Results 41 to 50 of about 1,844,217 (391)
Optimal production scheduling of food process industries
Computers & Chemical Engineering, 2020 Abstract The production scheduling problem of a real-life food industry is addressed in this work. An efficient MILP-based solution strategy is developed to optimize weekly schedules for a Spanish canned fish production plant. The multi-stage, multi-product facility under study consists of both continuous and batch operations resulting in an ...
Georgiadis, Georgios P. +3 more
openaire +1 more source
Optimal Fair-Workload Scheduling: A Case Study at Glorytek
Mathematics, 2023 Taichung is the center of the Taiwanese precision optical industry. Optics companies are modernized and automated, with most running 24 h production lines.
Tzu-Chin Lin, Bertrand M. T. Lin
doaj +1 more source
Processes, 2020 Background: With the ever-increasing availability of data and a higher level of automation and simulation, production scheduling in the factory for prefabrication can no longer be seen as an autonomous solution.
Zhao Xu, Xiang-gang Wang, Zezhi Rao
semanticscholar +1 more source
Journal of the Operational Research Society, 2023 Steel-making and continuous casting (SCC) processes are considered the main bottlenecks in the steel industry. We consider planning and scheduling problems in SCC processes and provide an overview of the literature with our commentary.
Myungho Lee +4 more
semanticscholar +1 more source
IEEE Access, 2022 Smart factory is an exemplification of the Industrial Internet of Things (IIoT), connecting devices to expedite the production process and delivery of customized products.
Anam Nawaz Khan +5 more
doaj +1 more source
Deep Reinforcement Learning for Dynamic Flexible Job Shop Scheduling with Random Job Arrival
Processes, 2022 The production process of a smart factory is complex and dynamic. As the core of manufacturing management, the research into the flexible job shop scheduling problem (FJSP) focuses on optimizing scheduling decisions in real time, according to the changes
Jingru Chang +4 more
semanticscholar +1 more source
Fog computing and convolutional neural network enabled prognosis for machining process optimization [PDF]
, 2019 Cloud enabled prognosis systems have been increasingly adopted by manufacturing industries. The effectiveness of the cloud systems is, however, crippled by the high latency of data transfer between shop floors and the cloud.To overcome the limitation ...
Li, Weidong +3 more
core +1 more source
Feasibility Analysis in Batch Process: A Machine Learning Approach
Chemical Engineering Transactions, 2021 Scheduling is a major issue in process operations, and it is essential for maximizing production output. Short-term scheduling is used in batch operations to allocate a set of restricted resources across time to manufacture one or more items according to
Piyush Kumar Kumawat +1 more
doaj +1 more source
Increasing the Efficiency and Productivity in the Production of Low Voltage Switchboard Using Resource Constrained Project Scheduling [PDF]
, 2018 Purpose: This research was made with the aim to give a scheduling proposal for the assembly activity and the proposal to allocate those activities into available resources using the resource-constrained project scheduling.
Maimury, Yona, Tannady, Hendy
core +5 more sources
Scheduling by NSGA-II: Review and Bibliometric Analysis
Processes, 2022 NSGA-II is an evolutionary multi-objective optimization algorithm that has been applied to a wide variety of search and optimization problems since its publication in 2000.
Iman Rahimi +4 more
semanticscholar +1 more source