Efficiency and productivity are among the top issues manufacturing companies have to tackle in times of global competition. In this article, you will learn how to assess the productivity of your machines and initiate appropriate measures. Key performance indicators (KPIs) like the Overall Equipment Effectiveness (OEE) support you in this endeavor.
Let’s say you have machines and equipment on your shop floor and you want to know how well a particular machine is running. One option could be to ask one of the supervisors or shift leaders. They will tell you what they think, but you won’t get hard facts. Significant and reliable KPIs would now be great. And they exist indeed.
Overall Equipment Effectiveness
Overall Equipment Effectiveness (OEE) probably is the best-known production KPI. OEE is calculated from three factors:
- Availability: ratio of machine utilization to available time – one could also say productive utilization.
- Performance: ratio of the current speed to the planned speed – one could also say achieved performance.
- Quality: ratio of the good units produced to the total quantity produced – one could also say yield.
If you multiply these three factors, you usually get a number between zero and one or a value between 0 and 100 percent – this is just a matter of how you want to present data. But how do you get the data necessary to calculate the three factors? Manufacturing IT supports you in this task, e.g. a Manufacturing Execution System (MES).
Collecting and processing machine data with MES
One of the main tasks of an MES is to collect shop floor data. These include:
- Machine data like machine statuses or malfunction reasons
- Process data like temperature or pressure
- Energy data like power consumption or power input
- Order data like quantities and times
- Quality data like scrap and absence reasons
Ideally, you get most data directly from the machine or machine control. Other information that the machine does not provide is entered manually on an industry PC or tablet. The MES posts the collected data and calculates KPIs like the OEE.
Increasing OEE
OEE is a KPI that can be used for nearly all company sectors to measure productivity and optimize processes. The management gets a quick overview of how well production is running. Division managers, supervisors and shift leaders break down the KPI to single machines. They are also interested in how the KPIs develop over time. Operators on the shop floor get a better feel for their current performance. Now let’s have a look at the three factors and how you can improve them.
Availability
If you use your machines more efficiently, availability increases in terms of overall equipment effectiveness. It has proven useful to implement planning solutions that are integrated in the MES or offered separately as Advanced Planning and Scheduling system (APS). It is key here that production planning integrates the collected data. Considering supporting processes like maintenance or intralogistics can also be of great help to reduce downtimes and interruptions to a minimum! Not to forget predictive maintenance that can further support you.
Performance
If your process allows, you can shorten cycle times to increase performance and produce more parts in the same time. It is also useful to reduce so-called micro-stops, i.e. short interruptions, to increase performance in terms of the overall equipment effectiveness. Use an MES to find out how often and how long your machines have unplanned downtimes or how the cycle time changes over a specific period of time. Artificial intelligence supports you in analyzing the conditions achieving the best results. Analyzing historical data also helps you deduce the perfect cycle time.
Quality
Quality has always been a decisive factor. The less scrap you produce, the less material, time and energy is wasted. That is why quality is a factor in calculating the OEE. Your objective must therefore be to achieve zero defect manufacturing. By the way – even rework has a negative impact on the quality rate and using the available resources as efficiently as possible is a key factor.
Three factors for an integral assessment
Choosing these three factors to calculate the OEE is not arbitrary as the factors interact. If you try to get the most out of the performance, the machine may wear quickly and the quality suffers. The performance increases but availability and quality drop. An experienced operator tries to balance the three OEE factors. And who else could that be than the operator spending hours on the machine and production process every day? Therefore, KPIs should not only be considered in retrospect but they should also be displayed for the current shift where operators can monitor them.
Practical example MES HYDRA X
Use HYDRA X, the MES of MPDV, to collect, evaluate and visualize all required data in real time. The mApp Machine Performance KPIs offers various charts like the OEE report or the OEE profile. The report can compare several machines with each other. The profile can provide an OEE analysis over multiple shifts or days.
HYDRA X also computes further KPIs that support you in assessing the productivity of your machines. This includes:
- Capacity utilization
- Assignment rate
- Scrap rate
- Technical efficiency
- MTBF (Mean Time Between Failure)
Read more about the calculation of KPIs like the OEE with HYDRA X.
