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口腔颌面外科杂志2021年4月第31卷第2期Journal o f Oral and Maxillofacial Surgery Vol.31 N o.2 April,2021•15!种植体颈部与唇侧骨板间距离对唇侧牙槽骨吸收及牙龈退缩的影响黄洁，王海丞，胡佳慧，周笑天，王佐林!上海牙组织修复与再生工程技术研究中心，同济大学口腔医学院，同济大学附属口腔医院口腔种植科，上海200012#[摘要]目的：探讨前牙美学区植入种植体的颈部与唇侧骨板间距离对种植体周软硬组织的影响。
方法：随机选取6只健康B eagle犬，在双侧上颌第一切牙处（共12个位点％行数字化外科导板辅助下的即刻种植和早期种植，并分为 4组，A组（早期种植1m m组），B组(早期种植2 m m组），C组（即刻种植1m m组），D组（即刻种植2 m m组）。
早期 种植不使用任何植骨材料，即刻种植在跳跃间隙内置入浓缩生长因子(concentrated growth factor, CGF)。
均米用埋入 式缝合，3个月后翻瓣行牙龈成形术，术后1个月处死B eagle犬。
比较各组唇侧牙骨（verticalbonere-sorption, V D)、水平骨吸收（horizontal bone resorption, H D)、唇侧骨板厚度（bone thickness, B T)、角化龈宽度（keratinized mucosa width, K W)、种植体-骨结合率 (bone-to-implant contact, BIC)。
结果:垂直骨吸收数值比较， A 组大于B 组，C组大于D组(！<0.05); 骨吸收数，A组B组，C组D组(！<0.05)。
种植体颈部1m m水平，A组的唇侧骨板大于B组。
种植体-骨结合率比较，A组和B组间的学意义（！>0.05)，C组大D组和A组（！<0.05)。
角化龈宽度比较，种植术后3个月，C组小于D组(！<0.05);在种植术4个月，A组小于B组(！<0.05)。
Optimized staircase profiles for diffractive optical devices made from absorbing materialsBernd Nöhammer,Christian David,and Jens GobrechtLaboratory for Micro-and Nanotechnology,Paul Scherrer Institut,CH-5232Villigen,SwitzerlandHans Peter HerzigInstitute of Microtechnology,University of Neuchâtel,CH-2000Neuchâtel,Switzerland We report on the optimization of staircase grating profiles for the case of absorbing grating inga simple numerical algorithm,we determined the grating parameters,maximizing the first-order diffractionefficiency for different numbers of staircase steps.The results show that there is a significant differencebetween the staircase profiles for nonnegligible and negligible absorption.The obtained solutions are ofimportance for diffractive optics in the soft-x-ray and extreme-ultraviolet ranges.Because of the progress in lithography and replicationtechniques that permit low-cost mass fabrication, diffractive optical elements(DOEs)have becomeimportant optical devices.1The most important andalso simplest form of DOE is gratings.There are also many other types of DOE that are generalized formsof gratings with a varying grating constant,such asFresnel zone plates or computer-generated holograms. Consequently the task of finding the optimum surfacerelief of a DOE can often be simplified to the problemof finding the optimum shape of a grating.In conventional optics the absorption of the gratingmaterial is usually negligible;therefore only the phase-shifting properties of the material(described by the real part of the refractive index)have to be taken intoaccount for this shape-optimization process.However,for wavelengths l in the extreme-ultraviolet(EUV)and x-ray ranges,where the refractive index n is conve-niently written as n͑l͒12d͑l͒1i b͑l͒,d and b areoften of the same order of magnitude;therefore absorp-tion(described by b)also has to be taken into accountfor the calculation of optimized grating profiles.A requirement for many applications is to diffract as much light as possible in a single(e.g.,the first)diffraction order.In the case in which absorption isnegligible,this is achieved by use of a blazed grating structure that has a sawtoothlike shape and a heighth c calculated from h cl͞j d j[Fig.1(A),dashed lines]. However,when absorption of the diffracting structures plays a role,the shape of the grating that gives maxi-mum first-order diffraction efficiency is quite different.Tatchyn et al.2have shown that in this general case the optimum profile is still sawtooth shaped and has the same slope as in the case of zero absorption[Fig.1(A), solid lines],but the structures are narrower,resulting in an open part b1.The size of the open fraction b1͞b depends on the ratio d͞b as indicated in Fig.1(B)and has to be calculated numerically.In practice,fabrication of a continuous sawtooth pro-file with the required accuracy is difficult.There-fore the ideal profile is often approximated by a stair-case profile(Fig.2).Such staircase profiles can be fabricated by use of several aligned lithography stepsand subsequent etching or deposition of the gratingmaterial.3For the case of staircase profiles optimized for neg-ligible absorption,the N distinct steps of the staircasehave equal width(w iw j;i,j1,...,N)and the heights,h i,of the steps follow the ideal profile for zeroabsorption,leading to h i͓͑i21͒͞N͔l͞j d j.Such pro-files give good results for optics in the visible spectral range,where absorption is normally negligible.Also, in the case of the first x-ray optics with staircase pro-files,which have been recently reported,4–6b was suf-ficiently small for the relevant photon energies in the hard-x-ray range.However,when considering optics in the EUV and soft-x-ray region,in most cases ab-sorption will play a role.In the current work we show how to optimize the design of a staircase profile to ob-tain maximum first-order diffraction efficiency for this case of nonnegligible absorption.In the EUV and soft-x-ray spectral ranges,thewavelength of the light is typically smallcomparedFig.1.(A)Design of a transmission grating maximizing the first-order diffraction efficiency in the case of absorbing grating material(solid lines)and in the case of negligible absorption(dashed lines).(B)Correlation between free de-sign parameter b1and the optical properties of the grating material(quantif ied by d͞b).Published in Optics Letters 28, issue 13, 1087-1089, 2003which should be used for any reference to this work1Fig.2.General form of a staircase profile enabling the optimization of the first-order diffraction efficiency.with the period b and the height of the gratings used;therefore in most cases a grating can be treated as a thin structure,and the thin-element approximation can be used (for a discussion of the validity of the thin-element approximation see,for example,Ref.1).In addition,d and b are typically very small;conse-quently ref lections at surfaces between different materials are negligible.With these approximations the diffraction efficiency h can be calculated with the aid of a Fourier analysis of the transmission function.For a discrete profile we get 1h ÉNX i 1f i É2,(1)wheref i exp ͑22p h i b ͞d ͒exp ͓2p i ͑h i 2x i ͔͒sin ͑p w i ͒͞p ,(2)and the normalized heights (h i ),widths (w i )andmiddle positions (x i )of the steps are denotedh i h i j d j ͞l ,w i w i ͞b ,x i x i ͞b .(3)Equation (1)is a sum of contributions from each step of the staircase profile shown in Fig.2.The first term in Eq.(2)describes the absorption within one step.The second term gives the phase of each contribution,originating from the material phase shift (h i )and the position of the step within the grating (x i ).The third term is obtained from the Fourier transform of a rect-angular function with width w i .The analytical treat-ment of the problem would be rather complex since the efficiency is a complicated sum over functions of all staircase parameters.Therefore we used a numerical approach,applying a local search algorithm 7to find the optimum values for the parameters in Eq.(3)with respect to diffraction efficiency.The principle of the algorithm is to make small,ran-dom,trial changes in the actual profile,where the change is allowed to take place only if the new profile (the new set of parameters h i ,w i ,and x i )has a higher diffraction efficiency than the previous one.By re-peating this step until a large number (n trial .100)of subsequent trial changes fails to improve the diffrac-tion efficiency,an optimum set of values of h i ,w i ,and x i will ultimately be reached.This kind of algorithm could fail because of the presence of local maxima and as a consequence would never yield reasonable results for the design parame-ters of the grating.However,the numerical resultsshow that the total number of maxima is rather small;therefore it is sufficient to repeat the whole algorithm a few (typically 20)times with different,randomly chosen starting parameters for the grating in order to obtain a parameter set that represents the global optimum with respect to diffraction efficiency.Figure 3shows the numerical results of using this algorithm in the case of a staircase profile with four levels.For low values of absorption (high values of d ͞b )we obtain the expected staircase profile,which has steps with equal width and normalized heights of 0,1͞4,1͞2,and 3͞4.When we go to higher values of absorption,the widths (as well as the heights)of the second and the third steps decrease and finally approach zero.The widths of the first and the fourth steps both increase,and for values of d ͞b near zero they both approach a value equal to half of the grating period b .Therefore in the limit of infinite absorption a conventional binary amplitude grating is obtained.These results for high values of absorption can be qualitatively understood because the staircase profile always has to provide an optimum approximation of the ideal profile in terms of diffraction efficiency.For the ideal grating in the case of strong absorption the main contributions to the diffraction efficiency come from regions of the grating with smallheight.Fig.3.Optimum normalized widths w i (A)and heights h i (B)of a four-step staircase profile as a function of d ͞b of the grating material.Fig.4.First-order diffraction efficiency of a four-step pro-file (solid curve)featuring optimal values for the heights and widths of the steps.In addition,the diffraction ef-ficiency of the ideal continuous profile (see Fig.1)and a four-step profile optimized for negligible absorption aredepicted.Fig.5.First-order diffraction efficiency for different opti-mized grating designs.Therefore it is important to get a good approximation of the region with zero height (provided by the first step with w 1ഠb 1)and a short region with small height at the beginning of the sawtooth (provided by the second and third steps,which therefore tend to have rather small widths and heights in the case of high absorption).In Fig.4the diffraction efficiency of a four-step pro-file with optimal values for h i ,w i ,and x i is depicted.In addition,the diffraction efficiency of the ideal con-tinuous profile and a four-step profile with the con-ventional design rule optimized for zero absorption are plotted for comparison.For high values of d ͞b thetwo different staircase profiles nearly have the same diffraction efficiency,whereas for values of d ͞b below 10a significant difference can be observed.There-fore the optimal design of the staircase profile has to be used in this case to guarantee maximum diffrac-tion efficiency (e.g.,for d 2the optimum four-step profile gives 22%diffraction efficiency in comparison with only 16%for a four-step profile optimized for zero absorption).When different step numbers N of the staircase profile are used,similar results are found.For high values of d ͞b (typically d ͞b .10)the anticipated profile optimized for zero absorption [w i w j and h i ͑i 21͒͞N ]is obtained.For the case of high absorption the staircase profile gives a good approxi-mation of the ideal continuous profile in regions with small or zero structure height and an inferior approximation in regions of large structure heights,as expected.Figure 5shows the first-order diffraction efficiencies of optimized profiles with different step numbers N .For small values of absorption a larger number N of steps leads to a strongly improved diffraction efficiency,whereas for strong absorption very little difference is found among all profiles.This is because,for all profiles,the normalized width of the region with zero height approaches 1͞2,going to small values of d ͞b .Consequently in the limit of infinite absorption all the staircase profiles will have the same optical properties as a binary amplitude grating.In summary,we have shown that material absorp-tion has to be taken into account for the optimization of gratings in the EUV and x-ray ranges.By use of a numerical local search algorithm we were able to calculate the optimum parameters for maximum first-order diffraction efficiency of gratings with staircase profiles.This work was funded by the Swiss National Sci-ence Foundation. B.N öhammer ’s e-mail address is **********************.References1.H.P.Herzig,ed.,Micro-optics (Taylor &Francis,Lon-don,1998).2.R.Tatchyn,P.L.Csonka,and I.Lindau,J.Opt.Soc.Am.72,1630–1639(1982).3.M.B.Stern,in Micro-optics ,H.P.Herzig,ed.(Taylor &Francis,London,1998),pp.53–86.4.E.Di Fabrizio,F.Romanato,M.Gentili,S.Cabrini,B.Kaulich,J.Susini,and R.Barrett,Nature 401,895–898(1999).5.W.Yun,i,A.A.Krasnoperova,E.Di Fabrizio,Z.Cai,F.Cerrina,Z.Chen,M.Gentili,and E.Gluskin,Rev.Sci.Instrum.70,3537–3541(1999).6.B.N öhammer,J.Hoszowska,H.P.Herzig,and C.David,presented at the X-Ray Microscopy Conference 2002,Grenoble,France,July 29–August 2,2002.7.E.Aarts and J.K.Lenstra,Local Search in Combinato-rial Optimization (Wiley,Chichester,U.K.,1997).。
.李雅普诺夫稳定性自动化专业英语词汇表公告记录成长的脚印,分享败绩、成功的智慧。
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) 日记总数： 47 品题数目： 42 访问次数： 15577 acceptance testing 验收测试 accumulated error积累误差 ac-dc-ac frequency converter 交-直-交变频器 ac(alternatingcurrent)electric drive交流电子传动 active attitude stabilization主动姿态稳定 actuator 驱动器,执行机构 adaline 线性适应元daptation layer适应层 adaptive telemeter system 适应遥测系统 adjoint operator 陪同算子 admissible error容许误差 aggregationmatrix结集矩阵ahp(analytic你好 erarchy process)条理分析法 amplifying element放大环节analog-digital conversion模数转换 ntenna pointing control接收天线指向控制anti-integral windup抗积分饱卷 aperiodic decomposition非周期分解 a posteriori estimate笱楣兰?approximate reasoning类似推理 a priori estimate 先验估计 articulated robot关节型机器人 assignment problem配置问题,分配问题 associative memory model遐想记忆模子 asymptotic stability渐进稳定性 attained pose drift现实位姿漂移 attitude acquisition姿态捕获aocs(attritude and orbit control system)姿态轨道控制系统 attitude angular velocity姿态角速度 attitude disturbance姿态扰动 attitude maneuver 姿态机动 augment ability可扩充性 augmented system增广系统 automatic manual station不用人力-手动操作器 autonomous system自治系统 backlash 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coordination method 目标协调法 grammatical inference 文法判断 grap 你好 c search 图搜索 gravitygradient torque 重力梯度力矩 group technology 成组技术 guidancesystem 制导系统 gyro drift rate 捻捻转儿漂移率 hall displacementtransducer 霍尔式位移传感器 hardware-in-the-loop simulation 半实物仿真 harmonious deviation 以及谐误差 harmonious strategy 以及谐计谋 heuristic inference 开导式推理你好 dden oscillation 隐蔽振动你好 erarc 你好 calchart 条理布局图你好 erarc 你好 cal planning 递阶规划你好 erarc你好 calontrol 递阶控制 homomorp 你好 c model 同态系统 horizontal decomposition 横向分解 hormonal control 内排泄控制 hydraulic step motor 液压步进马达 hypercycle theory 超循环意见 i controller 积分控制器 identifiability 可辨识性 idss(intelligent decision support system)智能决定计划支持系统 image recognition 图象辨认 impulse function 冲击函数,电子脉冲函数 incompatibility principle 不相容原理 incrementalmotion control 增量运动控制 index of merit 品质因数 inductiveforce transducer 电感式位移传感器 inductive modeling method 归纳建模法 industrial automation 工业不用人力化 inertial attitude sensor 惯性姿态敏锐器 inertial coordinate system 惯性坐标系 inertialwh eel 惯性轮 inference engine 推理机 infinite dimensional system 无限维系统information acquisition 信息采集 infrared gasanalyzer 红外线气体分析器 inherent nonlinearity 本来就有非线性 inherent regulation 本来就有调节 initial deviation 初始误差 injection attitude 入轨姿式input-output model 投入产出模子 instability 不稳定性 instructionlevel language 指令级语言 integral of absolute value of errorcriterion 绝对于误差积分准则integral of squared error criterion 平方误差积分准则 integral performance criterion 积分性能准则 integration instrument 积算摄谱仪 intelligent terminal 智能终端 interactedsystem 互接洽统,关接洽统 interactive prediction approach 互联预估法,关联预估法 intermittent duty 断续事情制ism(interpretivestructure modeling) 诠释布局建模法 invariant embedding principle 不变镶嵌原理 inventory theory 库伦论 inverse nyquist diagram 逆奈奎斯特图 investment decision 投资决定计划 isomorp 你好 c model 同构模子iterative coordination 迭代协调 jet propulsion 喷气推进 job-lot control 分批控制kalman-bucy filer 卡尔曼-布西滤波器 knowledgeaccomodation 常识适应knowledge acquisition 常识获取 knowledgessimilation 常识夹杂kbms(knowledge base management system) 常识库管理系统 knowledge representation 常识抒发 lad der diagram 菪瓮?lag-lead compensation 滞后超前赔偿 lagrange duality 拉格朗日对于偶性 laplace transform 拉普拉斯变换 large scale system 大系统 lateral in 你好 bition network 侧抑制采集 least cost input 最小成本投入 least squares criterion 最小二乘准则 level switch 物位开关 libration damping 天平动阻尼 limit cycle 极限环 linearizationtechnique 线性化要领 linear motion electric drive 直线运动电气传动 linear motion valve 直行程阀 linear programming 线性规划 lqr(linear quadratic regulator problem) 线性二次调节器问题 oad cell 称重传感器 local asymptotic stability 局部渐近稳定性 local optimum 局部最优 log magnitude-phase diagram 对于数幅相图long term memory 长期记忆 lumped parameter model 集总参量模子 lyapunov theorem of asymptotic stability 李雅普诺夫渐近稳定性定理 macro-economic system 宏观经济系统 magnetic dumping 磁卸载 magnetoelastic weig 你好ng cell 磁致弹性称重传感器 magnitude- frequencycharacteristic 幅频特征magnitude margin 幅值裕度 magnitudecale factor 幅值缩尺 man-mac 你好ne coordination 人机协调 manualstation 手动操作器 map(manufacturing automation protocol) 创造不用人力化以及谈 marginal effectiveness 边岸效益mason's gain formula 梅森增益公式 matc 你好 ng criterion 匹配准则 maximum likelihood estimation 最大似然估计 maximum ove rshoot 最大超调量maximum principle 极大值原理 mean-square error criterion 均方误差准则mechanismmodel 机理模子 meta-knowledge 元常识 metallurgical automation 冶金不用人力化 minimal realization 最小使成为事实 minimum phase system 最小相位系统 minimum variance estimation 最小方差估计 minor loop 副回路missile-target relative movement simulator 弹体- 目标相对于运动仿真器 modal aggregation 模态结集 modal transformation 模态变换 mb(model base)模子库model confidence 模子置信度 model fidelity 模子传神度 model reference adaptive control system 模子参考适应控制系统 model verification 模子证验mec(mostconomic control)最经济控制 motion space 可动空间 mtbf(mean time between failures) 均等妨碍距离时间 mttf(mean timeto failures)均等无妨碍时间 multi-attributive utility function 嗍粜孕в 煤??multicriteria 多重判据 multilevel 你好 erarc 你好 cal structure 多级递阶布局 multiloop control 多回路控制 multi- objective decision 多目标决定计划 multistate logic 多态逻辑multistratum 你好 erarc 你好 calcontrol 多段递阶控制 multivariable control system 多变量控制系统 myoelectric control 肌电控制 nash optimality 纳什最优性 naturallanguage generation 自然语言天生 nearest- neighbor 这段邻necessitymeasure 肯定是性侧度 negative feedback 负反馈 neural assembly 神经集合 neural network computer 神经采集计较机 nichols chart 尼科尔斯图noetic science 思维科学 noncoherent system 非枯燥关接洽统 noncooperative game 非互助博弈 nonequilibrium state 非平衡态 nonlinear element 非线性环节nonmonotonic logic 非枯燥逻辑 nonparametric training 非参量训练nonreversible electric drive 不成逆电气传动 nonsingular perturbation 非奇妙摄动 non-stationaryrandom process 非平稳 rand 历程 nuclear radiation levelmeter 核辐射物位计 nutation sensor 章动敏锐器 nyquist stability criterion 奈奎斯特稳定判据 objective function 目标函数 observability index 可测候指数observable canonical form 可测候标准型 on-line assistance 在线帮忙 on- off control 通断控制 open loop pole 开环极点 operational research model 运筹学模子 optic fiber tachometer 光纤式转速表 opt imal trajectory 最优轨迹optimization technique 最优化技术 orbital rendezvous 轨道交会 orbit gyrocompass 轨道捻捻转儿罗经 orbit perturbation 轨道摄动 order parameter 序参量 orientationcontrol 定向控制 oscillating period 振动周期 output predictionmethod 输出预估法 oval wheel flowmeter 椭圆齿轮流量计overalldesign 总体设计 overlapping decomposition 交叠分解 pade approximation 帕德类似 pareto optimality 帕雷托最优性 passive attitude stabilization 不主动姿态稳定 path repeatability 路径可重复性 pattern primitive 标准样式基元 pr(pattern recognition)标准样式辨认 p control 比例控制器 peak time 峰值时间penalty function method 罚函数法 periodic duty 周期事情制 perturbation theory 摄动意见 pessimisticvalue 悲观值 phase locus 相轨迹 phase trajectory 相轨迹hase lead 相位超前 photoelectric tachometric transducer 光电式转速传感器phrase-structure grammar 短句布局文法 physical symbol system 物理符号系统 piezoelectric force transducer 压电式力传感器 playbackrobot 示教再现式机器人 plc(programmable logic controller)可编步伐逻辑控制器 plug braking 反接制动 plug valve 旋塞阀 pneumaticactuator 气动执行机构 point-to-point control 点位控制 polar robot 极坐标型机器人 pole assignment 极点配置 pole-zero cancellation 零极点相消 polynom ial input 多项式输入 portfolio theory 投资配搭意见 pose overshoot 位姿过调量 position measuring instrument 位置丈量仪posentiometric displacement transducer 电位器式位移传感器 positive feedback 正反馈 power system automation 电力系统不用人力化 predicate logic 谓词逻辑pressure gauge with electric contact 电接点压力表 pressure transmitter 压力变送器 price coordination 价格协调 primal coordination 主协调 primary frequency zone 主频区 pca(principal component analysis)主成份分析法principlef turnpike 通途原理 process- oriented simulation 面向历程的仿真production budget 生产预算 production rule 孕育发生式法则 profitforecast 利润预测 pert(program evaluation and review technique) 计划评审技术program set station 步伐设定操作器 proportionalcontrol 比例控制 proportional plus derivative controller 比例微分控制器 protocol engineering 以及谈工程pseudo random sequence 伪 rand 序列 pseudo-rate-increment control 伪速度增量控制 pulse duration 电子脉冲持续时间 pulse frequency modulation control system 电子脉冲调频控制系统 pulse width modulation controlsystem 电子脉冲调宽控制系统 pwm inverter 脉宽调制逆变器 pushdown automaton 下推不用人力机 qc(quality control)质量管理 quadratic performance index 二次型性能指标 quali tative physical model 定性物理模子quantized noise 量化噪声 quasilinear characteristics 准线性特征 queuing theory 列队论 radio frequency sensor 射频敏锐器 ramp function 斜坡函数 random disturbance rand 扰动 random process rand 历程 rateintegrating gyro 速度积分捻捻转儿 ratio station 比率操作器 reactionwheel control 反效用轮控制realizability 可以使成为事实性,能使成为事实性 eal time telemetry 实时遥测receptive field 感受野 rectangularrobot 直角坐标型机器人 recursive estimation 递推估计 reducedorder observer 降阶测候器 redundant information 冗余信息 reentrycontrol 再入控制 regenerative braking 回馈制动,再生制动 regionalplanning model 地区范围规划模子 regulating device 调节装载 relationalalgebra 关系代数 relay characteristic 继电器特征 remote manipulator 遥控操作器 remote set point adjuster 远程设定点调整器 rendezvo 目前世界上最强大的国家 nd docking 交会以及对于接 resistance thermometer sensor 热电阻 esolution principle 归结原理 resource allocation 资源分配responsecurve 相应曲线 return difference matrix 回差矩阵 return ratiomatrix 回比矩阵 reversible electric drive 可逆电气传动 revoluterobot 关节型机器人revolution speed transducer 转速传感器 rewritingrule 重写法则 rigid spacecraft dynamics 刚性航天动力学 riskdecision 危害分析 robotics 机器人学 robot programming language 机器人编程语言 robust control 鲁棒控制 roll gap measuring instrument 辊缝丈量仪 root locus 根轨迹 roots flowmeter 腰轮流量计otameter 浮子流量计,转子流量计 rotary eccentric plug valve 偏疼旋转阀 rotary motionvalve 角行程阀 rotating transformer 旋转变压器 routh approximation method 劳思类似判据 routing problem 肪段侍?sampled-data control system 采样控制系统 sampling controlsystem 采样控制系统 saturation characteristics 饱以及特征 scalarlyapunov function 标量李雅普诺夫函数 scara(selective complianceassembly robot arm) 最简单的面关节型机器人 scenario analysis method 情景分析法 scene analysis 物景分析 self- operated controller 自力式控制器 self-organizing system 自组织系统 self-reproducing system 自繁殖系统self-tuning control 自校正控制 semantic network 语义采集 semi-physical simulation 半实物仿真 sensing element 敏锐元件 sensitivity analysis 活络度分析sensory control 觉得控制 sequentialdecomposition 挨次分解 sequential least squares estimation 序贯最小二乘估计 servo control 伺服控制,随动控制servomotor 伺服马达 settling time 过渡时间 short term planning 短期计划shorttime horizon coordination 短时程协调 signal detection and estimation 旌旗灯号检测以及估计 signal reconstruction 旌旗灯号重构 simulated interrupt 仿真中断 simulation block diagram 仿真框图 simulation experiment 仿真实验simulation velocity 仿真速度 single axle table 单轴转台 single degree of freedom gyro 单自由度捻捻转儿 single levelprocess 单级历程 single value nonlinearity 单值非线性 singularattractor 奇妙吸引子 singular perturbation 奇妙摄动 slave dsystem 受役系统 slower-than-real-time simulation 欠实时仿真slow subsystem 慢变子系统 socio-cybernetics 社会形态控制论 socioeconomic system 社会形态经济系统软体 psychology 软件生理学 solar array pointing control 日头帆板指向控制 solenoid valve 电磁阀 speed control system 魉傧低spin axis 自旋轴 stability criterion 稳定性判据 stabilitylimit 稳定极限 stabilization 镇定,稳定 stackelberg decision theory 施塔克尔贝格决定计划意见 state equation model 状况方程模子 state space description 状况空间描写 static characteristics curve 静态特征曲线 station accuracy 定点精密度stationary random process 平稳 rand 历程 statistical analysis 统计分析 statistic pattern recognition 统计标准样式辨认 steady state deviation 稳态误差steadystate error coefficient 稳态误差系数 step-by-step control 步进控制step function 阶跃函数 stepwise refinement 慢慢精化 stochasticfinite automaton rand 有限不用人力机 strain gauge load cell 应变式称重传感器 strategic function 计谋函数 strongly coupled system 狂詈舷低?subjective probability 主观频率 supervised training 喽窖??supervisory computer control system 计较机监控系统 sustainedoscillation 矜持振动 swirlmeter 旋进流量计 switc 你好 ng point 切换点 symbolic processing 符号处理 synaptic plasticity 突触可塑性syntactic analysis 句法分析 system assessment 系统评价 systemhomomorp 你好sm 系统同态 system isomorp 你好 sm 系统同构 system engineering 系统工程target flow transmitter 靶式流量变送器 task cycle 功课周期 teac 你好 ng programming 示教编程 telemetering system ofrequency division type 频分遥测系统 teleological system 目的系统 temperature transducer 温度传感器template base 模版库 theoremproving 定理证实 therapy model 治疗模子 t 你好ckness meter 厚度计 three-axis attitude stabilization 三轴姿态稳定 three state controller 三位控制器 thrust vector control system 推力矢量控制系统 time constant 时间常数 time-invariant system 定常系统,非时变系统 time schedule controller 时序控制器 time-sharing control 分时控制 time-varying parameter 时变参量 top-down testing 自上而下测试topological structure 拓扑布局 tqc(total quality control)全面质量管理 tracking error 跟踪误差 trade-off analysis 权衡分析 transfer function matrix 传递函数矩阵transformation grammar 转换文法 transient deviation 瞬态误差 transient process 过渡历程 transition diagram 转移图 transmissible pressure gauge 电远传压力表 trend analysis 趋向分析 triple modulation telemetering system 三重调制遥测系统 turbine flowmeter 涡轮流量计 turing mac 你好 ne 剂榛?two-time scale system 双时标系统 ultrasonic levelmeter??镂患?unadjustable speed electric drive 非调速电气传动 unbiasedestimation 无偏估计 uniformly asymptotic stability 一致渐近稳定性 uninterrupted duty 不间断事情制,长期事情制 unit circle 单位圆 unit testing 单位测试 unsupervised learing 非监视进修upperlevel problem 较高等级问题 urban planning 城市规划 utility function 效用函数 value engineering 价值工程 variable gain 可变增益,可变放大系数 variable structure control system 变布局控制 vectorlyapunov function 向量李雅普诺夫函数 velocity error coefficient 速度误差系数 velocity transducer 速度传感器vertical decomposition 纵向分解 vibrating wire force transducer 振弦式力传感器 viscousdamping 粘性阻尼 voltage source inverter 电压源型逆变器vortexprecession flowmeter 旋进流量计 vortex shedding flowmeter 涡街流量计 wb(way base) 要领库 weig 你好 ng cell 称重传感器 weightingfactor 权因数weighting method 加权法 w 你好 ttaker-shannon samplingtheorem 惠特克-喷鼻农采样定理 wiener filtering 维纳滤波 work stationfor computer aided design 计较机匡助设计事情站 w-plane w 最简单的面 zero-based budget 零基预算 zero-input response 零输入相应 zero-stateresponse 零状况相应 zero sum game model 零以及对于策模子2022 年 07 月 31 日历史上的今天：ipad2 怎么贴膜好吧,我还是入了 iPad2 2022-06-26 斗破苍穹快眼看书 2斗破苍穹 22 下载 20 11-06-26特殊声明：1：资料来源于互联网，版权归属原作者2：资料内容属于网络意见，与本账号立场无关3 ：如有侵权，请告知，即将删除。
P rocedia - Social and Behavioral Sciences 96 ( 2013 ) 2383 – 23941877-0428 © 2013 The Authors. Published by Elsevier Ltd. Open access under CC BY-NC-ND license.Selection and peer-review under responsibility of Chinese Overseas Transportation Association (COTA).doi: 10.1016/j.sbspro.2013.08.267ScienceDirectAvailable online at 2384L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 2394 Reasonable design of feeder-bus network related to urban rail transit can promote service level, efficiency and competitiveness of public transport. Feeder-bus network is the set of bus lines which serves transferpassenger between buses and trains. Each bus line connects to one feeder railway station, serves some bus stops in a certain order, and operates in certain frequency. Thus the feeder-bus network-design problem (FBNDP) is to determine feeder-bus routes composed of the feeder station, the route structure and the operating frequency (Byrne & Vuchic, 1972; Kuah & Perl, 1988; Kuah & Perl, 1989).2.Literature reviewExisting research on FBNDP includes analytic approach and network programming (also known as mathematical programming). Early research mainly uses analytic approach, which derives the optimal route spacing, operating headway and the optimal stop spacing based on assumptions regarding the shape of the street geometry and the spatial distribution of demand, those assumptions have their limitations. Supposing thatpassenger demand distributes in rectangular region composed of a rail line and parallel bus lines which areperpendicular to the rail line, Byrne and Vuchic (1972) studied the optimal location and headway of parallel bus lines, and the method to determine the optimal number of bus lines was given. On the basis of this work, Byrne (1976) determined the lengths, positions and headways of bus lines which could minimize user travel time and operating costs in response to a general population density function and differing line speeds. Hurdle (1973) studied how parallel feeder lines should be located and how their schedules should respond to a passenger arrival pattern that varied with travel location and time. Wirasinghe, Hurdle and Newell (1977) put forwardoptimizations formulations for the optimal railway interstation spacings, feeder-bus zone boundary and train headways mainly by use of basic calculus in conjunction with continuum approximations of certain discrete parameters. Wirasinghe (1980) supposed that a rail plus feeder bus system served a peak-period demand type of M-to-1, and presented an approximate analytical model and corresponding solution algorithm, the model was applied to the Calgary (South Corridor) LRT system. Kuah and Perl (1988) optimized the route spacing,operating headway and the stop spacing simultaneously, and analyzed influencing factors of bus-stop spacing in three different cases. Supposing that the location of rail line to be studied was predetermined, Chien andSchonfeld (1998)cut urban corridor into several traffic zones with different length and same width, and jointly optimized rail line length, railway station spacing, bus headways, bus stop spacing and bus route spacing under conditions that passenger flow density in each traffic zone was same and that only one feeder-bus line connected to the same railway station. Chien and Yang (2000) developed a model for finding the optimal bus route location and its operating headway in a heterogeneous service area while considering intersection delays. In the model, irregular and discrete M-to-1 demand distributions were considered, the near-optimal algorithm wasdemonstrated.Network programming approach could better deal with feeder-bus network-design problem. In the approach, urban traffic network is composed of two types of nodes: rail nodes and bus nodes, which represent bus stops and railway stations respectively, bus sections represent feeder-bus route segments and the demand is assumed to be concentrated at bus nodes. Kuah and Perl (1989) developed a mathematical programming model for FBNDP under M-to-1 demand pattern and designed heuristic algorithm based on savings approach. They generalized M-to-M FBNDP to M-to-1 FBNDP by separating bus stops into dummy child nodes the number of which is same with railway stations, and they analyzed sensitivity of the model for change of the design objective, passenger demand variability, vehicle capacity, labour and fuel costs, the rail network. On the above basis, Martins and Pato (1998) built up the initial solution through a sequential savings or a two-phase method, and designed local search as well as tabu search heuristics with diversification and intensification strategies. Shrivastav and Dhingra (2001) discussed development of feeder routes for operational integration of suburban railway stations and public buses, and developed a heuristic algorithm using different node selection and insertion strategies. Kuan and Ong mainly focused on the application of meta-heuristic algorithms on FBNDP, such as simulated annealing and tabu search2385L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 ) 2383 – 2394 (2004), genetic algorithm and ant colony optimization (2006), analyzed and compared the optimal resultsobtained by these algorithms.Lately, Ciaffi (2012) dealt with feeder-bus network design problem in a solving procedure with 2 phases. In the first phase, a heuristic algorithm was used to generate two different and complementary sets of feasible routes, in order to provide a good balance between maximization of the service coverage area and minimization of the overall travel time. In the second phase, the sets generated in the first phase were used as input data and GA was designed to find a sub-optimal set of routes with the associated frequencies. On this basis, they constructed a model for layout region of feeder buses.In this paper, in accord with realistic passenger distribution characteristics, the existing assumption that passengers travel from multiple origins to a single destination (M-to-1), is relaxed to more general passenger demand pattern (M-to-M) that means passenger demand distributes in all stops and stations. Then, bus and rail transit are regarded as a whole transfer service system and passenger travel cost is considered based on the transfer network, feeder-bus network-design problem is studied to minimize passenger travel cost and bus operation cost. Furthermore, a new generation algorithm (GA) is developed and optimal results under different passenger patterns are analyzed and compared. 3. model ConstructionThe constraints of feeder-bus can be obtained according to the above assumptions and transit operating requirement. Compared with M-to-1 demand pattern, network construction constraints under M-to-M pattern are completely identical.. Under M-to-M demand pattern, under considering passenger generalized travel cost,multiple destinations of passengers at every stop will effect on their feeder station selection, then feeder-bus route structure and feeder-bus network construction will be influenced. 3.1. Constraints analysisTo represent feeder-bus network constraints, ij Y and ihk X are defined to denote relationship between nodes or nodes and routes.1,if bus node is assigned to rail node , 1,,;1,,otherwiseij i j Y i I j I I J1,if node precedes node on bus route ,1+1otherwiseihki h kX i h =,,I J;k =,,KThe following section will analyze all constraints which feeder-bus network need to satisfy. 1) Feeder-bus network connectedness constraintIn the feeder-bus network, any sub-set of bus stops must link to feeder stations directly or via other bus stops, i.e. the following connectedness constraint:11,for all Kihki H h H k X H(1)H is any proper subset of N containing the set of all rail nodes.2) Feeder-bus route integrity constraintsEach bus route must link to a single railway station:11=1,1,,II Jijk i j I X k K(2)A route terminates in a certain feeder station d T where the route passengers are transported to, i.e.,2386L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942387 L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942388L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942389 L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942390L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942391 L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 )2383 – 23942392 L ian-bo Deng et al. / P rocedia - Social and Behavioral Sciences 96 ( 2013 ) 2383 – 2394shows the calculation results, figure 1 is the optimal feeder-bus network when demand uniformly distributesbetween 4 railway stations (50a ).Fig.1 Optimal feeder-bus network when 50aTable 2 Indicators of optimal solutions under various demand distributionsStation’s demand fromeach stopStation’s Transfer Passengers 56 57 58 59Systemcost($)Numbers of route Averageroute lengthAverageroute frequency Average traveltime (bus : train) Divertedrouting factor 50 50 50 50 6515 1600 3800 4600 100019 0.79 21.88 0.51: 0.53 1.28 40 46 54 60 6511 1400 3600 5000 100019 0.80 21.93 0.51: 0.51 1.27 30 43 57 70 6505 800 3800 4600 180018 0.84 22.06 0.50: 0.48 1.27 20 40 60 80 6494 1000 3000 5200 180018 0.84 21.99 0.50: 0.48 1.25 10 37 63 90 6476 800 2800 5600 180016 0.93 22.21 0.47: 0.41 1.25 0 33 67 100 6437 800 2800 4800 2600170.8922.040.50: 0.421.22From Table 2, some laws can be obtained:(1) For one railway station, with the increase of passengers whose destination is this station, the number of passengers who choose to feeder at this station increase correspondingly, as Figure 2 shows:Fig.2Relation between demand density and feeder passengers at stationsLian-bo Deng et al. / Procedia - Social and Behavioral Sciences 96 (2013) 2383 – 23942393(2) Demand distribution has an obvious effect on average bus riding-time and average train riding-time, just as Figure 3 shows. With increase of imbalance of demand distribution at stations, feeder station and structure of routes are influenced by advantage passengers, difference of average travel time at two traffic modes increases gradually. Simultaneously, total travel time on integrated transport network decreases.Fig.3 Relation between demand distribution and travel time(3) As Figure 4 shows, with increase of imbalance of demand distribution at stations, namely concentration of demand destinations, circumambulate ratio falls and system total cost also decreases markedly. Reason is that concentration of demand destinations makes advantage passengers share better service and brings decline of system total cost.Fig.4 The effect of termination passengers on feeder passengers at stationsWe can see that passengers will choose different feeder-bus stations and structure of travel routes will differ under different demand distributions, all these will influence total cost of the whole feeder system.6. ConclusionThis paper studies optimal design problem of feeder-bus network related to urban rail transit under M-to-M passenger demand pattern between bus stops and railway stations, the passenger demand do not be limited to a single destination (M-to-1), which more accords with realistic demand distribution law. In order to minimize passenger travel cost and transit operating cost, integrated public transport system of feeder-bus network and railway is regarded as a whole to overall calculate passenger travel cost. Results show that passenger demand distributions have significant influence on feeder bus network construction. Therefore, demand distributions should be considered when designing feeder-bus network related to urban rail transit2394Lian-bo Deng et al. / Procedia - Social and Behavioral Sciences 96 (2013) 2383 – 2394Usually public transportation network planning has symmetry, though differences at two directions are not considered in designing feeder-bus network. If demand on feeder-bus network has obvious tidal phenomenon with time distribution, and operating frequencies at different directs differ greater, directed feeder-bus network is designed according to directional demand.AcknowledgementsThe work described in this paper was supported by grants from the National Natural Science Foundation of China (Project no. 70901076), the Research Fund for the Doctoral Program of Higher Education of China (Project no. 20090162120021), and the Research Fund for Fok Ying Tong Education Foundation of Hong Kong (Project no. 132017).ReferencesMay A.D. (1991). Integrated transport strategies: a new approach to urban transport policy formulation in the UK. Transport Reviews, 2(3), 233-247. Stanger R.M., Vuchic V.R. (1979). The design of bus-rail transit facilities. Transit Journal, 5, 61-72. Dunn J.A. (1980). Coordination of urban transit services: the German model. Transportation, 9, 33-43. Byrne B.F., Vuchic V. (1972). 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Optimal feeder bus routes on irregular street networks. Journal of Advanced Transportation, 34(2), 213-248. Kuah GK, Perl J. (1989). The feeder-bus network-design problem. Journal of the Operational Research Society, 40, 751-767. Matins C.L., Pato M.V. (1998). Search strategies for the feeder bus network design problem. Europe Journal Operational Research, 106, 425-440. Shrivastav P., Dhingra S.L. (2001). Development of feeder routes for suburban railway station using heuristic approach. Journal of Transportation Engineering, 127(4), 334-341. Kuan S.N., Ong H.L., Ng K.M. (2004). Applying metaheuristics to feeder bus network design problem. Asia-Pacific Journal of Operational Research, 21(4), 543-560. Kuan S.N., Ong H.L., Ng K.M. (2006). Solving the feeder bus network design problem by genetic algorithms and ant colony optimization. Advances in Engineering Software, 37, 351-359. Ciaffi F, Cipriani E, Petrelli M. (2012). Feeder bus network design problem: a new metaheuristic procedure and real size applications. 15th meeting of the EURO Working Group on Transportation.。
机械设计需要优化的英文词The Need for Optimization in Mechanical Design.Mechanical design is a crucial aspect of engineering that involves the creation of machines, devices, and systems. It plays a pivotal role in converting theoretical concepts into practical applications. However, to ensure the efficiency, reliability, and performance of these designs, it's imperative to consider optimization. Optimization in mechanical design involves identifying areas of improvement and implementing strategies to enhance the overall design.1. Importance of Optimization.Optimization in mechanical design is essential for several reasons:Efficiency: By optimizing designs, engineers can improve the efficiency of machines and systems, reducingenergy waste and operational costs.Reliability: Well-optimized designs are more likely to withstand wear and tear, ensuring longer service life and reduced maintenance requirements.Performance: Optimization can enhance the performance of mechanical systems, improving their speed, accuracy, and overall output.Safety: By identifying and addressing potential hazards, optimization can help ensure the safety of operators and users.Sustainability: Optimized designs often lead to reduced environmental impact, such as reduced energy consumption and waste generation, aligning with sustainable development goals.2. Areas of Optimization.There are several areas in mechanical design whereoptimization can be applied:Material Selection: Choosing the right material for a particular application can significantly impact the performance and durability of a design. Optimization involves selecting materials that offer the best combination of strength, weight, cost, and durability.Geometric Design: Geometric optimization involves modifying the shape, size, and arrangement of components to improve performance. This can include optimizing theprofile of a gear, the spacing of bearings, or the layout of a mechanical system.Thermal Design: Heat management is crucial in mechanical systems, as excessive heat can lead to performance degradation and failure. Optimization techniques can help identify effective heat dissipation strategies, such as the use of heat sinks or fans.Dynamic Analysis: Analyzing the dynamic behavior of mechanical systems can help identify areas of vibration orresonance that may affect performance. Optimization can involve modifying system parameters to reduce vibrations or improve stability.Control System Design: Optimizing the control system can enhance the precision and responsiveness of mechanical systems. This may involve developing more efficient control algorithms or improving the integration of sensors and actuators.3. Optimization Techniques.There are various techniques and tools available for optimizing mechanical designs:Finite Element Analysis (FEA): FEA is a numerical method used to predict the response of a material or structure to applied loads and boundary conditions. It can help identify stress concentrations, deformation, and other factors that affect the performance of a design.Computational Fluid Dynamics (CFD): CFD is used tosimulate fluid flow within and around mechanical systems.It can help optimize fluid paths, heat transfer, and aerodynamic performance.Optimization Algorithms: These algorithms can search for the best design parameters that maximize performance or minimize cost functions. Techniques such as genetic algorithms, simulated annealing, and gradient-based optimization can be used to find optimal solutions.Design for Manufacturing and Assembly (DFMA): DFMA involves considering manufacturing and assembly constraints during the design phase. It aims to simplify the manufacturing process, reduce costs, and improve assembly efficiency.4. Conclusion.Optimization plays a crucial role in mechanical design, enabling engineers to create efficient, reliable, and sustainable systems. By applying optimization techniques and tools, designers can identify areas of improvement andimplement strategies to enhance the overall performance of their designs. As technology continues to advance, so will the need for optimization in mechanical design, ensuring that machines and systems continue to meet the demands of a rapidly evolving world.。
随着时代的飞速发展，高度自主化的机器人在人类社会中的地位与作用越来越大。
而机械臂作为机器人的一个最主要操作部件，其运动规划问题，例如准确抓取物体，在运动中躲避障碍物等，是现在研究的热点，对其运动规划的不断深入研究是非常必要的。
机械臂的运动规划主要在高维空间中进行。
RRT （Rapidly-exploring Random Tree）算法[1]基于随机采样的规划方式，无需对构型空间的障碍物进行精确描述，同时不需要预处理，因此在高维空间被广为使用。
近些年人们对于RRT算法的研究很多，2000年Kuffner等提出RRT-connect算法[2]，通过在起点与终点同时生成两棵随机树，加快了算法的收敛速度，但存在搜索路径步长较长的情况。
2002年Bruce等提出了ERRT（Extend RRT）算法[3]。
2006年Ferguson等提出DRRT （Dynamic RRT）算法[4]。
2011年Karaman和Frazzoli提出改进的RRT*算法[5]，在继承传统RRT算法概率完备性的基础上，同时具备了渐进最优性，保证路径较优，但是会增加搜索时间。
2012年Islam等提出快速收敛的RRT*-smart算法[6]，利用智能采样和路径优化来迫近最优解，但是路径采样点较少，使得路径棱角较大，不利于实际运用。
2013年Jordan等通过将RRT*算法进行双向搜索，提出B-RRT*算法[7]，加快了搜索速度。
同年Salzman等提出在下界树LBT-RRT中连续插值的渐进优化算法[8]。
2015年Qureshi等提出在B-RRT*算法中插入智能函数提高搜索速度的IB-RRT*算法[9]。
同年Klemm等结合RRT*的渐进最优和RRT-connect的双向搜基于改进的RRT*-connect算法机械臂路径规划刘建宇，范平清上海工程技术大学机械与汽车工程学院，上海201620摘要：基于双向渐进最优的RRT*-connect算法，对高维的机械臂运动规划进行分析，从而使规划过程中的搜索路径更短，效率更高。
第 51 卷 第 3 期石 油 钻 探 技 术Vol. 51 No.3 2023 年 5 月PETROLEUM DRILLING TECHNIQUES May, 2023◄测井录井►doi:10.11911/syztjs.2023068引用格式：亢武臣，杨书博，赵琪琪，等. 基于优化变分模态分解和互相关的钻井液脉冲信号处理方法[J]. 石油钻探技术，2023, 51（3）：144-151.KANG Wuchen, YANG Shubo, ZHAO Qiqi, et al. A pulse signal processing method for drilling fluid based on optimal variational mode decomposition and cross-correlation [J]. Petroleum Drilling Techniques，2023, 51(3)：144-151.基于优化变分模态分解和互相关的钻井液脉冲信号处理方法亢武臣1,2， 杨书博2， 赵琪琪3， 黄豪彩1， 丁士东2（1. 浙江大学海洋学院, 浙江舟山 316021；2. 中石化石油工程技术研究院有限公司, 北京 102206；3. 中国石油大学（北京）地球物理学院, 北京102249）摘 要: 随着油气勘探开发不断深入，钻井技术逐渐向深井、超深井和小井眼方向发展，对钻井液脉冲信号处理提出了更高的要求。
通过分析脉冲位置调制编码的基本原理，提出了一种基于优化变分模态分解和互相关的钻井液脉冲信号处理方法，并利用在苏北地区某页岩油井采集的钻井液脉冲信号验证了该方法的可行性。
基于优化变分模态分解算法，实现了在低信噪比条件下有用信号的有效提取；基于同步头相关器对去噪后的信号进行互相关处理，实现了数据帧起始位置的可靠计算；基于数据块相关器对数据块内波形进行互相关处理，实现了码值的准确获取。
与传统的钻井液脉冲信号处理方法相比，上述方法具有可靠性高和误码率低的特点，能够很好地满足复杂井眼环境下钻井液脉冲信号处理的需求。
潜在失效模式及后果分析（FMEA）常用语发布人：圣才学习网发布日期：2010-08-25 10:20 共人浏览[大] [中] [小]设计/过程FMEA （design/process FMEA）项目名称（item）主要参加人员（core team）设计/过程责任部门（design/process responsibility）关键日期（key date）编制（prepared by）审批（approved by）过程功能（process function）要求（requirements）潜在失效模式（potential failure mode）潜在失效后果（potential effects of failure）严重度数（severity）级别（classification）潜在的失效起因/机理（potential causes/mechanisms of failure）频度数（occurrence）现行过程控制（current process control）预防（prevention）探测（detection）风险顺序数（risk priority number）建议的措施（recommended actions）责任和目标完成日期（responsibility & target completion date）措施结果（action results）采取措施（actions taken） ?影响产品特性/二次加工周期/外观/装配功能（affect product characteristic/ postprocessing period/ appearance/assembling function ）用料不符合要求（inconformable material to the requirements）温度控制不当（incorrect temperature control）模具/机板不平行（die/machine platen in unparallel）锁模力过小（lack of locking force）模具温度过低（lower die temperature）射料力/打锤时间不足（lack of injection force/shot time）料温过低/过高（lower/excessive metal temperature）模具过热（excessive hot die）运水量过低（lower volume of cool water）喷雾过大（release agent to excess）射速太快（rapid injection velocity）喷雾频次过少或喷雾不均匀（infrequent/ uneven spraying release agent ）模温过高导致蚀模（excessive hot die leads to die corrosion）模具尺寸不符合要求（die size out of the specification）工模行位柯磨损（core slides worn out）开模时间过短（shortage of die－open time）顶出时间过短（shortage of ejector time）冲剪夹具有缝隙（trimming die with crack）操作时摆放不正确（lay products in disorder during operation）除批锋时操作不当而刮伤表面（surface scratch due to the improper handling in removing flash）摆放不正确堆积产品（pile products up due to laying in disorder）磨光轮选择不合适（unsuitable polishing wheels）布轮（polishing/cotton wheels）麻轮（sisal/sisal buffing wheels）砂布轮（sanding wheels）铜丝轮（brass brush wheels）磨料（abrasive medium） ?手工磨光（manual polishing）抽取样品时产品有碰撞（bump at sampling）货与货之间碰撞（bump among products）电子磅误差超标（digital balance out of allowable error）主管对员工培训不足（lack of necessary training for employees）按工作指示设定压铸参数/锁模力/射料力/射料速度/打锤时间/喷雾量/开模时间/顶出时间/压力参数/料温/控制温度/作业（set die－casting paramete r/locking force/ injection force/injection velocity/shot time/ volume of release agent/die－open time/ ejector time/pressure rating/metal temperature/ control temperature/ operation according to WI）开拉前培训（training before operation）定期校准电子磅（regular calibration for digital balance）。
