Revolutionizing Manufacturing: How Realtime Robotics and Schaeffler are Transforming Robot Collaboration and Efficiency

Manufacturing facilities are increasingly turning to automation to improve efficiency and productivity. However, with the rise of complex environments and the addition of more robots to the factory floor, keeping operations collision-free and optimized can be a challenge. Realtime Robotics’ RapidPlan motion control and collision avoidance software provides a solution for manufacturers looking to improve productivity in these complex environments. In this article, we will explore how RapidPlan software helped Schaeffler optimize bin-picking operations with multiple robots, resulting in a significant increase in throughput.

Initial goal of the application

Schaeffler, a global supplier of bearings and automotive parts, wanted to optimize its use of robotics by having two robots pick parts from the same bin without colliding. This was a challenging task that required a solution that could accurately control the movement of the robots and prevent collisions in real-time.

Results of the Testing

Realtime Robotics’ RapidPlan software was the solution that Schaeffler turned to. The software was tested in a complex and unpredictable environment, where it was observed that running two separate robots together would dramatically improve the bin-picking time. The software exceeded expectations by improving throughput without significantly complicating the programming layers. Traditionally, to avoid collisions, each robot has to wait for the other one to complete its task before moving into its space. However, with RapidPlan, companies can truly capitalize on maximum productivity by adding additional robots to their application.

Benefits of RapidPlan

One of the primary benefits of RapidPlan is that it allows for more robots to be added to the application while capitalizing on maximum productivity. Most people would think that the addition of a second robot to operations would double throughput. However, in reality, companies typically only see about a 28-30% overall throughput increase. With RapidPlan, Schaeffler was able to improve throughput without significantly complicating the programming layers.

Results for Schaeffler

Schaeffler had set a target of a 60% increase in throughput, but the results far exceeded expectations with an almost double increase in throughput. RapidPlan significantly improved throughput for Schaeffler while eliminating the chance of time-consuming robot collisions. The test results have helped Schaeffler to further optimize its robot cells by adding more robots without slowing down operations.

Robot manufacturer-agnostic software

Another significant advantage of RapidPlan is that it is built to be robot manufacturer-agnostic, meaning that companies can use it to streamline the cell commissioning process. Companies no longer need to worry about compatibility issues with their current robots, as RapidPlan can work with any robot manufacturer.

Simulation capabilities with RapidPlan

Schaeffler used RapidPlan to quickly simulate their robot cells and gain a holistic cell simulation, which made it easy to plan out how the robots would move. Furthermore, they used the same simulation software to develop the real-life robot actions, leading to better and more efficient operations.

Realtime Robotics’ RapidPlan software is a game-changer for manufacturers looking to improve productivity in complex environments. The software optimizes robot movement in real-time while ensuring collision-free operations, leading to a significant increase in throughput. Furthermore, with RapidPlan’s robot manufacturer-agnostic and simulation capabilities, companies can streamline their cell commissioning process and optimize their operations even further. The future of robotics and manufacturing looks bright, and RapidPlan is leading the way.

Explore more

Python Programming vs. Machine Learning: A Comparative Analysis

Understanding the nuanced relationship between a versatile programming language like Python and the sophisticated algorithmic structures of machine learning is essential for anyone navigating the current landscape of artificial intelligence. In 2026, the distinction between writing code and training a model remains a fundamental crossroad for developers and researchers alike. Python serves as a high-level, interpreted programming language that prioritizes

Autonomous Customer Experience – Review

The modern enterprise landscape has reached a pivotal juncture where the static database of the traditional customer relationship management system is no longer sufficient to meet the dynamic expectations of a hyper-connected global marketplace. For decades, organizations relied on historical data and manual entry to manage their interactions, often resulting in fragmented experiences that frustrated both employees and consumers. However,

Trend Analysis: Telecommunications Market Consolidation

The global telecommunications landscape is undergoing a radical transformation as major carriers abandon their dreams of vast international empires to seek safety within the familiar confines of their domestic borders. This era of the “Mega-Telco” reached a definitive conclusion as global giants traded geographic reach for domestic stability and financial simplicity. In a move that mirrors a broader industry shift,

Can Pepeto and Utility Tokens Lead the Next Crypto Surge?

The transition from purely speculative digital assets to those offering verifiable functional value has fundamentally altered how both retail and institutional investors approach the current 2026 market cycle. Market analysts observe that the era of blind investment is fading, replaced by a rigorous focus on technical “reset” levels and liquidity cycles. Identifying the specific price floors that trigger sustained institutional

Transforming CX Into a Customer-Led Growth Operating System

The vast majority of modern enterprises have successfully mastered the art of collecting customer feedback, yet they remain remarkably ineffective at converting those high-level sentiments into measurable financial growth. This disconnect has created a paradoxical environment where survey scores might look healthy on a digital dashboard while actual customer retention and lifetime value are simultaneously eroding. As the business landscape