7 QC Tools.pptx for engineering and technology

7 tool for quality check

1. 7 QC Tools Solving Quality Issues in the Manufacturing Industry. Submitted by: Aniq Ahmed (IM-21070) Saif Ferozi (IM-21060) MD. Ishraq (IM-21066) Abdullah Ahmed (IM-21074) Jawwad Khan (IM-21076) Mqc im-213

2. About Us SSG Industries is a highly reputable machine tool manufacturing company with a strong presence in the industrial town of Coimbatore. They have been in business for over 50 years and are known for the strength and durability of their products. The company followed the practice of backward integration, producing raw structures with their foundry and forging units and then completing the machining and finishing process in-house. In recent years, SSG Industries has expanded into producing semi-automatic and fully automatic machine tools, which have been in high demand for the automobile industry. The company places a high emphasis on quality control, in order to ensure that all products have zero rejections in the assembly section. 2

3. The Issue at Hand 3 SSG Industries manufactures a majority of their products in the form of lathes. Quality control is essential in the production of lathe beds, as the alignment of other components and the machining accuracy of parts depend on the quality of the bed. In several production batches, the lathe beds were found to have cracks, which caused them to be rejected. In order to investigate the cause of the rejections, a meeting was held between Mr. Tayub, Amit, Murugan, the supervisory staff of the foundry division, and Sundar from the heat treatment division. It was decided that 7 QC tools would be used to analyze the situation and find a solution. Quality improvement is a primary goal in any manufacturing industry and 7 QC tools are commonly used due to their simplicity and effectiveness in solving quality issues. Kaoru Ishikawa suggested that 95% of quality problems can be solved by using 7 QC tools, emphasizing their power.

4. 7 QC TOOLS The 7 Quality Control Tools are graphical methods which help to transform data into easily understandable diagrams or charts. This helps to identify and prioritize problems quickly and more effectively, assist the decision making process and provide a vehicle for communicating problems and resolutions throughout the business. The tools are: Cause and Effect Diagram, Check sheet, Control Chart, Flow Chart, Histogram, Pareto Chart, and Scatter Diagram. The Cause and Effect Diagram is also called a Fishbone or Ishikawa Diagram and is useful for listing and classifying the causes of a problem. The Check Sheet is a list in the form of a diagram or table format for data recording and later analysis. The Control Chart is a line graph used to assess and validate the stability of a process. The Flow Chart is a graphical method of displaying a system's operation or sequence. The Histogram is a frequency distribution diagram which displays data in the form of a bar graph. The Pareto Diagram is a specialized bar graph to show the relative frequency of events. Finally, the Scatter Diagram represents the relationship between two variables.. 4

5. What is a Pareto Chart? A Pareto chart is a graphical tool used to identify and prioritize quality improvements in manufacturing processes. It is based on the Pareto principle, which states that roughly 80% of the effects come from 20% of the causes. How to Create a Pareto Chart Identify the problem or issue you want to address. Collect data on the problem or issue, categorizing it into specific causes. Calculate the total number of occurrences for each cause and the percentage it represents of the total occurrences. Rank the causes in descending order of frequency or impact. Plot the cumulative percentage of occurrences for each cause on the y-axis and the causes themselves on the x-axis. 5 Pareto Charts

6. A flowchart is a visual representation of a process or system. It uses symbols and arrows to show the flow of information or materials through the different steps of a process. Flowcharts are used in process mapping to help identify inefficiencies, bottlenecks, and areas for improvement. Basic Flowchart Symbols There are several common symbols used in flowcharts: Rectangle: represents a process step Diamond: represents a decision point, with different paths depending on the answer to a question or the outcome of a calculation Circle: represents the start or end of a process 6 FLOWCHARTS

7. 7 Check Sheets for Process Improvement Check sheets are a simple and effective tool for collecting data on a process. By analyzing the data collected on a check sheet, you can identify patterns and trends in the process that can lead to improvements. Here are the steps to analyze and use data collected from check sheets for process improvement: Step 1: Define the Problem Before you begin collecting data on a process using a check sheet, you need to define the problem you are trying to solve. This will help you determine what data to collect and how to analyze it. Step 2: Collect Data Once you have defined the problem, you can begin collecting data using a check sheet. The check sheet should be designed to capture the specific data you need to analyze the process. Be sure to train those collecting data on how to use the check sheet accurately. Step 3: Analyze the Data After you have collected the data, you can begin analyzing it. Look for patterns and trends in the data that may indicate areas for improvement. Use statistical tools such as histograms or Pareto charts to help visualize the data and identify the most significant issues. Step 4: Implement Improvements Once you have identified areas for improvement, you can begin implementing changes to the process. Be sure to track the impact of the changes using another check sheet to ensure that the improvements are sustained.

8. 8 HISTOGRAM A histogram is a graphical representation of the distribution of numerical data. It is an estimate of the probability distribution of a continuous variable. To construct a histogram, the first step is to "bin" the range of values—that is, divide the entire range of values into a series of intervals—and then count how many values fall into each interval. The bins are usually specified as consecutive, non-overlapping intervals of a variable. The bins (intervals) must be adjacent and are often (but not necessarily) of equal size .

9. A fishbone diagram, also known as an Ishikawa diagram or cause-and-effect diagram, is a tool used to identify the potential causes of a problem or issue. It is a visual representation that helps to organize and analyze data in order to determine the root cause of a problem. Purpose Fishbone diagrams are commonly used in quality control and process improvement initiatives. They help teams to identify the underlying causes of problems and to develop effective solutions. By identifying the root cause of a problem, teams can implement targeted solutions that address the underlying issue, rather than just treating the symptoms . 9 Fishbone Diagrams

10. What is a Scatter Diagram? A scatter diagram is a type of chart that displays the relationship between two variables. It consists of a series of data points, each representing the value of one variable plotted against the value of the other variable. How to Interpret a Scatter Diagram To interpret a scatter diagram, you need to look for patterns or trends in the data. If the points on the diagram form a roughly straight line, this suggests a strong linear relationship between the two variables. If the points are scattered randomly, there may be no relationship between the variables, or the relationship may be weak. You can also look for outliers, which are data points that are significantly different from the others. Outliers can be caused by errors in data collection or measurement, or they may represent a real anomaly in the data. Understanding the cause of outliers can help you make more informed decisions based on the data. 10 Scatter diagrams

11. Control charts are a tool used in statistical process control (SPC) to monitor and control a process over time. They are used to identify when a process is out of control and to help identify the source of the problem. Control charts are based on the idea that a process is in control when it is stable and predictable, with only natural variation present. There are several types of control charts, including the X-bar chart, which is used to monitor the central tendency of a process, and the R chart, which is used to monitor the process variability. Control charts typically include a center line, which represents the process mean, and upper and lower control limits, which represent the acceptable range of variation . 11 Control charts

12. Mr. Tayub, Amit, and Murugan discussed the analysis report and wanted to find a way to reduce the number of rejections in the heat treatment process. Amit suggested conducting a simulated test to decide the course of action. The two then used the Sigma scale to understand the benchmark and improvement level. The results of the simulation experiment showed that the process was within control, but the process capability was inadequate and the rejections were estimated to be around 10%. To understand the effect of the two variables on the hardness, the three decided to note down the gap and the speed of travel for at least 10 lathes. The next day, they handed over a report to Tayub and proposed to continue with manual adjustments to minimize the defects. 12 Action plan

13. This case study investigated the rejections of lathe beds due to defects that occurred after the flame hardening process. The process involves a stationary lathe bed treated with movable equipment using a gas torch to provide the heating. The flame hardening process is expected to impart a hardness of 42-48 HRC, and any beds with a hardness higher than 48 HRC are rejected. Data was collected on 32 beds and the run chart indicated that 6 of the 32 lathe beds had excess hardness. The main causes of defects in hardness were found to be metallurgical errors or errors in the flame-hardening process. A cause and effect diagram was constructed and the process capability analysis results showed that the process was not properly centered and had a sigma level of 2.1, rendering it not acceptable. 13 Image SLide conclusion

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