Project Brief – How can digital twin technology help a Robotic Production Lab to create and simulate a circular wood factory?
Project type – Digital Transformation
Duration – 5 months
Location – Amsterdam, Netherlands
I was part of a multi-disciplinary team and responsible for innovation research as a design generalist. The project helped me to develop familiarity with lean methods including SCRUM and project managment tools like JIRA. I directed the team with my creative thinking to figure out new innovative ways within manufacturing industry and came up with a flexible factory setup of the future during the initial stage of research. During the final phase of the project I worked on the UI of our concept using Figma and created a working prototype. I also assisted the team with our concept video as an editor and created the final version using video editing tools such as After Effects.
The robot lab is a place where students, researchers and digital production experts investigate new possibilities for the circular economy. They explore how to reuse valuable waste materials from urban and industrial sources, by integrating digital design and robotic production. This system follows a linear information flow, where communication and data sharing play a significant role. Apart from this, the system also needs to be resilient if any unexpected changes occur during prototyping phase of projects. So, as team we set out on a journey to find gaps and opportunity that can be solved by implemented a digital twin for the whole process of collaboration and production. Therefore the major challenges were :
+ Increasing efficiency of information flow between multiple stakeholders and make it accessible in realtime
+ Digital twinning the process to pre-determine and pre-validate the possibilities of production
The concept we proposed can be summarised in three distinct parts.
Part 1 – Waste wood database and inventory expansion | The first part explains how a user can create a database of waste wood for production using the innovative capabilities of emerging tech like LiDar sensors and cloud computing.
Part 2 – Generative design and inventory management | The second part takes into account the persona of a creator who uses parametric design and generative artificial intelligence to generate multiple design solutions using the waste wood inventory accumulated in the first stage. The second part also makes room for resource sourcing by incorporating an interface for suppler selection and communication.
Part 3 – Pre-production scheduling and simulation | The third phase of digital twin gives access to the production lab of a resource allocator where they can schedule and allocate projects to multiple robots, depending on their availability. This phase also amalgamates a simulator, which aids the lab in predicting the health and functioning of the selected manufacturing cell. In case of any setbacks, the digital twin can assist in sourcing and troubleshooting the problems before they even arise.
The following video elaborates further on the final concept proposed by us at the end of our traineeship. The video also gives an insight on how these stakeholders might interact with each other in a real life scenario.