The term "predictive capacity planning" is particularly important in the areas of Industry and Factory 4.0, automation and artificial intelligence. It describes a method used by companies and production operations to optimise the planning of their resources such as machines, personnel or materials in advance. The aim is to recognise bottlenecks or overcapacity at an early stage and thus save time, costs and energy.
So instead of just reacting when problems occur, predictive capacity planning relies on data analysis and intelligent forecasts. Modern software analyses historical production data, current orders and trends to predict when and where which capacities are needed.
An illustrative example: In a car factory, predictive capacity planning is used to precisely calculate the coming months. The software recognises that more electric vehicles will need to be built in eight weeks' time. It suggests ordering more batteries in good time and adjusting employee shifts. This keeps production running smoothly and the company remains competitive.
Forward-looking capacity planning helps to conserve resources, reduce costs and respond quickly to fluctuating demand - a clear advantage in the digital age.
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