Innovation Challenges

Challenge Owner(s) JTC Corporation
Organiser(s) JTC Corporation
Industry Type(s)
Digital/ICT, Infrastructure, Sustainable Energy, Urban Solutions
Opportunities and Support Funding of up to $250,000 for project duration of up to 12 months. Potential trial, testbed and pilot opportunities.
Application Start Date 27 May 2022
Application End Date 8 July 2022
Website Click here to learn more

About Challenge

JTC has committed $4 million for the JTC Innovation Challenge to seek innovative solutions to operational challenges in the built environment faced by JTC and the public sector. If successfully developed, there is intention to pilot/deploy these co-developed solutions into JTC estates and projects, pushing for adoption into the industry. 

The JTC Innovation Challenge hopes to quickly launch small-scale projects and demonstrate the solutions to stakeholders for their buy-in. Proposed solutions should not involve too upstream research, and should ideally be deployed within 3 years.

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Challenge Owner(s)JTC Corporation
Industry Types(s)
Digital/ICT, Electronics, Infrastructure

JTC Corporation

Building Information Models (BIM), particularly that of the Mechanical, Electrical and Plumbing (MEP) components, has many use cases. However, BIM of completed buildings, also known as the as-built BIM, are often not available or inaccurate.

While it is possible to build BIM retroactively, it is very challenging and labourious. The staff need to measure and determine the properties of everything in the building/infrastructure, then manually build the BIM and update the information.

Challenges

Archival drawings of existing buildings can provide important information, but they could be missing or damaged or outdated. LiDar scans can provide as-built point cloud data, but the conversion to distinct BIM elements remains difficult.

What We Are Looking For

The challenge is to deliver a solution/product/platform that can make use of data from reality captures to automatically produce as-built BIM of existing assets’ selected objects that satisfy JTC Model Content Requirement’s (MCR) as-built stage geometrical requirement.

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Challenge Owner(s)JTC Corporation
Industry Types(s)
Electronics, Energy & Chemicals, Sustainable Energy

JTC Corporation

Chiller plant systems use 30% to 60% of a building’s total energy consumption, hence it’s important to ensure that chiller plants are designed optimally. 

Engineering teams design chiller plant systems based on a cooling load profile, that is affected by occupancy and the activity profile of the building. The chiller plant system will iterate with different combinations of chillers and their accompanying components due to different chiller cooling capacity, brands and staging configuration to obtain the most energy efficient chiller plant system. 
 
The chiller plant system efficiency varies based on many factors. See Annex A (through this link) for a typical workflow of the design process, as well as a list of variables which may affect the chiller plant system efficiency.

Challenges
 

Typically, the iterative selection process is done on Excel. However, due to the large number of variables affecting chiller plant performance, there is a limitation on the number of chiller configurations (~3 to 5) considered during design stage. This results in sub-optimal chiller plant equipment selection.

Many of the variables affecting chiller plant efficiency are chiller dependent. Correspondingly, chillers are the largest determinant of chiller plant system performance: 

Chiller size and brand:

  • The first iteration is often based on the designer’s experience or supplier recommendation. From there, subsequent fine-tuning is carried out. Probable and effective chiller configurations may be missed out.
  • Supplier input is required for each subsequent design iteration, which is a time-consuming process as well.

Chiller staging:

  • This is often done manually for each chiller configuration, and the process is repeated for different chiller brands. This process is time consuming, and often subject to human error, such as unoptimized chiller staging, mistakes in interpolation, etc.
What We Are Looking For

The envisioned solution’s workflow from a chiller plant designer’s perspective will be:

1. Manpower productivity & carbon savings - based on the solution’s database of existing chiller plant components in the market, to propose energy efficient chiller plant configurations.

2. Manpower productivity - using these proposed chiller plant recommendations to seek technical data sheets from the suppliers.

3. Manpower productivity & carbon savings - based on the suppliers’ response, the user will input data into the software to iterate different proposals for comparison.

The successfully developed solution will significantly improve manpower productivity for JTC’s chiller plant designers and reduce the operating carbon footprint of JTC’s industrial estates.

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Challenge Owner(s)JTC Corporation
Industry Types(s)
Digital/ICT, Electronics, Energy & Chemicals

JTC Corporation

Air conditioning (AC) systems, consume a large share of the total energy used in buildings. Maintaining optimal operational efficiency in air conditioning systems is a constant challenge - one that all air conditioning and mechanical ventilation engineers work tirelessly to overcome.

JTC is seeking innovative solutions to enable real time automated optimisation of AC systems (include both chilled water and air-side systems), to achieve both operational productivity and energy efficiency while maintaining critical operations and satisfactory occupants’ thermal comfort.

Challenges

Some of the solutions available mainly focus on optimising either chilled water or air-side systems. There is a lack of solutions that provide real time automated optimisation covering both the water and air-side systems, as well as taking occupants’ comfort into consideration.

What We Are Looking For

The envisioned solution shall optimise

  1. Facility management operational productivity with regards to AC system (include both water and air-side systems).
  2. AC system efficiency (include both water and air-side systems) for continuous optimization in one of JTC’s buildings with existing BMS system to meet the following key performance indicators:
    1. Improve facility management efficiency e.g. improve FM productivity, focus on critical operating parameters.
    2. Safety & continuity of essential operations e.g. prevent unnecessary potential failures.
    3. Ensure occupants’ comfort to produce equipment analysis for quicker troubleshooting to any operations issues on the ground e.g. Reduces turnaround time.
    4. Realtime optimisation to offer fine-tuning to a higher resolution - down to hourly or even less to achieve optimal operation efficiency.

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Challenge Owner(s)JTC Corporation
Industry Types(s)
Digital/ICT, Infrastructure, Urban Solutions

JTC Corporation

2 types of defects detections are usually carried out. (a) During construction for the purpose of construction quality control and (b) During building operations where Periodic Building Inspection (PBI) is carried out by JTC yearly and Periodic Structural Inspection (PSI) is carried out by third party Professional Engineers (PE) every 5 years.

Defects inspection, together with their documentation, analysis and reporting are very manual, unproductive, and time-consuming process. It is also highly dependent on the inspector’s skill, experience, and alertness. Defects inspection when carried out poorly with missed defects, misinterpretations and poor accuracy not only led to unreliable findings that requires reworks but may also be a potential risk to the construction teams and building occupants.

Challenges

What if we can develop a solution that can digitalise and automate defects inspection process during construction and periodic building/structural inspections in the following ways to improve detection accuracy, productivity and save costs?

1. Auto-tag key information (metadata) to photos captured on site
    E.g. Project Info, time-stamped, location stamped (BIM & site map) and etc.

2. Identify, match (from database) and classify the defects & non-conformance (NC) from the captured photos automatically.

3. Generate useful information from data to help project and system level planning and decision making.
    E.g. Defects and NC overviews by classification for follow up actions

   a. Diagnosis/assessment of defects (applicable to structural defects during building operation only)

   b. Building Structural inspection/health Reports

   c. Recommendation for immediate and future actions/rectifications

   d. Track and close rectification works

What We Are Looking For

  1. Achieve defects and NC detection/ identification/ severity assessment of defects >80% accuracy
  2. Improve overall productivity in construction quality control and/or PBI/PSI inspection >50% 
  3. Auto-generate structural defects and NC reports to JTC’s requirement
  4. Perform diagnosis/severity assessment of each structural defects detected (applicable to building operation).
  5. Identify the building’s overall structural condition at operation stage.
  6. Provide Big Data analytics & insights from cross-inspection database

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