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[Audio] QA/QC -203 Statistical Quality Control Part 2 Unit 12: 1 44 Pg:.

[Audio] U-1-2 Statistical Quality Control Part 2 Objectives  Understanding and Applying Quality Control Methods ( Control Charts, Histogram , Pareto Analysis ) in Construction.

[Audio] U-1-2 Statistical Quality Control Part 2 Control Charts  Control charts in construction are statistical tools used in quality control to monitor and control the processes involved in various construction activities.  They help identify variations in the process and determine whether they are due to common causes (inherent to the process) or special causes (due to specific issues). Control charts are essential for ensuring that construction processes, such as concrete pouring, material testing, or pavement laying, meet the required standards and specifications..

[Audio] U-1-2 Statistical Quality Control Part 2 Application in Construction  Concrete Strength Monitoring: By taking samples of concrete and testing their compressive strength, control charts can be used to track whether the concrete meets design specifications. If a trend or shift is detected in the control chart, it signals the need for corrective action before more concrete is poured.  Asphalt Pavement Quality: Control charts can track key properties like density and compaction during road construction. Any deviations in these parameters can be quickly identified to ensure the pavement meets durability requirements..

[Audio] U-1-2 Statistical Quality Control Part 2 Application in Construction  Material Testing: Regular testing of construction materials such as steel, aggregates, or cement can be plotted on control charts to monitor consistency over time.  Dimensional Control: Measurements taken during excavation, foundation setting, or the installation of structural components can be tracked on control charts to ensure the work is done within tolerance limits..

[Audio] U-1-2 Statistical Quality Control Part 2 Steps to Implement Control Charts  Collect Data: Regularly sample data from construction processes (for example, strength tests, dimensional checks).  Plot Data: Plot the data points on the control chart over time.  Set Control Limits: Determine upper and lower control limits based on historical performance or design specifications.  Analyze Variability: Monitor the process to detect any signs of variation that exceed control limits or display unusual patterns.  Take Action: If the control chart shows signs of special cause variation (for example, points outside control limits), investigate the cause and implement corrective measures..

[Audio] U-1-2 Statistical Quality Control Part 2 Benefits of Using Control Charts in Construction  Improved Process Control: Helps in maintaining process stability and preventing defective work.  Reduced Rework: Early detection of issues helps avoid costly rework later in the project.  Data-Driven Decisions: Provides a clear, visual tool for making informed decisions regarding quality control.  Compliance with Standards: Ensures that construction processes comply with industry and project-specific standards..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts  X-Bar and R Charts (Mean and Range Charts):  Purpose: Used to monitor the average (X-Bar) and variability (Range) of a process.  Application: In construction, these charts can monitor the compressive strength of concrete samples over time or the thickness of asphalt layers across different batches.  Process: Samples are taken at regular intervals, and the average and range of each sample set are plotted. Control limits (Upper Control Limit U-C-L--, and Lower Control Limit L-C-L--) are calculated, and any data points outside these limits indicate that the process may need adjustment..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts  Example: Concrete Strength Control Samples of concrete are taken daily, and compressive strength is tested. The X-Bar chart monitors whether the average strength remains within the control limits. If the average deviates, the mix ratio may need adjustment..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (1) X-Bar and R Charts in Construction Scenario: Concrete samples are taken from every batch delivered to a construction site and the compressive strength is measured at 7 days. The target compressive strength is 35 MPa. Collected Data: Sample 1: [36, 35, 34] MPa Sample 2: [33, 35, 36] MPa Sample 3: [34, 35, 35] MPa Sample 4: [32, 33, 34] MPa Sample 5: [36, 37, 35] MPa.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (1) X-Bar and R Charts in Construction Calculating X-bar and Range: Sample 1: X-bar = (36 plus 35 plus 34)/3 = 35 MPa, Range = 36 34 = 2 Sample 2: X-bar = (33 plus 35 plus 36)/3 = 34.67 MPa, Range = 36 33 = 3 Sample 3: X-bar = (34 plus 35 plus 35)/3 = 34.67 MPa, Range = 35 34 = 1 Sample 4: X-bar = (32 plus 33 plus 34)/3 = 33 MPa, Range = 34 32 = 2 Sample 5: X-bar = (36 plus 37 plus 35)/3 = 36 MPa, Range = 37 35 = 2.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (1) X-Bar and R Charts in Construction Control Chart: The X-bar chart would plot the average strength of each sample (for example, 35, 34.67, 34.67, 33, 36) over time, while the R chart tracks the variability within each sample (for example, 2, 3, 1, 2, 2). Control limits for the X-bar and R charts are typically set at ±3 standard deviations from the process mean. Let's assume the upper and lower control limits (UCL and L-C-L--) are: U-C-L (X-bar) = 37 MPa, L-C-L (X-bar) = 33 MPa U-C-L (R) = 4 MPa, L-C-L (R) = 0 MPa.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (1) X-Bar and R Charts in Construction Analysis: If Sample 4 has an X-bar of 33 MPa, which is at the L-C-L--, it would trigger an investigation into why the concrete is underperforming. If the R values stay below 4 MPa, the variability is acceptable, but a sudden spike in range would indicate issues like inconsistent mixing..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts  P-Charts (Proportion Charts):  Purpose: Used to monitor the proportion of defective units in a process.  Application: P-Charts are suitable for tracking defect rates in construction materials like steel bars, concrete batches, or welded joints.  Process: The proportion of defective units in each batch is plotted on the chart. If the defect rate exceeds the control limits, further investigation into the cause is necessary..

[Audio] U-1-2 Quality Control Principles and Process Types of Control Charts  Example: Defective Welds Monitoring Inspecting a sample of 100 welds on a steel frame, and recording how many fail visual or X-ray inspection. The P-chart tracks this failure rate over time. If the proportion of defective welds crosses the control limit, a review of the welding process may be needed..

[Audio] U-1-2 Quality Control Principles and Process Types of Control Charts.

[Audio] U-1-2 Quality Control Principles and Process Example (2) P-Charts in Construction Scenario: During tile installation, a sample of 100 tiles is inspected daily to check for defects (for example, cracks, misalignment). The acceptable defect rate is 5%. Collected Data (Defective Tiles per 100): Day 1: 3 defects Day 2: 6 defects Day 3: 2 defects Day 4: 8 defects Day 5: 4 defects.

[Audio] U-1-2 Quality Control Principles and Process Example (2) P-Charts in Construction P-chart Calculation: Proportion of defective tiles per day: Day 1: 3/100 = 0.03 Day 2: 6/100 = 0.06 Day 3: 2/100 = 0.02 Day 4: 8/100 = 0.08 Day 5: 4/100 = 0.04 Average Proportion (P-bar) = (0.03 plus 0.06 plus 0.02 plus 0.08 plus 0.04) / 5 = 0.046.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (2) P-Charts in Construction Control Limits (UCL and LCL): UCL = P-bar plus 3 * √(P-bar(1 P-bar)/n) = 0.046 plus 3 * √(0.046(1 0.046)/100) ≈ 0.046 plus 3(0.021) = 0.109 LCL = P-bar 3 * √(P-bar(1 P-bar)/n) = 0.046 0.063 = 0 (since the L-C-L cannot be negative for proportions). Analysis: On Day 4, the proportion of defects (0.08) is below the U-C-L of 0.109, meaning it's still within control, but it is a warning that the defect rate is higher than the average. A sustained increase would require further action..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts  C-Charts (Count of Defects per Unit): Purpose: Used for monitoring the count of defects per unit or area. Application: Useful for processes like surface finishing, where multiple defects (for example, cracks, pores, or unevenness) may appear within a defined area. Process: The number of defects per unit (for example, per square meter of plastered wall) is counted and plotted over time..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts  Example: Defects in Wall Plastering Workers count the number of visible cracks on a newly plastered wall. A C-chart tracks these cracks per unit area. If the number of cracks increases significantly, corrective actions (for example, mix adjustments, worker training) are required..

[Audio] U-1-2 Statistical Quality Control Part 2 Types of Control Charts.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (3) C-Charts in Construction Scenario: During road construction, the contractor monitors defects like cracks, potholes, and uneven spots in 100-meter sections. The goal is to keep defects to a minimum. Collected Data (Defects per 100 meters): Section 1: 2 defects Section 2: 5 defects Section 3: 3 defects Section 4: 7 defects Section 5: 4 defects.

[Audio] U-1-2 Statistical Quality Control Part 2 Example (3) C-Charts in Construction C-chart Calculation: The total number of defects = 2 plus 5 plus 3 plus 7 plus 4 = 21 defects. Average Number of Defects (C-bar) = 21/5 = 4.2 defects per section. Control Limits (UCL and LCL): UCL = C-bar plus 3√C-bar = 4.2 plus 3√4.2 ≈ 4.2 plus 3(2.05) = 10.35 defects LCL = C-bar 3√C-bar = 4.2 3(2.05) = -2.85 (LCL is set to 0 since the number of defects cannot be negative)..

[Audio] U-1-2 Statistical Quality Control Part 2 Example (3) C-Charts in Construction Analysis: The number of defects per section is within control limits. However, Section 4 (7 defects) is nearing the U-C-L--, indicating a potential problem with the paving process in that section. If the trend continues, further investigation would be required, possibly checking the quality of the materials or paving technique..