Spring and autumn pajamas women's long sleeve ice silk thin style Korean fashion sweet two-piece set of simulation silk loose home clothes

[wholesale] ¥60.00RMB

In Stock:4

Product Details

Product Attributes：Fabric Name: imitation silk product category: suit style: luxury noble functions: comfort, ventilation, bathing, elasticity, home, leisure, cool Externally wearable source category: whether OEM is supported in stock: whether OEM is supported: supported item No.: 2793-2 main fabric component: polyester fiber (polyester) main fabric component content: 95 style: suit origin: Taizhou thickness: thin style applicable gender: female applicable crowd category: Women's weaving method: woven collar type: lapel collar shape: V-neck sleeve length: long sleeve pants length: long pants error range: 1-3cm applicable seasons: spring, autumn Foreign trade in summer: no inventory: Yes inventory type: whole order production cycle: 15 OEM objects: Taobao sellers, external processing, tmall brand main sales channels: brand stores, individual entities, Taobao, tmall, domestic shopping malls, supermarkets revision: the minimum amount of OEM that can be revised: 300 imported: no color: black, wine red, pink, off white, ginger size: XL, l M whether it is a special supply source for cross-border export: no applicable age group: Youth (18-40 years old) applicable scene: outdoor, hotel baths, wedding studios, home listing time: 2022 fabric thickness (g weight): thin (101-120 g / m2);This company provided the product of Production and processing:(Taizhou Jiaojiang lanzhimi garment factory);The main business model of this enterprise is Production and processing.This enterprise has registered with Alibaba and applied for chengchengtong. Now, it has the current level of chengchengtong：AA;Company is located in Taizhou City,Zhejiang,China ;Registered Capital：0.0ten thousand ;Company Website：https://shop38758p3mv6461.1688.com ;You can view more detailed information through this product website ：https://detail.1688.com/offer/665056410376.html

Recommends