---
_id: '13337'
abstract:
- lang: eng
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.
article_type: original
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '86180'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Tharsika Pakeerathan
full_name: Srirajan, Tharsika Pakeerathan
last_name: Srirajan
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
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. Journal
of Manufacturing Systems. 2026;84(2):541-560. doi:10.1016/j.jmsy.2025.12.020'
apa: 'Herrmann, J.-P., Tackenberg, S., Srirajan, T. P., & Nitsch, V. (2026).
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(2), 541–560. https://doi.org/10.1016/j.jmsy.2025.12.020'
bjps: 'Herrmann J-P et al. (2026) 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, 541–560.'
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.” Journal of Manufacturing Systems
84, no. 2 (2026): 541–60. https://doi.org/10.1016/j.jmsy.2025.12.020.'
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. Journal of Manufacturing Systems 84,
Nr. 2: 541–560. doi:10.1016/j.jmsy.2025.12.020,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Srirajan,
Tharsika Pakeerathan ; Nitsch, Verena:
Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance. In: Journal of Manufacturing Systems Bd. 84. Amsterdam, Elsevier
BV (2026), Nr. 2, S. 541–560'
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.'
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,”
Journal of Manufacturing Systems, vol. 84, no. 2, pp. 541–560, 2026, doi:
10.1016/j.jmsy.2025.12.020.'
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.” Journal of Manufacturing Systems,
vol. 84, no. 2, 2026, pp. 541–60, https://doi.org/10.1016/j.jmsy.2025.12.020.'
short: J.-P. Herrmann, S. Tackenberg, T.P. Srirajan, V. Nitsch, Journal of Manufacturing
Systems 84 (2026) 541–560.
ufg: 'Herrmann, Jan-Phillip u. a.: Incorporating scheduling autonomy of workers
into flexible job shop scheduling: Learning and balancing decentralized task sequencing
decisions with overall scheduling performance, in: Journal of Manufacturing
Systems 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.'
date_created: 2026-01-12T08:29:09Z
date_updated: 2026-01-12T08:54:27Z
department:
- _id: DEP7027
doi: 10.1016/j.jmsy.2025.12.020
intvolume: ' 84'
issue: '2'
keyword:
- Human-centered scheduling
- Job autonomy
- Learning-to-rank
- Flexible job shop scheduling
- Human decision-making
- Explainable artificial intelligence
language:
- iso: eng
page: 541-560
place: Amsterdam
publication: Journal of Manufacturing Systems
publication_identifier:
issn:
- 0278-6125
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: 'Incorporating scheduling autonomy of workers into flexible job shop scheduling:
Learning and balancing decentralized task sequencing decisions with overall scheduling
performance'
type: scientific_journal_article
user_id: '83781'
volume: 84
year: '2026'
...
---
_id: '13349'
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.
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '86180'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Florens
full_name: Burgert, Florens
last_name: Burgert
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 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;253:1820-1829. doi:10.1016/j.procs.2025.01.244
apa: Herrmann, J.-P., Tackenberg, S., Burgert, F., & Nitsch, V. (2025). Influencing
factors on worker task sequencing decisions in a medium-sized hydraulic cylinder
manufacturer. Procedia Computer Science, 253, 1820–1829. https://doi.org/10.1016/j.procs.2025.01.244
bjps: Herrmann J-P et al. (2025) Influencing Factors on Worker Task
Sequencing Decisions in a Medium-Sized Hydraulic Cylinder Manufacturer. Procedia
Computer Science 253, 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.” Procedia Computer Science 253 (2025): 1820–29.
https://doi.org/10.1016/j.procs.2025.01.244.'
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. Procedia Computer Science 253: 1820–1829.
doi:10.1016/j.procs.2025.01.244,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Burgert,
Florens ; Nitsch, Verena:
Influencing factors on worker task sequencing decisions in a medium-sized hydraulic
cylinder manufacturer. In: Procedia Computer Science Bd. 253. Amsterdam,
Elsevier BV (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.
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,”
Procedia Computer Science, vol. 253, pp. 1820–1829, 2025, doi: 10.1016/j.procs.2025.01.244.'
mla: Herrmann, Jan-Phillip, et al. “Influencing Factors on Worker Task Sequencing
Decisions in a Medium-Sized Hydraulic Cylinder Manufacturer.” Procedia Computer
Science, vol. 253, 2025, pp. 1820–29, https://doi.org/10.1016/j.procs.2025.01.244.
short: J.-P. Herrmann, S. Tackenberg, F. Burgert, V. Nitsch, Procedia Computer Science
253 (2025) 1820–1829.
ufg: 'Herrmann, Jan-Phillip u. a.: Influencing factors on worker task sequencing
decisions in a medium-sized hydraulic cylinder manufacturer, in: Procedia Computer
Science 253 (2025), S. 1820–1829.'
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.
date_created: 2026-01-29T10:15:17Z
date_updated: 2026-02-10T10:54:05Z
department:
- _id: DEP7020
doi: 10.1016/j.procs.2025.01.244
intvolume: ' 253'
keyword:
- Task Sequencing
- Manufacturing
- Learning To Rank
- Scheduling Human Factors
- Case Study
language:
- iso: eng
page: 1820-1829
place: Amsterdam
publication: Procedia Computer Science
publication_identifier:
issn:
- 1877-0509
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: Influencing factors on worker task sequencing decisions in a medium-sized hydraulic
cylinder manufacturer
type: scientific_journal_article
user_id: '83781'
volume: 253
year: '2025'
...
---
_id: '13350'
abstract:
- lang: ger
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.
author:
- first_name: Jan-Phillip
full_name: Herrmann, Jan-Phillip
id: '75846'
last_name: Herrmann
- first_name: Sven
full_name: Tackenberg, Sven
id: '71470'
last_name: Tackenberg
- first_name: Verena
full_name: Nitsch, Verena
last_name: Nitsch
citation:
ama: 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, ed.). GfA-Press; 2025:415-420. doi:10.61063/FK2025
apa: 'Herrmann, J.-P., Tackenberg, S., & 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.), Arbeit 5.0: Menschzentrierte Innovationen für die
Zukunft der Arbeit (pp. 415–420). GfA-Press. https://doi.org/10.61063/FK2025'
bjps: 'Herrmann J-P, Tackenberg S and Nitsch V (2025) Analyse Der Entscheidungsfindung
von Fertigungsmitarbeitenden Durch Erklärbare Künstliche Intelligenz Zur Ableitung
Arbeitsorganisatorischer Gestaltungsempfehlungen, Gesellschaft für Arbeitswissenschaft
e.V. Sankt Augustin (ed.). Sankt Augustin: GfA-Press.'
chicago: 'Herrmann, Jan-Phillip, Sven Tackenberg, and Verena Nitsch. Analyse
Der Entscheidungsfindung von Fertigungsmitarbeitenden Durch Erklärbare Künstliche
Intelligenz Zur Ableitung Arbeitsorganisatorischer Gestaltungsempfehlungen.
Edited by Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin. Arbeit
5.0: Menschzentrierte Innovationen Für Die Zukunft Der Arbeit. Sankt Augustin:
GfA-Press, 2025. https://doi.org/10.61063/FK2025.'
chicago-de: 'Herrmann, Jan-Phillip, Sven Tackenberg und Verena Nitsch. 2025. Analyse
der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare künstliche
Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen.
Hg. von Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin. Arbeit 5.0:
Menschzentrierte Innovationen für die Zukunft der Arbeit. Sankt Augustin:
GfA-Press. doi:10.61063/FK2025,
.'
din1505-2-1: 'Herrmann, Jan-Phillip
; Tackenberg, Sven ; Nitsch,
Verena ; Gesellschaft für Arbeitswissenschaft
e.V. Sankt Augustin (Hrsg.): Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden
durch erklärbare künstliche Intelligenz zur Ableitung arbeitsorganisatorischer
Gestaltungsempfehlungen. Sankt Augustin : GfA-Press, 2025'
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.
ieee: 'J.-P. Herrmann, S. Tackenberg, and V. Nitsch, Analyse der Entscheidungsfindung
von Fertigungsmitarbeitenden durch erklärbare künstliche Intelligenz zur Ableitung
arbeitsorganisatorischer Gestaltungsempfehlungen. Sankt Augustin: GfA-Press,
2025, pp. 415–420. doi: 10.61063/FK2025.'
mla: 'Herrmann, Jan-Phillip, et al. “Analyse Der Entscheidungsfindung von Fertigungsmitarbeitenden
Durch Erklärbare Künstliche Intelligenz Zur Ableitung Arbeitsorganisatorischer
Gestaltungsempfehlungen.” Arbeit 5.0: Menschzentrierte Innovationen Für Die
Zukunft Der Arbeit, edited by Gesellschaft für Arbeitswissenschaft e.V. Sankt
Augustin, GfA-Press, 2025, pp. 415–20, https://doi.org/10.61063/FK2025.'
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.
ufg: 'Herrmann, Jan-Phillip/Tackenberg, Sven/Nitsch, Verena: 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.'
conference:
end_date: 2025-03-27
location: Aachen
name: 71. Kongress der Gesellschaft für Arbeitswissenschaft e.V.
start_date: 2025-03-25
corporate_editor:
- Gesellschaft für Arbeitswissenschaft e.V. Sankt Augustin
date_created: 2026-01-29T10:20:46Z
date_updated: 2026-02-10T12:24:29Z
department:
- _id: DEP7020
doi: 10.61063/FK2025
keyword:
- Flexible Job Shop Scheduling
- Learning To Rank
- Erklärbare Künstliche Intelligenz
- Planungsautonomie
- Simulation
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.gesellschaft-fuer-arbeitswissenschaft.de/publikationen_gfa-press-tagungsband.htm
oa: '1'
page: 415-420
place: Sankt Augustin
publication: 'Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit'
publication_identifier:
eisbn:
- 978-3-936804-36-2
publication_status: published
publisher: GfA-Press
status: public
title: Analyse der Entscheidungsfindung von Fertigungsmitarbeitenden durch erklärbare
künstliche Intelligenz zur Ableitung arbeitsorganisatorischer Gestaltungsempfehlungen
type: conference_editor_article
user_id: '83781'
year: '2025'
...
---
_id: '1721'
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.
article_number: '56'
author:
- first_name: Marc Philippe
full_name: Hoffarth, Marc Philippe
id: '42198'
last_name: Hoffarth
- first_name: Timo
full_name: Broeker, Timo
id: '43927'
last_name: Broeker
- first_name: Jan
full_name: Schneider, Jan
id: '13209'
last_name: Schneider
orcid: 0000-0001-6401-8873
citation:
ama: 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). doi:10.3390/fermentation5030056
apa: Hoffarth, M. P., Broeker, T., & Schneider, J. (2019). Effect of N2 on Biological
Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis.
Fermentation, 5(3), Article 56. https://doi.org/10.3390/fermentation5030056
bjps: Hoffarth MP, Broeker T and Schneider J (2019) Effect of N2 on Biological
Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter Marburgensis.
Fermentation 5.
chicago: Hoffarth, Marc Philippe, Timo Broeker, and Jan Schneider. “Effect of N2
on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter
Marburgensis.” Fermentation 5, no. 3 (2019). https://doi.org/10.3390/fermentation5030056.
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. Fermentation 5, Nr. 3. doi:10.3390/fermentation5030056,
.
din1505-2-1: 'Hoffarth, Marc Philippe
; Broeker, Timo ; Schneider,
Jan: Effect of N2 on Biological Methanation in a Continuous Stirred-Tank
Reactor with Methanothermobacter marburgensis. In: Fermentation Bd. 5,
MDPI (2019), Nr. 3'
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).
ieee: 'M. P. Hoffarth, T. Broeker, and J. Schneider, “Effect of N2 on Biological
Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter marburgensis,”
Fermentation, vol. 5, no. 3, Art. no. 56, 2019, doi: 10.3390/fermentation5030056.'
mla: Hoffarth, Marc Philippe, et al. “Effect of N2 on Biological Methanation in
a Continuous Stirred-Tank Reactor with Methanothermobacter Marburgensis.” Fermentation,
vol. 5, no. 3, 56, 2019, https://doi.org/10.3390/fermentation5030056.
short: M.P. Hoffarth, T. Broeker, J. Schneider, Fermentation 5 (2019).
ufg: 'Hoffarth, Marc Philippe/Broeker, Timo/Schneider, Jan: Effect of N2
on Biological Methanation in a Continuous Stirred-Tank Reactor with Methanothermobacter
marburgensis, in: Fermentation 5 (2019), H. 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).
date_created: 2019-07-30T09:33:08Z
date_updated: 2024-05-17T11:23:55Z
department:
- _id: DEP4018
doi: 10.3390/fermentation5030056
intvolume: ' 5'
issue: '3'
keyword:
- biological methanation
- CSTR
- Methanothermobacter marburgensis
- methane
- carbon dioxide
- dinitrogen
- hydrogen
- power-to-gas
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/2311-5637/5/3/56
oa: '1'
publication: Fermentation
publication_identifier:
issn:
- 2311-5637
publication_status: published
publisher: 'MDPI '
status: public
title: Effect of N2 on Biological Methanation in a Continuous Stirred-Tank Reactor
with Methanothermobacter marburgensis
type: journal_article
user_id: '83778'
volume: 5
year: '2019'
...
---
_id: '599'
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"
author:
- first_name: Li
full_name: Li, Li
id: '58482'
last_name: Li
- first_name: L.
full_name: Schulze, L.
last_name: Schulze
citation:
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. Production Engineering and Management.
Lemgo; 2015:319-326.'
apa: Li, L., & 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, & Department of Production Engineering and Management (Eds.), Production
Engineering and Management (pp. 319–326). Lemgo.
bjps: Li L and Schulze L (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), Production
Engineering and Management. Lemgo, pp. 319–326.
chicago: Li, Li, and L. Schulze. “Improving the Productivity of a Man-to-Goods Order
Picking System through Optimization of Order Batching.” In Production Engineering
and Management, edited by Elio Padoano, Franz-Josef Villmer, and Department
of Production Engineering and Management, 319–26. Lemgo, 2015.
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: Production
Engineering and Management, hg. von Elio Padoano, Franz-Josef Villmer, und
Department of Production Engineering and Management, 319–326. Lemgo.'
din1505-2-1: 'Li, Li ; 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
(Hrsg.): Production Engineering and Management. Lemgo, 2015, S. 319–326'
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.'
ieee: L. Li and L. Schulze, “Improving the Productivity of a Man-to-Goods Order
Picking System through Optimization of Order Batching,” in Production Engineering
and Management, Trieste, Italy, 2015, no. 1, pp. 319–326.
mla: Li, Li, and L. Schulze. “Improving the Productivity of a Man-to-Goods Order
Picking System through Optimization of Order Batching.” Production Engineering
and Management, edited by Elio Padoano et al., no. 1, 2015, pp. 319–26.
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.'
ufg: 'Li, Li/Schulze, L. (2015): Improving the Productivity of a Man-to-Goods
Order Picking System through Optimization of Order Batching, in: Elio Padoano
et. al. (Hgg.): Production Engineering and Management, Lemgo, S. 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.'
conference:
end_date: 2015-10-02
location: Trieste, Italy
name: Proceedings5th International Conference
start_date: 2015-10-01
corporate_editor:
- Department of Production Engineering and Management
- Hochschule Ostwestfalen-Lippe
date_created: 2019-02-19T07:34:56Z
date_updated: 2023-03-15T13:50:03Z
department:
- _id: DEP7000
- _id: DEP1306
editor:
- first_name: Elio
full_name: Padoano, Elio
last_name: Padoano
- first_name: Franz-Josef
full_name: Villmer, Franz-Josef
last_name: Villmer
issue: '1'
keyword:
- Order picking
- man-to-goods
- order batching
- picking productivity
- genetic algorithm
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf
oa: '1'
page: 319-326
place: Lemgo
publication: Production Engineering and Management
publication_identifier:
isbn:
- 978-3-941645-11-0
publication_status: published
related_material:
link:
- relation: contains
url: https://www.hs-owl.de/fileadmin/diman/Veroeffentlichungen/PEM_Tagung_zusammen2015.pdf
status: public
title: Improving the Productivity of a Man-to-Goods Order Picking System through Optimization
of Order Batching
type: conference
user_id: '45673'
year: 2015
...