Keynote. The evolution of ship design from a manual toward a computer-aided, digital approach has been drastic after the 1970s, with the explosive development of computer hardware and software systems. In today’s era of smart digitalization in the frame of Industry 4.0, recently introduced digital/software tools and systems increase the efficiency and quality of the life-cycle ship design process, but also the operational complexity and the demand for proper training of users of software platforms. Parametric optimisation and simulation-driven design, product lifecycle management, digital twins and artificial intelligence are nowadays frequently used by the maritime industry during the commissioning/quality control activities and in the various phases of ship design, ship operation and ship production. This paper presents an overview of notable developments in the above areas and the way ahead to respond to present and future challenges of the maritime industry.

Shipowners need to prepare for low-emission fuel alternatives to meet the IMO 2050 goals. This is a complex problem due to conflicting objectives and a high degree of uncertainty. To help navigate this problem, this paper investigates how methods that take uncertainty into account, like robust optimization and stochastic optimization, could be used to address uncertainty while taking into account multiple objectives. Robust optimization incorporates uncertainty using a scalable measure of conservativeness, while stochastic programming adds an expected value to the objective function that represents uncertain scenarios. The methods are compared by applying them to the same dataset for a Supramax bulk carrier and taking fuel prices and market-based measures as uncertain factors. It is found that both offer important insights into the impact of uncertainty, which is an improvement when compared to deterministic optimization, that does not take uncertainty into account. From a practical standpoint, both methods show that methanol and LNG ships allow a cheap but large reduction in emissions through the use of biofuels. More importantly, even though there are limitations due to the parameter range assumptions, ignoring uncertainty with respect to future fuels is worse as a starting point for discussions.