Manufacturing & Operations Analytics for Beginners: A Practical Guide to Production Analytics, OEE, Quality, Lean Manufacturing, Maintenance, Capacity Planning, AI, and Operational Excellence - Softcover

Mishra, Aruj

9798170527137: Manufacturing & Operations Analytics for Beginners: A Practical Guide to Production Analytics, OEE, Quality, Lean Manufacturing, Maintenance, Capacity Planning, AI, and Operational Excellence

Softcover

ISBN 13: 9798170527137

Verlag: Independently published, 2026

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Von EUR 22,20

Turn factory data into better decisions — without becoming a data scientist.

Modern manufacturing generates more data than ever before. Production counts, downtime records, quality results, maintenance histories, machine sensors, labor hours, and ERP systems all contain valuable information. The challenge is knowing what to measure, how to analyze it, and what action to take.

Manufacturing & Operations Analytics for Beginners is a practical, plain-English guide for manufacturing professionals who want to use analytics to improve factory performance without needing advanced statistics, programming, or data-science experience.

Inside, you'll learn how to:

Measure factory performance using OEE, throughput, cycle time, takt time, yield, scrap, downtime, and capacity utilization
Diagnose why actual production differs from plan
Identify bottlenecks and constraints that limit output
Analyze downtime using Pareto and root-cause techniques
Measure quality using first-pass yield, process capability, SPC, and Six Sigma concepts
Apply Lean, value-stream mapping, takt time, line balancing, and continuous improvement analytics
Improve maintenance using MTBF, MTTR, equipment criticality, and predictive maintenance
Analyze labor productivity and manufacturing capacity
Understand MES, ERP, SCADA, PLC, CMMS, IoT, and Industry 4.0 data
Use AI and ChatGPT to support manufacturing analysis and decision-making
Understand digital twins, simulation, and smart-factory analytics
Build practical manufacturing dashboards in Excel

Every chapter follows a structured learning format with worked numerical examples, real-company business cases, practical exercises, common pitfalls, formulas, and key takeaways. The manuscript covers 25 chapters across production, quality, lean, maintenance, capacity, AI, Industry 4.0, and manufacturing dashboards.

Whether you're a production manager, manufacturing engineer, operations analyst, quality professional, maintenance manager, continuous-improvement specialist, MBA student, or aspiring plant leader, this book gives you the analytical vocabulary and practical frameworks needed to make better operational decisions.

You don't need to learn Python. You don't need advanced mathematics. You need to understand the numbers that run your factory.

Start turning manufacturing data into operational improvement.

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