The Perfect Mining Production Day, Each and Every Day

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I’ve had some very interesting conversations recently that have made it clear to me there is a lack of understanding on how to improve a production organisation. My ex-colleague from CSIRO, Grant Wellwood (now at Jenike & Johanson), recently posted on this topic of the “Perfect Production Day” on LinkedIn.

The thinking behind improving production processes was established many years ago as mass production was being established, then progressed through the need to gear up for the production needs of World War 2, and became fully established by luminary figures such as Ohno, Deming, Juran and Shingo in the re-establishment of manufacturing in post-war Japan.

The leaders above established several central tenants that still today guide our thinking, and one of the key pieces is that the driver of inefficiency (and thus cost) is variability.

Grant notes that in mining there is often a “large variation in their daily (24-hour) output; often in the order of 30-40% above the long-term average.”

How in the world do you address such enormous variability? How do you close the gap between the “perfect day” and the “average day” and do it consistently?  Well, the good news is there are some clear steps you can take.


The first step is stability of the production chain. Taiichi Ohno of Toyota fame had people stand at the problem machine for the entire eight-hour shift and record the production plan versus the actual amount in small increments, such as 15 minutes to one hour. At the end of the shift, all the losses and the actual reasons for them were identified in a Pareto chart.   Our client, Vince Aurora, called this “Stop the Stops,” and just this one basic step can make a huge difference.  For an interesting article with more detail please see “Improving Plant Operations”

And once stability is achieved, you can move on to additional steps, such as improving the process (energy, quality), better planning and scheduling (once you have a stable process, you can plan with certainty) and looking at step changes through simulation and optimisation – topics I will address in future blogs.

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