Manufacturing Resource Management and Control for Production Site of Complex Products

In response to the complex composition,scattered data storage,and differences in management levels of manufacturing resources in the production site of complex products,the research and application of digital technology for perception and control of manufacturing resources in the production site of complex products are of great significance for accelerating the digital transformation and upgrading of complex product manufacturing enterprises.Firstly,focusing on the problems of single element of local management,high cost of heterogeneous integration of multiple data sources,and the difficulty in cleaning up the global status of manufacturing resources in the production site of complex products,basic requirements and core requirements of enterprises for global management and control of manufacturing resources in the production site are deeply analyzed.Secondly,the indicators and data sources of different manufacturing resources that managers at different levels are concerned about are analyzed,providing guidance for refined management.Thirdly,a reference architecture of the manufacturing resource management and control platform for the production site of complex products is proposed,supporting access,integration,and global unified management of manufacturing resource information through the access strategy,data,basic component,and APP layers.Finally,the feasibility,effectiveness,and practicality of the architecture are verified through practical cases,aiming to provide a reference for the manufacturing resource management of complex product manufacturing enterprises.

Resource management framework for manufacturing grid

Based on open grid service architecture (OGSA) and Globus Toolkit 3. 0 (GT3), a manufacturing grid (MG) is proposed to realize resource sharing and collaborative working among manufacturing enterprises. Nevertheless, resource management in MG is much more complicated than that in other grid applications due to the geographically distributed manufacturing resources, which range from CAD, CAPP and CAE to various kinds of machine tools. With the interaction of manufacturing grid information service (MGIS, developed by ourselves) and globus resource allocation manager (GRAM, provided by GT3), a resource management framework is presented to perform the functions of resource encapsulation, registry, discovery and monitoring. Furthermore, the application architecture and an example are depicted to illustrate the utilization of the resource management system.

Manufacturing Resource Planning Technology Based on Genetic Programming Simulationnn

Network-based manufacturing is a kind of distributed system, which enables manufacturers to finish production tasks as well as to grasp the opportunities in the market, even if manufacturing resources are insufficient. One of the main problems in network-based manufacturing is the allocation of resources and the assignment of tasks rationally, according to flexible resource distribution. The mapping rules and relations between production techniques and resources are proposed, followed by the definition of the resource unit. Ultimately, the genetic programming method for the optimization of the manufacturing system is put forward. A set of software for the optimization system of simulation process using genetic programming techniques has been developed, and the problems of manufacturing resource planning in network-based manufacturing are solved with the simulation of optimizing methods by genetic programming. The optimum proposal of hardware planning, selection of company and scheduling will be obtained in theory to help company managers in scientific decision-making.

Resources publication and discovery in manufacturing grid

In the manufacturing grid＇s architecture, Resources Management System （RMS） is the central component responsible for disseminating resource information across the grid, accepting requests for resources, discovering and scheduling the suitable resources that match the requests for the global grid resource, and executing the requests on scheduled resources. In order to resolve the problem of resources publication and discovery in Manufacturing Grid （MGrid）, the classification of manufacturing resources is first researched after which the resources encapsulation class modes are put forward. Then, a scalable two-level resource management architecture is constructed on the model, which includes root nodes, domain nodes and leaf nodes. And then an RIMS is proposed, and the resources publication and discovery mechanism are detailedly described. At last, an application prototype is developed to show the validity and the practicability of the proved theory and method.

The Cloud Manufacturing Resource Scheduling Optimization Method Based on Game Theory

In order to optimize resource integration and optimal scheduling problems in the cloud manufacturing environment,this paper proposes to use load balancing,service cost and service quality as optimization goals for resource scheduling,however,resource providers have resource utilization requirements for cloud manufacturing platforms.In the process of resource optimization scheduling,the interests of all parties have conflicts of interest,which makes it impossible to obtain better optimization results for resource scheduling.Therefore,amultithreaded auto-negotiation method based on the Stackelberg game is proposed to resolve conflicts of interest in the process of resource scheduling.The cloud manufacturing platform first calculates the expected value reduction plan for each round of global optimization,using the negotiation algorithm based on the Stackelberg game,the cloud manufacturing platformnegotiates andmediateswith the participants’agents,to maximize self-interest by constantly changing one’s own plan,iteratively find multiple sets of locally optimized negotiation plans and return to the cloud manufacturing platform.Through multiple rounds of negotiation and calculation,we finally get a target expected value reduction plan that takes into account the benefits of the resource provider and the overall benefits of the completion of the manufacturing task.Finally,through experimental simulation and comparative analysis,the validity and rationality of the model are verified.

Research on Cloud Manufacturing Resource-Aware and Access Technology Using RFID

With the continuous development of cloud manufacturing technology,in order to solve more complex manufacturing problem and conduct large-scale networked manufacturing,combining with the characteristic of discrete manufacturing enterprise's demands and RFID( Radio Frequency Identification),a kind of RFIDbased cloud manufacturing resource-aware and access technology is proposed. Firstly,the architecture of the cloud manufacturing system and RFID system is briefly introduced. Then,the key technologies of manufacturing resource-aware and access technology are analyzed,including anti-collision technology,reader management technology and so on. Finally,taking the manufacturing of the key components in discrete manufacturing enterprise as an example,the practicality and feasibility of the technology is verified. The results show that the application of this technology provides a strong guarantee for the sharing and collaboration of manufacturing resources and capacity in the discrete manufacturing industry.

Simulation Based Energy-resource Efficient Manufacturing Integrated with In-process Virtual Management

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow （productivity） and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

Research of Enterprise Resource Management Supporting Networked Manufacturing

The nature of networked manufacturing and agile manufacturing is to recognize enterprise resources timely and accurately. This paper mainly discusses an enterprise resource model method and the construction process. Furthermore, the system frameworks of software and application are put forward to realize various enterprise resources management based on a resource business process. Thus, we ensure the integration and sharing of enterprise resources for the requirement of networked manufacturing.

A Heuristic for Resource Reconfiguration of Agile Manufacturing Supply Chain

The agile manufacturing is a new conception for rap id reaction to the consumers. One of its implements is establishing a virtual ente rprise (VE) around the task, where each manufacturing unit, or sub-task, probab ly have at least one resource, or referred to as suppliers. Because each manufac turing unit might be carried out in different geographical places that implies t his probably gives rise to transportation cost, the selection of resources for e ach manufacturing unit must considers not only the manufacturing price of each r esource but also the transfer cost between any two potential resources. This pap er discusses the resource reconfiguration problem with two hypotheses: 1. Permit s one or more resources to attend the same manufacturing unit as long as the tot al cost can reach its least; 2. The freight contains the initial part, that is t he freight concave. Indeed, these hypotheses are much meaningful in the real wor ld. Furthermore, to simplify the solution for this problem, we propose two conce pts: assembly tree (AT) and combinatorial mode base (CMB). Formally an AT is a c omplete production line, which can ensure the parts equilibrium, and its capacit y is subjected to the least capacity of every resources and every path in it. In the end, we propose an implicit enumeration algorithm (IEA) by the use of CMB, including it is a heuristic algorithm for integer programming (HAIP) by the use of AT. The IEA can be outlined that for a determined combinatorial mode, if it h as not enumerated, we use the HAIP to get an near optima and corresponding CMB, marking every combinatorial mode extended from the CMB as enumerated, other cont inue a new iteration. The HAIP can be outlined that for a determined combinatori al mode, there are some determined number of AT, we select an AT with the le ast slope, and select the volume of this AT to its ultimate within its capacity, iterates this doing until the needed volume reached. In the end, we conclude th is paper and prospect the deep research based on GA thought.

The Optimization of Manufacturing Resources Allocation Considering the Geographical Distribution

From the perspective of the geographical distribution, considering production fare, supply chain information and quality rating of the manufacturing resource(MR), a manufacturing resource allocation(MRA) model considering the geographical distribution in cloud manufacturing(CM) environment is built. The model includes two stages, preliminary selection stage and optimal selection stage. The membership function is used to select MRs from cloud resource pool(CRP) in the first stage, and then the candidate resource pool is built. In the optimal selection stage, a multi-objective optimization algorithm, particle swarm optimization(PSO) based on the method of relative entropy of fuzzy sets(REFS_PSO), is used to select optimal MRs from the candidate resource pool, and an optimal manufacturing resource supply chain is obtained at last. To verify the performance of REFS_PSO, NSGA-Ⅱ and PSO based on random weighting(RW_PSO) are selected as the comparison algorithms. They all are used to select optimal MRs at the second stage. The experimental results show solution obtained by REFS_PSO is the best. The model and the method proposed are appropriate for MRA in CM.

Segregation Treatment and Resource Recycling of Enteric Coating and Heparin Sodium Manufacturing Wastewater

Firstly, the water-quality characteristics of intestinal lavage wastewater and enzymolysis wastewater from the typical heparin sodium pro- ductive process were analyzed, and then the segregation treatment was applied in the treatment of enteric coating and heparin sodium manufacturing wastewater. Finally, the treatment of the two kinds of wastewater by different methods were discussed. The results showed that, COD of enzymolysis wastewater treated by centrifugation-coagulation-Fenton reagent oxidation-adsorption process was lower than 100 mg/L, while intestinal lavage wastewater treated by coagulation-ASBR-SBR process could meet the first standard of Comprehensive Discharge Standard of Sewage （GB8978-1996） after one month of continuous operation.

Study on the Manufacturability Evaluation Based on Double-layer Model of Manufacturing Resources

Virtual organization is a new production patter and a principal part in advanced manufacturing systems such as agile manufacturing. Manufacturability evaluation is the necessary condition to form the virtual organization. A new manufacturability evaluation approach is described in this paper, which is carried out based on every process feature under the double-layer model of manufacturing resources proposed by authors. The manufacturing resources that build up the virtual organization are selected according to the results of manufacturability evaluation.

Dynamic Allocation of Manufacturing Tasks and Resources in Shared Manufacturing

Shared manufacturing is recognized as a new point-to-point manufac-turing mode in the digital era.Shared manufacturing is referred to as a new man-ufacturing mode to realize the dynamic allocation of manufacturing tasks and resources.Compared with the traditional mode,shared manufacturing offers more abundant manufacturing resources and flexible configuration options.This paper proposes a model based on the description of the dynamic allocation of tasks and resources in the shared manufacturing environment,and the characteristics of shared manufacturing resource allocation.The execution of manufacturing tasks,in which candidate manufacturing resources enter or exit at various time nodes,enables the dynamic allocation of manufacturing tasks and resources.Then non-dominated sorting genetic algorithm(NSGA-II)and multi-objective particle swarm optimization(MOPSO)algorithms are designed to solve the model.The optimal parameter settings for the NSGA-II and MOPSO algorithms have been obtained according to the experiments with various population sizes and iteration numbers.In addition,the proposed model’s efficiency,which considers the entries and exits of manufacturing resources in the shared manufacturing environment,is further demonstrated by the overlap between the outputs of the NSGA-II and MOPSO algorithms for optimal resource allocation.

Research on Evaluation and Management of Networked Manufacturing Resources Based on WUXIASP

The data models and description of manufacturing resources are discussed for realizing distributed networked manufacturing and the multi-goal evaluating model is put forward. The factors and process in networked manufacturing resources evaluating are given, and the service function and the system architecture of WUXIASP is set up. It is useful to actualize area networked manufacture.

Resource Encapsulation in Manufacturing Grid Environment

A feasible hierarchical structure of MG is introduced and an XML format to describe manufacturing resource, an embedded NC system is illustrated. An example of encapsulated resource sharing is given to demonstrate the processes involved in realizing a user＇s request for a CAD resource service through parallel design and computing.

A Multi-Agent Resource Selection Model in Manufacturing Grid Environment

A group of agents are intimately cooperated to set the assessment indices, establish the weight of each index in overall result of evaluation, collect the experts＇ scores given to each available resource, and the manufacturing resource whose overall assessment value is highest is taken as the optimal choice. Architecture of the proposed system is outlined and an example is offered to show the process of accomplishing the assessment.

AI-Driven Resource and Communication-Aware Virtual Machine Placement Using Multi-Objective Swarm Optimization for Enhanced Efficiency in Cloud-Based Smart Manufacturing

Cloud computing has emerged as a vital platform for processing resource-intensive workloads in smart manu-facturing environments,enabling scalable and flexible access to remote data centers over the internet.In these environments,Virtual Machines(VMs)are employed to manage workloads,with their optimal placement on Physical Machines(PMs)being crucial for maximizing resource utilization.However,achieving high resource utilization in cloud data centers remains a challenge due to multiple conflicting objectives,particularly in scenarios involving inter-VM communication dependencies,which are common in smart manufacturing applications.This manuscript presents an AI-driven approach utilizing a modified Multi-Objective Particle Swarm Optimization(MOPSO)algorithm,enhanced with improved mutation and crossover operators,to efficiently place VMs.This approach aims to minimize the impact on networking devices during inter-VM communication while enhancing resource utilization.The proposed algorithm is benchmarked against other multi-objective algorithms,such as Multi-Objective Evolutionary Algorithm with Decomposition(MOEA/D),demonstrating its superiority in optimizing resource allocation in cloud-based environments for smart manufacturing.

Test and Experiment Study on Synchronous Cooperative Design System Over Networked Manufacturing Platform

Based on the analysis on the previous research in virtual manufacturing and virtual enterprises,this paper pro- vides a novel architecture of networked manufacturing system around the cooperative design.The key technologies for synchronous cooperative design in networked manufacturing platform,such as the cooperative mechanism,cooperative rules,control authority conveyed,cooperative efficiency,are detailed,with which a synchronous cooperative design system is developed.Due to the cooper- ative efficiency is the major bottleneck of the synchronous cooperative design over Internet,this research details the test and experi- ment to demonstrate the practicality of the system.Finally the advantages of the system are illustrated compared with current soft- ware tools.

Strategic Green Supply Chain Based on Circular Economy——A New View for Sustainable Manufacturing in China

Due to recent changing environmental requirements affecting manufacturing operations,increasing attention is given to developing environmental management strategies for the supply chain. This paper discusses the strategies of green supply chain based on the concept of circular economy which was promoted in China as a new development strategy to alleviate the shortage of resource supply by improving the resource productivity and eco-efficiency of production and consumption,which will accelerate the economic transformation from the traditional supply chain to the green supply chain.