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Predictive maintenance with machine learning

by
Odoo

262.60

v 17.0 Third Party
Availability
Odoo Online
Odoo.sh
On Premise
Odoo Apps Dependencies Maintenance (maintenance)
Repairs (repair)
Discuss (mail)
Inventory (stock)
Sales (sale_management)
Invoicing (account)
Lines of code 1585
Technical Name ewall_predictive_maintenance
LicenseOPL-1
Websitehttps://www.ewallsolutions.com
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Availability
Odoo Online
Odoo.sh
On Premise
Odoo Apps Dependencies Maintenance (maintenance)
Repairs (repair)
Discuss (mail)
Inventory (stock)
Sales (sale_management)
Invoicing (account)
Lines of code 1585
Technical Name ewall_predictive_maintenance
LicenseOPL-1
Websitehttps://www.ewallsolutions.com

Predictive Maintenance on Milling Machinery Equipments using Machine Learning model
Intelligent Maintenance Tracking

Predictive Maintenance with Machine Learning

Smart Maintenance Automation: Our module leverages a Random Forest classifier to analyze milling machinery records and detect potential failures in advance. Automatically notify technicians and create repair requests to prevent unexpected breakdowns. Seamlessly integrated with the Odoo Repairs module for efficient maintenance management. Perfect for businesses seeking to optimize asset performance and streamline repair processes.

Purpose of the application:

The Predictive Maintenance module using a Random Forest classifier enables businesses to proactively manage milling machinery maintenance by predicting potential failures based on historical maintenance records. The module leverages a pre-trained machine learning model with the milling machinery records to analyze equipment data, automatically detecting anomalies and identifying potential failure. If a potential failure is detected, the system instantly notifies the assigned technician, allowing for timely intervention before breakdowns occur.

Seamlessly integrated with the Odoo Repairs module, this solution automates the creation of maintenance requests and repair orders, ensuring a streamlined workflow for issue resolution. By optimizing maintenance schedules and reducing unexpected downtimes, businesses can extend asset lifespan and improve operational efficiency. The module enhances decision-making with data-driven insights, enabling organizations to shift from reactive to predictive maintenance strategies.

Prerequisites:

  • Install the dependencies indicated in the 'requirements.txt' file for the module.

Note: We trained our predictive maintenance machine learning model using our own randomly generated milling machines dataset with pre-defined parameters.

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Configuration of the Predictive Maintenance Model

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Configure the equipment categories for predictive maintenance

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Create maintenance products for the equipment

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Map equipment categories and products to the respective equipment

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Pre-trained machine learning model using a Random Forest classifier for maintenance prediction and its model performance score

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Import or create logs for the respective equipment to enable predictive analysis

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Use the "Make Prediction" button for manual predictions, or the system will do predictions automatically through scheduled actions

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If maintenance is needed, the system notifies the technician to create a maintenance request

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If needed, create a repair order from the maintenance request and proceed with the repair

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Use the "Retrain" button to update the model with the latest maintenance log

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Use the "Prepare Training Dataset" button to generate the latest dataset for the specified date range

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Review the prepared dataset and click the "Retrain Model" button to check the updated performance score

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Compare model scores and use "Override Trained Model" to update the model for future predictions

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Dashboard with useful insights of predictive maintenance

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For Support Contact

support@ewallsolutions.com

Don't hesitate to reach out if you have any further questions or need assistance!

Odoo Proprietary License v1.0

This software and associated files (the "Software") may only be used (executed,
modified, executed after modifications) if you have purchased a valid license
from the authors, typically via Odoo Apps, or if you have received a written
agreement from the authors of the Software (see the COPYRIGHT file).

You may develop Odoo modules that use the Software as a library (typically
by depending on it, importing it and using its resources), but without copying
any source code or material from the Software. You may distribute those
modules under the license of your choice, provided that this license is
compatible with the terms of the Odoo Proprietary License (For example:
LGPL, MIT, or proprietary licenses similar to this one).

It is forbidden to publish, distribute, sublicense, or sell copies of the Software
or modified copies of the Software.

The above copyright notice and this permission notice must be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
DEALINGS IN THE SOFTWARE.

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