Cloud edge integrated security architecture of new cloud manufacturing system

With the rapid development of cloud manufacturing technology and the new generation of artificial intelligence technology,the new cloud manufacturing system(NCMS)built on the connotation of cloud manufacturing 3.0 presents a new business model of“Internet of everything,intelligent leading,data driving,shared services,cross-border integration,and universal innovation”.The network boundaries are becoming increasingly blurred,NCMS is facing security risks such as equipment unauthorized use,account theft,static and extensive access control policies,unauthorized access,supply chain attacks,sensitive data leaks,and industrial control vulnerability attacks.Traditional security architectures mainly use information security technology,which cannot meet the active security protection requirements of NCMS.In order to solve the above problems,this paper proposes an integrated cloud-edge-terminal security system architecture of NCMS.It adopts the zero trust concept and effectively integrates multiple security capabilities such as network,equipment,cloud computing environment,application,identity,and data.It adopts a new access control mode of“continuous verification+dynamic authorization”,classified access control mechanisms such as attribute-based access control,rolebased access control,policy-based access control,and a new data security protection system based on blockchain,achieving“trustworthy subject identity,controllable access behavior,and effective protection of subject and object resources”.This architecture provides an active security protection method for NCMS in the digital transformation of large enterprises,and can effectively enhance network security protection capabilities and cope with increasingly severe network security situations.

A HOLONIC FRAMEWORK OF RECONFIGURABLE SHOP FLOOR CONTROL SYSTEMS IN AUTOMATED MANUFACTURING SYSTEMS

The agility and the flexibility of the current shop floor control systems have been limited so far, owing to the lack of structural flexibility and agility in its control software layer. Most of them are based on traditional hierarchical architecture and the top down approach and depend structurally on their specific configuration and job scheduling. Not only can they hardly satisfactorily adapt to these increasing changes and disturbances, but also make the redevelopment and maintenance of shop floor control system (SFCS) to need high cost and much time. And SFCS based on the heterarchical architecture don′t provide a predictable and high performance system, especially not in the heterogeneous environments, where the resources are scarce and the current decisions have serious repercussions on the future performances. For this reason, the heterarchical control is hardly applied in industry. Obviously, it is necessary to develop a new structural framework of reconfigurable SFCS to improve their agility, flexibility and maintainability. This paper presents a holonic framework of reconfigurable SFCS based on holonic manufacturing concepts. The framework is composed of resource holons, product holons and other staff holons. The model of each holon and the co operative mechanisms of holons are described. To verify the proposed approach experimentally, a prototype reconfigurable SFCS for a flexible manufacturing shop floor producing discrete parts is implemented.

BIO-INSPIRED SELF-ADAPTIVE MANUFACTURING SYSTEM CONTROL ARCHITECTURE

Future manufacturing systems need to cope with frequent changes and disturbances, therefore their control architectures require constant adaptability, agility, stability, self-organization, intelligence, and robustness. Bio-inspired manufacturing system can well satisfy these requirements. For this purpose, by referencing the biological organization structure and the mechanism, a bio-inspired manufacturing cell is presented from a novel view, and then a bio-inspired self-adaptive manufacturing model is established based on the ultra-short feedback mechanism of the neuro-endocrine system. A hio-inspired self-adaptive manufacturing system coordinated model is also established based on the neuro-endocrine-immunity system （NEIS）. Finally, an example based on pheromone communication mechanism indicates that the robustness of the whole manufacturing system is improved by bio-inspired technologies.

Intelligent Examination Monitoring and Maintenance for the Safety of Operation of Flexible Manufacturing Systems

Based on the system of electric power supply for flexible manufacturing systems (FMS), a study has been carried out on the intelligent safety examination, monitoring and maintenance of its running environment. On the basis of the specific feature of the power supply network of an FMS, real time monitoring system of the power supply network and the fault diagnostic expert system for the power equipment have been designed. This system can diagnose not only definite fault phenomena, but also fuzzy, uncertain fault phenomena as well. Fault diagnostic knowledge base for the power equipment has been founded hierarchy architecture model and the method of fault tree analysis. Feasibility of this system has been proved by computer simulation.

Holonic Manufacturing System:the Holonic Revolution

This work shows how to develop a methodology to support and integrate the concepts and projects of the Holonic Manufacturing System(HMS)with the other areas of the organization for full organizational management success,being a new entrepreneurial management,with support of this new technology in the reduction of costs and increased value added.HMS is in the process of being developed in the so-called"Consortium of the Rich Countries for the 21st Century",which involves governments,companies and universities from the first world countries,developing technology and knowledge related to the Holonic Manufacturing System(HMS).This new concept,under development by the above consortium,will allow the countries that hold this advancement to overcome the challenges of the globalized market and gain even more international competitiveness.

Optimal deadlock avoidance Petri net supervisors for automated manufacturing systems

Deadlock avoidance problems are investigated for automated manufacturing systems with flexible routings. Based on the Petri net models of the systems, this paper proposes, for the first time, the concept of perfect maximal resourcetransition circuits and their saturated states. The concept facilitates the development of system liveness characterization and deadlock avoidance Petri net supervisors. Deadlock is characterized as some perfect maximal resource-transition circuits reaching their saturated states. For a large class of manufacturing systems, which do not contain center resources, the optimal deadlock avoidance Petri net supervisors are presented. For a general manufacturing system, a method is proposed for reducing the system Petri net model so that the reduced model does not contain center resources and, hence, has optimal deadlock avoidance Petri net supervisor. The controlled reduced Petri net model can then be used as the liveness supervisor of the system.

Simultaneous scheduling of machines and automated guided vehicles in flexible manufacturing systems using genetic algorithms

The problem of simultaneous scheduling of machines and vehicles in flexible manufacturing system (FMS) was addressed.A spreadsheet based genetic algorithm (GA) approach was presented to solve the problem.A domain independent general purpose GA was used,which was an add-in to the spreadsheet software.An adaptation of the propritary GA software was demonstrated to the problem of minimizing the total completion time or makespan for simultaneous scheduling of machines and vehicles in flexible manufacturing systems.Computational results are presented for a benchmark with 82 test problems,which have been constructed by other researchers.The achieved results are comparable to the previous approaches.The proposed approach can be also applied to other problems or objective functions without changing the GA routine or the spreadsheet model.

MANUFACTURING SYSTEM SCHEDULING BASED ON MULTI-AGENT COOPERATION GAME

Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduling problems and forming the cOrrespOnding agents. Then, the importance and the restriction of each agent are cOnsidered, to obtain an order of simple scheduling problems based on the cooperation game theory. With this order, the scheduling of sub-questions is implemented in term of rules, and the almost optimal scheduling results for meeting the restriction can be obtained. Experimental results verify the effectiveness of the proposed scheduling algorithm.

Intelligent Manufacturing Systems in COVID‑19 Pandemic and Beyond:Framework and Impact Assessment

Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks.The intelligent manufacturing(IM)systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms.The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network,which mitigates the severity of industrial chain disruption.In this study,we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks.Considering the constraints of the IM resources,we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

Motion/Posture Modeling and Simulation Verification of Physically Handicapped in Manufacturing System Design

Non-obstacle design is critical to tailor physically handicapped workers in manufacturing system. Simultaneous consideration of variability in physically disabled users, machines and environment of the manufacturing system is extremely complex and generally requires modeling of physically handicapped interaction with the system. Most current modeling either concentrates on the task results or functional disability. The integration of physical constraints with task constraints is far more complex because of functional disability and its extended influence on adjacent body parts. A framework is proposed to integrate the two constraints and thus model the specific behavior of the physical handicapped in virtual environment generated by product specifications. Within the framework a simplified model of physical disabled body is constructed, and body motion is generated based on 3 levels of constraints（effecter constraints, kinematics constraints and physical constraints）. The kinematics and dynamic calculations are made and optimized based on the weighting manipulated by the kinematics constraints and dynamic constraints. With object transferring task as example, the model is validated in Jack 6.0. Modelled task motion elements except for squatting and overreaching well matched with captured motion elements. The proposed modeling method can model the complex behavior of the physically handicapped by integrating both task and physical disability constraints.

Component-based Control Software Design for Flexible Manufacturing System

A new method that designs and implements the component-based distributed & hierarchical flexible manufacturing control software is described with a component concept in this paper. The proposed method takes aim at improving the flexibility and reliability of the control system. On the basis of describing the concepts of component-based software and the distributed object technology, the architecture of the component-based software of the control system is suggested with the Common Object Request Broker Architecture (CORBA). And then, we propose a design method for component-based distributed & hierarchical flexible manufacturing control system. Finally, to verify the software design method, a prototype flexible manufacturing control system software has been implemented in Orbix 2.3c, VC + + 6. 0 and has been tested in connection with the physical flexible manufacturing shop at the WuXi Professional Institute.

Social Sensors (S^2ensors): A Kind of Hardware-Software-Integrated Mediators for Social Manufacturing Systems Under Mass Individualization

Currently, little work has been devoted to the mediators and tools for multi-role production interactions in the mass individualization environment. This paper proposes a kind of hardware-software-integrated mediators called social sensors （S2ensors） to facilitate the production interactions among customers, manufacturers, and other stakeholders in the social manufacturing systems （SMS）. The concept, classification, operational logics, and for- malization of S2ensors are clarified. S2ensors collect sub- jective data from physical sensors and objective data from sensory input in mobile Apps, merge them into meaningful information for decision-making, and finally feed the decisions back for reaction and execution. Then, an S2en- sors-Cloud platform is discussed to integrate different S2- ensors to work for SMSs in an autonomous way. A demonstrative case is studied by developing a prototype system and the results show that S2ensors and S2ensors- Cloud platform can assist multi-role stakeholders interact and collaborate for the production tasks. It reveals the mediator-enabled mechanisms and methods for production interactions among stakeholders in SMS.

Configuration Selection for Reconfigurable Manufacturing Systems by Means of Characteristic State Space

The configuration selection for reconfigurable manufacturing systems（RMS） have been tackled in a number of studies by using analytical or simulation models. The simulation models are usually based on fewer assumptions than the analytical models and therefore are more wildly used in modeling complex RMS. But in the absence of an efficient gradient analysis method of the objective function, it is time-consuming in solving large-scale problems by using a simulation model coupled with a meta-heuristics algorithm. In this paper, a new approach by means of characteristic state space is presented to improve the efficiency of the configuration selection for an RMS. First, a characteristic state equation is set up to represent the input and the output resources of each basic activity in an RMS. A production process model in terms of matrix equations is established by iterating the equations of basic activities according to the resource flows. This model introduces the production process into a characteristic state space for further analysis. Second, the properties of the characteristic state space are presented. On the basis of these properties, the configuration selection in an RMS is considered as a path-planning problem, and the gradient of the objective function is computed. Modified simulated annealing（SA） is also presented, in which neighborhood generation is guided by the gradient to accelerate convergence and reduce the run time of the optimization procedure. Finally, several case studies on the configuration selection for some actual reconfigurable assembly job-shops are presented and compared to the classical SA. The comparison shows relatively positive results. This study provides a more efficient configuration selection approach by using the gradient of the objective function and presents the relevant theories on which it is based.

Layout Planning Technology of Cellular Manufacturing System Based on Process Interconnection Analysis

With sustaining change of production mode,layout planning is no longer a thing built once for all.Cellular layout(CL) is becoming a hotspot in the research field of manufacturing system layout.Traditional researches on layout planning are mainly concentrating on aspects of layout arithmetic,style and evaluation,etc.Relatively seldom efforts are paid to CL and its specific problems as cell formation(CF),equipment sharing and CL analysis.Through problem analyzing of layout in cellular manufacturing system(CMS),research approach of cell formation,interactive layout and layout analysis threaded with process interconnection relationship(PIR) is proposed.Typical key technologies in CL like CF technology based on similarity analysis of part processes,interactive visual layout technology,layout evaluation technology founded on PIR analysis and algorithm of cell equipment sharing are put forward.Against the background of one enterprise which encounters problems of low utility of key equipments and disperse material logistic,an example of four-cell layout is given.The CL adjustment and analysis results show that equipment with high level of sharing degree should be disposed around the boundary of its main cell,and be near to other sharing cells as possible; process route should be centralized by all means,so equipment adjustment is to be implemented along direction that route intersection can be decreased; giving consideration to the existence of discrete cell,logistic route and its density should be centralized to cells formed.The proposed research can help improve equipment utility and material logistic efficiency of CL,and can be popularized to other application availably.

An Edge-Fog-Cloud Computing-Based Digital Twin Model for Prognostics Health Management of Process Manufacturing Systems

The prognostics health management(PHM)fromthe systematic viewis critical to the healthy continuous operation of processmanufacturing systems(PMS),with different kinds of dynamic interference events.This paper proposes a three leveled digital twinmodel for the systematic PHMof PMSs.The unit-leveled digital twinmodel of each basic device unit of PMSs is constructed based on edge computing,which can provide real-time monitoring and analysis of the device status.The station-leveled digital twin models in the PMSs are designed to optimize and control the process parameters,which are deployed for the manufacturing execution on the fog server.The shop-leveled digital twin maintenancemodel is designed for production planning,which gives production instructions fromthe private industrial cloud server.To cope with the dynamic disturbances of a PMS,a big data-driven framework is proposed to control the three-level digital twin models,which contains indicator prediction,influence evaluation,and decisionmaking.Finally,a case study with a real chemical fiber system is introduced to illustrate the effectiveness of the digital twin model with edge-fog-cloud computing for the systematic PHM of PMSs.The result demonstrates that the three-leveled digital twin model for the systematic PHM in PMSs works well in the system’s respects.

Scheduling optimization of task allocation in integrated manufacturing system based on task decomposition

How to deal with the collaboration between task decomposition and task scheduling is the key problem of the integrated manufacturing system for complex products. With the development of manufacturing technology, we can probe a new way to solve this problem. Firstly, a new method for task granularity quantitative analysis is put forward, which can precisely evaluate the task granularity of complex product cooperation workflow in the integrated manufacturing system, on the above basis; this method is used to guide the coarse-grained task decomposition and recombine the subtasks with low cohesion coefficient. Then, a multi-objective optimieation model and an algorithm are set up for the scheduling optimization of task scheduling. Finally, the application feasibility of the model and algorithm is ultimately validated through an application case study.

STOCHASTIC OBJECT-ORIENTED PETRI NETS (SOPNS) AND ITS APPLICATION IN MODELING OF MANUFACTURING SYSTEM RELIABILITY

Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.

Enabling Technology of Multiagent Manufacturing System:A Novel Mode of Self-organizing IoT Manufacturing

As the manufacturing mode focuses more on network and community,the orders and production processes are becoming highly dynamic and unpredictable.The traditional manufacturing system cannot handle those exceptional events such as rush orders and machine breakdowns.Nevertheless,the multiagent manufacturing system(MAMS)becomes a critical pattern to deal with these disturbances in a real-time way.However,due to the lack of universality,MAMS is difficult to be applied to industrial sites.A new multiagent architecture and the relay cooperation model based on a positive process relation matrix are proposed to address this paper’s issue.An optimized contract net protocol(CNP)-based negotiation mechanism is developed to improve the efficiency of collaboration in the proposed architecture.Finally,a case study of self-organizing internet of things(Io T)manufacturing system is used to test the feasibility and effectiveness of the method.It is shown that the proposed self-organizing Io T manufacturing mode outperforms the traditional manufacturing system in terms of makespan and critical machine workload balancing under disturbances through comparison.

A Reconfigurable Manufacturing System for In-site Machining Component with Large Scale

To cope with various unpredictable changes in large scale parts,the concept of reconfigurable manufacturing system (RMS) for machining these components is presented.Considering with large-size space measurement and the fixed-free manufacture mode,an automatically localizing machining method for large scale part is studied in this paper,and the architecture of the RMS for machining large scale parts is proposed.According to the method and structure,the automatically localizing model is established.The theoretical analysis and simulation examples demonstrate the feasibility and validity of the proposed method,and the results indicate that the method is suitable and effective for machining large scale components in significant scientific projects.