BeginnerFree 4 days · 50 tasks

Casting Defect Spike and OEE Drop

An auto-parts plant's rejects jumped in July and its OEE is sliding. Clean the shop-floor logs, calculate reject rate and OEE, and trace the problem to a material supplier, an ageing machine and the night shift.

Sahyadri Auto Components Pvt Ltd · SQL · Python (pandas, seaborn) · solved in your browser

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The problem

The plant head does not know how far quality and OEE (overall equipment effectiveness) have fallen, which lines and shifts are responsible, or whether the supplier change, the machine condition or the people are the main cause. A data-backed analysis of production from 1 April to 30 September 2026 is needed to decide whether to go back to the old supplier, bring forward the Line 5 overhaul and support the night shift.

How it works

Start the project — the 4-day timer begins and the workspace opens with every table loaded.
Solve 50 tasks in SQL or Python (30 basic, 15 intermediate, 5 hard). Each is checked instantly.
Write the final report in the workspace and add charts from your notebook.
Score = 70% tasks + 30% report review. 60 or more earns a certificate.

What you will deliver

Answers to the 50 analysis tasks (30 basic, 15 intermediate, 5 hard), solved with SQL or Python in the JobPrax workspace.
A final report written in the workspace for the Plant Head: executive summary, data quality, findings and recommendations.
Two to four charts from your Python notebook, added to the report (for example Line 3 reject rate by month, downtime Pareto and OEE by line).