Engine and Equipment Performance Analytics

Task leader: University of Southern Denmark

Task number: 1.3

Improved performance and uptime for engines and connected equipment as well as cost-efficient maintenance and spare parts planning through advanced analytics and condition based / preventive maintenance

‘Engine and Equipment Performance Analytics’ has the following aim and objectives:

  1. To improve engine uptime and performance
  2. To optimize maintenance and spare parts planning and in turn efficiency of shipping operations
  3. Using ship data about engine conditions, ship operating conditions, maintenance plans and events, breakdown history etc. deploy analytical models for performance monitoring, fault detection, condition based and predictive maintenance.
  4. To validate the business and monetary benefits of tested solutions and evaluate implications for potential gain sharing contracts between equipment suppliers, vessel operators and owners
  5. Finally through project execution and dissemination of results, position Danish shipping industry as the fore-runner in use of digital technologies for planned maintenance and spare parts planning

Ship operators’ efficiency suffers because of sub-optimal performance of machinery and equipment and increased costs of maintenance. Currently, ship operators do not have access to models, which can predict deterioration of performance or failure of parts in equipment and thereby support better maintenance planning for ship operators / owners and help equipment manufacturers in spare parts planning. Equipment manufacturers also have limited visibility of on-board vessel conditions, the maintenance schedules on the ships, breakdown history etc which limit their ability to improve prediction, reliability and performance of their equipments, while minimizing the costs of ensuring uptime of equipment through maintenance and spare parts planning.

Improved and more reliable shipping operations through optimal performance and minimal stoppages of equipments, resulting in cost avoidance of costly maintenance activities, reduced energy costs. For example for Lauritzen, the annual maintenance and damage costs for MAN ME engines is estimated at 62,524 USD per vessel per year. Similar figures for Torm will be around 50,000 USD per year. A 5% savings of this cost will result in direct savings of 3124 USD per vessel per year for Lauritzen and 2500 USD per vessel per year for TORM.  In addition on an average an engine will be under breakdown for 10 hours in a year resulting in a potential loss of 7500 USD per year. The project will help in avoiding these breakdown costs. Improving prediction of failure of parts will help MAN plan production of spare parts better, which will directly impact the order intake and thus EBIT. The proposed project will also result in inventory cost reduction for MAN PrimeServ. Currently more than 23% of the total inventory value has not moved for last 6 months, which will be reduced.

Task partners

University of Southern Denmark

BW Epic Kosan

RINA Digital Solutions

MAN Energy Solutions

Maersk Tankers