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.

About the Problem Statement:

One of the future growth pillars for Mitsubishi Chemical Holdings Corporation’s (MCHC) healthcare business is to provide ‘around the pill solutions’ enabled by digital technology, intended to improve the quality of life of patients and their families, in their core therapeutics areas. Therapeutics areas of interest include the central nervous system (especially neuromuscular disease), autoimmune diseases and metabolic diseases.

Objectives:

To establish multiple touchpoints with patients during the patient journey from prevention to prognosis, to collect and analyse healthcare data and expand the value of current treatments.

Examples of such solutions could be digital platforms enabling patient-centric disease management, electronic patient-reported outcomes, digital diagnostics, disease tracking, digital medication management, digital biomarker, etc.

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.

Objectives:

• The purpose of i4.0 implementation is to increase productivity or promote process transparency.
• To convince and attract the decision-makers / top management.
• Provide a cost-benefit analysis in this i4.0 transformation process to address and educate the benefits of i4.0 implementation and that it should be of high priority.
• Lower the cost of implementing new technologies.

Desired Outcomes:

• The reasons for the reluctance to bring operations to the Internet/Cloud are often security and cost.
• There is currently no one-size-fits-all solution that can be easily applied to companies for a large scale internal review to produce the cost-benefit report for consideration to move operations to the Internet/Cloud.
• There is also no ability to effectively visualise these benefits and present data coherently to address cost and security concerns. 

Current Limitations:

• i4.0 implementation can consist of various technologies/services, which can be costly overall.
• Despite the time and effort spent, the solution proposed may not yield positive results or be up to the business owner’s expectations.
• No ability to effectively visualise benefits – business owners cannot gauge the results / ROI.
• Difficult for a large-scale internal review to produce a cost-benefit report.

Objectives:

• To help establish fully interconnected and digitised smart factories
• Data to be extracted from legacy machining data/throughput
• Data within legacy machines/systems can integrate with external condition monitoring systems into one complete dashboard

Desired Outcomes:

• Key users are management and shop-floor personnel.
• One current method to obtain data from legacy machines is to introduce sensors in a non-invasive way to extract data for visualisation and analysis.
• However, there are still crucial data of these legacy machines or data from their Manufacturing Execution system that are still not retrievable.
• The limitation to the add-on sensors is that they cannot generate data to the needs of business owners fully.

Current Limitations:

• Costly and unjustifiable to replace existing legacy machines/systems (e.g. CNC/laser cutting).
• Lack of standard IoT communication protocols like MQTT and OPC UA.
• External sensors can only fulfil a partial wish list of business owners – mainly on reducing downtime and saving wastage costs.
• Crucial data like cutting speed, machine uptime, and throughput are also needed for OEE.

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

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

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

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

As part of the Capitaland Master Sustainability Plan, Ascott is committed to reducing waste over the next few years. There is an increasing need for the group to find solutions that can address the needs of the properties that Ascott operates globally. The properties range from Serviced Residences, Rental Housing, Hotels, Senior Living Estates and Student Accommodations.

Objectives:

Because each Ascott property is on average 200 rooms, and does not operate F&B, the scale of the property does not justify the purchase of expensive equipment that costs tens of thousands of dollars.

The Ascott is looking for a solution that will help Ascott-operated properties with at least two out of four of the following:

• Waste Measurement
• Waste Tracking
• Recycling
• Waste Reduction

Working Model:

The solution should be lightweight and if possible, offered on the as-a-service model.