“If you can’t measure it, you can’t improve it.” – Peter Drucker
One of the most important quotes in business management couldn’t be more important for Australian manufacturers today. With the right metrics, you can understand what’s working in your production line, and what’s not. You can find weak spots and barriers to efficient production. You can see quality issues causing rejects by customers, and the processes slowing down your operators down.
The biggest question is, where do you begin?
Here’s our quick guide to the 14 most important metrics for Australian manufacturers:
OVERALL EQUIPMENT EFFECTIVENESS (OEE)
OEE is a best-practice metric for measuring the effectiveness and efficiency of a manufacturing process. Calculated as the product of three factors– Availability, Performance and Quality – it shows a percentage of the planned production time that is truly productive. An OEE score of 100% represents perfect production: manufacturing only good parts, as fast as possible, with no downtime.
OEE = Availability x Performance x Quality
(We explain more about Availability, Performance and Quality in the points below)
Why measure it:OEE is useful as both a benchmark and a baseline. As a benchmark, use OEE to compare the performance of one piece of equipment to similar equipment, industry standards, or to results for different shifts working on the same equipment. As a baseline, use OEE to track progress in eliminating losses/waste from a piece of equipment. In fact, OEE is so important we’ve dedicated an entire blog series to help you. Read this basic introduction to OEE, and how to avoid common OEE mistakes.
Availability is the percentage of time the machine is ready to produce, working properly, and not in the middle of changeovers or adjustments. This metric takes into account any events that stop planned production, whether unplanned (equipment failure, material shortages, etc.) or planned (product changeovers).
Availability rate = Available time (scheduled operating time − downtime) ÷ Scheduled operating time
Even though it’s not possible to eliminate planned events, you still need to include them in the calculation as they represent time that could otherwise be used for manufacturing. In many cases, this time could be significantly reduced (this is often the case for changeovers, as we discuss above in #2).
Why measure it: You need to measure Availability to calculate OEE. But also, by itself, the metric can help you identify those things that are negatively affecting machine availability, such as unplanned equipment downtime, material shortages and changeover time.
This is the ratio of output produced compared with a standard. For standard output, use the best output rate known to be produced on the machine. This rate takes into account Performance Loss, which is anything that causes the manufacturing process to run at less than the maximum possible speed. This could be machine wear, substandard materials, jams, errors, and so on.
Performance rate = Actual output ÷ Standard output
Standard output = 500 parts
Actual output = 250 parts
Performance rate = Actual output ÷ Standard output = 250 ÷ 500 parts = 50%
Why measure it:You need to measure Performance to work out OEE. But it also helps you identify, and tackle, two of the six big losses that are the most common causes of equipment-based productivity loss in manufacturing. In this case, we’re talking about small stops and slow cycles. For example, there might be times where the equipment stops for a short period of time before the operator resolves the stop. For example, it might be caused by incorrect settings, material jam or blocked sensor. Even though it’s only a minute or two, this is a performance loss.
Quality rate is the ratio of good output compared with actual output. It takes into account Quality Loss, that is parts that do not meet quality standards and require rework or scrapping.
Quality rate = Right-first-time output ÷ Actual output
Actual output = 250 parts
Defective parts, rejects, scrap = 25 parts
Good parts = 250 – 25 = 225 parts
Quality Rate = Right-first-time output ÷ Total actual output = 225 good parts ÷ 250 actual parts produced = 90%
Why measure it: Again, you need to measure Quality to work out OEE. But it also highlights another two of the six big losses: production rejects and start-up rejects.
MANUFACTURING CYCLE TIME
Cycle time is the total time from the beginning to end of a process – the time taken to convert the raw goods (or parts) into finished goods. The total time an item spends in the manufacturing system between the order release and completion is the “total manufacturing cycle time”.
Manufacturing cycle time = Process time + Move time + Inspection time + Queue time
Why measure it:Knowing your manufacturing cycle time means you can make better-informed decisions about your business – how to adapt your processes and improve efficiencies. Reducing this time can deliver reduced costs, better response to customers and increased flexibility.
A changeover is the process of converting a line or machine from running one product to another. So, this metric simply measures the speed or time it takes to make the switch. Depending on your equipment and the product, a changeover can last minutes, hours or even days.
Why measure it:Tracking this metric helps you identify how and where you can improve your changeover times. For example, using equipment that is easier to set up and configure can shave valuable minutes of the changeover process. (This software helps deliver a more streamlined operation with quick changeovers, as well as validation and error detection. Find out how Kimberley-Clark Australia achieved this.)
One of the simplest manufacturing metrics, throughput is also one of the most important. It measures the average number of units being produced on a machine, line, unit or plant over a specified period of time. For example, you might measure units per minute.
Why measure it:Throughput is the heart monitor of your production line. If your throughput suddenly decreases, you know that you have an issue on the line. Improving throughput can be achieved with automated equipment, lean processes and so on (Lean isn’t just for the big guys – read more about how SMEs can benefit from Lean in this article.)
A favourite for operations staff, this metric indicates how much of the total manufacturing output capacity is utilised at a given point in time. In other words, to what degree are your potential output levels being met or used? Capacity utilisation is shown as a percentage of total potential output. So, when your facility is said to be working at full capacity, there is 100% capacity utilisation.
Why measure it:This metric gives insight into the overall slack in your facility. It also shows trends in overall manufacturing and is an important measure of inflation. For example, earlier in 2018, NAB reported that the capacity utilisation rate for Australian manufacturers was trending upwards, which is a good sign for future investment and employment.
SCHEDULE OR PRODUCTION ATTAINMENT
How often does your facility achieve its target level of production within the set time? This is the “schedule attainment score” or “production attainment score”. This metric measures the actual production as a percentage of the scheduled production.
Why measure it:Lower percentages may indicate that a machine isn’t optimised properly or that the production team isn’t able to plan for real-life changes.
PLANNED MAINTENANCE PERCENTAGE (PMP)
Planned maintenance percentage (PMP) is a widely used measure for maintenance staff. It shows the percentage of the total number of maintenance hours spent on planned maintenance activities in a given time period. For example, if 300 hours were spent on planned maintenance activities out of 400 total hours spent on all maintenance, the PMP is 75%. This could also be shown as a ratio metric, which indicates how often scheduled maintenance takes place versus more unplanned (emergency) maintenance — in this case 3:1.
Why measure it:The idea is to use PMP to reduce the incidences of unplanned work. Why? Because unplanned maintenance can cost up to 9 X more than planned maintenance due to rushed parts, service callouts, downtime, overtime and so on. Read the three steps to a successful planned maintenance program, and find out the difference between preventive maintenance vs breakdown repair.
This is one of the oldest metrics in the book. You can measure First Pass Yieldand Overall Yield:
First Pass Yield (FPY)is the percentage of products that are manufactured correctly and to specifications the first time. No scrap, re-runs or rework.
FPY = (units of products completed from process to specification with no rework) / (total units of products entering the process).
If 100 units enter a process and 99 are finished to specification and 3 are reworked:
First Pass Yield = (99-3) / 100 = 0.96 = 96%
Overall Yieldis the total final output of a production line. It includes any units that had to be reworked due to defects or errors, but still got the stamp of approval.
Why measure it: Yield helps you measure manufacturing flow, letting you identify problems or failures in the process. FPY is a starting point for measuring a single operation in the line, so you can see whether it is contributing to rework. This helps you eliminate waste from that process.
This metric tells you how many times customers reject products or request returns because they have received bad-quality or out-of-specification products. The calculation applies to all shipped units, including parts, and should include items that had to be reworked by customers.
Why measure it: It is direct evidence of your quality standards. However, if you are measuring all of the above correctly and acting on the results, this should never be a high number!
SUPPLIER QUALITY INCOMING
This metric is the percentage of good quality materials coming into the manufacturing process from a supplier. Alternatively, you can measure the percentage of bad quality materials coming in, i.e. supplier defect rate.
Why measure it: Measuring supplier quality is crucial in determining a product’s final quality. By measuring supplier quality, you can ensure your suppliers are meeting their KPIs. If necessary, you can use the information to negotiate on a better price or find an alternative supplier.
CUSTOMER FILL RATE
Also known as on-time delivery or perfect order percentage, this metric shows you the percentage of your orders that are shipped in full and on time as a percentage of all your orders. In other words, it tells you the likelihood that you will effectively service your customers. The higher your fill rate, the more likely your customers are to trust you and choose you over your competitors. It also helps show how efficient your production line is when it comes to getting the product out of the door, and how successfully you are keeping to production schedules.
Why measure it:This metric is key to the order-management process and will ultimately determine your customer relationships. Never aim lower than 100%.
It’s one thing collecting the right metrics, and another thing acting on the results. As former Hewlett-Packard CEO, Carly Fiorina said, “The goal is to turn data into information, and information into insight.”
That’s where iDSnet and the OFS reporting module can help. This integrated module will deliver seamless OEE dashboards, so you can see OEE and downtime data in real time and respond to situations as they are happening. As a result, your business is able to achieve continuous improvement and successfully drive Lean and Six Sigma strategies.
Speak to our OEE specialists to find out how iDSnet powered by OFS can transform your business.
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