Service provider (SP) know-hows are essential in machining service (MS) encapsulation in the cloud. However, since the acquisition of the know-hows for complex parts machining requires investing considerable manpower and resources in R&D, this kind of machining know-hows is usually considered as one of the core competences of the SP who makes them unshareable. Targeting the problem, this paper presents a new cloud manufacturing (CM) architecture in which MSs are encapsulated within each SP with standardized machining task description strategies (SMTDS). Only the capability information about what the SP can do is provided to the cloud. During service matching, SMTDS is also applied for user request formulation to improve the matching efficiency and quality. For complex parts in large size, high machining requirements, high value, short delivery cycle, and complex structures, e.g., aircraft structural parts, unacceptable machining quality or delivery delay may cause a much greater loss not only in economy. In the proposed CM architecture, to guarantee the feasibility of the MSs for complex structural parts, machining operations for the user preferred services could be generated by mapping the corresponding typical machining plans (TMP) to the part based on the dynamic feature concept to support accurate evaluations of the MSs. The machining of an aircraft structural part is then applied as a test user request to demonstrate how the proposed method works for finding MS for complex parts.
A Cloud Manufacturing Architecture for Complex Parts Machining
Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received October 13, 2014; final manuscript received February 16, 2015; published online September 9, 2015. Assoc. Editor: Xun Xu.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Liu, X., Li, Y., and Wang, L. (September 9, 2015). "A Cloud Manufacturing Architecture for Complex Parts Machining." ASME. J. Manuf. Sci. Eng. December 2015; 137(6): 061009. https://doi.org/10.1115/1.4029856
Download citation file:
- Ris (Zotero)
- Reference Manager