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Statistical-Approach-to-Quality-Management.pptx

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Statistical Approach to Quality Management
Establishing the Quality Requirements  The first step for quality control is to understand, establish & accept the customers' quality requirements. This involves the following steps. 1. Getting customers specifications regarding the quality, 2. Referring our past performance, 3. Discussing with the Quality Control Department, 4. Discussing with the Production Department, 5. Giving the Feed Back to the customers, 6. Receiving the revised quality requirements customers, 7. Accepting the quality parameters. from the
Quality Management System Offline Quality Control (Testing) Physical Tests Chemical Tests Online Quality Control (Inspection) 3  Grey Fabric Inspection  Visual Appearance  Garments Defects Inspection etc.  GSM of Fabric  Rubbing Fastness  Pilling Test etc.  Shrinkage Test  Fastness to Water  pH Test etc.
Methods of quality control: Basically two methods are used for garments quality control – i) Testing ii) Inspection. Maximum garments manufacturers apply inspection method due to high cost of testing equipment.
Inspection: Inspection may be defined examination in relation to some standards. as the visual Objective: The main objectives of inspection are – i. Detection of defects. ii. Correcting the defects or defective garments. Inspection
Inspectio n Identify Defects Inform the Concerne d Authority Identify the Cause of Defect Rectify Defects 6 Inspection Loop Inspection Examining with Bare Eyes Grey Fabric Inspection 4-point inspection system, 10-point inspection system etc.
Steps of inspection in garments industry: 1. Piece goods quality control 2. Cutting quality control 3. In process quality control (Sewing) 4. Washing section 5. Quality control of finishing sections 6. Testing (Lab test)
4-Point Fabric Inspection System • ASTM D 5430–04 standard • This system is agreed by The American Society for Quality Control, Textile and Needle Trades Division • Evaluated by the number of defective points in one hundred square yards of fabrics. 8
Working Procedure Generally fabric inspection process is done by the fabric inspection machine. 9 Dirt’s mark/stain mark Weaving and knitting defects Slub and knots Holes Factors to be considered
Tools for Fabric Checking • D-65 light source (sunlight) / TL-84 light source at the inspection frame. • Measuring tape & scissor. • Stickers or masking tape to identify the faults. • Pick glass. • Master fabric sample or customer’s reference sample. • Fabric inspection form. • Digital camera for taking reference snaps. 1 0
Criteria for giving penalty points Defective Length Penalty Point Hole Penalty point Upto 3” 1 Upto 1” 2 3” to 6” 2 Above 1” 4 6” to9” 3 Over 9” 4 **The maximum penalty point for a single defect cannot be more than “4” 1 1
Point Calculation For an individual roll: • Points per 100 square yards = Total points for the roll x 3600 Inspected yards x cuttable fabric width (inch) • Points per 100 square meters= Total points for the roll x 100,000 Inspected meters x cuttable fabric width (MM) 1 2
1 3 Point Calculation • In general, acceptable level of ‘points per 100 linear yards’ or ‘points per 100 square yards’ are different for different fabric types. • For example:  For Cotton Twill/Denim: 28 points per 100 square yards (23 points per 100 square meters) for individual fabric roll.  For All synthetic fabrics: 20 point per 100 square yards (16 points per 100 square meters) for individual fabric roll.
Example A fabric roll 120 yards long and 46 inch wide contains following defects. 4 defects up to 3 inch length 4 x 1 4 points 3 defects from 3 to 6 inch length 3 x 2 6 points 2 defects from 6 to 9 inch length 2 x 3 6 points 1 defect over 9 inch length 1 x 4 4 points 1 hole over 1 inch 1 x 4 4 points Total defect points 24 Points Therefore, Points / 100 sq. yards: (24 X 3600) / (120 X 46) = 15.652 points / 100 sq. yards 1
Common Defects Found in Textile Fabrics Fabric Defects Source of Defects Fabric Defects Source of Defects Fabric Defects Source of Defects  Slubs,  Knots,  Broken filaments etc. • Flaws in yarns or filaments .  Missing end,  Oily or Soiled ends,  Floats,  Snarls,  Oil and strains,  Holes,  Selvedge defect etc. • Occur during weaving process.  Bleaching spots,  Dyestuff Stain,  Uneven dyeing,  Misprint,  Pilling and raising defects,  Faulty embroidery design etc. • Defects during fabric dyeing, machine embroidery and screen printing. 1 5
1 6
Traffic Light System in Garments: TLS System Standard Sample Size: 5 pieces. Garment Inspection to be done after every two hours. Color marking procedures: Circles will be filled with color GREEN: If found No defect YELLOW: If found 1 defect RED: If found 2 defects GREEN YELLOW RED 1 7 ***** The acceptance level is set by the Company.
Traffic Light System in Garments: TLS System
How to fill/use the format: • The above format is used for a single operator or workstation. A single sheet will keep the record for the whole month for an operator. • As a quality auditor, on the first day of the month, you have to fill details such as Operator name, Operation name, Line number, Floor number, and the name of the Month. • The format is displayed in two sections to cover 31 days (whole month). Write the date in the cells of the top row. • Each column contains 4 circles, represents four inspections in a day. After inspection fill the respective circle (date and number of inspection of the day).
Eligibility Criteria for a Quality Inspector • The person must be well educated. • The person must be physically fit. • He/She must be well versed with the inspection system. • A good vision is must. • He/She must not be colorblind. 2 0
Why Four Point System is Preferable for Fabric Inspection? • Very simple & easily applicable. • Easy to learn. • Easy to calculate. • Reliable. • Easy to Evaluate. • Internationally recognized inspection system. 2 1
AQL (Acceptable Quality Level ) A certain proportion of defectives will always occur in any manufacturing process. If the percentage does not exceed a certain limit, it will be economical to allow the defective to go through instead of screening the entire lot. This limit is called the "Acceptable Quality Level" ( AQL )
AQL (Acceptable Quality Level ) • In practice, three types of defects are goods, the distinguished. For most limits are: consumer – 0% for critical defects (totally unacceptable: a user might get harmed, or regulations are not respected). – 2.5% for major defects (these products would usually not be considered acceptable by the end user). – 4.0% for minor defects (there is some departure from specifications, but most users would not mind it).
12 AQL (Acceptable Quality Level ) Following inspection/audit is done to attainAQL. a)Process inspection: Garments are checked process wise in the finishing section to identify defects and pass only the passed garments. b)Two hourly audit: Every after two-hours audit is done on finishing lot to attainAQL the requiredAQL. c)Days final audit: At the end of the day accumulated lot of finished garments are statistically audited to attain requiredAQL. d)Lot final audit: On completion of packing of one complete lot of garment, QA manager conduct statistical audit based on required AQL garments. Garments are offered for final inspection by buyer /clients for shipment only when these are through in this audit.
Statistical Process Control: Definition  SPC stands for statistical process control. Statistical process cause variation from manufacturing, service and financial processes. SPC is a key continuous improvement tool.  It is a collection of tools that can result in process stability and variance reduction (process improvement) when used together.  Its also called statistical quality control (SQC). control is a scientific visual method used to monitor, control and improve processes by eliminating special
Application of SPC The application of SPC involves three main phases of activity: 1. Understanding the process and the specification limits. 2. Eliminating assignable (special) sources of variation, so that the process is stable. significant changes of mean or variation. 3. Monitoring the ongoing production process, assisted by the use of control charts, to detect
Limitations • SPC is applied to reduce or eliminate process waste. This, in turn, eliminates the need for the process step of post-manufacture inspection. • The success of SPC relies not only on the skill with which it is applied, but also on how suitable or amenable the process is to SPC. • In some cases, it may be difficult to judge when the application of SPC is appropriate.
Variation in manufacturing • In manufacturing, quality is defined as conformance to specification. However, no two products or characteristics are ever exactly the same, because any process contains many sources of variability. • In mass-manufacturing, traditionally, the quality of a finished article is ensured by post-manufacturing inspection of the product. Each article (or a sample of articles from a production lot) may be accepted or rejected according to how well it meets its design specifications.
Variation in manufacturing • In contrast, SPC uses statistical tools to observe the performance of the production process in order to detect significant variations before they result in the production of a sub-standard product/article. • Any source of variation at any point of time in a process will fall into one of two classes. 1. "Common Causes / non-assignable causes" 2. "Special Causes / assignable causes"
Variation in manufacturing • Common Causes: sometimes referred to as non-assignable, normal sources of variation. It refers to many sources of variation that consistently acts on process. These types of causes produce a stable and repeatable distribution over time. • Special Causes: sometimes referred to as assignable sources of variation. It refers to any factor causing variation that affects only some of the process output. They are often intermittent and unpredictable.
Objectives of Statistical Process Control (SPC) • Find out how much common cause variation the process has. • Find out if there is assignable cause variation. • Aprocess is in control if it has no assignable cause variation – Being in control means that the process is stable and behaving as it usually does.
Seven Management & Planning Tools • In 1976, the Union of Japanese Scientists and Engineers (JUSE) saw the need for tools to promote innovation, communicate information and successfully plan major projects. • A team researched and developed the seven new quality control tools, often called the seven management and planning tools, or simply the seven management tools.
What are the New Seven Q.C. Tools  Affinity Diagrams  Relations Diagrams  Tree Diagrams  Matrix Diagrams  Arrow Diagrams  Process Decision Program Charts  Matrix DataAnalysis
Elementary/Basic SPC Tools • Quality management is now extremely important for all organizations, especially for the textile and apparel industry as it struggles with competition from less developed countries that offer much cheaper products. • Tools for quality management can help companies in this industry to reduce costs, realize zero defects and thus achieve better results. • Furthermore, the application of the quality tools help companies to identify the causes of the problems and to manage that problems.
Relation Between New Seven Q.C. Tools and Basic Seven Tools Facts /activity Data Numerical Data V erbal Data Organize The Seven New Tools Information The Basic Seven Tools •Generate Ideas •Formulate plans •Analytical approach Define problem after collecting numerical data Define problem before collecting numerical data
Elementary SPC Tools / Seven Quality Tools • The Seven Tools – Histograms, – Pareto Charts, – Cause and Effect Diagrams, – Run Charts, – Scatter Diagrams, – Flow Charts, – Control Charts
Histograms 10/24/2016 Histogram Defined Ahistogram is a bar graph that shows frequency data. Histograms provide the easiest way to evaluate the distribution of data. It looks very much like bar chart. The data are represented as a series of rectangles. The width of a rectangle is the class interval and the area represents the class frequency.
Histograms Purpose: To determine the spread or variation of a set of data points in a graphical form How is it done?: • Collect data, 50-100 data point • Determine the range of the data • Calculate the size of the class interval • Divide data points into classes Determine the class boundary • Count # of data points in each class • Draw the histogram Stable process, exhibiting bell shape
Pareto Charts Lecture by Md. Syduzzaman- BUTex Pareto Chart Defined A pareto chart is a cumulative bar graph with longest bars on left and shortest to the right. The longest bar represents the most vital cause. Pareto charts are used to identify and prioritize problems to be solved. They are actually histograms aided by the 80/20 rule adapted by Joseph Juran. •Remember the 80/20 rule states that approximately 80% of the problems are created by approximately 20% of the causes.
Pareto Charts Purpose: Prioritize problems. How is it done? • Create a preliminary list of problem classifications. • Tally the occurrences in each problem classification. • Arrange each classification in order from highest to lowest • Construct the bar chart
Cause and Effect Diagrams • Cause and Effect Diagram Defined – The cause and effect diagram is also called the Ishikawa diagram or the fishbone diagram. – It is a tool for discovering all the possible causes for a particular effect. – The major purpose of this diagram is to act as a first step in problem solving by creating a list of possible causes. Machine Man Environment Method Material
Fishbone Diagram Purpose: Graphical representation of the trail leading to the root cause of a problem How is it done? • Decide which quality characteristic, outcome or effect you want to examine (may use Pareto chart) • Backbone –draw straight line • Ribs – categories/primary causes • Medium size bones –secondary causes • Small bones – root causes
Makes custome r wait Absent receiving party Working system of operators Customer Operator Fishbone diagram analysis Absent Out of office Not at desk Lunchtime Too many phone calls Absent Not giving receiving party’s coordinates Complaining Leaving a message Lengthy talk Does not know organization well Takes too much time to explain Does not understand customer
Scatter Diagrams • Scatter Diagrams Defined – Scatter Diagrams are used to study and identify the possible relationship between the changes observed in two different sets of variables.
Scatter Diagrams Purpose: To identify the correlations that might exist between a quality characteristic and a factor that might be driving it. • A scatter diagram shows the correlation between two variables in a process. – These variables could be a Critical To Quality (CTQ) characteristic. • Dots representing data points are scattered on the diagram. – The extent to which the dots cluster together in a line across the diagram shows the strength with which the two factors are related.
Scatter Diagrams How is it done?: • Decide which paired factors you want to examine. Both factors must be measurable on some incremental linear scale. • Collect 30 to 100 paired data points. • Find the highest and lowest value for both variables. • Draw the vertical (y) and horizontal (x) axes of a graph. • Plot the data • Title the diagram The shape that the cluster of dots takes will tell you something about the relationship between the two variables that you tested.
Scatter Diagrams • The variables are correlated, when one changes the other probably also changes. • Dots that look like they are trying to form a line, are strongly correlated.
Flow Charts • Flow Charts Defined – A flow chart is a pictorial representation showing all of the steps of a process.
Flow Charts Purpose: Visual illustration of the sequence of operations required to complete a task  Schematic drawing of the process to measure or improve.  Starting point for process improvement  Potential weakness in the process are made visual.  Picture of process as it should be. Toolbox How is it done?  Write the process step inside each symbol  Connect the Symbols with arrows showing the direction of flow -
Run Charts • Run Charts Defined – Run charts are used to analyze processes according to time or order. Performance Time
Run Charts Creating a Run Chart  Gathering Data  Some type of process or operation must be available to take measurements for analysis.  Organizing Data  Data must be divided into two sets of values X and Y . X values represent time and values of Y represent the measurements taken from the manufacturing process or operation.  Charting Data  Plot the Y values versus the X values.  Interpreting Data  Interpret the data and draw any conclusions that will be beneficial to the process or operation.
Control Charts • Control Charts Defined – Control charts are used to determine whether a process will produce a product or service with consistent measurable properties.
Control Charts Purpose: The primary purpose of a control chart is to predict expected product outcome. Benefits: • Predict process out of control and out of specification limits • Distinguish between specific, identifiable causes of variation • Can be used for statistical process control
Control Charts Individual X charts How is it done? • The data must have a normal distribution (bell curve). • Have 20 or more data points. Fifteen is the absolute minimum. • List the data points in time order. Determine the range between each of the consecutive data points. • Find the mean or average of the data point values. • Calculate the control limits (three standard deviations) • Set up the scales for your control chart. • Draw a solid line representing the data mean. • Draw the upper and lower control limits. • Plot the data points in time sequence.
Control Charts • Next, look at the upper and lower control limits. If your process is in control, 99.73% of all the data points will be inside those lines. • The upper and lower control limits represent three standard deviations on either side of the mean. • Divide the distance between the centerline and the upper control limit into representing deviations. three equal zones three standard
Control Charts  Strategy for eliminating assignable-cause variation:  Get timely data so that you see the effect of the assignable cause soon after it occurs.  As soon as you see something that indicates that an assignable cause of variation has happened, search for the cause.  Change tools to compensate for the assignable cause.  Strategy for reducing common-cause variation:  Do not attempt to explain the difference between any of the values or data points produced by a stable system in control.  Reducing common-cause variation usually requires making fundamental changes in your process
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Statistical-Approach-to-Quality-Management.pptx

  • 2. Establishing the Quality Requirements  The first step for quality control is to understand, establish & accept the customers' quality requirements. This involves the following steps. 1. Getting customers specifications regarding the quality, 2. Referring our past performance, 3. Discussing with the Quality Control Department, 4. Discussing with the Production Department, 5. Giving the Feed Back to the customers, 6. Receiving the revised quality requirements customers, 7. Accepting the quality parameters. from the
  • 3. Quality Management System Offline Quality Control (Testing) Physical Tests Chemical Tests Online Quality Control (Inspection) 3  Grey Fabric Inspection  Visual Appearance  Garments Defects Inspection etc.  GSM of Fabric  Rubbing Fastness  Pilling Test etc.  Shrinkage Test  Fastness to Water  pH Test etc.
  • 4. Methods of quality control: Basically two methods are used for garments quality control – i) Testing ii) Inspection. Maximum garments manufacturers apply inspection method due to high cost of testing equipment.
  • 5. Inspection: Inspection may be defined examination in relation to some standards. as the visual Objective: The main objectives of inspection are – i. Detection of defects. ii. Correcting the defects or defective garments. Inspection
  • 6. Inspectio n Identify Defects Inform the Concerne d Authority Identify the Cause of Defect Rectify Defects 6 Inspection Loop Inspection Examining with Bare Eyes Grey Fabric Inspection 4-point inspection system, 10-point inspection system etc.
  • 7. Steps of inspection in garments industry: 1. Piece goods quality control 2. Cutting quality control 3. In process quality control (Sewing) 4. Washing section 5. Quality control of finishing sections 6. Testing (Lab test)
  • 8. 4-Point Fabric Inspection System • ASTM D 5430–04 standard • This system is agreed by The American Society for Quality Control, Textile and Needle Trades Division • Evaluated by the number of defective points in one hundred square yards of fabrics. 8
  • 9. Working Procedure Generally fabric inspection process is done by the fabric inspection machine. 9 Dirt’s mark/stain mark Weaving and knitting defects Slub and knots Holes Factors to be considered
  • 10. Tools for Fabric Checking • D-65 light source (sunlight) / TL-84 light source at the inspection frame. • Measuring tape & scissor. • Stickers or masking tape to identify the faults. • Pick glass. • Master fabric sample or customer’s reference sample. • Fabric inspection form. • Digital camera for taking reference snaps. 1 0
  • 11. Criteria for giving penalty points Defective Length Penalty Point Hole Penalty point Upto 3” 1 Upto 1” 2 3” to 6” 2 Above 1” 4 6” to9” 3 Over 9” 4 **The maximum penalty point for a single defect cannot be more than “4” 1 1
  • 12. Point Calculation For an individual roll: • Points per 100 square yards = Total points for the roll x 3600 Inspected yards x cuttable fabric width (inch) • Points per 100 square meters= Total points for the roll x 100,000 Inspected meters x cuttable fabric width (MM) 1 2
  • 13. 1 3 Point Calculation • In general, acceptable level of ‘points per 100 linear yards’ or ‘points per 100 square yards’ are different for different fabric types. • For example:  For Cotton Twill/Denim: 28 points per 100 square yards (23 points per 100 square meters) for individual fabric roll.  For All synthetic fabrics: 20 point per 100 square yards (16 points per 100 square meters) for individual fabric roll.
  • 14. Example A fabric roll 120 yards long and 46 inch wide contains following defects. 4 defects up to 3 inch length 4 x 1 4 points 3 defects from 3 to 6 inch length 3 x 2 6 points 2 defects from 6 to 9 inch length 2 x 3 6 points 1 defect over 9 inch length 1 x 4 4 points 1 hole over 1 inch 1 x 4 4 points Total defect points 24 Points Therefore, Points / 100 sq. yards: (24 X 3600) / (120 X 46) = 15.652 points / 100 sq. yards 1
  • 15. Common Defects Found in Textile Fabrics Fabric Defects Source of Defects Fabric Defects Source of Defects Fabric Defects Source of Defects  Slubs,  Knots,  Broken filaments etc. • Flaws in yarns or filaments .  Missing end,  Oily or Soiled ends,  Floats,  Snarls,  Oil and strains,  Holes,  Selvedge defect etc. • Occur during weaving process.  Bleaching spots,  Dyestuff Stain,  Uneven dyeing,  Misprint,  Pilling and raising defects,  Faulty embroidery design etc. • Defects during fabric dyeing, machine embroidery and screen printing. 1 5
  • 16. 1 6
  • 17. Traffic Light System in Garments: TLS System Standard Sample Size: 5 pieces. Garment Inspection to be done after every two hours. Color marking procedures: Circles will be filled with color GREEN: If found No defect YELLOW: If found 1 defect RED: If found 2 defects GREEN YELLOW RED 1 7 ***** The acceptance level is set by the Company.
  • 18. Traffic Light System in Garments: TLS System
  • 19. How to fill/use the format: • The above format is used for a single operator or workstation. A single sheet will keep the record for the whole month for an operator. • As a quality auditor, on the first day of the month, you have to fill details such as Operator name, Operation name, Line number, Floor number, and the name of the Month. • The format is displayed in two sections to cover 31 days (whole month). Write the date in the cells of the top row. • Each column contains 4 circles, represents four inspections in a day. After inspection fill the respective circle (date and number of inspection of the day).
  • 20. Eligibility Criteria for a Quality Inspector • The person must be well educated. • The person must be physically fit. • He/She must be well versed with the inspection system. • A good vision is must. • He/She must not be colorblind. 2 0
  • 21. Why Four Point System is Preferable for Fabric Inspection? • Very simple & easily applicable. • Easy to learn. • Easy to calculate. • Reliable. • Easy to Evaluate. • Internationally recognized inspection system. 2 1
  • 22. AQL (Acceptable Quality Level ) A certain proportion of defectives will always occur in any manufacturing process. If the percentage does not exceed a certain limit, it will be economical to allow the defective to go through instead of screening the entire lot. This limit is called the "Acceptable Quality Level" ( AQL )
  • 23. AQL (Acceptable Quality Level ) • In practice, three types of defects are goods, the distinguished. For most limits are: consumer – 0% for critical defects (totally unacceptable: a user might get harmed, or regulations are not respected). – 2.5% for major defects (these products would usually not be considered acceptable by the end user). – 4.0% for minor defects (there is some departure from specifications, but most users would not mind it).
  • 24. 12 AQL (Acceptable Quality Level ) Following inspection/audit is done to attainAQL. a)Process inspection: Garments are checked process wise in the finishing section to identify defects and pass only the passed garments. b)Two hourly audit: Every after two-hours audit is done on finishing lot to attainAQL the requiredAQL. c)Days final audit: At the end of the day accumulated lot of finished garments are statistically audited to attain requiredAQL. d)Lot final audit: On completion of packing of one complete lot of garment, QA manager conduct statistical audit based on required AQL garments. Garments are offered for final inspection by buyer /clients for shipment only when these are through in this audit.
  • 25. Statistical Process Control: Definition  SPC stands for statistical process control. Statistical process cause variation from manufacturing, service and financial processes. SPC is a key continuous improvement tool.  It is a collection of tools that can result in process stability and variance reduction (process improvement) when used together.  Its also called statistical quality control (SQC). control is a scientific visual method used to monitor, control and improve processes by eliminating special
  • 26. Application of SPC The application of SPC involves three main phases of activity: 1. Understanding the process and the specification limits. 2. Eliminating assignable (special) sources of variation, so that the process is stable. significant changes of mean or variation. 3. Monitoring the ongoing production process, assisted by the use of control charts, to detect
  • 27. Limitations • SPC is applied to reduce or eliminate process waste. This, in turn, eliminates the need for the process step of post-manufacture inspection. • The success of SPC relies not only on the skill with which it is applied, but also on how suitable or amenable the process is to SPC. • In some cases, it may be difficult to judge when the application of SPC is appropriate.
  • 28. Variation in manufacturing • In manufacturing, quality is defined as conformance to specification. However, no two products or characteristics are ever exactly the same, because any process contains many sources of variability. • In mass-manufacturing, traditionally, the quality of a finished article is ensured by post-manufacturing inspection of the product. Each article (or a sample of articles from a production lot) may be accepted or rejected according to how well it meets its design specifications.
  • 29. Variation in manufacturing • In contrast, SPC uses statistical tools to observe the performance of the production process in order to detect significant variations before they result in the production of a sub-standard product/article. • Any source of variation at any point of time in a process will fall into one of two classes. 1. "Common Causes / non-assignable causes" 2. "Special Causes / assignable causes"
  • 30. Variation in manufacturing • Common Causes: sometimes referred to as non-assignable, normal sources of variation. It refers to many sources of variation that consistently acts on process. These types of causes produce a stable and repeatable distribution over time. • Special Causes: sometimes referred to as assignable sources of variation. It refers to any factor causing variation that affects only some of the process output. They are often intermittent and unpredictable.
  • 31. Objectives of Statistical Process Control (SPC) • Find out how much common cause variation the process has. • Find out if there is assignable cause variation. • Aprocess is in control if it has no assignable cause variation – Being in control means that the process is stable and behaving as it usually does.
  • 32. Seven Management & Planning Tools • In 1976, the Union of Japanese Scientists and Engineers (JUSE) saw the need for tools to promote innovation, communicate information and successfully plan major projects. • A team researched and developed the seven new quality control tools, often called the seven management and planning tools, or simply the seven management tools.
  • 33. What are the New Seven Q.C. Tools  Affinity Diagrams  Relations Diagrams  Tree Diagrams  Matrix Diagrams  Arrow Diagrams  Process Decision Program Charts  Matrix DataAnalysis
  • 34. Elementary/Basic SPC Tools • Quality management is now extremely important for all organizations, especially for the textile and apparel industry as it struggles with competition from less developed countries that offer much cheaper products. • Tools for quality management can help companies in this industry to reduce costs, realize zero defects and thus achieve better results. • Furthermore, the application of the quality tools help companies to identify the causes of the problems and to manage that problems.
  • 35. Relation Between New Seven Q.C. Tools and Basic Seven Tools Facts /activity Data Numerical Data V erbal Data Organize The Seven New Tools Information The Basic Seven Tools •Generate Ideas •Formulate plans •Analytical approach Define problem after collecting numerical data Define problem before collecting numerical data
  • 36. Elementary SPC Tools / Seven Quality Tools • The Seven Tools – Histograms, – Pareto Charts, – Cause and Effect Diagrams, – Run Charts, – Scatter Diagrams, – Flow Charts, – Control Charts
  • 37. Histograms 10/24/2016 Histogram Defined Ahistogram is a bar graph that shows frequency data. Histograms provide the easiest way to evaluate the distribution of data. It looks very much like bar chart. The data are represented as a series of rectangles. The width of a rectangle is the class interval and the area represents the class frequency.
  • 38. Histograms Purpose: To determine the spread or variation of a set of data points in a graphical form How is it done?: • Collect data, 50-100 data point • Determine the range of the data • Calculate the size of the class interval • Divide data points into classes Determine the class boundary • Count # of data points in each class • Draw the histogram Stable process, exhibiting bell shape
  • 39. Pareto Charts Lecture by Md. Syduzzaman- BUTex Pareto Chart Defined A pareto chart is a cumulative bar graph with longest bars on left and shortest to the right. The longest bar represents the most vital cause. Pareto charts are used to identify and prioritize problems to be solved. They are actually histograms aided by the 80/20 rule adapted by Joseph Juran. •Remember the 80/20 rule states that approximately 80% of the problems are created by approximately 20% of the causes.
  • 40. Pareto Charts Purpose: Prioritize problems. How is it done? • Create a preliminary list of problem classifications. • Tally the occurrences in each problem classification. • Arrange each classification in order from highest to lowest • Construct the bar chart
  • 41. Cause and Effect Diagrams • Cause and Effect Diagram Defined – The cause and effect diagram is also called the Ishikawa diagram or the fishbone diagram. – It is a tool for discovering all the possible causes for a particular effect. – The major purpose of this diagram is to act as a first step in problem solving by creating a list of possible causes. Machine Man Environment Method Material
  • 42. Fishbone Diagram Purpose: Graphical representation of the trail leading to the root cause of a problem How is it done? • Decide which quality characteristic, outcome or effect you want to examine (may use Pareto chart) • Backbone –draw straight line • Ribs – categories/primary causes • Medium size bones –secondary causes • Small bones – root causes
  • 43. Makes custome r wait Absent receiving party Working system of operators Customer Operator Fishbone diagram analysis Absent Out of office Not at desk Lunchtime Too many phone calls Absent Not giving receiving party’s coordinates Complaining Leaving a message Lengthy talk Does not know organization well Takes too much time to explain Does not understand customer
  • 44. Scatter Diagrams • Scatter Diagrams Defined – Scatter Diagrams are used to study and identify the possible relationship between the changes observed in two different sets of variables.
  • 45. Scatter Diagrams Purpose: To identify the correlations that might exist between a quality characteristic and a factor that might be driving it. • A scatter diagram shows the correlation between two variables in a process. – These variables could be a Critical To Quality (CTQ) characteristic. • Dots representing data points are scattered on the diagram. – The extent to which the dots cluster together in a line across the diagram shows the strength with which the two factors are related.
  • 46. Scatter Diagrams How is it done?: • Decide which paired factors you want to examine. Both factors must be measurable on some incremental linear scale. • Collect 30 to 100 paired data points. • Find the highest and lowest value for both variables. • Draw the vertical (y) and horizontal (x) axes of a graph. • Plot the data • Title the diagram The shape that the cluster of dots takes will tell you something about the relationship between the two variables that you tested.
  • 47. Scatter Diagrams • The variables are correlated, when one changes the other probably also changes. • Dots that look like they are trying to form a line, are strongly correlated.
  • 48. Flow Charts • Flow Charts Defined – A flow chart is a pictorial representation showing all of the steps of a process.
  • 49. Flow Charts Purpose: Visual illustration of the sequence of operations required to complete a task  Schematic drawing of the process to measure or improve.  Starting point for process improvement  Potential weakness in the process are made visual.  Picture of process as it should be. Toolbox How is it done?  Write the process step inside each symbol  Connect the Symbols with arrows showing the direction of flow -
  • 50. Run Charts • Run Charts Defined – Run charts are used to analyze processes according to time or order. Performance Time
  • 51. Run Charts Creating a Run Chart  Gathering Data  Some type of process or operation must be available to take measurements for analysis.  Organizing Data  Data must be divided into two sets of values X and Y . X values represent time and values of Y represent the measurements taken from the manufacturing process or operation.  Charting Data  Plot the Y values versus the X values.  Interpreting Data  Interpret the data and draw any conclusions that will be beneficial to the process or operation.
  • 52. Control Charts • Control Charts Defined – Control charts are used to determine whether a process will produce a product or service with consistent measurable properties.
  • 53. Control Charts Purpose: The primary purpose of a control chart is to predict expected product outcome. Benefits: • Predict process out of control and out of specification limits • Distinguish between specific, identifiable causes of variation • Can be used for statistical process control
  • 54. Control Charts Individual X charts How is it done? • The data must have a normal distribution (bell curve). • Have 20 or more data points. Fifteen is the absolute minimum. • List the data points in time order. Determine the range between each of the consecutive data points. • Find the mean or average of the data point values. • Calculate the control limits (three standard deviations) • Set up the scales for your control chart. • Draw a solid line representing the data mean. • Draw the upper and lower control limits. • Plot the data points in time sequence.
  • 55. Control Charts • Next, look at the upper and lower control limits. If your process is in control, 99.73% of all the data points will be inside those lines. • The upper and lower control limits represent three standard deviations on either side of the mean. • Divide the distance between the centerline and the upper control limit into representing deviations. three equal zones three standard
  • 56. Control Charts  Strategy for eliminating assignable-cause variation:  Get timely data so that you see the effect of the assignable cause soon after it occurs.  As soon as you see something that indicates that an assignable cause of variation has happened, search for the cause.  Change tools to compensate for the assignable cause.  Strategy for reducing common-cause variation:  Do not attempt to explain the difference between any of the values or data points produced by a stable system in control.  Reducing common-cause variation usually requires making fundamental changes in your process
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