Ferry Manufacturing Snippets: April 8th - 14th 2024

Here's the weekly digest of Ferry's manufacturing snippets!

Monday - 8th April

In manufacturing, the "production-SKU" mix is absolutely critical to get right .

A machine can yield significantly different characteristics depending on what you're producing. The rate of production can swing wildly across SKUs . Certain products may induce downtime more often than others .

Track this closely. Tie it back into how you plan production .

You may find that there is serious money left on the table by reorganising what you make, when, and in which order.

Tuesday - 9th April

Manufacturing intelligence is fundamentally a data flow problem at the core.

You have to bring together information from machines & operators on the line, and enrich it with context from the rest of the business.

The challenge? Data siloes are everywhere. Workflows are still often on pen & paper.

Being able to integrate with multiple systems is not enough. Just because you can connect to factory equipment, does not mean that you can combine machine data seamlessly with how operators run production to improve efficiency.

The meat & potatoes of the problem is orchestration over integration.

Wednesday - 10th April

More jargon busting in manufacturing. OEE v OOE v TEEP

1. Overall Equipment Effectiveness (OEE). A measure of how well a machine is utilized relative to its theoretical peak performance. Derived from 3 components multiplied together: Availability (the % of time a machine is actually running relative to its total scheduled run time), Performance (% of how fast the machine is running relative to its full potential), Quality (% of good units relative to all units produced)

   1. Scheduled run time is super important. This is shift time removing the time when equipment is not planned to be running (i.e. planned maintenance)

2. Overall Operations Effectiveness (OOE). The same calculation as OEE but with one big difference. The Availability metric reflects the % of time a machine is actually running relative to total shift time. OOE measures how well a machine is utilized during shift hours.

3. Total Effectiveness Equipment Performance (TEEP). The same as OEE but with one big difference. This time, the Availability metric reflects the % of time a machine is actually running relative to all time (24/7). TEEP measures how well you utilize a machine across the business.

In short: TEEP < OOE < OEE

The difference lies in how Availability is measured.

Thursday - 11th April

A memorable quote from a recent chat with one of the pioneers of industrial automation :

"There are 8 billion people in the world. There are 1 billion like us in the West with our cars, our smartphones, with a universe of products we can buy.

There's another 7 billion who are working hard for - and over time will achieve - a similar access to choice to what we enjoy here.

There is no way we can produce enough goods in our current factories to meet that demand.

The only answer is more industrial automation. Industrial automation is the one market that is guaranteed to grow ."

Friday - 12th April

What is a data historian in manufacturing?

No, it's not a job title!

Data historians are the original time series database. They are designed to collect & store large volumes of data from the factory floor with efficient compression baked in (i.e. see OSI PI).

Thing is, now we have next-gen time series databases with the likes of InfluxData & Timescale.

With even greater flexibility, cheaper cost, powerful dev tools and a closer likeness to modern IT databases (i.e. Timescale extends Postgres).

It seems like the old-school days of data historians are probably over.

Special shout out to Timescale in particular, we're big fans of them at Ferry.