Use of graphic displays of process capability data to facilitate producibility analyses

To specify realistic tolerances and ensure acceptable product yields, a product development team must take into account the current process capability of the factory. Using historical process capability data in product development is frequently discussed in academic and industry literature. However, while many organizations have databases, the use of historical data in design is limited. This paper addresses the technical challenges of implementing a producibility analysis tool. First, a description of how data is currently collected and recorded is given. Second, the infeasibility of a “just-press-a-button” system for checking producibility is described. Finally, a new paradigm for data access is proposed, implemented in software, and tested on data used by industry.

[1]  Carl D. Sorensen,et al.  A general approach for robust optimal design , 1993 .

[2]  Anna C. Thornton,et al.  Process Capability Database Usage In Industry: Myth vs. Reality , 1999 .

[3]  Nanxin Wang,et al.  Automatic Generation of Tolerance Chains from Mating Relations Represented in Assembly Models , 1993 .

[4]  Ben Shneiderman,et al.  The alphaslider: a compact and rapid selector , 1994, CHI Conference Companion.

[5]  Kevin Otto,et al.  SIMULTANEOUS ENGINEERING OF QUALITY THROUGH INTEGRATED MODELING , 1998 .

[6]  Ben Shneiderman,et al.  The alphaslider: a compact and rapid selector , 1994, CHI Conference Companion.

[7]  J. C. Naish Process capability modelling in an integrated concurrent engineering system — the feature-oriented capability module , 1996 .

[8]  E. Degarmo Materials and Processes in Manufacturing , 1974 .

[9]  Daniel D. Frey,et al.  Evaluating Process Capability During the Design of Manufacturing Systems , 2000 .

[10]  T. C. Woo,et al.  Tolerance Analysis for Sheet Metal Assemblies , 1996 .

[11]  M. Perzyk,et al.  Selection of manufacturing process in mechanical design , 1998 .

[12]  Jr. Allen B. Tucker,et al.  The Computer Science and Engineering Handbook , 1997 .

[13]  Kosuke Ishii,et al.  QUANTIFYING DESIGN AND MANUFACTURING ROBUSTNESS THROUGH STOCHASTIC OPTIMIZATION TECHNIQUES , 1996 .

[14]  Spencer P. Magleby,et al.  Generalized 3-D tolerance analysis of mechanical assemblies with small kinematic adjustments , 1998 .

[15]  Kristin L. Wood,et al.  Functional tolerancing: A design for manufacturing methodology , 1996 .

[16]  Spencer P. Magleby,et al.  Including Geometric Feature Variations in Tolerance Analysis of Mechanical Assemblies , 1996 .

[17]  Wei-Hsin Huang,et al.  Study of an assembly tolerance allocation model based on Monte Carlo simulation , 1997 .

[18]  Moon Jung Chung,et al.  Managing engineering data for complex products , 1995 .

[19]  Kwun-Lon Ting,et al.  Performance Quality and Tolerance Sensitivity of Mechanisms , 1996 .

[20]  Woodie C. Flowers,et al.  Metrics for the design of visual displays of information , 1999 .

[21]  Alice M. Agogino,et al.  Formal solution of N-type robust parameter design problems with stochastic noise factors , 1994 .

[22]  R. I. Campbell,et al.  Creating a database of rapid prototyping system capabilities , 1996 .

[23]  Ben Shneiderman,et al.  Designing the User Interface: Strategies for Effective Human-Computer Interaction , 1998 .

[24]  Greg Nagler Sustaining competitive advantage in product development : a DFM tool for printed circuit assembly , 1996 .

[25]  Ben Shneiderman,et al.  Visual information seeking: tight coupling of dynamic query filters with starfield displays , 1994, CHI '94.

[26]  Madara Ogot,et al.  Dimensional Tolerance Allocation of Stochastic Dynamic Mechanical Systems Through Performance and Sensitivity Analysis , 1993 .

[27]  Chun Zhang,et al.  Robust design of assembly and machining tolerance allocations , 1998 .