Quality and process improvement HNC/HND engineering

Quality and process improvement

1. Quality and Process Improvement

2. Task : Research and define the concept of quality in an industrial environment, and identify why process improvement is critical to achieving quality.

3. Quality is the degree to which a product or service meets customer requirements and expectations. In manufacturing , quality means producing goods free of defects, within specified tolerances, and to standard specifications. In service , quality means delivering services consistently, timely, and as promised.

4. Task : Research and define the concept of Statistical Process Control (SPC) and Cost of Quality ( CoQ )

5. Statistical Process Control (SPC) is a quality control methodology that uses statistical tools to monitor and control processes.

6. Statistical Process Control (SPC)

7. Importance of SPC in Industrial Environments

8. Example Applications : Airports : Sampling customer satisfaction regarding restaurant cleanliness. Car Manufacturers : Periodic checks on door panel conformity to ensure machinery is performing correctly.

9. Kaoru Ishikawa – as much as 95% of all quality related problems in the factory can be solved with seven fundamental quantitative tools. The Seven Basic Quality Tools are essential for quality management and process improvement. They provide systematic methods for identifying, analyzing, and solving quality issues, leading to better decision-making and enhanced process control.

10. 2. Cause-and-Effect Diagram (Ishikawa or Fishbone Diagram) Description : A diagram that identifies many possible causes for an effect or problem. It resembles a fishbone, with the main problem at the head and various causes branching off from the spine. Usage : Helps teams brainstorm and sort ideas into useful categories, such as People, Methods, Machines, Materials, Measurements, and Environment. Example : Used in root cause analysis to identify the underlying causes of defects or quality issues in a production process.

11. 3. Check Sheet Description : A structured, prepared form for collecting and analyzing data. It is designed to be easy to use and interpret. Usage : Effective for data gathering and analysis, ensuring consistent data collection. Example : Used in defect or failure logging to record the frequency of specific problems during a production shift.

12. 4. Control Chart Description : A graph used to study how a process changes over time. It displays data points plotted in time order and includes a central line (mean), an upper control limit, and a lower control limit. Usage : Helps in monitoring process variability and stability by showing whether a process is in control or out of control. Example : Used in process control to monitor the quality of a manufacturing process, ensuring that variations are within acceptable limits

13. The control limits are + or – standard deviation from the centre line The dats for the process which we are plotting is within the control limits , then the process is in control

14. Control Charts in SPC Purpose : Not only for single sample checks but to monitor quality over time. Functionality : Control charts help determine if a process is performing correctly or if it is "out of control". Early detection of problems allows for corrective actions before significant issues arise. Example : Charting the percentage of dissatisfied restaurant customers over time. A rising trend in dissatisfaction indicates a need for management intervention.

15. Importance of Control Charts Trend Analysis : Identifying worsening trends to investigate underlying issues. Identifying improving trends to understand and replicate successful processes. Management Insights : Sharing successful practices across the organization. Potentially stopping processes that improve quality but add unnecessary expense

16. 5. Histogram Description : A bar graph that shows the frequency distribution of a dataset. Each bar represents the frequency of data points within a specified range. It differs from a bar graph which relates 2 variables. Usage : Displays the shape and spread of continuous sample data, helping to understand the distribution pattern. Example : Used in distribution analysis to identify patterns, such as whether data follows a normal distribution.

17. Understanding Process Variation with Histograms Process Stability : When no exceptional factors influence the process, variations will show a predictable pattern. Histogram Development : Initial measurements form a rough histogram. Over time, more data smooth out the histogram into a normal distribution.

18. 6. Scatter Diagram Description : A graph that shows the relationship between two variables. Each point on the graph represents an observation. Usage : Identifies potential relationships or correlations between variables, helping to understand how one variable affects another. Example : Used in correlation studies to determine if there is a relationship between two factors, such as temperature and product yield

19. 7. Flowchart (Process Diagram) Description : A graphical representation of a process, showing the sequence of steps involved. It uses symbols to denote different types of actions or decisions. Usage : Helps to understand and improve processes by providing a visual overview, identifying inefficiencies, and areas for improvement. Example : Used in process mapping and redesign to visualize the steps in a customer service process, identifying bottlenecks and areas for improvement.