Assembly problems often surface late, when fixes cost more and timelines slip. A new simulation approach aims to catch those issues earlier.

Keysight Technologies has launched Keysight Assembly, a new virtual process simulation solution designed to help manufacturers identify assembly issues earlier in development, before they become costly production problems.
Developed in collaboration with automotive OEM partners, the software enables engineers to replicate shop-floor processes—including part positioning, clamping, and joining—through guided workflows and templates that do not require specialized finite element modeling (FEM) skills. This allows teams to identify distortion and dimensional risks much earlier than physical prototyping, reducing reliance on trial-and-error approaches, shortening production timelines, and improving build accuracy.
The move addresses a persistent challenge in automotive and industrial manufacturing, where late-stage assembly failures can be expensive and disruptive. Recalls and warranty claims cost major U.S. automakers billions of dollars, with many defects only surfacing during the physical build stage. The later an issue is discovered, the more costly it becomes to fix, often leading to significant rework and delays in product launches.
Keysight Assembly also integrates with the company’s existing stamping simulation software, allowing engineers to carry stamped-part data from forming through assembly and validate outcomes against pre-production scan data. By linking separate stages of manufacturing development into a single workflow, the platform helps teams detect variation earlier and improve correlation between simulation and physical results.
Mathilde Chabin, Director of Product Management for Virtual Manufacturing, Keysight, said: “Engineers know the frustration of discovering distortion only after parts are on the shop floor. Traditional tools stop at part-level analysis and don’t reflect how assemblies are actually built. Keysight Assembly simulates real production workflows, so teams can see process sensitivity early, when changes are easy and inexpensive.”
Click here for the original announcement.



