speedikon® C has always supported the comprehensive documentation of all equipments and technical installations; further many of our customers use the system the support their planned preventive maintenance. Thereby all technicals assets are very known and docuvmented on a global scale.
The next big thing is looking at the daily life of the equipment, meaning the documentation of all messages and fault reports the techical asset generates. In most cases these messages and errors are already collected within a central control system, processed and handled by the technician in charge and finally resolved. A centralised documentation of all those messages is usually missing though, which means that a downstream analyses concerning the error-proneness and frequency are almost to impossible carry out.
In order to facilitate those analyses and enable our customers to evaluate their equipment precisely, we combined our know-how in the areas of asset documentation and data capture and created a powerful solution.
All messages and reports are collected from the technical installations and control systems using standardised interfaces and are stored centrally. Error codes and cryptical messages are processed and forwarded using corresponding matching tables. To avoid being flooded by messages and error codes, we have implemented intelligent algorithms. These algorithms analyse all incoming messages and ensure that only the “real” messages are stored. The preprocessed messages are the stored in a specialised table and linked to their corresponding equipment. If needs be, these messages and also be processed using existing workflows.
Using the reporting tools built-in into speedikon® C, all collected messages can be analysed and evaluated. By the push of a button, a user can examine how often a certain asset has failed last month, how long each downtime lasted, and wheter or not the reason for the failure was the same every time. The conclusions of these analyses can be used for various strategic decsisions. Typically the are used to optimise maintenance measures or the stock-keeping of spare parts. From a more strategic point of view they are also helpful for judging the sustainability of repairs or even to influence future investment decisions.
The system thereby creates a living digital twin, that is constantly enhanced using current equipment information and status.