Facilities Maintenance Prioritization Dashboard (FMPD-lite)

Project Overview

FMPD-lite is a lightweight decision-support tool designed to prioritize maintenance activities in a facilities engineering environment.

The system uses a weighted scoring model to rank maintenance tasks based on asset condition, criticality, and task urgency.

The results are visualized using Excel and Power BI dashboards to support operational decision-making.

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Dashboard Preview

The Dashboard provides an executive overview of maintanance priorities, asset condition, and key operational performance indicators.

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Repository Structure

FMPD-lite/
|
|-- README.md
|
|-- data/
|   |-- assets.xlsx
|   |-- maintenance_tasks.xlsx
|
|-- model/
|   |-- scoring_model.xlsx
|
|-- outputs/
|   |-- prioritized_schedule.xlsx
|   |-- kpi_summary.xlsx
|
|-- dashboards/
|   |-- powerbi_dashboard.pbix
|
|-- documentation/
|   |-- system_overview.md

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Methodology

The model applies a weighted scoring system:

Priority Score = (Asset Criticality × 3) + (Condition Risk × 2) + (Task Urgency × 2)

Tasks are ranked in descending order of score to generate a prioritized maintenance schedule.

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Data Description

assets.xlsx

Contains:

• Asset ID
• Type (Pump, Compressor, Valve, etc.)
• Location
• Condition (Good, Fair, Poor)
• Criticality (Low, Medium, High)

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maintenance_tasks.xlsx

Contains:

• Task ID
• Asset ID
• Task Type
• Urgency level
• Duration (hours)

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Model Layer

scoring_model.xlsx

Implements:

• Asset criticality scoring
• Condition risk scoring
• Task urgency weighting
• Final priority score computation

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Outputs

prioritized_schedule.xlsx

Ranked maintenance tasks sorted by priority score.

kpi_summary.xlsx

Operational KPIs such as:

• Total tasks
• High-priority tasks
• Average score

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Dashboard Layer (Power BI)

A Power BI dashboard is included to visualize:

• Asset condition distribution
• Maintenance priority ranking
• Workload by asset type
• High-risk asset identification
• KPI summary overview

File:

• powerbi_dashboard.pbix

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Engineering Purpose

This project demonstrates:

• Maintenance prioritization logic
• Industrial decision-making using weighted scoring
• Structured data handling in Excel
• Data visualization using Power BI
• Basic operations research (OR-lite) thinking

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Tools Used

• Microsoft Excel
• Power BI

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Limitations

• No real-time data integration
• No optimization solver
• Static scoring model
• Simplified assumptions for industrial operations

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Author

Blaise Atambo

Facilities Engineering Portfolio Project

Focus: Industrial Analytics | Operations Engineering | Maintenance Systems