When manufacturers use business intelligence (BI) to monitor performance, there's often uncertainty about what specific numbers or trends they should be reviewing. How do you know you're analyzing the right metrics?
In general, it's best to use BI to measure effectiveness, not efficiencies. Efficiency measures an individual or department's performance in a vacuum. But what's the value if a worker on the shop floor is being highly efficient at the expense of the organization as a whole? Effectiveness, on the other hand, measures performance across the value stream, looking at how all of the departments work together as one unit.
The single most important measure for manufacturers is overall equipment effectiveness (OEE).
OEE is a great tool that uncovers hidden waste and emphasizes collaboration by bringing together three performance variables:
1) Availability: This variable increases your understanding of a particular piece of equipment, and whether it's available and running when needed. For maximum effectiveness, you'd want the equipment 100 percent available. If it's only 50 percent available, that indicates a lot of downtime, and that's a problem.
But you also want to understand why the equipment isn't running. Is the downtime due to quality issues? Preventative maintenance? Operators that are taking too many breaks? Business intelligence technology brings together performance indicators, sensors and optics to show you the top reasons the equipment isn't running and the top places where this is occurring. Once you have that information, you're able to measure and maximize availability.
2) Machine speed and performance: This variable is important to OEE because products are priced based on machines running at optimal speed. For those prices to be accurate, you need to understand how fast the machine is running and how well it performs at that speed. As with availability, you want to understand the reasons behind the numbers. Say you have a machine that runs at an optimal speed of 100 strokes per minute, but your BI tools indicate that it's running at only 85 strokes per minute. What's the cause? It might be due to preventative maintenance, or applying the wrong standards.
3) Quality: This last variable looks at how consistently you're producing good parts. If the machine produces 98 good parts out of a run of 100, you have 98 percent good quality. It's important to understand which failures (bad parts) are due to internal and external problems. If it's an internal problem, you're going to incur downtime while you replace faulty pieces of equipment. If it's an external problem, it's a job for warranty service personnel.
Calculating Your OEE
Availability x Speed x Quality = Overall equipment effectiveness
Let's say you're running 50 percent of the time at 85 percent of the speed, with 95 percent good quality. If you were only looking at speed, 85 percent is pretty good. Since you're only scrapping 5 percent of the parts, that's also great. But the equipment's overall effectiveness is actually quite poor when you calculate the OEE:
50% x 85% x 95% = 40 percent effective
OEE performance metrics also align well with a manufacturer's strategic initiatives. Machine performance is tied in to the price of a product, and has an impact on variances, which are a big problem for manufacturers. Variance comes from the three variables that go into OEE: downtime, speed and scrap produced.
Manufacturers typically create a standard for what they think it costs to produce a product; if that cost turns out to be higher, due to lower OEE, it results in variances and profit erosion. For example, if you estimate it costs $10 to produce a product and end up with $2 in variances against it, you just lost $2. In other words, when your OEE diminishes, it has a negative impact on overall profitability.
In the end, everyone in your organization has an impact on OEE. People need to ask themselves what they could do to maximize the availability and the design speed of the machine and produce perfect products every time. And that's the power of OEE: When you look at every single critical piece of equipment you have and combine those metrics to understand your organization's overall effectiveness.