Automated human tasks, and automated product handling with small changeover time.

Objectives:

• Establish integration tools for data extraction, transformation and loading.
• Develop AI data processing platforms.
• Scalable for operations implementation.
• Enable domain experts to perform data analytics independently.

Desired Outcomes:

• Focus on predictive maintenance for automated material handling equipment.
• To package prototypes into a suite of recommended platforms and tools. 
• Develop AI algorithms related to the project scope. 
• AI SMART Discovery: Demonstrate capability for prototype analytics for the layman.

Current Limitations:

• Problem centric data analysis: Engineers must analyse a voluminous amount of data for actionable insights through various data sources (OEE, yield, product data & recipes, machine alarms, etc.).
• High effort, time and subject matter knowledge are required for effective cause and effect analysis.

Alternative transport modes, fuels, packing materials & end-to-end services.

Technology and best practices to turn our middle managers into data citizens.

Perfect low-code platforms to capture more relevant data and improve efficiency.

Objectives:

• Automate tasks assignment and prioritisation based on technical requirements and technicians’ profiles.
• Optimise execution with a grouping of tasks to improve efficiency.
• Predict the demand vs supply and forecast the overtime planning.
• Identify the technical competency gap among technicians.

Desired Outcomes:

• Over 34 technicians with different skillsets for operation and engineering tasks are complex and vary widely, from logistical units collection to equipment setup.
• To have a one-stop solution platform between managers, engineers and technicians.
• Interactive solution on a mobile device for technicians to receive notifications and report efficiently.
• If the execution of tasks can be on auto-pilot mode and optimised continuously driven by data analytics, this would significantly improve work efficiency.

Current Limitations:

• Engineers need to manually book the necessary resources, including equipment and technicians’ availability.
• Independent systems are used to check and book different resources, e.g. equipment booking, technician scheduling, engineering samples, etc.
• Manual and tedious effort on engineers to communicate, cross-check, and set priorities with managers and teammates.

Automatic 3-way invoice match against shipment information & rate cards, for air/ocean freight & customs brokerage/trucking operations.