TPM stands for Total Productivity Maintenance. TPM is a maintenance management approach that foresees autonomous maintenance in production and service processes, with the participation of all employees, adopts an approach to prevention rather than troubleshooting, and maximizes machine and equipment efficiency.
TPM aim to change the company culture by developing employees machines and equipment.
It has detailed features such as efficiency measurement, evaluation, goal determination and comparison of the actual situation according to the goals.
It is seen that the TPM methodology aims to increase the usability as much as possible. It is seen in our field experience that the parameter that brings the OEE value down the most in the A, P, Q breakdown is usability.
For successful TPM(Total Productivity Maintenance), problems should be brought to the attention of managers by analyzing the current situation with real data. So, how accurately and precisely can you measure this in current situation?
Detailed and accurate data collected from the field are required for statistical process control. How much can you collect or how far is its accuracy from 100%?
IF YOU CAN’T MEASURE IT, YOU CAN’T FIX IT
TPM has the same goal with succesful companies, to create a profitable and sustainable organization. If we need to list some of them;
The realization of these points passes through a properly managed TPM system, and the properly managed TMP system requires a correctly adapted MES. I can give an example to reveal this clearly.
For example; A company that is not an MES user has to operate the TPM manually and is dependent on the human factor, so it has to accept the errors brought about by this dependency.
But this is not the case for companies with a correctly built MES. The records that are formed as a result of an event such as equipment signals, Panel session logs, “Fault Intervention” transactions are processed flawlessly in the MES and presented to the user with accurate analysis and fast feedback. In this way, the MES user can make error-free and efficient TPM management.
Digitalization is the name given to the process of transferring accessible information and existing resources (for example, your documents, processes) to digital media that can be read by a computer.
Manually tracking maintenance time is sometimes a forgettable issue. This can lead to serious costly problems, but we can automatically track the times in the digital environment, or we can access this information from any computer in the field and perform faster maintenance operations instead of going to the office during the intervention and getting the manual of this machine. It even allows us to access processes like what has been done before, instead of searching in files and archives.
In today’s world, where everything is speed, digitalization gives us serious speed. Rapid intervention in the maintenance process also means shorter uses of time and more production.
An element of autonomous maintenance is that the operatör should know the production machine well, should be aware of possible malfunctions and can understand their leading signs and take the necessary measures or alert the relevant units.
When the maintenance team is triggered by notification and come to the machine, they can receive, read or even follow the instructions regarding maintenance operations paperless through Panel PCs (They have great interface). This will significantly increase the impact of everyone from maintenance team and operators in process management.
Tracking equipment lifetimes will increase control over the entire system.
MES systems, which allow anomaly monitoring, will prevent possible malfunctions on the machine or production of faulty products.
What are the important KPIs in maintenance processes?
There are two important KPIs that are used to demonstrate whether maintenance processes are running correctly.
– MTBF (Mean Time Between Failure): Mean time between failures is the estimated time between natural failures of a mechanical or electronic system during normal system operation. MTBF can be calculated as the arithmetic mean time between failures of a system. The purpose here is to give information about when the failure will occur again. In addition, it is aimed to extend MTBF in planned maintenance.
– MTTR (Mean Time to Repair): Average time until repair is called. It refers to the average repair time expected since the failure was detected. This criterion is the basic criteria of maintenance services. If we define the MTTR value briefly, it gives us the time between the best product that came out before the failure and the best product that came out after the failure was repaired.
We can say that Predictive Maintenance is the correct and adequate maintenance by taking data from the monitored equipment without any deterioration. It is in the same logic with the periodic maintenance of vehicles. The same logic applies to molds or machines in the production area, just as certain parts need to be changed and maintained after vehicles travel a certain kilometer. When a certain part is produced, some parts and equipments must be checked. The difference is that there is no clear maintenance schedule at the production site as much as the vehicles. This is where the MES solution comes into play. It can save us from more maintenance costs by processing data such as the number of production, temperature and vibration collected from the production site, and predict the maintenance time more clearly.
There are 8 major losses that limit equipment effectiveness. These;
The situation we often encounter in company field analyzes; Since the planned maintenance works for longer setup times than it should be due to its inability to manage correctly, its usability value is very low because it cannot follow the waste-discard amount clearly and can not eliminate the root cause because of the excessive amount of time and quantity.
We’ve blended our perceived value with the solutions we provide, while transforming our customers to our solution partners, and are working tirelessly to bring our services to every point of the globe.
