Excel as a Bridge: Streamlining Simulation Data When Databases Aren’t Ready

Excel as a Bridge: When connected databases aren’t available, simulation projects often face delays and inefficiencies. In this session, Natalia Weis and Cristina Palomares from Lear Corporation present a practical solution: using pre-templated Excel tables to streamline data integration in Siemens Tecnomatix Plant Simulation. This method reduces errors, saves time, and empowers users—regardless of expertise—to manage data efficiently. With a focus on flexibility, standardization, and ease of use, this approach has proven effective across automotive projects and beyond. Attendees will gain actionable insights and see real-world examples of how Excel can act as a powerful bridge between disconnected data and effective simulation.

Stepping into the future with Siemens Process Simulate Copilot: AI-Driven Robotic Simulation [VIDEO]

Explore how to use Process Simulate Copilot to streamline the creation of a pass template, a structured list of standard robot actions used to configure trajectories. Designed to help simplify complex robotic simulations, Process Simulate Copilot empowers engineers by accelerating decision-making, enhancing simulation workflows, all while distilling simulation data into concise study information summaries. Whether it’s optimizing robot paths or solving collision issues faster than ever before, the Copilot provides intelligent guidance, unlocking new levels of efficiency in digital manufacturing.

Crane simulation reduces costs while enhancing planning reliability

Crane simulation plays a vital role in optimizing industrial production by improving workflow efficiency and ensuring seamless coordination between human operators and machinery. Integrating remote control systems allows for precise movement and synchronization, minimizing delays and inefficiencies. Accurate simulations also help determine the ideal number of cranes required, preventing costly overdimensioning. Additionally, assessing load distribution on crane runways ensures structural stability and avoids expensive retroactive modifications. By leveraging digital tools, businesses can enhance planning reliability, reduce costs, and improve safety. At the Plant Simulation User Conference 2025, Steffen Bangsow will present insights on optimizing crane-based production systems.

Powering advanced bin-picking with Concept Analysis, Dynamic Simulation, and Virtual Commissioning 

Bin-picking refers to the automated process of using robots, often equipped with vision systems, to identify, pick, and place parts from a bin or container. Explore how static analysis, robotics simulation and virtual commissioning technology help evaluate, debug, and validate bin-picking stations before physical hardware is deployed, reducing risks and avoiding costly delays.

Maximize pharmaceutical plant efficiency with the power of Siemens Plant Simulation

In the fast-paced world of pharmaceutical manufacturing, optimizing plant design and operations is crucial for ensuring high-quality production and meeting regulatory standards. As the industry continues to evolve, adopting advanced technologies like simulation has become essential for designing and improving pharmaceutical plants. Utilizing simulation tools not only allows you to create more efficient and flexible plant layouts but also helps you predict and optimize resource consumption, material flow, and production line design before any physical construction takes place.

Process simulate collaborate

Advancing 3D Collaboration with Process Simulate Collaborate [video]

In today’s interconnected landscape, engineers often face cumbersome tasks in process simulation, hindering collaboration. Read how Tecnomatix’s Process Simulate Collaborate streamlines this process, freeing up to 20% of engineers’ time by providing cloud-based access, storage, and secure sharing for 3D simulation studies.

Simulation-based collision detection

Thirty (30) years ago, I learned in school how to calculate the intersection of two spheres in 3D space. Today,…

Part 2: How Digital Twins Help Scale Up Industrial Robotics AI

Training a robotic task with Reinforcement Learning Artificial Intelligence (AI) and Machine Learning (ML) are technologies that enable robots to…

How Digital Twins Help Scale Up Industrial Robotics AI

Part 1: Commissioning a vision-based Supervised Learning solution Artificial Intelligence (AI) and Machine Learning (ML) are technologies which enable robots…