Seeking novel proposals to automate and improve the productivity of the maintenance and repair damage assessment and repair verification process

Posted by InnogetVery responsive · Specific Technical Innovation · Project Size Range : Strategic project backed by large scale funding € · Deadline at 24/10/2020 · European Union

Desired outcome

We are seeking a solution that automates and improves the productivity of the maintenance and repair damage assessment and repair verification process. The proposed solution should provide the following features:

• Automated recognition, labelling of survey results (images, reports etc.)
• Automated classification of damage
• Automated recommendation for type of repair
• Automated smart suggestion regarding repair location
• Automated smart decision on optimized repositioning of repaired equipment
• Note that the images of existing damage components of the containers will be available to the solution provider for training.


• Ship owner
• Depots
• Damage surveyor
• Equipment Owner
• Repair company/depot



PIL Maintenance and Repair (MNR) department is responsible for the maintenance and repair of containers.

This includes vetting all repair recommendations submitted to PIL.

These repair recommendations are done by third party quantity surveyors who inspect PIL’s containers upon their arrival at any port.

If the surveyor discovers any damage that he deems as requiring a repair, he submits a repair recommendation to PIL with below

  • Container number
  • List of damaged components
  • List of recommend repair actions
  • Images taken of the container


Problem #1

Using the images uploaded for each recommendation, a PIL staff has to verify that:

  • The container number tallies
  • Each damaged component listed can be found in the images
  • The recommended repair for each damaged component is reasonable given the extent of the damage detailed by the images

The images uploaded are not labelled to suggest which damage component it captures, and the PIL staff has to manually comb through all the images submitted for each repair recommendations to manually verify all the above pointers.

Problem #2

The next step in the container repair process after the container has been verified to require the specific repair job is to decide whether to repair the container locally or to reposition it overseas for a cheaper or higher quality repair.

The factors affecting the decision include:

  • Type of the container needing repair
  • Shipping schedule
  • Availability of the type of repair and the difference in cost of repair in the different ports.
  • Agreement rates of terminal cost of the port.

The team either sacrifices a huge amount of time to read through the details of the tariffs or to decide based on past experiences, which may not always provide the best course of action for the particular repair case.

Pain Points

  • A lot of manual and redundant work involved
  • Repetitive and unproductive work done by MNR staff
  • Lack of a streamlined process
  • Dependency on personnel due to the required experience in the verification process

Trade and Connectivity Challenge 2020

The present Innovation Call is part of theTrade and Connectivity Challenge 2020 co-organised by Enterprise Singapore along with IPI Singapore.

Singapore’s position as a strategic trade hub is backed by its strong regional networks and connectivity. In recent years, Singapore has also transformed into a hub for innovation activity.

The Trade and Connectivity Challenge (TCC) leverages Singapore’s vibrant ecosystem of global trade, connectivity and innovation as a call for solutions to drive partnerships in the aviation, maritime, land mobility, logistics, and trade sectors. Now, in its second year, TCC 2020 continues to provide opportunities for startups and SMEs to co-innovate, deploy, and adopt innovative solutions.

Enterprise Singapore, together with IPI, invites you to showcase your innovative solutions in growth areas, such as big data analysis, Internet of Things and sustainability post-COVID19.

Related keywords

  • Electronics, IT and Telecomms
  • Automation, Robotics Control Systems
  • Information Processing, Information System, Workflow Management
  • Artificial Intelligence (AI)
  • Internet of Things
  • Applications for Transport and Logistics
  • Process control and logistics
  • Process automation
  • Logistics
  • Artificial intelligence applications for cars and transport
  • Sensors & Wireless products
  • Data Communications
  • Big data management
  • Artificial intelligence related software
  • Industrial Automation
  • Other industrial automation
  • container

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