The Model of Probe Configuration and Setup Planning for Inspection of PMPs Based on GA

Author(s):  
Slavenko M. Stojadinović ◽  
Vidosav D. Majstorović
Keyword(s):  
Author(s):  
Satyandra K. Gupta

Abstract Sheet metal bending press-brakes can be setup to produce more than one type of parts without requiring a setup change. To exploit this flexibility, we need setup planning techniques to generate press-brake setups that can be shared among many different parts. In this paper, we describe an algorithm which partitions a given set of parts into setup compatible part families which can be produced on the same setup. Our algorithm is based on a two step approach. The first step is to identify setup constraints for each individual part. The second step is to form setup-compatible part families based on the compatibility of setup constraints. We expect that by producing many different types of parts on the same setup, we can significantly reduce the required number of setups and enable cost effective small batch manufacturing.


Author(s):  
T. Srikanth Reddy ◽  
M. S. Shunmugam

An automated planning system extracts data from design models and processes it efficiently for transfer to manufacturing activity. Researchers have used face adjacency graphs and volume decomposition approaches which make the feature recognition complex and give rise to multiple interpretations. The present work recognizes the features in prismatic parts considering Attributed Adjacency Matrix (AAM) for the faces of delta volume that lie on rawstock faces. Conceptually, intermediate shape of the workpiece is treated as rawstock for the next stage and tool approach direction is used to recognize minimum, yet practically feasible, set of feature interpretations. Edge-features like fillets/undercuts and rounded/chamfer edges are also recognized using a new concept of Attributed Connectivity Matrix (ACM). In the first module, STEP AP-203 format of a model is taken as the geometric data input. Datum information is extracted from Geometric Dimension and Tolerance (GD&T) data. The second module uses features and datum information to arrive at setup planning and operation sequencing on the basis of different criteria and priority rules.


2005 ◽  
Vol 128 (1) ◽  
pp. 220-227 ◽  
Author(s):  
Nuo Xu ◽  
Samuel H. Huang

Setup planning is an intermediate phase of process planning, and automating setup planning constitutes a critical component of computer-aided process planning. The common absence of a clearly defined optimality of setup plans has been a major obstacle to converting automatic setup planning research progress into real advancement in practice. The optimality of a setup plan is a multiple attributes problem associated with uncertainties, and human interaction is vital in clarifying the optimality structure in a dynamic setup planning environment. In this paper, a quantitative setup plan evaluation system driven by multiple-attributes utility analysis coupled with manufacturing error simulation is proposed to serve three purposes: (1) to clarify what is optimality of setup plans, (2) to provide a systematic method of evaluating setup plan alternatives quantitatively, and (3) to incorporate in existing automatic setup planning systems a human interface to fulfill their potential values.


Sign in / Sign up

Export Citation Format

Share Document