Innovative Production Machines and Systems Conference - Advanced Production Machines and Systems

Welcome

Brousseau — Thu, 05 Jul 2007 09:20:31 +0100

Welcome to the Advanced Production Machines and Systems session of the IPROMS2007 conference.

My name is Emmanuel Brousseau and I am here to co-chair this session, for which we have a very "tasty" menu on offer.

In particular, you will find two papers on condition monitoring that have been prepared by our Spanish and French colleagues. Another paper from Germany presents an new concept for the manufacturing of medical products. We also have a British contribution that describes results in the characterisation of different parallel kinematic machine configurations. Finally, you will also find some results of a European collaboration that took place witin the framwork of the EC project HYMM (Advanced Hybrid Mechatronic Materials for ultra precise and high performance machining systems design).

An innovative device for the manufacture of disprosable medical- and healthcare products

Rolshofen — Fri, 22 Jun 2007 14:17:48 +0100

Competitive manufacturing of medical and healthcare products requires high production speed and high flexibility for
easy size changeover and future product generation. Thanks to the combination of an inertia-reduced design and a
flexibel servo single drive concept the presented innovative device fulfils above mentioned requirements.

Monitoring of drilling for burr detection using Machine Learning techniques

cargelich — Fri, 22 Jun 2007 14:17:47 +0100

Developing a monitoring control system for burr formation during aluminium, Al 7075-T6, drilling in order to eliminate or reduce a non-productive operation; deburring. Monitoring system based on internal signal from spindle torque capturing, to detect non desired burr formation. 10 variables were analysed as burr-related (5 cutting conditions and 5 torque magnitudes), applying Hill-Climbing for attribute selection they turned out to be 5 with an important influence on burr formation (2 cutting conditions and 3 torque magnitudes). A data base was built and later on analysed by Machine Learning in order to extract the necessary information to develop an algorithm able to detect whether the burr is over aeronautical limits or not.

Higher order statistics estimation of the modeling error for chatter monitoring

charbonnaud — Fri, 22 Jun 2007 14:17:47 +0100

This paper proposes a design method for chatter monitoring based on the fourth order statistics estimation applied to the modelling error. Usually, a test of hypothesis is built on an a priori knowledge of the statistical distribution. The frequency function is often assumed Gaussian. In the case of machining process without chatter, the Gaussian assumption is not valid. Consequently, the proposal of an adaptive estimation of the fourth cumulant on a sliding window is introduced for machining process monitoring with possible chatters. The modelling error of the cutting force is the difference between the output of nonlinear model of cutting force and a real force estimation taking into account the stiffness of the sensor.

Computation and Analysis of dexterous workspace in PKMs

azfar — Fri, 22 Jun 2007 14:17:47 +0100

The emerging interest in the use of parallel kinematic machines (PKM) for machining applications requires extensive research to address clear determination of the workspace, dexterity and stiffness issues depending on the inherent design concepts. This paper deals with the issues regarding the use of PKM as machine tools. Comparison criteria are set and a quantitative analysis is made to compare the characteristics of serial and parallel kinematics with respect to their potential suitability in building micro machines. Different configurations of PKM are discussed with the mobility, workspace and stiffness characteristics as examples.

Advanced Hybrid Mechatronic Materials for Ultra Precise and High Performance Machining Systems Design

Meo — Fri, 22 Jun 2007 14:17:46 +0100

The machinery field is traditionally a sector poor in term of structural material solutions, but where machine performances are increasing so sharply that new materials are urgently required. Getting more intelligent and integrated structural solutions is essential to really introduce enormous benefits in machine tool design and development. The future technological challenge will be the availability of a new class of smart composite materials whose elasto-dynamic response can be adapted in real time in order to significantly enhance the performance of structural and mechanical systems like machine tools under a wide range of operating conditions.