File size: 2,858 Bytes
da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 da14378 f563847 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
import streamlit as st
import pandas as pd
import numpy as np
# Streamlit App Configuration
st.set_page_config(page_title="Maintenance Prediction & Scheduling", layout="wide")
# Sidebar for Navigation and File Upload
st.sidebar.title("Navigation")
view_option = st.sidebar.radio("Choose View:", ["Home", "Upload Data", "Maintenance Schedule", "Equipment Insights"])
st.sidebar.title("Upload Data")
data_upload = st.sidebar.file_uploader("Upload Equipment Data (CSV):", type=["csv"])
# App Title
st.title("Maintenance Prediction & Scheduling App")
st.markdown(
"This app predicts maintenance needs and schedules activities to minimize downtime for construction equipment like HVAC, elevators, and generators."
)
# Helper Function - Process Uploaded Data
def process_uploaded_data(uploaded_file):
try:
data = pd.read_csv(uploaded_file)
st.success("Data uploaded successfully!")
st.dataframe(data)
return data
except Exception as e:
st.error(f"Error processing the uploaded file: {e}")
return None
# Main Views
uploaded_data = None
if view_option == "Home":
st.image("https://via.placeholder.com/800x400.png?text=Maintenance+Scheduling+App", caption="Welcome Screen")
st.markdown(
"""
### Key Features:
- Upload site data for analysis.
- Predict maintenance needs based on historical data.
- Schedule maintenance tasks and download the schedule.
"""
)
elif view_option == "Upload Data":
st.subheader("Upload Equipment Data")
if data_upload:
uploaded_data = process_uploaded_data(data_upload)
elif view_option == "Maintenance Schedule":
st.subheader("Maintenance Schedule")
if data_upload and uploaded_data is not None:
st.write("Generating maintenance schedule...")
# Simulate maintenance schedule
uploaded_data["Maintenance_Due"] = np.where(uploaded_data["Condition_Score"] < 75, "Yes", "No")
st.dataframe(uploaded_data[["Equipment_ID", "Equipment_Type", "Maintenance_Due"]])
st.download_button(
label="Download Schedule as CSV",
data=uploaded_data.to_csv(index=False).encode('utf-8'),
file_name="maintenance_schedule.csv",
mime="text/csv",
)
else:
st.info("Please upload data in the 'Upload Data' section.")
elif view_option == "Equipment Insights":
st.subheader("Equipment Insights")
if data_upload and uploaded_data is not None:
st.write("Analyzing equipment performance...")
st.bar_chart(uploaded_data[["Usage_Hours", "Condition_Score"]].set_index(uploaded_data["Equipment_Type"]))
else:
st.info("Please upload data in the 'Upload Data' section.")
# Footer
st.markdown("---")
st.markdown("Developed by [Your Name] - Enhancing Maintenance Planning with AI")
|