Production scheduling in the context of Industry 4.0: review and trends
Notwithstanding its disruptive potential, which has been the object of considerable debate,
Industry4. 0 (I4. 0) operationalisation still needs significant study. Specifically, scheduling is …
Industry4. 0 (I4. 0) operationalisation still needs significant study. Specifically, scheduling is …
Deep learning for big data applications in CAD and PLM–Research review, opportunities and case study
With the increasing amount of available data, computing power and network speed for a
decreasing cost, the manufacturing industry is facing an unprecedented amount of data to …
decreasing cost, the manufacturing industry is facing an unprecedented amount of data to …
[HTML][HTML] Deep learning for manufacturing sustainability: Models, applications in Industry 4.0 and implications
Recent advancements and developments in artificial intelligence (AI) based approaches
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
have shifted the manufacturing practices towards the fourth industrial revolution, considered …
Curator:{Self-Managing} Storage for Enterprise Clusters
I Cano, S Aiyar, V Arora, M Bhattacharyya… - … USENIX Symposium on …, 2017 - usenix.org
Modern cluster storage systems perform a variety of background tasks to improve the
performance, availability, durability, and cost-efficiency of stored data. For example, cleaners …
performance, availability, durability, and cost-efficiency of stored data. For example, cleaners …
[图书][B] Scheduling
ML Pinedo - 2012 - Springer
Michael L. Pinedo Theory, Algorithms, and Systems Sixth Edition Page 1 Scheduling Michael L.
Pinedo Theory, Algorithms, and Systems Sixth Edition Page 2 Scheduling Page 3 Michael L …
Pinedo Theory, Algorithms, and Systems Sixth Edition Page 2 Scheduling Page 3 Michael L …
Machine learning applications for sustainable manufacturing: a bibliometric-based review for future research
Purpose The role of data analytics is significantly important in manufacturing industries as it
holds the key to address sustainability challenges and handle the large amount of data …
holds the key to address sustainability challenges and handle the large amount of data …
A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times
In this paper, we propose a model for Flexible Job Shop Scheduling Problem (FJSSP) with
transportation constraints and bounded processing times. This is a NP hard problem …
transportation constraints and bounded processing times. This is a NP hard problem …
Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge
DC Li, CS Wu, TI Tsai, YS Lina - Computers & Operations Research, 2007 - Elsevier
Neural networks are widely utilized to extract management knowledge from acquired data,
but having enough real data is not always possible. In the early stages of dynamic flexible …
but having enough real data is not always possible. In the early stages of dynamic flexible …
TRACON: Interference-aware scheduling for data-intensive applications in virtualized environments
Large-scale data centers leverage virtualization technology to achieve excellent resource
utilization, scalability, and high availability. Ideally, the performance of an application …
utilization, scalability, and high availability. Ideally, the performance of an application …
Learning-based scheduling of flexible manufacturing systems using ensemble methods
Dispatching rules are commonly applied to schedule jobs in Flexible Manufacturing Systems
(FMSs). However, the suitability of these rules relies heavily on the state of the system; …
(FMSs). However, the suitability of these rules relies heavily on the state of the system; …