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.

An Improved Hyperplane Assisted Multiobjective Optimization for Distributed Hybrid Flow Shop Scheduling Problem in Glass Manufacturing Systems

To solve the distributed hybrid flow shop scheduling problem(DHFS)in raw glass manufacturing systems,we investigated an improved hyperplane assisted evolutionary algorithm(IhpaEA).Two objectives are simultaneously considered,namely,the maximum completion time and the total energy consumptions.Firstly,each solution is encoded by a three-dimensional vector,i.e.,factory assignment,scheduling,and machine assignment.Subsequently,an efficient initialization strategy embeds two heuristics are developed,which can increase the diversity of the population.Then,to improve the global search abilities,a Pareto-based crossover operator is designed to take more advantage of non-dominated solutions.Furthermore,a local search heuristic based on three parts encoding is embedded to enhance the searching performance.To enhance the local search abilities,the cooperation of the search operator is designed to obtain better non-dominated solutions.Finally,the experimental results demonstrate that the proposed algorithm is more efficient than the other three state-of-the-art algorithms.The results show that the Pareto optimal solution set obtained by the improved algorithm is superior to that of the traditional multiobjective algorithm in terms of diversity and convergence of the solution.

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.

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.

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.

Modeling the Scheduling Problem in Cellular Manufacturing Systems Using Genetic Algorithm as an Efficient Meta-Heuristic Approach

This paper presents a new,bi-criteria mixed_integer programming model for scheduling cells and pieces within each cell in a manufacturing cellular system.The objective of this model is to minimize the makespan and intercell movements simultaneously,while considering sequence-dependent cell setup times.In the cellular manufacturing systems design and planning,three main steps must be considered,namely cell formation(i.e,piece families and machine grouping),inter and intra-cell layouts,and scheduling issue.Due to the fact that the cellular manufacturing systems problem is NP-Hard,a genetic algorithm as an efficient meta-heuristic method is proposed to solve such a hard problem.Finally,a number of test problems are solved to show the efficiency of the proposed genetic algorithm and the related computational results are compared with the results obtained by the use of an optimization tool.

Decomposition Methods for Manufacturing System Scheduling:A Survey

Manufacturing is the application of labor, tools,machines, chemical and biological processing, to an original raw material by changing its physical and geometrical characteristics, in order to make finished products. Since the first industrial revolution, to accommodate the large-scale production,tremendous changes have happened to manufacturing through the innovations of technology, organization, management, transportation and communication. This work first reviews the highvolume low-mix process by focusing on the quantity production,transfer line and single model assembly line. Then, it reviews the high-volume high-mix process. For such a process type,mixed/multi model assembly line is usually adopted. Hence,two main decisions on them, i.e., balancing and, sequencing are reviewed. Thereafter, it discusses the low-volume high-mix process in detail. Then, technology gap and future work is discussed, and at last, conclusions are given.

Robust Deadlock Avoidance Policy for Automated Manufacturing System With Multiple Unreliable Resources

This work studies the robust deadlock control of automated manufacturing systems with multiple unreliable resources. Our goal is to ensure the continuous production of the jobs that only require reliable resources. To reach this goal, we propose a new modified Banker's algorithm(MBA) to ensure that all resources required by these jobs can be freed. Moreover,a Petri net based deadlock avoidance policy(DAP) is introduced to ensure that all jobs remaining in the system after executing the new MBA can complete their processing smoothly when their required unreliable resources are operational. The new MBA together with the DAP forms a new DAP that is robust to the failures of unreliable resources. Owing to the high permissiveness of the new MBA and the optimality of the DAP, it is tested to be more permissive than state-of-the-art control policies.

Fog-IBDIS:Industrial Big Data Integration and Sharing with Fog Computing for Manufacturing Systems

Industrial big data integration and sharing(IBDIS)is of great significance in managing and providing data for big data analysis in manufacturing systems.A novel fog-computing-based IBDIS approach called Fog-IBDIS is proposed in order to integrate and share industrial big data with high raw data security and low network traffic loads by moving the integration task from the cloud to the edge of networks.First,a task flow graph(TFG)is designed to model the data analysis process.The TFG is composed of several tasks,which are executed by the data owners through the Fog-IBDIS platform in order to protect raw data privacy.Second,the function of Fog-IBDIS to enable data integration and sharing is presented in five modules:TFG management,compilation and running control,the data integration model,the basic algorithm library,and the management component.Finally,a case study is presented to illustrate the implementation of Fog-IBDIS,which ensures raw data security by deploying the analysis tasks executed by the data generators,and eases the network traffic load by greatly reducing the volume of transmitted data.

A Beam Search-based Algorithm for Flexible Manufacturing System Scheduling

A new algorithm is proposed for the flexible manufacturing system (FMS) scheduling problem in this paper. The proposed algorithm is a heuristic based on filtered beam search. It considers the machines and automated guided vehicle (AGV) as the primary resources. It utilizes system constraints and related manufacturing and processing information to generate machines and AGV schedules. The generated schedules can be an entire scheduling horizon as well as various lengths of scheduling periods. The proposed algorithm is also compared with other well-known dispatching rules-based FMS scheduling. The results indicate that the beam search algorithm is a simple, valid and promising algorithm that deserves further research in FMS scheduling field.

Research on Technological Process Control Model of Reverse Logistics in Manufacturing System

This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary,and established four kinds of technological process control models of reverse logistics in manufacturing system according to different processing methods. These models embed each other that form a cubic control system of reverse logistics.

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.

Digital Aircraft Sheet Metal Part Manufacturing System and Its Key Technology

The architecture of digital sheet metal manufacturing system is proposed based on the classification of sheet metal manufacturing information.The essence of digital manufacturing is the definition,management and transfer of information,and the key technologies are brought forward and described.It is pointed out that knowledge-based manufacturing elements design is necessary to make digital technology efficient.The management of all kinds of sheet metal manufacturing element information is to build single source of manufacturing data.Multi-state model-based digital transfer and coordination method is designed to provide a foundation for digital manufacturing of aircraft sheet metal part.The application of digital sheet metal manufacturing is exemplified with an aircraft sheet metal part.The application result is compared to that of the traditional analog transfer technology.It is shown that the developed technology can improve part quality,shorten manufacturing time and lower manufacturing cost.

Development of a Simulation-Based Intelligent Decision Support System for the Adaptive Real-Time Control of Flexible Manufacturing Systems

This paper describes a simulation-based intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS) with machine and tool flexibility. The manufacturing processes involved in FMS are complicated since each operation may be done by several machining centers. The system design approach is built around the theory of dynamic supervisory control based on a rule-based expert system. The paper considers flexibility in operation assignment and scheduling of multi-purpose machining centers which have different tools with their own efficiency. The architecture of the proposed controller consists of a simulator module coordinated with an IDSS via a real time event handler for implementing inter-process synchronization. The controller’s performance is validated by benchmark test problem.

Exploiting Virtual Elasticity of Manufacturing Systems to Respect OTD—Part 2: Post-Optimality Conditions for the Cases of Ergodic and Non-Ergodic Order Rate with Deterministic Product-Mix

Respecting the on-time delivery (OTD) for manufacturing orders is mandatory. However, for non-JIT Batch & Queue Push-manufacturing systems, the compliance of OTD is not intrinsically guaranteed. As an OTD related manufacturing theory is largely missing it is crucial to understand and formalize the necessary conditions of OTD compliance for complex production environments for maximum exploitation of the production capacity. This paper evaluates the conditions of post-optimality while being OTD compliant for production systems, which are characterized by stochastic order rate and a deterministic product-mix. Instead of applying discrete event simulation to explore the real case-by-case order scheduling optimization for OTD compliance, a Cartesian approach is followed. This enables to define theoretically the solution space of order backlog for OTD, which contributes to developing further manufacturing theory. At the base stands the recently defined new concept of virtual manufacturing elasticity by reducing lead-time to increase virtually production capacity. The result has led to defining additional two corollaries to the OTD theorem, which sets up basic OTD theory. Apart from defining the post-optimal requirements to guarantee for orders at least a weak solution for OTD compliance, this paper reveals that for a deterministic product-mix a non-ergodic order arrival rate can be rescheduled into an ergodic order input rate to the shopfloor if the virtual elasticity T is large enough, hence the importance of having fast and flexible production lines.

An Agent-Based Distributed Manufacturing System

Agent theories have shown their promising capability in solving distributed complex system ever since its development. In this paper,one multi-agent based distributed product design and manufacturing planning system is presented. The objective of the research is to develop a distributed collaborative design environment for supporting cooperation among the existing engineering functions. In the system,the functional agents for design,manufacturability evaluation,process planning and scheduling are efficiently integrated with a facilitator agent. This paper firstly gives an introduction to the system structure,and the definitions for each executive agent are then described and a prototype of the proposed is also included at the end part.

Analysis of Key Technologies and Equipments Development of Largescale Melted Extrusion Manufacturing Systems

To develop large-scale RP systems used to producing functional parts and large-sized models has become an urgentcall now. In this paper, a large-scale RP system, MEM600-l, based on the melted extrusion manufacturing (MEM)process has been developed successfully. And the key issues to develop such a system are discussed. Based on theactual forming experiment, it is concluded that the MEM600-l works reliably and the forming efficiency is muchhigher than its parallel equipments.

An Open CNC Based Integrated Measuring,Modeling and Manufacturing System Architecture

A new architecture based on open-architecture CNC of an integrated measuring,modeling and manufacturing system is presented. A 3-axis vertical milling structure is used to achieve the manufacturing function. And a computer vision camera is to be set up on the holder of the milling machine to capture the images of the work-piece and a image data acquisition card is used to translate the image data to the control computer,which acts as the measuring subsystem. Through processing the image data the model of the work-piece is established which plays the role of modeling subsystem. A motion control card is inserted into an industry computer to construct an open CNC system of the type of NC embedded PC which is more sophisticated than other new technologies on open CNC. The embedded motion card burdens the real-time tasks of the system and the IPC does the other management and planning tasks. The IPC together with the motion control card command the three axes of the system to accomplish the manufacturing and measuring functions and further the modeling function.

Study on the Digital Manufacturing System of Ship Model Surface

Because a ship model surface (SMS) is a large double-curved 3-D surface,the machining efficiency of the cur- rent handcraft manufacturing method are very low,and the precision is difficult to control also.In order to greatly improve the machining efficiency and precision of SMS,based on the CAD/CAM/CNC technology,this paper proposed a model of SMS digi- tal manufacturing system,which is composed of five functional modules (preprocess module,CAD module,CAM module,post- process module and CNC module),and a twin-skeg SMS as an example,the key technologies & design principle of the nodtules were investigated also Based on the above research works,the first set of 4-axis SMS Digital Manufacturing System in China has been successfully developed,which can reduce the machining time of the twin-skeg SMS from 30 working days needed for the cur- rent handcrafting manufacturing method to 8 hours now,and which can control more effectively the precision of SMS also.

Generalized Reactive Manufacturing System

Generalized reactive manufacturing system named GRMS is introduced. GRMS is a human-centered system based on Multi-agent. Its management and control organization is made up of three types of agents named device agent,task agent and shop-floor agent. GRMS adopts a top down and bottom- up competition and cooperation strategy based on the dynamic sifter and funnel To constrain the behavior of agents, a reward and penaity policy is introduced into the system and the closed-loop adjustment of GRMS is realized through such policy.Agents for the same task should be cooperated with each other and agents for different tasks should compete for survival in the dynamic changing environment. A distributed-hierarchical architecture with three levels of master-slave relationships among agents are proposed.Self-propelled process planning is also discussed. In order to evaluate GRMS, a time-driven simulation system-GRMOSS is developed to check the physical consistency of GRMS.