Deliverables

Executive Summaries

Deliverable D1.2C
System Specification and Pre-Selection of Case Studies

In order to specify the requirements of the ConTemp system, it was essential to first determine the process conditions under which the system will be implemented in an industrial environment. The main objectives were to identify industrially relevant materials and to define the requirements as well as a specification catalogue for the ConTemp system. Within this task, the end users therefore defined workpiece materials which currently present a challenge to the manufacturing industry. These include hypereutectic aluminium alloys, titanium alloys and heat treatable steels. The academic partners then performed cutting experiments with these workpiece materials and measured the thermal and mechanical loads on the cutting tool during the machining process. The state of the art industrial cutting conditions for these difficult to machine materials were thus defined. The machining of these materials in the form of specific case studies, i.e. a real industrial part which is to be machined, will be undertaken in Work Package 5. The pre-selected case studies are the cutting of an aluminium alloy and steel widely applied in the automotive sector as well as the cutting of titanium alloy applied in the aeronautic and motorsport sectors. Potential exploitations are the manufacturing of automotive aluminium gearbox and engine parts, titanium aero-engine cases, disks and blades as well as hardened steel shafts, gears and suspension parts. More details on Case Studies are included in the deliverable D5.1 “Preliminary roadmaps and description of the end users selected case studies”.

Deliverable D2.2B
Simulation Model and Results for Heat Flow in the Cooling 

In order to begin designing and modelling the cooling structure, of the ConTemp internally cooled cutting tool; a value of the energy supplied to the tool during cutting was calculated. This value for the heat flux was then applied to simulation models for the subsequent designs of the cooling structure. Common features such as the overall size and shape of the cutting insert and inlet/out channels remain constant for all variations simulated; whereas the cooling structure was modified and simulated to achieve the best possible cooling effect. Using FEM (Finite Element Method) and CFD (Computational Fluid Dynamics) several alternate designs have been trialled before designs were chosen for the creation of the first prototypes in work package 3. Once a design for the physical structure of the tool was confirmed simulations of the working tool under different conditions were undertaken in order to establish the working envelope of the tool. This includes structural simulations to establish the strength of the tool under turning conditions, the use of different types of coolant and the effects of varying the coolant flow rate. The data produced by the simulations provides a cutting tip temperature and heat distribution, these results are subsequently used to produce the working prototype which is then used to validate the simulation models. As the design of the tooling and internal geometry evolves with each tool/geometry variation, new simulations are carried out; adding to the consortium’s pool of knowledge on internally cooled tooling. It is the purpose of deliverable 2.2 to chronicle this knowledge for use in the ConTemp project; in order to achieve the best possible design for the cutting tool and its associated internal cooling geometry. All the simulations included in this document are for use in the associated work packages WP3, WP4, WP5 and WP6. D2.2 will also be used as the basis for future deliverable D2.3 where optimisation iterations will be implemented to improve the tool performance which will in turn optimise the ConTemp tool system.

Deliverable D3.1B
Cooling System for the Test Benches

The cooling system has the function of supplying the inner-cooled cutting tool with cooling liquid. Thus specifications generated in task 2.1 (modelling of the cooling process by FEM and CFD methods) are used to design the cooling periphery. Several steps were undertaken to design a functional cooling system.

Deliverable D3.3.1B
Tool Manufacturing

The architecture of the first inner-cooled ConTemp tool is described in this report. A cutting insert, a tool head and a tool head holder were developed and joined together to become the first prototype. During the development technical challenges occur and the consortium solved them successfully. Key challenges in our case were a leak-proof tool, low manufacturing costs and tool durability.
The aim of work package 5 is to test and optimise, in laboratory conditions, the cutting tools, cooling system and self-learning control for application in the end user’s “case studies”. A description of relevant applications for the different industrial sectors has already been undertaken in deliverable D1.2 and some preliminary “case studies” have been proposed to the Consortium and approved during the Six Months Meeting. The objective of this deliverable is mainly to provide preliminary roadmaps for the applications and to describe in detail the selected case studies.

Deliverable D4.1B
Control System Structure

This document describes the control system structure to be used for controlling the temperature of internally cooled tools being developed within the ConTemp project. The structure proposed is the result of preparatory work and the views and requirements of ConTemp partners.
Essentially the control system can be used to monitor tool temperature when the coolant flow rate is fixed or to control tool temperature by adjusting the coolant flow rate when it is variable. The control system uses an Artificial Neural Network (ANN) to define a relationship between machining parameters and tool temperature that can be used as criteria to prevent the tool from overheating, determine whether the tool is worn or enable optimum machining conditions to be found. A means of training the ANN and acquiring the experimental data necessary for training is included as an integral part of the control system. The training function enables the control system to be adapted to different tool designs and workpiece materials.
The benefit of the control system is a reduced risk of tool failure from overheating, improved machining productivity and/or a lower rate of  tool wear from knowing or controlling tool operating temperature.

Deliverable D4.3A
Software for Interfacing with Standard CNC Machine Tool Controllers for Optimising a Defined Cutting Process and Controlling the Temperature of Internally Cooled Tools

This document describes the software to be used for controlling the temperature of internally cooled tools being developed as part of the ConTemp project. The document complements Deliverable 4.1 that describes the software structure and system architecture.
Essentially the control system can be used to monitor tool temperature when coolant flow rate is fixed or control tool temperature by adjusting coolant flow rate when it is variable. The control system uses an Artificial Neural Network (ANN)  to define a relationship between machining parameters and tool temperature that can be used as a criterion to prevent the tool from overheating, determine whether the tool is worn or enable optimum machining conditions to be found. A means of training the ANN and acquiring the experimental data necessary for training is included as an integral part of the control system described here.
This version of the software is intended for use in an R&D environment and allows the user some freedom to design and train ANN’s for different tool designs work piece materials and machining conditions. When experimental data is available from WP3 a second version of the program will be developed for which the ANN design function will be eliminated and the training function simplified or also eliminated.Mid Term Report

 

Deliverable D7.1B
Dissemination Plan

The main objective of the Dissemination Plan is to provide a strategy and guideline for the dissemination of project results. During the first period of the project most dissemination activities were focused on creating public awareness of the project and it's overall objectives. The success of these activities is visible in several expressions of interest in the project results by external experts. In the second half of the project the dissemination activities will become more specific as results of the project are achieved. First scientific papers on thermal management in cutting tools and self-learning control are being published. For the co-ordination and planning of dissemination activities, a dissemination database was created.
Additionally the results of the Exploitation Strategy Seminar and the following discussion on exploitable results and IPR are reported in this deliverable. However, exploitation and IPR are subject to ongoing discussion in the consortium and the reported status can only represent the interim status.

 

Mid Term Report

Cooling lubrication is widely applied in cutting processes. However, conventional flood cooling causes environmental and health risks and high costs for coolant processing and disposal. Within the ConTemp project an internally cooled cutting tool in combination with a self-learning control is being developed. This innovative system reacts to changing process conditions and keeps the tool temperature constant. With a constant temperature gradient from the hot tool tip to the coolant channels in the cutting tool, thermal shock damage is minimised, thus achieving a better tool life. A closed coolant circuit avoids the release of coolant into the environment and at the same time the coolant is not contaminated by the process, simplifying supply and disposal.
In the first reporting period basic experiments were carried out in order to determine the heat distribution and other characteristic process data that are necessary for the design of the internally cooled tool. Simulations and bench top tests with internal cooling structures in cutting tools increase the process understanding and support the design of the cooling structures. Based on the process conditions determined in the basic experiments, CFD and FEM simulations of the cooling process were undertaken. Several manufacturing options and procedures and their advantages and disadvantages were identified and discussed. Based on an Artificial Neural Network (ANN), the control system structure was developed. First bench top tests with the self-learning algorithm demonstrated an excellent concurrence between predicted and measured temperatures, the deviation is better than 4°C for tool temperatures higher than 172°C with only 69 data entries used for training.
The first tool prototypes have been manufactured and will be applied in first tests under laboratory conditions for further optimisation. Three groups of materials have been identified to be used for the cutting tests and will be used to test the efficiency of the system in case studies later in the project: AlSi7 as a widely used material in the automotive industry, TiAl6V4 (the machining of which depends very much on efficient cooling) as a representative of applications for the automotive and aerospace sector and steel 38MnV as a common material in mechanical engineering.