You will get a predictive maintenance ML model for equipment monitoring
Project details
You will get a predictive maintenance machine learning solution designed to help monitor equipment health, predict failures, reduce downtime, and improve maintenance planning. Using Python, machine learning, and industrial analytics techniques, I build intelligent systems that transform operational and sensor data into actionable maintenance insights.
This project can include equipment failure prediction models, downtime analysis, maintenance scheduling insights, anomaly detection, health monitoring dashboards, and deployment-ready solutions tailored to industrial operations. Depending on your use case, models such as Random Forest, XGBoost, classification algorithms, regression models, and time series forecasting techniques can be applied for predictive analysis.
With a background in Industrial and Production Engineering and experience in data analytics, machine learning, and operations analytics, I focus on creating practical AI solutions that help manufacturing, logistics, and industrial businesses improve reliability, optimize maintenance operations, and reduce unexpected equipment failures.
This project can include equipment failure prediction models, downtime analysis, maintenance scheduling insights, anomaly detection, health monitoring dashboards, and deployment-ready solutions tailored to industrial operations. Depending on your use case, models such as Random Forest, XGBoost, classification algorithms, regression models, and time series forecasting techniques can be applied for predictive analysis.
With a background in Industrial and Production Engineering and experience in data analytics, machine learning, and operations analytics, I focus on creating practical AI solutions that help manufacturing, logistics, and industrial businesses improve reliability, optimize maintenance operations, and reduce unexpected equipment failures.
Machine Learning Tools
Apache MXNet, BERT, Chainer, ChatGPT, deeplearn.js, Deeplearning4j, GitHub Copilot, Keras, Microsoft CNTK, Microsoft Power BI, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, R, scikit-learn, SQL, Stata, Tableau, TensorFlow, Weka, XGBoostWhat's included
| Service Tiers |
Starter
$80
|
Standard
$200
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 6 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Graphs/Charts | 4 | 8 | 12 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
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AU
Akintobi U.
Jun 1, 2026
Excel Dashboard for Business Reporting
Azeez demonstrated outstanding attention to detail and business understanding throughout the project. His expertise in data analytics, reporting, and KPI tracking, leveraging Microsoft Excel, added significant value to our decision-making process.
LW
Li W.
Sep 15, 2023
Freelance HR Business Partner (1A35)
LW
Li W.
Aug 16, 2023
Freelance HR Business Partner (1A35)
NZ
Nan Z.
Jul 6, 2023
Recruiting Tasks (NncL): Resume Screening & Assessment
Olasupo helped us evaluate candidates for an open position in finance relating to our investments in technology, healthcare, publishing, philanthropy, and sustainability (ESG). Olasupo helped us in a timely and productive way, and was completely responsive and communicative about all our goals. We're thankful for the help and would consider working together again the next time we need an HR partner.
IE
Iyanulowa E.
Oct 26, 2022
Wix, Zapier and Activecampaign Expert
Thank you for your support and great communication. You clearly solvedmy integration problems... I'll definitely,, use your service again. Thanks.
About Olasupo
Supply Chain Analytics | Inventory Optimization | Demand Forecasting
Ikeja, Nigeria - 9:13 am local time
With a background in Industrial and Production Engineering and hands-on experience in supply chain operations, analytics, and business intelligence, I specialize in demand forecasting, inventory optimization, procurement analytics, KPI reporting, and supply chain performance analysis
I worked with an energy company in the gas-to-power sector where I applied data analytics and data science techniques to support operational efficiency and business decision-making by:
• Automating reporting pipelines and operational data workflows
• Cleaning, transforming, and analyzing large operational and energy datasets
• Building analytical dashboards for KPI monitoring and performance insights
• Supporting predictive and data-driven operational decision-making processes
• Improving data visibility, reporting efficiency, and business intelligence across operations
My technical toolkit includes:
• Excel & Google Sheets
• SQL (PostgreSQL, MySQL, SQL Server, SQLite)
• Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
• Time Series Forecasting (ARIMA, SARIMA, ARMA, VAR, VARMA, Holt-Winters, Prophet)
• Machine Learning & Predictive Analytics
• ML Model Deployment & Automation
• Tableau & Power BI
• Streamlit Dashboard Development
• Inventory Optimization & Supply Chain Analytics
• Data Cleaning, ETL & Business Reporting
I can help you with:
✔ Business dashboards & KPI reporting
✔ Demand forecasting & time series analysis
✔ Machine learning & predictive modeling
✔ Inventory and sales analytics
✔ Data cleaning, preprocessing & transformation
✔ Excel automation & reporting systems
✔ SQL queries, database analysis & ETL workflows
✔ ML deployment using Streamlit and Python apps
✔ Supply chain and operations analytics projects
I focus on delivering clean, scalable, and business-focused analytical solutions that help clients improve decision-making, optimize operations, reduce inefficiencies, and uncover meaningful insights from their data.
Let’s work together to turn your data into smart business solutions.
Steps for completing your project
After purchasing the project, send requirements so Olasupo can start the project.
Delivery time starts when Olasupo receives requirements from you.
Olasupo works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Client shares equipment data, maintenance history, operational details, and project goals.
Data Cleaning & Analysis
I clean, preprocess, and analyze the dataset for predictive modeling.