[{"type":"scientific_journal_article","intvolume":"        84","user_id":"83781","_id":"13337","doi":"10.1016/j.jmsy.2025.12.020","place":"Amsterdam","article_type":"original","publication_status":"published","issue":"2","abstract":[{"text":"In manufacturing systems with a job shop organization, queues between workstations create an intermittent process flow, allowing workers to schedule tasks entering the queue based on their needs and preferences. The resulting scheduling autonomy of individual workers often leads to inefficiencies in the overall production process due to the loss of control. Companies are therefore increasingly using algorithmic scheduling systems to assign task sequences to workers, thereby drastically reducing their autonomy and negatively affecting their job performance and well-being. This paper extends the existing flexible job shop scheduling problem by sequencing preferences (FJSPSP) to incorporate a human-centered perspective by predicting workers’ task sequencing decisions using learning-to-rank (LTR) methods. By learning workers’ individual task sequencing preferences, it becomes possible to predict the processing sequence based on task characteristics. The scheduling algorithm for the FJSPSP presented in the paper incorporates workers’ learned sequencing preferences as constraints. Considering workers’ learned task sequencing decisions, the FJSPSP optimizes only task assignments to maintain workers’ autonomy over task sequences. The contributions of this paper are fourfold, namely, (1) presenting an approach to elicit sequencing decision datasets from workers, (2) demonstrating the successful prediction of humans’ and an actual worker’s task sequencing decisions with LTR, (3) formulating the FJSPSP variant that integrates workers’ sequencing preferences as constraints and proving its effectiveness in a simulation study, and (4) consolidating these steps into an explainable artificial intelligence (XAI)- and LTR-enabled sociotechnical system design framework. The paper closes with a discussion of the overall methodology and future research perspectives.","lang":"eng"}],"department":[{"_id":"DEP7027"}],"publisher":"Elsevier BV","quality_controlled":"1","publication":"Journal of Manufacturing Systems","publication_identifier":{"issn":["0278-6125"]},"date_created":"2026-01-12T08:29:09Z","date_updated":"2026-01-12T08:54:27Z","keyword":["Human-centered scheduling","Job autonomy","Learning-to-rank","Flexible job shop scheduling","Human decision-making","Explainable artificial intelligence"],"language":[{"iso":"eng"}],"title":"Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance","citation":{"bjps":"<b>Herrmann J-P <i>et al.</i></b> (2026) Incorporating Scheduling Autonomy of Workers into Flexible Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing Decisions with Overall Scheduling Performance. <i>Journal of Manufacturing Systems</i> <b>84</b>, 541–560.","mla":"Herrmann, Jan-Phillip, et al. “Incorporating Scheduling Autonomy of Workers into Flexible Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing Decisions with Overall Scheduling Performance.” <i>Journal of Manufacturing Systems</i>, vol. 84, no. 2, 2026, pp. 541–60, <a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">https://doi.org/10.1016/j.jmsy.2025.12.020</a>.","havard":"J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance, Journal of Manufacturing Systems. 84 (2026) 541–560.","ufg":"<b>Herrmann, Jan-Phillip u. a.</b>: Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance, in: <i>Journal of Manufacturing Systems</i> 84 (2026), H. 2,  S. 541–560.","van":"Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance. Journal of Manufacturing Systems. 2026;84(2):541–60.","chicago":"Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan, and Verena Nitsch. “Incorporating Scheduling Autonomy of Workers into Flexible Job Shop Scheduling: Learning and Balancing Decentralized Task Sequencing Decisions with Overall Scheduling Performance.” <i>Journal of Manufacturing Systems</i> 84, no. 2 (2026): 541–60. <a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">https://doi.org/10.1016/j.jmsy.2025.12.020</a>.","apa":"Herrmann, J.-P., Tackenberg, S., Srirajan, T. P., &#38; Nitsch, V. (2026). Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance. <i>Journal of Manufacturing Systems</i>, <i>84</i>(2), 541–560. <a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">https://doi.org/10.1016/j.jmsy.2025.12.020</a>","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;\">Srirajan, Tharsika Pakeerathan</span> ; <span style=\"font-variant:small-caps;\">Nitsch, Verena</span>: Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance. In: <i>Journal of Manufacturing Systems</i> Bd. 84. Amsterdam, Elsevier BV (2026), Nr. 2, S. 541–560","chicago-de":"Herrmann, Jan-Phillip, Sven Tackenberg, Tharsika Pakeerathan Srirajan und Verena Nitsch. 2026. Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance. <i>Journal of Manufacturing Systems</i> 84, Nr. 2: 541–560. doi:<a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">10.1016/j.jmsy.2025.12.020</a>, .","short":"J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Journal of Manufacturing Systems 84 (2026) 541–560.","ama":"Herrmann JP, Tackenberg S, Srirajan TP, Nitsch V. Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance. <i>Journal of Manufacturing Systems</i>. 2026;84(2):541-560. doi:<a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">10.1016/j.jmsy.2025.12.020</a>","ieee":"J.-P. Herrmann, S. Tackenberg, T. P. Srirajan, and V. Nitsch, “Incorporating scheduling autonomy of workers into flexible job shop scheduling: Learning and balancing decentralized task sequencing decisions with overall scheduling performance,” <i>Journal of Manufacturing Systems</i>, vol. 84, no. 2, pp. 541–560, 2026, doi: <a href=\"https://doi.org/10.1016/j.jmsy.2025.12.020\">10.1016/j.jmsy.2025.12.020</a>."},"volume":84,"author":[{"id":"86180","full_name":"Herrmann, Jan-Phillip","first_name":"Jan-Phillip","last_name":"Herrmann"},{"id":"71470","first_name":"Sven","last_name":"Tackenberg","full_name":"Tackenberg, Sven"},{"full_name":"Srirajan, Tharsika Pakeerathan","last_name":"Srirajan","first_name":"Tharsika Pakeerathan"},{"full_name":"Nitsch, Verena","last_name":"Nitsch","first_name":"Verena"}],"year":"2026","status":"public","page":"541-560"},{"doi":"10.1016/j.procs.2025.01.244","_id":"13349","language":[{"iso":"eng"}],"keyword":["Task Sequencing","Manufacturing","Learning To Rank","Scheduling Human Factors","Case Study"],"place":"Amsterdam","intvolume":"       253","date_updated":"2026-02-10T10:54:05Z","user_id":"83781","type":"scientific_journal_article","date_created":"2026-01-29T10:15:17Z","publication_identifier":{"issn":["1877-0509"]},"publication":"Procedia Computer Science","quality_controlled":"1","publisher":"Elsevier BV","page":"1820-1829","status":"public","abstract":[{"lang":"eng","text":"In weakly-structured work processes, workers are free to decide in which sequence to process their tasks. Predicting their decision-making helps plan production more accurately while preserving workers’ autonomy. The factors that influence workers’ decision-making depend on the manufacturing process and person considered, and they must be newly collected for each use case. This paper identifies the factors influencing workers when deciding in which sequence to process manufacturing tasks in a medium-sized hydraulic cylinder manufacturer. Five workers and two lead workers were observed and interviewed during several work shifts about influencing factors. The authors propose a new interview technique called indifference testing to overcome subjects’ difficulty articulating their decision-making process. Collected factors were categorized using inductive category formation and context analysis. The analyses identified 75 influencing factors comprising 37 decision attributes and 38 decision rules. The identified decision attributes indicate that worker preferences are influenced by attributes from the classical scheduling literature and attributes related to worker well-being, circadian rhythms, and ergonomics. The identified decision rules are useful constituents of more complex preference functions. The decision attributes and rules enable the construction of machine learning models to predict workers’ task sequencing decisions in job shops. Potential applications include systematically eliminating or controlling influencing factors through workplace design measures to increase worker well-being and optimality of their decisions."}],"department":[{"_id":"DEP7020"}],"author":[{"id":"86180","full_name":"Herrmann, Jan-Phillip","first_name":"Jan-Phillip","last_name":"Herrmann"},{"first_name":"Sven","last_name":"Tackenberg","id":"71470","full_name":"Tackenberg, Sven"},{"first_name":"Florens","last_name":"Burgert","full_name":"Burgert, Florens"},{"full_name":"Nitsch, Verena","last_name":"Nitsch","first_name":"Verena"}],"year":"2025","publication_status":"published","volume":253,"citation":{"ieee":"J.-P. Herrmann, S. Tackenberg, F. Burgert, and V. Nitsch, “Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer,” <i>Procedia Computer Science</i>, vol. 253, pp. 1820–1829, 2025, doi: <a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">10.1016/j.procs.2025.01.244</a>.","ama":"Herrmann JP, Tackenberg S, Burgert F, Nitsch V. Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer. <i>Procedia Computer Science</i>. 2025;253:1820-1829. doi:<a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">10.1016/j.procs.2025.01.244</a>","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;\">Burgert, Florens</span> ; <span style=\"font-variant:small-caps;\">Nitsch, Verena</span>: Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer. In: <i>Procedia Computer Science</i> Bd. 253. Amsterdam, Elsevier BV (2025), S. 1820–1829","chicago-de":"Herrmann, Jan-Phillip, Sven Tackenberg, Florens Burgert und Verena Nitsch. 2025. Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer. <i>Procedia Computer Science</i> 253: 1820–1829. doi:<a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">10.1016/j.procs.2025.01.244</a>, .","short":"J.-P. Herrmann, S. Tackenberg, F. Burgert, V. Nitsch, Procedia Computer Science 253 (2025) 1820–1829.","chicago":"Herrmann, Jan-Phillip, Sven Tackenberg, Florens Burgert, and Verena Nitsch. “Influencing Factors on Worker Task Sequencing Decisions in a Medium-Sized Hydraulic Cylinder Manufacturer.” <i>Procedia Computer Science</i> 253 (2025): 1820–29. <a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">https://doi.org/10.1016/j.procs.2025.01.244</a>.","apa":"Herrmann, J.-P., Tackenberg, S., Burgert, F., &#38; Nitsch, V. (2025). Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer. <i>Procedia Computer Science</i>, <i>253</i>, 1820–1829. <a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">https://doi.org/10.1016/j.procs.2025.01.244</a>","ufg":"<b>Herrmann, Jan-Phillip u. a.</b>: Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer, in: <i>Procedia Computer Science</i> 253 (2025),  S. 1820–1829.","havard":"J.-P. Herrmann, S. Tackenberg, F. Burgert, V. Nitsch, Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer, Procedia Computer Science. 253 (2025) 1820–1829.","bjps":"<b>Herrmann J-P <i>et al.</i></b> (2025) Influencing Factors on Worker Task Sequencing Decisions in a Medium-Sized Hydraulic Cylinder Manufacturer. <i>Procedia Computer Science</i> <b>253</b>, 1820–1829.","mla":"Herrmann, Jan-Phillip, et al. “Influencing Factors on Worker Task Sequencing Decisions in a Medium-Sized Hydraulic Cylinder Manufacturer.” <i>Procedia Computer Science</i>, vol. 253, 2025, pp. 1820–29, <a href=\"https://doi.org/10.1016/j.procs.2025.01.244\">https://doi.org/10.1016/j.procs.2025.01.244</a>.","van":"Herrmann JP, Tackenberg S, Burgert F, Nitsch V. Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer. Procedia Computer Science. 2025;253:1820–9."},"title":"Influencing factors on worker task sequencing decisions in a medium-sized hydraulic cylinder manufacturer"},{"keyword":["Flexible Job Shop Scheduling","Learning To Rank","Erklärbare Künstliche Intelligenz","Planungsautonomie","Simulation"],"language":[{"iso":"eng"}],"oa":"1","date_updated":"2026-02-10T12:24:29Z","corporate_editor":["Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin"],"publication_identifier":{"eisbn":["978-3-936804-36-2"]},"publication":"Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit","date_created":"2026-01-29T10:20:46Z","status":"public","page":"415-420","year":"2025","main_file_link":[{"url":"https://www.gesellschaft-fuer-arbeitswissenschaft.de/publikationen_gfa-press-tagungsband.htm","open_access":"1"}],"author":[{"id":"75846","last_name":"Herrmann","full_name":"Herrmann, Jan-Phillip","first_name":"Jan-Phillip"},{"first_name":"Sven","id":"71470","last_name":"Tackenberg","full_name":"Tackenberg, Sven"},{"first_name":"Verena","last_name":"Nitsch","full_name":"Nitsch, Verena"}],"citation":{"chicago":"Herrmann, Jan-Phillip, Sven Tackenberg, and Verena Nitsch. <i>Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen</i>. Edited by Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin. <i>Arbeit 5.0: Menschzentrierte Innovationen Für Die Zukunft Der Arbeit</i>. Sankt Augustin: GfA-Press, 2025. <a href=\"https://doi.org/10.61063/FK2025\">https://doi.org/10.61063/FK2025</a>.","apa":"Herrmann, J.-P., Tackenberg, S., &#38; Nitsch, V. (2025). Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen. In Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin (Ed.), <i>Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit</i> (pp. 415–420). GfA-Press. <a href=\"https://doi.org/10.61063/FK2025\">https://doi.org/10.61063/FK2025</a>","havard":"J.-P. Herrmann, S. Tackenberg, V. Nitsch, Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen, GfA-Press, Sankt Augustin, 2025.","mla":"Herrmann, Jan-Phillip, et al. “Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen.” <i>Arbeit 5.0: Menschzentrierte Innovationen Für Die Zukunft Der Arbeit</i>, edited by Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin, GfA-Press, 2025, pp. 415–20, <a href=\"https://doi.org/10.61063/FK2025\">https://doi.org/10.61063/FK2025</a>.","bjps":"<b>Herrmann J-P, Tackenberg S and Nitsch V</b> (2025) <i>Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen</i>, Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin (ed.). Sankt Augustin: GfA-Press.","ufg":"<b>Herrmann, Jan-Phillip/Tackenberg, Sven/Nitsch, Verena</b>: Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen, hg. von Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin, Sankt Augustin 2025.","van":"Herrmann JP, Tackenberg S, Nitsch V. Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen. Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin, editor. Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit. Sankt Augustin: GfA-Press; 2025.","chicago-de":"Herrmann, Jan-Phillip, Sven Tackenberg und Verena Nitsch. 2025. <i>Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen</i>. Hg. von Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin. <i>Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit</i>. Sankt Augustin: GfA-Press. doi:<a href=\"https://doi.org/10.61063/FK2025\">10.61063/FK2025</a>, .","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;\">Nitsch, Verena</span> ; <span style=\"font-variant:small-caps;\">Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin</span> (Hrsg.): <i>Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen</i>. Sankt Augustin : GfA-Press, 2025","short":"J.-P. Herrmann, S. Tackenberg, V. Nitsch, Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen, GfA-Press, Sankt Augustin, 2025.","ieee":"J.-P. Herrmann, S. Tackenberg, and V. Nitsch, <i>Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen</i>. Sankt Augustin: GfA-Press, 2025, pp. 415–420. doi: <a href=\"https://doi.org/10.61063/FK2025\">10.61063/FK2025</a>.","ama":"Herrmann JP, Tackenberg S, Nitsch V. <i>Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen</i>. (Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin, ed.). GfA-Press; 2025:415-420. doi:<a href=\"https://doi.org/10.61063/FK2025\">10.61063/FK2025</a>"},"title":"Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen","place":"Sankt Augustin","_id":"13350","doi":"10.61063/FK2025","user_id":"83781","type":"conference_editor_article","publisher":"GfA-Press","conference":{"name":"71. Kongress der Gesellschaft für Arbeitswissenschaft e.V.","location":"Aachen","start_date":"2025-03-25","end_date":"2025-03-27"},"department":[{"_id":"DEP7020"}],"abstract":[{"text":"In einer humanzentrierten Kleinserien- und Einzelfertigung mit Werkstattorganisation verfügen Fertigungsmitarbeitende häufig über eine hohe Autonomie und Entscheidungsfreiheit. Das Zusammenspiel individueller Planungsstrategien von Mitarbeitenden innerhalb eines Fertigungsprozesses kann sich positiv als auch negativ auf das Erreichen der produktionslogistischen Zielgrößen auswirken. In diesem Beitrag wird eine Variante des Flexible Job Shop Scheduling Problems vorgestellt, welches das Entscheidungsverhalten autonomer Arbeitspersonen bezüglich der Bearbeitungsreihenfolgebildung berücksichtigt. Weiterhin wird die Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen durch die Analyse individueller Planungsstrategien von Arbeitspersonen mittels Methoden der erklärbaren künstlichen Intelligenz demonstriert. Betrachtungsgegenstand der Analyse ist die Entscheidung von Arbeitspersonen, in welcher Reihenfolge sie ihre täglichen Aufgaben abarbeiten. Der Beitrag schließt mit einer Diskussion über die Nutzung der vorgestellten Verfahren zur Ableitung von arbeitsorganisatorischen Gestaltungsempfehlungen.","lang":"ger"}],"publication_status":"published"},{"keyword":["biological methanation","CSTR","Methanothermobacter marburgensis","methane","carbon dioxide","dinitrogen","hydrogen","power-to-gas"],"language":[{"iso":"eng"}],"oa":"1","date_updated":"2024-05-17T11:23:55Z","publication_identifier":{"issn":["2311-5637"]},"publication":"Fermentation","date_created":"2019-07-30T09:33:08Z","status":"public","author":[{"full_name":"Hoffarth, Marc Philippe","first_name":"Marc Philippe","id":"42198","last_name":"Hoffarth"},{"first_name":"Timo","last_name":"Broeker","id":"43927","full_name":"Broeker, Timo"},{"last_name":"Schneider","first_name":"Jan","id":"13209","full_name":"Schneider, Jan","orcid":"0000-0001-6401-8873"}],"year":"2019","main_file_link":[{"url":"https://www.mdpi.com/2311-5637/5/3/56","open_access":"1"}],"citation":{"short":"M.P. Hoffarth, T. Broeker, J. Schneider, Fermentation 5 (2019).","chicago-de":"Hoffarth, Marc Philippe, Timo Broeker und Jan Schneider. 2019. Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis. <i>Fermentation</i> 5, Nr. 3. doi:<a href=\"https://doi.org/10.3390/fermentation5030056\">10.3390/fermentation5030056</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Hoffarth, Marc Philippe</span> ; <span style=\"font-variant:small-caps;\">Broeker, Timo</span> ; <span style=\"font-variant:small-caps;\">Schneider, Jan</span>: Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis. In: <i>Fermentation</i> Bd. 5, MDPI  (2019), Nr. 3","van":"Hoffarth MP, Broeker T, Schneider J. Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis. Fermentation. 2019;5(3).","bjps":"<b>Hoffarth MP, Broeker T and Schneider J</b> (2019) Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter Marburgensis. <i>Fermentation</i> <b>5</b>.","mla":"Hoffarth, Marc Philippe, et al. “Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter Marburgensis.” <i>Fermentation</i>, vol. 5, no. 3, 56, 2019, <a href=\"https://doi.org/10.3390/fermentation5030056\">https://doi.org/10.3390/fermentation5030056</a>.","havard":"M.P. Hoffarth, T. Broeker, J. Schneider, Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis, Fermentation. 5 (2019).","ufg":"<b>Hoffarth, Marc Philippe/Broeker, Timo/Schneider, Jan</b>: Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis, in: <i>Fermentation</i> 5 (2019), H. 3.","apa":"Hoffarth, M. P., Broeker, T., &#38; Schneider, J. (2019). Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis. <i>Fermentation</i>, <i>5</i>(3), Article 56. <a href=\"https://doi.org/10.3390/fermentation5030056\">https://doi.org/10.3390/fermentation5030056</a>","chicago":"Hoffarth, Marc Philippe, Timo Broeker, and Jan Schneider. “Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter Marburgensis.” <i>Fermentation</i> 5, no. 3 (2019). <a href=\"https://doi.org/10.3390/fermentation5030056\">https://doi.org/10.3390/fermentation5030056</a>.","ama":"Hoffarth MP, Broeker T, Schneider J. Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis. <i>Fermentation</i>. 2019;5(3). doi:<a href=\"https://doi.org/10.3390/fermentation5030056\">10.3390/fermentation5030056</a>","ieee":"M. P. Hoffarth, T. Broeker, and J. Schneider, “Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis,” <i>Fermentation</i>, vol. 5, no. 3, Art. no. 56, 2019, doi: <a href=\"https://doi.org/10.3390/fermentation5030056\">10.3390/fermentation5030056</a>."},"volume":5,"title":"Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis","_id":"1721","article_number":"56","doi":"10.3390/fermentation5030056","intvolume":"         5","user_id":"83778","type":"journal_article","publisher":"MDPI ","issue":"3","abstract":[{"lang":"eng","text":"In this contribution, the effect of the presence of a presumed inert gas like N2 in the feed gas on the biological methanation of hydrogen and carbon dioxide with Methanothermobacter marburgensis was investigated. N2 can be found as a component besides CO2 in possible feed gases like mine gas, weak gas, or steel mill gas. To determine whether there is an effect on the biological methanation of CO2 and H2 from renewable sources or not, the process was investigated using feed gases containing CO2, H2, and N2 in different ratios, depending on the CO2 content. A possible effect can be a lowered conversion rate of CO2 and H2 to CH4. Feed gases containing up to 47N2 were investigated. The conversion of hydrogen and carbon dioxide was possible with a conversion rate of up to 91 but was limited by the amount of H2 when feeding a stoichiometric ratio of 4:1 and not by adding N2 to the feed gas.</jats:p>"}],"department":[{"_id":"DEP4018"}],"publication_status":"published"},{"user_id":"45673","type":"conference","_id":"599","place":"Lemgo","publication_status":"published","issue":"1","abstract":[{"lang":"eng","text":"Order picking has long been identified as the most labor costly and intensively activity in warehouse management. The orders from the customers need to be fulfilled tightly and timely. In order to keep the required high service level, the warehouse has to increase the picking productivity under the constraints of limited capacity. This paper concerns a man-togoods order picking system, in which the order pickers have to drive with a pallet jack to the storage locations. Considering that the orders are mostly small orders which consist of less lines, it is efficient to combine severalsingle customer orders into one picking order. Under this circumstance, this paper intends to answer the question of how customer orders should be grouped into picking orders with the aim of minimizing the total travel length through the warehouse. Consequently the productivity of the order picking system can be improved. An optimization problem for order batching is introduced. The optimization method of order batching is then proposed. Based on the simulation of different scenarios of incoming orders, it can be concluded that the developed method is effective in improving the productivity of the concerned order picking system.\r\n"}],"conference":{"start_date":"2015-10-01","end_date":"2015-10-02","location":"Trieste, Italy","name":"Proceedings5th International Conference"},"department":[{"_id":"DEP7000"},{"_id":"DEP1306"}],"editor":[{"last_name":"Padoano","full_name":"Padoano, Elio","first_name":"Elio"},{"full_name":"Villmer, Franz-Josef","first_name":"Franz-Josef","last_name":"Villmer"}],"corporate_editor":["Department of Production Engineering and Management","Hochschule Ostwestfalen-Lippe"],"related_material":{"link":[{"relation":"contains","url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf"}]},"date_updated":"2023-03-15T13:50:03Z","date_created":"2019-02-19T07:34:56Z","publication":"Production Engineering and Management","publication_identifier":{"isbn":["978-3-941645-11-0"]},"language":[{"iso":"eng"}],"keyword":["Order picking","man-to-goods","order batching","picking productivity","genetic algorithm"],"oa":"1","citation":{"chicago":"Li, Li, and L. Schulze. “Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching.” In <i>Production Engineering and Management</i>, edited by Elio Padoano, Franz-Josef Villmer, and Department of Production Engineering and Management, 319–26. Lemgo, 2015.","apa":"Li, L., &#38; Schulze, L. (2015). Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. In E. Padoano, F.-J. Villmer, &#38; Department of Production Engineering and Management (Eds.), <i>Production Engineering and Management</i> (pp. 319–326). Lemgo.","ufg":"<b>Li, Li/Schulze, L. (2015)</b>: Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching, in: Elio Padoano et. al. (Hgg.): <i>Production Engineering and Management</i>, Lemgo, S. 319–326.","mla":"Li, Li, and L. Schulze. “Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching.” <i>Production Engineering and Management</i>, edited by Elio Padoano et al., no. 1, 2015, pp. 319–26.","havard":"L. Li, L. Schulze, Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management (Eds.), Production Engineering and Management, Lemgo, 2015: pp. 319–326.","bjps":"<b>Li L and Schulze L</b> (2015) Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. In Padoano E, Villmer F-J and Department of Production Engineering and Management (eds), <i>Production Engineering and Management</i>. Lemgo, pp. 319–326.","van":"Li L, Schulze L. Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. In: Padoano E, Villmer F-J, Department of Production Engineering and Management, editors. Production Engineering and Management. Lemgo; 2015. p. 319–26.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Li, Li</span> ; <span style=\"font-variant:small-caps;\">Schulze, L.</span>: Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. 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>. Lemgo, 2015, S. 319–326","chicago-de":"Li, Li und L. Schulze. 2015. Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. In: <i>Production Engineering and Management</i>, hg. von Elio Padoano, Franz-Josef Villmer, und Department of Production Engineering and Management, 319–326. Lemgo.","short":"L. Li, L. Schulze, in: E. Padoano, F.-J. Villmer, Department of Production Engineering and Management (Eds.), Production Engineering and Management, Lemgo, 2015, pp. 319–326.","ieee":"L. Li and L. Schulze, “Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching,” in <i>Production Engineering and Management</i>, Trieste, Italy, 2015, no. 1, pp. 319–326.","ama":"Li L, Schulze L. Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching. In: Padoano E, Villmer F-J, Department of Production Engineering and Management, eds. <i>Production Engineering and Management</i>. Lemgo; 2015:319-326."},"title":"Improving the Productivity of a Man-to-Goods Order Picking System through Optimization of Order Batching","page":"319-326","status":"public","year":2015,"main_file_link":[{"open_access":"1","url":"https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf"}],"author":[{"full_name":"Li, Li","id":"58482","last_name":"Li","first_name":"Li"},{"full_name":"Schulze, L.","first_name":"L.","last_name":"Schulze"}]}]