Artificial Intelligence as decision maker in engine room maintenance planning: A case study based on interviews with Swedish shipowners of product tankers and their opinions regarding risks, advantages, and challenges

Abstract

The safety and security of a maritime vessel is to a big extent due to the maintenance of the machinery which supports it. In the maritime industry, regulations from the International Maritime Organization and classification societies set regulatory standards of operation. In the product tanker sector, OCIMF sets an even higher standard and controls the vessels which are shipping oil products. For all parties in the shipping industry, maintenance costs are a big part of the operating expenses and following the manufacturers’ recommendation and parts are in many cases changed prematurely. To combat this, already approved methods of condition-based maintenance exist with sensors monitoring machinery. However, due to the new processing power of computers, AI is becoming a prevalent tool in the manufacturing industry (Industry 4.0) and in the evolution towards predictive maintenance, extending the lifetime of parts. This thesis was aimed to find the opinions of AI as a decision maker in engine room shipboard systems based on interviews with shipowners of Swedish flagged product tanker vessels as well as the risks, advantages, and challenges. The study found that development will most likely need to come from the manufactures of systems, be class approved and be shown to improve workload before implementation. The thesis also concludes that it is not likely that the workforce in the engine department could be lowered if an AI maintenance system was introduced and that the general opinion is that the risk of such system is that the workload increased.