Making the Best Use of Resources: Tracking Energy Consumptions
Besides all the financial costs, knowing the environmental costs of energy consumption, maintenance activities and manufacturing creates a sense of responsibility about making the best use of energy in order to achieve net-zero goals. Energy monitoring stands out by collecting current and voltage data from the machines and tracking the energy consumed by the machines to determine which machines consume more energy than they are supposed to.
Energy Used in Industry is Responsible for 24.2% of Overall Global Carbon Emission
How Predictive Maintenance Help
Autonomous analysis of sensor data supports transparency of machine health and paves the way for highly accurate predictions for future failures.
Find Inefficiencies in Drive Trains
In different operating conditions and loads, monitor the energy consumed by machines and examine how they respond to different conditions. Make a maintenance plan by identifying the problematic parts in your production line.
Contribute to Decarbonization
Rendering the energy consumed by the machines in the line returns to normal by applying accurate maintenance actions, and consequently reducing the energy spent for production causes less carbon emissions.
Determine the Energy Costs
Know your energy costs ahead of time without facing unexpected charges during billing periods. Find out the amount of energy costs of each machine.
Working Against Unplanned Downtime
Our solutions operate and watch over machinery 24/7 not missing any beat letting you plan your downtime, and ensuring smooth operations.
Remaining Useful Lifetime
With Sensemore AI, gradual faults can be detected in their earliest stages and their advancement can be predicted by creating remaining useful lifetime estimation.
Reliability Experts
Easily request an inspection for the suspicious health state of your machines. Our expert engineers are ready to discuss.
Precise Diagnostics From Day One
We offer an end-to-end solution to predict and prevent machinery malfunctions. Our AI-backed technology identifies root causes months in advance.
High Quality Data
Many applications fail due to improper sensors and data acquisition settings. We run an assessment to ensure data is collected from the right location and right moment with our dedicated devices.
Digitalized Machinery
Changing machine types and processes make predictive maintenance difficult. By digitizing your machines and processes, we ensure that the most appropriate analyzes are made.
Root-Cause Detection
Anomaly detection is insufficient to assist maintenance operations. The root cause classification capability of Sensemore AI increases the efficiency of maintenance operations and reduces costs.
Blog Posts
We share our knowledge with the community, please check our blog pages. If you need further information feel free to contact us.
December 16, 2022
Sustainable Future by Improving the Maintenance Strategies
Sustainability in industry can be achieved by reducing industrial carbon…
October 25, 2022
Predictive Maintenance with Electrical Signature Analysis (ESA)
Predictive maintenance through machine health monitoring aims to prevent costly unplanned downtime using analysis techniques such as…
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