HMS OCEAN was sold to the Brazilian Navy as a fully operational platform. Xpedite was contracted by MoD DE&S to be part of the transition team, focusing primarily on the transfer of the Maintenance Management System (MMS). The project required Xpedite to provide SQEP personnel with RN marine engineering and data engineering capabilities. The project entailed the transfer of their current Unit Maintenance Management System (UMMS) data into an alternative MMS.

Xpedite engaged with industry and the customers to evaluate current MMS systems available on the market to choose the best fit application. The project chose AMOS as an operating system. SQEP Xpedite personnel initially conducted a sanitisation process to remove MoD UK eyes-only data and information. This included data from the asset configuration, maintenance, job information cards, and manuals.

Xpedite provided the toolsets and personnel to extract, clean, and validate the current UMMS data into AMOS. The transfer was conducted within a bespoke transfer toolset developed between Xpedite and SPECTEC, the AMOS vendor. SQEP engineering personnel also manually plugged any data gaps highlighted during the data transfer process.

Xpedite’s team supported the project throughout the disposal process, including aftercare, directly with the Brazilian Navy. All the UMMS data could not be transferred to AMOS; therefore, Xpedite built a data library to contain all the historical data. This was a bespoke application which stored legacy data and allowed interrogation and insights.

Xpedite has significant experience in asset generation, data manipulation, maintenance delivery, and through-life asset management. We are aware of many of the practical issues likely to arise in the implementation of a future MMS. Xpedite has maintained our relationship with the Brazilian Navy to ensure a smooth transition of data into the new system.

The follow-on support requirement included MMS training, maintenance optimisation, operating cycle evaluation, and maintenance loading assessments. It was highlighted during the project that the combination of hard engineering experience and data engineering processes proved extremely effective.