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Order Fulfillment Improvement Model Applying MRP, SLP with Digital Twins and Standardization Integrated with Poka Yoke in a Company in the Metalworking Sector

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Authors
Peña-Mendoza, Luis Enrique
Alvarez-Arteaga, José Luis
Coila-Ruiz, Cintya Rosmeri
Zarate-Muñoz, Eros
Issue Date
2026-01-01
Keywords
Digital Twins
Metalworking industry
On Time Delivery
Process Standardization
Smart Manufacturing
System Poka Yoke

Metadata
Show full item record
Publisher
Springer Science and Business Media B.V.
Journal
Mechanisms and Machine Science
URI
http://hdl.handle.net/10757/689113
DOI
https://doi.org/10.1007/978-3-032-11791-5_43
Abstract
The metalworking industry plays a fundamental role in the global economy. In this context, manufacturing companies in the metalworking sector with the Engineer to Order (ETO) and Make to Order (MTO) strategies have experienced significant growth in the industrial field. However, these companies face considerable challenges, one of them being delays in order delivery. These delays are due to multiple factors, including defective products, material shortages, and excessive travel times due to an inefficient distribution of work areas. In response to this problem, a model is proposed that integrates tools such as MRP (Material Requirements Planning), SLP (Systematic Design Planning) with Digital twins for plant redistribution, and process standardization techniques with Poka Yoke. The implementation of these tools seeks to optimize the production chain, reduce manufacturing times, and improve operational efficiency. The development of this model is measured with the On Time Delivery indicator, which seeks to go from 89% to 96%. This work not only seeks to address the specific challenges of the study company but aspires to become a replicable model to solve production flow difficulties and improve punctuality in the delivery of orders throughout the metalworking industry.
Type
http://purl.org/coar/resource_type/c_6501
Rights
http://purl.org/coar/resource_type/c_f744
Language
eng
ISSN
2211-0984
EISSN
2211-0992
ae974a485f413a2113503eed53cd6c53
https://doi.org/10.1007/978-3-032-11791-5_43
Scopus Count
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Seccion en procesamiento

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