One of the first articles we published on this blog was “How to Save Time and Money on the Engineering Design Process.” We identified five strategies you can use to stay on schedule and on budget. Here, we build on that foundation with four tools to help you work faster without sacrificing quality.
1. Cloud-based collaborative engineering platform
Creating functional and elegant designs takes time. In an ideal world, all of that time would be spent on the actual design process — researching requirements, brainstorming solutions, testing solutions, and so on.
But, we don’t live in an ideal world. And, too often, the biggest chunks of time are spent on much less exciting tasks, like exporting and importing data, manually checking cross-references, and tracking down the source of a mistake.
A cloud-based collaborative engineering platform brings all of your data and documentation together under a single umbrella accessible by all of the stakeholders on your project. This saves you time by providing a centralized location for all project data, eliminating inconsistencies and mistakes, and freeing up your engineers for higher-value work.
2. Schedule performance index (SPI)
The schedule performance index (SPI) is a tool commonly used by project managers to identify small problems before they become big ones. It measures how far ahead or behind a project is compared to the schedule. For a detailed explanation of how SPI is calculated, see this article on ProcessEngineer.net.
For a paper presented in 2013, J.A. Villanueva and J.V. Kovach found that the SPI was an effective tool for engineers in the oil and gas industry. Between 20% and 30% of overall project costs for EPC firms are spent on the engineering/design of instrumentation and controls (I&C). The researchers found that the SPI helps firms “measure project schedule performance and identify conditions within engineering/design work-processes that lead to schedule variability.” That way, they can better understand project delays and implement best practices that reduce schedule uncertainties.
3. Digital twins
A digital twin is a virtual representation of a physical thing — whether that’s a plant, a process, or a city. Digital twins have many applications throughout a project lifecycle. One of the most important is right at the beginning, before the physical thing is built.
During the design process, a digital twin is like a prototype that lets you try out different solutions and measure the effects of various conditions, like weather and age. But it has an advantage over traditional prototypes: you can test as many scenarios as you can think up!
4. Bi-level multi-objective optimization
Engineering projects are becoming more complex, and it’s causing trouble. In a 2012 Aberdeen Group study, increasing product complexity came in at #4 on the list of top engineering design challenges. One of the causes of increased complexity is multidisciplinary collaboration.
Now, don’t get me wrong — we believe that multidisciplinary collaboration yields huge benefits. And we believe that engineers should do more of it. But we also know that when you add stakeholders with different perspectives to a project, complexity will naturally increase.
Enter bi-level multi-objective optimization. It’s a mouthful, but the idea is simple. Different stakeholders have different objectives at different levels. And they all need to be optimized for.
For example, in the design of a food plant, the process engineer’s may be focused on food safety, the plant manager on productivity, and the person writing the check on cost-effectiveness. These three objectives operate at different levels. Bi-level multi-objective optimization is aimed optimizing for all objectives by identifying the tradeoffs that need to be made among design variables. It saves time by formalizing the process upfront.
Learn more about this approach in different industrial contexts:
- A bi-level multi-objective optimization algorithm with a bounded multi-variate conjugate gradient method
- Bi-level optimization for a dynamic multiobjective problem
- Bi-level multiobjective programming applied to water resources allocation
Do you want to save time on engineering design? Join us December 5 for a free webinar on how our collaborative engineering platform can help you save time by centralizing your data. Claim your spot here!