CBIMS: Case-based impeller machining strategy support system

  • Authors:

  • Min-Ho Cho;Dong-Won Kim;Chan-Gie Lee;Eun-Young Heo;Jae-Won Ha;F. Frank Chen

  • Affiliations:

  • Department of Industrial & Information Systems Engineering, Chonbuk National University, Jeonju, South Korea;Department of Industrial & Information Systems Engineering, Chonbuk National University, Jeonju, South Korea;Department of Industrial & Information Systems Engineering, Chonbuk National University, Jeonju, South Korea;Department of Industrial & Information Systems Engineering, Chonbuk National University, Jeonju, South Korea;Department of Industrial & Information Systems Engineering, Chonbuk National University, Jeonju, South Korea;Department of Mechanical Engineering & Center for Advanced Manufacturing & Lean Systems, University of Texas at San Antonio, TX 78249, USA

  • Venue:
  • Robotics and Computer-Integrated Manufacturing
  • Year:
  • 2009

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Abstract

Impeller machining strategies cannot be easily formalized due to the complex, overlapping and twisted shapes that form impeller blades. Skilful machining process planners may generate appropriate machining strategies based on their experiences and previous machining data. However, in practice, most shop floor data for impeller machining is not well-structured and it cannot be used effectively by process planners to produce the required machining strategies and process plans. This paper presents the development of a case-based impeller machining strategy support system (CBIMS) that employs case-based reasoning (CBR) to obtain an efficient machining strategy for an impeller by using the existing machining strategies from the shop floor. The CBIMS generates impeller machining strategies through a stepwise reasoning process considering the similarities of the blade shapes and machining regions between existing impellers and a new one. The system can provide a process planner with machining strategies such as tool specifications, machining area partitioning, and the machining parameters including feed rate, depth of cut, RPM and machining tolerance. A case study is provided to demonstrate that the CBIMS can generate useful machining strategies while ensuring that it can be effectively used to support the process planner.