Optimize Industrial Operations and Supply Chains to Reduce Carbon Emissions
Businesses are urgently trying to address climate change by meeting new carbon emissions mandates. New regulations as well as weather disruptions are changing how they consume energy as plan production.
Upgrading existing systems and staying competitive, while complying with new climate directives, presents new and more complex challenges.
Simulation modeling offers a good, low-risk way to test solutions in a virtual environment, but simulation alone does not surface all the insights an organization needs.
Simulations optimized with Pathmind AI are better at discovering solutions when businesses need to be efficient while also lowering their carbon footprint. Since the AI has no preconceptions about the “right” decisions, it is able to reveal new ideas to improve existing systems. Simulations for production line optimization, delivery routing, and resource management can all benefit from AI optimization.
Optimize Business Processes for Efficiency
Manufacturing facilities, mining sites, and other operations that require many processes to work simultaneously can find lowering their carbon footprints to be a unique challenge. Unlike other optimization tools, Pathmind’s AI is able to improve performance at individual stages while also monitoring larger systems as a whole. This feature allows for more insight into how green changes will impact revenue and production. Applications such as production line optimization, delivery truck routing, and facility layout planning can all be made more efficient and environmentally friendly with AI.
Manage Resource Usage with AI
Operations that use large amounts of resources can see their bottom lines impacted by variability in prices. Unpredictable costs make it difficult to plan production schedules and prevent businesses from running as efficiently as they should. Simulations with traditional optimizers are not equipped to understand those price fluctuations and often prove ineffective. Since Pathmind is powered by AI, it is better able to understand how and when resources prices will change. That knowledge can help businesses better strategize production and purchasing choices, increasing profits and lowering their carbon footprint simultaneously.
Carbon Emission Reduction Use Cases
Featured Case Studies
Pathmind Optimization Cuts Power Usage and Saves Metals Processor 10% on Energy Spending
Pathmind partnered with a major engineering firm to solve an energy management problem at a metals processor. Fluctuations in electricity costs made effective production planning impossible with optimizers unable to predict change. Pathmind’s AI learned to pick up on subtle signals that indiciated the price was going to change so that the processor could lower production during surges. The simulation demonstrated a 10% savings in electricity spending, while also cutting down on the processor’s power consumption.
Accenture and Pathmind Simulation Model Optimizes Deliveries While Reducing Carbon Emissions
Accenture’s Applied Intelligence team worked with Pathmind to model carbon emissions in a product delivery simulation. The team looked to find ways to efficienctly deliver goods between manufacturing centers and distributors while also considering pollution. The final model maximized efficiency while minimizing both delivery wait times and carbon emissions.
Reduce Your Carbon Footprint with AI
Contact us to see how Pathmind reinforcement learning can help you make more efficient, climate-friendly business decisions.