{"keyword":["Data Quality Assessment","Advanced Planning","Scheduling","Bayesian Network","Enterprise Resource Planning"],"main_file_link":[{"open_access":"1","url":"https://www.sciencedirect.com/science/article/pii/S1877050922002277"}],"status":"public","citation":{"van":"Herrmann JP, Tackenberg S, Padoano E, Hartlief J,  Rautenstengel J, Loeser C, et al. An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks. Procedia Computer Science. 2022;200:194–204.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Herrmann, Jan-Phillip</span> ; <span style=\"font-variant:small-caps;\">Tackenberg, Sven</span> ; <span style=\"font-variant:small-caps;\">Padoano, Elio</span> ; <span style=\"font-variant:small-caps;\">Hartlief, Jörg</span> ; <span style=\"font-variant:small-caps;\"> Rautenstengel, Jens</span> ; <span style=\"font-variant:small-caps;\">Loeser, Christine</span> ; <span style=\"font-variant:small-caps;\">Böhme, Jörg </span>: An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks. In: <i>Procedia Computer Science</i> Bd. 200, Elsevier (2022), S. 194–204","ama":"Herrmann JP, Tackenberg S, Padoano E, et al. An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks. <i>Procedia Computer Science</i>. 2022;200:194-204. doi:<a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>","chicago-de":"Herrmann, Jan-Phillip, Sven Tackenberg, Elio Padoano, Jörg Hartlief, Jens  Rautenstengel, Christine Loeser und Jörg  Böhme. 2022. An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks. <i>Procedia Computer Science</i> 200: 194–204. doi:<a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>, .","short":"J.-P. Herrmann, S. Tackenberg, E. Padoano, J. Hartlief, J.  Rautenstengel, C. Loeser, J. Böhme, Procedia Computer Science 200 (2022) 194–204.","chicago":"Herrmann, Jan-Phillip, Sven Tackenberg, Elio Padoano, Jörg Hartlief, Jens  Rautenstengel, Christine Loeser, and Jörg  Böhme. “An ERP Data Quality Assessment Framework for the Implementation of an APS System Using Bayesian Networks.” <i>Procedia Computer Science</i> 200 (2022): 194–204. <a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>.","ufg":"<b>Herrmann, Jan-Phillip u. a.</b>: An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks, in: <i>Procedia Computer Science</i> 200 (2022),  S. 194–204.","bjps":"<b>Herrmann J-P <i>et al.</i></b> (2022) An ERP Data Quality Assessment Framework for the Implementation of an APS System Using Bayesian Networks. <i>Procedia Computer Science</i> <b>200</b>, 194–204.","apa":"Herrmann, J.-P., Tackenberg, S., Padoano, E., Hartlief, J.,  Rautenstengel, J., Loeser, C., &#38; Böhme, J. (2022). An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks. <i>Procedia Computer Science</i>, <i>200</i>, 194–204. <a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>","havard":"J.-P. Herrmann, S. Tackenberg, E. Padoano, J. Hartlief, J.  Rautenstengel, C. Loeser, J. Böhme, An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks, Procedia Computer Science. 200 (2022) 194–204.","ieee":"J.-P. Herrmann <i>et al.</i>, “An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks,” <i>Procedia Computer Science</i>, vol. 200, pp. 194–204, 2022, doi: <a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>.","mla":"Herrmann, Jan-Phillip, et al. “An ERP Data Quality Assessment Framework for the Implementation of an APS System Using Bayesian Networks.” <i>Procedia Computer Science</i>, vol. 200, 2022, pp. 194–204, <a href=\"https://doi.org/10.1016/j.procs.2022.01.218\">https://doi.org/10.1016/j.procs.2022.01.218</a>."},"type":"journal_article","title":"An ERP Data Quality Assessment Framework for the Implementation of an APS system using Bayesian Networks","language":[{"iso":"eng"}],"date_updated":"2024-08-06T11:45:41Z","date_created":"2023-01-25T12:00:32Z","intvolume":"       200","year":"2022","_id":"9356","publication_status":"published","quality_controlled":"1","author":[{"last_name":"Herrmann","first_name":"Jan-Phillip","id":"75846","full_name":"Herrmann, Jan-Phillip"},{"full_name":"Tackenberg, Sven","id":"71470","first_name":"Sven","last_name":"Tackenberg"},{"full_name":"Padoano, Elio","first_name":"Elio","last_name":"Padoano"},{"full_name":"Hartlief, Jörg","last_name":"Hartlief","first_name":"Jörg"},{"last_name":" Rautenstengel","first_name":"Jens","full_name":" Rautenstengel, Jens"},{"full_name":"Loeser, Christine","last_name":"Loeser","first_name":"Christine"},{"first_name":"Jörg ","last_name":"Böhme","full_name":"Böhme, Jörg "}],"department":[{"_id":"DEP7020"}],"publisher":"Elsevier","page":"194-204","doi":"https://doi.org/10.1016/j.procs.2022.01.218","user_id":"83781","volume":200,"oa":"1","abstract":[{"text":"In today’s manufacturing industry, enterprise-resource-planning (ERP) systems reach their limit when planning and scheduling production subject to multiple objectives and constraints. Advanced planning and scheduling (APS) systems provide these capabilities and are an extension for ERP systems. However, when integrating an APS and ERP system, the ERP data frequently lacks quality, hindering the APS system from working as required. This paper introduces a data quality (DQ) assessment framework that employs a Bayesian Network (BN) to perform quick DQ assessments based on expert interviews and DQ measurements with actual ERP data. We explain the BN’s functionality, design, and validation and show how using the perceived DQ of experts and a semi-supervised learning algorithm improves the BN’s predictions over time. We discuss applying our framework in an APS system implementation project involving an APS system provider and a medium-sized manufacturer of hydraulic cylinders. Despite considering the DQ assessment framework in such a specific context, it is not restricted to a particular domain. We close by discussing the framework’s limits, particularly the BN as a DQ assessment methodology and future works to improve its performance.","lang":"eng"}],"publication_identifier":{"issn":["1877-0509 "]},"publication":"Procedia Computer Science"}