What is the content of qc 7 techniques: relationship diagram method, kj method, system diagram method, matrix diagram method, matrix data analysis method, pdpc method, network diagram method?

QC 7 major techniques content what? \x0d\\new QC 7 techniques \x0d\1. Correlation Diagram Method - TQM implementation, Pointers Management, Quality Control Improvement, Production Mode, \x0d\ Production Management Improvement \x0d\2. KJ Method - Development, TQM implementation, QCC implementation, Quality Improvement \x0d\3. System Diagram Method - Development, Quality Assurance, Quality Improvement \x0d\4. Matrix Diagram Method - Development Quality Improvement, Quality Assurance \x0d\5. Matrix Data Analysis Method - Planning, Development, Engineering Analysis \x0d\6. PDPC Method - Planning, Quality Assurance, Safety Management, Trial Evaluation, Productivity Management \x0d\Improvement, Facility Management Improvement \x0d\7. Arrow Diagramming Method - Quality Design, Development, Quality Improvement \x0d\\new and old QC 7 Practices \\x0d\7. x0d\\\\x0d\1, QC seven techniques are divided into: \x0d\\\x0d\1, simple seven techniques: Gantt chart, flow chart, 5W2H, foolproof method, radar method, statistical charts, push charts \x0d\2, QC old seven techniques: Characteristics of the key factors analysis chart, Plato, checklist, layer method, scatter diagrams, histogram, control charts \x0d\3, QC new seven techniques: Guanlian diagram, systematic diagram method, KJ diagram, systematic diagram method, control charts \x0d\3, QC new seven techniques: Guanlian diagram, systematic diagram method, KJ diagram method, control charts, control charts, control charts. Diagram, System Diagram Method, KJ Method, Arrow Diagram Method, Matrix Diagram Method, PAPC Method, Matrix Data Analysis Method \x0d\ Counting value: the number of qualified, the number of shortcomings, etc. using the number of points to calculate the data is generally known as counting data. (Count a number) \x0d\ Measurement value: to the importance, time, content, length and other data that can be measured and obtained, generally known as the measurement of value, such as length, importance, concentration, there is a decimal point where rounding are called. (Measure a measure) \x0d\\\\x0d\4, QC seven techniques by five charts, a table and a method: \x0d\ five charts: Plato, scatterplot, histogram, control charts, characteristics of the key factors analysis chart (fishbone diagram) \x0d\\\x0d\a table: Checklist (Gantt Chart) \x0d\\a method: the method of layer method \x0d\\\x0d\2, to introduce the simple seven techniques: \x0d\\\\4, Gantt chart (Gantt chart) \x0d\4, QC seven techniques: the method of layer method. Gantt Chart: \x0d\1, Gantt Chart: \x0d\1, Work Schedule \x0d\2, Checking Work Progress \x0d\3, Keeping Track of the Status Quo \x0d\4, Daily Program Management \x0d\4, Progress Self-Management \x0d\4, It is one of the easiest and most effective ways to manage your progress. \x0d\\\\2, Statistical Chart (Bar Chart): \x0d\\\x0d\ Usage \x0d\\\1, Abnormal data at a glance. \x0d\\\\x0d\2, easy to compare against. \x0d\\\\x0d\3, easy to see the conclusion. \x0d\\Apply charts that can be seen in the most common newspapers and magazines. \x0d\\\\\x0d\ Apply to layer method. \x0d\\\\\x0d\3, Nudge Chart (Trend Chart): \x0d\\\x0d\ Uses \x0d\\\x0d\1, data to time change management use. \x0d\\\\x0d\2, can grasp the current situation, grasp the problem point. \x0d\\\\x0d\3, effect, difference comparison. \x0d\\ The easiest way to understand the differences in data, widely used. \x0d\\\\\\x0d\\\ substandard rates, nudge charts. \x0d\\\\\x0d\4, flowchart: \x0d\\\x0d\ Usage \x0d\\\x0d\1, representation of work content. \x0d\\\\\x0d\2, easy to grasp workstation. \x0d\\\\\x0d\3, for education and explanation. \x0d\\\ Work instructions, content of the easy way to show. \x0d\\\\\x0d\5, circle diagram: \x0d\\\x0d\ Usage \x0d\\\x0d\1, used to compare the proportion of the composition of each part. \x0d\\\\x0d\2, to clock the direction of rotation from the largest to the smallest arrangement, the circle into a number of sectors. \x0d\\\\x0d\3, a straightforward depiction of the proportion of each item. \x0d\\ Use the layer differentiation method. \x0d\\\\\x0d\3, Introducing the old seven methods: \x0d\\\x0d\1, CHECK LIST \x0d\\x0d\ Usage \x0d\\\\\x0d\1, for day-to-day management \x0d\\\\\x0d\2, for data collection \x0d\\\x0d\3, for improvement of management \x0d\helps each individual to complete the necessary data collection in the shortest possible time. Data Collection \x0d\\\\\2, Stratification: \x0d\\\\\x0d\ Usage \x0d\\\\x0d\1, Apply Stratification to find out the factors that cause discrepancies in the data, and then apply the right remedy. \x0d\\\\x0d\2, to 4M, every 1M layer. \x0d\1, borrow other graphs, no graphs of its own. \x0d\\\\\x0d\2, arranged from largest to smallest. \x0d\\\\\x0d\3, Plato (counting statistics): \x0d\\\x0d\borrowed from layer-by-layer graphs. \x0d\\\\x0d\\ by the production site after the collection of data, must be effectively analyzed, use, in order to become a human value data. Classifying, organizing, and charting this data to fully grasp the problem points and important reasons is an indispensable management tool nowadays. The most popular diagram for data management is Plato. \x0d\\\\x0d\\definition: 1) A graph that organizes and classifies data collected according to different criteria such as cause of defects, defective conditions, defective items, and location of defects, and seeks to identify the cause or location that accounts for the largest percentage of defects, and then arranges them in the order of their magnitude and adds the cumulative values. \x0d\\\\\x0d\2) from the Plato can see which item has a problem, its impact on how to determine where the problem is, and to take improvement measures for the problem point, so also known as the ABC chart, (analyze the control of the previous 2-3 important items.) \x0d\\\\\x0d\3) And because the chart is arranged in order of size, it can also be called an arrangement chart. \x0d\\\\\x0d\4) Instructions for making a Plato: \x0d\\\x0d\A Decide on the items to be categorized in the data \x0d\\\\x0d\a Categorization of the results includes bad items, places, time, and works. \x0d\\\x0d\b Categorization of causes includes material aliasing (manufacturer, composition, etc.). The way don't (operating conditions, procedures, methods, environment, etc.), people (age, proficiency, experience, etc.), equipment don't (machinery, tools, etc.). \x0d\\\\x0d\ classified items must be in line with the crux of the problem, the general classification of the first from the results of the classification, in order to understand the location of the problem, and then carry out a cause analysis, analyze the causes of the problem, in order to take effective countermeasures. The results of this analysis are plotted on a plat map according to the results and causes. \x0d\\\\x0d\B Decide on the period of time for which the data will be collected and collect the data by categorized items within the period. \x0d\\\\x0d\B Consider the situation in which the problem occurs, and select the appropriate period (e.g., a day, a week, a month, a quarter, or a year as the period) from which to collect data. \x0d\\\\\x0d\C Organize the data by category and make statistical tables. \x0d\\\x0d\a Arrange the items in the order of occurrence of the data, with the other items in the last order, and find the cumulative number of items. (The other items must not be larger than the first three, and if they are larger, they should be subdivided). \x0d\\\\\x0d\b Find the degree of influence of the cumulative number of ratios accounted for by the data of each item. \x0d\\\\\\x0d\c Other items are ranked last, if they are too large, it is necessary to review whether there are other important factors that need to be raised. \x0d\\\\x0d\\\\defective rate (%) = number of defects ÷ total number of inspections * 100 \x0d\\\x0d\\affect (%) = number of defects ÷ total number of defects * 100 \x0d\\x0d\\d\D Recorded on graph paper and drawn as a bar chart according to the size of the data. \x0d\\\x0d\a Record the vertical and horizontal axes on chart paper. The left side of the vertical axis is filled with the number of defects, the defect rate, or the amount of loss, and the right side of the vertical axis is scaled to indicate the cumulative impact (ratio); 100% is scored at the top, and the left side is scaled appropriately according to the size of the data collected. The horizontal axis is filled with the names of the categorized items, which are entered from left to right according to their percentage size, while the other items are recorded on the far right. \x0d\\\x0d\b The horizontal and vertical axes should be appropriately proportioned and the horizontal axis should not be longer than the vertical axis. \x0d\\\x0d\E Plotting the cumulative curve: \x0d\\\x0d\a Cumulative number of defects (or cumulative defective rate) at point \x0d\x0d\a. \x0d\\\x0d\b Connect with a broken line. \x0d\\\\x0d\f Plot the cumulative rate: \x0d\\x0d\a Plot the line to the right of the vertical axis ending at 100%. \x0d\\\x0d\b Divide the line from 0 to 100% into 10 equal divisions and write down the % divisions (i.e., cumulative influence). \x0d\\\x0d\c Mark whether the cumulative impact of the first three (or four) items is >80% or close to 80%. \x0d\\\\x0d\j Enter the necessary items: \x0d\\\x0d\a Title (purpose). \x0d\\\x0d\b Period of data collection. \x0d\\\x0d\c Data totals (total inspections, number of defects, defect rate? etc.). \x0d\\\x0d\d Project别. \x0d\\\x0d\e Composer (including recorder, plotter?). \x0d/\x0d/\e \x0d\\\\x0d\\ Drawing Notes: 1) The horizontal axis of the Plato is arranged by project in ascending order of magnitude, with [other] items in the last position. \x0d\\\\\x0d\2) The width of the bar chart of the Plato's should be the same, and the ratio of the vertical axis to the horizontal axis is 3:2. \x0d\\\x0d\3) The highest point of the vertical axis is the total number of defects, and the distance between the representations is the same. \x0d\\\\x0d\4) When there are too many items with a small number of times, the latter items can be considered to be grouped into [other] items; the other items should not be larger than the previous ones, and if they are larger than that, they should be analyzed again. Sometimes, changing the stratification or categorization method can also reduce the number of categorized items. Usually, the item categories including other items to not more than 4~6 items as a principle. \x0d\\\\\x0d\5) Comparison before and after improvement: \x0d\\\x0d\a After improvement, the horizontal axis items are arranged in order of appearance from high to low. \x0d\\\x0d\b Comparison benchmarks before and after must be the same, and the scale should be the same, it is easier to compare. \x0d\\\x0d\4, control charts: \x0d\\\x0d\(1) What is a control chart: \x0d\\x0d\ for the quality of the scene to achieve what we call "management" operations, generally to detect the product's \x0d\\x0d\quality characteristics instead of "management" operations. "Management" operation is normal or not, and the quality characteristics are with time, various conditions have high and low changes; then exactly how high or low to what condition is considered abnormal? Therefore, to set a reasonable high and low boundaries, as we detect the site process conditions in the "management" state, that is, the basic root of the control chart. \x0d\\\x0d\\ Control Chart was invented in 1924 by American quality control guru, Dr. Huey Hart. It is a graphical representation of the time sequence \x0d\\\x0d\ of the actual product quality characteristics compared to the control limits of the process capability as judged by past experience. \x0d\\\\\x0d\(2) Basic Characteristics: \x0d\\\x0d\ General control charts are generally set up for the vertical axis of the quality characteristics of the product, with the data of the process changes as the index; the horizontal axis is the group code, number, or year, month and day of the test product, and so on, and the points are plotted on the chart in the order of time or the manufacturing sequence. \x0d\\\x0d\ There are three straight horizontal lines on the control chart, the middle one is the Center Line (CL), which is generally drawn as a solid blue line. One of the upper left is called the upper control limit (Upper Control Limit, UCL), in the lower part of the control is called the lower control limit (Lower Control Limit, LCL), on the upper and lower control boundaries of the drawing, are generally used in the red dotted line of the performance of the acceptable range of variation; as for the actual product quality characteristics of the point of the even line is mostly in black. The actual product quality characteristics of the dotted lines are mostly drawn in black solid lines. \x0d\\\\x0d\(3) control chart principle: \x0d\\\x0d\1) the formation of quality variation causes \x0d\\\x0d\generally in the manufacturing process, no matter how sophisticated equipment, the environment, the quality of the characteristics of the changes will certainly be made, can never be done exactly the same products; and the cause of change can be divided into two kinds of reasons, one for the accidental (opportunity) reasons, one for the abnormal (non-opportunity) reasons. （The causes of variation can be divided into two types, one for chance (opportunity) causes and one for abnormal (non-chance) causes. \x0d\\\\x0d\2) Control chart boundaries of the composition: \x0d\\\x0d\control chart is based on the theory of constant distribution of the three standard deviations, the center line for the average, the upper and lower control boundaries of the average plus or minus three standard deviations (± 3σ) of the value, in order to determine whether there are problems occurring in the process, which is the method created by Dr. Hueyhart. \x0d\\\\x0d\(4) Types of control charts: \x0d\\\x0d\1) Classification according to the nature of the data: \x0d\\x0d\A Measurement Value Control Chart: The so-called measurement value refers to the control chart of the data belong to the actual measurement by the gauge; for example, length, weight, concentration and other characteristics of the continuity of the person. Commonly used: \x0d\\\x0d\a Mean and distance control chart (X (-)-R Chart) \x0d\\x0d\b Mean and standard deviation control chart (X (-)-σChart) \x0d\\x0d\c Median and distance control chart (X (~)-R Chart) \x0d\x0d\c Median and distance control chart (X (~)-R Chart) \x0d\\x0d\c Median and distance control chart (X (~)-R Chart) \x0d\\x0d\d Individual Value and Shift Overall Distance Chart (X-Rm Chart) \x0d\x0d\e Maximum Value and Minimum Value Chart (L-S Chart) \x0d\\x0d\B Counter Value Control Chart: The so-called Counter Value refers to the control chart of data belonging to the unit of the calculation of the number of people; for example, the number of defects, the number of flaws, and other intermittent data belongs to it. Commonly used are: \x0d\\\x0d\a defect rate control chart (P chart) \x0d\\x0d\b defects control chart (Pn chart, also known as np chart or d chart) \x0d\\\x0d\c defects control chart (C chart) \x0d\\x0d\d unit defects control chart (U chart) \x0d\ \x0d\2) Comparison of the Application of Count and Measurement Charts \x0d\\\x0d\measurement \x0d\count \x0d\measurement \x0d\ count \x0d\\x0d\advantages \x0d\\1, very sensitive, easy to investigate the true cause. \x0d\\\\x0d\2, can respond to defects in a timely manner, so that the quality can be stabilized. \x0d\1, the required data can be obtained in a simple way. \x0d\\\\\x0d\2, easier to understand the overall quality situation. \Disadvantages \x0d\\\1, sampling is more frequent and time-consuming. \x0d\\\\\2, the data must be measured, and then calculated, must be trained personnel can be competent. \x0d\1, can not find the real cause of the problem. \x0d\\\\\2, Timeliness is not enough, easy to delay. \x0d\\\\x0d\(5) Drawing of Control Chart: \x0d\\\x0d\introduction: Measurement Value Control Chart (X-R) Commonly used \x0d\\\x0d\1) Collect more than 100 pieces of data first, and arrange them according to the order of measurement. \x0d\\\\x0d\2) Take 2~5 data as a group (usually 4~5) and divide them into about 20-25 groups. (\x0d\\\\x0d\3) Record each group of data into the data table field. \x0d\\\\x0d\4) Calculate the mean value of each group X. (Take to the next digit of the smallest unit of measurement) \x0d\\\x0d\5) Calculate the full distance R of each group. (Maximum value - minimum value = R) \x0d\\\x0d\6) Calculate the total mean X. \x0d\\x0d\X=(X1+X2+X3+? +Xk)/k=ξXi/k (k is the number of groups) \x0d\\\x0d\7) Calculate the average of the full distance R: \x0d\\x0d\R=(R1+R2+R3+? +Rk)/k=ξRi/k \x0d\\\x0d\8) Calculate the control limits \x0d\\\x0d\X control chart: centerline (CL)=X \x0d\\x0d\upper control limit (UCL)=X+A2R \x0d\x0d\lower control limit (LCL)=X-A2R \x0d\\x0d\R control chart: centerline (CL)=R \x0d\x0d\R control chart: centerline (CL)=R \x0d\\x0d\R control chart: centerline (CL)=R \x0d\\\x0d\R control chart: center line (CL) = R \x0d\\x0d\Upper control limit (UCL) = D4R \x0d\\x0d\Lower control limit (LCL) = D3R \x0d\\x0d\\A2, D3, D4, the value of the sample size of each group, but still follow the principle of the three standard deviations, the calculation of the results, has been organized into a table of commonly used coefficients. \x0d\\\\\x0d\9) Plot the centerline and control limits, and include the points in the diagram. \x0d\\\\\x0d\10) Record each data history and special reasons for checking, analyzing and judging. \x0d\\\\\x0d\(6) Guidelines for drawing control points: \x0d\\\x0d\1) The name of each project, the control characteristics, the measurement unit, the equipment type, the operator, the size of the sample, the material type, the change in the environment, etc. should be clearly entered. Any changes in the data should be clearly filled in so that the data can be analyzed and organized. \x0d\\\x0d\2) Measurement value change control chart (X-R, X-R?, etc.) its X control chart and R control chart control boundary mat width taking method, the general principle of the group of the number of samples (n) as a reference, the X control chart of the unit of the degree of control chart for the R control chart of about 1 / n times. \x0d\\\\x0d\\(Vertical axis control limits width of about 20-30m/m; horizontal axis of each group spacing of about 2-5mm) \x0d\\x0d\3) Center line (CL) is recorded in the solid line, the control limits are recorded in the dotted line; each line must be recorded in accordance with the line of the CL, UCL, LCL, and other symbols. \x0d\\\\\x0d\4) The number of digits of CL, UCL, and LCL is calculated to be two digits more than the measured value. \x0d\\\\\x0d\\(The average number of digits calculated for each group of data is one digit more than the measured value.) \x0d\\\x0d\5) Points are drawn with [?] , [○], [△], [×]? etc., preferably standardized by the factory. \x0d\\\\\x0d\6) Variable control charts, two control charts drawn at least 20mm apart, if possible, preferably about 30mm apart. \x0d\\\\x0d\(7) Interpretation of control charts: \x0d\\\x0d\1) Judgment of control status (process in steady state) \x0d\\x0d\A Most of the dots are concentrated near the centerline. \x0d\\x0d\B A few dots fall near the control limits. \x0d\\\x0d\C The distribution and beating of the dots is random and irregular. \x0d\\\\x0d\D No dots fall outside the control limits. \x0d\\\\\x0d\2) Whether the control limit can be extended as a benchmark for subsequent process control: \x0d\\\x0d\A Consecutively, more than 25 dots appear within the control limit line (93.46% chance). \x0d\\\x0d\B Out of 35 consecutive points, no more than 1 point appears outside the control line. \x0d\\\x0d\C Out of 100 consecutive points, when there are no more than 2 dots outside the control limits. \x0d\\\\x0d\\C When the process meets the above conditions, although it can be considered that the process is under control and the control limits will not be changed, it is not acceptable for the points to be outside the control limits; there must be an abnormal reason for the exceeding of the control limits, therefore, the cause should be investigated and eliminated. \x0d\\\\x0d\3) Principles of Inspection and Interpretation: \x0d\\\x0d\A Each point should be regarded as a distribution, not just a point. \x0d\\\x0d\B The movement of the dots represents the change of the process; even if there is no abnormal cause, the dots may still have differences within the boundaries. \x0d\\\\x0d\C General principles of abnormality checking: (as shown in the figure) \x0d\\\x0d\(8) Precautions for the use of control charts: \x0d\\\x0d\1) Before the use of the control charts, the on-site work should be completed by standardized work. \x0d\\\\\x0d\2) Before the use of control charts, it is necessary to decide on the control items, including the selection of quality characteristics and the number of samples to be taken. \x0d\\\\\x0d\3) Control limits should never be replaced by specification values. \x0d\\\\\\x0d\4) The selection of the type of control chart should be matched with the decision of the control item. \x0d\\\\\\x0d\5) Sampling method should be based on the principle of obtaining a reasonable sample group. (\x0d\\\\\\x0d\6) If the points exceed the limit or have abnormal status, it is necessary to utilize all kinds of measures to improve or cooperate with statistical methods to find out the cause of the abnormality and eliminate it at the same time. \x0d\\\\\x0d\7) The size of the group (n) in the X-R control chart, generally n=4-5 is the most suitable. \x0d\\\\\x0d\8) R-control chart has no lower limit, because the R value is obtained by subtracting the minimum value from the maximum value of the same group of data, so it is meaningless to take a negative value of the LCL. (\x0d\\\\x0d\9) process control is not done well, control charts are useless, to make the control charts effective, should make the product process capability in the Cp value (process precision) is greater than 1 or more