There is a strong industrial driving force to find alternative production technologies in order to make the production of aero engine components of superalloys even more efficient than it is today. Introducing new and nonconventional machining technologies allows taking a giant leap to increase the material removal rate and thereby drastically increase the productivity. However, the end result is to meet the requirements set for today's machined surfaces.The present work has been dedicated to improving the knowledge of how the non-conventional machining methods Abrasive Water Jet Machining, AWJM, Laser Beam Machining, LBM, and Electrical Discharge Machining, EDM, affect the surface integrity. The aim has been to understand how the surface integrity could be altered to an acceptable level. The results of this work have shown that both EDM and AWJM are two possible candidates but EDM is the better alternative; mainly due to the method's ability to machine complex geometries. It has further been shown that both methods require post processing in order to clean the surface and to improve the topography and for the case of EDM ageneration of compressive residual stresses are also needed.Three cold working post processes have been evaluated in order to attain this: shot peening, grit blasting and high pressure water jet cleaning, HPWJC. There sults showed that a combination of two post processes is required in order to reach the specified level of surface integrity in terms of cleaning and generating compressive residual stresses and low surface roughness. The method of high pressure water jet cleaning was the most effective method for removing the EDM wire residuals, and shot peening generated the highest compressive residual stresses as well as improved the surface topography.To summarise: the most promising production flow alternative using nonconventional machining would be EDM followed by post processing using HPWJC and shot peening.

<p>Predmet istraživanja ove disertacije predstavlja unapređenje, modelovanje i optimizacija procesa elektroerozivne obrade (EDM) savremenih inženjerskih materijala. Prvo su predstavljene dve inovativne metode: EDM u dielektrikumu sa pome&scaron;anim prahom i EDM sa pomoćnom elektrodom, a zatim i njihova kombinacija. Za generisanje matematičkih modela primenjene su metodologija odzivne povr&scaron;ine i alati ve&scaron;tačke inteligencije. U nastavku su postavljeni optimizacioni procesi određivanja ulaznih parametara sa jednom i vi&scaron;e funkcija cilja koji su re&scaron;eni primenom klasičnih metoda optimizacije. U zavr&scaron;nom osvrtu sprovedena je verifikacija dobijenih modela i optimalnih ulaznih parametara elektroerozivne obrade.</p> / <p>The subject of the research of this dissertation is the improvement, modeling and optimization of the electrical discharge machining (EDM) of advanced engineering materials. First, two innovation methods are presented: EDM in powder mixed dielectric fluid and EDM with assisted electrode and that their combination. The method of response surface and artificial intelligence tools were applied to generate mathematical models. The optimization problems of determining the input parameters with single and multiple target functions are solved by the application of classical optimization methods. Finally, verification of the obtained models and optimal input parameters of electrical discharge machining was carried out.</p>

The search for increased productivity and cost reduction in machining can be interpreted as the desire to increase the material removal rate, MRR, and maximize the cutting tool utilization. The CNC process is complex and involves numerous limitations and parameters, ranging from tolerances to machinability. A well-managed preparation process creates the foundations for achieving a reduction in manufacturing errors and machining time. Along the preparation process of the NC-program, two different studies have been conducted and are presented in this thesis. One study examined the CAM programming preparation process from the Lean perspective. The other study includes an evaluation of how the cutting tools are used in terms of MRR and tool utilization. The material removal rate is defined as the product of three variables, namely the cutting speed, the feed and the depth of cut, which all constitute the cutting data. Tool life is the amount of time that a cutting tool can be used and is mainly dependent on the same variables. Two different combinations of cutting data might provide the same MRR, however the tool life will be different. Thereby the difficulty is to select the cutting data to maximize both MRR and cutting tool utilization. A model for the analysis and efficient selection of cutting data for maximal MRR and maximal tool utilization has been developed and is presented. The presented model shortens the time dedicated to the optimized cutting data selection and the needed iterations along the program development.