Metric Series

Metric Series - Status Time

%Status Time.PNG

One of the insightful metrics generated by andon is %Status Time.  This view (example above) shows the time split between red, green, and yellow light status for each line or station.  At the station level this is percent of time spent in each status.  For example, if a given day had 12 hrs in green light status, 8 hrs in yellow light status, and 4 hrs in red light status the split would be shown as 50% green (12/24 hrs), 33% yellow (8/24 hrs), and 17% red (4/24 hrs).  At the line level the same methodology is applied, just that all of the times in each status for each line's station are added together.

Having these insights into how status is trending over time is incredibly useful for root causing production output issues.  This is one simple but clear way that andon extends value beyond a traditional stack light.  The great thing about andon is that these powerful view are generated from very simple red/yellow/green input data.  As always, we focus on maximizing value to you while maintaining an incredibly simple and intuitive platform.  For more details on historical trends, see the guide on the support page [link here].

 

Metric Series - Yield Calculation

yield.PNG

In this new series we will be highlighting how each of the key metrics are calculated.  If your org is brand new to andon then of course you won't have a large data set to show historical metrics.  In this case the demo org [instructions to join here] can be a great resource for viewing metrics as it has a built-in comprehensive historical data set.

Today we want to highlight the Yield metric.  For each station, yield is calculated by taking the # of 'pass' units produced and dividing by the total number of units; in short: # of pass/(# of pass + # of fail).  For each line, yield is calculated by multiplying all of the individual station yields together. 

With andon you can graph line and station yield on the same chart as shown in the screenshot above.  The results are often very compelling - clearly showing how issues at stations have a compounding affect on the overall performance of the line.  With these views you can target the problem areas quickly and work with your team to implement and evaluate corrective actions.  While simple, this metric is very powerful at quickly pinpointing areas to focus improvement efforts.