A winding condition generating apparatus includes: an input unit; an output unit; and a condition calculation unit. A winding condition calculation unit includes a learning model created by machine learning using a combination of a winding parameter and a winding condition in producing a wound web that satisfies a target winding quality as training data, and calculates a winding condition of a new wound web using the learning model, from a winding parameter of a new wound web input through the input unit. The output unit outputs the winding condition. The winding parameter includes a web width, a web transport velocity, and a web winding length. The winding condition includes a tension of the web at the start of winding and a tension of the web at the end of winding.

A winding condition generating apparatus includes: an input unit; an output unit; and a condition calculation unit. A winding condition calculation unit includes a learning model created by machine learning using a combination of a winding parameter and a winding condition in producing a wound web that satisfies a target winding quality as training data, and calculates a winding condition of a new wound web using the learning model, from a winding parameter of a new wound web input through the input unit. The output unit outputs the winding condition. The winding parameter includes a web width, a web transport velocity, and a web winding length. The winding condition includes a tension of the web at the start of winding and a tension of the web at the end of winding.