Mihael Junkar

Simulation of abrasive water jet cutting process: Part 1. Unit event approach

Abrasive water jet (AWJ) machined surfaces exhibit the texture typical of machining with high energy density beam processing technologies. It has a superior surface quality in the upper region and rough surface in the lower zone with pronounced texture marks called striations. The nature of the mechanisms involved in the domain of AWJ machining is still not well understood but is essential for AWJ control improvement. In this paper, the development of an AWJ machining simulation is reported on. It is based on an AWJ process unit event, which in this case represents the impact of a particular abrasive grain. The geometrical characteristics of the unit event are measured on a physical model of the AWJ process. The measured dependences and the proposed model relations are then implemented in the AWJ machining process simulation. The obtained results are in good agreement in the engraving regime of AWJ machining. To expand the validity of the simulation further, a cellular automata approach is explored in the second part of the paper.

Simulation of abrasive water jet cutting process: Part 2. Cellular automata approach

A new two-dimensional cellular automata (CA) model for the simulation of the abrasive water jet (AWJ) cutting process is presented. The CA calculates the shape of the cutting front, which can be used as an estimation of the surface quality. The cutting front is formed based on material removal rules and AWJ propagation rules. The material removal rule calculates when a particular part of the material will be removed with regard to the energy of AWJ. The AWJ propagation rule calculates the distribution of AWJ energy through CA by using a weighted average. The modelling with CA also provides a visual narrative of the moving of the cutting front, which is hard to observe in real process. The algorithm is fast and has been successfully tested in comparison to cutting fronts obtained with cutting experiments of aluminium alloy.

Identifying the grinding process by means of inductive machine learning

Abstract Grinding is one of the most complex and unpredictable metal-working processes. Although the results of recent research clarify the underlying physical and chemical phenomena to a certain extent, the prediction of the process evolution remains hard. Employing the machine learning methodology, we have explored the identification of plunge grinding via vibration signals generated by the grinding wheel and the workpiece. A two-stage experiment has been carried out, comprising (1) grinding, signal detection, extraction of spectral attributes and assessment of performance classes, and (2) learning the process evolution from the extracted data. Within the learning stage, a decision tree has been synthetized, predicting the grinding wheel performance from the attribute values. Two important aspects of the machine learning approach to the grinding process identification have been demonstrated by the experiment. First, the synthesized knowledge enables new insight in the problem domain, and second, it provides a ground for an efficient control algorithm.

Using inductive machine learning to support decision making in machining processes

Abstract In spite of their practical success, knowledge-based systems still suffer from considerable limitations. Specialized for problem solving in a narrow domain, most systems possess very limited knowledge and are rather inflexible. Moreover, building a knowledge base is the most critical phase in developing an expert system. In overcoming these limitations, existing machine learning techniques, capable of deriving concepts from data, can be effectively applied. This work focuses on machine learning from examples and its potential in discovering knowledge hidden in technological databases. Practically oriented studies of automating two-decision procedures related to machining processes are presented: classification of dielectric fluids used in electrical discharge machining, and tool selection in an industrial grinding process. The results show the approach is beneficial in preventing poor process performance and improving product quality. It also allows for better understanding of the processes at the shop floor level, and advances decision making at the technology planning level.

Percentage of harmful discharges for surface current density monitoring in electrical discharge machining process

Abstract Electrical discharge machining (EDM) is performed in the gap between the workpiece (usually the anode) and the electrode (usually the cathode). The gap is filled with a dielectric and the pulses generated by a special generator cause an electrical breakdown in the gap. A breakdown discharge occurs which removes material from the workpiece. The EDM process has been used for more than 50 years, but the influence of the surface current density on the process stability is not well understood. The surface current density is very important in the case of the machining of rough surfaces where the highest material removal rate (MRR) is preferred. For a given eroding surface there exists an optimal electrical current at which the highest MRR is achieved. It is reported in the literature that the percentage of the discharges that are harmful to the EDM process depends on the surface current density in the gap. Thus, experiments were performed to find out the possibility of using the percentage of harmful discharges to monitor the surface current density of the EDM process.

Machining parameters selection for varying surface in EDM

To achieve high removal rate and low electrode wear when roughing by the sinking electrical discharge machining process (EDM), appropriate average surface power density is required in the gap between the workpiece and the electrode. Since machining surface varies with the depth of machining, the rough machining parameters have to be selected on-line to obtain appropriate average surface power density in the gap. In this paper, a system for on-line selection of the machining parameters according to the given machining surface is presented. The selection of the machining parameters is based on the acquisition of only one process attribute, i.e. the percentage of short-circuit discharges, which is significant improvement comparing to known systems.

Experimental and Numerical Study of the Tool in Water Jet Incremental Sheet Metal Forming

Incremental Sheet Metal Forming(ISMF) is a very flexible technology for fast prototyping and small batch production of sheet metal parts. This contribution deals with an innovative variant of ISMF, where instead of a rigid tool a Water Jet(WJ) is used as the main tool. Such a process can be addressed as Water Jet Incremental Sheet Metal Forming(WJISMF). The main aim of this paper is to present the technological window for WJISMF and characterise the attributes of the WJ used as the main tool. A Finite Element Analysis(FEA) simulation was developed to simulate the impact of a WJ on a rigid surface. The FEA simulation was experimentally validated by measuring the surface pressure at the interface between the WJ and the rigid surface. Numerical results are in good agreement with those obtained experimentally.

A novel approach to DFM in toolmaking: a case study

A novel approach to avoid the knowledge gap between design and production is presented in this paper. The main idea is to build a system in the form of a computer program whose core is the manufacturing expert systems to be used by the product designer. The system reveals critical features of the designed product from the manufacturing point of view and points them out to the product designer. The product designer can decide whether to change the critical part of the product or not. The system presented in this paper is prepared for the toolmaking, where a lot of relatively cheap products are made by one relatively expensive tool. Since the shape of the cavity in the tool is the negative shape of the product, small changes in the product design can significantly reduce the manufacturing costs of the tool.

Thermal aspects of ice abrasive water jet technology

During the last few years, different research groups have been developing systems for the transition of abrasive water jet into ice abrasive water jet. The aim of this new technology is to make the technology cleaner from both practical and ecological points of view. Mineral abrasive is replaced with ice grains that melt away after the machining process, leaving the workpiece uncontaminated. Several different approaches to this technology were studied. Thermal aspects of integrating the ice abrasive water jet technology into commercially available machines were considered. The results and analyses of water temperature measurements on the ice abrasive water jet machine are presented in this article.

Water jet machining of MEDM tools

This contribution presents an investigation about the possibilities of using Water Jet (WJ) technology in combination with Micro Electrical Discharge Machining (MEDM) for tooling production in micro manufacturing. In the first phase the tool copper used in MEDM is produced by WJ machining. Afterwards, the final tool in steel is produced by MEDM. Such kinds of tools intend to be used in processes like hot embossing, molding, and other replication technologies in the field of micro manufacturing. The first results are very promising and the proposed tooling strategy, which involves besides MEDM also WJ technology, shows a lot of potential especially in the design and developing phase of micro-fluidic devices.