Optimizing Factory Robot Movements to Cut Energy and Emissions

This patent describes a system for industrial facilities that measures the energy use and carbon emissions of different groups of robots moving along a track, then adjusts their operations to reduce environmental impact.

What it covers

The patent describes a system for managing industrial movers, like robots on a track, to reduce their environmental impact. It works by having one or more processors first "determine a first amount of energy consumption associated with a first portion of the plurality of movers and a second amount of energy consumption associated with a second portion of the plurality of movers" (Claim 1). Then, it calculates "emissions per unit" for these different groups of movers based on their energy use. Based on these emission figures, the system "determine[s] one or more operating settings for the mover system" and "send[s] one or more commands" (Claim 1) to control the movers. For example, if one section of movers is found to be highly inefficient, the system might "cause at least one of the plurality of movers to be powered down, powered up, parked, or any combination thereof" (Claim 10) to optimize overall emissions.

What it doesn't cover

• —Does not cover systems that only optimize for speed or throughput without considering energy consumption or emissions per unit.
• —Does not cover systems that control individual movers without considering groups or portions of movers.
• —Does not cover systems that determine operating settings based solely on cost, without factoring in emissions or energy use.
• —Does not cover systems that lack the ability to send commands to adjust mover operations based on the determined settings.
• —Does not cover systems that manage movers not operating on a track.

The clever bit

The novelty lies in specifically calculating "emissions per unit" for *portions* of a mover system and then using that metric to dynamically adjust operating settings, rather than just optimizing for speed or overall energy. This allows for granular, sustainability-focused control.

Why it matters

As industries increasingly focus on sustainability, this technology provides a way to directly measure and reduce the environmental footprint of automated manufacturing and logistics. It allows companies to make data-driven decisions about their factory floor operations, potentially leading to lower energy bills and compliance with environmental regulations. This kind of optimization is crucial for large-scale industrial operations aiming for net-zero goals.

Real-world examples

• 1.Automated assembly lines in car factories
• 2.Robotic sorting systems in warehouses
• 3.Automated guided vehicles (AGVs) in logistics hubs
• 4.Conveyor belt systems in manufacturing plants