Quality Journey -Introduction to 7QC Tools2.0.pdf
- 1. Quality Journey by Nilesh Jajoo Quality Journey Session -1 Introduction to 7QC Tools
- 2. Quality Journey by Nilesh Jajoo Quality Journey QualityControl 1930’s Qualityassurance & QualityCircle 1960’s TQM 1970’s Six Sigma 1980’s ISO 1990’s COPC VSM FMEA Poka -Yoke 5S KANO PDCA 7QC Tool
- 3. Quality Journey by Nilesh Jajoo Quality Definition Quality is defined from customer’s point of view as anything that enhance their satisfaction William Edwards Deming ( Oct 14,1900– Dec 20 1993) Fitness for use .Those product features which meet the needs of customer and there by provide product satisfaction .Freedom from deficiencies Joseph Moses Juran ( Dec 24, 1904 -- Feb 28 , 2008) My Definition :- Doing the right thing , right at first time and every time,meeting customer’s & investor’s expectations .
- 4. Quality Journey by Nilesh Jajoo Myth about Quality :- Cost of Quality Higher the Quality Higher the Cost Higher the Quality Lower the Cost Cost of waste Cost ofRework Cost of overproduction Myth Fact
- 5. Quality Journey by Nilesh Jajoo Cant be measured cant be improved 350 400 450 500 550 600 Something which can’t be measured Can’t be Improved Repeat Quality AHT CSAT/SSAT NPS FCR Weight Speed Height Temperature Shrinkage Attrition
- 6. Quality Journey by Nilesh Jajoo 7 QC Tool Process Flow Diagram Scatter Diagram Control Charts Cause and Effect Diagram Pareto Chart Histogram Check Sheet A structured, prepared form for collecting and analyzing data; a generic tool that can be adapted for a wide variety of purposes. The most commonly used graph for showing frequency distributions, or how often each different value in a set of data occurs. (also called as Vital Few Trivial Many) : Shows on a bar graph which factors are more significant (also called Ishikawa or fishbone chart): Identifies many possible causes for an effect or problem and sorts ideas into useful categories. Graphs used to study how a process changes over time. Graphs pairs of numerical data, one variable on each axis, to look for a relationship A pictorial presentation of the process flow , helping in identifying the input and output for each activity in the process
- 7. Quality Journey by Nilesh Jajoo Check Sheet When to Use a Check Sheet When data can be observed and collected repeatedly by the same person or at the same location. When collecting data on the frequency or patterns of events, problems, defects, defect location, defect causes, etc. When collecting data from a production process. Check Sheet Procedure Decide what event or problem will be observed. Develop operational definitions. Decide when data will be collected and for how long. Design the form. Set it up so that data can be recorded simply by making check marks or Xs or similar symbols and so that data do not have to be recopied for analysis. Label all spaces on the form. Test the check sheet for a short trial period to be sure it collects the appropriate data and is easy to use. Each time the targeted event or problem occurs, record data on the check sheet Example :- Quality audit format CSAT RCA format Repeat RCA format Time and motion
- 8. Quality Journey by Nilesh Jajoo Histogram(1) When to Use a Histogram • When the data are numerical. • When you want to see the shape of the data’s distribution, especially when determining whether the output of a process is distributed approximately normally. • When analyzing whether a process can meet the customer’s requirements. • When analyzing what the output from a supplier’s process looks like. • When seeing whether a process change has occurred from one time period to another. • When determining whether the outputs of two or more processes are different. • When you wish to communicate the distribution of data quickly and easily to others. Typical Histogram Shapes and What They Mean Normal. A common pattern is the bell–shaped curve known as the “normal distribution.” In a normal distribution, points are as likely to occur on one side of the average as on the other. Be aware, however, that other distributions look similar to the normal distribution. Statistical calculations must be used to prove a normal distribution. Don’t let the name “normal” confuse you. The outputs of many processes—perhaps even a majority of them—do not form normal distributions, but that does not mean anything is wrong with those processes. For example, many processes have a natural limit on one side and will produce skewed distributions. This is normal — meaning typical — for those processes, even if the distribution isn’t called “normal”!
- 9. Quality Journey by Nilesh Jajoo Histogram(2) Skewed.:- The skewed distribution is asymmetrical because a natural limit prevents outcomes on one side. The distribution’s peak is off center toward the limit and a tail stretches away from it. For example, a distribution of analyses of a very pure product would be skewed, because the product cannot be more than 100 percent pure. Other examples of natural limits are holes that cannot be smaller than the diameter of the drill bit or call-handling times that cannot be less than zero. These distributions are called right – or left–skewed according to the direction of the tail. Double-peaked or bimodal. The bimodal distribution looks like the back of a two-humped camel. The outcomes of two processes with different distributions are combined in one set of data. For example, a distribution of production data from a two-shift operation might be bimodal, if each shift produces a different distribution of results. Stratification often reveals this problem. Plateau Edge peak Comb. Truncated or heart-cut..
- 10. Quality Journey by Nilesh Jajoo Pareto (80/20 principle) The Pareto analysis is also known as the 80/20 rule because it is based on the idea that 80 percent of a project's benefit can come from doing 20 percent of the work. Conversely, 80 percent of a situation's problems can be traced to 20 percent of the causes. When to Use a Pareto Chart When analyzing data about the frequency of problems or causes in a process. When there are many problems or causes and you want to focus on the most significant. When analyzing broad causes by looking at their specific components. When communicating with others about your data. Pareto Chart Procedure Pareto analysis begins by ranking problems from highest to lowest in order to fix priority The cumulative number of problems is plotted on the vertical axis of the graph against the cause/phenomenon Pareto by Causes e.g. Man, Machine, Method etc. Pareto by Phenomenon e.g. Quality ,Cost, Delivery Tells about the relative sizes of problems indicates an important message about biggest few problems, if corrected, a large % of total problems will be solved
- 11. Quality Journey by Nilesh Jajoo Fish Bone (Cause and Effect) Process Policy People Plant Effect Cause Cause • EFFECT is “WHAT?”Happens • CAUSE is “WHY?” it Happens • EFFECT = RESULT OR OUTCOME • CAUSE = REASON(S) OR FACTOR(S) CONTRIBUTING TO THE EFFECT 5 WHY’s is the additional process aligned People Policy Procedure Plant Environment ISHIKAWA DIAGRAM or FISH BONE DIAGRAM The cause and effect diagram was developed by Dr. K. ISHIKAWA to represent the relationship between EFFECT or PROBLEM and all the possible CAUSES influencing it. For every EFFECT there are likely to be several CAUSES. The major causes can be summarized generally under four categories known as 4M’s —MAN,MACHINE,MATERIAL & METHOD, OR 4P’s – PLANT,POLICY,PEOPLE,PROCEDURE
- 12. Quality Journey by Nilesh Jajoo Process Flow When to Use a Flowchart • Todevelop understanding of how a process is done. • Tostudy a process for improvement. • Tocommunicate to others how a process is done. • When better communication is needed between people involved with the same process. • Todocument a process. • When planning a project Start /End Preparation Display Y N Process Decision Predefine Process Data storage Documents Delay Commonly used symbols Manual Input Extract • Testingthe Flow • Arethe processstepsidentifiedcorrectly? • Isevery feedbackloopclosed? • Does every arrowhaveabeginningandendingpoint? • Isthere morethanonearrow from anyactivitybox? Perhapsit couldbea diamond. • Areallthe stepscovered? Important Points
- 13. Process Flow (sample) Customer calls Call Answered? No Yes Enter customerdetails in the system Take order details Confirm payment type Credit card? Take card details Yes No Deliver & collect money, if non-credit card customer Dispatch Order Activity :-Practice Process Flow
- 14. Quality Journey by Nilesh Jajoo Control Chart (1) The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data. By comparing current data to these lines, you can draw conclusions about whether the process variation is consistent (in control) or is unpredictable (out of control, affected by special causes of variation). Control charts for variable data are used in pairs. The top chart monitors the average, or the centering of the distribution of data from the process. The bottom chart monitors the range, or the width of the distribution. If your data were shots in target practice, the average is where the shots are clustering, and the range is how tightly they are clustered. Control charts for attribute data are used singly. When to Use a Control Chart When controlling ongoing processes by finding and correcting problems as they occur. When predicting the expected range of outcomes from a process. When determining whether a process is stable (in statistical control). When analyzing patterns of process variation from special causes (non-routine events) or common causes (built into the process). When determining whether your quality improvement project should aim to prevent specific problems or to make fundamental changes to the process.
- 15. Quality Journey by Nilesh Jajoo Control Chart (2) 80% 78% 82% 84% 86% 88% 90% Wk1 Wk2 Wk3 Wk4 Wk5 Wk6 Wk7 Wk8 Wk9 Wk10 Control Chart USL Target LSL NPS USL LSL Target Special Cause Special Cause USL :- Upper Specified limit --An upper specification limit, also known as an upper spec limit, or USL, is a value below which performance of a product or process is acceptable LSL :- Lower Specified limit --A lower specification limit is a value above which performance of a product or process is acceptable. This is also known as a lower spec limit or LSL UCL :- Upper Control limit LCL :- Lower Control limit
- 16. Quality Journey by Nilesh Jajoo Scatter Diagram Definition :- Scatter plots are used to plot data points on a horizontal and a vertical axis in the attempt to show how much one variable is affected by another. Each row in the data table is represented by a marker whose position depends on its values in the columns set on the X and Y axes. When to Use a Scatter Diagram When you have paired numerical data. When your dependent variable may have multiple values for each value of your independent variable. When trying to determine whether the two variables are related, suchas… Connected tool to Scatter Diagram :- Correlation
- 17. Quality Journey by Nilesh Jajoo