { - margin: 10px 0; + margin: 0; + padding: 6px 0; } .sub-menu .menu-item { display: inline-block; } -@media (min-width: 1200px) { - .sidebar-active { - padding-left: 320px; - } - .sidebar-active .footer-fixed { - left: 320px; - } +.sub-menu .menu-item a { + background: transparent; + margin: 5px 10px; + padding: initial; } -.sidebar { - left: -320px; +.sub-menu .menu-item a:hover { + background: transparent; + color: #fc6423; } -.sidebar-active .sidebar { - left: 0; +.sub-menu .menu-item-active { + border-bottom-color: #fc6423; + color: #fc6423; +} +.sub-menu .menu-item-active:hover { + border-bottom-color: #fc6423; } .sidebar { - background: #222; - bottom: 0; - box-shadow: inset 0 2px 6px #000; - max-height: 100vh; - overflow-y: auto; - position: fixed; - top: 0; - transition: all 0.2s ease-out; - width: 320px; - z-index: 20; + position: -webkit-sticky; + position: sticky; + top: 12px; } -.sidebar a { - border-bottom-color: #555; - color: #999; +@media (max-width: 991px) { + .sidebar { + display: none; + } } -.sidebar a:hover { - border-bottom-color: #eee; - color: #eee; +.sidebar-inner { + background: var(--content-bg-color); + border-radius: initial; + box-shadow: initial; + box-sizing: border-box; + color: var(--text-color); + margin-top: 12px; + max-height: calc(100vh - 24px); + visibility: hidden; } -.links-of-author:not(:first-child) { - margin-top: 15px; +.site-state-item { + padding: 0 10px; } -.links-of-author a { - border-bottom-color: #555; - display: inline-block; - margin-bottom: 10px; - margin-right: 10px; - vertical-align: middle; +.sidebar .sidebar-button { + border-bottom: 1px dotted #ccc; + border-top: 1px dotted #ccc; } -.links-of-author a::before { - background: #ffff61; - display: inline-block; - margin-right: 3px; - transform: translateY(-2px); - border-radius: 50%; - content: ' '; - height: 4px; - width: 4px; +.sidebar .sidebar-button button { + border: 0; + color: #fc6423; + display: block; + width: 100%; +} +.sidebar .sidebar-button button:hover { + background: none; + border: 0; + color: #e34603; +} +.links-of-author { + display: flex; + flex-wrap: wrap; + justify-content: center; } -.links-of-blogroll-item { - padding: 2px 10px; +.links-of-author-item { + margin: 5px 0 0; + width: 50%; } -.links-of-blogroll-item a { +.links-of-author-item a { box-sizing: border-box; display: inline-block; - max-width: 280px; + max-width: 100%; overflow: hidden; + padding: 0 5px; text-overflow: ellipsis; white-space: nowrap; } -.popular-posts .popular-posts-item .popular-posts-link:hover { - background: none; +.links-of-author-item a { + border-bottom: 0; + border-radius: 4px; + display: block; } 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5680083..ad203c5 100644 --- a/2023/11/28/hello-world/index.html +++ b/images/hello-world.html @@ -3,7 +3,8 @@ - + + @@ -17,30 +18,31 @@ - + - + - + - + - - + + - + - + -Hello World | 博格达峰下的赶路人 +Hello World | 博格达峰下的赶路人 + @@ -53,6 +55,7 @@ + @@ -63,6 +66,9 @@

@@ -73,19 +79,51 @@

博格达峰下的赶路人

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对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考

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- Hello World -

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Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.

+ + +
+

Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.

Quick Start

Create a new post

1
$ hexo new "My New Post"

More info: Writing

@@ -201,25 +218,17 @@

Deployment

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+ + +
- - -
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- 刘栋 + 刘 栋

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Hexo & NexT.Muse 强力驱动 +
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Hexo & NexT.Pisces 强力驱动
- -
0% @@ -259,20 +276,25 @@

- + + + + - + + + diff --git a/index.html b/index.html index a00a4fd..c7ff932 100644 --- a/index.html +++ b/index.html @@ -3,7 +3,8 @@ - + + @@ -17,17 +18,17 @@ - + - + - + - - + + @@ -51,6 +52,7 @@ + @@ -61,6 +63,9 @@
@@ -71,19 +76,51 @@

博格达峰下的赶路人

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对工业自动化、工业物联网、工业信息技术,以及工业项目管理方法的独立思考

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博格达峰下的赶路人

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博格达峰下的赶路人

- +

- +

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-

Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.

-

Quick Start

Create a new post

1
$ hexo new "My New Post"
+

#智能制造的回顾与困惑
从德国政府宣布的工业4.0开始算起,新一代工业设施建设也已近10年了。而从计算机集成制造技术进入工厂实践开始,数字化制造或者智能制造的理念的推广可能还要更早,对中国的工厂管理者来说已经不是什么新鲜的概念了。就中国开工建设的“灯塔工厂”数量也是世界之最。所谓“数字孪生”“工业互联网”“IIoT”“人工智能”“SaaS”“PaaS”这些热词,即便是车间的班组长也都有所听闻并不陌生。

+

然而在实践中,除少数行业头部和大型企业以外,更多的中小型企业恐怕并没有真正去考虑建设或者升级成智能制造工厂。
成为智能制造企业,可以提高工厂的竞争力,提高生产柔性、降低运营成本,为企业带来更多的收益,难道这些听起来“不香”嘛?香或许是香,但是这些新建和升级并不是没有代价的,甚至在等来可见的“收益”前,前期投资已经让不少中小企业不堪重负了。

+

面对UNCA时代的挑战,特别是疫情后全球供应链挑战,制造业转移和回流,过去以性价比见长的中国制造业特别是中小型制造企业,必须要拥抱数字化与智能化来确保未来的竞争力。

+

这样就出现了“进则担负升级改造的高投入风险,退则抱残守缺逐渐丧失竞争力”的两难局面;如何破局?小步快跑,边走边跑或许是一个中小企业可取的办法。具体说就先从简单的、可见的、可迅速与提高制造效率和收益的项目开始,比如,就可以从实践OEE的自动可视化开始……

+

#什么是OEE?其历史与对制造工厂的提高?
OEE是Overall Equpment Efficiency的缩写,翻译为综合设备效率,也有会翻译成设备稼动率;其意义是通过考量设备的运行时间、性能和质量来评估设备在生产过程中的效率和利用率。

+

简而言之就是观测设备的有效运行状况判断当前设备的“赚钱”的能力。这就好比很多出租车运营者会考虑让两个或三个司机轮换开车来提高车辆的运营,通过多跑载客时间或里程,减少空闲,提高收益。

+

OEE的概念进入最早是在以精益制造而闻名的丰田的TPS系统中,在TPS中其中一个重要的内容就是TPM,即全员生产性维护,通过提供现场操作人员对设备进行即时与定时的保养,是设备始终保持在一个良好的作业状态,从而提供制造的效率和质量,减少如设备停机,不良品返工等浪费现象(六大损失),其中OEE就是度量当个设备的运行状态的重要指标KPI
OEE的计算公式是:

+
OEE = 设备的可用率X设备的效能率X产品良品率,
+
+

这其中:

+
    +
  1. 设备的可用率,是指设备的实际工作时间与设备计划工作时间的比率,
  2. +
  3. 设备的效能率,是指设备无故障工作时间和折算的全速工作时间与实际工作时间的比率
  4. +
  5. 设备的良品率,就如字面意思一样就是设备生产的合格品与所有产出品的比率
  6. +
+

在逻辑上,只要我们提高的OEE,也就意味着可以提高设备的可用时间,提高产品的质量,从而为企业创造了更高的价值。

+

如此好的工具,但实施起来并不是那么容易的,特别是对中小企业而言。原因如下:

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    +
  • OEE本身和企业的收益联系并不是直接可显的,特别是通过公式我们可以看到这个OEE实际上是一个时间窗口的计算值,而且还是一个滞后指标。通过OEE来分析其提高的途径,或许可以间接的提高企业的综合收益,但是这也绝非一朝一夕就可以实现的。
  • +
  • 最初的OEE都是通过人工手动来完成的,在大型制造企业中,这些数据的收集都是有车间的价值流经理、精益专员来完成,少数有设备的操作员来完成,使用人工测量和计算对数据的准确性提出挑战,而如果对操作员来完成相关测量,有可能降低操作员工作效率,更不用说人力资源紧张的中小型企业;
  • +
  • 或许有的自动化设备提供了可以在线实施测量设备工作状态的数据接口,但是也会有设备数据的转换、数据通讯协议的转换等相关问题,对现场的OT和IT工程师提出了挑战;
  • +
  • 特别是不同数据如何获取、从什么渠道获取,并且让数据可以建立相关联系并展现出来,不仅是对中小企业,即便是拥有_数据科学家和数据工程师_的大企业也需要仔细面对。
  • +
  • 特别是对于一些重要生产设备但非自动化设备,如果不考虑用专门的人员来测量和计算其设备相关设备,如何通过适当的改造,最好是不停机改造来实现设备数据采集,又不至于对现下的生产产生中断和大影响,这对缺少自动化与数字化工程师和相关经验的中小企业都是挑战;
  • +
+

另外还有现场设备太多,设备协议太多……等问题,也是阻碍OEE实施的一些原因。

+

#智能化与数字化制造,从OEE开始
虽然有上述很多困难阻碍OEE的实施,但借助工业物联网(IIoT)的技术发展普及,OEE的项目实施依旧是中小企业开始数字化和智能制造升级的最重要与最合适的第一步,这就是OEE自动化数据获取;

+

数字化转型与精益生产的思想是一致的,就是从客户的需求出发进行制造,与其无目标的收集数据,又或者目标太多需要大量大范围数据,OEE的KPI需求是明确的且可以明显反映设备生产状况的,可以拉动相关设备数据采集和改进方向;

+

通过OEE的数据,中小企业迅速判断当前的设备投资状况,比如,与其购买添置新设备,是否可以通过提高设备OEE来发掘潜力,减少重复投资;又或者通过OEE比较,寻找整个生产流程的瓶颈,并加以改善;

+

相对于复杂的商业智能BI或者其它数字辅助决策,OEE所需要的数据量是非常有限的,这样对升级所需的投资规模也是合理与可控的,如果是自动化设备且具有相应数据开放的接口,或许仅需要一些软件的升级与修改就可以完成,而对于性能良好的“哑巴”设备,部署有限的传感器和数采设备就可以完成升级,对中小型企业而言是“惠而不费”的。

+

据调查,尽管欧美制造企业对诸如“物理升级制造技术以与IT基础设施连接”,“变得更具有成本效益和资源效率”“优化能源管理”,“优化设备性能”等数字化企业KPI更加看重,但这些都是以OEE流程自动化为基础。特别是对于计划采购数字孪生技术的企业,OEE自动建设更不是不可或缺的,它现实与虚拟设备结果的重要比较的数据,为企业优化运营提供支持
#那企业如何实施部署OEE,也许仅仅需要三部就可以:

+
    +
  1. OEE数据采集自动化:如前面所提到的,如果设备继续使用人工方式来收集OEE数据,不仅浪费巨大的人工,降低操作员的工作效率,同时数据采集的准确性和可靠性都会大打折扣,降低其可用性;通过使用自动化设备的控制器数据接口获取数据,或者在老旧设备中增设如“安灯”数据采集,设备电流互感器等传感器自动收集设备信息。有些设备可以改造为在线检测的,可及时获取质量数据,而对于加工后检测的就需要在IT系统中自动获取产品的质量信息;
  2. +
  3. 设备运行的事件记录:尽管自动化和AI程度的很高,但是我们依旧无法离开“人”在制造流程中的参与,特别是还处于半自动化半手工状态的众多小型制造企业,比如对设备突发的状况人工干预。这些状况坑定会对OEE产品印象。如果我们仅知道设备OEE水平低,但是并不知什么原因导致如此表现,则就无法找到改进的方向。将操作人员的事件类记录(非结构数据)与OEE对比才是数字化改造的重要目的;
  4. +
  5. 最后将生产调度中的数据拉入OEE的计算公式中,自动获得不同角度的OEE,为制造运营改善提供洞察insight;比如有文章建议,可以测量三种不同的时间窗的OEE:最后一小时OEE,最近换班OEE,和开机后OEE。通过观察不同时段的OEE,可以获取更多有关生产的见解,比如,不同班次的OEE的差别原因是什么?如辅具更换速度,准备时间长短,环境数据等。又比如企业在工艺调整后,观察对OEE的提高判断改善的有效性。
  6. +
+

但是在使用OEE时,也需要企业特比小型和谨慎,比如:

+
    +
  1. OEE数据为经营改善提供了改善,但是如果将OEE数据作为考核指标,则有可能诱发运营人员操弄数据,虚假提升的问题。就比如,当前的OEE是 OEE=0.7X0.6X0.9=0.378,而通过提供运营可用性,而降低产品质量,可能的数据就是OEE=0.85X0.6X0.8=0.408. 这样看似OEE提升了,但是产品次品率提升,对企业声誉产生影响,并非可取之策
  2. +
  3. OEE一定要结合特定的生产环境中,制造企业中的生产环境不一样,产品不同,工艺不同,即便是同样的设备也有可能是不同的OEE,不能一概而论,或者强行比较,特别是将设备OEE与最终产品价值进行比较。比如,虽然同样的机床,但是加工工件所需工艺和时间不同,但产品的价值就完全不同。OEE作为改善指引,最后是用其与同一个设备的历史值(或者数字孪生同设备的虚拟值)进行比较。
  4. +
  5. OEE仅仅是数字化运营升级的第一步,但绝对不是仅此一步或就此一步,正如精益管理核心理念之一的持续改善一样,数字化与智能化升级也无法“毕其功于一役”,持续的发现需求,发现瓶颈,挖掘潜力才是数字化制造企业长期追求目标;
  6. +
  7. OEE的目标仅仅与时考察单台设备的运行指标,且如前文所讲还是一个滞后指标,随着AI技术的发展和IIoT技术的进步,特别是预测性维护技术的发展,正如有的文章指出的那样,OEE的重要作用将让位于设备健康值,即在数字化运营特别是MES(MOM)的优化后,设备“借故偷懒”的机会已经不多了,只要设备健康就可以持续产生收益。此时OEE可能仅成为一项设备是否需要投资的参考最低阀值。
  8. +
+

#总结:
虽然OEE是个单一的指标,但是对计划进行数字化建设和升级的企业,特别是中小型制造企业,是个非常合适的发起和实现的项目,通过当前IIoT的技术,特别是通过设备互联做到数据自动采集,仅需要有限的投资和部署,就可以为企业带来数字化提升制造效率和运营水平的初期效果。

+

hello http://example.com/2023/11/30/如何改造成为智能制造工厂?让我们从OEE开始/ bye

+ + +
+ + + + + +
+
+ +
+

+ + + + + + + + +
+ + + +
+ + + -

More info: Writing

-

Run server

1
$ hexo server
+ -

More info: Server

-

Generate static files

1
$ hexo generate
+ +
+

+ +

-

More info: Generating

-

Deploy to remote sites

1
$ hexo deploy
+ +
+ + + +
+

参加工作以来我就认为,只有终身学习才是职业发展的根本动力,为此不断的工作和生活中参加各种学习活动,自己电脑中的各种材料(电子书、白皮书……)加起来也几十个G了,但是后来发现自己沉迷于“厚积”,却忘了“博发”。 + +

+ + 阅读全文 » + +
+ +
@@ -228,21 +450,29 @@

- 刘栋 + 刘 栋

-
Hexo & NexT.Muse 强力驱动 +
+ + +
+
Hexo & NexT.Pisces 强力驱动
- -
0% @@ -255,20 +485,25 @@

- + + + + - + + + diff --git a/search.xml b/search.xml new file mode 100644 index 0000000..c87a17d --- /dev/null +++ b/search.xml @@ -0,0 +1,67 @@ + + + + 发刊感想 + /2023/11/29/%E5%8F%91%E5%88%8A%E6%84%9F%E6%83%B3/ + 参加工作以来我就认为,只有终身学习才是职业发展的根本动力,为此不断的工作和生活中参加各种学习活动,自己电脑中的各种材料(电子书、白皮书……)加起来也几十个G了,但是后来发现自己沉迷于“厚积”,却忘了“博发”。

+

博客的动机

记得有一个理论说,最好的学习方式是将自己的学习成果进行展示,教会别人。在教会给别人的同时自己的也得到了学习的深化。很有道理,所以我想对自己的知识进行“博发”深度学习是这个博客的第一动机吧。
从机械专业毕业却进入到工业自动化企业工作,本想做个技术宅,但是“阴差阳错”下做了销售工程师、产品经理和项目经理。在职业的成长中,对工业企业中“产品管理”、“项目管理”和其它管理给自己带了很多的感谢,与看客分享自己的“博闻”,得到认可或讨论,也许是博客的第二动机。
虽然离开了技术的专深,但确始终在工业自动化这个“大圈子”中游弋,随着工业信息化的发展,工业技术也进入了全新的阶段,有幸在自动化的工业信息技术的工作经历,自己也算是OT于IT都有所专擅的“广博”之辈,很想把这个博采与同道一起分享,这算是博客的第三动机。
其实搭建这个博客实际上还是花了一些时间,由于不想在传统的CMD中进行写作,所以在学习了几篇帖子以后,决心自己搭建这个博客,到底是岁数大了,还是有些费劲。不过总算折腾出来了。

+

一点期望

我其实写作的能力一般,而且也不知道会什么时候突然就不想写了,但是我的另外一个习惯是,只要去做就想办法做到精致,所以博客中的文章会有很多的别人的文章,但一定会有自己的思考。这些思考或许不一定正确,但是如果有看客能给我提出指正,那我会诚挚感谢,并进行在学习和研究。
或许,也有看客可以通过我的文章后,想和我合作一些项目,那也许会成为我以后发博的第四动机和成长动力吧。

+

hello http://example.com/2023/11/29/发刊感想/ bye

+]]> + + 发刊词 + + + + 如何改造成为智能制造工厂?让我们从OEE开始 + /2023/11/30/%E5%A6%82%E4%BD%95%E6%94%B9%E9%80%A0%E6%88%90%E4%B8%BA%E6%99%BA%E8%83%BD%E5%88%B6%E9%80%A0%E5%B7%A5%E5%8E%82%EF%BC%9F%E8%AE%A9%E6%88%91%E4%BB%AC%E4%BB%8EOEE%E5%BC%80%E5%A7%8B/ + #智能制造的回顾与困惑
从德国政府宣布的工业4.0开始算起,新一代工业设施建设也已近10年了。而从计算机集成制造技术进入工厂实践开始,数字化制造或者智能制造的理念的推广可能还要更早,对中国的工厂管理者来说已经不是什么新鲜的概念了。就中国开工建设的“灯塔工厂”数量也是世界之最。所谓“数字孪生”“工业互联网”“IIoT”“人工智能”“SaaS”“PaaS”这些热词,即便是车间的班组长也都有所听闻并不陌生。

+

然而在实践中,除少数行业头部和大型企业以外,更多的中小型企业恐怕并没有真正去考虑建设或者升级成智能制造工厂。
成为智能制造企业,可以提高工厂的竞争力,提高生产柔性、降低运营成本,为企业带来更多的收益,难道这些听起来“不香”嘛?香或许是香,但是这些新建和升级并不是没有代价的,甚至在等来可见的“收益”前,前期投资已经让不少中小企业不堪重负了。

+

面对UNCA时代的挑战,特别是疫情后全球供应链挑战,制造业转移和回流,过去以性价比见长的中国制造业特别是中小型制造企业,必须要拥抱数字化与智能化来确保未来的竞争力。

+

这样就出现了“进则担负升级改造的高投入风险,退则抱残守缺逐渐丧失竞争力”的两难局面;如何破局?小步快跑,边走边跑或许是一个中小企业可取的办法。具体说就先从简单的、可见的、可迅速与提高制造效率和收益的项目开始,比如,就可以从实践OEE的自动可视化开始……

+

#什么是OEE?其历史与对制造工厂的提高?
OEE是Overall Equpment Efficiency的缩写,翻译为综合设备效率,也有会翻译成设备稼动率;其意义是通过考量设备的运行时间、性能和质量来评估设备在生产过程中的效率和利用率。

+

简而言之就是观测设备的有效运行状况判断当前设备的“赚钱”的能力。这就好比很多出租车运营者会考虑让两个或三个司机轮换开车来提高车辆的运营,通过多跑载客时间或里程,减少空闲,提高收益。

+

OEE的概念进入最早是在以精益制造而闻名的丰田的TPS系统中,在TPS中其中一个重要的内容就是TPM,即全员生产性维护,通过提供现场操作人员对设备进行即时与定时的保养,是设备始终保持在一个良好的作业状态,从而提供制造的效率和质量,减少如设备停机,不良品返工等浪费现象(六大损失),其中OEE就是度量当个设备的运行状态的重要指标KPI
OEE的计算公式是:

+
OEE = 设备的可用率X设备的效能率X产品良品率,
+
+

这其中:

+
    +
  1. 设备的可用率,是指设备的实际工作时间与设备计划工作时间的比率,
  2. +
  3. 设备的效能率,是指设备无故障工作时间和折算的全速工作时间与实际工作时间的比率
  4. +
  5. 设备的良品率,就如字面意思一样就是设备生产的合格品与所有产出品的比率
  6. +
+

在逻辑上,只要我们提高的OEE,也就意味着可以提高设备的可用时间,提高产品的质量,从而为企业创造了更高的价值。

+

如此好的工具,但实施起来并不是那么容易的,特别是对中小企业而言。原因如下:

+
    +
  • OEE本身和企业的收益联系并不是直接可显的,特别是通过公式我们可以看到这个OEE实际上是一个时间窗口的计算值,而且还是一个滞后指标。通过OEE来分析其提高的途径,或许可以间接的提高企业的综合收益,但是这也绝非一朝一夕就可以实现的。
  • +
  • 最初的OEE都是通过人工手动来完成的,在大型制造企业中,这些数据的收集都是有车间的价值流经理、精益专员来完成,少数有设备的操作员来完成,使用人工测量和计算对数据的准确性提出挑战,而如果对操作员来完成相关测量,有可能降低操作员工作效率,更不用说人力资源紧张的中小型企业;
  • +
  • 或许有的自动化设备提供了可以在线实施测量设备工作状态的数据接口,但是也会有设备数据的转换、数据通讯协议的转换等相关问题,对现场的OT和IT工程师提出了挑战;
  • +
  • 特别是不同数据如何获取、从什么渠道获取,并且让数据可以建立相关联系并展现出来,不仅是对中小企业,即便是拥有_数据科学家和数据工程师_的大企业也需要仔细面对。
  • +
  • 特别是对于一些重要生产设备但非自动化设备,如果不考虑用专门的人员来测量和计算其设备相关设备,如何通过适当的改造,最好是不停机改造来实现设备数据采集,又不至于对现下的生产产生中断和大影响,这对缺少自动化与数字化工程师和相关经验的中小企业都是挑战;
  • +
+

另外还有现场设备太多,设备协议太多……等问题,也是阻碍OEE实施的一些原因。

+

#智能化与数字化制造,从OEE开始
虽然有上述很多困难阻碍OEE的实施,但借助工业物联网(IIoT)的技术发展普及,OEE的项目实施依旧是中小企业开始数字化和智能制造升级的最重要与最合适的第一步,这就是OEE自动化数据获取;

+

数字化转型与精益生产的思想是一致的,就是从客户的需求出发进行制造,与其无目标的收集数据,又或者目标太多需要大量大范围数据,OEE的KPI需求是明确的且可以明显反映设备生产状况的,可以拉动相关设备数据采集和改进方向;

+

通过OEE的数据,中小企业迅速判断当前的设备投资状况,比如,与其购买添置新设备,是否可以通过提高设备OEE来发掘潜力,减少重复投资;又或者通过OEE比较,寻找整个生产流程的瓶颈,并加以改善;

+

相对于复杂的商业智能BI或者其它数字辅助决策,OEE所需要的数据量是非常有限的,这样对升级所需的投资规模也是合理与可控的,如果是自动化设备且具有相应数据开放的接口,或许仅需要一些软件的升级与修改就可以完成,而对于性能良好的“哑巴”设备,部署有限的传感器和数采设备就可以完成升级,对中小型企业而言是“惠而不费”的。

+

据调查,尽管欧美制造企业对诸如“物理升级制造技术以与IT基础设施连接”,“变得更具有成本效益和资源效率”“优化能源管理”,“优化设备性能”等数字化企业KPI更加看重,但这些都是以OEE流程自动化为基础。特别是对于计划采购数字孪生技术的企业,OEE自动建设更不是不可或缺的,它现实与虚拟设备结果的重要比较的数据,为企业优化运营提供支持
#那企业如何实施部署OEE,也许仅仅需要三部就可以:

+
    +
  1. OEE数据采集自动化:如前面所提到的,如果设备继续使用人工方式来收集OEE数据,不仅浪费巨大的人工,降低操作员的工作效率,同时数据采集的准确性和可靠性都会大打折扣,降低其可用性;通过使用自动化设备的控制器数据接口获取数据,或者在老旧设备中增设如“安灯”数据采集,设备电流互感器等传感器自动收集设备信息。有些设备可以改造为在线检测的,可及时获取质量数据,而对于加工后检测的就需要在IT系统中自动获取产品的质量信息;
  2. +
  3. 设备运行的事件记录:尽管自动化和AI程度的很高,但是我们依旧无法离开“人”在制造流程中的参与,特别是还处于半自动化半手工状态的众多小型制造企业,比如对设备突发的状况人工干预。这些状况坑定会对OEE产品印象。如果我们仅知道设备OEE水平低,但是并不知什么原因导致如此表现,则就无法找到改进的方向。将操作人员的事件类记录(非结构数据)与OEE对比才是数字化改造的重要目的;
  4. +
  5. 最后将生产调度中的数据拉入OEE的计算公式中,自动获得不同角度的OEE,为制造运营改善提供洞察insight;比如有文章建议,可以测量三种不同的时间窗的OEE:最后一小时OEE,最近换班OEE,和开机后OEE。通过观察不同时段的OEE,可以获取更多有关生产的见解,比如,不同班次的OEE的差别原因是什么?如辅具更换速度,准备时间长短,环境数据等。又比如企业在工艺调整后,观察对OEE的提高判断改善的有效性。
  6. +
+

但是在使用OEE时,也需要企业特比小型和谨慎,比如:

+
    +
  1. OEE数据为经营改善提供了改善,但是如果将OEE数据作为考核指标,则有可能诱发运营人员操弄数据,虚假提升的问题。就比如,当前的OEE是 OEE=0.7X0.6X0.9=0.378,而通过提供运营可用性,而降低产品质量,可能的数据就是OEE=0.85X0.6X0.8=0.408. 这样看似OEE提升了,但是产品次品率提升,对企业声誉产生影响,并非可取之策
  2. +
  3. OEE一定要结合特定的生产环境中,制造企业中的生产环境不一样,产品不同,工艺不同,即便是同样的设备也有可能是不同的OEE,不能一概而论,或者强行比较,特别是将设备OEE与最终产品价值进行比较。比如,虽然同样的机床,但是加工工件所需工艺和时间不同,但产品的价值就完全不同。OEE作为改善指引,最后是用其与同一个设备的历史值(或者数字孪生同设备的虚拟值)进行比较。
  4. +
  5. OEE仅仅是数字化运营升级的第一步,但绝对不是仅此一步或就此一步,正如精益管理核心理念之一的持续改善一样,数字化与智能化升级也无法“毕其功于一役”,持续的发现需求,发现瓶颈,挖掘潜力才是数字化制造企业长期追求目标;
  6. +
  7. OEE的目标仅仅与时考察单台设备的运行指标,且如前文所讲还是一个滞后指标,随着AI技术的发展和IIoT技术的进步,特别是预测性维护技术的发展,正如有的文章指出的那样,OEE的重要作用将让位于设备健康值,即在数字化运营特别是MES(MOM)的优化后,设备“借故偷懒”的机会已经不多了,只要设备健康就可以持续产生收益。此时OEE可能仅成为一项设备是否需要投资的参考最低阀值。
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#总结:
虽然OEE是个单一的指标,但是对计划进行数字化建设和升级的企业,特别是中小型制造企业,是个非常合适的发起和实现的项目,通过当前IIoT的技术,特别是通过设备互联做到数据自动采集,仅需要有限的投资和部署,就可以为企业带来数字化提升制造效率和运营水平的初期效果。

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hello http://example.com/2023/11/30/如何改造成为智能制造工厂?让我们从OEE开始/ bye

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+ + 智能制造 OEE + +
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