Day 81 SQL Challenge: Factory Processing Time Analysis

Today I tackled an interesting SQL problem involving machine activity logs from a factory system. The task was to calculate each machine's average processing time to complete a process.

Problem Statement:

We are given a table that logs machine activities - specifically, process start and end events. Each machine runs multiple processes, and every process has a start and an end timestamp.

The goal:

• For each machine, calculate the average time it takes to complete its processes
• Round the result to 3 decimal places for precision

Approach:

To solve this, I used a self-join on the table to pair each start with its corresponding end event (based on machine_id and process_id). Then, I calculated the time taken for each process and finally averaged it per machine.

Here's the SQL solution:

SELECT a.machine_id, 
            ROUND(AVG(b.timestamp-a.timestamp),3) AS processing_time
FROM Activity a 
JOIN Activity b 
ON a.machine_id=b.machine_id 
AND a.process_id=b.process_id 
AND a.activity_type='start' 
AND b.activity_type='end' 
GROUP BY machine_id;        

Key Concepts Used:

• Self Join
• Aggregate Functions
• Timestamp Operaations
• Rounding results

Learning

This problem was a great reminder of how powerful SQL joins are - especially when analyzing event logs or timelines. It also reinforced the importance of understanding the structure of data and designing efficient queries to derive insights.

Would love to hear how you might solve it differently or any tips you follow for optimizing similar queries!

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