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Analysis on Steel Composition and its Effect on Weld Quality: A Case-Study Done on EB Welded Diaphragms at Siemens SIT
KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
2014 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The repair rate on electron beam welded diaphragm hasn’t been at the desired level at Siemens SIT for several years. An improvement program the past five years has reduce the repair rate from 60% to 12-15% but the goal of 5% repair rate hasn’t been met. Collection of diaphragm weld and repair data started in the fall 2011 and in this thesis the material composition of the materials used for the production will be analysed from a statistical perspective. The thesis includes a comprehensive research of the nonparametric statistical methods suitable for non normally distributed, highly kurtotic and skewed data. Unfortunately a lot of statistical tests loose their power to correctly reject a false hypothesis with this kind of data. All of the elements in the material composition and the mechanical properties were analysed individually. In some of the cases it was possible to use statistical methods but in other it was not possible to conclude anything with statistics. Every case of outliers was evaluated individually. The main conclusions are that in all of the four materials there are some elements and mechanical properties outside of the material specifications. A number of cases also had outliers inside of the material specification and in most cases those were causing the variability in the data and had higher repair rates than the overall repair rate. Some trends were found, for example the weld quality was better for lower yield strength in all materials and higher chromium content in material A produced better quality. The first steps to improvement for Siemens are to find out why materials outside of the material specifications are getting all the way to the production without anyone noticing. A simple material process control chart could visually notify if a material is outside of the specification limits or even just outside of the usual. Knowing exactly how the material is before starting the production will give time and space for preventive measures if they are necessary and could improve lead times and decrease costs.

Abstract [sv]

För några år har Siemens hatt kvalitetsproblem med Electron Beam svetsing av mellanväggar. Förbättringsprojekt har reducerat reparationer intensivt men fortfarande finns det problemer med svetsningen. Inga mellanväggar lämnar produktionen utan att ha bra kvalitet så att förbättringarna ska fokusera på att reducera produktionskostnader och ledtider. Hösten 2011 började Siemens att samla reparation data för mellanväggarna och i det examens arbetet blir materialsamansättningen analyserad med statistiska metoder. Arbetet innehåller övergripande analysis på non-parametriska statistiska metoder och hur dom funkerar på skevat data med hög kurtosis. Tyvärr finns det inte många metoder som har hög chans att förkasta falska hypoteser när man jobbar med sånt data. Alla elementer och mekaniska egenskaper av materialet blev analyserade, men tyvärr inte alltid med statistiska metoder. Alla extremvärden blev analyserade individuellt. I alla fyra materialer finns det elementer och mekaniska egenskaper utan förmaterialets specifikationer. I vissa fall finns det outliers inom materialets specifikationer men som har högre reparation procent än det vanliga och orsakar variationen i datat. Vissa tendenser kunne hittas, till exempel att det går bättre att svetsa materialer med lägre sträckgräns och högre kromhalt går bättre för material A. Simpelt processstyrningdiagram skulle kunna visa om material är utanför material specifikationen men också om materialet är utanför det ”vanliga”. Att veta exact hur materialet är innan produktion kan sjunka ledtider och produktionskostnader.

Place, publisher, year, edition, pages
2014. , 104 p.
, Degree Project in Production Engineering Management, Second Level, 611
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-151255OAI: diva2:747208
Available from: 2014-09-16 Created: 2014-09-16 Last updated: 2014-09-16Bibliographically approved

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