Connected, Intelligent & Automated Workflows for (Additive) Manufacturing

Manufacturing Execution System – or MES – can come across as a rather generic term, but understanding the real meaning and implementing it in a factory is about as important as it gets for any manufacturing operation, wherever they are located and however big or small. Workflow is another generic, underrated term that often gets overlooked.

And let’s face it, MES and workflow certainly do not sound as exciting as the current buzzwords being used to engage the global manufacturing community. “Industry 4.0” and/or the “4th Industrial Revolution” are certainly more catchy terms and they need to be, because the definitions are, let’s say, unwieldy. Moreover, the prerequisite technological innovations that are driving towards the fulfilment of Industry 4.0 continue to develop at pace. These innovations also come with what can seem like buzzword labels due to their over- and often mis-use. Continuous development with Artificial Intelligence (AI), Industrial IoT (IIoT), additive manufacturing (AM) and cloud-based services and software are all enabling the vision of Industry 4.0 to edge closer to reality. We’re still not there though.

At Oqton, what we have discovered over the last couple of years is that one of the biggest problems that manufacturers face is the overwhelming nature and speed of technological developments. This coupled with equally overwhelming volumes of information telling them what they need to do to keep up can often have the opposite effect and result in a state of stasis: a sort of “if it’s not broken, don’t fix it” attitude.

This is understandable for a number of reasons, not least the fact that manufacturing technology selection — whether hardware, software and data services (for collection, storage, analysis) — is daunting, often expensive and requires new skills/expertise.

Another challenge for manufacturers is the fragmented nature of these technological developments — a decision to invest in AM for a specific production application, for example, can derive significant benefits in terms of producing complex geometries that cannot be made any other way, increased product functionality and value, materials, customization and production lead times (compared with tooling for injection moulding). These benefits of AM, for a growing number of applications, are today undeniable. However, implementing any given AM system hardware and software into an existing manufacturing operation is far from simple and the often-overlooked reality is that AM will rarely be used as a singular production method, rather it will be used as a manufacturing tool alongside other manufacturing tools. Compatibility with existing manufacturing infrastructure is problematic to say the least, software interoperability is also a huge issue.

Connectivity is the key

Connects all of the factory equipment

Beyond the connectivity, though, the system has intelligence built in that is capable of leveraging the power of AI technology to capture the expert knowledge required to run any manufacturing machines, including AM machines, thereby simplifying, streamlining and automating repetitive tasks and complex workflows. This intelligence extends even further for additive manufacturing specific applications, with data preparation and build support algorithms that can produce the most effective lattice structures based on machine learning capabilities.