Case study on delivery time determination using a machine learning approach in small batch production companies

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Authors

Delivery times represent a key factor influencing the competitive advantage, as manufacturing companies strive for timely and reliable deliveries. As companies face multiple challenges involved with meeting established delivery dates, research on the accurate estimation of delivery dates has been source of interest for decades. In recent years, the use of machine learning techniques in the field of production planning and control has unlocked new opportunities, in both academia and industry practice. In fact, with the increased availability of data across various levels of manufacturing companies, machine learning techniques offer the opportunity to gain valuable and accurate insights about production processes. However, machine learning-based approaches for the prediction of delivery dates have not received sufficient attention. Thus, this study aims to investigate the ability of machine learning to predict delivery dates early in the ordering process, and what type of information is required to obtain accurate predictions. Based on the data provided by two separate manufacturing companies, this paper presents a machine learning-based approach for predicting delivery times as soon as a request for an offer is received considering the desired customer delivery date as a feature.
Titel in ÜbersetzungFallstudie: Lieferterminbestimmung in der Kleinserienproduktion mittels maschinellen Lernens
OriginalspracheEnglisch
ZeitschriftJournal of Intelligent Manufacturing
Jahrgang35
Ausgabenummer8
Seiten (von - bis)3937-3958
Anzahl der Seiten22
ISSN0956-5515
DOIs
PublikationsstatusErschienen - 12.2024

Bibliographische Notiz

Publisher Copyright:
© The Author(s) 2024.

DOI

Zuletzt angesehen

Publikationen

  1. A Robust Decoupling Estimator to Indentify Electrical Parameters for Three-Phase Permanent Magnet Synchronous Motors
  2. Self-regulated learning and self assessment in online mathematics bridging courses
  3. Anticipated imitation of multiple agents
  4. Increasing personal initiative in small business managers or owners leads to entrepreneurial success: A theory-based controlled randomized field intervention for evidence-based management
  5. Effects of tree diversity on canopy space occupation vary with tree size and canopy space definition in a mature broad-leaved forest
  6. Environmental performance, carbon performance and earnings management
  7. Dimension theoretical properties of generalized Baker's transformations
  8. Cascade MIMO P-PID Controllers Applied in an Over-actuated Quadrotor Tilt-Rotor
  9. Trade Dynamics, Trade Costs and Market Size: First Evidence from the Exporter and Importer Dynamics Database for Germany
  10. Motion-decoupled internal force control in grasping with visco-elastic contacts
  11. Nitrogen uptake by grassland communities
  12. Deliberative mapping of ecosystem services within and around Doñana National Park (SW Spain) in relation to land use change
  13. The role of the situation model in mathematical modelling
  14. Investigation of the deformation behavior of Fe-3%Si sheet metal with large grains via crystal plasticity and finite-element modeling
  15. Effects of Soil Properties, Temperature and Disturbance on Diversity and Functional Composition of Plant Communities Along a Steep Elevational Gradient on Tenerife
  16. PyFin-sentiment
  17. Green deserts, but not always
  18. Evidence on copula-based double-hurdle models with flexible margins
  19. Deep Rolling for Tailoring Residual Stresses of AA2024 Sheet Metals
  20. User experience predicts the effectiveness of a gamified recovery app
  21. A PD Fuzzy Control of a Nonholonomic Car-Like Robot for Drive Assistant Systems
  22. Land-use change differentially affects endemic, forest andopen-land butterflies in Madagascar
  23. Modeling of Friction-Induced Vibrations during Tightening of Bolted Joints