Overprocessing: How one Manufacturer identified and is working to eliminate this significant source of waste

An example of over processing is when companies use aggressive PM programs to manage their systems. 

When time instead of condition is used to change out their washers, rinse tanks, coolant sumps or oil systems.  

When there is no cost effective way to identify and track end of life, then plants are stuck using wasteful preventative measures, however when the KPI's that do impact performance can be tracked and monitored, then condition monitoring lets you not only eliminate wasteful over processing, but it provides the data necessary to make better decisions moving forward.  

By adding work that is not required, Over-processing costs money with regards to the time of staff, the materials used and the wear on the equipment.

These costs can amount to a considerable sum over a period of time, they will also reduce efficiencies as the operators that are Over-processing could be performing other value adding tasks that the customer is actually willing to pay you for.

In our world we see a lot of over processing that results from trying to contain problems. 

When the lead KPI’s are not be controlled, companies are forced to be preventative, using past events and tribal knowledge to build PM schedules in their effort to avoid events.. 

This leads to significant waste and wasteful activity. 

In this example, the source of over-processing identified was a final parts washing process. 

The facility had installed this washer in an effort to address a part cleanliness issue they were having. 

By running all the various components cleaned by 4 upstream washers, they used this final wash process as an extra level of insurance to minimize the risk of a quality event. 

It increased costs, increased WIP inventory, consumed valuable floor space, required staffing etc.  but if it meant they weren’t experiencing a “customer detected quality event”, it was worth it. 

The problem was that this containment action didn’t address the real issue and repeated quality spills meant they had to look at the problem from a different perspective.   

In most circumstances, all the KPI's are not known ahead of time, but by implementing a standardized approach to data collection and correlation, its possible to move from preventative to condition based in most systems.  

And the move from preventative to condition based is essential for companies looking to get world class.