Title :
An estimation method of processes capacity based on quality control oriented to small batch customization
Author :
Li Hu ; Yang Jianyu ; Wu Wenzheng ; Wang Wanshan
Author_Institution :
Sch. of Mech. Eng. & Autom., Northeastern Univ., Shenyang, China
Abstract :
The process capacity oriented to small batch customization should be analyzed and estimated, which is the essential precondition for factory to make decision whether to accept a piece of manufacturing order form. One kind of model based on quality driven for the process capacity estimation was provided to solve the critical problem. And the network service system of process capacity estimation was established, by making full use of quality function analysis (QFD), similar procedure query and rough set theory combined with the character parameters such as work-part size tolerance, surface roughness, manufacturing time, cost and etc. Furthermore, some key enabling technologies were investigated in detail, including quality control technology oriented low volume customization and process capacity analysis technology based on rough set (RS) theory. The prototype system of process capacity estimation based on quality control oriented to small batch customization was developed, which provides an effective method for the factory decision when they face a piece of unfamiliar order form.
Keywords :
batch processing (industrial); quality control; quality function deployment; rough set theory; estimation method; processes capacity; quality control; quality function analysis; rough set theory; similar procedure query; small batch customization; surface roughness; work-part size tolerance; Enterprise resource planning; Machining; Manufacturing automation; Manufacturing processes; Process control; Production facilities; Quality control; Set theory; Statistical analysis; Statistics; Customization; Process Capacity; Quality Control; Rough Sets; Small Batch;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5191851