6sigma项目运作实例(doc74)-精益生产(编辑修改稿)

6sigma项目运作实例(doc74)-精益生产(编辑修改稿)内容摘要：

An FMEA identifies problems before they occur FMEA serves as a record of improvement amp。 knowledge For the future: FMEA helps evaluate the risk of process changes FMEA identifies areas for other studies – multivari, ANOVA, DOE 6s Process FMEA Terminology FMEA: A systematic analysis of a process used to identify potential failures and to prevent their occurrence Potential Failure mode: The manner in which the process could potentially fail to meet the process requirements. Potential Failure Effect: The results of the failure mode on the customer. Severity: An assessment of the seriousness of a failure mode. Severity applies to the effects only. Cause: How the failure could occur, described in terms of something that can be corrected or controlled. Occurrence: The likelihood that a specific failure mode is projected to occur. Detection: The effectiveness of current process controls to identify the failure mode (or the failure effect) prior to occurring, prior to release to production, or prior to shipment to the customer. 中国最大的管 理 资料下载中心 (收集 \整理 . 大量免费资源共享 ) 第 15 页 共 67 页 RPN Risk Priority Number: The product of Severity, Occurrence amp。 Detection FMEA Examples Plating Example An aerospace plating pany was shipping product to its customers with nickel plating that was too thin. Parts were failing corrosion testing at the customer. Shipping Example The shipping department of an electronics pany is unable to ship an assembly without its clam shell protective packaging. This causes occasional late shipments to the customer. In the following examples, a single line from the FMEA is used as an illustration for each of the above examples. 图形技术分析 : Graphical Methods Process Variation Noise variation from discrete inputs Different operators, machines, setups Different days, shifts Different batches, mixtures, raw materials Noise variation from continuous inputs Ambient temperature, humidity, pressure Wear, drift, erosion, chemical depletion ) ,..., , ( 2 1 k Process x x x f y =) ,..., , ( 2 1 k Noise n n n f + Intentional Unwanted The equation just means that any output is determined by the intentional process settings and the unwanted noise variation. Common Classification of Noise Variables Positional (within part variation) Variation within a single production unit Thickness variation across a plated part Variation across a unit containing many parts Variation across a semiconductor wafer with many die Variation by position in a batch process Cavitytocavity variations in an injection molding operation Cyclical (parttopart variation) Variation between consecutive production units Batchtobatch average differences – consecutive batches Temporal (timetotime variation) Shifttoshift, DaytoDay, Setuptosetup 中国最大的管 理 资料下载中心 (收集 \整理 . 大量免费资源共享 ) 第 16 页 共 67 页 Variation not accounted for by Positional or Cyclical 2 2 2 2 Temporal Cyclical Positional Noise σ σ σ ++= Graphical Analysis – Example Injection molding is used to make a type of socket, four pieces at a time, one piece per slot. Measurements of the sockets consist of thickness values in excess of millimeters. The gauges measure in hundredths of a millimeter. The specification is 11 177。 6. Four times a day the supervisor would go to the press and gather up the parts produced by five consecutive cycles of the press. Since each cycle produced four parts, he would have 20 parts to measure every two hours. The supervisor kept track of the cycle and the cavity from which each part came and wrote his twenty measurements in an array like this: The supervisor collected samples four times a day for five days (20 samples total, 20 parts per sample). Calculate the process capability and use a MultiVari chart to help determine sources of variation. A BCDE S1 18 19 20 19 21 S2 13 16 14 13 13 S3 10 11 13 10 13 S4 11 12 13 13 13 Exercise: Determine Capability Using Minitab, analyze the Thick data in for process capability  Remember, the specifications are: 11 177。 6 What is the shortterm process capability? What is the longterm process capability? Are these good or bad values? Remember, one goal of Six Sigma is to reduce variation, which will increase capability. It is always important to understand the process capability. Preparing Data for Marginal Plot by “Slot” Marginal plots require both variables to be defined numerically  We need to convert “Slot” to a numeric column first  Step 1: Convert “Slot” 中国最大的管 理 资料下载中心 (收集 \整理 . 大量免费资源共享 ) 第 17 页 共 67 页 ManipCodeText to Numeric Manip Code Text to Numeric MultiVari Analysis – Defined A graphical analysis tool Uses logical subgrouping Analyzes the effects of discrete X’s on continuous Y’s A capability and process analysis tool Data collected for a relatively short time  Data can estimate capability, stability, and y = f(x)’s Major focus: study uncontrolled noise variation first Variation in noise variables produces chronic and acute mean shifts, changes in variability, and instability Noise variation must be reduced or eliminated in order to leverage the important controllable variables systematically Multivari analysis is a very useful tool for graphically identifying sources of variation, especially noise variation. Later this week, we will be。