**London**: Joy Basu, CEO of Smart Ship Hub, advocates for a shift from scheduled to predictive maintenance in shipping, utilising data-driven innovations to reduce costs, enhance operational efficiency, and promote sustainability in maritime practices amidst evolving technological advancements.
In a substantial shift in the maritime sector, Joy Basu, the Chief Executive Officer of Smart Ship Hub, has emphasised the pressing need for the shipping industry to move away from scheduled maintenance towards a predictive maintenance model. This transition is framed as not only an upgrade but rather as an essential evolution for the future of shipping amid rapidly advancing technological innovations.
Scheduled maintenance, long considered the industry standard, typically dictates servicing based on predetermined timelines irrespective of a vessel’s actual condition. This method, Basu suggests, is becoming increasingly obsolete as vessels and their components rely on technical innovations providing data-driven insights tailored for optimal maintenance schedules. By adopting predictive maintenance technologies, shipping companies can gain a significant competitive advantage while simultaneously reducing operational risks and increasing profitability.
Current advancements in the field include digital twin technology, AI-driven analytics, and cloud-based fleet management, all of which are fostering this transition. Predictive maintenance capitalises on data such as engine performance and fuel consumption to ascertain the most efficient operational methodologies. This data-driven approach facilitates better fuel management, environmental sustainability through lower emissions, and overall improved performance of ship operations.
Basu highlighted the pitfalls of the traditional maintenance approach, explaining that it often results in either over-maintenance—where components are replaced prematurely, leading to unnecessary costs—or under-maintenance, where equipment fails before the next scheduled service occurs, causing unexpected downtimes. He elucidated that predictive maintenance distinguishes itself by utilising sensor measurements and sophisticated algorithms to foresee the optimal timing for maintenance interventions.
The efficacy of timely maintenance is crucial for maritime operations, as efficient vessel upkeep minimises the risks of failures or breakdowns that could lead to accidents or delays, ultimately safeguarding the crews on board. While recognising that maintenance incurs costs, Basu noted that strategic asset management could yield savings by averting more expensive repairs associated with neglected or deferred maintenance activities.
The evolution from condition-based maintenance (CBM) towards predictive strategies reflects a significant step forward, enabling shipping practices to shift from reliance on averages and statistical assumptions to interventions that are specifically tailored to the condition of the equipment. He elaborated that this approach allows for more efficient resource deployment and minimizes the operational impacts of maintenance activities on vessel operations.
Despite the apparent advantages, the maritime sector continues to grapple with various challenges—both technical and structural—when implementing effective condition-based maintenance systems. Basu posited that many of these challenges could be mitigated through the deeper integration of data analytics within maintenance workflows, ultimately leading to the formation of a data-driven condition-based maintenance (DCBM) process.
By marrying traditional maintenance methods with cutting-edge analytics, Basu argued that the industry has the potential to vastly enhance the reliability and efficiency of marine vessels. This vision includes the development of advanced diagnostic systems and real-time monitoring capabilities, as well as comprehensive digital platforms aimed at eradicating inefficiencies and optimising workflows.
As the maritime industry stands on the cusp of this shift towards predictive maintenance, the companies that adopt these innovations are expected to enjoy the benefits of reduced costs and enhanced operational effectiveness. The shift from a schedule-based approach to a predictive method marks a notable transformation in the industry, aimed at improving the overall quality and reliability of maritime operations.
Source: Noah Wire Services