The key concept of the identification procedure in this paper is to find a feature of the measured random response (sound pressure) that can be used to discriminate between stable and unstable process-machine interaction (PMI) in milling. The dynamic condition of the machining system is represented by the operational dynamic parameters (ODP), which refer to the contribution of the structural vibration modes and process vibration modes resulting during machining system operation. It is shown that the sound pressure level acquired by a microphone, located in the machine’s working area, is able to follow rapid changes in the process dynamics and therefore may be used as input in the recursive estimation scheme. The primary contribution of this paper lies within the formulation and implementation of recursive parametric models for the study of the real-time dynamics of a face milling operation PMI. A comparison between the experimental, simulated, and identified results is outlined.

In today’s highly competitive environment there is a need for fast and accurate methods to assess the capability of manufacturing units. The traditional estimation of the dynamic properties of machine tools is usually time consuming and assumes time-invariant properties. This paper introduces a method for analyzing machine tool structure dynamic properties by recursive estimation of modal and operational parameters. A contact-less excitation system and a specially designed tool were employed to enable spindle speed sweep. The primary contribution of this paper lies within the formulation and implementation of recursive parametric models for tracking the time-varying dynamic properties of a machine tool structure.

Models of manufacturing resources as machine tools, fixtures and cutting tools contribute to efficient and simplified operation planning. With operation planning domain concept, defined in ontology and used during modelling of coherent ISO 10303-214 conforming data models of manufacturing resources, stable implementation solutions are ensured while capable of representing current manufacturing resources and resources developed in the future. Using similarities between different types of resources, a unified modelling approach may be applied independent of the type of object. Information classes as interfaces, kinematics, performance and behavior are identified and related to corresponding construct of the standardized product generic schema. With the common representation of shared information between applications domains as operation planning, maintenance and factory layout design, presented result contributes to set the basis for a digital factory used in virtual manufacturing to continuously improve the production system.

The aim of this paper is to introduce a novel methodology, based on a finite element (FE) computation engine for validating of real-time identification schemes applied in machining. FE modelling of the milling process has the purpose of being accountable for a thorough validation of the parametric identification approach, and of providing a good physical insight into the phenomena investigated. The system considered here has a lower number of degree-of-freedoms which permits a thorough analysis. However, when taking into account the system’s nonlinear and time-varying nature, it is clear that the results are far from being trivial. Therefore, the analysis of the milling process, taking into account nonlinearities restricting the growth of response amplitudes in the case of chatter-type instability, provides some intrinsic information of the basic features on the system that might be of both fundamental interest and practical use.