Scheduling and controlling production in an internet of things environment for industry 4.0: an analysis and systematic review of scientific metrological data

L Tan, TL Kong, Z Zhang, ASM Metwally, S Sharma… - Sustainability, 2023 - mdpi.com
To review the present scenario of the research on the scheduling and control of the
production process in the manufacturing industry, this comprehensive article has extensively …

Using machine learning techniques to reduce uncertainty for outpatient appointment scheduling practices in outpatient clinics

D Golmohammadi, L Zhao, D Dreyfus - Omega, 2023 - Elsevier
Most outpatient clinics apply deterministic block scheduling policies to patient visits even
though patients utilize varying amounts of time, leaving patients, operations managers, and …

Hyper-heuristic coevolution of machine assignment and job sequencing rules for multi-objective dynamic flexible job shop scheduling

Y Zhou, JJ Yang, LY Zheng - IEEE Access, 2018 - ieeexplore.ieee.org
Nowadays, real-time scheduling is one of the key issues in cyber-physical system. In real
production, dispatching rules are frequently used to react to disruptions. However, the man …

Multi-agent based hyper-heuristics for multi-objective flexible job shop scheduling: A case study in an aero-engine blade manufacturing plant

Y Zhou, JJ Yang, LY Zheng - Ieee Access, 2019 - ieeexplore.ieee.org
In the paper, a case study focusing on multi-objective flexible job shop scheduling problem
(MO-FJSP) in an aero-engine blade manufacturing plant is presented. The problem …

Energy-aware flowshop scheduling: A case for AI-driven sustainable manufacturing

M Danishvar, S Danishvar, E Katsou… - IEEE …, 2021 - ieeexplore.ieee.org
A fully verifiable and deployable framework for optimizing schedules in a batch-based
production system is proposed. The scheduler is designed to control and optimize the flow of …

The Problem of Machine Part Operations Optimal Scheduling in the Production Industry Based on a Customer's Order

P Mitić, S Petrović Savić, A Djordjevic, M Erić, E Sukić… - Applied Sciences, 2023 - mdpi.com
This research focuses on small-and medium-sized businesses that provide machining or
other process services but do not produce their own products. Their daily manufacturing …

Automatic design of scheduling policies for dynamic flexible job shop scheduling by multi-objective genetic programming based hyper-heuristic

Y Zhou, JJ Yang - Procedia CIRP, 2019 - Elsevier
This study proposes four multi-objective genetic programming based hyper-heuristic
methods (MO-GPHH) for automated heuristic design to solve the multi-objective dynamic …

Task Allocation in Human–Machine Manufacturing Systems Using Deep Reinforcement Learning

T Joo, H Jun, D Shin - Sustainability, 2022 - mdpi.com
Catering for human operators is a critical aspect in the sustainability of a manufacturing
sector. This paper presents a task allocation problem in human–machine manufacturing …

A dynamic quality control approach by improving dominant factors based on improved principal component analysis

G Diao, L Zhao, Y Yao - International Journal of Production …, 2015 - Taylor & Francis
Process variables in manufacturing process are critical to the final quality of product,
especially in continuous process. Their abnormal fluctuations may cause many quality …

A Decision-Making tool based on historical data for service time prediction in outpatient scheduling

D Golmohammadi - International Journal of Medical Informatics, 2021 - Elsevier
Background Appointment scheduling in outpatient settings typically uses simple
classification rules to assign patients to long or short appointment slots, based on the …