1. What measures has your company taken to develop autonomous ship?
What is the purpose of launching the world’s first autonomous shipping firm, Massterly?
Wilhelmsen came together with Kongsberg in 2018 to create Massterly, a joint venture company that will allow the two firms create a complete value chain for autonomous maritime logistics; covering design and development of vessels and shore systems, project management, control systems, approvals from relevant authorities, insurance, logistics services and safe and efficient vessel operations.
The main purpose of Massterly is to develop environmentally friendly, safe and cost-efficient logistics, enabling a shift in transportation from congested roads to the sea. For short-sea shipping, the major cost drivers are crew and manual port handling. These costs can be significantly reduced by introducing autonomy technology and a new competition area for maritime players is created.
A “Remote Control Centre” is under construction at the Massterly (c/o Wilhelmsen Ship Management) office in Norway. When the needed customer base is established, Massterly will provide 24/7 manned monitoring and control from shore for short-sea vessels with reduced crew, or no crew, onboard. Massterly will also serve conventional (both deep-sea and short-sea) vessels with performance monitoring and land-based assistance to reduce the OPEX for the ship owners and operators; not only on the crewing side but also on fuel and maintenance cost, as well as ensuring higher operational safety and better environmental, contractual and regulatory compliance. Such services include periodically unmanned bridge, condition-based and predictive maintenance, operational support to minimize delays and risks, automated mandatory reporting and crew training.
How do you evaluate the impact of 4th industrial revolution on shipping industry?
The license to operate for the shipping industry is rapidly changing. New demand from regulators, customers and financial institutions are forcing shipping companies to re-shape their operational model and customer journey.
Access to data in real-time and deployment of modern software has never been more important, but we are still faced with the paradox that the connectivity and technology infrastructure onboard ships are archaic and desperately lack standardization.
If we look at the reality in the maritime industry is the 4th industrial revolution in scale still yet far away from a near time reality. The technology infrastructure onboard the majority of ships is still mainly a client-server architecture with silo oriented on-prem software and systems. Real-time access to data and systems onboard vessels that can be used to improve our processes, systems and customer journey is still very difficult and are holding us back. The paradox we are faced with is that open and scalable access to OT data (data from the operational systems) is difficult due to high fragmentation, proprietary systems and lack of standardization.
The timing and readiness to start leveraging cloud-based data platforms have never been better. The market is mature and attractive from an ROI perspective. The data platform players are extremely developer-friendly and we see exponential growth in new capabilities around analytics, ML, AI and low-code frameworks. This gives us amazing opportunities to leverage data to innovate and our customer journey and automate inefficient processes.
The big question we are faced with today is how we are going to enable to run modern software in a containerized environment on the Edge as we do on the Cloud today. We need a new Edge infrastructure onboard the vessels that can collect, compute and analyze data closer to where the data it is created. For this new infrastructure to be successful is it required to be open and not force customers to put all their data in one cloud data platform, but support a hybrid data platform strategy.
The success of cloud and data platforms has been dependant on a well functioning open-source eco-system. The same need to happen if the Edge infrastructure and eco-system is going to flourish. What made cloud disrupt on-prem data centres was not the technology alone, but the business model and openness to the developer community. It offered small development teams to build enterprise-grade solutions that could compete with larger teams and global companies without huge Capex investments.
My prediction is that we will look back at 2020 was an important milestone when shipping companies started to utilize cloud data platforms in scale and that an Edge infrastructure became an enabler for this transformation.
3. Would you please explain about your cooperation with TTI and Semtech on IoT network?
Wilhelmsen aim to bridge land and sea by building end-to-end secured LoRaWAN 2,4GHz.
Instrumental in the set-up of this new IoT system, is developing the digital infrastructure for the future of autonomous shipping. Enabling us to better monitor and optimize operations and deliver genuine environmental benefits to the industry.
Evaluating existing wireless solutions, nothing can match the openness, robustness and low-cost the LoRaWAN delivers. The LoRa ecosystem combines the needs of land and sea into one trusted, global and customizable IoT service”
Traditionally, sensor data is carried through wired systems, or managed via periodic manual readings. However, with LoRa now established as the leading IoT network technology, it is possible to complement these systems with numerous easy to install, connected low-cost sensor solutions.
Wilhelmsen has selected Semtech’s popular LoRa (long range) open source, wireless radio platform as the foundation for its new maritime IoT network. Part of the Wilhelmsen’s ongoing portfolio-wide digitalization strategy, the company, in partnership with technology provider The Things Industries (TTI), will utilize LoRa to deliver a cost-effective, robust and proven IoT solution, available to its diverse customer base worldwide.
4. What is the role of advance-analytics, Machine-Learning/Artificial Intelligence on the future of shipping industry?
The maritime industry has a huge potential of utilizing ML/AI to get rid of unnecessary waste and inefficiency. My prediction is that we do not see use cases were ML/AI will significantly change operation models until we have solved standardization, compatibility and digital infrastructure that can run ML models on the Edge. Condition-based maintenance will probably be the first type of use cases where we will see ML provide value and efficiency gains.