[{"keyword":["multidimensional sensor arrays","MOS sensors","beer fermentation","process control","gas analysis","metal oxide semiconductors","intentional data analysis","chemometrics","PLSR","PCA","first-order calibration"],"language":[{"iso":"eng"}],"oa":"1","date_updated":"2025-06-25T13:00:14Z","publication_identifier":{"issn":["1424-8220 "]},"publication":"Sensors","date_created":"2024-06-03T07:43:48Z","status":"public","pmid":"1","author":[{"first_name":"Julia","last_name":"Kruse","id":"82298","full_name":"Kruse, Julia"},{"first_name":"Julius","full_name":"Wörner, Julius","last_name":"Wörner","id":"79011"},{"orcid":"0000-0001-6401-8873","full_name":"Schneider, Jan","last_name":"Schneider","first_name":"Jan","id":"13209"},{"first_name":"Helene","last_name":"Dörksen","full_name":"Dörksen, Helene","id":"46416"},{"first_name":"Miriam","id":"64952","full_name":"Pein-Hackelbusch, Miriam","last_name":"Pein-Hackelbusch","orcid":"0000-0002-7920-0595"}],"main_file_link":[{"url":"https://www.mdpi.com/1424-8220/24/11/3520","open_access":"1"}],"year":"2024","external_id":{"pmid":["38894312"],"isi":["001245424000001"]},"volume":24,"citation":{"ieee":"J. Kruse, J. Wörner, J. Schneider, H. Dörksen, and M. Pein-Hackelbusch, “Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses ,” <i>Sensors</i>, vol. 24, no. 11, Art. no. 3520, 2024, doi: <a href=\"https://doi.org/10.3390/s24113520\">10.3390/s24113520</a>.","ama":"Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>. 2024;24(11). doi:<a href=\"https://doi.org/10.3390/s24113520\">10.3390/s24113520</a>","chicago":"Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen, and Miriam Pein-Hackelbusch. “Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i> 24, no. 11 (2024). <a href=\"https://doi.org/10.3390/s24113520\">https://doi.org/10.3390/s24113520</a>.","apa":"Kruse, J., Wörner, J., Schneider, J., Dörksen, H., &#38; Pein-Hackelbusch, M. (2024). Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i>, <i>24</i>(11), Article 3520. <a href=\"https://doi.org/10.3390/s24113520\">https://doi.org/10.3390/s24113520</a>","ufg":"<b>Kruse, Julia u. a.</b>: Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses , in: <i>Sensors</i> 24 (2024), H. 11.","bjps":"<b>Kruse J <i>et al.</i></b> (2024) Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i> <b>24</b>.","havard":"J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses , Sensors. 24 (2024).","mla":"Kruse, Julia, et al. “Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses .” <i>Sensors</i>, vol. 24, no. 11, 3520, 2024, <a href=\"https://doi.org/10.3390/s24113520\">https://doi.org/10.3390/s24113520</a>.","van":"Kruse J, Wörner J, Schneider J, Dörksen H, Pein-Hackelbusch M. Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . Sensors. 2024;24(11).","din1505-2-1":"<span style=\"font-variant:small-caps;\">Kruse, Julia</span> ; <span style=\"font-variant:small-caps;\">Wörner, Julius</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span> ; <span style=\"font-variant:small-caps;\">Dörksen, Helene</span> ; <span style=\"font-variant:small-caps;\">Pein-Hackelbusch, Miriam</span>: Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . In: <i>Sensors</i> Bd. 24, MDPI (2024), Nr. 11","chicago-de":"Kruse, Julia, Julius Wörner, Jan Schneider, Helene Dörksen und Miriam Pein-Hackelbusch. 2024. Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses . <i>Sensors</i> 24, Nr. 11. doi:<a href=\"https://doi.org/10.3390/s24113520\">10.3390/s24113520</a>, .","short":"J. Kruse, J. Wörner, J. Schneider, H. Dörksen, M. Pein-Hackelbusch, Sensors 24 (2024)."},"title":"Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses ","_id":"11495","doi":"10.3390/s24113520","article_number":"3520","user_id":"83781","intvolume":"        24","type":"scientific_journal_article","publisher":"MDPI","quality_controlled":"1","department":[{"_id":"DEP4028"}],"abstract":[{"text":"To evaluate the suitability of an analytical instrument, essential figures of merit such as the limit of detection (LOD) and the limit of quantification (LOQ) can be employed. However, as the definitions k nown in the literature are mostly applicable to one signal per sample, estimating the LOD for substances with instruments yielding multidimensional results like electronic noses (eNoses) is still challenging. In this paper, we will compare and present different approaches to estimate the LOD for eNoses by employing commonly used multivariate data analysis and regression techniques, including principal component analysis (PCA), principal component regression (PCR), as well as partial least squares regression (PLSR). These methods could subsequently be used to assess the suitability of eNoses to help control and steer processes where volatiles are key process parameters. As a use case, we determined the LODs for key compounds involved in beer maturation, namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and 2-phenylethanol, and discussed the suitability of our eNose for that dertermination process. The results of the methods performed demonstrated differences of up to a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to suggest potential for monitoring via eNose. ","lang":"eng"}],"issue":"11","article_type":"original","publication_status":"published","isi":"1"},{"publisher":"IEEE","quality_controlled":"1","status":"public","abstract":[{"lang":"eng","text":"Low voltage direct current microgrids (DC-MG) provide a solution for increased efficiency by the reduction of conversion losses, total reuse of recuperation energy and an increased share of local power generation. Especially industrial applications ask for high uptimes and a stable voltage supply, which are both at stake in a power grid dominated by renewable generation. DC-MGs overcome these drawbacks by balancing energy distribution and power demand locally. For the planning and design of these grids a systemic approach is needed, due to the fact that many components are interacting. The task arises of structuring the knowledge available for individual technologies in an overall design framework. For this purpose, current state-of-the-art design processes are discussed in this article. These processes are mapped into the context of the requirements in an industrial environment. The findings are transferred to the design of industrial DC networks. Finally, a complete design process for DC-MGs is derived, which is proposed as a basis for the development of tools."}],"year":"2022","conference":{"end_date":"2021-12-18","start_date":"2021-12-16","location":" Macau, Macao ","name":"3rd International Conference on Electrical Engineering and Control Technologies (CEECT)"},"department":[{"_id":"DEP6020"},{"_id":"DEP5018"}],"citation":{"ieee":"D. Schaab, P. Spanier, M. Ehlich , and E. Fosselmann, Eds., <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. Piscataway, NJ: IEEE, 2022. doi: <a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">10.1109/CEECT53198.2021.9672633</a>.","ama":"Schaab D, Spanier P, Ehlich  M, Fosselmann E, eds. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. IEEE; 2022. doi:<a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">10.1109/CEECT53198.2021.9672633</a>","chicago-de":"Schaab, Darian, Patrick Spanier, Martin  Ehlich  und Eric  Fosselmann, Hrsg. 2022. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. 2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT). Piscataway, NJ: IEEE. doi:<a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">10.1109/CEECT53198.2021.9672633</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Schaab, D.</span> ; <span style=\"font-variant:small-caps;\">Spanier, P.</span> ; <span style=\"font-variant:small-caps;\">Ehlich , M.</span> ; <span style=\"font-variant:small-caps;\">Fosselmann, E.</span> (Hrsg.): <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>, <i>2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT)</i>. Piscataway, NJ : IEEE, 2022","short":"D. Schaab, P. Spanier, M. Ehlich , E. Fosselmann, eds., Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications, IEEE, Piscataway, NJ, 2022.","chicago":"Schaab, Darian, Patrick Spanier, Martin  Ehlich , and Eric  Fosselmann, eds. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. 2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT). Piscataway, NJ: IEEE, 2022. <a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">https://doi.org/10.1109/CEECT53198.2021.9672633</a>.","apa":"Schaab, D., Spanier, P., Ehlich , M., &#38; Fosselmann, E. (Eds.). (2022). <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. IEEE. <a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">https://doi.org/10.1109/CEECT53198.2021.9672633</a>","ufg":"<i><i>Schaab, Darian</i> u. a.</i>: Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications, Piscataway, NJ 2022 (2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT)).","bjps":"<b>Schaab D <i>et al.</i> (eds)</b> (2022) <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. Piscataway, NJ: IEEE.","havard":"D. Schaab, P. Spanier, M. Ehlich , E. Fosselmann, eds., Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications, IEEE, Piscataway, NJ, 2022.","mla":"Schaab, Darian, et al., editors. <i>Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications</i>. IEEE, 2022, <a href=\"https://doi.org/10.1109/CEECT53198.2021.9672633\">https://doi.org/10.1109/CEECT53198.2021.9672633</a>.","van":"Schaab D, Spanier P, Ehlich  M, Fosselmann E, editors. Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications. Piscataway, NJ: IEEE; 2022. (2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT))."},"publication_status":"published","title":"Design Framework for Multiple Infeed DC-Microgrids in Industrial Applications","series_title":"2021 3rd International Conference on Electrical Engineering and Control Technologies (CEECT)","_id":"8437","doi":"10.1109/CEECT53198.2021.9672633","keyword":["Renewable energy sources","Power demand","Process control","Voltage","Robustness","Planning","Stakeholders"],"place":"Piscataway, NJ","language":[{"iso":"eng"}],"editor":[{"full_name":"Schaab, Darian","first_name":"Darian","last_name":"Schaab"},{"first_name":"Patrick","last_name":"Spanier","full_name":"Spanier, Patrick","id":"43516"},{"last_name":"Ehlich ","full_name":"Ehlich , Martin ","first_name":"Martin "},{"first_name":"Eric ","full_name":"Fosselmann, Eric ","last_name":"Fosselmann"}],"user_id":"83781","date_updated":"2024-08-07T09:37:05Z","publication_identifier":{"isbn":["978-1-6654-4042-4"],"eisbn":["978-1-6654-4041-7"]},"date_created":"2022-07-06T08:55:01Z","type":"conference_editor"},{"isi":"1","publication_status":"published","department":[{"_id":"DEP7000"}],"abstract":[{"text":"Additive manufacturing is being increasingly focused on the production of end-use parts. Compared to the prototyping application, the production of end-use parts demands a higher level of repeatability and process quality. To achieve this, increased knowledge is required about the influence of various process parameters on the part characteristics and the parameter interrelations. Design of Experiment methods can be applied to gain knowledge on the process behavior, but the applicability of different DoE methods for AM processes has to be validated. This paper describes the application of a definitive screening design for the identification of influencing parameters in Laser Powder Bed Fusion of CoCrW alloy. The impact of various hatch parameters on the part porosity is analyzed. The experimental setup and results are described. The results are validated in an additional test series, comparing the part quality achieved by parameter-sets obtained by different optimization approaches. Furthermore, the correlation of the porosity towards mechanical properties is investigated. Finally, the opportunities and limitations of the method are discussed.","lang":"eng"}],"issue":"4-5","publisher":"Taylor & Francis","type":"scientific_journal_article","user_id":"83781","intvolume":"        35","place":"London [u.a.]","doi":"10.1080/0951192x.2021.1901313","_id":"12789","title":"Experimental approach towards parameter evaluation in laser powder bed fusion of metals","volume":35,"citation":{"ama":"Huxol A, Villmer FJ. Experimental approach towards parameter evaluation in laser powder bed fusion of metals. <i>International Journal of Computer Integrated Manufacturing</i>. 2021;35(4-5):556-567. doi:<a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">10.1080/0951192x.2021.1901313</a>","ieee":"A. Huxol and F.-J. Villmer, “Experimental approach towards parameter evaluation in laser powder bed fusion of metals,” <i>International Journal of Computer Integrated Manufacturing</i>, vol. 35, no. 4–5, pp. 556–567, 2021, doi: <a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">10.1080/0951192x.2021.1901313</a>.","short":"A. Huxol, F.-J. Villmer, International Journal of Computer Integrated Manufacturing 35 (2021) 556–567.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Huxol, Andrea</span> ; <span style=\"font-variant:small-caps;\">Villmer, Franz-Josef</span>: Experimental approach towards parameter evaluation in laser powder bed fusion of metals. In: <i>International Journal of Computer Integrated Manufacturing</i> Bd. 35. London [u.a.], Taylor &#38; Francis (2021), Nr. 4–5, S. 556–567","chicago-de":"Huxol, Andrea und Franz-Josef Villmer. 2021. Experimental approach towards parameter evaluation in laser powder bed fusion of metals. <i>International Journal of Computer Integrated Manufacturing</i> 35, Nr. 4–5: 556–567. doi:<a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">10.1080/0951192x.2021.1901313</a>, .","van":"Huxol A, Villmer FJ. Experimental approach towards parameter evaluation in laser powder bed fusion of metals. International Journal of Computer Integrated Manufacturing. 2021;35(4–5):556–67.","ufg":"<b>Huxol, Andrea/Villmer, Franz-Josef</b>: Experimental approach towards parameter evaluation in laser powder bed fusion of metals, in: <i>International Journal of Computer Integrated Manufacturing</i> 35 (2021), H. 4–5,  S. 556–567.","havard":"A. Huxol, F.-J. Villmer, Experimental approach towards parameter evaluation in laser powder bed fusion of metals, International Journal of Computer Integrated Manufacturing. 35 (2021) 556–567.","bjps":"<b>Huxol A and Villmer F-J</b> (2021) Experimental Approach towards Parameter Evaluation in Laser Powder Bed Fusion of Metals. <i>International Journal of Computer Integrated Manufacturing</i> <b>35</b>, 556–567.","mla":"Huxol, Andrea, and Franz-Josef Villmer. “Experimental Approach towards Parameter Evaluation in Laser Powder Bed Fusion of Metals.” <i>International Journal of Computer Integrated Manufacturing</i>, vol. 35, no. 4–5, 2021, pp. 556–67, <a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">https://doi.org/10.1080/0951192x.2021.1901313</a>.","apa":"Huxol, A., &#38; Villmer, F.-J. (2021). Experimental approach towards parameter evaluation in laser powder bed fusion of metals. <i>International Journal of Computer Integrated Manufacturing</i>, <i>35</i>(4–5), 556–567. <a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">https://doi.org/10.1080/0951192x.2021.1901313</a>","chicago":"Huxol, Andrea, and Franz-Josef Villmer. “Experimental Approach towards Parameter Evaluation in Laser Powder Bed Fusion of Metals.” <i>International Journal of Computer Integrated Manufacturing</i> 35, no. 4–5 (2021): 556–67. <a href=\"https://doi.org/10.1080/0951192x.2021.1901313\">https://doi.org/10.1080/0951192x.2021.1901313</a>."},"author":[{"last_name":"Huxol","full_name":"Huxol, Andrea","id":"43559","first_name":"Andrea"},{"first_name":"Franz-Josef","full_name":"Villmer, Franz-Josef","id":"14290","last_name":"Villmer"}],"year":"2021","external_id":{"isi":["000630944800001"]},"page":"556-567","status":"public","date_created":"2025-04-15T08:18:06Z","publication":"International Journal of Computer Integrated Manufacturing","publication_identifier":{"issn":["0951-192X"],"eissn":["1362-3052"]},"date_updated":"2025-06-26T07:56:42Z","language":[{"iso":"eng"}],"keyword":["Additive manufacturing","quality control","process qualification","process control","screening design"]},{"title":"Improving surface quality in selective laser melting based tool making","volume":32,"citation":{"apa":"Simoni, F., Huxol, A., &#38; Villmer, F.-J. (2021). Improving surface quality in selective laser melting based tool making. <i>Journal of Intelligent Manufacturing</i>, <i>32</i>(7), 1927–1938. <a href=\"https://doi.org/10.1007/s10845-021-01744-9\">https://doi.org/10.1007/s10845-021-01744-9</a>","chicago":"Simoni, Filippo, Andrea Huxol, and Franz-Josef Villmer. “Improving Surface Quality in Selective Laser Melting Based Tool Making.” <i>Journal of Intelligent Manufacturing</i> 32, no. 7 (2021): 1927–38. <a href=\"https://doi.org/10.1007/s10845-021-01744-9\">https://doi.org/10.1007/s10845-021-01744-9</a>.","van":"Simoni F, Huxol A, Villmer FJ. Improving surface quality in selective laser melting based tool making. Journal of Intelligent Manufacturing. 2021;32(7):1927–38.","ufg":"<b>Simoni, Filippo/Huxol, Andrea/Villmer, Franz-Josef</b>: Improving surface quality in selective laser melting based tool making, in: <i>Journal of Intelligent Manufacturing</i> 32 (2021), H. 7,  S. 1927–1938.","havard":"F. Simoni, A. Huxol, F.-J. Villmer, Improving surface quality in selective laser melting based tool making, Journal of Intelligent Manufacturing. 32 (2021) 1927–1938.","mla":"Simoni, Filippo, et al. “Improving Surface Quality in Selective Laser Melting Based Tool Making.” <i>Journal of Intelligent Manufacturing</i>, vol. 32, no. 7, 2021, pp. 1927–38, <a href=\"https://doi.org/10.1007/s10845-021-01744-9\">https://doi.org/10.1007/s10845-021-01744-9</a>.","bjps":"<b>Simoni F, Huxol A and Villmer F-J</b> (2021) Improving Surface Quality in Selective Laser Melting Based Tool Making. <i>Journal of Intelligent Manufacturing</i> <b>32</b>, 1927–1938.","short":"F. Simoni, A. Huxol, F.-J. Villmer, Journal of Intelligent Manufacturing 32 (2021) 1927–1938.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Simoni, Filippo</span> ; <span style=\"font-variant:small-caps;\">Huxol, Andrea</span> ; <span style=\"font-variant:small-caps;\">Villmer, Franz-Josef</span>: Improving surface quality in selective laser melting based tool making. In: <i>Journal of Intelligent Manufacturing</i> Bd. 32. Dordrecht [u.a.], Springer Science and Business Media (2021), Nr. 7, S. 1927–1938","chicago-de":"Simoni, Filippo, Andrea Huxol und Franz-Josef Villmer. 2021. Improving surface quality in selective laser melting based tool making. <i>Journal of Intelligent Manufacturing</i> 32, Nr. 7: 1927–1938. doi:<a href=\"https://doi.org/10.1007/s10845-021-01744-9\">10.1007/s10845-021-01744-9</a>, .","ieee":"F. Simoni, A. Huxol, and F.-J. Villmer, “Improving surface quality in selective laser melting based tool making,” <i>Journal of Intelligent Manufacturing</i>, vol. 32, no. 7, pp. 1927–1938, 2021, doi: <a href=\"https://doi.org/10.1007/s10845-021-01744-9\">10.1007/s10845-021-01744-9</a>.","ama":"Simoni F, Huxol A, Villmer FJ. Improving surface quality in selective laser melting based tool making. <i>Journal of Intelligent Manufacturing</i>. 2021;32(7):1927-1938. doi:<a href=\"https://doi.org/10.1007/s10845-021-01744-9\">10.1007/s10845-021-01744-9</a>"},"year":"2021","author":[{"first_name":"Filippo","last_name":"Simoni","full_name":"Simoni, Filippo"},{"first_name":"Andrea","last_name":"Huxol","id":"43559","full_name":"Huxol, Andrea"},{"first_name":"Franz-Josef","id":"14290","full_name":"Villmer, Franz-Josef","last_name":"Villmer"}],"external_id":{"isi":["000636136100001"]},"page":"1927-1938","status":"public","date_created":"2025-04-15T09:17:22Z","publication":"Journal of Intelligent Manufacturing","publication_identifier":{"eissn":["1572-8145"],"issn":["0956-5515"]},"date_updated":"2025-06-26T13:41:37Z","language":[{"iso":"eng"}],"keyword":["Direct rapid tooling","Toolmaking","Additive manufacturing process chain","Process control","Production systems","Selective laser melting","Surface roughness","Laser surface remelting"],"isi":"1","publication_status":"published","department":[{"_id":"DEP7000"}],"issue":"7","abstract":[{"text":"n the last years, Additive Manufacturing, thanks to its capability of continuous improvements in performance and cost-efficiency, was able to partly replace and redefine well-established manufacturing processes. This research is based on the idea to achieve great cost and operational benefits especially in the field of tool making for injection molding by combining traditional and additive manufacturing in one process chain. Special attention is given to the surface quality in terms of surface roughness and its optimization directly in the Selective Laser Melting process. This article presents the possibility for a remelting process of the SLM parts as a way to optimize the surfaces of the produced parts. The influence of laser remelting on the surface roughness of the parts is analyzed while varying machine parameters like laser power and scan settings. Laser remelting with optimized parameter settings considerably improves the surface quality of SLM parts and is a great starting point for further post-processing techniques, which require a low initial value of surface roughness.","lang":"eng"}],"publisher":"Springer Science and Business Media","type":"scientific_journal_article","user_id":"83781","intvolume":"        32","place":"Dordrecht [u.a.]","doi":"10.1007/s10845-021-01744-9","_id":"12790"},{"keyword":["Additive manufacturing","quality control","process qualification","process control","screening design"],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2405-8963"]},"publication":"13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)","date_created":"2025-04-15T09:27:00Z","date_updated":"2025-06-26T13:40:48Z","year":"2019","author":[{"id":"43559","last_name":"Huxol","first_name":"Andrea","full_name":"Huxol, Andrea"},{"id":"14290","last_name":"Villmer","full_name":"Villmer, Franz-Josef","first_name":"Franz-Josef"}],"status":"public","page":"270-275","title":"DoE Methods for Parameter Evaluation in Selective Laser Melting","citation":{"van":"Huxol A, Villmer FJ. DoE Methods for Parameter Evaluation in Selective Laser Melting. 13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS). Amsterdam [u.a.]: Elsevier BV; 2019. (IFAC-PapersOnLine; vol. 52).","ama":"Huxol A, Villmer FJ. <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>. Vol 52. Elsevier BV; 2019:270-275. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">10.1016/j.ifacol.2019.10.041</a>","ufg":"<b>Huxol, Andrea/Villmer, Franz-Josef</b>: DoE Methods for Parameter Evaluation in Selective Laser Melting, Bd. 52, Amsterdam [u.a.] 2019 (IFAC-PapersOnLine).","mla":"Huxol, Andrea, and Franz-Josef Villmer. “DoE Methods for Parameter Evaluation in Selective Laser Melting.” <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>, vol. 52, Elsevier BV, 2019, pp. 270–75, <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">https://doi.org/10.1016/j.ifacol.2019.10.041</a>.","havard":"A. Huxol, F.-J. Villmer, DoE Methods for Parameter Evaluation in Selective Laser Melting, Elsevier BV, Amsterdam [u.a.], 2019.","bjps":"<b>Huxol A and Villmer F-J</b> (2019) <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>. Amsterdam [u.a.]: Elsevier BV.","apa":"Huxol, A., &#38; Villmer, F.-J. (2019). DoE Methods for Parameter Evaluation in Selective Laser Melting. In <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i> (Vol. 52, pp. 270–275). Elsevier BV. <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">https://doi.org/10.1016/j.ifacol.2019.10.041</a>","ieee":"A. Huxol and F.-J. Villmer, <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>, vol. 52. Amsterdam [u.a.]: Elsevier BV, 2019, pp. 270–275. doi: <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">10.1016/j.ifacol.2019.10.041</a>.","chicago":"Huxol, Andrea, and Franz-Josef Villmer. <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>. <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Vol. 52. IFAC-PapersOnLine. Amsterdam [u.a.]: Elsevier BV, 2019. <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">https://doi.org/10.1016/j.ifacol.2019.10.041</a>.","short":"A. Huxol, F.-J. Villmer, DoE Methods for Parameter Evaluation in Selective Laser Melting, Elsevier BV, Amsterdam [u.a.], 2019.","chicago-de":"Huxol, Andrea und Franz-Josef Villmer. 2019. <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>. <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Bd. 52. IFAC-PapersOnLine. Amsterdam [u.a.]: Elsevier BV. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2019.10.041\">10.1016/j.ifacol.2019.10.041</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Huxol, Andrea</span> ; <span style=\"font-variant:small-caps;\">Villmer, Franz-Josef</span>: <i>DoE Methods for Parameter Evaluation in Selective Laser Melting</i>, <i>IFAC-PapersOnLine</i>. Bd. 52. Amsterdam [u.a.] : Elsevier BV, 2019"},"volume":52,"_id":"12791","doi":"10.1016/j.ifacol.2019.10.041","place":"Amsterdam [u.a.]","type":"conference_editor_article","intvolume":"        52","user_id":"83781","abstract":[{"text":"Additive manufacturing is being increasingly focused on the production of end-use parts. Compared to the prototyping application, the production of end-use parts demands a higher level of repeatability and process quality. To achieve this, increased knowledge is required about the influence of various process parameters on the part characteristics and the parameter interrelations. Design of Experiment methods can be applied to gain knowledge on the process behavior, but the applicability of different DoE methods for AM processes has to be validated. This paper describes the application of a definitive screening design for the identification of influencing parameters in Selective Laser Melting. The experimental setup and results are described and opportunities and limitations of the method are discussed. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.","lang":"eng"}],"conference":{"start_date":"2019-08-12","end_date":"2019-08-14","name":"13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)","location":"Oshawa, CANADA"},"department":[{"_id":"DEP7000"}],"publisher":"Elsevier BV","series_title":"IFAC-PapersOnLine","publication_status":"published"},{"abstract":[{"lang":"eng","text":"Additive Manufacturing has arisen as a ground-breaking set of technologies that, thanks to their capability of continuous improvements in performance and cost-efficiency, was able in the last years to replace well-established manufacturing processes. Proficiency in the fabrication of highly complex parts forced this astonishing development. This research is based on the idea that through the integration of additive and conventional manufacturing technologies it is possible to achieve great cost and operational benefits especially in the field of tool making for injection molding. Such an integrated manufacturing solution could overcome the limitations of independent additive, subtractive, and post-processing procedures by strengthening their potentialities. The present study highlights the opportunities of a synergy between the above-mentioned manufacturing technologies for the optimized fabrication of injection molds. An additive manufacturing process chain is presented, and special attention is given to the surface quality and its optimization directly in the Selective Laser Melting process. The potentialities of the Laser Surface Re-melting technique are analyzed, and the process optimization leads to a reduction of 45% of the average roughness directly in the SLM process. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved."}],"conference":{"location":"Oshawa, CANADA","name":"13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)","end_date":"2019-08-14","start_date":"2019-08-12"},"department":[{"_id":"DEP7000"}],"publisher":"Elsevier BV","series_title":"IFAC-PapersOnLine","publication_status":"published","_id":"12792","doi":"10.1016/j.ifacol.2019.10.032","place":"Amsterdam [u.a.]","type":"conference_editor_article","intvolume":"        52","user_id":"83781","author":[{"first_name":"Filippo","last_name":"Simoni","full_name":"Simoni, Filippo"},{"id":"43559","first_name":"Andrea","full_name":"Huxol, Andrea","last_name":"Huxol"},{"full_name":"Villmer, Franz-Josef","id":"14290","first_name":"Franz-Josef","last_name":"Villmer"}],"year":"2019","status":"public","page":"254-259","title":"Approach Towards Surface Improvement in Additively Manufactured Tools","volume":52,"citation":{"chicago-de":"Simoni, Filippo, Andrea Huxol und Franz-Josef Villmer. 2019. <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>. <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Bd. 52. IFAC-PapersOnLine. Amsterdam [u.a.]: Elsevier BV. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">10.1016/j.ifacol.2019.10.032</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Simoni, Filippo</span> ; <span style=\"font-variant:small-caps;\">Huxol, Andrea</span> ; <span style=\"font-variant:small-caps;\">Villmer, Franz-Josef</span>: <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>, <i>IFAC-PapersOnLine</i>. Bd. 52. Amsterdam [u.a.] : Elsevier BV, 2019","short":"F. Simoni, A. Huxol, F.-J. Villmer, Approach Towards Surface Improvement in Additively Manufactured Tools, Elsevier BV, Amsterdam [u.a.], 2019.","chicago":"Simoni, Filippo, Andrea Huxol, and Franz-Josef Villmer. <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>. <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>. Vol. 52. IFAC-PapersOnLine. Amsterdam [u.a.]: Elsevier BV, 2019. <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">https://doi.org/10.1016/j.ifacol.2019.10.032</a>.","apa":"Simoni, F., Huxol, A., &#38; Villmer, F.-J. (2019). Approach Towards Surface Improvement in Additively Manufactured Tools. In <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i> (Vol. 52, pp. 254–259). Elsevier BV. <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">https://doi.org/10.1016/j.ifacol.2019.10.032</a>","ufg":"<b>Simoni, Filippo/Huxol, Andrea/Villmer, Franz-Josef</b>: Approach Towards Surface Improvement in Additively Manufactured Tools, Bd. 52, Amsterdam [u.a.] 2019 (IFAC-PapersOnLine).","mla":"Simoni, Filippo, et al. “Approach Towards Surface Improvement in Additively Manufactured Tools.” <i>13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)</i>, vol. 52, Elsevier BV, 2019, pp. 254–59, <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">https://doi.org/10.1016/j.ifacol.2019.10.032</a>.","havard":"F. Simoni, A. Huxol, F.-J. Villmer, Approach Towards Surface Improvement in Additively Manufactured Tools, Elsevier BV, Amsterdam [u.a.], 2019.","bjps":"<b>Simoni F, Huxol A and Villmer F-J</b> (2019) <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>. Amsterdam [u.a.]: Elsevier BV.","van":"Simoni F, Huxol A, Villmer FJ. Approach Towards Surface Improvement in Additively Manufactured Tools. 13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS). Amsterdam [u.a.]: Elsevier BV; 2019. (IFAC-PapersOnLine; vol. 52).","ieee":"F. Simoni, A. Huxol, and F.-J. Villmer, <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>, vol. 52. Amsterdam [u.a.]: Elsevier BV, 2019, pp. 254–259. doi: <a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">10.1016/j.ifacol.2019.10.032</a>.","ama":"Simoni F, Huxol A, Villmer FJ. <i>Approach Towards Surface Improvement in Additively Manufactured Tools</i>. Vol 52. Elsevier BV; 2019:254-259. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2019.10.032\">10.1016/j.ifacol.2019.10.032</a>"},"keyword":["Direct rapid tooling","toolmaking","additive manufacturing process chain","process control","production systems","selective laser melting","surface roughness","laser surface re-melting"],"language":[{"iso":"eng"}],"publication":"13th International-Federation-of-Automatic-Control (IFAC) Workshop on Intelligent Manufacturing Systems (IMS)","publication_identifier":{"issn":["2405-8963"]},"date_created":"2025-04-15T09:32:02Z","date_updated":"2025-06-26T13:40:36Z"},{"abstract":[{"text":"A rising number of product variants together with decreasing lot sizes are a result of the trend of individualization. Besides the upcoming organizational issues, changes in the production technologies are required. Direct digital manufacturing contributes to solve this problem by enabling the production of parts right from the CAD data.Process capability analysis is applied in several industries to prove the reliable compliance of products with quality requirements. As it is based on statistical methods, new challenges arise in the context of single-part production.The paper describes and compares different approaches for the adoption of process capability analysis for single-part production with special focus on additive manufacturing technologies. The statistical background and the applicability of different capability parameters are discussed. An overview of existing research work is given and supplemented by own approaches for the adoption of statistical methods for single-part production. The aim of the research work is to establish a first approach for the qualification of new technologies in single-part production.","lang":"eng"}],"issue":"1","conference":{"start_date":"2017-09-28","end_date":"2017-09-29","location":"Pordenone, Italy","name":"Proceedings7th International Conference"},"department":[{"_id":"DEP1306"}],"publication_status":"published","series_title":"Publication series in direct digital manufacturing ","_id":"577","place":"Lemgo","user_id":"45673","type":"conference","page":"63-74","status":"public","author":[{"first_name":"Andrea","full_name":"Huxol, Andrea","last_name":"Huxol","id":"43559"},{"full_name":"Davis, Andrea","first_name":"Andrea","id":"68611","last_name":"Davis"},{"id":"14290","first_name":"Franz-Josef","full_name":"Villmer, Franz-Josef","last_name":"Villmer"},{"last_name":"Scheideler","full_name":"Scheideler, Eva","first_name":"Eva","id":"61522"}],"year":2017,"main_file_link":[{"url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf","open_access":"1"}],"citation":{"chicago-de":"Huxol, Andrea, Andrea Davis, Franz-Josef Villmer und Eva Scheideler. 2017. Deployment of Process Capability Analysis for Single-Part Production. In: <i>Production Engineering and Management</i>, hg. von Elio Padoano, Franz-Josef Villmer, und Department of Production Engineering and Management, 63–74. Publication series in direct digital manufacturing . Lemgo.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Huxol, Andrea</span> ; <span style=\"font-variant:small-caps;\">Davis, Andrea</span> ; <span style=\"font-variant:small-caps;\">Villmer, Franz-Josef</span> ; <span style=\"font-variant:small-caps;\">Scheideler, Eva</span>: Deployment of Process Capability Analysis for Single-Part Production. In: <span style=\"font-variant:small-caps;\">Padoano, E.</span> ; <span style=\"font-variant:small-caps;\">Villmer, F.-J.</span> ; <span style=\"font-variant:small-caps;\">Department of Production Engineering and Management</span> (Hrsg.): <i>Production Engineering and Management</i>, <i>Publication series in direct digital manufacturing </i>. Lemgo, 2017, S. 63–74","short":"A. Huxol, A. Davis, F.-J. Villmer, E. Scheideler, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management (Eds.), Production Engineering and Management, Lemgo, 2017, pp. 63–74.","bjps":"<b>Huxol A <i>et al.</i></b> (2017) Deployment of Process Capability Analysis for Single-Part Production. In Padoano E, Villmer F-J and Department of Production Engineering and Management (eds), <i>Production Engineering and Management</i>. Lemgo, pp. 63–74.","mla":"Huxol, Andrea, et al. “Deployment of Process Capability Analysis for Single-Part Production.” <i>Production Engineering and Management</i>, edited by Elio Padoano et al., no. 1, 2017, pp. 63–74.","havard":"A. Huxol, A. Davis, F.-J. Villmer, E. Scheideler, Deployment of Process Capability Analysis for Single-Part Production, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management (Eds.), Production Engineering and Management, Lemgo, 2017: pp. 63–74.","ufg":"<b>Huxol, Andrea et. al. (2017)</b>: Deployment of Process Capability Analysis for Single-Part Production, in: Elio Padoano et. al. (Hgg.): <i>Production Engineering and Management</i> (=<i>Publication series in direct digital manufacturing </i>), Lemgo, S. 63–74.","van":"Huxol A, Davis A, Villmer F-J, Scheideler E. Deployment of Process Capability Analysis for Single-Part Production. In: Padoano E, Villmer F-J, Department of Production Engineering and Management, editors. Production Engineering and Management. Lemgo; 2017. p. 63–74. (Publication series in direct digital manufacturing ).","chicago":"Huxol, Andrea, Andrea Davis, Franz-Josef Villmer, and Eva Scheideler. “Deployment of Process Capability Analysis for Single-Part Production.” In <i>Production Engineering and Management</i>, edited by Elio Padoano, Franz-Josef Villmer, and Department of Production Engineering and Management, 63–74. Publication Series in Direct Digital Manufacturing . Lemgo, 2017.","apa":"Huxol, A., Davis, A., Villmer, F.-J., &#38; Scheideler, E. (2017). Deployment of Process Capability Analysis for Single-Part Production. In E. Padoano, F.-J. Villmer, &#38; Department of Production Engineering and Management (Eds.), <i>Production Engineering and Management</i> (pp. 63–74). Lemgo.","ama":"Huxol A, Davis A, Villmer F-J, Scheideler E. Deployment of Process Capability Analysis for Single-Part Production. In: Padoano E, Villmer F-J, Department of Production Engineering and Management, eds. <i>Production Engineering and Management</i>. Publication series in direct digital manufacturing . Lemgo; 2017:63-74.","ieee":"A. Huxol, A. Davis, F.-J. Villmer, and E. Scheideler, “Deployment of Process Capability Analysis for Single-Part Production,” in <i>Production Engineering and Management</i>, Pordenone, Italy, 2017, no. 1, pp. 63–74."},"title":"Deployment of Process Capability Analysis for Single-Part Production","language":[{"iso":"eng"}],"keyword":["Statistical process control","Process capability analysis","Single-part production","Process optimization"],"oa":"1","editor":[{"first_name":"Elio","full_name":"Padoano, Elio","last_name":"Padoano"},{"last_name":"Villmer","full_name":"Villmer, Franz-Josef","first_name":"Franz-Josef"}],"corporate_editor":["Department of Production Engineering and Management","Hochschule Ostwestfalen-Lippe"],"related_material":{"link":[{"url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf","relation":"contains"}]},"date_updated":"2023-03-15T13:50:01Z","date_created":"2019-02-18T11:16:07Z","publication":"Production Engineering and Management","publication_identifier":{"isbn":["978-3-946856-01-6"]}},{"type":"conference","user_id":"83781","intvolume":"      2017","place":"Lemgo","_id":"580","series_title":"\t Publication series in direct digital manufacturing ","publication_status":"published","department":[{"_id":"DEP1306"}],"conference":{"end_date":"2017-09-29","start_date":"2017-09-28","location":"Pordenone, Italy","name":"7th International Conference on Production Engineering and Management"},"issue":"1","abstract":[{"text":"Additive Manufacturing (AM) is increasingly used to design new products. This is possible due to the further development of the AM-processes and materials. The lack of quality assurance of AM built parts is a key technological barrier that prevents manufacturers from adopting. The quality of an additive manufactured part is influenced by more than 50 parameters, which make process control difficult. Current research deals with using real time monitoring of the melt pool as feedback control for laser power. This paper illustrates challenges and opportunities of applying statistical predictive modeling and unsupervised learning to control additive manufacturing. In particular, an approach how to build a feedforward controller will be discussed.","lang":"eng"}],"publication":"\t Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy ","publication_identifier":{"isbn":["978-3-946856-01-6"]},"date_created":"2019-02-18T11:34:36Z","date_updated":"2024-03-22T13:19:02Z","related_material":{"link":[{"url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf","relation":"contains"}]},"corporate_editor":["Department of Production Engineering and Management","Hochschule Ostwestfalen-Lippe"],"editor":[{"first_name":"Elio","full_name":"Padoano, Elio","last_name":"Padoano"},{"first_name":"Franz-Josef","id":"14290","last_name":"Villmer","full_name":"Villmer, Franz-Josef"}],"oa":"1","keyword":["Additive manufacturing","Process control","Predictive modeling","Predictive control"],"language":[{"iso":"eng"}],"title":"Quality Control of Additive Manufacturing Using Statistical Prediction Models","citation":{"ama":"Scheideler E, Ahlemeyer-Stubbe A. Quality Control of Additive Manufacturing Using Statistical Prediction Models. In: Padoano E, Villmer FJ, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe, eds. <i>  Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy </i>. Vol 2017.   Publication series in direct digital manufacturing . ; 2017:3-12.","ieee":"E. Scheideler and A. Ahlemeyer-Stubbe, “Quality Control of Additive Manufacturing Using Statistical Prediction Models,” in <i>  Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy </i>, Pordenone, Italy, 2017, vol. 2017, no. 1, pp. 3–12.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Scheideler, Eva</span> ; <span style=\"font-variant:small-caps;\">Ahlemeyer-Stubbe, Andrea</span>: Quality Control of Additive Manufacturing Using Statistical Prediction Models. In: <span style=\"font-variant:small-caps;\">Padoano, E.</span> ; <span style=\"font-variant:small-caps;\">Villmer, F.-J.</span> ; <span style=\"font-variant:small-caps;\">Department of Production Engineering and Management</span> ; <span style=\"font-variant:small-caps;\">Hochschule Ostwestfalen-Lippe</span> (Hrsg.): <i>  Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy </i>, <i>  Publication series in direct digital manufacturing </i>. Bd. 2017. Lemgo, 2017, S. 3–12","chicago-de":"Scheideler, Eva und Andrea Ahlemeyer-Stubbe. 2017. Quality Control of Additive Manufacturing Using Statistical Prediction Models. In: <i>  Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy </i>, hg. von Elio Padoano, Franz-Josef Villmer, Department of Production Engineering and Management, und Hochschule Ostwestfalen-Lippe, 2017:3–12.   Publication series in direct digital manufacturing . Lemgo.","short":"E. Scheideler, A. Ahlemeyer-Stubbe, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),   Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy , Lemgo, 2017, pp. 3–12.","mla":"Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Quality Control of Additive Manufacturing Using Statistical Prediction Models.” <i>  Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy </i>, edited by Elio Padoano et al., vol. 2017, no. 1, 2017, pp. 3–12.","bjps":"<b>Scheideler E and Ahlemeyer-Stubbe A</b> (2017) Quality Control of Additive Manufacturing Using Statistical Prediction Models. In Padoano E et al. (eds), <i>  Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy </i>, vol. 2017. Lemgo, pp. 3–12.","havard":"E. Scheideler, A. Ahlemeyer-Stubbe, Quality Control of Additive Manufacturing Using Statistical Prediction Models, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.),   Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy , Lemgo, 2017: pp. 3–12.","ufg":"<b>Scheideler, Eva/Ahlemeyer-Stubbe, Andrea</b>: Quality Control of Additive Manufacturing Using Statistical Prediction Models, in: <i>Padoano, Elio u. a. (Hgg.)</i>:   Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy , Bd. 2017, Lemgo 2017 (  Publication series in direct digital manufacturing ),  S. 3–12.","van":"Scheideler E, Ahlemeyer-Stubbe A. Quality Control of Additive Manufacturing Using Statistical Prediction Models. In: Padoano E, Villmer FJ, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe, editors.   Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy . Lemgo; 2017. p. 3–12. (  Publication series in direct digital manufacturing ; vol. 2017).","chicago":"Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Quality Control of Additive Manufacturing Using Statistical Prediction Models.” In <i>  Production Engineering and Management : Proceedings 7th International Conference, September 28 and 29, 2017, Pordenone, Italy </i>, edited by Elio Padoano, Franz-Josef Villmer, Department of Production Engineering and Management, and Hochschule Ostwestfalen-Lippe, 2017:3–12.   Publication Series in Direct Digital Manufacturing . Lemgo, 2017.","apa":"Scheideler, E., &#38; Ahlemeyer-Stubbe, A. (2017). Quality Control of Additive Manufacturing Using Statistical Prediction Models. In E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, &#38; Hochschule Ostwestfalen-Lippe (Eds.), <i>  Production engineering and management : proceedings 7th international conference, September 28 and 29, 2017, Pordenone, Italy </i> (Vol. 2017, Issue 1, pp. 3–12)."},"volume":2017,"author":[{"first_name":"Eva","last_name":"Scheideler","id":"61522","full_name":"Scheideler, Eva"},{"full_name":"Ahlemeyer-Stubbe, Andrea","first_name":"Andrea","last_name":"Ahlemeyer-Stubbe"}],"year":"2017","main_file_link":[{"open_access":"1","url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_2017_Proceeding_web.pdf"}],"status":"public","page":"3-12"},{"publication_status":"published","abstract":[{"text":"This paper is aimed to discuss current research using data mining techniques and industry statistics in production environments. The general research approach is based on the idea of using data mining processes and techniques of industry statistics to find rare and hidden patterns behind failures of complex components. A case study will be applied to illustrate how the technique is carried out and where the limits of this approach occur. The case study deals with a component supplier of printing machines, which received an increasing number of client complaints, all related to one distinct problem. The observed failures seem to occur only among clients with very high quality standards. The affected component undergoes a very complex production process with several steps in different departments. Every single production unit records data information from multiple process variables and at different points in time. In the beginning there was no understanding of the failure causes in production at all. Therefore a huge amount of production data had to be analyzed to find the pattern that discloses the failure.\r\nThe data mining process starts with a first step in which the given data sets are prepared and then cleaned. Followed up by building a prediction model. The aim is to detect the root causes for failures and to predict potential failures in affected components. This paper shows how to use data mining to get the answer on pressing production failures.\r\n","lang":"eng"}],"issue":"1","department":[{"_id":"DEP7000"},{"_id":"DEP1306"}],"conference":{"location":"Trieste, Italy","name":"5th International Conference \"Production Engineering and Management\" ","start_date":"2015-10-01","end_date":"2015-10-02"},"publisher":"Hochschule Ostwestfalen-Lippe","type":"conference","user_id":"83781","_id":"597","place":"Lemgo","title":"Data Mining: A Potential Detector to Find Failure in Complex Components","citation":{"ama":"Scheideler E, Ahlemeyer-Stubbe A. Data Mining: A Potential Detector to Find Failure in Complex Components. In: Padoano E, Villmer FJ, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe, eds. <i>Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy</i>. Hochschule Ostwestfalen-Lippe; 2015:163-174.","ieee":"E. Scheideler and A. Ahlemeyer-Stubbe, “Data Mining: A Potential Detector to Find Failure in Complex Components,” in <i>Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy</i>, Trieste, Italy, 2015, no. 1, pp. 163–174.","ufg":"<b>Scheideler, Eva/Ahlemeyer-Stubbe, Andrea</b>: Data Mining: A Potential Detector to Find Failure in Complex Components, in: <i>Padoano, Elio u. a. (Hgg.)</i>: Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy, Lemgo 2015,  S. 163–174.","havard":"E. Scheideler, A. Ahlemeyer-Stubbe, Data Mining: A Potential Detector to Find Failure in Complex Components, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.), Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy, Hochschule Ostwestfalen-Lippe, Lemgo, 2015: pp. 163–174.","mla":"Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Data Mining: A Potential Detector to Find Failure in Complex Components.” <i>Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy</i>, edited by Elio Padoano et al., no. 1, Hochschule Ostwestfalen-Lippe, 2015, pp. 163–74.","bjps":"<b>Scheideler E and Ahlemeyer-Stubbe A</b> (2015) Data Mining: A Potential Detector to Find Failure in Complex Components. In Padoano E et al. (eds), <i>Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy</i>. Lemgo: Hochschule Ostwestfalen-Lippe, pp. 163–174.","van":"Scheideler E, Ahlemeyer-Stubbe A. Data Mining: A Potential Detector to Find Failure in Complex Components. In: Padoano E, Villmer FJ, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe, editors. Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy. Lemgo: Hochschule Ostwestfalen-Lippe; 2015. p. 163–74.","chicago":"Scheideler, Eva, and Andrea Ahlemeyer-Stubbe. “Data Mining: A Potential Detector to Find Failure in Complex Components.” In <i>Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy</i>, edited by Elio Padoano, Franz-Josef Villmer, Department of Production Engineering and Management, and Hochschule Ostwestfalen-Lippe, 163–74. Lemgo: Hochschule Ostwestfalen-Lippe, 2015.","apa":"Scheideler, E., &#38; Ahlemeyer-Stubbe, A. (2015). Data Mining: A Potential Detector to Find Failure in Complex Components. In E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, &#38; Hochschule Ostwestfalen-Lippe (Eds.), <i>Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy</i> (Issue 1, pp. 163–174). Hochschule Ostwestfalen-Lippe.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Scheideler, Eva</span> ; <span style=\"font-variant:small-caps;\">Ahlemeyer-Stubbe, Andrea</span>: Data Mining: A Potential Detector to Find Failure in Complex Components. In: <span style=\"font-variant:small-caps;\">Padoano, E.</span> ; <span style=\"font-variant:small-caps;\">Villmer, F.-J.</span> ; <span style=\"font-variant:small-caps;\">Department of Production Engineering and Management</span> ; <span style=\"font-variant:small-caps;\">Hochschule Ostwestfalen-Lippe</span> (Hrsg.): <i>Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy</i>. Lemgo : Hochschule Ostwestfalen-Lippe, 2015, S. 163–174","chicago-de":"Scheideler, Eva und Andrea Ahlemeyer-Stubbe. 2015. Data Mining: A Potential Detector to Find Failure in Complex Components. In: <i>Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy</i>, hg. von Elio Padoano, Franz-Josef Villmer, Department of Production Engineering and Management, und Hochschule Ostwestfalen-Lippe, 163–174. Lemgo: Hochschule Ostwestfalen-Lippe.","short":"E. Scheideler, A. Ahlemeyer-Stubbe, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management, Hochschule Ostwestfalen-Lippe (Eds.), Production Engineering and Management : Proceedings, 5th International Conference, October 1 and 2, 2015, Trieste, Italy, Hochschule Ostwestfalen-Lippe, Lemgo, 2015, pp. 163–174."},"author":[{"id":"61522","last_name":"Scheideler","full_name":"Scheideler, Eva","first_name":"Eva"},{"last_name":"Ahlemeyer-Stubbe","first_name":"Andrea","full_name":"Ahlemeyer-Stubbe, Andrea"}],"year":"2015","main_file_link":[{"open_access":"1","url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf"}],"status":"public","page":"163-174","publication":"Production engineering and management : proceedings, 5th international conference, October 1 and 2, 2015, Trieste, Italy","publication_identifier":{"isbn":["978-3-941645-11-0"]},"date_created":"2019-02-19T07:15:57Z","corporate_editor":["Department of Production Engineering and Management","Hochschule Ostwestfalen-Lippe"],"editor":[{"first_name":"Elio","last_name":"Padoano","full_name":"Padoano, Elio"},{"first_name":"Franz-Josef","full_name":"Villmer, Franz-Josef","last_name":"Villmer","id":"14290"}],"related_material":{"link":[{"relation":"contains","url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf"}]},"date_updated":"2024-03-22T13:12:47Z","oa":"1","keyword":["Data mining","production failure","multi-variant analysis","multivariate process control","predictive modelling","case study"],"language":[{"iso":"eng"}]}]