Hands on Tutorial for AI implementation in Manufacturing -- Part 1

Here is first part of the guide on implementing ML and AI solutions into manufacturing company. Following guide can be applied to all types of factories and products, which generate structured data preferable stored in the databases. It will work best for high volume products that get tested and have measurable output properties e.g.: resistance, latency, frequency, torque, power, energy consumption, pressure, speed, vibration, strength, clearance, efficiency, timing, thrust and all possible numeric or categorical properties that can be measured and are important for final characteristic and production yield. In terms of name for that system it could be called: Automated Production Optimisation or simply Digital Twin of Process and/or product. As you can imagine following examples suggest it can be used for things such as: PCB, Jet and rocket engines, gearboxes, combustion engines and all other mechanical, electronic, pneumatic and hydraulic devices.