Process Behavior Chart Excel Workbook

As discussed in the current newsletter issue article, a Process Behavior Chart (PBC) is a control chart that can monitor the variation in your process over time. Here is a step-by-step guideline for end users to use the provided Excel file for monitoring broiler market body weight using a Process Behavior Chart.

Step 1: Download and Open the Excel File

Open the provided Excel file for monitoring broiler market body weight across your flocks.

Step 2: Enter Data

In the second column, labeled “Final BW Data,” enter the body weight data for each flock as they become available. Each row should correspond to a different flock.

Step 3: Calculate Average Body Weight and Moving Range

In the third column, labeled “Average BW,” the average body weight of flocks will be automatically calculated as you enter the data in the second column. You do not need to manually enter values in this column.

In the fourth column, labeled “Moving Range,” the moving range for each data point will be automatically calculated as the absolute difference between consecutive rows in the “Final BW Data” column. This calculation is usually done automatically using Excel formulas.

The fifth column, labeled “Moving Range Bar,” is the average value of the moving range column. The value of the moving range bar is used to calculate the upper and lower control limits.

The sixth and last columns specify the lower control limit (LCL) and upper control limit (UCL).

Step 4: Components of the Chart

The chart should be updated automatically as you enter new data in the “Final BW Data” column. The chart will include the following elements:

  • A line representing the average body weight of the flocks.
  • Data points for the body weight of each flock.
  • Lower and Upper Control Limits 

Monitor the chart for trends or points outside the control limits (LCL and UCL). These points are indicators of potential variations in broiler body weight.

Step 5: Interpretation of the Chart

Pay special attention to signals on the chart. A signal is a data point or group of data points that are not likely to occur randomly, indicating that something has changed in the system and should be investigated and addressed.

There are three types of signals to look out for:

  1. Rule 1: A single data point that falls outside the upper or lower control limits. When this occurs, it is appropriate to ask why and figure out what happened. Investigate to understand the cause of this variation.
  2. Rule 2: Eight consecutive data points that are all above or below the baseline average. This is unlikely to happen randomly and signals that something significant has changed in the system. Try to investigate to determine the cause.
  3. Rule 3: A cluster of either three consecutive data points or three out of four data points that are closer to the control limits than they are to the average. This indicates a significant shift in the system. Investigate and identify the underlying reason.

If any of the three signal types mentioned above occur, it is crucial to investigate and take corrective actions. Signals suggest that there have been significant changes or anomalies in broiler body weight data. The following picture shows the three signal types concerning process variation.

Picture source:

Step 6: Historical Data and Continuous Monitoring

Over time, the chart will accumulate historical data, allowing you to see long-term trends and patterns in broiler body weight. To keep the chart up to date, continue to enter data for new flocks and monitor the process over time. Regularly review the chart to ensure the broiler body weight remains within the desired control limits.

By following these guidelines, end users can effectively use the Excel file to monitor broiler market body weight and detect variations in the process, helping maintain product quality and consistency in the poultry industry. The Excel spreadsheet is versatile and can be employed to evaluate various production factors within a poultry farm, including but not limited to egg mass, egg weight, egg production, lighting intensity, and environmental temperature.

About the author(s)

Research Associate at Poultry Innovation Partnership | + posts