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1. DEFINITION of 'Quality Control' A process through which a business seeks to ensure that product quality is maintained or improved and manufacturing errors are reduced or eliminated. Quality control requires the business to create an environment in which both management and employees
creating benchmarks for product quality, and testing products to check for statistically significant variations.
A major aspect of quality control is the establishment of well-defined controls. These controls help standardize both production and reactions to quality issues. Limiting room for error by specifying which production activities are to be completed by which personnel reduces the chance that employees will be involved in tasks for which they do not have adequate training.
2. Importance of quality control Quality control is essential to building a successful business that delivers products that meet or exceed customers’ expectations. It also forms the basis of an efficient business that minimizes waste and operates at high levels of productivity. A quality control system based on a recognized standard, such as ISO 9001 published by the International Organization for Standardization, provides a strong foundation for achieving a wide range of marketing and operational benefits.
3. Competitiveness The ability to offer customers quality products provides a strong competitive advantage. Quality helps you to win business from competitors who are not able to match your standards and gives you the opportunity to charge premium prices for a superior product. It can also open new business opportunities in market sectors where quality is critical.
4. Customer Loyalty Providing the market with quality products helps to increase customer satisfaction and loyalty. Satisfied customers have confidence that your products will continue to provide reliable performance in the future, and that increases the likelihood that they will buy from you again. Satisfied customers may also recommend your products to other companies, either directly or by providing testimonials that you can use in your marketing communications.
5. Reputation Quality makes an important contribution to your company’s reputation, particularly with the growth of social media. Customers share their views on products and services on product review sites and social media, such as Face book. Positive reviews and comments can reinforce your own marketing efforts, but quality problems can have a damaging effect on your reputation if the word spreads. A major quality issue, such as a product recall, may also attract media attention, causing further damage.
6. Compliance Compliance with recognized quality standards may be essential for doing business with certain groups of customers. If you are part of a supply chain, for example, the lead manufacturer may impose consistent quality standards on all members of the chain. Some customers aim to reduce or eliminate the cost of inspecting incoming components or materials by insisting that their suppliers implement the same quality system. If you operate in a regulated sector, such as chemicals or food, you may have to comply with industry quality standards.
Quality control can help to reduce your production and product support costs. A quality control system helps to lower levels of waste and rework, cutting costs and improving productivity and production efficiency. Delivering quality products can also reduce the number of returns you have to handle or the cost of repairing or servicing products in the field.
Benefits of Using Quality Control in Manufacturing The most obvious beneficiary of quality control is the customer, who receives a highquality product. This in turn benefits the company by ensuring customer satisfaction, which leads to repeat business, customer loyalty, and spreading the word about the quality of the company's product. Therefore, quality control in manufacturing pays off for a company in both reputation and revenue. Companies with quality control procedures in place are far less likely to face product recalls or safety hazards from poorly constructed products. The cost associated with these recalls can be steep: In 2009, Toyota had to recall 12.4 million cars for sticky gas pedals and floor mats that could jam accelerators, at a cost of approximately $2 billion. This could have been avoided had quality control been properly implemented.
Methods of quality control Old 7 tools
Paretochart Fishbonediagram Controlchart Histogram check sheet Scatterdiagram Stratification (flow chart or run chart)
Feature of this tools: Dataorientation:Focuson numericaldatameasure andcalculation
1) Pareto chart or Pareto diagram A Pareto chart is a bar graph. The lengths of the bars represent frequency or cost (time or money), and are arranged with longest bars on the left and the shortest to the right. In this way the chart visually depicts which situations are more significant.
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
Decide what categories you will use to group items. Decide what measurement is appropriate. Common measurements are
frequency, quantity, cost and time. Decide what period of time the Pareto chart will cover: One work cycle? One
full day? A week? Collect the data, recording the category each time. (Or assemble data that
already exist.) Subtotal the measurements for each category. Determine the appropriate scale for the measurements you have collected. The maximum value will be the largest subtotal from step 5. (If you will do optional steps 8 and 9 below, the maximum value will be the sum of all
subtotals from step 5.) Mark the scale on the left side of the chart. Construct and label bars for each category. Place the tallest at the far left, then the next tallest to its right and so on. If there are many categories with small
measurements, they can be grouped as “other.” Steps 8 and 9 are optional but are useful for analysis and communication. Calculate the percentage for each category: the subtotal for that category divided by the total for all categories. Draw a right vertical axis and label it with percentages. Be sure the two scales match: For example, the left
measurement that corresponds to one-half should be exactly opposite 50% on
the right scale. Calculate and draw cumulative sums: Add the subtotals for the first and second categories, and place a dot above the second bar indicating that sum. To that sum add the subtotal for the third category, and place a dot above the third bar for that new sum. Continue the process for all the bars. Connect the dots, starting at the top of the first bar. The last dot should reach 100 percent on the right scale.
Pareto Chart Examples Example #1 shows how many customer complaints were received in each of five categories. Example #2 takes the largest category, “documents,” from Example #1, breaks it down into six categories of document-related complaints, and shows cumulative values. If all complaints cause equal distress to the customer, working on eliminating document-related complaints would have the most impact, and of those, working on quality certificates should be most fruitful.
2) The fishbone diagram A Cause-and Effect Diagram also known as fish bone diagram is a tool that shows systematic relationship between a result or a symptom or an effect and its possible causes. It is an effective tool to systematically generate ideas about causes for problems and to present these in a structured form. This tool was devised by Dr. Kouro Ishikawa and as mentioned earlier is also known as Ishikawa Diagram.
Procedure The steps in the procedure to prepare a cause-and-effect diagram are : 1. Agree on the definition of the 'Effect' for which causes are to be found. Place the effect in the dark box at the right. Draw the spine or the backbone as a dark line leading to the box for the effect. 1. Determine the main groups or categories of causes. Place them in boxes and connect them through large bones to the backbone. 2. Brainstorm to find possible causes and subsidiary causes under each of the main groups. Make sure that the route from the cause to the effect is correctly depicted. The path must start from a root cause and end in the effect. 3. After completing all the main groups, brainstorm for more causes that may have escaped earlier. 4. Once the diagram is complete, discuss relative importance of the causes. Short list the important root causes.
3) Check sheets Also called: defect concentration diagram. .A check sheet is a structured, prepared form for collecting and analyzing data. This is a generic tool that can be adapted for a wide variety of purposes.
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.
Check Sheet Example The figure below shows a check sheet used to collect data on telephone interruptions. The tick marks were added as data was collected over several weeks
4) Control chart 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 centring 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.
4.1 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.
Control Chart Basic Procedure Choose the appropriate control chart for your data. Determine the appropriate time period for collecting and plotting data. Collect data, construct your chart and analyze the data. 12
Look for “out-of-control signals” on the control chart. When one is identified, mark it on the chart and investigate the cause. Document how you investigated, what you learned, the cause and how it was corrected. Out-of-control signals A single point outside the control limits. In Figure 1, point sixteen is above the UCL (upper control limit). Two out of three successive points are on the same side of the centreline and farther than 2 σ from it. In Figure 1, point 4 sends that signal. Four out of five successive points are on the same side of the centreline and farther than 1 σ from it. In Figure 1, point 11 sends that signal. A run of eight in a row are on the same side of the centreline. Or 10 out of 11, 12 out of 14 or 16 out of 20. In Figure 1, point 21 is eighth in a row above the centreline. Obvious consistent or persistent patterns that suggest something unusual about your data and your process.
Continue to plot data as they are generated. As each new data point is plotted,
check for new out-of-control signals.
6 When you start a new control chart, the process may be out of control. If so, the control limits calculated from the first 20 points are conditional limits. When you have at least 20 sequential points from a period when the process is operating in control, recalculate control limits.
5) Histogram chart A frequency distribution shows how often each different value in a set of data occurs. A histogram is the most commonly used graph to show frequency distributions. It looks very much like a bar chart, but there are important differences between them.
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.
Histogram Construction Collect at least 50 consecutive data points from a process. Use the histogram worksheet to set up the histogram. It will help you determine the number of bars, the range of numbers that go into each bar and the labels for the bar edges. After calculating W in step 2 of the worksheet, use your judgment to adjust it to a convenient number. For example, you might decide to round 0.9 to an even 1.0. The value for W must not have more decimal places than the numbers you will be graphing. 14
Draw x- and y-axes on graph paper. Mark and label the y-axis for counting data values. Mark and label the x-axis with the L values from the worksheet. The spaces between these numbers will be the bars of the histogram. Do not allow for spaces between bars. For each data point, mark off one count above the appropriate bar with an X or by shading that portion of the bar.
Histogram Analysis Before drawing any conclusions from your histogram, satisfy yourself that the process was operating normally during the time period being studied. If any unusual events affected the process during the time period of the histogram, your analysis of the histogram shape probably cannot be generalized to all time periods. Analyze the meaning of your histogram’
6) Scatter chart The scatter diagram graphs pairs of numerical data, with one variable on each axis, to look for a relationship between them. If the variables are correlated, the points will fall along a line or curve. The better the correlation, the tighter the points will hug the line. 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, such as… When trying to identify potential root causes of problems. After brainstorming causes and effects using a fishbone diagram, to determine objectively whether a particular cause and effect are related. When determining whether two effects that appears to be related both occur with the same cause. When testing for autocorrelation before constructing a control chart.
Scatter Diagram Procedure Collect pairs of data where a relationship is suspected. Draw a graph with the independent variable on the horizontal axis and the dependent variable on the vertical axis. For each pair of data, put a dot or a symbol where the xaxis value intersects the y-axis value. (If two dots fall together, put them side by side, touching, so that you can see both.) 17
Look at the pattern of points to see if a relationship is obvious. If the data clearly form a line or a curve, you may stop. The variables are correlated. You may wish to use regression or correlation analysis now. Otherwise, complete steps 4 through 7. Divide points on the graph into four quadrants. If there are X points on the graph, Count X/2 points from top to bottom and draw a horizontal line. Count X/2 points from left to right and draw a vertical line. If number of points is odd, draw the line through the middle point. Count the points in each quadrant. Do not count points on a line. Add the diagonally opposite quadrants. Find the smaller sum and the total of points in all
lower lower and
right left B
N =A+ B Look up the limit for N on the trend test table. If Q is less than the limit, the two variables are related. If Q is greater than or equal to the limit, the pattern could have occurred from random chance.
Scatter Diagram Example The ZZ-400 manufacturing team suspects a relationship between product purity (percent purity) and the amount of iron (measured in parts per million or ppm). Purity and iron are plotted against each other as a scatter diagram, as shown in the figure below. There are 24 data points. Median lines are drawn so that 12 points fall on each side for both percent purity and ppm iron. To
A = points in upper left + points in lower right = 9 + 9 = 18 B = points in upper right + points in lower left = 3 + 3 = 6 Q
the smaller of A and B =
N = A + B = 18 + 6 = 24
the smaller of 18 and
6 = 6
Then they look up the limit for N on the trend test table. For N = 24, the limit is 6. Q is equal to the limit. Therefore, the pattern could have occurred from random chance, and no relationship is demonstrated.
Scatter Diagram Example Scatter Diagram Considerations Here are some examples of situations in which might you use a scatter diagram: Variable A is the temperature of a reaction after 15 minutes. Variable B measures the colour of the product. You suspect higher temperature makes the product darker. Plot temperature and colour on a scatter diagram. Variable A is the number of employees trained on new software, and variable B is the number of calls to the computer helps line. You suspect that more training reduces the number of calls. Plot number of people trained versus number of calls. To test for autocorrelation of a measurement being monitored on a control chart, plot this pair of variables: Variable A is the measurement at a given time. Variable B is the same measurement, but at the previous time. If the scatter diagram shows correlation, do another diagram where variable B is the measurement two times previously. Keep increasing the separation between the two times until the scatter diagram shows no correlation. 20
Even if the scatter diagram shows a relationship, do not assume that one variable caused the other. Both may be influenced by a third variable. When the data are plotted, the more the diagram resembles a straight line, the stronger the relationship. If a line is not clear, statistics (N and Q) determine whether there is reasonable certainty that a relationship exists. If the statistics say that no relationship exists, the pattern could have occurred by random chance. If the scatter diagram shows no relationship between the variables, consider whether the data might be stratified. If the diagram shows no relationship, consider whether the independent (x-axis) variable has been varied widely. Sometimes a relationship is not apparent because the data don’t cover a wide enough range. Think creatively about how to use scatter diagrams to discover a root cause. Drawing a scatter diagram is the first step in looking for a relationship between variables.
7) Stratification Stratification is a technique used in combination with other data analysis tools. When data from a variety of sources or categories have been lumped together, the meaning of the data can be impossible to see. This technique separates the data so that patterns can be seen.
When to Use Stratification
Before collecting data. When data come from several sources or conditions, such as shifts, days of the
week, suppliers or population groups. When data analysis may require separating different sources or conditions.
Stratification Procedure Before collecting data, consider which information about the sources of the data might have an effect on the results. Set up the data collection so that you collect that information as well. When plotting or graphing the collected data on a scatter diagram, control chart, histogram or other analysis tool, use different marks or colours to distinguish data from various sources. Data that are distinguished in this way are said to be “stratified.” Analyze the subsets of stratified data separately. For example, on a scatter diagram where data are stratified into data from source 1 and data from source 2, draw quadrants, count points and determine the critical value only for the data from source 1, then only for the data from source 2.
Stratification Example The ZZ–400 manufacturing team drew a scatter diagram to test whether product purity and iron contamination were related, but the plot did not demonstrate a 22
relationship. Then a team member realized that the data came from three different reactors. The team member redrew the diagram, using a different symbol for each reactor’s data:
Now patterns can be seen. The data from reactor 2 and reactor 3 are circled. Even without doing any calculations, it is clear that for those two reactors, purity decreases as iron increases. However, the data from reactor 1, the solid dots that are not circled, do not show that relationship. Something is different about reactor 1.
Stratification Considerations Here are examples of different sources that might require data to be stratified: Equipment Shifts Departments Materials 23
Suppliers Day of the week Time of day Products Survey data usually benefit from stratification. Always consider before collecting data whether stratification might be needed during analysis. Plan to collect stratification information. After the data are collected it might be too late. On your graph or chart, include a legend that identifies the marks or colours used.
Now starting with new 7 quality control tool Need of new quality control tool. Many customer requirements cannot always be adequately expressed by numerical data alone. Nevertheless, even verbal statements can be expressions of facts, because it represents facts, we ought to use Verbal data as well as numerical data in controlling the managing quality. It provides both quality control as well as improvement during the manufacturing process.
Benefits of new 7 quality control tool
Combine verbal with Numerical data Looking for root cause Clarify, prioritize goals and schedule Involve everyone into full cooperation and generate new ideas
The first new quality control tool is:
1) Affinity Diagram Application An affinity diagram is used to organize into groupings large number of ideas, opinions or concerns about a Particular topic.
Description When a large number of ideas, opinions or other concerns about a particular topic are being collected, this tool organizes the information into grouping~~based on the natural relationships that exist among them. The process is designed to stimulate creativity and full participation; It works best in groups of limited Size (a maximum
of eight members is recommended) in which members are accustomed to working together. This tool is often used to organize ideas generated by brainstorming.
Procedure: State the topic to be studied in broad terms(details may prejudice the response). Record as many individual ideas, opinions or concerns as possible on cards
(one per card). Mix the cards and spread them randomly on a large table. Group related cards together as follows: a)sort cards that seem to be related into groups, and b) limit number of grouping to ten without forcing single cards into groups. Locate or create a header card that captures the meaning of each group. Place this header card on top. Transfer the information from cards onto paper, organized by groupings.
For next generation digital camera we can organize the customer
Complains and requirements in an Affinity Diagram.�
2) Tree diagram Application A tree diagram is used to show the interrelation between a topic and its component elements. Description: A tree diagram systematically breaks down a topic into its component elements. Ideas generated by Brainstorming and graphed or clustered with an affinity diagram can be converted into a tree diagram to show logical and sequential links. This tool can be used in planning and problem solving. Procedure: State the topic to be studied clearly; Define the major categories of the topic;(brainstorm or use the header cards from the affinity diagram); Construct the diagram by placing the topic in a box on the left-hand side; Branch the major categories laterally to the right; For each major category, define the component elements and sub-elements, if any; Laterally branch to the right the component elements and sub-elements for each major category; and Review the diagram to ensure that there are no gaps in either sequence or logic.
3) Arrow diagram Purpose: To create a visual presentation of the steps of a process or tasks necessary to complete a project with special emphasis on the time taken for these activities.
Procedure: 1. List all the tasks or activities needed to be accomplished before the process of the project. 2. Decide which steps are undertaken in series and which steps can be run in parallel. Arrange the Activities in a proper sequence. 3. Prepare ‘Event Nodes’ at the completion of steps and number them. 4. Write the description of the step and decide the time required for completing each step 5. Calculate the earliest time to reach an event node for the start of the process. 7. Ager the time for all event nodes including the completion of the process or the project is available, one calculates the latest time by which an event node must be reached.
Application: The diagram is also useful in planning and scheduling steps in complicated processes, especially in planning and scheduling projects which involve a large number of activities.
1. Identify the tasks. E.g.: 1,2,3,…,15. 2. Know the time each task needs. 3. Determine which tasks can be run in parallel and in normal sequences. 4. Draw the sequence diagram and find the critical path. 5. Calculate the project duration. 6. Calculate the earliest starting time (or the earliest finishing time of last task) and the latest finishing time of each task(the latest starting time for the following task). 7. Mark the time indication.
4) Process, Decision Program Chart (PDPC) Def: The process decision program chart (PDPC) method helps us select the best processes to obtain optimum results by evaluating the progress of events and various conceivable outcomes . Description The process decision program chart (PDPC) method is used to define the solution process when dealing with problems that have more than one possible outcome. [t anticipates the unexpected Outcomes at each stage and plans for it. PDPC has two following patterns: Pattern I – In this pattern process starts with initial condition ‘A’ and proceeds to the desired final condition ‘Z’ in an organized manner . Pattern 11- In this pattern, first the final condition’s’ is set. Then the process from ‘Z’ to the initial point ‘A’ is developed with the inclusion of various alternatives from many points of view .
Discuss the issues related to the project among a cross-functional team. Discuss which issues must be examined and identify those issues. Consider and note down all the anticipated results for the identified issues. Weigh the feasibility of each solution proposed and investigate alternate
solutions. Classify each issue according to its urgency, number of operations required, likelihood of Occurrence and difficulty. Consider the anticipated results and alternative solutions related to issues that must be addressed immediately and link the items with arrows to the desired goal. Prioritize the different issues and consider them all together. Information related to one set of 34
Possibilities could influence another set. Related items shall be linked with a broken line. If the department that will handle a process involving several lines is determined, circle the process and write the name of the department within. Set a target date for completion. Have regular meetings to check progress in terms of the original PDPC.
5) Matrix diagram: Purpose: 1) Explore the existence and the extent of relations between individual items in 2 sets of factors or features and characteristics and express them in a symbolic form that is easy to understand. 2) Mostly used to understand the relations between the customer expectations as expressed by the customers and product characteristics as designed, manufactured and tested by the manufacturer.
Procedures: 1. Determine 2 sets of factors for which the relations are needed to be established. 2. Divide the features and characteristics into primary, secondary and tertiary characteristics. 3. Place the features vertically on the leg side of the matrix and characteristics horizontally on top of the matrix. 4. Enter the importance of the features on the column ager that for the tertiary features.�
5. In the main body of the matrix, use the symbols to represent the degree of connections between the feature and characteristics. 6. Choose and define relationship symbols. Most commonly used symbols are as given below:
Application • Matrix diagram can be used to solve problems by arranging data in such a way that the relations between relevant factors are brought into sharp focus. • There is no limit to the use of the tool. • The most important application of matrix diagram is in clarifying relations between individual features of customer requirements and individual product characteristics. Example 1
Matrix Diagram for Quality Functions and Responsibilities
6) Matrix Data Analysis Diagram� Purpose:
To present numerical data about two sets of factors in a matrix form and
analyze it to get numerical output. Can be applied in understanding the products and products characteristics.
Procedure� 1. Decide the two factors whose relations are to be analyzed. 2. Check the number of individual items in the two factors. 3. Prepare a matrix to accommodate all the items of the two factors. 4. Enter numerical data in the matrix. 5. Give the diagram a suitable title. Example
7) Relationship diagram This diagram clarifies the interrelations in a complex situation involving many interrelated factors and serves to clarify the cause and effect relationships among factors. Description Relations diagram is defined as a technique used to solve problems that have complex cause and effect relationships among a number of problems and factors that influence them.
Format A special feature of relation diagram is its unrestricted Format. However general formats are as given below.
1) Centrally converging relations diagram The major item or problem to be solved is located in the center, and the related factors are arranged around the item or problem in such a way as to indicate close relationships.
2) Directionally intensive relations diagram The major item or problem to be solved is located on one side of the diagram, and the various factors arranged in accordance with the flow of their major cause-and-effect relationships on the other side.
3) Relationship indication relations diagram: There are no restrictions on this format because the main point is to arrange the causeand-effect Relationships of the application items or factors so that they are expressed in a straightforward manner in a Diagram.
Procedure 1) Define the issue/problem in such a way that it is clearly understood and agreed on by team members. 2) Assemble the cross-functional team. 3) Layout all the ideas/issue cards that have been brought from other tools. 4) Look for cause/influence relationships between all ideas and draw relationship arrows: a) Choose any of the ideas as a starting point and work through them in sequence; b)An outgoing arrow from an idea indicates that it is the stronger cause or influence; c) Draw only one way relationship arrows in the direction of the stronger cause or Influence. Make a decision on the stronger direction. Do not draw two headed arrows. 5) Review and revise the relations’ diagram. 6) Tally the number of outgoing and incoming arrows and select key items for further planning: -record and clearly mark next to each issue the number of arrows going in and out of it. -find the items with the highest number outgoing arrows and the items with the highest number of incoming
-a high number of outgoing arrows indicate that the item is a root cause and should be tackle first;
-a high number of incoming arrows indicate that the item is a key outcome and may become a focus for planning either as a meaningful measure of overall success or as a redefinition of the original issue under discussion Example:
Statististical QC is chiefly concerned in making sure that several procedures and working arrangements are in place to provide for effective and efficient statistical processes, to minimize the risk of errors or weaknesses in
procedures or systems or in source material. Seven QC tools are most helpful in troubleshooting issues related to quality. All processes are affected by multiple factors and therefore statistical QC tools
can be applied to any process. The continuous use of these tools upgrades the personnel characteristics of the people involved. It enhances their ability to think generate ideas, solve problem and do proper planning.