Polyhedrika

     Statistical Process Control is used to detect when a significant change has taken place in a process.  We want to detect this change as soon as possible. What is real-time will depend on the process.  All processes have variation as observed in any of their metrics but not all variation is significant from the statistical point of view.  Random Variation Vs Trends: Statistical Process Control When we want to control a process by adjusting some process parameter we can make two mistakes: Over-react by adjusting when we shouldn't Under-react by failing to adjust when we should Control over-reaction A case of over-reaction is illustrated by the following example: Someone is shooting at a target and, based on the deviation of the impacts, he adjusts the gun site after each shot. The end result will be an increase of the dispersion of the impacts, therefore the adjustments will make the process worse. The correct way is, of course, to fire 5 or 6 shots without adjustments and then

Time variation and WIP cause a vicious circle that increases value stream lead time making it difficult to keep pace with changing customer demand. Time is a continuous variable which can be easily recorded without the need of special equipment: PCs or smartphones used to collect data can automatically record a timestamp. When it comes to analyse cause and effect between process parameters and results time is key. Time Variation Causes Accumulation of WIP You can experience this effect in exercise 7 with a simulator  : This WIP Increase Causes a Lead Time Increase As seen in the same simulator: This is due to the fact that items have to wait in the queues formed before steps 2 and 3. Long Lead Times Cause an Amplification Upstream of the Market Variation  This effect is well illustrated in the Beer Game  which can be experienced with various simulators in the web. The game was first described by Peter Senge  in The Fifth Discipline . A small variation in the market demand is amplified

  When it comes to process improvement Lean and Six Sigma are both useful and complement each other. Lean focuses on the elimination of waste (non-value-add) Six Sigma tries to get to the root cause of waste to avoid problems from reoccurring   A common source of waste is variation   Six Sigma focuses on reducing variation What comes first?  Philosophy or Tools? Lean and Six Sigma philosophies are essential to justify and understand the tools required to implement them. But these philosophies are difficult to understand without a deep understanding of the tools.  Manage the Improvement Project  A project charter is useful to define the project, participants, objectives, etc. Project scheduling keeps track of who does what and when An Obeya Room is often used to focus all project improvement actions and keep everyone up to date. Understand the Current Process  Before we start improving we need a deep understanding of the current process so we can Go to Gemba and build a Value Str

Optimize both Yield and Cost with Minitab Design of Experiments Design of Experiments is a powerful technique to optimize process outputs in complex processes where multiple factors affect the outputs. When we want to optimize more than one output the problem becomes more complex. With this example we want to follow the steps, using Minitab, to optimize both process yield and cost by acting on 3 critical factors which have been identified by previous experiments. Process Improvement Steps DEFINE: The first step in process improvement is to map the current process as it is really happening with a  Value Stream Map . MEASURE: Then we need to  collect process data  in the line. MEASURE VARIATION: To understand the process dynamic behavior we will need statistically significant data to enable  simulation     CONTROL: The first data analysis is to check for stability with  Statistical Process Control MEASURE CAPABILITY: Once we insure the process is stable we want to know to what extent i