TY - JOUR

T1 - Condition-based tool management for small batch production

AU - Denkena, Berend

AU - Krüger, Max

AU - Schmidt, Justin

PY - 2014/6/6

Y1 - 2014/6/6

N2 - This paper presents a novel tool management concept for cutting processes which integrates tool relevant information, such as distribution data, tool orders, tool condition, and allocation data, within a centralized information cycle. The developed tool management approach uses decentralized identification and storage technologies, enabling an autonomous cooperation of tools and machine tools within a production. The first part of the paper is focused on the assessment of tool condition in a flexible job shop production. A tool wear monitoring system based on cutting force coefficients is developed and demonstrated by an exemplary milling operation. Thereby, it is shown that cutting force coefficients are suitable for wear monitoring and prediction, even for varying cutting conditions. For the online assessment of the current tool condition and for the prediction of residual tool life, an empirical tool wear model is demonstrated. This is applied to a novel condition-based tool management strategy which enables the optimum exploitation of the life time and performance of the cutting tool. The developed condition-based tool management concept is finally demonstrated by a software demonstrator.

AB - This paper presents a novel tool management concept for cutting processes which integrates tool relevant information, such as distribution data, tool orders, tool condition, and allocation data, within a centralized information cycle. The developed tool management approach uses decentralized identification and storage technologies, enabling an autonomous cooperation of tools and machine tools within a production. The first part of the paper is focused on the assessment of tool condition in a flexible job shop production. A tool wear monitoring system based on cutting force coefficients is developed and demonstrated by an exemplary milling operation. Thereby, it is shown that cutting force coefficients are suitable for wear monitoring and prediction, even for varying cutting conditions. For the online assessment of the current tool condition and for the prediction of residual tool life, an empirical tool wear model is demonstrated. This is applied to a novel condition-based tool management strategy which enables the optimum exploitation of the life time and performance of the cutting tool. The developed condition-based tool management concept is finally demonstrated by a software demonstrator.

KW - Cutting process

KW - Monitoring

KW - Small batch production

KW - Tool management

KW - Tool wear

UR - http://www.scopus.com/inward/record.url?scp=84906312818&partnerID=8YFLogxK

U2 - 10.1007/s00170-014-6013-2

DO - 10.1007/s00170-014-6013-2

M3 - Article

AN - SCOPUS:84906312818

VL - 74

SP - 471

EP - 480

JO - International Journal of Advanced Manufacturing Technology

JF - International Journal of Advanced Manufacturing Technology

SN - 0268-3768

IS - 1-4

ER -