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Digital twin model-driven capacity evaluation and scheduling optimization for ship welding production line

JOURNAL OF INTELLIGENT MANUFACTURING 2024年第7期35卷 3353-3375页

作者： Liu, Jinfeng Ji, Qiukai Zhang, Xiaohu Chen, Yu Zhang, Yiming Liu, Xiaojun Tang, Mingming Jiangsu Univ Sci & Technol Sch Mech Engn Zhenjiang 212003 Peoples R China Southeast Univ Sch Mech Engn Nanjing 211198 Peoples R China

Approximately 45% of ship delivery delays are due to welding quality. To solve the problematic control of production tempo and process sequence optimization in the welding process, it is urgent to combine the characteristics of the digital twin for dynamic simulation and optimization. Therefore, the capacity evaluation and scheduling optimization for the ship welding production line (WPL) based on the digital twin is proposed. Firstly, to describe the construction method of the digital twin model and digital twin data, a strategy is proposed for the construction of a digital twin ship component WPL model. Based on the fusion mapping of model and data, the construction of the digital twin model for WPL (DTM-WPL) is achieved. Secondly, by using equipment failure rate, processing time and buffer capacity as evaluation indicators, an WPL optimization model based on digital twins is constructed to solve the WPL production sequencing problem. Thirdly, to illustrate the welding quality traceability and prediction process, a DTM-WPL synchronous mapping for quality prediction and adjustment method is proposed. Finally, taking small and medium-sized WPL as the research object, the capacity evaluation and scheduling optimization system of ship components is developed to evaluate the production capacity of ship components. The validation results indicate that the optimized process scheme has increased production efficiency by 7.27%.

关键词： Welding production line Digital twin Capacity evaluation scheduling optimization

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A New Optoelectronic Hybrid Network Based on scheduling optimization of Optical Links

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IEEE TRANSACTIONS ON COMPUTERS 2021年第6期70卷 863-876页

作者： Shao, En Tan, Guangming Wang, Zhan Yuan, Guojun Cao, Zheng Sun, Ninghui Chinese Acad Sci State Key Lab Comp Architecture Inst Comp Technol Beijing 518055 Peoples R China Univ Chinese Acad Sci UCAS Beijing 100864 Peoples R China

The emergence of exascale computers will represent a milestone in high-performance computing (HPC). Optoelectronic interconnections and configurable switches will change the traditional supercomputer architecture. However, new hardware is not easily adapted to dynamic running conditions. Based on scheduling optimization of optical links, we propose a new optoelectronic hybrid network, the software-defined network accelerator (sDNA), for an exascale computer. Our scheduling optimization contains an optical interconnection method and an adaptive routing method. The main contribution of our work is an extended edge forwarding index (E-EFI) optical interconnection method based on slow-switching optical devices. The optical link connections are established by evaluating the traffic offloading revenue for each optical link candidate. To support optical interconnection, sDNA selects a suitable routing strategy according to the job-schedule information and prior HPC application knowledge. We tested sDNA in a network simulator and a prototype exascale computer system using both the US Department of Energy (DOE) application and real-world communication benchmarks. The verification results for traffic offloading reveal that our optical interconnection method not only offloads traffic from electrical links to optical links but also avoids the congestion inherent to electrical links. sDNA maintains a throughput of more than 80 percent bandwidth and reduces the communication delay by 10 percent in our real prototype system and simulator. Thus, sDNA is an ideal candidate for accelerating the communication performance of exascale computers.

关键词： Optical switches Optical interconnections Processor scheduling Network topology Topology Routing Optical devices scheduling optimization large-scale communication optical network and system long-distance communication slow-switching optical device run-time control prototype exascale computer system

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An agent-oriented approach to resolve scheduling optimization in intelligent manufacturing

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2010年第1期26卷 39-45页

作者： Guo, Qing-lin Zhang, Ming N China Elect Power Univ Sch Comp Sci & Technol Beijing 102206 Peoples R China Peking Univ Dept Comp Sci & Technol Beijing 100871 Peoples R China

Agent technology is considered as a promising approach for developing optimizing process plans in intelligent manufacturing. As a bridge between computer aided design (CAD) and computer aided manufacturing (CAM), the computer aided scheduling optimization (CASO) plays an important role in the computer integrated manufacturing (CIM) environment In order to develop a multi-agent-based scheduling system for intelligent manufacturing, it is necessary to build various functional agents for all the resources and an agent manager to improve the scheduling agility. Identifying the shortcomings of traditional scheduling algorithm in intelligent manufacturing, the architecture of intelligent manufacturing system based on multi-agent is put forward, among which agent represents the basic processing entity. Multi-agent-based scheduling is a new intelligent scheduling method based on the theories of multi-agent system (MAS) and distributed artificial intelligence (DAI). It views intelligent manufacturing as composed of a set of intelligent agents, who are responsible for one or more activities and interacting with other related agents in planning and executing their responsibilities. In this paper, the proposed architecture consists of various autonomous agents that are capable of communicating with each other and making decisions based on their knowledge. The architecture of intelligent manufacturing, the scheduling optimization algorithm, the negotiation processes and protocols among the agents are described in detail. A prototype system is built and validated in an illustrative example, which demonstrates the feasibility of the proposed approach. The experiments prove that the implementation of multi-agent technology in intelligent manufacturing system makes the operations much more flexible, economical and energy efficient. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Intelligent manufacturing Multi-agent Functional agent scheduling optimization Ontology Model

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Multi-parallel work centers scheduling optimization with shared or dedicated resources in low-volume low-variety production systems

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APPLIED MATHEMATICAL MODELLING 2020年 80卷 472-505页

作者： Russell, Arya Taghipour, Sharareh Ryerson Univ 350 Victoria St Toronto ON M5B 2K3 Canada

A new methodology for modeling large-scale scheduling problems in low-volume low-variety production systems is proposed through this paper. Such scheduling problems are constrained by limited time and resources, where each work center is assigned a unique statement of work, to be completed on-time with the budgeted number of resources. Products assembled in low-volume low-variety production systems are processed through a series of stations referred to as work centers, where varying levels and classifications of resources are deployed onto the product. Aircraft, heavy aero-structures, and heavy military equipment are examples of products assembled in low-volume low-variety production systems. To ensure products are delivered on-time and on-budget, it is crucial to execute to a detailed schedule, such that all precedence, resource, zonal, and other constraints and characteristics inherent in such production systems are successfully satisfied. Despite the criticality of detailed schedules in delivering products on-time and on-budget, limited research is reported on mixed-integer programming approaches for scheduling optimization of activities in low-volume low-variety production systems. The discrete-time linear mixed-integer mathematical programming model developed in this paper fills the gap in the current literature with a direct impact on the organizations' service levels and bottom line. The proposed mathematical programming models are validated through a real-world case-study of the assembly process of a narrow body aircraft to ensure compatibility in the modeling of large-scale industrial problems. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Goal programming Integer programming Low-volume low-variety production systems Parallel work centers scheduling optimization Shared resources

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Multi-path Allocation scheduling optimization Algorithm for Network Data Traffic Based on SDN Architecture

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IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION 2020年第4期37卷 1237-1247页

作者： Lu, Lihua Northwest Polytech Univ Sch Comp Sci Xian 710129 Shaanxi Peoples R China

The explosive growth of network data traffic puts new demands on traffic scheduling. In this paper, the scheduling algorithm based on the software-defined network (SDN) architecture is studied. Firstly, the SDN architecture was introduced, then an SDN-based adaptive multi-path load balancing algorithm was proposed and finally the algorithm was simulated on the Mininet simulation platform to compare the performance of the proposed algorithm and traditional equal-cost multi-path routing algorithm by using Ryu as the controller. It was found that the proposed algorithm had greater throughput, higher bandwidth utilization and shorter transmission time in allocation scheduling of network data traffic, which could effectively reduce network congestion and ensure the reliability of the network. This study verifies the effectiveness of the proposed method in allocation scheduling of network data traffic and provides some theoretical bases for the further application of the SDN architecture-based allocation scheduling algorithm.

关键词： SDN architecture load balancing multi-path scheduling optimization

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A scheduling optimization method for maintenance, repair and operations service resources of complex products

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JOURNAL OF INTELLIGENT MANUFACTURING 2020年第7期31卷 1673-1691页

作者： Li, Hao Mi, Shanghua Li, Qifeng Wen, Xiaoyu Qiao, Dongping Luo, Guofu Zhengzhou Univ Light Ind Henan Prov Key Lab Intelligent Mfg Mech Equipment Zhengzhou 450002 Peoples R China

scheduling optimization of maintenance, repair and operations (MRO) service resources of complex product can help an enterprise improve customer service satisfaction, build value-added products, and enhance the enterprise's market competitiveness. This paper studies a scheduling optimization method for the MRO service resources of complex product. First, the scheduling problem in service resources is analyzed, a mathematical model for the service scheduling problem is given, and three objective functions to be optimized are proposed, which are to reduce customer waiting time, reduce excessive human resources, and maximize the cost performance index of the resources. Then, three separate objectives for optimizing service resource scheduling are analyzed based on three proposed methods which are improved genetic algorithm method, combined weight coefficient optimization method, and multi-objective optimization method based on the nondominated sorting genetic algorithm II (NSGA-II). Finally, we use the three methods to carry out scheduling optimization of MRO service resources in the case of a large vertical mill. According to the analysis and comparison of results, the multi-objective optimization method based on the NSGA-II algorithm has an advantage in the scheduling optimization of complex product MRO service resources. In the engineering application, the service scheduling of complex products for managers provides theoretical basis, and can reduce the loss caused by subjective judgment.

关键词： Maintenance repair and operations scheduling optimization Improved genetic algorithm NSGA-II algorithm

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Multiagent-based scheduling optimization for Intelligent Manufacturing System

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2009年第5-6期44卷 595-605页

作者： Guo, Qing-lin Zhang, Ming N China Elect Power Univ Sch Comp Sci & Technol Beijing 102206 Peoples R China Peking Univ Dept Comp Sci & Technol Beijing 100871 Peoples R China

Multiagent-based scheduling is a new intelligent scheduling method based on the theories of multiagent system (MAS) and distributed artificial intelligence (DAI). Multiagent-based scheduling can dynamically and flexibly schedule manufacturing processes by means of cooperation and coordination among the agents. It has been considered that the Agent technology is an important method to build the model of distributed industrial system, the most natural way to design and implement the distributed Intelligent Manufacturing environment, and one of the significant technologies to construct the manufacturing system of next generation. On the basis of briefly summarizing the technology of Agent and Multiagent system, the architecture of Intelligent Manufacturing System based on Multiagent is put forward, among which, Agent represents the basic processing entity. The control strategy and scheduling optimization algorithm of Intelligent Manufacturing is provided, which is feasible proved by the result of stimulation experiment. Compared with the traditional artificial scheduling, it has distinct advantages. Finally, the model of communication and negotiation between Agents in the Intelligent Manufacturing System is studied, which utilizes the features of Agent such as autonomy, social interaction, response capability, preliminary capability, etc so that Intelligent Manufacturing System could make distributed decisions. The cooperation of system is completed by communication and negotiation. During the process of interaction, Agent is endowed with a role to meet the demand of flexibility of building models in the complicated process of Intelligent Manufacturing, as well as to construct an extended frame for reusable components. Experiments do prove that it is feasible to use the method to develop an Intelligent Manufacturing System, which is valuable for further study in more depth.

关键词： Multiagent Intelligent Manufacturing scheduling optimization Model Petri net

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Multi-station test scheduling optimization method for industrial robot servo system

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022年第3期13卷 1321-1337页

作者： Tang, Shaomin Liu, Guixiong Lin, Zhiyu Li, Xiaobing South China Univ Technol Sch Mech & Automot Engn Guangzhou 510640 Peoples R China CEPREI Guangzhou 510610 Peoples R China

This study examined the test scheduling optimization problem of industrial robot servo system (IRSS) samples with unequal numbers of different types of test items on the multiple IRSS comprehensive test platforms with the same function. In order to improve IRSS performance test efficiency, a multi-station test scheduling optimization method, which combines IRSS sample-level scheduling and test item-level scheduling, was proposed. First, the IRSS sample-level scheduling was carried out, and a model was established with reference to the identical parallel machine problem (IPMP). The optimal result of IRSS sample-level multi-station scheduling was obtained by solving the model. Second, based on the result of IRSS sample-level multi-station scheduling, and taking the ideal optimal test completion time of IRSS multi-station scheduling as the target, the test items at the stations were reallocated to obtain the optimal scheduling result. Finally, an application example was used to verify the efficiency of the proposed method, and the experiment result showed that the proposed method can effectively fulfill the optimal allocation of different IRSS test items of multiple IRSS samples on multiple IRSS comprehensive test platforms. The test time was 247 min shorter than the conventional sequential parallel test and only one min longer than the ideal optimal test completion time.

关键词： Industrial robot Servo system Performance testing scheduling model scheduling optimization

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Cross-regional integrated energy system scheduling optimization model considering conditional value at risk

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2020年第7期44卷 5564-5581页

作者： Yu, Xiaobao Zheng, Dandan Shanghai Univ Elect Power Sch Econ & Management Shanghai 200090 Peoples R China

Integrated energy system is a very important way to improve energy efficiency. Based on the combined heating cooling and power system, combined with energy storage equipment, a cross-regional integrated energy system scheduling optimization problem is studied. An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region. Meanwhile, the value at risk (VaR) theory is introduced and the operating constraints of equipment in the integrated energy system fully considered, the integrated energy system scheduling model with VaR is established. The example shows that the model can realize multi-type electrical, heating, and cooling load optimized by schedule across regions under the premise of satisfying the balance of energy supply and demand, which can reduce the system operation cost. The sensitivity analysis of the minimum expected cost and the influencing factors of conditional VaR is carried out to verify the validity and feasibility of the proposed model. An integrated energy system scheduling optimization model is established that meets the requirements of electrical, heating, and cooling load under a variety of energy sources while both considering the interaction of electrical, heating, and cooling load between regions, and complementation of them within one region. By using the conditional value at risk theory to consider various types of the integrated energy system complements and evaluates the operational risk of the system under optimal operating conditions of the system. The total cost of system scheduling operation is proportional to the storage capacity, which is inversely proportional to the heat storage capacity and inversely proportional to the pipeline capacity within a certain interval.

关键词： CCHP conditional value at risk cross-region integrated energy system scheduling optimization

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Vessel transportation scheduling optimization based on channel-berth coordination

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OCEAN ENGINEERING 2016年 112卷 145-152页

作者： Zhang, Xinyu Lin, Jun Guo, Zijian Liu, Tieshu Dalian Maritime Univ Key Lab Maritime Dynam Simulat & Control Minist Transportat Dalian 116026 Peoples R China Dalian Univ Technol Fac Infrastruct Engn Dalian 116024 Peoples R China Tianjin Marine Traff Management Ctr Tianjin 300456 Peoples R China

Channels and berths are important resources for vessels in port operation. This study aims to improve the efficiency of vessel transportation scheduling by coordinating channels and berths. Therefore, in consideration of scheduling order, travel direction and distance of the berth, a mathematical model with minimum total waiting time as the objective function is established. Furthermore, it applies a simulated annealing and multiple population genetic algorithm (SAMPGA) to solve the proposed model for vessel transportation scheduling in port. This study simulates numerical examples for 10 and 20 vessels. Calculations indicate waiting and total scheduled times of 485 min and 342 min, respectively, for 10 vessels and 1731 min and 456 min, respectively, for 20 vessels. Compared with the simple genetic algorithm (SGA) and the "first come, first served" (FCFS) method, the total waiting time, scheduled time, and maximum waiting time are decreased significantly through SAMPGA. The results show that the proposed model and algorithm can ensure safety and improve the efficiency of vessel transportation scheduling simultaneously. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Vessel transportation One-way channel Channel-berth coordination scheduling optimization Simulated annealing and multiple population genetic algorithm (SAMPGA)

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