E-CERTIFICATES SMARTER OPERATIONS 17
Simply efficient “Smart survey booking is a major move in streamlin- ing a previously tedious and often inefficient manual task,” says Østby. The smart survey booking solution automatically finds the best window for a ship’s an- nual survey, allowing for as many requirements and requests as possible to be covered in one survey to avoid multiple inspections.
“Based on this time window and a list of possible
ports entered by the operator, the system also looks for the closest geographical location, accounting for the scope and duration of the survey, port capabili- ties and surveyor availability, and issues a recom- mendation. This minimizes both the time involved in booking the survey and the inconvenience for the vessel while keeping the costs down by helping reduce surveyor travel times,” Østby says. An automated version of the application is
expected to be available before 2019. “The software will enable us to track ship itineraries and notify them in advance so they can order earlier, which leaves them with a larger time window for planning and owner preparation,” Østby points out. A link to all DNV GL-approved service suppliers in the respective port will soon be added, along with a host of ad- ditional features designed to improve efficiency and keep the survey costs down.
Learning application Many improvements are made possible by introduc- ing machine learning, or ML, into the survey booking process. “ML is used to calculate the time required for each survey,” says Østby. “When the scope and other parameters are set, the system outputs a time estimate based on historical data.” DNV GL has also incorporated ML into its
DATE (Direct Access to Technical Experts) service where a customer’s problem description transmit- ted by e-mail can make it challenging to assign the case to the correct category and expert or section for fast processing. “A discrepancy between the de- scription and interpretation may cause the inquiry to be routed to the wrong expert,” says Sethumad- havan. “Now DATE uses ML to vet cases based on historical data and quickly directs them to the proper expert. This cuts down on manual vetting and reduces time wasted on re-routing and finding another expert. We are already seeing that ML- assisted vetting is more than 80 per cent accurate, and it gets better every day.” Each ML-vetted routing receives a confidence
rating before being enacted. Any inquiry that has not received a very high confidence rating is returned for manual vetting. “ML is chosen for cat- egory assignment only when the confidence level is
REMOTE INSPECTION: EYES ANYWHERE
Ship inspection often poses a conundrum: The object may be a fairly straightforward structure or piece of equipment on board, but human eyes are still required to verify its state. Tradition- ally that means the human doing the looking has to be on board. But that is not necessarily true anymore.
Remote technology is enabling eyes to see the object of inspection from virtually anywhere in the world. Equipped with something as simple as a smartphone app, personnel on board can connect to the surveyor on land, and the survey is underway. “The expert steers the input and evaluates the quality of the data,” says DNV GL‘s Senior Principal Consultant Morten Østby. In other words, the “cameraman” on board takes instruc- tions from the surveyor on land who acts as the “director”. One key prerequisite: the surveyor must have actual on-board experience. “You have to have been there to be able to know what you are seeing,” Østby confirms.
“But the customer must be willing to cooper-
ate,” he adds. “Proof of repair or remediation must be provided.” For the time being the technology will be used on occasional surveys, not for certifi- cation, and possibly for selected follow-up items when the surveyor has left the ship. Remote inspection could also be used for
certification of materials and components. “The first steps have been taken. Many more will fol- low,” Østby assures.
From his land-based computer the surveyor can instruct the personnel on board during a video survey.
very high,” explains Sethumadhavan. “But by using continuous learning logic, the ML system is con- stantly refining its selection criteria and improving its hit rates quickly.” But there are other human factors that complicate the advisory process. “While we all use English only, there are different language patterns and rules in dif- ferent parts of the world,” Østby says. “We have had to teach the machines to accept compound words and different spellings. We can even teach them to vet incorrect language.”
02/2017 MARITIME IMPACT The Report • March 2018 • Issue 83 | 55
Photos: ©Africa Studio –
stock.adobe.com, DNV GL
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