不同的购房支付方式，产生纠纷时，会有不同的法律后果。在此，笔者提醒，购房付款时要留个“心眼儿”。 　　一、为自己购房，购房款来源于自己的支付方式。购房时间是在单身未婚状态之时，要区分两种情况：1、一次性支付购房款，且产权证只登记在自己名下，可采用银行转账模式。这样，可避免点数现金的不便和保障携带资金的安全性。2、先付定金及首付款，余款需从银行贷。这里，要涉及较长年限的月还贷款，或结婚后共同还贷、或可能面对结婚后将房屋卖掉再购房等问题。因此，付款方式要格外慎重。建议采用银行转账 方式付款最好，即直接将房款从自己名下的账户内打入房地产开发商或上家账上，妥善保存好付款转账的银行凭证及单据，以便备用。 　　二、为自己购房，购房款是他人付的支付方式。1、现金方式。在自己购房，他人付款的情况下，用现金方式支付购房款，非常有利于购房人。因为产权证登记在购房人一人名下，即使他人陪同购房人一起去售楼处付款并由他人现场支付，发票也只会写购房人的名字。日后如产生纠纷，购房人声称购房现金来源于己，举证责任对他人不利。2、银行转账方式。自己购房，房款由他人从其名下的账户转账到房产开发商或上家，会直接产生一个法律隐患：他人代自己支付房款的行为是什么法律性质？是赠与还是借贷？如果说是赠与，在他人已婚的情况下，可能会涉及侵犯其配偶权益产生法律纠纷，并且，还有可能产生赠与是否附有条件的法律争议；如果说是借贷，只有转账支付记录而没有借条，也会使争议复杂难辨。因此，银行转账方式付款，在自己购房他人付款的情况下，要慎重考虑。 　　如我们代理的一个案子即是。已婚人士张先生的朋友刘女士买房，从张先生名下的银行卡中划了50万元进入了刘女士购房的开发商处，后划款凭条被张先生的妻子赵女士发现，赵女士勃然大怒，向法院起诉。要求确认张先生侵犯了自己的财产权益，要求刘女士返还自己先生出资的那一部分，确认房产出资部分属先生与她共有，遂引发争议。 　　三、为他人购房，但产权证不写自己名字的支付方式。同理，为他人购房，但产权证不写自己名字的情况，最好也采用银行转账的方式，这样至少可以充分证明购房款是本人支付。日后若产生争议，才会有探讨是赠与还是借贷的事实基础。同时，必须提醒房款代付人，即使以后同购房人产生争议，所能涉及的，只能是基于所付房款而形成“债权”的法律问题，而不会因为购房款是自己支付的而想去分得购房人所买的房产。因产权证登记在购房人的名下，付款的出资者不可能通过诉讼方式去争取到房产的物权。 　　四、婚后购房，用自己个人或父母家人资金购房的支付方式。1、婚后购房，动用了自己婚前的个人存款。如果产权证登记在夫妻二人名下，自己婚前存款支付房款的这一部分金钱，基本上就“转化”成了产权共有的房屋所有权益。如果以后离婚分割房产，你主张你婚前个人存款部分的出资或出资增值部分归你自己，法院一般是不会支持的。原因在于，法院一般会认定，你在明知房产登记在二人名下的前提下，仍动用属于你个人的婚前存款去支付，支付行为构成了对配偶的赠与；再者，因产权登记为共同共有，因此，产权分割还是按共同共有的原则分割。反之，如果产权登记在你一个人名下，房产被认定为共同共有的可能性虽然很大，但对你婚前个人出资的部分，法院在分割共同财产时扣除你个人出资部分再分割的可能性较大。2、婚后购房，动用自己父母资金的情况。婚后购房，由自己父母出资的出资款在以后产生争议的认定，主要看产权登记的情况。如果产权登记在自己一个人的名下，这部分出资在上海地区法院被认定为父母对自己子女个人赠与的可能性大。但是，如果婚后购房自己父母出资，产权证登记在小夫妻双方的名下，则父母的出资会被认定为对双方的赠与。若以后产生离婚争议，该房产会按均等的原则分割，即如果离婚，配偶会“沾便宜”。如要防止日后产生争议，更好地保护老人的出资权益，可以在产证上写上父母的名字，约定共同或按份共有；或由小夫妻双方共同写下欠条来保障父母的出资权益。 　　五、婚后购房，用夫妻共同财产购房的支付方式。婚后购房，即使是使用夫妻共同存款购房，出于共同财产开销证据的考虑，还是建议采用转账方式购房。夫妻间如果产生纠纷，配偶让你说出你名下财产的下落和花销所在。那么，从自己名下划款买房，证据确凿，谁也不能否认。 　　综述，购房出资的支付方式，须加以注意，以防日后麻烦出现。 收起阅读 »

在"中国标准交流互助"论坛注册了N久,里面标准N多,但是积分难度也较高,今天帮别人下载一份GB 7826-1987标准,分扣了,可标准没到手, 仔细想想,下载了五次,没一次自己下成功过!浪费了俺的心血啊,好不容易换来的积分就这样不在了,现在连下一个标准的积分都不够了,这网站也真让人郁闷了!无赖呀!
本来想自己能在里面产足了,为朋友能做得更多,更好呢,没想到啊,还是徙劳无功! 收起阅读 »

新浪网等媒体又开始炒做超级女声的话题了，不过这次炒做的是超级女声现象是否毒害年轻人。
　　这一两天，新浪网都在首页链接了一个抨击超级女声的话题，今天腾讯网也在新闻的首页链接关于超级女声的这个话题进行炒做。
　　这个争论是这样引起的，全国政协常委刘忠德先生前些天对超女现象表态说：“作为政府文化艺术有关管理部门来讲，不应该允许超女这类东西存在。参加超女的被害了，看这个节目的也被害了。”并指超女、超男活动是对艺术的玷污，这大概是第一个政府官员对超女节目的抨击。此话一出即在网络界引发了掀然大波，各地网民争论极为激烈。
　　我个人并不喜欢看超女，一来没精力，二来没兴趣，三来也不喜欢其风格。但我并不会限制别人看超女的权利，并且我特别反感一些老家伙们利用手中的实权来妖魔化超级女声这个节目，人为的将这个娱乐节目添加政治色彩，扣上一个大帽子然后进行攻击。
　　这次发言的是全国政协常委刘忠德，我特意查询了一下他的个人资料，发现了他已经有73岁的高龄，其个人资料如下：刘忠德，1933年5月出生，吉林省集安人。原中宣部副部长、文化部部长，现任全国政协常委、科教文卫体委员会主任，中国工程院主席团顾问。
　　中央多年来形成一个关于退休的惯例性制度，在邓小平力主废除领导干部终身制之后，在实践中逐渐形成了中央领导70岁左右退休，省部级官员65岁离岗，副部及地厅级官员60岁退休，超过50岁一般不再提拔为县级领导等一系列制度或惯例。
　　而这位年过七旬的老人居然还继续担任领导职务而不退休，不但违反了邓小平主导的废除领导干部终身制的制度，并且还在公众媒体发表这样引起大众争议的讲话，请问他想要达到的目的是什么呢？他说这番话的动机又是什么？
　　很多人年纪一大就犯糊涂，容易在不恰当的时候做不恰当的事情。目前我国正处在发展的关键时期，只有保持稳定，才能聚精会神搞建设，一心一意谋发展。稳定是和谐的前提和基础，也是构建和谐社会的重要内容。保持社会稳定，才能化解矛盾、理顺情绪，而刘忠德在社会媒体前如此发言，激化社会矛盾，引起一些毫无意义的争论，影响了稳定团结的大好局面，是不恰当、不合时宜的，我们这些合法的纳税人深切地希望我们的领导阶层能够严格执行关于邓小平主导的领导干部退休制度，超过规定年龄的应该立即退休，并严格淘汰党内一些的捣乱分子和投机分子，真正把精力放在经济建设上。 收起阅读 »

2
如对于设立新厂的方案，上司最关心的还是投资的回收问题。他希望了解投资的数额，投资回收期，项目的盈利点，盈利的持续性等等问题。因此你在说服上司时，就要重点突出，简明扼要地回答上司最关心的问题，而不要东拉西扯，分散上司的注意力。-质量-SPC ,six sigma,TS16949,MSA,FMEAe`-MeK1US8CNx1h0Jbbs.6sq.net(五)面带微笑，充满自信#n9rp1a!l%yb-质量-SPC ,six sigma,TS16949,MSA,FMEA ,u`)v-G"h3f i]bbs.6sq.net我们已经知道，在与人交谈的时候，一个人的语言和肢体语言所传达的信息各占50%。一个人若是对自己的计划和建议充满信心，那么他无论面对的是谁，都会表情自然；反之，如果他对自己的提议缺乏必要的信心，也会在言谈举止上有所流露。试想一下，如果你的下属表情紧张、局促不安地对你说：“经理，我们对这个项目有信心。”你会不会相信他？ G# I:f)?!vq\你肯定会说，我从他的肢体语言上读到了“不自信”这三个字，我不太敢相信他的建议是可信任的。同样道理，在你面对自己的上司时，要学会用你自信的微笑去感染上司，征服上司。-Z4N h4ag%i9yZF,V-质量-SPC ,six sigma,TS16949,MSA,FMEA :t:J/m3~(r3R|&V(六)尊敬上司，勿伤上司自尊0mW R VJ`Obbs.6sq.net Sv$RG$PWLN六西格玛品质论坛最后要注意一点，上司毕竟是上司，因此，无论你的可行性分析和项目计划有多么完美无缺，你也不能强迫上司接受他们。毕竟，上司统管全局，他需要考虑和协调的事情你并不完全明白，你应该在阐述完自己的意见之后礼貌的告辞，给上司一段思考和决策的时间。即使上司不愿采纳你的意见，你也应该感谢上司倾听你的意见和建议，同时让上司感觉到你工作的积极性和主动性即可。六西格玛品质论坛SX D8sHyi[
Bh4{\4_D【自检】o+Yh VG
AE8Cbbs.6sq.net在说服上司时，你注意过以下要点吗？ZA/dk[x*J\A六西格玛品质论坛说服上司的要点 一贯如此(3分) 经常如此(2分) 很少如此(1分)bbs.6sq.netRpE |W#U:ZV2\:K能够自始至终保持自信的笑容，并且音量适中。 w\al
lL六西格玛品质论坛善于选择上司心情愉悦、精力充沛时的谈话时机。 六西格玛品质论坛'^ I~!U et已经准备好了详细的资料和数据以佐证你的方案。 Kcy~dv对上司将会提出的问题胸有成竹。 2n2b[B5M0Pdnj3M-E语言简明扼要，重点突出。 L!XH-B+HXv4C]bbs.6sq.net和上司交谈时亲切友善，能充分尊重上司的权威。 't#SYqw S\Mfqd .i pojn{'PI六西格玛品质论坛得分：sCR U\8z14～18分：能在工作中自觉的运用沟通技巧。你是一个非常受欢迎的人，你的上司很赏识你。3~s"Ke6~E六西格玛品质论坛7～13分：你已经掌握了很多沟通的技巧，并已经尝试着在工作中运用。你的上司人认为你是一个有潜力的人，但还需加紧努力。(k8m8I-JUf0～6分：你应该抓紧时间学习一下和上司的沟通技巧了。因为你现在和上司的关系很不融洽，适当的改善沟通技巧，可以帮助你充分发挥自己的能力，去争取更为广阔的发展空间。六西格玛品质论坛tM1XESG【本讲总结】,x4~JAO.u上司也是人，也希望与下属沟通交流，也希望建立融洽和谐的上下级关系。所以，不要害怕，也不要犹豫，勇敢地去做，合上本书以后就开始思考一下你要怎样才能更好地运用沟通技巧与上司相处，要怎样才能把本讲所提及的沟通技巧熟记于胸，灵活运用 收起阅读 »

今天上网时发现一个免费下载管理类资料的网站，大家去看看。
http://www.study365.cn/

LCD的閃爍之前曾經帶一個項目，給日本人SHARP做LCD-TV,我們公司本身有一定的研發能力。但制造端的功能缺陷分析能力比較低，當時有項不良特別奇怪--1080i畫面閃爍, 試產時一批幾百裡面有1－2個，量產後問題遍地開花我們做的驗證情況為：同一臺機不良發生後間隔幾分鐘測試就不會閃爍了，同一台機換個工位測試就不會閃爍同一台機換個測試設備測試就不會閃爍同一台機重新插拔再測試此現象就消失同一臺機換個線測試也沒有問題工程部門給分析結果，從頭到尾千奇百怪（歷時幾個月）＝（電阻/電容/IC重焊OK，測試環境干擾,測試設備/cable不匹配，重測OK **** 　　）好象把我們當做小孩哄騙，從開始我們自己觀察分析都知道他們是在胡扯（他們自己也知道是在胡扯），但我們也沒有好的法子，那個問題從小批量試產就一直掛著，當然，局限內部，每次QA-meeting都瞞著小日本。從開始我們QA內部也是意見不統一，但多半傾向是車間內部信號干擾，環境影響所致。但當後續同類產品衍生出幾個小機種生產量猛然加大後問題就嚴重了，嚴重時候每天都有20台左右，生產部門暴跳， 收起阅读 »

李云龙为什么会给和尚报酬---------------------------------有感于'管理杂谈'"如果你是李..你会给和尚报酬吗"一文如果你在下层干过，你了解他们，这种事情，你必须出头！ 这就是李云龙说的，他不报仇，这兵他没法带了... ... 你可以揉沙子处理，你可以说要讲究策略，你可以批评这是什么主义,违反什么原则,但如果到硬的时候你不硬起来，那你就是痿！这种时候就是要你硬！说下俺的一次经历，A主管当众侮辱（举动而非语言，定性为侮辱是我向我老板汇报时候说的）俺一同事：当时她找A去签一个单，对方之前已经多次拒绝，因为那上面最终归结的责任部门是他们，签后将减少他的奖金。也许当时那哥们实在受不了了，当众接过那单说，我就是不签，看你怎么着！~说完揉揉仍旁边的垃圾桶里了！~！！ （目击证人N多）我那女同事脸上挂不住了，哭泣着来找俺哭诉，‘反了！’，我第一反应！我立马到那A面前，大吼，‘你把那单现在拣起来，签了~！！！’ 他看了看我，红着脸，没吭声，我马上指着他鼻子说，‘签完明天早会当着大家面前给她道歉！！！’，他还是没动。如果他不是比我壮太多,老子立马上去抽他! 当然，我不是他老板，我的话他可以不听。 我随后先找的他老板B，B嬉皮笑脸地说，‘别生气，那小子就那脾气，呆会我去教训他。’不痛不痒的给我软顶了过来，我转身就走。坐在我老板面前，我们俩把事情说了一遍，老板开始只是说，让我通报给他们老板，让他们自己处理得了，我接着强调，日常基层Q工作环境已经非常差，如果这件事情解决不好，日后基层一线的工作将非常难以开展，严重影响大家的工作情绪，事情可大可小，并且我话已经放出去了，处理不好我明天就辞职！ 在我的强硬要求下，老板无奈下手了......结局是，那A把我说的几点都做了，他揉的那单他自己又找了回来，哭泣着做了深刻检讨/道歉......事隔N月后我离开那公司的最后散戏宴上，大家才对那次我的举动大谈心得，其中几个人哭泣感谢我的帮忙，让他们走起路来都有精神！ 收起阅读 »

李湘离婚尽管，她结婚时候N多人认为这是个短命婚姻，尽管，说相声的那大嘴更是夸张宣布他们蜜月结束时就会离婚！尽管，我当时也觉得最多1-2年就离婚，但，这两天看到她公布早已经离婚后还是感觉很惊讶！ 王老五可不是那么容易嫁的哦...婚姻真的需要预热期，去深刻的了解对方，除非你不想长久。包括自己，预热了几年也才敢走入婚姻殿堂。身边年轻的离婚的多的是，有个朋友结婚完真的是蜜月一结束就办理离婚手续了！人怎么了？？？一边离婚的熙熙攘攘，一边等待结婚的焦急万分... ... 收起阅读 »

　像片片飘落的叶，归于尘土一般。这季节，又有人过世，灵堂就设在楼下，正对着我们这个单元的窗口。中午开始搭灵堂，下午我出去时就已经全部搞定。据说，现在有专业的人士服务，只需打个电话。如果愿意，还可以请到专门哭灵的人，哭得不真不要钱。 　　等我从外面回来时，花圈已经从大门口摆到了单元门口。从花圈的文字内容上，可以看得出这是一位父亲去世，敬献的挽联还可以看出他子女双全。子女双全的丧事自然不能差到那里去，要不，一片孝心如何体现？ 　　自古就有红白喜事的说法。往往结婚的人想到的是，反正一生就一回，讲讲排场又何妨。不过，逐年上升的离婚的人数正在打破这个观点，也就是说，结婚这事一生还指不定有几回，这排场讲不讲，怎么讲，那还要另说。两个人的事情两个人商量着办不是。 　　反倒是这白的喜事，是自己说了算。没见有商商量量一起办的，也没见这事还有要邀请的。不敢想象，大限来时要走的人，见到人就说，我不行了，你要不要和我一起上路？肯定没有这样的。所以，这白的喜事，虽说不能选择何种方式，但在走这个问题上真正是自己的主宰。如果有家人过世，活着的人大多认为，必要的排场还是应该有的。 　　葬礼也能检验事实的真相，我信！曾经见到过比这还讲排场的丧事。哭灵的人都请了一个班。那阵势，大！可还是掩饰不了子女身前不孝的事实。身前对老太太一点不好，死了都还想靠这个捞一把，为分东西，几个人争着比试武功，老太爷看着心凉，就差一口气不来被活活气死。那时，我很为这个活着的风烛残年的老人担心。 　　我也亲眼见过白发人送黑发人。八十多岁的唐婆婆，照顾了两年身患癌症的儿子，无微不至。有太阳时，母子两人一起晾晒那些我不知道名字的中药，母亲的镇定，儿子的平静，给我留下了深刻印象。儿子走时，灵堂里没见哀乐，放的是佛乐。老人一直也没哭，说是哭了对儿子不好。只是后来，我发现送走儿子的老人，背越发的驼了。 　　有句老话说：娘想儿，路来长；儿想娘，扁担长。两场不同的葬礼，让我再次见识了这句话。也让我对生与死看淡了许多。我们每个人的身份，随着年龄的增长总是在不断变化，子女－父母－祖父母，到头来，还是难逃一死，说大是自然规律，说小，这由得了自己吗？ 　　生活就像一场繁华的盛宴，每一个人从出生开始，就注定是来参加一场宴会，完了，该干嘛干嘛。诗人说，“悄悄的我走了，正如我悄悄的来，我挥一挥衣袖，不带走一片云彩。”要我说，我们每个人都是诗人，赤条条的我走了，正如我赤条条的来，我挥不挥手，都带不走一片云彩。少有的干净！所以看《红楼梦》时，最喜欢宝钗念的《寄生草》里的句子：“……没缘法转眼分离乍。赤条条来去无牵挂……” 　　做人难，难就难在，很多事情自己都无法选择、决定。但有一样，也许可以温暖人心，那就是亲情。什么也割不断一脉相连的骨肉亲情。说这话的定是有人情味的家，有人情味的人。倘若不是，换来试试，恐怕也说不出那样的一句话。 　　今晚，外面麻将声声，吃东西的吃东西，说笑的说笑，好不热闹，见不到一点哀伤的气氛。我不知道这家人的情况，也不能乱说，只当他（她）们用办喜事的精神，为老人送上最后的热闹和繁华。三天以后，这里什么也不会留下，一切都将归于平静。就像繁花过尽，终究还是一场空。人生，不过如此！ 收起阅读 »

其实简单就是一种美，一种崇高的境界，一种无知的力量，一种坚定的信念，人活着其本身就是一个很简单的过程，无论你活得怎样轰轰烈烈，都离不开生活琐碎的简单，而当你不把名誉地位看得太重，那么简单的你就会轻松如意，我们生活条件的差异在不同程度上彰显了人的个性差异，而你不把奢侈享受看的太重，那么简单的你就会回归自然。让自己保留那么一份简单是可贵的，不要让人感到一个天天躲在面纱后面的你心绪沉重，做人要活得真实，活得坦诚，不要让欺骗和谎言把自己包裹的透不过气，应该让简单的你直面人生。而当简单的你要真实的去做每一件简单的事，带给你的意外收获也将是你人生里最大的快慰和满足。 　　不久前，一位大哥看到了我的博客，让他感到大吃一惊，因为我在他的眼里就是一个天天很能闹的调皮鬼，而让他意想不到的是，就是这样一个简单的从来没有想写点什么的淘气包子竟然把自己的博客办的有声有色。因为看到我的博客好，他却要拜我为师，就这样一个政府要员很谦虚很简单的成为了我的学生。 　　帮助大哥注册了博客之后，却没想到这博客又改变了他的人生志趣，原本不爱说话的大哥乐观了，原本辍笔停耕的他仅在月间就写出上万字的文章，原本开始时茫然不知所措的他变得轻松自如，而这一切的收获都是大哥告诉我的，那都是来自于我最简单的建议，这建议给大哥带来了意想不到收获，带来了美的享受，成为他一生中难忘的记忆。 　　我在大哥的博客里看到这样一则故事：有一外国记者在采访一位曾获得世界诺贝尔奖的科学家时，问科学家一生中最大的收获是在哪个重点研究所或哪所高等学府，出乎意料，科学家告诉记者，他最大的收获是在幼儿园里。记者不解地问为什么？科学家回答，我在幼儿园时学到了“别人的东西不要拿，自己的东西要分给小朋友一半，饭前要洗手，要善于动脑筋认真观察事物。”也正是这样一些很简单的道理影响了一个人的一生，这其实就是一个简单的做人的道理。想当年，董存瑞舍身举起炸药包炸掉敌人的碉堡，黄继光用身体堵住敌人的枪眼。也许当时他们想得比较简单，就是要消灭敌人，但是他们却为中国革命的胜利做出了英勇的贡献，他们的伟大壮举也将永世长存！ 　　我在博客里很简单的记录了生活中的快乐和幽默，却给来参与的朋友们带来了意想不到的收获，那是来自心灵的快乐。一种简单的境界却给观赏博客的朋友带来了对生活的感受和求知的欲望。我为许多朋友建立了博客，他们把简单的祝福送给我，却让我感受到了最真实的情意。我为帮助了别人而带来的满足而自豪，虽然只是为大家做了简单的事情，而我获得的收获将是许多年以后的鲜花和掌声，这就是简单带给我们的最大的享受和充实的人生。 收起阅读 »

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天气: 冷心情: 平静山有木兮木有枝，
心悦君兮君不知？视频: http://www.jxllt.com/ad/shunchi/yuerenge.wma

一个月没来这里了，今天极度郁闷，就来这发发牢骚！突然知道公司要搬了，搬到一个小地方，领导说还只能带几个人去，不是全部！那破地方谁愿意去！大伙都不愿意去的，一夜间，全部被失业！人心惶惶的，各自谋出路吧！想想真去那地方，面临几个问题：是否涨工资，吃、住、、、烦啊！去哪里了肯定是被降工资，领导肯定说那里消费低，什么什么的 收起阅读 »

The Final TestEdmond L. Kyser, Ph.D.Cisco Systems
版权属于作者


Abstract
Manufacturers of complex electronic equipment invariably have a 'Final Test' - a test where product that passes is shipped to the customer, and product that fails is sent to rework for repair. Traditionally, these Final Tests fall into three categories: Burn-In (power on and functional at room temperature for an extended period of time), Conformance (power on and functional at design limit of temperature and possibly other stresses), and Overstress (power on and functional at stresses beyond design limits). The decision of which Final Test to employ is analyzed in this paper in terms of Type I and Type II errors (false failures and false passes), and the conceptual biases commonly found in this decision process.Introduction
In the manufacturing process for complex electronic products, there are many test operations, each of which can be considered a 'confirmation' of the immediately preceding assembly operation. At the conclusion of each test, there are two possible outcomes - the product is either 'shipped' to the next assembly operation or is returned for rework. The 'good' or 'normal' outcome is that the board passes.
In statistical terms [1], we call the good outcome the Null Hypothesis. The Test is designed to confirm the Null Hypothesis. Here we will be concerned with the design of the Test - specifically, what is the criteria for the board to be judged 'good', and how accurate is the Test in confirming this 'goodness'?. Setting aside for the moment the definition of 'good', the situation is as shown in Table 1.






Test: Positive

Test: Negative


Good board

Correct result

Type I error


Bad board

Type II error

Correct result
Table 1Type I and Type II errors
A Type I error - designating a good board as bad - is called the producer's risk, or a false fail. A Type II error - designating a bad board good - is called the consumer's risk, or a false pass. In this case, these are the only types of error possible. A good test will minimize these errors. Burn-in, Conformance and Overstress
It is common for complex electronic products to exhibit the reliability characteristic shown in Figure 1. A high initial failure rate (or parts return rate) is followed by a more-or-less asymptotic decline over a period of time to a steady failure rate, sometimes called the 'mature' failure rate. This is the same characteristic as the front end of the infamous 'bathtub curve'. However, the data in Figure 1 do not show an increasing failure rate as time passes, indicating that there is no evidence of 'end-of-life, or wearout. In what follows, we will use the generic characteristic of Figure 2 for the products being analyzed.
Figure 1Part Replacement rate vs. Time for 5 computer products

Figure 2Generic Field Failure Characteristic
Figure 2 is the metric of success for the benefits of the final Test. We expect product that passes the final test to perform better in the field - that is, to have fewer early life failures, and a larger MTTF.
Consider now three candidates for Final Test - Burn-in, Compliance, and Overstress.




Final Test

Characteristic


Burn-in

Functional test at ambient or elevated temp for extended time


Compliance

Functional test at design limits


Overstress

Functional test beyond design limits
Each of these candidates for Final Test has its champions, its history, its advantages and drawbacks [2,3,4]. The task before the manufacturing test engineer is which to recommend for a specific product, and the task set here in this paper is to systematize the decision.


At this point we have introduced two measures of 'badness' - Type I and Type II errors - and one measure of 'goodness' - MTBF improvement, or early life failure reduction. The three Final Test proposals differ primarily in the level of stress applied. In addition, the error rates at final Test will be Stress level dependent - assuming that the stresses selected are relevant (more on this later). This is illustrated in Figure 3.

Figure 3Type I and Type II errors vs. Stress Level

Several comments are in order relating to Figure 3. Most importantly, it is a metaphor - a model of reality. As the advertisements say, your results may vary. However, the general characteristics of figure 3 are representative of the products that the author has experience with. If Burn-in is performed at ambient conditions with stresses that are close to end user reality, then the Type I error rate (false fails) should be essentially zero. However, Type II errors (false passes) will be relatively high (remember that ALL field failures are by definition Type II errors). The appeal of Burn-in is that it is a low cost, low engineering content, low risk test - and the cost of test escapes is deferred until failed product is returned. It does not typically assure (or test for) product functionality over the entire design stress range. The producing company has promised performance it has decided not to confirm in a Final Test.

A Conformance Test is designed to alleviate the deficiencies of Burn-in, possibly at the cost of increasing Type II errors. For example, a product specified to operate from 0 to 50C, 15% to 85% humidity, +-5% supply voltage, and some maximum load in terms of users or traffic, should be tested at all combinations of these extreme values for a comprehensive Conformation test. In practice, this is seldom done. One alternative is to test at two corners of the conformance space - the 'fast' corner of high temperature and low voltage, and the 'slow' corner of low temperature and high voltage. The expectation for a conformance test is that Type II errors will be reduced and Type I errors will increase, as compared to Burn-in. The appeal of conformance testing is that the stresses are identical with the design criteria, and that it should produce a more robust product that Burn-in.

If only Burn-in and Conformance were represented in Figure 3, the curious engineer would likely ask the following questions: where is the optimum stress level - and could it possibly lie beyond the design/conformance level? After all, the curves for Type I and II errors are continuous through the design limit stress level - the best stress level could very likely be beyond the design limit. The real answers will require an assignment of relative importance to Type I and Type II errors. The use of stresses beyond design limits - overstress testing - was begun in the early 1980's, notably by the US Armed Forces, in an attempt to improve system reliability [5].

COSTS AND BENEFITS

The following cost-benefit analysis was developed in [4] as a method of 'netting out' all the positives and negatives relating to Environmental Stress Screening. The model allows for variables with unknown values to be estimated in terms of probability distributions, and the outcome calculated by Monte Carlo techniques. The output is a probability distribution of Net Present Savings per board tested. The software used was ‘Analytica”, published by Lumina Decision systems [6].

Figure 4 shows the relationships between the variables in the model. The costs of Type I errors are calculated in the node labeled ‘Cost of Test Failures’. The costs of Type II errors are calculated in the node labeled ‘total field Failure cost’. Since field failures occur, on average, at the MTTF, these must be discounted by the Cost of Capital to yield ‘Present Value of FF’, which can then be compared directly to ‘Cost of Test Failures’. The ‘NPS Importance’ node gives the relative importance of the variables in calculating Net Present Value. This will be discussed in a following section.

Figure 4Cost Model Variables and Relationships


It should be clear that cost considerations are not included in the definitions of Type I and Type II errors. The addition of cost in the model above allows us to evaluate the Net Present Savings per board generated by Final Test. The details of this model and the definitions of the mathematical relationships are given in [4]. Here we want to apply the model to 3 very different product scenarios in order to evaluate proposals to strengthen final Test and to reduce Type II errors.Table 4 shows the parameters for 3 products. Case 1 is for a fault-tolerant high-end Server, Case 2 is a Controller with a small imbedded processor, and case 3 is a telecommunications Router. The question in each case is should the Final Test be strengthened to Overstress status.




Variable Name

Units

Comments

Case 1: Server

Case 2: Controller

Case 3: Router


Cost of Inventory

%/week

Includes Depreciation and liquidity effects

Lognormal (0.5, 1.5)

Lognormal (0.5, 1.5)

Lognormal (0.5,1.5)


Test Failure Repair Cost

NP$

Material and Labor costs for debug and repair

Lognormal (1500, 1.5)

Lognormal (8,2)

Lognormal(1000,2)


Time to Repair Test Failure

Weeks

WIP time

Lognormal (6, 1.5)

Lognormal (.5,2)

Lognormal (1, .5)


Replacement Cost of Field Failure

Future$

Material and Labor (warranty costs)

Lognormal (2500, 1.25)

Linear (5,10)

Lognormal(190+0.52H, 1.5)


MTTF of Unscreened Unit

Years

Mean Time To Failure

Lognormal(5, 1.5)

8

Normal(20,2)


Impact of ESS on MTTF

%

Factor by which ESS improves unit MTTF

Normal (25%, 15%)

Normal (20%,15%)

Normal(20%, 15%)


Operational Costs

NP$

Variable cost only (no fixed costs)

Lognormal (50, 1.5)

5

Lognormal(20,2)


Whole Product Cost

NP$

Used to calculate inventory, depreciation, and replacement costs

5000

100

8000


ESS Yield

-

Probability of passing ESS screen

90%

90%

90%


IBP for Field Failure

Future$

A measure of the intangible costs

2500

Linear (20,40)

H/2


Cost of Capital

%/year

Time vs. money discount rate

15%

15%

15%

Table 4Input Variables for 3 Products

Once these values are input into the model, it calculates the probability of achieving Net Present Savings. For the Server, the results are shown in figure 5. Figure 5NPS for Server

From Figure 5, the cumulative probability of breaking even ($0 NPS) occurs at 0.3, meaning that there is a 30% probability of a negative NPS (costs exceed benefits, and the final Test looses money) and 70% probability of a positive NPS. The Expected Value of NPS, which is defined as 50% cumulative probability, is about $180. We expect this version of Final Test to save us $180 per board tested. Therefore, this program should be implemented.

Typically, a few uncertain inputs are responsible for most of the uncertainty in the final result. I have had opponents of overstress testing argue, for example, that the cost of repairing Type I failures would make the entire test worthless. This type of question is best answered by using Importance analysis – which, in statistical terms, is the absolute rank-order correlation between the sample of output values and the sample for each uncertain input. (See [6]).

Figure 6 shows the Importance analysis for the Server. Here we see that ‘Impact of ESS on MTTF’ is an order of magnitude more important than ‘Test Failure Repair Cost’ – and thus, if the model is to be challenged or improved, one should focus on Impact of ESS.

Figure 6Variable Importance for Server


Looking at Figure 7, NPS for an Embedded controller, the cumulative probability of breaking even ($0 NPS) occurs at 0.9, meaning that there is a 90% probability of a negative NPS (costs exceed benefits, and the final Test looses money) and 10% probability of a positive NPS. The Expected Value of NPS, which is defined as 50% cumulative probability, is about -$3.00. We expect this version of Final Test to loose $3 per board tested. Therefore, this program should not be implemented. Looking at the input values, we suspect that this conclusion is dominated by the high reliability of the unscreened board, and the low cost of a field failure.

Figure 7NPS for Controller

Variable importance for the controller is shown in Figure 8. Note that once again the impact of ESS on MTTF is the leading contributor to uncertainty in the final result of NPS. Also, importance is only calculable for variables, not input constants. Therefore, for example, operational costs which were variable for the server and show up on the ‘importance’ chart, are input as constant for the controller, and do not appear on the importance plot.

Figure 8Variable Importance for Controller

Turning to the case of the Router in figure 9, the probability of breaking even ($0 NPS) occurs at 0.4, meaning that there is a 40% probability of a negative NPS (costs exceed benefits, and the final Test looses money) and 60% probability of a positive NPS. The Expected Value of NPS, which is defined as 50% cumulative probability, is $52. We expect this version of Final Test to save us $52 per board tested. Here the risks are high, and the outcome is uncertain. A good policy would be to go back and re-evaluate the input parameters, or to run a preliminary test in an effort to reduce uncertainty.

Figure 9NPS for Router

Router Variable Importance in Figure 10 shows Impact of ESS again the leading cause of uncertainty, but now Test Failure Repair costs are significant.

Figure 10Variable Importance for Router

Finally, we can extract from the preceding analyses the costs of Type I and Type II errors for each of the 3 cases being examined. These results are shown in Table 5. Note particularly how expensive a Type II error is compared to Type I, and the importance of including the cost of money in discounting Type II errors to current dollars for MTTF years. I believe that information like that given in Table 5 can serve well to overcome the reluctance to consider overstress testing. The bias against overstress is often based on fear of creating additional Type I errors.







Server

Controller

Router


Type I error (cost of test fail)

$201.00

$1.13

$146.00


Type II error (field failure)

$5,063.00

$37.50

$8,566.00


MTTF (years)

5

8

20


Type II error in current $

$2,486.00

$14.62

$501.00
Table 5Cost of Type I and Type II errors

Conclusions


Optimizing the final Test can be done in a systematic manner, using statistically represented variables where the true values are unknown at the time of the analysis. The decision of which 'Final Test’ to employ can be analyzed in terms of Type I and Type II errors (false failures and false passes), and calculation of Net Present Savings per board to be realized by the test.Overstress tests can be more effective than either burn-in or conformance, depending on product parameters such as MTTF and cost of repair. The analysis shows that improving the MTTF of the product is the predominately important variable.Each product must be analyzed. Variations from product to product are key, with variables assuming vastly different importance for different products.Type II failures (field failures) are often an order of magnitude more costly than Type I failures (test failures in-house).

References

1. Statistical Analysis for Engineers and Scientists, J. Wesley Barnes, McGraw-Hill, 19942. Burn-In Testing, Dmitri Kececioglu and Feng-Bin Sun, Prentice Hall, 19973. Burn-In, Finn Jensen and Neils Eric Petersen, Wiley, 19824. “The Politics of Accelerated Stress Testing”, Edmond L. Kyser, Eugene Hnatek and Mark Roettgering, Proc. IEST, March 20005. Environmental Stress Screening, Dmitri Kececioglu and Feng-Bin Sun, Prentice Hall, 19956. Analytica Users Guide, Lumina Decision Systems, 1999

收起阅读 »

今天，我的心情非常好，我刚刚提出辞职的想法，结果立刻就有高阶主管
和我聊天，大意是“给我个面子，再留下来帮我。”
上帝保佑，希望他们可以答应我的要求，我这个人很容易满足的，在这里我还有好多自己想做的事情。
everything under in my control !~ 收起阅读 »

Sn-Ag焊料是目前商业推广中最有前景的一种无铅焊料。通过高温试验、热循环试验、热振动复合应力试验，研究了Sn-3.5Ag-0.75Cu、Sn-2Ag-0.75Cu-3Bi和Sn-10Pb镀层、Ni/Pd/Au镀层间焊点可靠性。另外对Sn-3.5Ag-0.75Cu焊料批量生产的试样PCB板进行了环境试验和长达三年的现场可靠性测试，并和传统的Sn-Pb共晶焊料进行了耐久性的比较。


测试方法


表1列出了可靠性测试的条件。组装部件用的是菊花链型内部连线的QFP（0.5mm引脚间距，100只引脚）。QFP的铜引脚采用传统的Sn-10Pb镀层和Ni/Pd/Au镀层。







表1

图1


图1给出了温度冲击试验中测量焊接部位导电性的方法。通过一个扫描仪和一个毫欧表，使用4线测量法可测量出菊花链QFP的导电性。


结果与讨论


图2显示了高温试验后焊点强度的变化。Sn-3.5Ag-0.75Cu焊料和Sn-Pb共晶焊料，不管使用的镀层类型如何，随着时间和循环数的增加其焊点强度都会下降。当作用于Ni/Pd/Au镀层的部件时，Sn-2Ag-0.75Cu-3Bi的焊点强度和其它焊料相比无太大差别；但是，当作用于Sn-10Pb镀层的部件时，其焊点强度会出现显著的降低。


图3是复合环境试验中Sn-10Pb镀层引脚的威布尔曲线。Sn-3.5Ag-0.75Cu和Sn-Pb共晶焊料的试验结果相差不大，在40～50循环下，失效率是50%（L50）。大约在试验开始后2小时，使用Sn-2Ag-0.75Cu-3Bi焊料的PCB板就开始出现失效，试验开始后30小时，所有此类焊料的评估用PCB板均失效。此类焊料用于Sn-10Pb镀层时，L50的出现时间是15个循环。但是，当此类焊料用于Ni/Pd/Au镀层时，在100小时后还没有失效发生。当不施加高温而仅使用振动试验时，无论是何种镀层类型，在试验500小时后都没有出现失效。这样的结果表明了温度的影响是导致焊接部位劣化的主要原因。







图2

图3


图4是经过100小时热振动复合试验后焊点截面背散射电子像。Sn-2Ag-0.75Cu-3Bi焊点开裂发生在焊料内部以及焊料/PCB板、焊料/引线界面处。Sn-3.5Ag-0.75Cu焊点开裂发生焊料/PCB板界面处。Sn-Pb共晶焊料组织变粗大，并在焊料内部产生开裂。


图5反映了界面金属间化合物层的厚度随试验时间的变化趋势。Sn-2Ag-0.75Cu-3Bi/Sn-10Pb镀层界面处金属间化合物层在高温条件下随着时间的延长不断变厚，其生长速度要快于Sn-3.5Ag-0.75Cu/Sn-10Pb的。对于Ni/Pd/Au镀层使用不同焊料，其界面处金属间化合物层的厚度差别不大。







图4

图5







图6



对Sn-2Ag-0.75Cu-3Bi作用于不同镀层的界面结构进行了分析。图6是2000小时高温试验后界面处元素面扫描图，结果表明当含Bi的焊料和Sn-10Pb镀层作用时，在高温阶段由于金属间化合物的快速生长会导致焊点强度下降。


量产PCB板的测试


批量生产的试样PCB板的可靠性测试温度条件设定为：—25℃~80℃。试验项目包括高温试验、高温高湿试验和热循环试验(-25℃/80℃,60分钟/循环)。


使用Sn-Pb共晶焊料的PCB板在2000个循环时开始出现断路，在3000个循环时所有试样均断路。导致的功能问题主要是数字电路系统失效。使用Sn-3.5Ag-0.75Cu焊料的PCB板在3000个循环后依然没有出现失效。


在进行可靠性试验的同时，我们还进行了应用于实际产品的现场可靠性测试。现场可靠性测试包括了在宇都宫和福知山工厂进行和评估的实际操作。到2003年7月为止，这项现场可靠性测试已经进行了差不多3年，操作时间接近20000小时。现场可靠性测试的结果表明没有产品失效发生。


结论






1.
无论使用哪种类型的镀层，Sn-3.5Ag-0.75Cu焊料的焊点强度和可靠性与Sn-Pb共晶焊料相当。






2.
Sn-2Ag-0.75Cu-3Bi焊料与传统的Sn-10Pb镀层焊接时，焊点强度下降。






3.
使用Sn-3.5Ag-0.75Cu焊料批量生产的试样PCB板可以确保至少3000个循环的温度试验，至少20000小时之久的现场可靠性试验的耐力度。






本文曾在第六届国际可靠性、维修性、安全性会议上发表。由爱斯佩克测试科技（上海）有限公司黄卫东共同参与研究完成。原文详细内容请参照会议论文集245-249。


版权属于作者http://www.reliaonline.com 收起阅读 »

[转帖]What is a “Bellcore test?”

Telecommunications suppliers for years have used test chambers to assure the quality of their equipment, making the phone system in the USA extremely reliable and cost-efficient. The regional phone companies have set common standards for quality, centrally issued by Bellcore (now called Telcordia). Up until the last couple years, these standards have remained in obscurity. But with today’s complete rebuilding of our telecommunications infrastructure with fiberoptics, they have come to the forefront.
Even if you aren’t involved in this industry, I think you may find it interesting to learn more. As more and more communications-related companies are created, the need to do this type of testing has increased dramatically (fiberoptic components are quite sensitive to environmental conditions, as opposed to copper-wire). Also increasing is the number of people unfamiliar with this type of test, but required to comply.
There is no single Bellcore test—each test is specific for a type of component and its application. They are all numbered. Most are called Generic Requirements, and are prefixed by GR. The name “Bellcore” has stuck to them, although they are now all officially called Telcordia standards.
For example, one of the popular standards is GR-1221-CORE for fiberoptic passive components. Within this standard are several different environmental tests including simulated storage at extremes, operational tests, and thermal shock tests.
In trying to comply with some of the specific test requirements, it has been our experience that the descrīption of the environmental conditions in the standards are not always written in consideration of the operation of a test chamber. More likely, they describe what was programmed into the test chamber, without considering what the test chamber actually does.
For example, one test (GR-1209-CORE 5.1.2) requires going from –40 to 75°C. At 2°C, the humidity control is required to start, controlled at 80% ±2%. Actually, when the humidity system is turned on, it takes a few minutes to heat up the water to generate moisture, then a little while to gain control at 80%. Meanwhile the temperature has increased, as required by the program. So the chamber never actually achieves the beginning condition of 2C/80% as the standard indicates!
I share this with you to let you know that following a test standard is not a process that doesn’t require you to think. What is acceptable to you, your company, and your customer? Only you can decide. Luckily, it has been our experience that those involved in the requirement for these tests have been reasonable and realistic. 收起阅读 »

天气: 晴朗心情: 郁闷有同事要離職了...因為是玩得比較好的姐妹,那感覺就像是自己離職一樣~~
她在郵件中寫道: 親愛的姐妹們,因我個人在工作上很不順利,不得已要離開妳們了,妳們不要太傷感哦..想當初剛來的時候,........(其中省略5000字).........我會想妳們的!byebye!
9m說得對,做人哪有不累?打工哪有不受氣?壓力無處不在,要懂得自我調節..
我喜歡看<<上帝也瘋狂>>,尤其喜歡其中的一段話:人類創造有利環境,但卻越來越難適應自己創造的 收起阅读 »

下午阿飞发信息告诉我明天他妈妈要来看他，多么幸福的事情啊，羡慕ing。我都快两年没见过我妈妈了，想他们的时候经常一天打一次电话，不过最近几个月因为爸爸在，所以电话也少打了。
昨天晚上爸爸又打来电话，不知道为什么就敷衍了几句挂掉了。不知道从什么时候开始有点逃避和爸爸说话，也许是因为我做的不够好 ，或者说做的太差，所以有点无颜见江东父老的感觉。妈妈问我春节回家不，这个问题从5月份就开始问我一直问了估计有上千次了。我说，现在也定不下来，春节确实不想回来，票太贵人太多我又晕车的厉害。妈妈说那你到底回不回，我说不回吧，明年回。妈妈很失望说你不想看看我吗，我可想看看你呀。我说哎呀，我还不是那样，嘿嘿~一笑带过，其实我也何尝不想家，不想妈妈？但是~~不知道为什么，就是不愿意回去。
也许是爸爸曾经说过的一些话，其实也不算是伤害我，我觉得是我太没用了。作为长女，我觉得我应该承担家庭的一切，爸爸老了，真的老了，上次见到他的时候我真的很心疼。可是我好象又不能为他们做的更多一点。每次在他们唠叨的时候，我只有默默的承受，安静的听着，做不到更多的事情，听听他们的唠叨，就算是为自己的心灵赎罪。
小林结婚了，交了漂亮女朋友，买了房子。这是我小学同学，我的邻居。我父母偶尔会在我面前提起，昨天又说小林快结婚了怎么怎么的。没心思去听。只是在想什么时候也可以象小林那样，做个父母的好孩子~ 收起阅读 »

暂无

天津市交通违章摄录专点分布！开车的一定注意！


常言道“常在河边走，哪能不湿鞋”大家天天在外面开车，难免会遇到摄像的警察叔叔，本人冒死窃得部分摄录点的分布，以飨各位GGJJDDMM们。
凡是路名，表示有警察叔叔在整条路上巡逻摄像；路口一般有固定摄像头和流动的警察叔叔共同把守。希望大家首先要严于律己，不要违章；同时尽量降低自己的损失，别把自己的辛苦钱都赞助了交通事业！

最新内部资料！！！！！！！！！！


和平区：
新兴路 违反临时停车规定
电台道 违反临时停车规定
解放路 违反机动车停放规定
柳州路 违反临时停车规定
南京路 违反临时停车规定
解放彰德 人行道网状线区停车
荣业街闸口街 逆向行驶的
兴安路多伦道 违反标志标线指示的
荣业街 不按规定车道行驶的
张自忠路 违反机动车停放规定
海光寺岗北口 违反排队缓慢行驶规定
大沽路 违反临时停车规定
西宁道 违反临时停车规定;
西康路 违反临时停车规定
南京徐州 违反标志标线指示的
卫津路广播电台门前 人行道网状线区停车
柳州路与潼关道交口未按规定使用转向灯
解放北路逆向行驶的
营口道违反灯光使用规定 气象台路违章停车
解放北路第一饭店和峰光酒楼之间路口,在峰光酒楼楼上有摄像头
解放北路由泰安道向曲阜道方向注意别压黄线
昆明路违反临时停车规定 电台道，单行，与卫津路交口处有摄录头


南开：
水上北路与东路交口 违反标志标线指示的
南开三马路 违反临时停车规定
迎水道飞鸿路交口 违反机动车停放规定
飞鸿路久华里1号楼下 违反机动车停放规定
黄河道南开区政府门前 人行道网状线区停车
鞍山西道 违反临时停车规定
城厢中路 违反机动车停放规定
南马路 违反机动车停放规定
八里台长途车站立交桥北 逆向行驶的
东南角 遇红灯继续通行
南丰路义兴里交口 逆向行驶的
长江道公交三厂门前 人行道网状线区停车
复康路桥下（王顶堤）逆行
华苑信义道右转违反灯光使用
南开区西湖道违反临时停车规定
白堤路违反临时停车规定
三潭路违反临时停车规定
西湖道卫津路口违反行车规定的


河东：
昆仑北路卫国道立交桥下 违反标志标线指示的
天山路 违反临时停车规定
河东易初莲花的肯德鸡门口，违章停车
华昌大街与新兆路交口 违反标志标线指示的
八纬路与八经路交口 未按规定时间道路行驶
河东广宁路和津塘路口
六纬六经至赤峰桥之间路段 不在机动车道内行驶的
张贵庄路雪莲桥旁逆向行驶的
河东家世界（就是第六大道）有拍逆行
卫国道与沙柳路交口逆向行驶的


河北：
金钟桥大街 违反临时停车规定
海河东路 违反标志标线指示的
中山北路 违反排队缓慢行驶规定
中山路人行道 违反临时停车规定
海河东路平安街 逆向行驶的
狮子林大街逆向行驶的
普济河道立交桥下逆向行驶的
普济河道立交桥上逆向行驶的
金钟河大街 违反机动车停放规定
金海道 违反标志标线指示的
狮子林大街上，米兰家园正对的那个路口禁止左拐
李公楼下桥左拐华龙道压线
勤俭桥底下，左拐，要拐大弯，否则逆行
东站.建国道的路口违章下人


河西：
永安道 违反临时停车规定
友谊北路 违反临时停车规定
解放南路 违反临时停车规定
利民道 违反临时停车规定
紫金山路韩江道交口 遇红灯继续通行
隆昌路 违反临时停车规定
福建琼州 未按规定时间道路行驶
尖山路设施处口 人行道网状线区停车
黄埔南路 违反临时停车规定
大沽南路洪泽路路口 逆向行驶的
黑牛城道和尖山路口
下瓦房琼州道从解放南路往河西医院方向违反规定的
河西区宾水道麦当劳门口压越网格线


红桥：
一号路 违反机动车停放规定
西青复兴 不按规定车道行驶的
金华桥北 违反标志标线指示的
西青道家乐超市出口 违反标志标线指示的
复兴路与先春园西街交口 违反标志标线指示的
中环西青 违反标志标线指示的
光荣道与咸阳北路交口西口 违反标志标线指示的
芥园道违反机动车停放规定
红桥纪念馆路与平津道交口 违反标志标线指示的
西青道的登发门口不按规定调头
芥园西道冶金路口 遇红灯继续通行
西青道的登发门口，非机动车道行驶
咸阳路和光荣道交口，占用非机动车道拐弯
古文化街门前违章停车



如果是在市内违法被摄录，必须到市内六区任何一个支队交纳罚款。

接受交通违法处理地点及处理时间：当事人可以在每周一至周五8：00-12：00、14：00-17：30到以下地点接受处罚。

和平支队：和平区康定路35号增2号
河西支队：河西区洞庭路35号增1号
河东支队：河东区张贵庄路59号
河北支队：河北区王串场富强道7号
红桥支队：红桥区光荣道保康路红桥机动车检测线院内
南开支队:南开区雅安道13号
卫国道大队：河东区卫国道93号
南马路大队：南开区城厢中路899号 收起阅读 »

天气: 冷心情: 平静对桌的儿子拿来一只小什么什么熊
样子象只小小小的小老鼠
小小的眼睛亮亮的
小小的耳朵支棱着
小小的尾巴一点点
小小的两只前爪常常翘了起来东张西望一翻
或者缩在胸前让自己站成一个椭圆的球
然后慢慢低垂了小小的脑袋闭了眼缩成一个灰黑的乒乓球睡去
吃东西的时候也是用两只前爪捧着迅速地啃食
好象怕别人抢了去似的
吃完还会用小爪子洗洗小脸捋捋小胡子
每天就这样吃睡溜达溜达
看久了,忽然觉得他好孤单哦
没有伴说话,没有伴玩耍,过着一只熊的孤单日子
他有没有烦恼呢?有没有觉得寂寞?
也许,一只熊不孤单,想一只熊才孤单。。。 收起阅读 »

愿你早日搞定所谓的定置管理图

版权属于作者

The Politics Of Accelerated Stress Testing

Edmond L. Kyser, Eugene R. Hnatek, and Mark H. RoettgeringCompaq Computer CorporationEnterprise Computing Group - Tandem Business UnitCupertino, California


BIOGRAPHIES
Edmond L. Kyser is Principal Member of the Technical Staff for the Tandem Division of Compaq, where he has technical responsibility for Accelerated Stress Testing. He holds eight US patents and has published 12 articles, nine on Accelerated Stress Testing. His Ph.D. is from UC Berkeley in Applied Mechanics.
Eugene R. Hnatek is director of the Tandem Product Evaluation Center where he is involved in complete hardware product assurance activities from early design through first customer ship. In this regard, he is intimately involved with HALT and ESS processes. Prior to this assignment he was component Engineering Manager at Tandem. He is a recognized authority on integrated circuit quality and reliability having published 11 books on the topic.
Mark H. Roettgering is a Senior Member of the Technical Staff for the Tandem Division of Compaq, where he serves as a program manager and as an internal consultant on strategic and operational issues. Prior to this assignment, he worked on fault-tolerant system design and hardware quality assurance at Tandem. Mark holds a B.S. in Electrical Engineering from UC Davis and an M.S. in Engineering Economic Systems & Operations Research from Stanford.
ABSTRACTThe technical literature and various technical conferences delve into the myriad details of the ESS process, the ESS profiles to be used for testing, the required equipment characteristics, etc. Most everything that can be written about the virtues of ESS and the inherent technical details has been written.
We contend that it is not the technical aspects of ESS that dominate decision-making: The real issues, for most companies, are of a political nature. ESS implementations become political when the functional organizations that bear the short-term costs of ESS do not get credit for the long-term benefits. Various factions within most large corporations rise to the surface to question processes like ESS from a self-serving viewpoint. Justifying the need for continuing with ESS eats up a lot of time in meetings, evaluating databases and developing position presentations. In this paper we discuss these commonly encountered political issues, provide a process for resolution of these issues, and conclude with recommendations for corporate ESS management. KEYWORDSEnvironmental Stress Screen (ESS), Net Present Value, Uncertainty, Decision-Making.
BACKGROUNDToday’s fast time to market and concern with low price may be taking our focus off quality and reliability. Frank Burge of Electronic Engineering Times in his September 27, 1999 editorial put it this way. “In a world where price is king, are we painting ourselves into a corner—a corner where design quality gives way to price or time, eliminating steps in the design verification/test process or choosing suppliers strictly on price? Are we back to making the numbers at any cost?”
Figure 1: Product Flow for AST Programs
The decision whether or not to perform ESS on a specific product is a typical example of the quality vs. cost problem with which many companies struggle, including our own. One of the problems in being able to make a decision based on data is the fact that very little real data (whether from current or equivalent products) is available to determine the value of ESS. Typically at stake are millions of dollars in investment capital, thousands of square feet of manufacturing floor space, tens of person years, and the reputation for quality and possibly the profitability of the corporation. A typical product flow diagram for Accelerated Stress Test (AST) processes is shown in Figure 1. Many separate stakeholders of the corporation are involved in this complex process, the core of which is manufacturing ESS: Product Development, Manufacturing, Field Service, Engineering Services, Sustaining Engineering and Information Services. Figure 2 illustrates a common hierarchy of these groups, each of which typically has its own agenda and point of view. Traditional guidelines, established product requirements documents, and


Figure 2: Generic Corporate Reporting Structure
standard procedures may not be sufficient or appropriate. Benchmarking is difficult. Evangelizers for specific approaches to increasing reliability are quick to offer their services and opinions, often at loggerheads with one another. Industry standards are rare and often ambiguous. Perhaps most significantly, the benefits (and the associated costs) realized from the program do not accrue proportionately to the functional units that bear the costs.
The goal of an ongoing AST program, such as implementation of manufacturing ESS, is to make cost effective improvements in the field reliability of the hardware being tested. Figure 3 shows a normalized field failure distribution for five recent Tandem products, all of which undergo 100% manufacturing ESS.
Figure 3: Field Data - Part Replacement Rate

Figure 4a: ESS Support
Figure 4b: ESS Opposition



All of the products represented in Figure 3 show the same pattern of a high initial return rate that decreases more or less asymptotically to a stable return rate in about two years. This is a classic characteristic of products that are most likely to benefit from an ESS program.

SURVEY OF ATTITUDES ON ESSDuring a recent IEEE workshop on Accelerated Stress Testing, we conducted a survey of attitudes towards AST to determine if there was a ‘common experience’ among industry practitioners that could be leveraged as the science evolves. The issue was defined as “Within your company, where do you see support for or opposition to ESS, and why?” The organizational results are summarized in Figures 4a and 4b. The respondents’ reasons behind the support and opposition are shown in the Tables 1a and 1b.

As the comments in the tables indicate, many of the reasons given are similar and can therefore be combined. The resulting ‘grouped’ categories of opposition and support are shown in Tables 2a and 2b. In cases where the reasons appeared to be ambiguous, require other processes to be considered, or deal with educational or organizational issues, the category ‘out of scope’ was used. ‘Out of scope’ does not imply that the reasons are invalid, just that they will not be addressed in detail in this paper.






Table 1a: Reasons for Supporting ESS


key

#

Stated Reason

Comments


a

11

Increased reliability / quality

Hard to measure - hard to quantify benefits - compare to n


b

9

Sales advantage / customer satisfaction

Same as a, but more difficult to quantify


c

6

Reduce field service costs

Equivalent to a


d

4

Reduce DOA / Early life fails

Equivalent to a


e

3


Identify failure modesin-house

Benefits seen only by redesigning to avoid failure modes


f

2

Better Product

Equivalent to a


g

2

Reduced field returns

Equivalent to a


h

2

More efficient than run-in

Weibull analysis can help determine this


i

1

Identify process failures

Equivalent to a + e


j

1

Improve yields
Equivalent to e






Table 1b: Reasons for Opposing ESS


key

#

Stated Reason

Comments


k

12

Additional cost

Virtually all opposition is cost based - Easier to measure than benefits


l

10

Outside of Component specs, design limits

Equivalent to n


m

5

Additional WIP Time

Additional step assumes all else equal - part of k


n

5

Decreases manufacturing yields

Easy to measure, easy to quantify. Compare to a


o

5


Afraid of damaging good product

See comments on a - effect on reliability is uncertain


p

3

Seen as critical of known good process

‘Known good’ implies improved reliability is of no benefit or screen is no good


q

2

Don’t understand process

Education issue


r

2

Difficult test to run / diagnose failures

Part of k + t


s

1

Additional handling problem

Equivalent to k + m


t

1

Repair costs
Part of k, s


u

1
run-in more efficient
See h


v

1
Doesn’t believe in benefits
See a

As Tables 2a and 2b indicate, we are left with two potential sources of benefit, and a large bucket containing severalcost factors: additional time, reduced manufacturing yields, test costs, and repair costs. The fear of product damage will be handled explicitly as part of the question of improved reliability.





Table 2a: Revised Reasons for ESS Support (Benefits)


key

#

Stated Reason

Comments


a

25

Increased reliability / quality

Hard to measure - hard to quantify benefits - compare to n


b

9

Sales advantage / customer satisfaction

Same as a, but more difficult to quantify


*

7

Out of scope






Table 2b: Revised Reasons for ESS Opposition (Costs)


key

#

Stated Reason

Comments


k

19

Additional cost

Virtually all opposition is cost based - Easier to measure than benefits


m

15

Decreases manufacturing yields

Easy to measure, easy to quantify. Compare to a


n

5

Additional Time

Additional step assumes all else equal - part of k


o

5
Afraid of product damage
See comments on a - effect on reliability is uncertain


*

4
Out of scope



The survey results we have been discussing represent the opinions of 32 individuals from 22 corporations active in ESS. One of the most striking results is that the same issues, or organizations, appear in BOTH the positive and negative columns. Obviously, there are strong differences of opinion, and a lack of mutually acceptable (accurate and meaningful) data on which to base decisions. This is equivalent to stating that there is a high degree of uncertainty about many important aspects of a manufacturing ESS program. Without a structured methodology in place to address this uncertainty, a common ground within the corporation may never be found.

We maintain that what is needed is a common metric of success that accommodates all of the above ‘reasons’ – since all are valid in the opinion holder’s frame of reference. How is one to ‘net out’ all the above positives and negatives? The problem can be formulated as follows:





We propose that the metric of success is the dollar, and the method of ‘netting out’ the positives and negatives is to discount all cash flows to net present value and calculate a net present cost. Rather than taking a ‘best guess’ at exact amounts of the costs and benefits, all uncertainty should be explicitly stated so that conflicting opinions about possible outcomes can be addressed simultaneously. This process is detailed in the following section. DECISION MODELA review of the pluses and minuses of ESS raised by the practicing community quickly reveals the major source of organizational problems that arise in an ESS implementation. The majority of the costs are easily identified and can be quantified with a high degree of accuracy. The manufacturing organization bears essentially all costs - using many common manufacturing metrics (end-to-end yield, inventory turns, WIP days, etc.) ESS is a negative. On the other hand, the benefits, while identifiable, possess the following characteristics. They are highly uncertain, difficult to quantify with any degree of accuracy, difficult to measure, require an explicit value statement by management, and are not immediately realized. The benefits are realized by the corporation as a whole, essentially through downstream cost-avoidance (lower field service and warranty costs) and through increased sales (product reputation).
It can be said that the problem with ESS acceptance is that it is high in both organizational and technical complexity. Technical complexity arises from the large number of strategic and operational decisions and processes that need to be in place for an ESS program to function in an efficient manner. Organizational complexity is inherent when...


Costs and benefits are realized by different groups.
Uncertainty allows a variety of advocates and opponents to champion opinions without fear of refutation by data.
There is a lack of strong cross-functional leadership from management.
Unfortunately, management attempts to solve problems of this nature by attacking the “people problem” first, through team-building, facilitation, consensus-building, etc. Despite these well-intentioned tactics, the underlying technical complexity invariably remains, and with it, the conflict. What is needed is a framework in which to solve the technical complexity first. Through creating a technically accurate and compelling business model, organizational disagreements can be addressed in a methodical and rigorous manner. Arguments like “Doesn’t believe the benefits” can be addressed by explicitly addressing which parts of the model are inconsistent with the beliefs of the opponent. Consequently, if the model is agreed to, and the inputs are agreed to, the resulting ‘netted-out’ cost or benefit of ESS should stand on its own, leaving nebulous and ambiguous arguments without legs.
We propose a normative decision model as the best method for solving the technical complexities of ESS. In this framework, we must first clearly identify what exactly we are modeling. Stated here: “What is the net present value of all future product costs for a unit which is to undergo ESS subtracted from the net present value of all future product costs for a unit which will not undergo ESS?” We call this quantity Net Present Savings or NPS.

The NPS we compute is a marginal savings on a per-unit basis. This eliminates the requirement to consider facility and capacity issues. We also assume that all other manufacturing processes remain the same: we do not explicitly consider the potential benefit of reduced run-in times here, although the framework allows for it. One last assumption is that we are discussing a particular ESS screen for a particular product: the selection or modification of screen parameters to maximize NPS is not performed here, although we have used the methodology to do parameter optimization at Tandem/Compaq. The model and theoretical results discussed in the following analysis were built using Analytica® analysis software from Lumina Decision Systems.


The influence diagram of Figure 5 illustrates the factors that have been included in our model. Based on the factors identified in the ESS survey, we will model seven uncertain – or random – variables (single ovals), and



Figure 5: Influence Diagram





Table 3: Model Variables and their Descrīptions


Key

Variable Name

Units

Comments

Value


A
Cost of Inventory
%/week
Includes Depreciation and liquidity effects
Lognormal(0.5, 1.5)


B
Test Failure Repair Cost
NP$
Material and Labor costs for debug and repair
Lognormal(1500, 1.5)


C
Time to Repair Test Failure
Weeks
WIP time
Lognormal(6, 1.5)


D
Replacement Cost of Field Failure
Future$
Material and Labor (warranty costs)
Lognormal(H/2, 1.25)


E
MTBF of Unscreened Unit
Years
Mean Time Before Failure
Lognormal(5, 1.5)


F
Impact of ESS on MTBF
%
Factor by which ESS improves unit MTBF
Normal(20%, 15%)


G
Operational Costs
NP$
Variable cost only (no fixed costs)
Lognormal(50, 1.5)


H
Whole Product Cost
NP$
Used to calculate inventory, depreciation, and replacement costs
5000


J
ESS Yield
-
Probability of passing ESS screen
90%


K
IBP for Field Failure
Future$

2000


M
Cost of Capital
%/year
Time vs. money discount rate
15%


N
Cost of Test Failures
NP$
Total cost of fail, debug, repair cycle
((1/J)-1)(B+H(((1+A)^C)-1))


P
Total Field Failure Cost
Future$
Includes direct and indirect costs
D+K


R
MTBF of Screened Unit
Years
See E.
E(1+F)


T
Total Cost
NP$
Total additional cost of ESS
N+G(1/J)


W
Total Benefit
NP$
Total downstream benefit per unit derived from ESS
(P/(1+M)^R)-(P/(1+M)^E


X
NPS
NP$
Per Unit Net Present Savings
W-T

NP$ is Net Present Dollars. Future$ is dollars not discounted to present value.Lognormal(x, y) is a distribution with mean x, and geometric standard deviation y. The range [x/y, x*y] contains about 68% of the probability mass.

four constant variables (trapezoids). Double ovals indicate deterministic variables (those that are known exactly once the inputs are known). A summary of the model variables is given in Table 3. Values are representative of our experience with a broad range of CPU products.

We use the lognormal distribution to express the uncertainty in almost all random variables included in this model. The lognormal has a sharp lower bound of zero and is positively skewed. For most cost and time parameters, these characteristics are highly desirable.

‘Field Failure Cost’ is one of the more difficult parameters in the model for most corporations to assess. We have broken it into two parts based on the results of the conference survey discussed above: Replacement cost, or warranty cost, and reputation cost. Replacement cost can be assessed directly through careful consideration of all contributing costs, but reputation cost (re-buy, word-of-mouth, etc.) may best be derived by discussing the Indifferent Buying Price (IBP) of a field failure. Suppose there were a wizard who was able to perform the following feat: Moments before a field failure is about to occur, the wizard calls the CEO of your company and offers to allow you to secretly swap out the failing unit before the failure takes place – for a price.

The CEO’s IBP for the field failure is the price at which she is indifferent between paying the wizard or not: the CEO would pay any lower price (in addition to the replacement cost), but would refuse to pay any more. Although IBP for field failures may be different for the same product depending on customer and application differences, a well thought out value for the IBP will be equivalent to the ‘reputation cost’ of a failure. Both replacement and reputation costs are valued at the time in the future at which the failure takes place.
With this groundwork in place, our model simply computes the ‘Total Benefit’ per unit for performing ESS as the difference between the present value of the total failure cost of a screened unit vs. an unscreened one.

Figure 6 displays the results of the model discussed above. The expected value of NPS is $180/unit: a good return on a $50 test. The cumulative distribution of NPS contains much more information, however. Indeed there is a 30% chance that this generic ESS program will lose money on a per unit basis. On the other hand, there is just as likely a chance that a net benefit of more than $325 per unit will be realized.



Figure 6: Probabilistic Model Output

Figure 7: Sensitivity of NPS to Variations in Screen Yield

Figure 8: Sensitivity of NPS to Yield and IBP

Any dispute with the conclusion that the hypothetical ESS program represented by this model and corresponding parameters is a ‘good bet’, should be stated in the context of the model or its parameters rather than with more abstract terms. A ‘good bet’ is a deal with an uncertain but positive expected outcome. By encoding differing points of view in the form of parametric uncertainty, and incorporating all stakeholders concerns into the model structure, discussions are moved from the political realm into the technical one.

Although this is a generic example, it is useful to demonstrate how insights may be gained through further analysis. One such analysis may be to address the following concern: “What if the screen yield required to achieve a 20% improvement in MTBF is either higher or lower than 90%?”Figure 7 shows the mean (average, or expected, value) NPS as a function of screen yield. As can be seen, any screen parameter set with a yield higher than 83% would be considered valuable. Similarly, the effect of IBP on the value of our generic ESS program can be investigated graphically in Figure 8. For a yield of 90%, the program would still have a mean value of $60 per unit even if the reputation cost (IBP) of a failure were valued at $0.

Finally, it is enlightening to examine the degree to which the uncertainty in the input variables contributes to the variation in the output variable, NPS. Table 4 lists the absolute rank-order correlation between NPS and the listed uncertain inputs. This analysis indicates that (as expected) the greatest opportunity to reduce uncertainty in the value of this hypothetical ESS program is to refine the ‘Impact of ESS on MTBF’ estimate.

Conversely, expenditures of effort on refining any of the bottom four variables in the table will do little to reduce the uncertainty in the estimate of per unit NPS.





Table 4: Input Variable Importance


Variable

Importance

Impact of ESS on MTBF
0.871

Replacement Cost of Field Failure
0.337

Test Failure Repair Cost
0.211

MTBF of Unscreened Unit
0.086

Time to Repair Test Failure
0.040

Operational Costs
0.013

Cost of Inventory
0.001
DATAWhen an ESS program is initiated, there must be decisions made in the face of many uncertainties. As the program progresses, real data becomes available, and the initial probability estimates can be replaced by real numbers. In this section, we show some of the manufacturing and field data collected at Tandem division of Compaq relating to our ESS program, and answer some of the issues raised earlier.

One roadblock to ESS is usually stated as follows: “We can’t afford the yield loss in manufacturing caused by ESS”. Translation: “We need to ship every unit we build in order to make our revenue target. We can’t worry about reliability at this point. ESS yields cost us money, both in shippable units (lost revenue) and reworked or scrapped PWAs”. Let’s look at two examples of the yield of CPU PWAs subjected to manufacturing ESS. Figure 9 is a composite bar chart showing combined manufacturing ESS yields for five different CPU products. Note that the ESS yield remains essentially constant. As process and component problems were solved, new problems emerged and were addressed. In this case, given the complexity of the products, 100% ESS was

Figure 9: PWA ESS Yields

Figure 10: Manufacturing Yield by PWA type for 3Q97

required for the entire life of each product. Figure 10 shows a breakout detail of the products included in last bar of Figure 9, and adds Post-ESS yields for each of the five. This chart shows the value of conducting ESS in production and the potential impact of loss in system test or the field if ESS was not conducted. Notice the high ESS yield of mature PWAs (PWAs #1-#3) but the low ESS yield of new boards (PWAs #4 and #5). The benefit of ESS for new products is evident here. Note particularly that the Post-ESS yields for both mature and immature products are equivalent, indicating that ESS is finding the latent defects. Nonetheless, the value of ESS must be constantly evaluated. At some point in time when yield is stable and high, it may make sense to discontinue its use for that PWA/product.

The ideal data set would allow the creation of a ‘failure rate vs. time’ plot, or hazard function, for a split population of screened and unscreened product. Unfortunately, this type of data is never available until several months or even years have elapsed. Figure 11 displays one real-world example. It took careful data mining of over five years of run-time and of more than 2000 total field installations to produce this information for a Compaq CPU server product. If this data were known ahead of time, ESS implementation decisions would have been simple: Screen yields would be known (92%), and so would the effect of the screen on the MTBF of shipped product (14%). Assuming all other model parameters discussed earlier apply to the product producing this field data, the cumulative distribution in Figure 12 reflects the value of its ESS program. The expected value is $110, with only a 20% chance of being negative.

Figure 11: Failure Rate vs. Time for Split Population

Figure 12: Calculated NPS using Value Model and Field Data

The amazing thing about this field data when applied back into the model is that our screening decision and our expected value remain virtually the same. The main benefit we gained through the gathering of field data is that our uncertainty about the true vale of NPS has been reduced. The 10%-90% range has shrunk from [-260, 650] to [-20, 260]. Considering that five years after data gathering began, the product is long past end-of-life. The reason a structured framework for dealing with this uncertainty about the future is so valuable is that it allows corporations to make the best decision possible – at the time the decision needs to be made. CONCLUSIONSDecisions relating to Environmental Stress Screening involve political aspects within a corporation to far greater a degree than almost any other manufacturing process. A correct decision on whether to perform ESS or not on a particular product requires a measure of success (metric) that is acceptable to all of the different corporate stakeholders. We suggest that Net Present Value of all associated costs and benefits is the metric of choice.

In addition to a robust cost-benefit model, the nature of ESS requires that there be a strong ‘company champion’ for ESS at a high level who can adjudicate the inevitable disagreements, focus on corporate goals, and provide direction for the discipline. However, the champion needs to remember that the goal of ESS is not “reliability at any price”, but rather “reliability at the right price”.

Finally, since ESS decisions assisted by a model of NPS will be based on probabilities estimated before actual data exists, yield and failure data must be obtained to verify the initial probabilistic estimates. The resulting data should be used to improve screening de 收起阅读 »

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转帖] Economic Justification of Halt Tests

Economic Justification of Halt Tests: The relationship between operating margin, test costs, and the cost of field returns Edmond L. Kyser and Nahum Meadowsong Cisco Systems, Inc.Email: ekyser#cisco.com nameadow#cisco.com
Introduction


Increasing pressures for cost reduction

Prototype build is a leading cost item in product development

Halt test requires destruction of (at least) one prototype at a critical stage (earliest stable hardware and software)

How is this cost best justified?

The benefit of a Halt test is AVOIDED COST –


Improved reliability (reduced RMA rate)

Reduced test cost (eliminate/reduce ORT, RDT)

What is the relationship between Halt results (operating margin) and RMA rate?

Under what conditions is the cost of Halt justified?

Operating Margin vs. ReliabilityCan Halt tests be used to predict field performance?



No !A Halt test is NOT a highly accelerated life test – it’s not a life test at all. There is no appropriate acceleration algorithm, no acceleration factor. The deliverables of a Halt test are operating margin and failure modes.

Yes !Operating margin is an indicator of field performance. Low margins indicate poor performance (short life), and high margins indicate good performance (long life). Halt tests determine operating margin, and failure modes show where margins may be improved.


The issue of relating Halt results (operating margin) to field reliability is NOT a yes/no issue, but rather how to express the relationship correctly.


It will be an Empirical relationship

It will not be independent (There will be other variables)

It will be probabilistic in nature - confidence interval

It will be product dependent

The following plot shows an Empirical relationship between Operating margin and Reliability for similar products (high performance line cards for Cisco routers)



Other Independent variables influence RMA rate:

Board complexity, measured by active component count-Includes ASIC, IC, FPGA, Transistors, Crystals, Diodes

The following plot shows Normalized RMA rate vs. parts count, FOR A LARGER RANGE OF PRODUCT.
The correlation is about 1/10 that of Normalized RMA vs Operating Margin for Line Cards

Cost justification 1: Eliminate RDT

The following 2 slides show traditional RDT and Halt RDT
Traditional RDT (80% confidence in MTBF > 75,000 hours) The dashed blue line shows RDT requires 40 boards tested for 10 weeks. (assuming 1 fail and Arrhenius acceleration due to 50C temp)
Halt RDT requires 1 board for 1 week. The dashed blue line shows 80% confidence for Operating margin of 30C indicating Normalized RMA rate below 0.55
Standard RDT

80% CONFIDENCE LEVEL

Cost Justification 2: Improve Reliability

From slide 6, if the operating margin is increased N °C , the normalized RMA rate is reduced 0.0192N
Each RMA costs approximately WPC$, where WPC is the cost of producing the board, the Whole Product Cost.
Thus the Benefit of a Halt test that increases Operating Margin N °C is
The benefit of a Halt testBenefit = (# of RMAs prevented) (cost of an RMA)= N(0.0192)(RMA intercept)(Pvol)(WPC)$WherePvol is the (annual) production volume
The cost of a Halt test Cost = WPC + Esalary + DEP + CON + CA
WhereEsalary = fully burdened weekly salaryDEP = Weekly Depreciation of equipmentCON = Consumable costsCA = Corrective action costs
The break-even point is where costs = benefits.
For a Halt test to be cost effective, it must, on average, increase the operating Margin N °C, where




N =

WPC + Esalary + DEP + CON + CA




(0.0192)(RMA intercept)(Pvol)(WPC)$ 收起阅读 »

The Next Generation of Environmental Testing

by William Lagattolla, Trace Laboratories-Central
HALT and HASS are starting to supplant traditional vibration and thermal testing to meet today’s quality targets.
For decades, product quality has been determined through environmental testing such as vibration, thermal cycling, mechanical shock, and thermal shock. More recently, there has been a significant trend in the marketplace to improve product quality even further.
The Need for Increased Product QualityOne of the most pervasive trends across a wide range of the consumer, industrial, and military markets is the need for increased product quality. In consumer markets, a high rate of product failure can result in the manufacturer’s loss of credibility with an attendant loss of sales, from which it can take years to recover. In industrial markets, a high failure rate can result in expensive field service calls or—potentially worse—significant downtime. In military markets, product failures can translate in the loss of lives.
Although the need for quality is increasing, certain developments are making it more difficult to maintain existing quality levels. The most challenging development has been the increased use of manufacturing subcontractors. The manufacturer whose name goes on a product is likely to be relying on an outside resource, a subcontractor, over which the manufacturer does not have direct control.
This subcontractor is relying on a number of vendors, further weakening the control that the manufacturer has on product quality. Should a product fail, the customer will blame the manufacturer—the one responsible for its quality level.
Another challenge to maintaining quality is a continually decreasing number of engineers with comprehensive QA/QC backgrounds at these manufacturing companies. Many of the highly experienced QA/QC engineers are retiring or being replaced by younger engineers who are far less experienced.
Traditional Vibration and Temperature TestingTraditional vibration and temperature testing has played an important role in the genesis of today’s reliable and sophisticated electronic and electromechanical products. The core philosophy of this testing method is to define a set of specifications, usually minimum or maximum temperatures and vibration levels, and conduct the tests by changing only one variable at a time. Vibration testing is performed one axis at a time. If the device still is functional after being tested according to the test specs, it is considered to have passed.
A passing result is a positive outcome. However, a pass result does not help identify the weakest link in the product. In other words, the traditional test cannot help the engineer make the product any more robust.
Furthermore, with the one-at-a-time change in environmental variables and the one-dimension vibration testing, the test specs are not similar to real-world operating environments. As a result, this kind of testing does not provide an accurate indication of how the product might perform in the field.
This critical look at traditional environmental testing is not intended to be a blanket condemnation of that process. After all, this kind of testing has played a key role in the evolution of today’s highly reliable products. Instead, this examination of certain weaknesses in classical environmental testing can be helpful in understanding how new testing methods, in particular HALT and HASS testing, can lead to even greater levels of product quality and reliability.
The Strengths of HALT and HASS Highly Accelerated Life Testing HALT exposes the product to a step-by-step cycling of environmental variables such as temperature, shock, and vibration. It involves simultaneous vibration testing in all three axes using a random mix of frequencies. Finally, HALT can include combinations of multiple environmental variables; for example, temperature cycling plus vibration testing.
Unlike conventional testing, the goal of HALT is to break the product. When the product fails, the weakest link is identified so engineers know exactly what needs to be done to improve product quality.
After a product has failed, weak components are upgraded or reinforced. The revised product then is subjected to another round of HALT, with the range of temperature, vibration, or shock further increased so the product fails again. This identifies the next weakest link.





Figure 1. Headlights, Front, On
By going through several iterations like this, the product can be made quite robust. With this informed approach, only the weak spots are identified for improvement. This type of testing provides so much information about the construction and performance of a product that it can be quite helpful for newer engineers assigned to a product with which they are not completely familiar.
HALT must be performed during the design phase of a product to make sure the basic design is reliable. But it is important to note that the units being tested are likely to be handmade engineering prototypes. At Trace, we have found that HALT also should be performed on actual production units to ensure that the transition from engineering design to production has not resulted in a loss of product quality or robustness.
Some engineers may consider this approach as scientifically reasonable but financially unrealistic. However, our customers have repeatedly found that the cost of HALT is much less than the cost of field failures, service calls, blanket recalls, and loss of credibility or business due to poor product quality. One of our clients even includes HALT as a line item on its bill of materials to make sure this testing is included in the product cost right from the beginning.

Highly Accelerated Stress Screening HASS, an abbreviated form of HALT, is an ongoing screening test performed on regular production units. Here, the idea is not to damage the product but rather to verify that actual production units continue to operate properly when subjected to the cycling of environmental variables used during the HASS test. The limits used in HASS testing are based on a skilled interpretation of the HALT parameters but do not exceed a product’s operating limits.
The importance of HASS testing can be appreciated when you consider today’s typical manufacturing scenario. Circuit boards are purchased from a vendor who uses materials purchased from other vendors. Components and subassemblies are obtained from manufacturers all over the world.
Often, the final assembly of the product is performed by a subcontractor. This means that the quality of the final product is a function of the quality or lack thereof of all the components, materials, and processes that are a part of that final product. These components, materials, and processes can and do change over time, affecting the quality and reliability of the final product. The best way to ensure that production units continue to meet reliability objectives is through HASS testing.
Case HistoriesThe benefits of HALT/HASS testing can be seen in two case histories.

Automotive Lamp Assembly A manufacturer of automotive lamp assemblies (headlight, brake light, and third brake light units) provides an example of the benefits of using HALT/HASS throughout the development of a new product.
An engineer at this company decided to submit a production sample for an abbreviated suite of HALT. The unit failed, and it was redesigned. When submitted for a retest, a full HALT was performed, with the power to the bulbs in the assemblies cycled on and off during the testing process. During HALT, temperatures were varied over the range of -100°C to +85°C, with vibration parameters of 0 to 50g rms (Figure 1).
Special fixtures were made to hold the assemblies at the exact same angle and under the exact conditions they would experience when installed in a car. The manufacturer was careful to test actual production units to ensure that the test results were an accurate reflection of product quality.
Automakers have been champions of sophisticated quality testing for years. When they saw the test setup and the test results from this lamp assembly manufacturer, the automakers were so impressed that they made the manufacturer a prime vendor for these assemblies and started requiring HALT from all their vendors.

Power Supply A manufacturer of custom power supplies used in telecom switching systems wanted to ensure reliability in the field, so the company contacted Trace Labs for HALT to verify and refine the basic design. After several iterations, the basic design was made reliable. The power supplies were HALT tested over the temperature range of -50°C to +130°C, with vibration levels ranging from 0 to 10g rms.
Next, the manufacturer developed the handmade units into production designs. We recommended the production units be HALT tested, but this recommendation was declined.
Unfortunately, when the first production units were placed in service, there were many failures. Eventually, some production units were brought into the lab, and a cursory examination revealed that the units had smaller heat sinks, the chassis were made of thinner metal, and the amount of structural bracing had been reduced compared to the original engineering design that had been subjected to HALT.
It turned out that in developing the design for production, the power supply manufacturer reacted to price pressure from its customer, reduced the cost of various aspects of the production design, and had inadvertently compromised the high reliability of the original design.
Now facing a serious field-failure problem, the manufacturer submitted actual production units for HALT. After five iterations, the design of the production units had been refined to provide good field reliability. Ironically, the cost of the redesigned production units was only 2% more than the amount specified in the original contract—a cost the customer was willing to pay.
However, damage had been done to the power supply vendor’s relationship with the customer. The customer next required 100% HASS testing of all power supplies from this manufacturer, and the manufacturer was not invited to submit quotes on subsequent RFQs. The entire problem could have been avoided if the manufacturer had been willing to spend the upfront costs for HALT on the original production units.
Fortunately, this story does have a happy ending. After three years of producing reliable power supplies, proven through HASS testing as well as successful field experience, the manufacturer once again is regarded as a primary vendor.
ConclusionClassic vibration and temperature testing definitely have helped improve product quality over the years, but today’s very high standards for product quality are requiring tests better able to reduce, or even eliminate, field failures.
HALT provides a controlled, repeatable method of determining product quality under conditions comparable to field operating conditions and is critical for proving the basic design of a product. HASS testing is a quick, effective screening process that can be used to ensure production units continue to meet quality standards.
While it is true that HALT and HASS testing can add to the short-term manufacturing cost of a product, the increment is surprisingly small in most cases. In the long run, the cost of the testing is much less than the cost of field failures or the loss of business due to reliability problems. 收起阅读 »

To be a good failure analyst one must also be a good manager. After all, failure analysis or problem solving is more than just brainstorming a solution to an identified problem. Successful analysis can only be achieved when a structured technique that uncovers the facts of the incident being investigated is used and adhered to at every step of the analysis process. As the manager or Principal Analyst for the failure your management skills will not only be put to the test but will be an integral part of the investigation.
Managing the Failure Definition
The first step in the analysis effort would be to clearly define what constitutes a failure. This may sound simple but I can assure you that it is not. Ask anyone and they will all tell you that they know what their failures are. Now explore a little deeper and you will find that they all know what’s breaking down but they care for a different reason. The fact is we all tend to care for a different reason and there are many factors that will directly affect the reason why we care thereby changing our failure definition. For example, consider a plant whose production levels are low and maintenance, downtime, and parts cost high. In this example the Operations Manager considers the low production levels to be the failure, while the Maintenance Manager considers the Mean Time Between Failure (MTBF) and Mean Time To Repair (MTTR) to be the failure. The Plant Manager considers the low bottom line to be the failure while the maintenance staff cares about the number of times that they must repair the equipment. What we have here is clearly a failure but a different failure definition at every level of the organization. Now add to the thought process by considering another factor that affects how we feel about the failure; i.e., the business environment. Low production levels in a non-sold out condition are not as big a problem as high maintenance cost. Conversely, in a sold out condition maintenance cost are not nearly as important as production levels and downtime. The job of the Principal Analyst is to recognize these factors and apply the necessary focusing tools (Impact – Effort Matrix, Decision by Pairs, Force Field Analysis, Failure Modes and Effects Analysis, etc.) to uncover those failures that represent the greatest amount of potential return or unrealized opportunity based on the right definition of failure for the facility.
Managing the Scope of the Analysis
Don’t bite off more than you can chew! The size and scope of the analysis you intend to tackle should not exceed the available resources for the analysis effort. Therefore, the scope of the analysis should be directly proportional to the resources available to conduct the analysis. Always remember that the bigger the scope the bigger the analysis. Process or system related-analyses tend to be the largest in size because of the many variables associated with the modes of failure. Whereas, single components tend to be the smallest due to the relatively few variables associated with a single item. The key is to determine what is really important and what you can reasonably manage. This is easily done if you have already determined the amount of opportunity by performing a Failure Modes and Effects Analysis (FMEA) and know the available resources on hand. Here the scope and the opportunity have already been identified. The goal is to eliminate failure and recover opportunity as quickly as possible by going after the biggest “bang for the buck”. In essence, limit the scope of the analysis at an early stage and get a payback as soon as possible. By doing so it becomes easier to dedicate resources for those analyses that are larger in scope and therefore more time consuming to resolve. Although the analysis with the largest scope may have the greatest potential return it is not always the best analysis to go after first. Managing the scope of the analysis is important when you realize that an incomplete effort is worse than a smaller completed problem resolution. In effect, don’t go after world hunger on your first attempt, although an attractive opportunity, it may be a bit more than you can chew with the available resources at hand.
Managing the Failure Data
One of the most challenging aspects of any failure analysis effort is the management of the data necessary to solve the failure. Failure data provides the key that unlocks the mystery when problem solving. What the data tells you are the facts of the failure. Therefore, the management of failure data is vital to the successful outcome of the analysis.
It is not enough to merely set down and identify the data necessary to find the root cause(s) of failure, but to develop and implement a data collection strategy that ensures that the integrity of the failure data is maintained. Not just identifying the person responsible for data collection, but how they are going to obtain the data and what they are going to do with it once it has been collected. Think of it like a police investigation. The forensic strategy is handled in such a manner as to ensure that all the evidence is collected and stored until needed. Pictures are taken, evidence is bagged and tagged for use in the investigation and in court, all the witnesses are interviewed and their statements recorded, locations and times are noted to determine all the positional information, etc. The collection of failure data should receive exactly the same type of stringent detail as the evidence collected at any crime scene.
Managing the Analysis Team
Managing the analysis team consists of more than just managing the people. This includes making sure you have the right team, not only in size but also in makeup. A common mistake made by most organizations is to form an ad hoc committee comprised entirely of subject matter experts (led by the most senior or experienced of the experts) to solve the egregious effects of the incident being investigated. The results tend to be pre-tailored solutions for the specific problem based on the expertise of the team. Make no mistake about it; although subject matter experts are absolutely necessary to solve the failure, to make sure all the possibilities are covered individuals that have little or no knowledge of the failure being investigated should compliment them. Non subject matter experts bring the element of questioning to the table. When they ask a question such as “can this happen or occur?” the subject matter experts then must think about the possibility and answer yes or no to the question. The problem with a team comprised solely of subject matter experts is that they often overlook possibilities due to their interment knowledge of the failure. They believe that they already know why the failure is occurring and want to follow that path to uncover root cause(s). Non subject matter experts want to explore all the possibilities because they have no pre-conceived notions.
It is not necessary for the Principal Analyst to be a subject matter expert in the failure. Quite to the contrary as this is often a detriment to the analysis effort because he also will have developed pre-conceived notions as to why the failure is occurring. What the Principal Analyst needs to be an expert in is the science of Problem Solving or Failure Analysis.
The perfect analysis team is usually made up of 5 to 7 cross-functional people who have a common goal and commitment to solving the failure under investigation. Proper management of the team involves not only the selection of the right people, but also the correct assignment of individuals involved. Each must have clearly defined roles and duties based on their unique strengths and weaknesses. For example, every team needs a critic to keep the team honest. Fortunately every organization seems to have an abundance of people with this characteristic. The job of the Principal Analyst is to make sure this individual is critical but not to the point of disruption.
Managing the Analysis Effort
The first step in managing the actual analysis effort is to determine what you expect from the final outcome. This can be easily accomplished by developing a charter that clearly delineates the terminal objective of the analysis. This is further enhanced through the development of critical success factors that will tell you whether or not the terminal objective has been obtained. For example, if you are solving a problem involving an administrative issue such as slow invoice processing your charter could be something like the following:
“Uncover the root causes of the recurring invoice processing problems. This includes identifying deficiencies in or lack of management systems. Appropriate recommendations for root causes will be communicated to management for rapid resolution.”
Examples of possible critical success factors could include the following:


Reduce invoice processing turnaround time from two weeks to one week.
No lost invoices.
No incorrect invoices.
Maintain an invoice tracking system that is 100% accurate.
By developing a good charter and critical success factors for the analysis the team has a common goal and focusing mechanism to keep them on track and stop them from straying off on tangents.When failure analysis begins the goal of the Principal Analyst is to make sure that the logic is sound and that all hypotheses have been proven or disproved. Here it is good to understand that the Principal Analyst manages the analysis and is responsible for its successful outcome. He owns the process and the team owns the failure. Keeping this in mind, if the team can prove it to the Principal Analyst, then he can subsequently prove it to management.
Often during the logic tree development portion of the analysis team members will disagree and some conflict will result. This conflict is not necessarily a bad thing. With conflict comes valuable discussion. As long as the conversation is pertinent to the analysis and provides benefit it should be allowed to continue. The trick is to keep this conflict from becoming confrontational and therefore detrimental to the analysis. One management technique used to maintain control during the analysis is for the Principal Analyst to ask questions that will help to clarify points. Questioning not only minimizes the amount of conflict between the team members it also keeps the team focused. This is especially important for those team members who are not subject matter experts in the failure under investigation.
Managing the Final Report
The final report is the alpha and omega of the failure. It represents the culmination of the analysis effort and the beginning of failure elimination. Remember that the goal of any failure analysis should be the elimination of identified causes. The final report is the tool used to obtain the resources necessary to implement solutions to the uncovered root cause(s) of the failure thereby achieving that goal. In essence, the final report can be thought of as a sales tool and should be developed with that in mind. At a minimum the final report should not only provide solutions with expected returns on investments but also identify how the failure occurred in the first place. To accomplish this an event summary, a descrīption of the failure mechanism and list of recommendations should be included in the report.
The event summary is nothing more than a brief descrīption of how the failure was first noticed, how long it has been going on and the method(s) used to isolate or mitigate the consequences of the failure.
The failure mechanism can be thought of as a summary of the root cause(s) that led to failure occurrence. It chronologically characterizes the things that must occur in order for the failure to manifest itself.
The list of recommendations should not only explain what, when and who is going to be responsible for implementation, it should also include a detailed cost benefit-ratio associated with each recommendation.
Summary
The success or failure of your problem solving efforts often depends on the management strategies used to conduct the analysis. A sound management strategy must be devised and put into place for every step in the Root Cause Analysis process in order for the analysis to be both effective and efficient.
Obviously collecting and maintaining the paperwork associated with the failure investigation can be a daunting task. For this reason the use of software that is designed specifically for this purpose is extremely beneficial and is highly recommended. Although there are several packages on the market RCI’s PROACT® is by far the best and most complete of the software packages designed for this purpose.
RCI’s PROACT® software not only makes this difficult job seem almost effort free, but also provides a mechanism that allows easy and ready access to all the pertinent data associated with the analysis, including the structured logic tree. Failure data is maintained in a database unique to the failure and can be sorted by type, person responsible for its collection, date required, etc.
Of equal importance to the analysis is keeping track of the verification techniques used for the hypotheses pertaining to how the failure occurred. PROACT® automatically requires the completion of a verification log once a hypothesis is identified. This log can then be retrieved at any time to determine how to proceed with the analysis. In addition, PROACT® has many features that help the analyst do his job. It will help you to determine what your critical success factors are for the analysis, write a report on the analysis, communicate your findings to management, and track the results of your analysis efforts, just to name a few.
As a failure analyst I find that PROACT® is an invaluable tool for doing my job. My analysis efforts are not only easily managed, but are much quicker than ever before. 收起阅读 »

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