The Modern Engineer's Guide to Process Automation: Breaking Free from Manual Tasks
In the modern world of engineering, efficiency is key. Yet many engineering teams still struggle with manual tasks that reduce productivity and hinder innovation. According to a study by Siemens and Tech-Clarity, engineering teams are losing a substantial amount of time in their day-to-day work. Another study, this time by Colab, found that engineers spend an alarming 23% of their time on non-value-added work. This not only impacts product quality, but also hampers market competitiveness. Given talent shortages and accelerated project timelines, automation is no longer just a luxury; it's a strategic necessity.
Challenges of Manual Processes
One of the biggest obstacles engineering teams face is the prevalence of manual and repetitive work. Tasks like adjusting CAD geometries or setting up analyses often consume valuable time. Tech-Clarity's research highlights that both small and large companies face similar challenges in managing repetitive tasks, while larger businesses are particularly hindered by collaboration and communication issues.
Poor collaboration also emerges as a significant challenge. Miscommunications between departments, such as delays in sharing FE analysis results or design updates, can lead to frustration and blame culture. Furthermore, interruptions from meetings or phone calls break the flow of focused work, compounding productivity losses.
The Role of Automation
To break free from these productivity barriers, engineering teams must embrace process automation. For instance, automating the process of applying fillets in CAD models can save hundreds of hours, as demonstrated by an engineering customer who drastically cut down manual operations with Synera’s visual programming tools. Not only does this reduce labor, but it also enhances consistency and accuracy in repetitive tasks.
Automation tools vary in complexity, from programming-based solutions like Python and MATLAB to low-code platforms like Synera, Grasshopper, and CATIA Visual Script Designer. While scripting languages offer flexibility, they require significant coding skills. On the other hand, visual programming environments provide intuitive interfaces suitable for engineers without a software background.
Developing an Automation Mindset
Successful automation implementation requires an algorithmic mindset - a shift from manual execution to process-oriented thinking. Engineers who are likely to thrive in automation initiatives often exhibit traits such as curiosity, the ability to recognise patterns, and a focus on parameter-driven outcomes. Encouraging this mindset within the team requires training, incentives and time for experimentation.
Organisations should identify potential automation champions - engineers who naturally think in terms of algorithms and process efficiency. By nurturing these abilities and allocating time for hackathons or learning sessions, companies can cultivate a culture of continuous improvement.
Tools and Approaches
Selecting the right tool is crucial for successful automation. Synera, for instance, offers a robust visual programming interface that integrates seamlessly with major CAD/CAE/PLM systems. Other tools like Python, TCL, and Grasshopper also provide valuable capabilities but may require more coding expertise or be limited to specific platforms.
Engineers should balance ease of use with technical requirements, ensuring that the chosen tool aligns with their project’s complexity and scope. Additionally, modular automation, which allows parameter adjustments without rebuilding the entire workflow, helps maintain flexibility without sacrificing reliability.
Case Studies and Examples
An excellent starting point for automation is to target repetitive, time-consuming tasks. One Synera customer automated CAD geometry orientation, achieving a 90% time reduction while maintaining 97% accuracy. Such quick wins demonstrate the value of automation and encourage wider adoption.
However, it’s essential to balance flexibility and robustness. While specific automations for stable, repetitive tasks can be highly efficient, more dynamic tasks may require adaptable solutions. By creating modular automations, engineers can fine-tune parameters without overhauling the entire setup.
Conclusion
Automation in engineering is not just about saving time; it's also about unleashing creative potential. By automating routine tasks, engineers can dedicate more time to innovative solutions and complex problem-solving. In today's competitive business landscape, integrating automation into everyday processes is essential. The question is no longer whether to automate, but how to begin and which processes to prioritise. Embracing an algorithmic mindset, selecting the appropriate tools and cultivating a culture of experimentation will enable engineering teams to overcome the challenges of modern product development in a more efficient and innovative manner.
