Six Sigma Level II Training-6

1、12003 Six Sigma Level II Training(Control)Managing the XsThe Loss Function and Realistic Tolerancing The premise of the loss function is that at some point as a process moves away from its Ideal value, there is a corresponding decrease in the quality of the response. This loss in quality may be hard

2、 to pinpoint by the customer but eventually reaches a threshold where a complaint occurs - well after the first signs of a problem were encountered.Realistic Tolerancing Marginal Distributions The underlying distribution of X, displayed as a marginal distribution in the graph above, Causes the margi

3、nal distribution Y. This cause-and-effect relationship can be used to determine the width and location of specification limits on X given requirements on Y.Marginal Distributions from Experiments Ideally, it is desired to set the allowable range of each X such that output of the process remains at a

4、 6 process. This could be accomplished by setting X tolerance to the equivalent of +/-3 of the response Y.Adjusting for Statistical Uncertainty in Realistic Tolerancing From experiments, there is uncertainty as to the true relationship between the input and the output. To compensate for this, a 95%

5、confidence interval could be constructed around the inputs. The net effect is to reduce the allowed variability of the input, relative to that shown on the previous diagram Note: The ability to set the tolerance on X is subject to the ability to control X over the range.Leveraging Interactions and N

6、on-Linearities in Robust DesignThe dotted line distributions approximate the expected distribution of Y as B varies between its low value and its high value. In the case of the non-linearity, the dotted line distributions represent the expected distribution of Y at two levels of A.Mistake ProofingMi

7、stake-Proofing Defined Mistake-proofing:Using wisdom and ingenuity to create devices that allow you to do your job 100% defect free 100% of the time.Mistake-Proofing Defined Everyday Examples of Mistake-Proofing:Home:Automated shutoffs on electric coffee potsChild-proof caps on medicationsButane lig

8、hters with a safety button Automobile:Seat beltsAir bagsCar engine warning lights Office:A “Do you want to delete?” message after you press the “Delete” button on your computerFactory:Dual palm buttons and other guards on machineryDefects vs. ErrorsA defect is the result of an error.An error is the

9、cause of defect.CAUSEERRORMISTAKEEFFECTDEFECTINCORRECTDAMAGEDPRODUCTINCOMPLETEBrainstorm A list of Errors/DefectsMistake-Proofing Process MapError Condition Error: When any of the conditions necessary for successful processing are wrong or absent The 10 most common errors (Causes of Defects) Process

10、ing omissions Processing errors Error in setting up the workplace Assembly omissions (missing parts) Inclusion of the wrong part/item Wrong workplace Operations errors Adjustment, measurement, and dimensional errors Error in equipment maintenance Error in the preparation of blades, jigs, or toolsErr

11、ors Are Causes of Defects Leaks Mis-wire Loose parts Noise Damaged parts/product Reversed parts/product Foreign matter present Mismatched parts Misaligned partsCommon Defect Categories Wrong or inconsistent dimensionally Unable to be assembled Inconsistent test results/test failure Bad incoming mate

12、rials Wrong material or parts Other. How does your organization approach human error?Human ErrorsNegative Defects are inevitable: People make mistakes Place blame Detect at the final inspection Sampling inspection Some reach the customerPositive Defects are eliminated Create the environment Ask, Why

13、? Apply a mistake-proofing device for 100% inspection Just Do It!Forgetfulness (not concentrating)Errors due to misunderstanding (jumping to conclusions)Errors in identification (viewing incorrectlyto far away)Errors made by untrained workersWillful errors (ignoring rules)Inadvertent errors (distrac

14、tion, fatigue)Errors due to slowness (delay in judgment)Errors due to lack of standards (written and visual)Surprise errors (machine not capable, malfunctions)Intentional errors (sabotage - least common)Errors due to work overload.Types of Human Errors Hints to help: Simple Inexpensive Give prompt f

15、eedback Give prompt action (prevention) Focused application Have the right people inputStrive For the Best DeviceMistake-Proofing Devices Here s a list, certainly not all inclusive, of mistake-proof devices that can be used to respond to red flags and prevent errors Guide/reference/interference rod

16、or pin Template Limit switch/micro-switch Sequence restriction Standardize and solve Critical condition indicator Stopper/gate SensorTypes of Mistake-Proofing Devices Human errors are usually inadvertent. Mistake - proof devices help us avoid defects, even when inadvertent errors are made. Here are

17、the five examples of mistake - proofing for detecting caused by human errors.Leaning ManufacturingThe Vision of Lean ManufacturingWhat Is Waste (MUDA)? There are seven elements of wasteMuda of correctionMuda of overproductionMuda of processingMuda of conveyanceMuda of inventoryMuda of motionMuda of

18、waiting Dont forget the goal: ELIMINATION OF MUDA! Muda of Correction Correcting or repairing a defect in materials or parts adds unnecessary costs because of additional equipment expenses and additional labor expenses. Example: The labor costs associated with scheduling employees to work overtime t

19、o re-work defects Muda of Overproduction Producing more parts than are necessary Producing parts at a rate faster than is required Mude of Processing Processing work that is unnecessary because it has no connection with advancing the line or improving the quality of the product Examples: Typing memo

20、s that could be handwritten Painting components or fixtures that are internal to the equipment Mude of Conveyance Conveyance is not something that directly contributes any added value to the product. It is an incidental required action It s vital to avoid conveyance unless it is supplying items when

21、 and where they are needed. Example: Transporting product across the planet instead of moving the machines closer together Mude of Inventory Inventory is a drain on an organization s overhead. The greater the inventory, the higher the overhead costs become. If quality issues arise and inventory is n

22、ot minimized, defective material is hidden in finished goods In order to remain flexible to customer requirements and to ensure control of product variation, we MUST minimize inventory With excess inventory, we cover up unacceptable setup times, excessive downtime, operator inefficiency, and lack of

23、 organizational sense of urgency to produce product Mude of Motion Any movement of people or machinery that does not contribute added value to the product Examples: Programming delay times Excessive walking distance between operations Muda of Waiting Idle time between operations or events Examples:

24、An operator waiting for a machine to finish cycling A machine waiting for an operator to load new part(s) Dead time in the engineering development cycle In order to ensure your gains are sustainable you must start with a firm foundations. 5S standards are the foundation that supports all the phases

25、of lean manufacturing. The system can only be as strong as the foundation upon which it is built The foundation of a production system is a CLEAN an SAFE work environment. Its strength depends upon the employees commiteed to maintaining it.5S Workplace Organization Sifting: Identify all items within

26、 the work area that are not required to perform the manufacturing process. Remove those items from the work area. Sorting: Any items identified as Required must be assigned a specific location. This location should be identified by outlining and/or labeling the item and its location Sweeping: All gr

27、ease, dirt, etc., Must be cleaned! Set a new level of cleanliness in your organization. Cleanliness not only provides a safe work area, but it also highlights potential problems in the work area (equipment leaks, loose or missing safety guards, etc.). Spic-n-span: The ultimate workplace organization

28、 is Spic-n-Span. This is the result of establishing acceptable levels for Sifting, Sorting, and Sweeping. Self-Discipline: This is each individual s personal and professional commitment to maintenance of 5S standards in his/her own work area. This the most difficult of the 5S standards.What Are 5S S

29、tandards? The first step of the visual factory is the 5S standards. Next, the team should ask the following questions: Can we readily identify downtime issues? Can we readily identify scrap issues? Can we readily identify setup problems? Can we readily line balancing opportunities? Can we readily id

30、entify excessive inventory levels? Can we readily identify extraneous tools and supplies? If you CANNOT readily identify any of these opportunities through a VISUAL glance of the area, the team should seek to establishThe Visual FactoryWhat Is Standardized Work? The “One best way” to perform each op

31、eration has been identified and agreed upon through general consensus. This becomes the “standard” work procedure We must understand: Variation = defects Variation = defectsStandardized work leads to Standardized work leads to reduced variationreduced variationWho standardized the work?Who standardi

32、zed the work? Availability of required tools (5S): Operators cannot be expected to maintain standard work if they are required to locate needed tools. Consistent flow of raw material: Operators cannot be expected to maintain standard work if they are hunting down needed parts. Visual alert of variat

33、ion in the process (visual factory):Operators, material handlers, and purchasing reps all need visual signals to keep “standard work” a standard. If they ca identify new lots of material or other variation, they can identify potential changes in the process. This visual check will assist in defect i

34、dentification and reduction. Identified and labeled in-process stock (5S): As inventory levels of in-process stock decrease, a visual signal should be sent to the material handlers to replenish this stock. Operators cannot maintain standard work without this.Pre-requisities for Standardized WorkWhat

35、 Is Kaizen? Definition: The philosophy of continual improvement: that every process can and should be continually evaluated and improved in terms of time required, resources used, resultant quality, and other aspects relevant to the process. Management support: Consider the corporate support, which

36、is why Six Sigma is a success in your organization. Measurable process: Without standardized work, we really wouldn t have a consistent process to measure. Cycle times would vary, assembly methods would vary, batches of materials would be mixed, etc. Analysis tools: In each organization, there are i

37、mprovement projects that cannot be solved by an operator. This is why we teach the analysis tools in the breakthrough strategy. Operator support: We, the overhead of the organization, need to understand that out future lies in the success of the value-added employees. Pre-requisities for KaizenWhat

38、Is Kanban? Kanban provides production, conveyance, and delivery information. In its purest form, the system will not allow any goods to be moved within the facility without an appropriate Kanban (or signal) attached to the goods. Kanban is the Japanese Word For a communication signal or card. This i

39、s typically a signal t begin work. Kanban is the technique used to “pull” products and material through and into the lean manufacturing system. The actual “Kanban” can be a physical signal such as an empty container or a small card.Prerequisties for a Successful Kanban System Improve setup procedure

40、s so they can be executed rapidly (the result of standardized work). Relatively stable demand cycle. The number of parts per Kanban (card) MUST be standard, and SHOULD be kept to as few as possible. If the process exhibits a large amount of variation (or defects), a Kanban system will not be success

41、ful. Zero defects should be sent to the assembly process. Consistent cycle times defined by standardized work. Material handlers must be trained in the organization of the transportation system, particularly in techniques for handling mixed loads, routing methods, and Kanban rules. Important Note: I

42、f implementation is attempted without providing for these preconditions, the system will not be able to sustain itself. This inherent lack of support will eventually lead to failure of the system and disillusionment among the operators and throughout the systemPre-Control Methodology Its use is not

43、restricted to a normally distributed process. The upper and lower control limits should be established based on the long-term capability of the process. The control limits are +/- 3s, where s is the long-term standard deviation of the process. Note: Green Zone: +/- 1.5s Yellow Zone: +/- 3.0s Red Zon

44、e: Beyond +/- 3.0s It is effective where the worker can measure and adjust a critical parameter. Rule 1: If the first part is green, take no action - continue to run. Rule 2: If the first part is yellow, check the second part: If the second part is green, go. If the second part is yellow on the same

45、 side, adjust. If the second part is yellow on the opposite side, stop. Rule 3: If any part is red, stop. Rule 4: The process is Qualified when five parts in a row are green.Rules of OperationGraphical Rules of LookSPCMain Points: All processes have natural variability (due to common causes) and unn

46、atural variability (due to special causes). We use SPC to monitor and/or improve the process. Attentive use of SPC can allow us to DETECT special cause variation through OUT-OF-CONTROL signals. Control limits are based on establishing +/- 3 sigma limits for the Ys or Xs being measured. Control chart

47、s CANNOT tell you WHY the process is out of control, only that it is.Individual X - Moving Range I-MRIndividual Moving range charts should be used for true Xs like temperature, humidity, concentration of a solution, or gas flow per minute: Low production volumes where only one piece is produced per

48、day or sometimes longer. High-cost testingwhen the cost of testing is very expensive, time consuming, destructive, or otherwise prohibitive. Chemical processing where only one measurement per bath is taken.I-MR ChartOften, only the X chart is evaluated for “in control,” using R only for chart constr

49、uction.ProsCons:Good where individual s data is most logically the “rational sub-group.”Shewwhat zone rules can be applied if individuals are normally distributed. Falsely suggests that not much data is required - best with 30 or more points Control limits tend to be very wide due to relatively smal

50、l sample sizes. I-MR Equations, Assumptions- Xi is the individual plot point.- Xbar is the average of the individuals and becomes the center line on the I chart. Xbar =S S Xi(sum of all individuals) / k(number of individuals)- Rm for this chart is called the moving range because it uses two (or more

51、) consecutive individual measurements for its high and low.- R bar is the average moving range and becomes the center line on the MR chart. R bar =S S Rmi (sum of all moving ranges for sub-group size n)/ K-n+1 (number of individuals - sub-group size + 1)- shat is the estimated process standard devia

52、tion shat = Rbar( computed above)/ d2 (table of constants for sub-group size n- Control limits are now calculated: UCLX = Xbar + E2Rbar UCLR = D4RbarLCRX = Xbar - E2Rbar LCLR = D3RbarIndividual and Moving Rang OutputI and MR Chart for Y 3Special Cause Tests for I-MR Charts Minitab can test for eight

53、 special causes that warrant further investigation. A, B, and C are zones at 3, 2, and 1 standard deviations from the center line. Sub-group sizes must be equal to use Tests in Minitab.Special Cause Tests For I-MR ChartsSpecial Cause Tests For I-MR ChartsMonitor Vs. Control Methods that monitor prod

54、uct characteristics are typically understood to be implemented on Ys. The idea is that we are not able to control the inputs of the process, thus we must continually monitor the outputs. Methods that control process characteristics are a statement of understanding causality. If you can “predict” the

55、 quality of the product outputs by measuring the process inputs, you are controlling the process. This module focuses on statistical tools that are used to monitor monitor product outputs (Ys). These are certainly NOT the only tools available. We have chosen several simple tools that work well on th

56、e shop floor. Keep in mind that the goal with control methods is always to mistake proof the inputs. With this in mind, monitoring methods should be viewed as a temporary containment.Sub-Grouping and Sampling Guideline Sample size (how many?) - Variables chart: between 5 and 10 if practical. - Attri

57、butes chart: 30 or more, depending on the probability of a defect occurring. Sample Frequency (how often?) - General rule: sample 10 times more often than the process goes out of control. - On-line monitoring methods offer real-time data on product as it is produced. - On-line control methods offer

58、real-time process control. Rational sub-groups (how homogeneous?) - Sub-groups should capture short-term variability. Analysis Method Step 1: Select the appropriate Y to chart. Step 2: Establish a rational Sub-group (frequency) and an appropriate sample size. Step 3: Select the appropriate control c

59、hart to use. Step 4: Implement the data-collection system Step 5: Calculate the center line and control limits. Step 6: Plot the data. Step 7: Check for out-of-Control (OOC) conditions. Step 8: Interpret findings investigate special cause variation, and make suggestions. P and nP Chart nP chart: A s

60、imple chart used to track the number of non-conforming units ( number of defective parts) Use when the sample size is constant. P chart: A simple chart used to track the number of non-conforming units. (percentage of defective parts). Use when the sample size is NOT necessary constant. The control l