Digital Manufacturing Processes & Design

Background / Motivation

Digital Manufacturing refers to the extensive application of inter-connected computer-controlled systems throughout the manufacturing process. It is the ultimate result of the “Digitalisation” of the manufacturing process, where design and manufacturing are integrated by digital tools. Highly automated, computer-controlled machines are used, such as CNC Machining centres or Additive Manufacturing “3D Printers”, which connect to the digital design and manufacturing scheduling systems.


IHPC’s digital manufacturing process and design efforts include: 

  • Manufacturing Process Simulation, is a branch of Computer-Aided Engineering applied to the numerical simulation of a wide variety of manufacturing processes. IHPC has modelled processes ranging from bulk material forming, moulding, fluid flow and mixing, to product assembly and filling of liquid products. When used at the design stage, such simulations function as virtual testing, allowing manufacturers to optimise the product design as well as look for improvements in the manufacturing process. 
  • Identify the cause of manufacturing issues as and when they occur. Coupled with Digital Twins, which are unique digital replicas of highly sensorised physical systems, these simulations can be used in a predictive manner, to identify issues early. 
  • Develop Artificial Intelligence systems that use data from sensors to provide predictive capabilities. For infrequent events, where there is a lack of data, these can be enhanced with more detailed physics-based models, including manufacturing process simulations, that can determine the outcome from an event, e.g., damage caused by an overload.  

Working with other A*STAR’s Research Institutes (RIs) such as the Singapore Institute of Manufacturing Technology (SIMTech) and Advanced Remanufacturing and Technology Centre (ARTC), IHPC seeks to develop complete Digital Manufacturing solutions that provides competitive advantage and enable new production technology to end users.


Manufacturing Process Simulation of Laser Powder Bed Fusion Additive Manufacturing

The flexibility of Additive Manufacturing opens up new opportunities for creating more efficient designs with short production runs. However, trial and error is often required before the parts can be printed successfully, which limits wider adoption of Additive Manufacturing. IHPC has developed a fully in-house software platform for simulating Laser Powder Bed Fusion (LPBF), one of the most popular metal Additive Manufacturing processes. In LPBF, parts are built up layer by layer using a laser that scans across the surface of the powder bed with sufficient spot energy to melt the metal powder under its path. Once each layer has been scanned, a new layer of powder is added and the process repeats until the part is completed. 

IHPC’s Additive Manufacturing “Digital Twin” uses advanced physics models that accurately simulate this process for a variety of printers, materials and printing conditions. The detailed predictions obtained reduce the chance of unexpected printing problems. For instance, the powder scale module of the AM Digital Twin predicts the melting and re-solidification of the individual metal particles in the powder and can predict the mechanical properties and potential defects. Fig 1 shows a simulation of a small region of powder being melted on the powder bed and indicates the location of this on the actual powder bed.

AM Digital Twin models
Fig 1. IHPC's Additive Manufacturing "Digital Twin" simulates melting and solidification of the metal powder 

Engineering Simulation of Manufacturing Machinery (the Predictive Digital Twin)

The use of a Digital Twins provides a virtual replica of each physical system and the opportunity to fully understand the operation of the plant. IHPC has explored the use of enhancing Digital Twins with its physics-based models so that actual operational data can be used for predictive analysis.

For example, the robot arm shown in Fig 2 illustrates how a stress analysis can be performed using the actual loads and position recorded on the robot as it moves and performs different tasks. The load cycles for this specific machine may differ significantly from those it was designed for, but because this information is captured in its digital twin, it can be used by other models to anticipate servicing needs or detect a potentially hazardous situation.

Engineering Integration with Digital Twin (A)

Engineering Integration with Digital Twin (B)

Fig 2. The integration of an engineering simulation with the Digital Twin

Collaboration Opportunities 

There is rapid development in the field of Digital Manufacturing with many organisations striving to implement Industry 4.0. IHPC offers broad technical expertise in computational applications and supports companies looking to improve their manufacturing and operational processes. IHPC collaborates with industrial partners to develop advanced simulation, modelling and AI applications as a key enabler in their digitalisation strategy. Opportunities include the development of Manufacturing Process Simulations and integration with Digital Twins that allow manufacturing systems to develop predictive capabilities.

IHPC is also interested to collaborate in developments of AI, where there are emerging techniques to perform automatic defect detection, or predictive maintenance using sensors coupled to AI and machine learning techniques. We are also working with partners on use of AI to make machines smarter, so that they can learn from and with human operators and work better together.

For more info or collaboration opportunities, please write to