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In a complex semiconductor manufacturing system (SMS) environment, the implementation of dynamic production scheduling and dispatching strategies is critical for SMS distributed collaborative manufacturing events to make quick and correct decisions. The purpose of this paper is to assist manufacturers in achieving the real time dispatching and obtaining integrated optimization for shop floor production scheduling.

In this paper, an integrated model is designed under assemble to order environment and a framework of a real time dispatching (IRTD) system for production scheduling control is presented accordingly. Both of the scheduling and ordering performances are integrated into the days of inventory based dispatching algorithm, which can deal with the multiple indicators of dynamic scheduling and ordering in this system to generate the “optimal” dispatching policies. Subsequently, the platform of IRTD system is realized with four modules function embedded.

The proposed IRTD system is designed to compare the previous constant work in process method in the experiment, which shows the better performance achievement of the IRTD system for shop floor production dynamic scheduling and order control. The presented framework and algorithm can facilitate real time dispatching information integration to obtain performance metrics in terms of reliability, availability, and maintainability.

The presented system can be further developed to generic factory manufacturing with the presented logic and architecture proliferation.

The IRTD system can integrate the real time customer demand and work in process information, based on which manufacturers can make correct and timely decisions in solving dispatching strategies and ordering selection within an integrated information system.

Steam turbine final assembly is a dynamic process, in which various interference events occur frequently. Currently, data transmission relies on oral presentation, while scheduling depends on the manual experience of managers. This mode has low information transmission efficiency and is difficult to timely respond to emergencies. Besides, it is difficult to consider various factors when manually adjusting the plan, which reduces assembly efficiency. The purpose of this paper is to propose a knowledge-based real-time scheduling system under cyber-physical system (CPS) environment which can improve the assembly efficiency of steam turbines.

First, an Internet of Things based CPS framework is proposed to achieve real-time monitoring of turbine assembly and improve the efficiency of information transmission. Second, a knowledge-based real-time scheduling system consisting of three modules is designed to replace manual experience for steam turbine assembly scheduling.

Experiments show that the scheduling results of the knowledge-based scheduling system outperform heuristic algorithms based on priority rules. Compared with manual scheduling, the delay time is reduced by 43.9%.

A knowledge-based real-time scheduling system under CPS environment is proposed to improve the assembly efficiency of steam turbines. This paper provides a reference paradigm for the application of the knowledge-based system and CPS in the assembly control of labor-intensive engineering-to-order products.

The main purpose of the paper is timing analysis of mixed critical applications on the multicore system to identify an efficient task scheduling mechanism to achieve three main objectives improving schedulability, achieving reliability and minimizing the number of cores used. The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

The paper opted for a simulation-based study. The simulation of mixed critical applications, like air traffic control systems and synthetic workloads, is carried out using a litmus-real time testbed on an Ubuntu machine. The heuristic algorithms for task allocation based on utilization factors and task criticalities are proposed for partitioned approaches with multiple objectives.

Both partitioned earliest deadline first (EDF) with the utilization-based heuristic and EDF-virtual deadline (VD) with a criticality-based heuristic for allocation works well, as it schedules the air traffic system with a 98% success ratio (SR) using only three processor cores with transient faults being handled by the active backup of the tasks. With synthetic task loads, the proposed criticality-based heuristic works well with EDF-VD, as the SR is 94%. The validation of the proposed heuristic is done with a global and partitioned approach of scheduling, considering active backups to make the system reliable. There is an improvement in SR by 11% as compared to the global approach and a 17% improvement in comparison with the partitioned fixed-priority approach with only three processor cores being used.

The simulations of mixed critical tasks are carried out on a real-time kernel based on Linux and are generalizable in Linux-based environments.

The rise in transient faults in embedded systems due to the use of low-cost processors has led to the use of fault-tolerant scheduling and mapping techniques.

This paper fulfills an identified need to have multi-objective task scheduling in a mixed critical system. The timing analysis helps to identify performance risks and assess alternative architectures used to achieve reliability in terms of transient faults.

In a mixed flow production environment, interactions between production planning and scheduling are critical for mixed flow distributed manufacturing management. The purpose of this paper is to assist manufacturers in achieving real-time ordering and obtaining integrated optimization of shop floor production planning and scheduling for mixed flow production systems.

A double decoupling postponement (DDP) approach is presented for production dispatch control, and an integrated model is designed under an assemble to order (ATO) environment. To generate “optimal” lots to fulfil real-time customer requests, constant work in progress (CONWIP) and days of inventory dispatching algorithms are embedded into the proposed DDP model, which can deal with real-time ordering and dynamic scheduling simultaneously. Subsequently, a case study is conducted, and experiments are carried out to verify the presented method.

The proposed DDP model is designed to upgrade a previous CONWIP method in the case study company, and the proposed model demonstrates better performance for the integration of production planning and scheduling in mixed flow manufacturing. As a result, the presented operation mechanism can reflect real-time ordering information to shop floor scheduling and obtain performance metrics in terms of reliability, availability and maintainability.

The presented model can be further proliferated to generic factory manufacturing with the proposed logic and architecture.

The DDP model can integrate real-time customer orders and work in process information, upon which manufacturers can make correct decisions for dispatch strategies and order selection within an integrated system.

In client/server distributed systems, the server is often the bottleneck. Improving the server performance is thus crucial for improving the overall performance of distributed information systems. Real‐time system is required to complete its work and deliver its services on a timely basis. The purpose of this paper is to propose a new scheduling algorithm for real‐time distributed system (client/server model) to achieve the above‐mentioned goal.

The ant colony optimization (ACO) algorithms are computational models inspired by the collective foraging behavior of ants. They provide inherent parallelism and robustness. Therefore, they are appropriate for scheduling of tasks in soft real‐time systems. During simulation, results are obtained with periodic tasks, measured in terms of success ratio and effective CPU utilization; and compared with results of earliest deadline first (EDF) algorithm in the same environment.

Analysis and experiments show that the proposed algorithm is equally efficient during underloaded conditions. The performance of EDF decreases as the load increases, but the proposed algorithm works well in overloaded conditions also. Because of this type of property, the proposed algorithm is more suitable for the situation when future workload of the system is unpredictable.

The application of ACO algorithms for scheduling of client/server real‐time distributed system, never found before in the literature. The new concept proposed in this paper will be of great significance to both theoretical and practical research in scheduling of distributed systems in the years to come.

This paper aims to describe the development of a new software tool for the scheduling of real‐time control messages in a time‐triggered control network. The prime application area for such a solution is in real‐time robotic controllers and other similar machine control systems.

The design of a scheduling tool, called SMART‐Plan, is described. The tool is based on a “least slack time” scheduling policy. A prototype tool for the time‐triggered controller area network (TTCAN) is developed. The design is validated against Society of Automotive Engineers Benchmark and a formal verification of the message schedule is also proposed.

The research findings show that it is feasible to develop such a message scheduling tool and the performance of the tool is comparable with other research solutions, which have been applied in the past to simple periodic schedulers, as opposed to time‐triggered networks.

Although the prototype solution assumes a TTCAN control network, the concept will also be feasible for other types of time‐triggered control networks. The availability of such a tool might encourage developers of robotic equipment to adopt the time‐triggered network approach for the architectural development of such control systems. To date, the problems associated with the message scheduling of such time‐triggered systems have been an inhibitor to such developments.

This is a new scheduling approach to the message scheduling of time‐triggerred control networks.

Basic project control through traditional methods is not sufficient to manage the majority of real-time events in most construction projects. The purpose of this paper is to propose a Dynamic Scheduling (DS) model that utilizes multi-objective optimization of cost, time, resources and cash flow, throughout project construction.

Upon reviewing the topic of DS, a worldwide internet survey with 364 respondents was conducted to define end-user requirements. The model was formulated and solution algorithms discussed. Verification was reported using predefined problem sets and a real-life case. Validation was performed via feedback from industry experts.

The need for multi-objective dynamic software optimization of construction schedules and the ability to choose among a set of optimal alternatives were highlighted. Model verification through well-known test cases and a real-life project case study showed that the model successfully achieved the required dynamic functionality whether under the small solved example or under the complex case study. The model was validated for practicality, optimization of various DS schedule quality gates, ease of use and software integration with contemporary project management practices.

Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste.

Optimized real-time scheduling can provide better resources management including labor utilization and cost efficiency. Furthermore, DS contributes to optimum materials procurement, thus minimizing waste.

The paper illustrates the importance of DS in construction, identifies the user needs and overviews the development, verification and validation of a model that supports the generation of high-quality schedules beneficial to large-scale projects.

Integrates CAD/CAM, production control and process control in a case study involving manufacturing automation. The manufacturing firm is a distributed cellular system operating in a produce‐to‐order environment. Combines a parametric CAD software with global variables and global relations to achieve a design automation. Results obtained from design automation are transmitted to update the design model and the associative manufacturing model. In addition, scheduling and control are also integrated in the system. Distinguishes three scheduling levels: static scheduling, rescheduling, and real‐time scheduling. For a distributed and effective reason, the distributed shifting bottleneck procedure (DSBP) is adopted as the static scheduler and rescheduler, and the LRPT (longest bottleneck processing time) despatching rule is adopted as the real time despatching rule. FInally, introduces the configuration of the system including the flexible manufacturing cell architecture and the input buffer device. Uses a PLC programming toll that follows the IEC 1131‐3 standard to implement cell controllers. The above implementation aims to easily and effectively execute the CIM system.

The purpose of this paper is to investigate the scheduling problem of real-time jobs executing on a DVS processor. The jobs must complete their executions by their deadlines and the energy consumption also must be minimized.

The two-phase energy-efficient scheduling algorithm is proposed to solve the scheduling problem for real-time jobs. In the off-line phase, the maximum instantaneous total density and instantaneous total density (ITD) are proposed to derive the speed of the processor for each time instance. The derived speeds are saved for run time. In the on-line phase, the authors set the processor speed according to the derived speeds and set a timer to expire at the corresponding end time instance of the used speed.

When the DVS processor executes a job at a proper speed, the energy consumption of the system can be minimized.

This paper does not consider jobs with precedence constraints. It can be explored in the further work.

The experimental results of the proposed schemes are presented to show the effectiveness.

The experimental results show that the proposed scheduling algorithm, ITD, can achieve energy saving and make the processor fully utilized.

In practical workshop production process, there are many production emergencies, e.g. new manufacturing tasks, facilities failure and tasks change. On one hand, it results in poor timeliness and reliability of real-time production data collection, acquisition and transmission; on the other hand, it increases the difficulty of real-time data tracking and monitoring. This paper aims to develop a novel RFID-based tracking and monitoring approach of real-time data in production workshop (TM_rfid) to solve them.

At first, a three-layer model of real-time data based on RFID has been constructed, which contains RFID-based integrated acquisition center; “RFID & Cloud-service-rules”-based calculation and analysis center; and “RFID & Ontology-knowledge-base”-based monitoring and scheduling center. Then, a targeted analysis and evaluation method of TM_rfid with feasibility, quality and performance has been proposed. Finally, a prototype platform of a textile machinery manufacturing enterprise has been built to verify the effective of TM_rfid.

The effectiveness of TM_rfid is verified by applying two groups of actual experimental data from the case enterprise, the results show that TM_rfid can promote the efficiency, reliability and feasibility of tacking and monitoring of real-time data in production workshop.

RFID-based tracking and monitoring approach of real-time data in production workshop has been developed to solve the data information transmission and sharing problem. Three analysis and evaluation approaches have been introduced to solve the un-standardized evaluation problem of RFID application. A prototype platform of a textile machinery manufacturing enterprise has been constructed.