Collaborative Framework for Dynamic Scheduling Supporting in Networked Manufacturing Environments

2014 ◽  
Vol 6 (3) ◽  
pp. 33-51
Author(s):  
Maria Leonilde R. Varela ◽  
André S. Santos ◽  
Ana M. Madureira ◽  
Goran D. Putnik ◽  
Maria Manuela Cruz-Cunha
Keyword(s):  
Real Time ◽  
Working Conditions ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Dynamic Adaptation ◽  
Networked Manufacturing ◽  
Shared Resources ◽  
Organization Model ◽  
Robust Scheduling ◽  
Manufacturing Environments

Scheduling continues to play an important role in manufacturing systems. It enables the production of suitable scheduling plans, considering shared resources between several different products, through several manufacturing environments including networked ones. High levels of uncertainty characterize networked manufacturing environments. Processes have specific and complex requirements and management requisites, along with diversified objectives, which are dynamic and often conflicting. Dynamic adaptation and a real-time response for manufacturing scheduling is still possible and is critical in this new manufacturing environments, which have a flexible nature, where disturbances on working conditions occur on a continuous and even unexpected basis. Therefore, scheduling systems should have the ability of automatically and intelligently maintain a real-time adaptation and optimization of orders production, to effectively and efficiently adapt these manufacturing environments to the inherent dynamic of markets. In this paper a collaborative framework for supporting dynamic scheduling in networked manufacturing environments is proposed, based on a hyper-organization model and on hyper-heuristics, in order to obtain feasible and robust scheduling plans.

INTEGRATION OF REAL-TIME CONTROL SIMULATION TO A VIRTUAL MANUFACTURING ENVIRONMENT

2002 ◽  
Vol 01 (01) ◽  
pp. 67-87 ◽  
Author(s):  
BYUNG-KWON MIN ◽  
ZHENGDONG HUANG ◽  
ZBIGNIEW J. PASEK ◽  
DEREK YIP-HOI ◽  
FORBES HUSTED ◽  
...  
Keyword(s):  
Machine Tool ◽  
Real Time ◽  
Machine Tools ◽  
Manufacturing Systems ◽  
Early Stage ◽  
Virtual Manufacturing ◽  
System Level ◽  
Manufacturing Environment ◽  
Manufacturing Environments ◽  
Virtual Manufacturing Environment

This paper presents a new integrated approach for simulation developed to improve the accuracy of virtual manufacturing environments. While machine tool simulation and virtual manufacturing for factory simulation have been frequently used in early stage plant development, each of these technique has been researched and implemented separately. This paper focuses on the utilization of real-time simulation of machine tools or active axes in manufacturing systems and integration of this simulation capability with virtual manufacturing environments. Machine-level simulation results are generated in real-time with a real machine tool controller and are fed to a virtual manufacturing environment. To integrate these two simulation techniques, system-level software is utilized as a communication platform. This system-level software was originally developed to control and configure whole manufacturing systems. The method has been successfully implemented within a testbed with full-scale machine tools. The results demonstrate that the proposed method advances the virtual manufacturing environments toward improved accuracy of factory level simulation, reduced effort for modeling and expanded functionality of machine-level simulations.

scholarly journals Industry 4.0-Based Real-Time Scheduling and Dispatching in Lean Manufacturing Systems

2020 ◽  
Vol 12 (6) ◽  
pp. 2272
Author(s):  
Muawia Ramadan ◽  
Bashir Salah ◽  
Mohammed Othman ◽  
Arsath Abbasali Ayubali
Keyword(s):  
Real Time ◽  
Lean Manufacturing ◽  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Mixed Integer ◽  
Value Stream Mapping ◽  
Real Time Scheduling ◽  
Time Scheduling ◽  
Lean Tools ◽  
Manufacturing Environments

Lean manufacturing is one of the most popular improvement agents in the pursuit of perfection. However, in today’s complex and dynamic manufacturing environments, lean tools are facing an inevitable death. Industry 4.0 can be integrated with lean tools to avoid their end. Therefore, the primary purpose of this paper is to introduce an Industry 4.0-based lean framework called dynamic value stream mapping (DVSM) to digitalize lean manufacturing through the integration of lean tools and Industry 4.0 technologies. DVSM with its powerful features is proposed to be the smart IT platform that can sustain lean tools and keep them alive and effective. This paper specifically tackles the scheduling and dispatching in today’s lean manufacturing environments, where the aim of this research is developing a smart lean-based production scheduling and dispatching model to achieve the lean target through optimizing the flow along the VSM and minimizing the manufacturing lead time. The developed model, called the real-time scheduling and dispatching module (RT-SDM), runs on DVSM. The RT-SDM is represented through a mathematical model using mixed integer programming. Part of the testing and verification process, a simplified IT-based software, has been developed and applied on a smart factory lab.

scholarly journals Predictive Process Adjustment by Detecting System Status of Vacuum Gripper in Real Time during Pick-Up Operations

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 634
Author(s):  
Sujeong Baek ◽  
Dong Oh Kim
Keyword(s):  
Real Time ◽  
Manufacturing Systems ◽  
Air Pressure ◽  
Economic Losses ◽  
Stable Operation ◽  
System Operation ◽  
Process Adjustment ◽  
Manufacturing Errors ◽  
Predictive Process ◽  
Considerable Loss

In manufacturing systems, pick-up operations by vacuum grippers may fail owing to manufacturing errors in an object’s surface that are within the allowable tolerance limits. In such situations, manual interference is required to resume system operation, which results in considerable loss of time as well as economic losses. Although vacuum grippers have many advantages and are widely used in the industry, it is highly difficult to directly monitor the current machine status and provide appropriate recovery feedback for stable operation. Therefore, this paper proposes a method to detect the success or failure of a suction operation in advance by analyzing the amount of outlet air pressure in the Venturi line. This was achieved by installing an air pressure sensor on the Venturi line to predict whether the current suction action will be successful. Through empirical experiments, it was found that downward movements in the z-axis of the vacuum gripper can easily rectify a faulty gripper suction operation. Real-time monitoring results verified that predictive process adjustment of the pick-up operation can be performed by modifying the z-position of the vacuum gripper.

scholarly journals A Real-Time, Automatic, and Dynamic Scheduling and Control System for PET Patients Based on Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1104
Author(s):  
Shin-Yan Chiou ◽  
Kun-Ju Lin ◽  
Ya-Xin Dong
Keyword(s):  
Control System ◽  
Real Time ◽  
Human Error ◽  
Dynamic Scheduling ◽  
Wearable Sensors ◽  
Time Data ◽  
Scan Time ◽  
Number Of Patients ◽  
And Control ◽  
Automatic Scheduling

Positron emission tomography (PET) is one of the commonly used scanning techniques. Medical staff manually calculate the estimated scan time for each PET device. However, the number of PET scanning devices is small, the number of patients is large, and there are many changes including rescanning requirements, which makes it very error-prone, puts pressure on staff, and causes trouble for patients and their families. Although previous studies proposed algorithms for specific inspections, there is currently no research on improving the PET process. This paper proposes a real-time automatic scheduling and control system for PET patients with wearable sensors. The system can automatically schedule, estimate and instantly update the time of various tasks, and automatically allocate beds and announce schedule information in real time. We implemented this system, collected time data of 200 actual patients, and put these data into the implementation program for simulation and comparison. The average time difference between manual and automatic scheduling was 7.32 min, and it could reduce the average examination time of 82% of patients by 6.14 ± 4.61 min. This convinces us the system is correct and can improve time efficiency, while avoiding human error and staff pressure, and avoiding trouble for patients and their families.

Research of Flexible Dynamic Scheduling Problem Based on Genetic Algorithm

2009 ◽  
Vol 16-19 ◽  
pp. 743-747
Author(s):  
Yu Wu ◽  
Xin Cun Zhuang ◽  
Cong Xin Li
Keyword(s):  
Genetic Algorithm ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Scheduling Problem ◽  
Static Scheduling ◽  
Coding Method ◽  
Scheduling Method ◽  
Distribution Principle ◽  
Working Procedure

Solve the flexible dynamic scheduling problem by using “dynamic management & static scheduling” method. Aim at the property of flexible Manufacturing systems, the dynamic scheduling methods are analyzed and a coding method based on working procedure is improved in this paper. Thus it can be efficiently solve the problem of multiple working routes selection under the active distribution principle. On the other hand, the self-adaptive gene is provided and the parameters of the genetic algorithm are defined. In such a solution, the scheduling is confirmed to be simple and efficient.

scholarly journals Robust scheduling and dispatching rules for high-mix collaborative manufacturing systems

2021 ◽  
Author(s):  
Andrea Maria Zanchettin
Keyword(s):  
Manufacturing Systems ◽  
Production Systems ◽  
Adaptive Scheduling ◽  
Dispatching Rules ◽  
Numerical Verification ◽  
Robust Scheduling ◽  
Collaborative Manufacturing ◽  
Processing Times ◽  
Increasing Demand ◽  
Variable Production

AbstractMotivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling and dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling and dispatching rules are derived to optimally track the desired production within the mix, while handling uncertainty in job processing times. The sequencing policy is dynamically adjusted by online forecasting the throughput of the facility as a function of the scheduling and dispatching rules. Numerical verification experiments confirm the possibility to accurately track highly variable production requests, despite the uncertainty of the system.

Real-Time Maintenance Policy in Manufacturing Systems With Intermediate Buffers

2015 ◽  
Author(s):  
Xi Gu ◽  
Xiaoning Jin ◽  
Jun Ni
Keyword(s):  
Real Time ◽  
Manufacturing Systems ◽  
Maintenance Policy ◽  
Discrete Time Markov Chain ◽  
Markov Decision ◽  
Maintenance Decision ◽  
Maintenance Policies ◽  
Time Buffer ◽  
Buffer Capacities ◽  
One Machine

Real-time maintenance decision making in large manufacturing system is complex because it requires the integration of different information, including the degradation states of machines, as well as inventories in the intermediate buffers. In this paper, by using a discrete time Markov chain (DTMC) model, we consider the real-time maintenance policies in manufacturing systems consisting of multiple machines and intermediate buffers. The optimal policy is investigated by using a Markov Decision Process (MDP) approach. This policy is compared with a baseline policy, where the maintenance decision on one machine only depends on its degradation state. The result shows how the structures of the policies are affected by the buffer capacities and real-time buffer levels.

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