Recently, emerging technologies are being discussed within the Life Sciences manufacturing space much more as companies are looking for ways to be more competitive and efficient. There are a lot of new software solutions that promise the moon, but which ones are the most promising? Here at Skellig, we’re most excited about MQTT, Inductive Automation’s Ignition, the Tulip Frontline Operations Platform, and Large Language Models (LLMs).
MQTT Communications Protocol
What is it?
MQTT (Message Queuing Telemetry Transport) is a lightweight and efficient messaging protocol designed for low-bandwidth, high-latency networks. This makes it ideal for Internet of Things (IoT) applications that require real-time data exchange. MQTT operates on a publisher-subscriber model, where devices (publisher) send data to a central broker (subscriber). Its simplicity, minimal overhead, and support for intermittent connections make MQTT a go-to solution for connecting and coordinating devices in diverse IoT ecosystems. Whether tracking sensor data or facilitating communication between industrial machines, MQTT serves as a reliable and scalable foundation for streamlined and responsive data exchange in connected environments.
Why does it matter?
MQTT offers a few major benefits over traditional communication protocols in industrial automation, such as OPC-UA. As factories become more connected with sensors everywhere, an organization’s bandwidth usage increases significantly. MQTT’s lightweight nature makes it more suitable for tomorrow’s connected smart factory as it is more efficient than OPC UA at transmitting data. Additionally, MQTT’s ability to handle intermittent connections works well to ensure no data is lost in transmission, a crucial constraint in Life Sciences manufacturing. One downside of MQTT in today’s current manufacturing environment is the lack of adoption, mainly due to the lack of native compatibility. However, Skellig has configured many types of equipment to work with MQTT.
Ignition
What is it?
Inductive Automation’s Ignition is a powerful industrial automation software platform that allows for the creation of flexible and scalable solutions for monitoring, controlling, and visualizing industrial processes. Ignition goes beyond traditional supervisory control and data acquisition (SCADA) systems by offering an open architecture built on Python. This enables seamless integration with various industrial systems using a multitude of communication protocols.
Ignition’s key strength lies in its cross-platform compatibility, allowing users to deploy applications on Windows, Linux, and macOS. Ignition facilitates rapid application development through its web-based, drag-and-drop design environment, allowing engineers to create custom Human-Machine Interface (HMI) and Supervisory Control and Data Acquisition (SCADA) solutions without extensive programming.
With robust features like real-time data visualization, historical data analysis, and mobile accessibility, Ignition serves as a versatile and user-friendly tool for optimizing industrial automation across a wide range of sectors.
Why does it matter?
Ignition’s significance lies in its ability to break down traditional data barriers/silos by offering a flexible, cross-platform solution that adapts to an organization’s specific needs. By providing an open and scalable platform, Ignition allows seamless integration with many different industrial systems which encourages interoperability and future-proof operations.
Best of all, Ignition has real-time data visualization, historical analysis capabilities, and mobile accessibility. These further enhance its relevance by enabling organizations to make informed decisions, optimize processes, and stay competitive in today’s data-driven industry.
Changing the MES Landscape
What is an MES?
A Manufacturing Execution System (MES) is a software system that orchestrates and optimizes production processes. It integrates with various manufacturing systems to facilitate real-time monitoring, tracking, and control of production activities. In the context of Life Sciences manufacturing, an MES ensures compliance with regulatory standards, enhances batch traceability, and provides actionable insights for quality control.
Traditional MES implementations have some issues, however. They are often very rigid in how they operate which can lead to manufacturing operations adjusting processes to work within MES constraints. The rigid nature can also lead to lower adoption rates after implementation. These systems require plant floor personnel and site admins alike to undergo significant training on how the system operates. Finally, these systems are often limited in what other systems they can connect to and are not open platforms. They also have rigid connection requirements.
One new platform that is looking to shake up the landscape and offer improvements over MES offerings is Tulip.
Why does Tulip matter?
Tulip is not an MES but a Frontline Operations Platform. The primary focus of Tulip is guiding operators through manufacturing processes using simple, easy-to-follow work instructions that are visually striking. Tulip is a no-code platform and prides itself on empowering those without strong computer science backgrounds to still be able to create robust manufacturing applications. Finally, Tulip rejects the monolithic approach to MES and encourages app designers to create as many or as few apps as needed to tailor the apps to the exact needs of a manufacturing space.
We’ve talked about Tulip before. Check out our overview here: https://skellig.com/blog-brief-overview-tulip/
Large Language Models (LLMs)
What is it?
What better way to learn what an LLM is than to ask one itself? The following was generated from OpenAI’s ChatGPT 3.5 with the prompt “What is a large language model?”
“A large language model refers to a sophisticated artificial intelligence system designed to understand, generate, and process human-like language patterns on a vast scale. These models are typically built using deep learning techniques, specifically recurrent neural networks (RNNs) or transformer architectures. The “large” designation indicates the extensive size and complexity of the model, often comprising tens or hundreds of billions of parameters.”
To summarize in one sentence, a large language model is an AI system that uses an extensive number of parameters to understand and generate human-like language responses.
Why does it matter?
One of the main use cases we’re excited about is using large language models to analyze large amounts of textual data and make that data available through a chatbot interface. An organization can feed all of its equipment’s technical manuals into an LLM so that engineers and other technical staff can ask the LLM questions rather than digging through endless manuals for information. An engineer can ask the LLM, “What is the tag that controls temperature for Bioreactor A?” and receive a straightforward, accurate answer.
Another use case is aiding in document drafting. LLMs can provide auto-completions and suggestions while typing, analyze the grammar or style of a document and summarize large documents. One example of this is feeding it a written paragraph and asking it to generate the paragraph with consistent tone and tense. Another example is feeding an LLM with the transcript from a meeting or speech and asking it to summarize the key points that were discussed.
Large Language Models are an incredibly new technology and it’s worth keeping tabs on to see how they are used in different applications.
Integrate modern technology into your Life Sciences process
New next-gen and industry 4.0 technologies have the potential to significantly improve Life Sciences manufacturing. Technologies like MQTT, Inductive Automation’s Ignition platform, Next-Generation MES solutions like Tulip and Apprentice, and Large Language Models (LLMs) represent a pivotal moment in enhancing efficiency, connectivity, and decision-making processes. As these technologies continue to mature and become commonplace, so too will their impact on Life Sciences manufacturing. Keep an eye on these advancements as they shape the future trajectory of the industry.
Interested in learning how your organization can benefit from these new technologies? Contact Skellig Automation today at info@skellig.com to get started!
