Supercharging additive manufacturing with software


By Doug Kenik, director of software manufacturing, Markforged.

As the additive manufacturing industry matures, the pace of software innovation has sped up to a sprint. It is effectively ‘catching up’ to the pace set by new development in hardware and materials as the industry moves towards industrial production.

Software success is centred around ensuring zero downtime, streamlined workflows and making machines smarter, underpinned by continued innovation. I’d argue that the adoption of additive manufacturing (AM) will be driven by real advancements in both software and data as it continues to move into industrial applications, and the overall movement towards ‘smart factories’.

Customising workflows and building confidence

Saving costs and reducing risk have become critical concerns for manufacturers in today’s climate. This applies to the processes they use right through to their storage capacity. Digital inventories and locally distributed manufacturing play an essential role in helping keep costs and risks under control.

In addition, those in head office through to employees on the factory floor need customisable workflows and manufacturing methods that will fit easily into their current methods of operation.  

Superior software with data at its heart (together with hardware and materials), not only aids in addressing these requirements, but also helps suppliers to build reputations of reliability - creating customer confidence and success. Software like Markforged’s Simulation, provides engineers with the detail, information and – most importantly – confidence they need to design the parts to meet these requirements. It also saves time and smooths workflows by eliminating the need for multiple iterations of trial and error.

Creating collaborative ecosystems

AM is solving problems through collaborative ecosystems, which are – in effect – customisable workflows. And these, in turn, give manufacturers the ability to scale using digital inventory. 

Digital inventories allow parts to be accessed anywhere in the world, through printing at the point of need. Software features like SAML SSO, Role Based Access Control (RBAC) and part validation workflows provide the necessary security measures to limit visibility and access while ensuring a single source of truth.

AM should enable users to scale as they adopt it more deeply into their current offerings. As customers require more machines, add more users and print more parts, the process should grow with them, helping to unlock new and required workflows. Forming customer partnerships and creating ecosystems through hardware, software and materials, with data sitting at the centre, enables customers to realise success – reinforcing their confidence.

Realising ROI

Software has traditionally been a ‘necessary evil’ to help people print parts - it was more of a fast-follower. As such, customers’ expectations were that software should be free, but they are now becoming more amenable to spending on it. This is due to the fact that software functionality is increasing and additive is becoming a more accepted production manufacturing method. , and software is now maturing through innovation and unlocking new opportunities for customers, as well as exposing new ways to increase efficiencies. 

OEMs have a responsibility to help customers realise ROI on the full additive manufacturing ecosystem. It is their responsibility to educate the user base on where and how additive can be applied from an ROI perspective. This can include light-weighting, part consolidation, reduced downtime through digital inventories or on-demand MRO systems.

The future is data

The power of the connected fleet relies on data. This will continue to be the most critical factor for the entire manufacturing industry – to mitigate risk and ensure that software and data underpin customers’ success strategies.

OEMs should be asking: ‘how do we use data for customer success?’. Answers to this include collecting data from a connected manufacturing infrastructure, and using this information to identify and troubleshoot existing and potential problems. For example, data can identify inspection or security problems, allowing them to be fixed quickly to avoid further issues. 

Access to data means problems can be solved in a fraction of the time using proactive support. 

Updates can be deployed at the point of need and connected machines can become smarter as new information becomes available, ensuring the manufacturing fleet improves with age. 

The ultimate success of AM will depend on scalable ecosystems. Data powers the connected fleet, and the success and growth of additive manufacturing will be won via scalable ecosystems.

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