IS MES limited to calculating OEE?
DEfinition and calculation of oee
The Overall Equipment Effectiveness (OEE) is defined by the NF E60-182 standard as the ratio of useful time to required time. It is intended to track the utilization rate of machines (measuring the efficiency and level of use of equipment). The OEE is a key indicator whose calculation and analysis help to determine the performance of one or more production lines and identify areas for improvement and action plans for optimization. It incorporates all components of machine efficiency and provides a comprehensive and accurate overview of production performance. It is currently the most widely used indicator in the company.
breakdown of OEE
other OEE calculations
There is a second calculation method which consists of multiplying Operational Availability (or Availability Rate) by the Performance Rate and the Quality Rate:
- Operational Availability: measures productivity losses related to unplanned downtime: breakdowns, waiting times, changeovers, etc. The higher this rate, the more the machine is available for production.
- Performance Rate: measures performance deviations due to variations in speed (under or overspeed) and micro-stops. A machine that runs at idle speed or accumulates micro-stops leads to a drop in performance.
- Quality Rate: measures productivity losses related to the production of parts that do not meet quality requirements. It is therefore affected by the number of parts declared non-compliant.
what is oee (overall equipment effectiveness)?
Calculating oee
The Overall Equipment Effectiveness (OEE) is calculated by dividing the number of correctly manufactured parts by the number of parts that the machine should have produced in its theoretical production time, taking into account the cycle time of each part. To simplify the operation, simply divide the total production time for compliant parts by the total theoretical production time (i.e., useful time/required time).
why calculate the oee?
Calculating the OEE is essential for identifying losses, finding areas for improvement, and increasing the productivity of production equipment… in order to achieve sustainable continuous improvement.
It is calculated by multiplying the three indicators mentioned above (Operational Availability, Performance Rate, Quality Rate), all of which are between 0 and 100%.
The closer the OEE is to 100%, the more efficient the production is. It focuses on identifying losses responsible for non-productivity. These can be of various kinds and enable manufacturers to take appropriate action by:
- Reducing the time spent on an operation
- Reducing operator errors
- Reducing machine downtime
- Improving quality
- Increasing team productivity
- Capitalizing on expertise
- …
oee: the benchmark indicator for tpm (total productive maintenance)
By identifying the bottleneck resource, i.e., the resource that causes the bottleneck and thus limits the production flow rate, we can improve the OEE.
By relating useful time to opening time or total time, we obtain the Overall Equipment Effectiveness (OEE) and the Economic Rate of Return (ERR), which define performance from a more generic point of view.
TPM, which officially originated in Japan in 1971, is an evolution of maintenance methods that aim to improve machine performance by identifying the main causes of failure in advance. Once detected, these are analyzed in order to minimize unplanned and unproductive downtime on production lines.
some concepts related to the operating times of a means of production
- Total time (Tt): corresponds to all possible states of the means, the time during which it is theoretically usable (24 hours for a day, 68 hours for a week, etc.).
- Opening time (To): is equal to the total time minus the workshop closing time. It corresponds to the working hours, including downtime such as cleaning, meetings, breaks, preventive maintenance, etc.
- To = total time – workshop closure
- Required time (Tr): period during which the means of production is engaged with the intention of producing (including unscheduled and scheduled downtime). Tr = opening time – (breaks, adjustments, staff absences, etc.)
- Operating time (Tf): time during which the means of production manufactures parts (good or bad). Tf = time required – (series changes, breakdowns, etc.)
- Net time (Tn): operating time during which the means of production produces parts in accordance with the reference cycle time. This time is not measurable. Tn = Operating time – speed variations
- Useful time (Tu): Time during which the means of production manufactures good quality parts. Tu = net time – time spent producing non-quality
Definition of MES
MES software (Manufacturing Execution System) is a computer system whose primary purpose is to collect real-time production data from a cell, workshop, production line, etc. in a factory in order to optimize production management. The process is controlled, quality and traceability are impeccable, and industrial performance is successful.
MES and oee
Most MES solutions focus on a very popular indicator, OEE (Overall Equipment Effectiveness). Integrating production events as diverse as unexpected downtime, rejects due to poor quality, machine speed reductions, and their impact on productivity on a scale of 0 to 100, OEE (Overall Equipment Efficiency) appears to be the universal performance indicator par excellence, and therefore the ultimate measure of an MES, whose goal is, after all, to increase production performance.
Following this reasoning, would MES essentially boil down to calculating and monitoring OEE? Is it that simple?
the keys to oee success
The keys to the success of OEE can be summed up in two words: synthesis and comparison. Most manufacturers had noticed for themselves that productivity gains could be made in machine downtime due to jams, adjustments, or other causes, and that rejects (broken parts, damaged products, or products outside tolerances) required higher production rates than those normally required to ensure production. But it is difficult to objectively measure the impact of a stoppage when there are dozens of them every day, some of which completely block the line, while others last only a minute or two. It is difficult to quantify the real significance of a few hundred rejects on a machine that produces several thousand items per hour, or a drop in speed for a few minutes each time the machine settings are changed…
This is where the genius of OEE lies: reducing all productivity losses (stops, non-quality, slowdowns) to time, including for parameters that are not directly involved at the outset (slowdowns) or not involved at all (rejects for non-quality)!
Simplicity of oee implementation
One of the main arguments in favor of implementing a OEE is its simplicity of implementation. This argument is legitimate, as long as suitable software is used. At the same time, one may wonder whether software is necessary: the calculation of OEE seems so simple that implementing it using a tool such as Excel seems sufficient…
There are two reasons why it is essential to use suitable software:
The first is that the simplicity of OEE calculation is only apparent. The formulas for calculating OEE and its breakdown (availability rate, performance rate, quality rate) are not very complex, but they are based on time. For these to be accurate, a real-time system, rather than retrospective data entry, is the only truly reliable solution. Furthermore, while calculating the OEE for a single machine is straightforward, calculating it for a production line where machines are interdependent is more complicated.
It involves the concepts of clean stops (due to the machine itself) and induced stops (material shortages due to the stoppage or under-cadence of an upstream machine). In this case, there is a significant risk of misinterpretation of a simplistic calculation.
The second is that the objective is to increase productivity, not the opposite! In addition to being a source of error, entering information for OEE calculation without the support of dedicated software is very time-consuming and distracts operators from their primary production objective. Dedicated software minimizes data entry and makes it easier when it is essential (e.g., pressing a single button to identify the cause of a stoppage).
It is therefore essential that manufacturers implement a tool for measuring and monitoring OEE in order to improve their productivity. But should they stop there?
be aware of the limitations of oee
As essential and indispensable as it may be, the OEE indicator is not without its flaws, and it is important to be aware of its limitations.
First of all, even though it incorporates many production event parameters, it does not incorporate all of them. For example, when taking non-quality into account, only the time lost in producing defective items is included in the indicator, but the corresponding loss of material (if it is not recycled) and its recovery are not included.
Many manufacturers therefore use other indicators (often referred to as KPIs, or Key Performance Indicators) alongside OEE to track material losses, energy consumption, etc. It is therefore important that MES software does not limit itself to calculating OEE and directly derived indicators, but is also capable of delivering other performance indicators, or allows them to be easily constructed.
MES: oee and much more
System is the key word here, because with the vast amount of data collected on a production facility, only a structured system—the ISA-95 standard is a great help in this structuring—will enable it to be used effectively to determine the most promising avenues for optimization. The ability of the MES software to process these different avenues for optimization, either immediately upon implementation or gradually, is essential.
The OEE indicator is an application of the DMAIC (Define, Measure, Analyze, Improve, Control) method, which should be extended to all areas of production that can be taken into account by a true MES system. In this respect, OEE is an emblematic indicator of the general approach to continuous improvement, which is the key not only to productivity but also, more generally, to the competitiveness of manufacturers, which includes innovation in particular.
The MES COOX solution allows you to implement all production optimization methods in an integrated and modular way, regardless of which ones you choose to prioritize.
improve your overall equipment effectiveness with mes
optimize the time spent on a machine
Planned or unplanned downtime hurts productivity. It is therefore important to record and analyze them, as they have a significant impact on the Overall Equipment Effectiveness (OEE).
Induced downtime corresponds to machine downtime (lack of personnel, parts saturation, power failure, supply failure, etc.).
Clean downtime, on the other hand, includes breakdown time, operational downtime, and functional downtime (planned downtime).
Digitization of operations
By digitizing the causes of downtime rather than recording them on paper and transmitting this information in real time from the machine, the operator saves time and helps to optimize response times. As a result, manufacturers increase their productivity.
operator assistance
In order to reduce downtime, it is equally important to guide operators in the performance of their tasks, for example by displaying the various steps of the operations to be carried out, with a progress report on their completion, and by integrating instructions, plans, videos, photos, etc.
This avoids interpretation and minimizes human error.
preventive maintenance
Preventive maintenance is also a major factor that affects productivity. By anticipating potential breakdowns and ensuring that machines are working properly, it reduces breakdowns, ensures safety, reduces downtime, and thus improves production.