An approach of using primitive feature analysis in manufacturability analysis systems for micro-milling/drilling

Manufacturability analysis systems (MASs) have been developed to enable the evaluation of easy to manufacture parts during the design stage, enabling the reduction of costs and time to market of the designed products. The feature analysis approach is one of the methods used to gather information from the proposed design for manufacturability assessment purposes. The objective of this paper is to explore a new technique - primitive features analysis (PFA) - in assessing the manufacturability of proposed designs and to demonstrate further its implementation in developed MAS explicitly for a custom-built miniature 4-axis machine tool (MMT). In the introduction to this paper, the definition, methodology and importance of MAS are discussed along with their relations to feature analysis. PFA analyses the defined primitive features (e.g. box, sphere, cylinder, cone, prism) of the proposed design based on their positions, interactions and geometrical details. The analysis is supported by a database containing rules and constraints that are specific to micro-machining processes in MMT; these account for primitive features orientations/interactions as well as machining conditions and workpiece materials. First, an index is evaluated for each primitive feature to reflect its manufacturability while taking into account key quality output measures (e.g. tolerance, surface roughness). Then, the overall manufacturability index is calculated taking into consideration the possible interactions/constraints among neighbouring primitive features of the desired component. The PFA technique was implemented within a unique algorithm consisting of data input mechanism, initial assessment (IA), single feature analysis (SFA) and coupled feature analysis (CFA) by use of Visual Basic.NET. The new MAS is able to illustrate the analysis of the PFA technique and it provides outputs such as redesign suggestions and manufacturability indices. Finally, the paper discusses the advantages, possible limitations of this approach followed by suggestions for future developments.