Chapter 20
Process downtime level
- Why: To better understand your process performance
- What: To measure the proportion of non-productive time
- When: When you want to understand the internal process efficiency
- The question this indicator helps you to answer: to what extent are we operating our processes or machines effectively?
Why does this KPI matter?
Any business wants to minimise non-productive time. If machines or processes are not available when they are needed, this reduces the output that can be generated and therefore reduces profits and margins for the business.
Downtime is any productive time in which a machine or process is not available due to circumstances such as faults or maintenance.
While machine downtime is traditionally associated with the manufacturing industry, process downtime is relevant to any industry. Take, for example, call centres that need to track the downtime of their help-desk processes or hospitals that want to monitor the non-availability of diagnostic equipment.
Understanding the level of downtime provides companies with an insight into how effective their internal operational processes are (whether they are equipment- or process-based).
How do I measure it?
How do I collect the data?
Data for machine or process downtime will come either directly from the machine or process or from records.
What formula do I use?
Machine or process downtime level can be measured as a ratio:
where:
PPTt is the planned productive time that a process or machine should be available in a given time period t.
TAt is the actual productive time that a process or machine has been available in a given time period t.
Or it can be measured as an actual time level:
Machine or process downtime level = PPT – TAt
How often do I measure it?
Machine or process downtime is a measure that can, especially if monitoring is automated, be measured continuously and reported as an indicator if the downtime reaches a predefined threshold. Alternatively, monthly or quarterly reporting might be sufficient.
Where do I find the data?
Data can be taken from the machine itself, as many machines track their own downtime automatically. If automated process monitoring is in place then the same applies to processes. In some cases, manual record keeping might be required.
How difficult or costly is it to measure?
Costs for measuring process or machine downtime are moderate, depending on the level of data already available. If machines and processes are automatically generating downtime data, the calculations are relatively simple. If manual record keeping is required, this will push up costs.
How do I set targets for this KPI?
The target for downtime level should be zero, with the aim of eliminating or at least minimising any unplanned interruptions to the production process – especially if a process or machine is not used around the clock and maintenance can be scheduled for non-productive times.
Practical example
Let’s look at a radiography department in a hospital, for example. The department has two CT (computed tomography) scanners for which it wants to measure downtime. The aim is to have at least one available 24 hours a day but both available during ‘routine business hours’ (between 9 a.m. and 5 p.m. = 8 hours).
The hospital is measuring downtime as any time when one of the scanners is not available during routine business hours and critical downtime as any time when both CT scanners are not available.
Here is an example of a 24-hour time-frame:
CT scanner 1 was not available between 1 p.m. and 3 p.m. because of a fault and between 7 p.m. and 10 p.m. it was undergoing maintenance.
CT scanner 2 was not available between 7 p.m. and 8 p.m. because of a fault.
Some tips and traps to consider
When measuring machine downtime level it is useful to understand the cost implications, such as the direct labour costs that you are losing because the machine is not available but you still have to pay for the people who are there to operate the machine.