Job shops provide their customers, typically larger OEMs, with an array of custom parts, and the variety of equipment used to produce those goods can be just as specialized. Does your job shop have numerous machines performing multiple functions? Have you determined how much value each is truly bringing to your business and whether each has resulted in a positive return on its investment?
Product mixes can vary daily and volumes fluctuate widely, meaning machine flows are being continually reconfigured. Measuring overall equipment effectiveness (OEE) manually can be a challenge, but knowing that data can help a job shop monitor performance and uncover hidden waste. That’s why many small manufacturers rely on business intelligence (BI) software to determine OEE, which is the single most important measure for job shops that want to discover and correct inefficiencies and determine a machine’s effectiveness.
OEE can expose many opportunities by highlighting three major performance variables:
In an ideal world, equipment would be 100 percent available for maximum productivity. A problem arises when there’s a lot of downtime and that machine is sitting idle for extended periods of time. Knowing whether your equipment is operating at peak availability or is simply taking up floor space most of the time will help you understand whether it’s adding value to your operation.
Ultimately, you want to understand why the equipment isn't running so you can make corrections. Are there quality issues? Is preventive maintenance being performed? Are operators being called upon to help in other areas? Is it really needed or can its function be performed by another piece of equipment or outsourced for a lower cost? With the use of business intelligence technology, a company can bring together performance indicators, sensors, and optics to reveal when and where downtime is taking place and the reasons for it. From there, you can address any issues and take measures to resolve them.
2. Machine Speed and Performance
You price products based on the assumption your machines are running at optimal speeds. As with availability, you want to understand why a machine isn’t running as fast as it should and how well it performs at those speeds. With BI software, you can see a comparison of optimal performance with actual output.
More importantly, the BI tools automatically collect data to determine why a machine isn’t performing at optimum speeds or producing maximum output. Sometimes there’s an acceptable reason for an interruption, such as scheduled preventive maintenance or system upgrades. Or, maybe the issue needs to be addressed, such as mishandled production schedules or delays during setup. Outlining a menu of downtime causes on the machine interface also can help operators quickly document any issues and determine if those issues happen repeatedly and need to be addressed, or if it’s a one-off problem that won’t persist.
Consistency is the key to efficiency and quality. There are internal and external factors that can interfere with a machine’s consistent output and cause failures, and identifying those factors requires accurate data. External factors, such as faulty or missing components, will need to be addressed with the provider and may initially be out of a job shop’s control. However, if the supplier is repeatedly sending faulty parts, the data collected by your BI tools can serve as supporting evidence for taking corrective measures. Internal issues, such as a faulty piece of equipment, employee error, or breakdowns, can be detected and addressed as well.
OEE = Availability x Speed x Quality
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 percent x 85 percent x 95 percent = 40 percent effective
Your job shop’s profitability will slump if the cost to produce a product exceeds expectations due to lower OEE. Every piece of equipment contributes to your output, and knowing which machines are contributing to profitability (and which aren’t) will help you focus on your greatest assets, maximize efficiencies, and leverage data to improve your bottom line.
To understand how your OEE can be improved through the implementation of business intelligence, reach out to a Wipfli consultant, and begin to improve your equipment’s impact on ROI.