Rescuing the Exhausted Engineer with Digital Manufacturing Simulation

Viewpoint: Product designers and engineers were overburdened even before the pandemic put extra pressure on their teams, workflows, and customers. Analyses enabled by virtually replicating both a product and its manufacturing processes can turn things around.

Manufacturers put a lot of weight on the shoulders of their product designers and engineers these days. It was tough for them before the pandemic, but now it’s even worse.

Supply chain disruptions, layoffs, furloughs, and government-imposed lockdowns have large manufacturers struggling to make up lost revenues and profits while trying to compete with smaller, more nimble competitors that have fully embraced digital transformation. There is constant pressure for product engineering teams working remotely to create more innovative designs, reduce manufacturing costs, and improve the overall efficiency of the design and delivery process — all at the same time.

These challenges impact more than designers. Consider procurement and cost engineering teams tasked with sourcing and costing the product parts that engineers have designed. It’s their job to deliver value for the money. Unfortunately, in most organizations, they don’t get invited to the party until it’s too late — typically at the prototype stage, when about 70% of the cost is already designed in. Once the design goes out for prototype manufacture, changes start to get very costly, both financially and schedule-wise.

Ideally, procurement and cost engineering personnel are working closely with the design team from the start, but that’s easier in concept than in practice. Many companies’ processes and cultures have been built up over decades and are hard to change. Engineering teams now working remotely are more isolated than in the past.

There may also be friction about roles and responsibilities. It’s often the case that a product looks great in the CAD software, but not all the features can be manufactured efficiently or within target cost. Designers may not appreciate it when a professional with limited product knowledge and experience questions some of the features and tolerances in their design.

Over the years, procurement and cost engineering professionals learn how to work with engineers, designers, and suppliers, but you can’t really hire for that. Many of those that have developed those relationships and tribal knowledge are nearing retirement or have already left the building.

Domino Effects

Further exacerbating the situation for manufacturers are their customers’ shrinking time-to-market windows as they react to shifts in demand. In response, manufacturers add more designers, but not more cost engineers, to keep pace. That means more pressure for procurement to make sure sourced products come in on time, so engineers aren’t idle. The time squeeze often leads to product design compromises which need to be addressed in the late stages or post-production, raising costs. This risk gets built into proposals as a buffer.

The rest is predictable: Manufacturers either lose contracts because they bid too high to cover potential extra costs, or sacrifice margin because there is not enough buffer built into their bid. And, in the worst-case scenario, customers end up disappointed.

This chain of events wastes organizational time, and attention as well. That in turn leads to missed business opportunities and a diminished ability to make the right decisions about which projects to pursue and where to invest resources.

Digitizing the Product Development Lifecycle from Design through Customer Delivery

The engineer’s job is to move a product from design to production: from nothing to something. In between those start and finish lines, they have to take care of product design, testing and verification, analysis and simulations, and documentation. Then they have to repeat the process with value engineering. It’s a lot to do.

In a perfect world, engineering, sourcing, and manufacturing teams would work in parallel. Once the engineers had a defined design in the product lifecycle management (PLM) system, sourcing and manufacturing can start to determine:

• How to acquire the necessary parts
• How to manufacture (Cast? Fabrication? 3D printing? Composite?)
• At what volumes/cost
• Where to buy/source
• How to stock and ship.

At the end of the design phase, they should know whether this new concept is manufacturable and whether they have the best price to manufacture that design. These two things go hand-in-hand. If the manufacturer gets this wrong (which happens often), there have to be some late-stage changes — in design, manufacturing process, and/or cost — before committing to tooling and starting production. These unplanned late-stage changes consume a lot of engineering’s time.

If we look at a typical product development timeline, the window of opportunity sits between the availability of the first CAD model and Release to Production. This is the sweet spot where there is enough information available to impact cost and manufacturability; before we commit to items with long lead times, such as prototyping, tooling, and materials. The question is how to gain the insights you need to take advantage of this window.



Digital Manufacturing Twins

To answer that question, consider this one: What if a virtual product could be put through the same series of design and manufacturing stages that a real product goes through? You would need a digital representation of the product design — and of the processes for manufacturing it — that could quickly and easily be analyzed and changed before anything is sent off to prototype or production. This would minimize late-stage changes in engineering and manufacturing, move delivery timelines forward, and enable engineers to focus more time on innovation. These advantages in turn would help their companies to gain market share and revenue.

There are new technologies and tools available today that use a “digital twin” developed from the CAD model and all the other information that surrounds it. These representations simulate the manufacturing environment and product requirements, and then cost the digital twin in “digital factories” that replicate process, materials, labor, and logistics costs around the world. The manufacturer gains valuable insights about cost and manufacturability earlier in the product lifecycle, enabling more focus on designing the best possible product at the lowest possible cost.

This information can be used at different stages of the product lifecycle:



The most important aspect of these tools is that they don’t require anything of the already overburdened engineer. Instead, these simulations can run in the background, with no interaction required from the design team. CAD designs are automatically analyzed for manufacturability and cost when they reach a certain point in their lifecycle; e.g., when they are checked into a PLM system, or another defined trigger.

The simulation generates all sorts of information related to manufacturability, process, costs, time-to-market, and resources required, and flags anything that is not optimized. Only when that flagging occurs do the engineering, sourcing, and cost engineering teams need to get involved. This way, resources are not diverted for anything unrelated to their role — or that does not need their attention. Then designers can focus on those issues that require their attention and make adjustments as needed in the product.

These tools can highlight the important manufacturing cost drivers and help get the right information to the right people at the right time to take advantage of important insights and opportunities.