Martin Gadsby looks at what digital twins are and how process analytical technologies (PAT) can help digitally clone manufacturing processes
The global importance of plastic-based medical and drug delivery devices is increasing the business opportunities for those in the medical plastics market.
The opportunities to improve competitiveness offered by the fourth industrial revolution (Industry 4.0) will help those medical plastic manufacturers that recognise and adopt them.
One of the key emerging Industry 4.0 technologies, the digital twin, has the potential to drive dramatic increases in-process responsiveness, productivity and efficiency.
There are a plethora of definitions and interpretations of what digital twins are. At their simplest, they are virtual replicas of physical entities that can be used to understand or predict real-world outcomes. These can represent single components, machines, end products, systems within a production line or entire manufacturing processes.
Also, they can be static, ie not interact with their real-world counterparts, or dynamic by using sensor-based feedback received from the physical entities to adjust their models accordingly and deliver optimized outputs and forecasts.
Digital twins are suitable for a wide range of applications, such as product lifecycle management (PLM), predictive maintenance of industrial machines, personnel training in virtual environments.
In addition, digital twins can support predictive manufacturing and advanced quality based Multi-Variate Statistical Process Control (MSPC).
In the medical plastic sector, a digital twin for quality based MSPC could mirror blow or injection molding processes, as well as post-production and finishing procedures, to predict how critical process parameters (CPPs), eg melt temperature or injection velocity, would affect real time product quality, durability and reliability.
Twin from another mother
The concept of digital twins, particularly when combined with MSPC, is relatively new, yet a well-constructed system based on Process Analytical Technology (PAT) will leverage both of these concepts, and as a result maximise your process’s quality and performance.
In fact, it provides a framework that is promoted by regulatory bodies, such as the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA), to de facto create cyber-physical systems of entire manufacturing processes.
As a result, businesses that are embarking with PAT can leverage their existing infrastructure together with new PAT technology and techniques to implement digital twins for Industry 4.0 applications.
PAT facilitates the creation of in-depth knowledge of the process in order to deliver accurate actionable insights.
By understanding the correlation between CPPs and product’s critical quality attributes (CQAs) – measured in real time in-line, on-line and /or at-line by suitable analytical instruments, the process can be controlled in real-time based on quality predictions to ensure the end product will fulfil any given specifications.
Manual or automated control is possible, as the process models can either ‘direct’ the operator as to the desired action or act independently.
For example, PAT has the potential for manufacturers of plastic-based medical and drug delivery devices to prevent thermal degradation of the polymers by finely tuning the extruder’s heating profile based on product quality predictions.
The beating heart of a PAT-enabled system is the knowledge management software. This processes and stores data as well as turning it into knowledge to optimise the manufacturing process. It offers manufacturers a platform to control the process based on quality predictions and provides a mechanism for continual improvement where the process gains will further increase over time.
These benefits are enhanced when a digital twin is implemented within the PAT knowledge manager, as it can greatly assist with the development, optimisation and continual improvement process.
One of the most advanced and popular regulatory-compliant PAT knowledge management platforms currently available is Optimal’s synTQ.
The software’s latest ‘test mode’ function is a true process digital twin. It allows authorized users to run either partial or complete PAT Methods (or Orchestrations, as they are called in synTQ), virtually at any point during the process’s lifecycle. Thus this test mode digital twin can be used effectively to create and test the process data flows before the real process is started up, and then used to optimise the process as more data and knowledge is generated and the models are refined.
The net result is that process start-ups are much more straightforward, and that improved models can be tested within the digital twin environment.
Once the optimal virtual orchestrations been created, tested and set, operators can systematically connect these with the physical plant to transmit the optimal operating conditions.
As a result, business can fine-tune their processes whilst incurring substantial savings in terms of cost, time, raw materials and waste.
In addition, synTQ can be used as a tool to realize wider Industry 4.0 principles, to help create an interconnected factory by linking Distributed Control Systems (DCSs) with higher-level Manufacturing Execution Systems (MESs).
By choosing state-of-the-art solutions, such as synTQ, manufacturers of plastic-based medical and drug delivery devices can use reliable systems such as this to future-proof their plants and processes.
Martin Gadsby is Director at Optimal Industrial Technologies.