Skip to main content

Sale until 1 Feb: Up to 30% off selected books.

Springer Vieweg

Machine Learning-based Prediction of Missing Parts for Assembly

No reviews yet
Product Code: 9783658450328
ISBN13: 9783658450328
Condition: New
$117.02
Manufacturing companies face challenges in managing increasing process complexity while meeting demands for on-time delivery, particularly evident during critical processes like assembly. The early identification of potential missing parts at the beginning assembly emerges as a crucial strategy to uphold delivery commitments. This book embarks on developing machine learning-based prediction models to tackle this challenge. Through a systemic literature review, deficiencies in current predictive methodologies are highlighted, notably the underutilization of material data and a late prediction capability within the procurement process. Through case studies within the machine industry a significant influence of material data on the quality of models predicting missing parts from in-house production was verified. Further, a model for predicting delivery delays in the purchasing process was implemented, which makes it possible to predict potential missing parts from suppliers at the time of ordering. These advancements serve as indispensable tools for production planners and procurement professionals, empowering them to proactively address material availability challenges for assembly operations.


Author: Fabian Steinberg
Publisher: Springer Vieweg
Publication Date: Jun 20, 2024
Number of Pages: NA pages
Language: English
Binding: Paperback
ISBN-10: 3658450320
ISBN-13: 9783658450328

Machine Learning-based Prediction of Missing Parts for Assembly

$117.02
 
Manufacturing companies face challenges in managing increasing process complexity while meeting demands for on-time delivery, particularly evident during critical processes like assembly. The early identification of potential missing parts at the beginning assembly emerges as a crucial strategy to uphold delivery commitments. This book embarks on developing machine learning-based prediction models to tackle this challenge. Through a systemic literature review, deficiencies in current predictive methodologies are highlighted, notably the underutilization of material data and a late prediction capability within the procurement process. Through case studies within the machine industry a significant influence of material data on the quality of models predicting missing parts from in-house production was verified. Further, a model for predicting delivery delays in the purchasing process was implemented, which makes it possible to predict potential missing parts from suppliers at the time of ordering. These advancements serve as indispensable tools for production planners and procurement professionals, empowering them to proactively address material availability challenges for assembly operations.


Author: Fabian Steinberg
Publisher: Springer Vieweg
Publication Date: Jun 20, 2024
Number of Pages: NA pages
Language: English
Binding: Paperback
ISBN-10: 3658450320
ISBN-13: 9783658450328
 

Customer Reviews

This product hasn't received any reviews yet. Be the first to review this product!

Faster Shipping

Delivery in 3-8 days

Easy Returns

14 days returns

Discount upto 30%

Monthly discount on books

Outstanding Customer Service

Support 24 hours a day