Energy and raw material consumption analysis of powder bed fusion: case study: CNC machining and laser additive manufacturing

Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

Thick Section Laser Beam Welding of Structural Steels: Methods for Improving Welding Efficiency

Laser beam welding (LBW) is applicable for a wide range of industrial sectors and has a history of fifty years. However, it is considered an unusual method with applications typically limited to welding of thin sheet metal. With a new generation of high power lasers there has been a renewed interest in thick section LBW (also known as keyhole laser welding). There was a growing body of publications during 2001-2011 that indicates an increasing interest in laser welding for many industrial applications, and in last ten years, an increasing number of studies have examined the ways to increase the efficiency of the process. Expanding the thickness range and efficiency of LBW makes the process a possibility for industrial applications dealing with thick metal welding: shipbuilding, offshore structures, pipelines, power plants and other industries. The advantages provided by LBW, such as high process speed, high productivity, and low heat input, may revolutionize these industries and significantly reduce the process costs. The research to date has focused on either increasing the efficiency via optimizing process parameters, or on the process fundamentals, rather than on process and workpiece modifications. The argument of this thesis is that the efficiency of the laser beam process can be increased in a straightforward way in the workshop conditions. Throughout this dissertation, the term “efficiency” is used to refer to welding process efficiency, specifically, an increase in efficiency refers an increase in weld’s penetration depth without increasing laser power level or decreasing welding speed. These methods are: modifications of the workpiece – edge surface roughness and air gap between the joining plates; modification of the ambient conditions – local reduction of the pressure in the welding zone; modification of the welding process – preheating of the welding zone. Approaches to improve the efficiency are analyzed and compared both separately and combined. These experimentally proven methods confirm previous findings and contribute additional evidence which expand the opportunities for laser beam welding applications. The focus of this research was primarily on the effects of edge surface roughness preparation and pre-set air gap between the plates on weld quality and penetration depth. To date, there has been no reliable evidence that such modifications of the workpiece give a positive effect on the welding efficiency. Other methods were tested in combination with the two methods mentioned above. The most promising - combining with reduced pressure method - resulted in at least 100% increase in efficiency. The results of this thesis support the idea that joining those methods in one modified process will provide the modern engineering with a sufficient tool for many novel applications with potential benefits to a range of industries.

Utilising student profiles in mathematics course arrangements

This thesis develops a method for identifying students struggling in their mathematical studies at an early stage. It helps in directing support to students needing and benefiting from it the most. Thus, frustration felt by weaker students may decrease and therefore, hopefully, also drop outs of potential engineering students. The research concentrates on a combination of personality and intelligence aspects. Personality aspects gave information on conation and motivation for learning. This part was studied from the perspective of motivation and self-regulation. Intelligence aspects gave information on declarative and procedural knowledge: what had been taught and what was actually mastered. Students answered surveys on motivation and self-regulation in 2010 and 2011. Based on their answers, background information, results in the proficiency test, and grades in the first mathematics course, profiles describing the students were formed. In the following years, the profiles were updated with new information obtained each year. The profiles used to identify struggling students combine personality (motivation, selfregulation, and self-efficacy) and intelligence (declarative and procedural knowledge) aspects at the beginning of their studies. Identifying students in need of extra support is a good start, but methods for providing support must be found. This thesis also studies how this support could be taken into account in course arrangements. The methods used include, for example, languaging and scaffolding, and continuous feedback. The analysis revealed that allocating resources based on the predicted progress does not increase costs or lower the results of better students. Instead, it will help weaker students obtain passing grades.