Precision manual and automated balancing machines for industrial production
Universal Balancing builds balancing machines for driveshafts, crankshafts, axles, brakes and aerospace components, with a controls stack built on Allen-Bradley, Siemens, FANUC, Kuka and ABB robotics plus EPLAN and SOLIDWORKS Electrical design tools. Hiring is accelerating and centered on US manufacturing and engineering roles, while job posts point to a push to grow aftermarket revenue through installed-base upgrades and service modernization.
Universal Balancing is a Bristol-based machinery manufacturer founded in 1995 that designs and builds precision balancing machines and measuring software. Its range covers manual and automated balancers for driveshafts, axles, crankshafts, brakes, general components and aerospace parts, aimed at high-volume production environments. The company joined the Burke Porter Group in 2015 and now operates as part of Burke Porter, an Ascential Technologies company, which extends its manufacturing and support footprint internationally. It employs 51–200 people and holds ISO 9001:2015 certification.
Its stack includes Allen-Bradley and Siemens PLCs, FANUC, Kuka, ABB and Motoman robotics, EPLAN, AutoCAD Electrical, SOLIDWORKS, PolyWorks, C++ and C#, plus JobBoss, IFS and Salesforce for business operations.
Yes. Hiring is accelerating, focused mainly on manufacturing and engineering roles at mid and senior levels, with openings located in the United States.
Universal Balancing is headquartered in Bristol, United Kingdom, and operates as part of Burke Porter, an Ascential Technologies company.
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Universal Balancing (now part of Burke Porter, an Ascential Technologies Company)'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.