Abstract: A coil electronic component that includes a body and a coil at least partially embedded in the body, and that has a length L1 in a first direction and a margin in the first direction. The margin in the first direction is an average distance from the coil to a surface of the body intersecting the first direction, and is greater than 0% and less than or equal to 7% of the length L1 in the first direction.

Abstract: A coil electronic component includes a main body including a magnetic material, a wound coil of which at least a part is embedded in the main body, and a first and second lead terminals connected to both end portions of the wound coil, respectively, where in a cross-section perpendicular to a width direction of the main body, a first distance D1, which is a distance between an end surface of the main body in a length direction and an outermost turn coil of the wound coil, measured along the length direction of the main body at a half point of a thickness T1 of the main body, is greater than or equal to 2% and smaller than or equal to 7.5% of a length L1 of the main body in the length direction.

Abstract: A coil component includes a body, a support member disposed within the body, a coil disposed on at least one of a first surface and a second surface of the support member opposing each other, and an external electrode disposed on the body and connected to the coil, wherein the support member includes a first layer and a second layer respectively including polyimide, and an average surface roughness of the surface of the support member on which the coil is disposed is 0.1 to 0.5 ?m in Ra value.

Abstract: The present disclosure relates to a method of deriving quality improvement requirements. The method according to some embodiments may include receiving a plurality of evaluation information for a first product from an evaluation information database, inputting the plurality of evaluation information into a key phrase extraction model and determining key phrases for the plurality of evaluation information based on an output of the key phrase extraction model, grouping some of the key phrases for the plurality of evaluation information into multiple groups and storing information on each of the multiple groups in a memory, ranking the key phrases included in each of the multiple groups and storing information associated with the ranks of the key phrases included in each of the multiple groups in the memory and determining top n key phrases from each of the multiple groups as quality improvement requirements.