Local efficiency versus global objectives in metal fabrication

These days, data is king. We’re told that the better you gather, scrutinize, and analyze it, the more successful you can be. It’s a central idea behind the Internet of Things and Industry 4.0. If you track machine uptime and overall equipment effectiveness (OEE), you know when machines aren’t producing, so you start to ask questions.

Why wasn’t the machine running? The material wasn’t’ available. Why wasn’t it available? The special material wasn’t in stock, and purchasing didn’t order it in time? Why didn’t they order it in time? The work order wasn’t submitted properly. Why wasn’t it submitted properly? And does this product really need this special material? Have we ever talked with the customer about alternatives?

Such questioning ultimately (if people with authority buy in to change) lead to better processes in the front office and smoother production on the floor.

All the same, analyzing data in certain ways can cause frustrations too. Earlier this summer I visited DLC Manufacturing & Fabrication, an eight-person shop recently that was cutting very thick material with a fiber laser. They had optimized the machine so it could cut a clean edge, but if anyone were analyzing the machine’s efficiency, that person would have turned off the operation after the nest was complete and transfer the plate to the CO2 laser. Cutting such thick plate, the fiber laser was running so slowly; why utilize such an expensive resource so poorly?

It was plain to see the reasoning; the fiber laser helped increase overall throughput. The shop could cut more material (this was extremely thick plate for laser cutting, the shop’s specialty) in less time and ship the plate to the customer faster.

Everyone at the shop seemed to think of the big picture: how long it took for a product to ship out the door. In technical terms, they thought about global objectives, not local efficiency.

DLC is a small operation, so thinking about the big picture isn’t too arduous. Just by turning your head, you can see how products flow from the lasers to the brake to packaging and out the door.

The real challenge, both logistically and (especially) culturally, lies with scaling up this thinking. If you have a department head, that person thinks about the efficiency of his department. He or she may be encouraged and even incentivized to think that way.

Say a shop buys a new automated bending center. The owners tell the department head to throw any and all parts at that machine, to make sure it’s fully utilized. That’s fine, but now there’s a bottleneck at the new machine, and it’s actually taking longer for parts to flow through forming, and products are late. The new machine has great utilization and efficiency numbers, but the global objective is suffering.

Having more data can be powerful, but it probably doesn’t guarantee success, especially if people focus on local efficiency to the detriment of global objectives.