Polyhedrika

Understanding variation is key to interpret the value stream behavior.  Not all variation is the same. Random Variation Vs Trends: Statistical Process Control     Variation These are some factors which may add variation to the process of cooking a turkey.  Every process has variation. Some causes of variation may be identified and acted upon. We can use two metrics for variation which complement each other: Manual Dice Throwing This simple exercise can help to experience process variation and understand the difference between a process change and inherent process variation. This understanding is key on management decisions to avoid both overreaction and lack of reaction. To run the exercise with actual dice print the form: Exercise: You will need a printed form and 4 dice for each team Throw 4 dice and add the outcomes Record the result in the Run Chart Repeat 50 times Join the dots in the Run Chart with a line Build the Histogram by counting the total number of dots on each group of

  Process variation analysis is essential in order to improve it. There is always variation. Sometimes we only have random variation such as in the case of dice throwing: https://polyhedrika.blogspot.com/2020/12/dice-throwing-exercise.html   Normally we have additional variation caused by special causes and these are the ones we should analyse and reduce first. Hourly Production  We are going to analyse the hourly production data collected during one month: Download this Excel file Trend Analysis.xlsx from OneDrive folder Process stability SPC charts allow us to check for stability: see if all variation is random. https://polyhedrika.blogspot.com/2020/12/spc-analysis.html We now apply an individuals SPC chart to our production data to check this: The green and red dots are a clear indication of lack of stability: there are special causes affecting production. Timestamp Data Collection When we collect process data either manually or automatically it is essential to collect the timestam