I’ve often said “I am not good with numbers, but I can spot a trend.” I have spent hours poring over data from milking machines. Unit-on time, peak milk flow, average milk flow, milk in the first two minutes, first 30 seconds and first 15 seconds are all data points that can be analyzed and at times need to be. But the truth is: At times the data can be truly overwhelming. What does it all mean?

Milking Technology Manager / Lely NA

I propose as singular numbers, not very much, because managing anything with one or even two numbers generally doesn’t work. For Packer fans my age, Brett Favre led the league in two categories – touchdowns and interceptions. One number is great, but the second paints a different picture.

I have started using a testing device that delivers a tremendous amount of data from multiple locations in the milking cluster. I believe this data points out trends that are priceless. These trends can indicate issues with what I like to call the cow/machine interface.

Today’s milking cow is a tremendous creature, producing a high-quality food source from grasses and grains at production levels unthinkable even 10 years ago. The cow/machine interface, in this instance, refers to the milking machine making contact with the cow to remove the milk.

The cow, when fully participating in the process, can deliver flows of milk at high rates, allowing a quick and comfortable milkout. Here is where the trend-spotting comes into play.

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When properly stimulated teats are placed into properly fitting and operating milking liners, very little vacuum gets past the barrel of the teat and into the mouthpiece of the milking liner. When teats are not properly stimulated, or when they reach the point of no longer having milk in them, they start to reduce in size.

When this reduction in size takes place, the amount of vacuum getting past the barrel of the teat and into the mouthpiece of the liner increases. This increase in mouthpiece vacuum is a very good indicator of proper liner fit and teat stimulation.

If, for example, as in Figure 1 , the teat is not properly stimulated at the start of milking, high mouthpiece vacuums are present until either the machine delivers ample stimulation or the pre-milking stimulation has enough lag time to deliver its intended reward.

the teat is not properly stimulated at the start of milking, high mouthpiece vacuums are present until either the machine delivers ample stimulation or the pre-milking stimulation has enough lag time to deliver its intended reward

In Figure 2 , proper stimulation was provided, but detacher thresholds were set too “dry” and over-milking occurred at the end of milking, resulting in higher mouthpiece vacuums.

proper stimulation was provided, but detacher thresholds were set too “dry” and over-milking occurred at the end of milking, resulting in higher mouthpiece vacuums

In Figure 3 , properly stimulated teats were delivered to a well-fitting liner, and cows were milking quickly and completely. The detacher then removed the milking cluster when the milk flow reduced.

properly stimulated teats were delivered to a well-fitting liner, and cows were milking quickly and completely. The detacher then removed the milking cluster when the milk flow reduced

Very little mouthpiece vacuum occurred at the beginning of milking. When the vacuum in the mouthpiece started to climb, it indicated the teat was starting to reduce in size and milk flow was reducing. Then the detacher shut off the vacuum and removed the cluster.

The tool used to do the test allows the tester to leave the parlor, let the operators get back to business as usual, and let the cows tell us how the system is working. In two of these instances, the mechanical system wasn’t being optimized by the cow/machine interface.

I have often referred to my three golden rules of milking a cow: 10 to 15 seconds of manual stimulation, 30 seconds of germicidal contact time and 90 seconds or more of lag time. If every cow achieves these three things every day, good things tend to happen.

If these three items are not achieved regularly, and in my experience they aren’t very often, variables enter the equation and allow for varying outcomes.

The real question then, and the reason for harvesting any data, is: What are we going to do with it? I believe the only reason to collect data is to help make decisions toward better outcomes. The difficult part is knowing how to deliver that better outcome.

Information harvested at the milking cluster can help make decisions about stimulation and lag time, using proper liners and developing proper system settings. We can address questions such as: Was the stimulation and/or lag time sufficient? Does the liner provide a good fit to the majority of the cows?

And is the cluster delivering the vacuum levels we are looking for? Information is great, but if we know the information is bad and we don’t know what to do about it, it is a bit like being on a plane and knowing we are out of fuel: Information is helpful; answers are better. I believe I have found a tool that helps me spot a trend. PD

paul peetz

Paul Peetz
The Almost Perfect Parlor blog