Achieve direct and indirect energy savings with explicit AI-guided process optimization from DataProphet.
Efficiencies gained through process optimization naturally result in energy savings across the production line. Yet, often reducing energy costs is a target on its own. When specifically applied to reduce energy consumption, AI-driven process optimization is a powerful tool. It uncovers hidden power drains in your control plan and defines new production parameters to reduce consumption and improve global operating performance. DataProphet CONNECT captures and digitizes historical and real-time production data, which DataProphet PRESCRIBE uses to find the process parameters that result in the lowest energy usage.
For manufacturers, intelligently harnessed prescriptive machine learning means continual improvements in industrial energy efficiency. DataProphet PRESCRIBE aggregates all changeable process parameters pertinent to a specific production line.
Our deep learning algorithms recognise the dynamic state of your plant from its process data history, and glean whether the actual process is within ideal operating ranges.
Depending on what metrics PRESCRIBE has been trained to improve, this can include the variables that underlie energy intensity and consumption. DataProphet PRESCRIBE then guides operators, process engineers, and technicians to make parametric adjustments to ensure continued energy efficiency during production ahead of real-time.
For some manufacturing processes, energy consumption is one of the main drivers of production cost, and any energy savings positively impact the plant’s performance.
In lean manufacturing, one form of waste to be eliminated derives from overprocessing when additional cycles and/or increased processing intensity do not yield additional value to the final product.
By reducing energy consumption, all factories mitigate their carbon emissions, supporting the global effort to comply with increasingly stringent environmental regulations.
In certain manufacturing processes, reducing operational energy intensity and optimizing energy consumption contributes to the lifespan of industrial assets.
Find out how much DataProphet can save you in direct and indirect energy costs.
Energy savings are often secondary to optimizing other production parameters, such as quality, throughput, and scrap reduction. DataProphet DETECT ingests data from existing machines, systems, and processes, helping you achieve indirect energy savings through reduced machine downtime, optimal machine use, and minimal impact on upstream and downstream processes.
There is an additional wasted energy cost for every item you scrap, not to mention the extra energy needed for rework and the time wasted finding the right machine setpoints. DataProphet PRESCRIBE finds the optimal recipe across production parameters to maximize the energy efficiency of your processes. This way, manufacturers use as little energy as possible to achieve the desired product quality.
DataProphet’s prescriptions have resulted in a significant reduction in scrap and rework, making a positive impact on our bottom line.
- CEO – Engine Block Manufacturer
Through continuous machine monitoring and parameter optimization, DataProphet AI-as-a-Service diagnoses complex failures and prescribes immediate corrective action to prevent down-the-line defects.
With DataProphet PRESCRIBE, you can:
Longer process cycle times use more energy. Optimizing the time that it takes to achieve a “first time pass” can significantly reduce your variable energy consumption and costs. Together with the suggested optimal operational parameters, DataProphet PRESCRIBE reduces expensive stops on the line through increased asset uptime and enhanced overall equipment effectiveness.
Explore how deep learning, pre-emptive analytics can help you identify root causes of energy waste, and prescribe optimal parameters for ideal energy efficiency on your production line. All while reducing scrap and eliminating the cost of non-quality ahead of real-time.
Our client successes include eliminating external automotive scrap, reducing mechanical welding defects by 75%, and halving the cost of non-quality – all within six months of implementation. Get results, fast.
Explore how prescriptive analytics is transforming manufacturing through optimized energy consumption, increased overall equipment effectiveness, and higher product quality.
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Our robust, deep learning solutions can target underlying energy consumption process variables specific to different manufacturing verticals.
By actively optimizing control parameters, we helped one German automotive OEM reduce autonomous welding defects by 75%, rendering their rate of energy consumption throughout the line more economical.
In high-tech, high-risk enterprises, systemic manufacturing defects translate into serious production energy loss. DataProphet improves chip fabrication, so semiconductor manufacturers gain full value from priceless yield ramps.
Improving the speed and first-pass rate of defect-prone rubber manufacturing with DataProphet’s Expert Execution Systems means eco-efficient production.
We have consistently achieved a 40% reduction in defect rates within three months at gray iron foundries, a highly energy-intensive vertical that prizes first pass production.
More than ever, competitive advantage in complex, multistep manufacturing means responsible consumption and eco-efficient production must be embedded in digital transformation. By partnering with DataProphet, you can leverage our Expert Execution Systems to step towards energy-economical autonomous manufacturing. Our partners embrace Industry 4.0. and become world-leading innovators in adopting AI-as-a-Service for sustainable manufacturing.
Stay up to date on machine learning developments, plus guidance on how to optimize your manufacturing processes using AI.