Results 211 to 220 of about 680,167 (353)

A DNA algorithm for the job shop scheduling problem based on the Adleman-Lipton model. [PDF]

PLoS One, 2020
Tian X, Liu X, Zhang H, Sun M, Zhao Y.
europepmc   +1 more source

FAIR and Structured Data: A Domain Ontology Aligned with Standard‐Compliant Tensile Testing

Advanced Engineering Materials, EarlyView.
The digitalization in materials science and engineering is discussed, emphasizing the importance of digital workflows and ontologies in managing diverse experimental data. Challenges such as quality assurance and data interoperability are tackled with semantic web technologies, focusing and introducing the tensile test ontology (TTO).
Markus Schilling, Bernd Bayerlein, Philipp von Hartrott, Jörg Waitelonis, Henk Birkholz, Pedro Dolabella Portella, Birgit Skrotzki   +6 more
wiley   +1 more source

Data-driven automated job shop scheduling optimization considering AGV obstacle avoidance. [PDF]

Sci Rep
Tang Q, Wang H.
europepmc   +1 more source

Order Management and Completion Date Prediction of Manufacturing Job-Shop Based on Deep Learning.

Comput Intell Neurosci, 2022
Wang M.
europepmc   +1 more source

Numerical Studies of Influencing Factors on the Homogeneity of the Powder Mixture during the Powder Spreading Process of Powder Bed Fusion–Laser Beam/Metal

Advanced Engineering Materials, EarlyView.
AISI 304L stainless steel powder is mixed with silicon nitride (Si3N4) powder and processed by PBF‐LB/M, allowing partial retention of Si3N4. The numerical approach effectively predicts the Si3N4 powder homogeneity and N content distribution on the powder bed. Recent studies have focused on the alloying of nitrogen (N) in high‐alloy stainless steels by
Yuanbin Deng, Ziping Sang, Jiali Zhang, Felix Radtke, Louis Becker, Simone Herzog, Sebastian Weber, Christoph Broeckmann   +7 more
wiley   +1 more source

Dynamic scheduling for flexible job shop based on MachineRank algorithm and reinforcement learning. [PDF]

Sci Rep
Ren F, Liu H.
europepmc   +1 more source

A Proposal of a Job Shop Scheduling Method for Solving Resources Contention Problems and its Verification

, 2001
Hiroaki Sugihara, Hisao Koizumi, Kataoka Nobuhiro, T. Takahara   +3 more
openalex   +2 more sources

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

An enhanced walrus optimization algorithm for flexible job shop scheduling with parallel batch processing operation. [PDF]

Sci Rep
Lv S, Zhuang J, Li Z, Zhang H, Jin H, Lü S.   +5 more
europepmc   +1 more source

An Automatized Simulation Workflow for Powder Pressing Simulations Using SimStack

Advanced Engineering Materials, EarlyView.
The implementation of Workflow active Nodes (WaNos) for the convenient execution and automated evaluation of discrete element method calculations of powder pressing is showcased. Purposeful combination of WaNos creates timesaving and resource‐effective computational workflows.
Bjoern Mieller, Masood Valavi, Celso Ricardo Caldeira Rêgo   +2 more
wiley   +1 more source