Bureau Veritas advances Digital Class with New Tool for Machinery Maintenance

Bureau Veritas (BV), a world leader in testing, inspection, and certification, has launched a new digital tool – Machinery Maintenance – that connects directly to owners’ Computer Machinery Maintenance System (CMMS) and helps them transition to optimized machinery maintenance schemes.

For ship operators to sail safely, their vessels must undergo regular inspections of their machinery equipment and systems. However, most modern ships have more than 300 separate pieces of machinery onboard, each with its own specific maintenance requirements. This poses a challenge to ship owners and operators on how to conduct machinery maintenance regularly, but also efficiently. For normal machinery maintenance scheme, this process is done through an in-person inspection of all machinery items by a BV surveyor once every five years, during the renewal survey. But today, a large part of the world’s fleet are using more optimised survey schemes such as Continuous Machinery Survey scheme (CMS) or a Planned Maintenance Survey System (PMS), by which each machinery item is given an individual maintenance schedule and scope.

The new BV Machinery Maintenance platform connects ship operators’ maintenance system with BV’s system, thereby facilitating the elaboration of a Planned Maintenance Survey System (PMS) plan with online guided booking. BV has developed an automated integration  that connect to owners computer maintenance management systems (CMMS) to collect data on the maintenance status of all machinery items, manage modifications to onboard equipment, and provide access to manufacturer manuals from planning initialization to in-service operations. It enables ship managers and BV surveyors to get a clear and comprehensive overview of onboard machinery maintenance, efficiently prepare for surveys and assess the machinery maintenance conditions. Pilots are currently being successfully deployed.

Bureau Veritas’ technical and digital experts are also currently working to enable the tool to support the promising Condition Based Maintenance (CBM), where maintenance is determined through condition monitoring by performing diagnosis and prognosis on each machinery item’s actual condition. The next step, when historical data is captured, will be to develop predictive maintenance schemes based on artificial intelligence (AI).

With this new tool, BV further enhances the Digital Classification experience, which is a key focus of its 2025 Strategic Direction. Moving forward, BV aims to reinforce digital and collaborative class processes and move towards optimized and predictive survey schemes.