Using augmented reality to build digital twin for reconfigurable additive manufacturing system

The extrusion-based additive manufacturing (AM) processes are those where one or multiple tools (usually nozzles) are driven along predefined paths to deposit fabrication materials. They are usually inherently slow because solid contours have to be filled with mere single deposition lines of material. An intuitive way to improve the fabrication speed is to introduce multiple independent actuators for concurrent deposition of materials without collision among them. In this paper, a methodology of using augmented reality (AR) technique is presented to conveniently communicate the layout information between a reconfigurable AM system made of robotic arms and its corresponding digital twin for toolpath planning and simulation. A prototype system made of two desktops AM robotic arms is developed, and transformation matrices are derived to determine the spatial relation between different items in the system, including camera, markers, robotic arms and part substrate. Case studies are conducted to demonstrate the capability of this methodology in automatically retrieving layout information and assisting users to deploy pre-determined layout. The results show that the developed methodology enables rapid retrieval of position information from the physical system layout into the digital twin simulation and optimization and facilitates convenient deployment of an optimized layout determined in the digital twin into the physical system.     

RMS中的基于时间的设备选择方法研究

根据生产需求快速确定制造资源是可重组制造系统高效快速响应市场变化的关键功能之一。文中提出了以系统整体加工时间消耗最少为目标的时间虚负荷矩阵算法,这种算法通过矩阵进行运算,计算简单直观,在计算过程中同时实现设备优化选择和工序分配,这种算法还可应用于车间作业调度。     

A heuristic based on multi-stage programming approach for machine-loading problem in a flexible manufacturing system

Manufacturing industries are rapidly changing from economies of scale to economies of scope, characterized by short product life cycles and increased product varieties. This implies a need to improve the efficiency of job shops while still maintaining their flexibility. These objectives are achieved by Flexible manufacturing systems (FMS). The basic aim of FMS is to bring together the productivity of flow lines and the flexibility of job shops. This duality of objectives makes the management of an FMS complex. In this article, the loading problem in random type FMS, which is viewed as selecting a subset of jobs from the job pool and allocating them among available machines, is considered. A heuristic based on multi-stage programming approach is proposed to solve this problem. The objective considered is to minimize the system unbalance while satisfying the technological constraints such as availability of machining time and tool slots. The performance of the proposed heuristic is tested on 10 sample problems available in FMS literature and compared with existing solution methods. It has been found that the proposed heuristic gives good results.     

Automatic multi-direction slicing algorithms for wire based additive manufacturing

One of the key challenges in Additive Manufacturing is to develop a robust algorithm to slice CAD models into a set of layers which requires minimal support structures. This paper reports the concept and implementation of a new strategy for multi-direction slicing of CAD models represented in STL format. Differing from the existing multi-direction slicing approaches that are mainly focused on finding an optimal volume decomposition strategy, this study presents a decomposition-regrouping method. The CAD model is firstly decomposed into sub-volumes using a simple curvature-based volume decomposition method. Then a depth-tree structure based on topology information is introduced to merge them into ordered groups for slicing. In addition, a model simplification step is introduced before CAD model decomposition to significantly enhance the capability of the proposed multi-direction strategy. The proposed strategy is shown to be simple and efficient on various tests parts especially for geometries with large number of holes.     

Deadlock prevention for flexible manufacturing system

Deadlock must be prevented via the shop controller during the flexible manufacturing system （FMS） performing. Various models have been tried for the analysis and design of shop controller. Petri net is suitable to describe the dynamic behavior of the discrete event system, such as concurrency, conflict and deadlock, however, the verification of the .system behavior needs structure analysis with complex theoretical proof method. Temporal logic model checking has important advantages over traditional theorem prover. It is flatly automatic and can produce possible counter-example which is particularly important in finding subtle error in complex transition systems. In this paper, a new method for the deadlock prevention based on Petri net and Temporal Logic model checking is presented. The specification in the Temporal Logic is expressed according to some result of structure analysis of the Petri net. The model checking is employed to execute the formal verification, which will conduct an exhaustive exploration of all possible behaviors. Finally, an example is presented to demonstrate how the method works.     

Deadlock p revention f or flexible manufacturing system

Deadlock must be prevented via the shop controller during the flexible manufacturing system (FMS) performing. Various models have been tried for the analysis and design of shop controller. Petri net is suitable to describe the dynamic behavior of the discrete event system , such as concurrency , conflict and deadlock , however , the verification of the system behavior needs ructure analysis with complex theoretical proof method. Temporal logic model checking has important advantages over traditional theorem prover. It is fully automatic and can produce possible unter- example which is particularly important in finding subtle error in complex transition systems. In this paper ,a new method for the deadlock prevention based on Petri net and Temporal Logic model checking is presented. The specification in the Temporal Logic is expressed according to some result of structure analysis of the Petri net . The model checking is employed to execute the formal verification ,which will conduct an exhaustive exploration of all possible behaviors. Finally ,an example is presented to demonstrate how the method works.     

可重构制造系统故障诊断多Agent自学习模型

提出了一种基于多Agent的可重构制造系统故障诊断自学习模型,模型为3层结构,从下向上分别为监测Agent层、诊断Agent层和管理Agent层,详细分析了模型的故障诊断自学习机理,自学习性是基于数据挖掘和基于粗糙集的.示例表明可重构制造系统重构前后,均能有效完成故障诊断.     

Support slimming for single material based additive manufacturing

In layer-based additive manufacturing (AM), supporting structures need to be inserted to support the overhanging regions. The adding of supporting structures slows down the speed of fabrication and introduces artifacts onto the finished surface. We present an orientation-driven shape optimizer to slim down the supporting structures used in single material-based AM. The optimizer can be employed as a tool to help designers to optimize the original model to achieve a more self-supported shape, which can be used as a reference for their further design. The model to be optimized is first enclosed in a volumetric mesh, which is employed as the domain of computation. The optimizer is driven by the operations of reorientation taken on tetrahedra with ‘facing-down’ surface facets. We formulate the demand on minimizing shape variation as global rigidity energy. The local optimization problem for determining a minimal rotation is analyzed on the Gauss sphere, which leads to a closed-form solution. Moreover, we also extend our approach to create the functions of controlling the deformation and searching for optimal printing directions.     

Optimizing modular product design for reconfigurable manufacturing

The problem of optimizing modular products in a reconfigurable manufacturing system is addressed. The problem is first posed as a generalized subset selection problem where the best subsets of module instances of unknown sizes are determined by minimizing an objective function that represents a trade-off between the quality loss due to modularization and the cost of reconfiguration while satisfying the problem constraints. The problem is then formulated and solved as an integer nonlinear programming problem with binary variables. The proposed method is applied to the production of a modular drive system composed of a DC motor and a ball screw. The study is a first attempt toward developing a systematic methodology for manufacturing modular products in a reconfigurable manufacturing system.     

Trends and perspectives in flexible and reconfigurable manufacturing systems

To better understand future needs in manufacturing and their enabling technologies, a survey of experts in manufacturing has been conducted. The survey instrument (i.e., questionnaire) tries to assess the experience to date with the use of flexible manufacturing systems (FMS) and to examine the potential roles and enabling technologies for reconfigurable manufacturing systems (RMS). The results show that two-thirds of respondents stated that FMSs are not living up to their full potential, and well over half reported purchasing FMS with excess capacity (which was eventually used) and excess features (which in many cases were not eventually used). They identified a variety of problems associated with FMS, including training, reconfigurability, reliability and maintenance, software and communications, and initial cost. However, despite these issues, nearly 75% of respondent expressed their desire to purchase additional, or expand existing FMSs. The experts agreed that RMS (which can provide exactly the capacity and functionality needed, exactly when needed) is a desirable next step in the evolution of production systems. The key enabling technologies for RMS were identified as modular machines, open-architecture controls, high-speed machining, and methods, training and education for the operation of manufacturing systems.     

Simulation modelling and analysis of part and tool flow control decisions in a flexible manufacturing system

This paper presents the details of a simulation study carried out for analyzing the impact of scheduling rules that control part launching and tool request selection decisions of a flexible manufacturing system (FMS) operating under tool movement along with part movement policy. Two different scenarios have been investigated with respect to the operation of FMS. In scenario 1, the facilities such as machines, tool transporter and part transporter are assumed to be continuously available without breakdowns, whereas in scenario 2, these facilities are prone to failures. For each of these scenarios, a discrete-event simulation model is developed for the purpose of experimentation. A number of scheduling rules are incorporated in the simulation models for the part launching and tool request selection decisions. The performance measures evaluated are mean flow time, mean tardiness, mean waiting time for tool and percentage of tardy parts. The results obtained through the simulation have been statistically analyzed. The best possible scheduling rule combinations for part launching and tool request selection have been identified for the chosen FMS.     

Physical simulation of work scheduling rules in a flexible manufacturing system

This paper describes a physical simulator of an actual flexible manufacturing system. The simulator was used to evaluate work scheduling rules for both part selection and machine selection. Twenty-eight decision rule sets were simulated and evaluated under six major performance criteria.     

Using mega-trend-diffusion and artificial samples in small data set learning for early flexible manufacturing system scheduling knowledge

Neural networks are widely utilized to extract management knowledge from acquired data, but having enough real data is not always possible. In the early stages of dynamic flexible manufacturing system (FMS) environments, only a litter data is obtained, and this means that the scheduling knowledge is often unreliable. The purpose of this research is to utilize data expansion techniques for an obtained small data set to improve the accuracy of machine learning for FMS scheduling. This research proposes a mega-trend-diffusion technique to estimate the domain range of a small data set and produce artificial samples for training the modified backpropagation neural network (BPNN). The tool used is the Pythia software. The results of the FMS simulation model indicate that learning accuracy can be significantly improved when the proposed method is applied to a very small data set.     

A non-retraction path planning approach for extrusion-based additive manufacturing

Notwithstanding the widespread use and large number of advantages over traditional subtractive manufacturing techniques, the application of additive manufacturing technologies is currently limited by the undesirable fabricating efficiency, which has attracted attentions from a wide range of areas, such as fabrication method, material improvement, and algorithm optimization. As a critical step in the process planning of additive manufacturing, path planning plays a significant role in affecting the build time by means of determining the paths for the printing head's movement. So a novel path filling pattern for the deposition of extrusion–based additive manufacturing is developed in this paper, mainly to avoid the retraction during the deposition process, and hence the time moving along these retracting paths can be saved and the discontinuous deposition can be avoided as well. On the basis of analysis and discussion of the reason behind the occurrence of retraction in the deposition process, a path planning strategy called “go and back” is presented to avoid the retraction issue. The “go and back” strategy can be adopted to generate a continuous extruder path for simple areas with the start point being connected to the end point. So a sliced layer can be decomposed into several simple areas and the sub-paths for each area are generated based on the proposed strategy. All of these obtainable sub-paths can be connected into a continuous path with proper selection of the start point. By doing this, separated sub-paths are joined with each other to decrease the number of the startup and shutdown process for the extruder, which is beneficial for the enhancement of the deposition quality and the efficiency. Additionally, some methodologies are proposed to further optimize the generated non-retraction paths. At last, several cases are used to test and verify the developed methodology and the comparisons with conventional path filling patterns are conducted. The results show that the proposed approach can effectively reduce the retraction motions and is especially beneficial for the high efficient additive manufacturing without compromise on the part resistance.     

A strategic investment model for phased implementation of flexible manufacturing systems

This paper describes a set of strategic, tactical, and operational models that can be used to analyze the phased implementation of flexible technology in a manufacturing system. The strategic model represents capital investment decisions, the tactical model represents aggregate production decisions, and the operational model represents the functional form of the production costs. Learning effects and other nonlinearities (such as setup costs, economies of scale, and congestion effects) can be quantified in the models. An efficient solution procedure (using dynamic programming and minimum cost network flow optimization) is described. The efficiency of the solution method permits a host of 'what-if' scenarios to be examined by the decision maker.     

A review on wire arc additive manufacturing: Monitoring,control and a framework of automated system

Wire arc additive manufacturing technology (WAAM) has become a very promising alternative to high-value large metal components in many manufacturing industries. Due to its long process cycle time and arc-based deposition, defect monitoring, process stability and control are critical for the WAAM system to be used in the industry. Although major progress has been made in process development, path slicing and programming, and material analysis, a comprehensive process monitoring, and control system are yet to be developed. This paper aims to provide an in-depth review of sensing and control design suitable for a WAAM system, including technologies developed for the generic Arc Welding process, the Wire Arc Additive Manufacturing process and laser Additive Manufacturing. Particular focus is given to the integration of sensor-based feedback control, and how they could be implemented into the WAAM process to improve its accuracy, reliability, and efficiency. The paper concludes by proposing a framework for sensor-based monitoring and control system for the GMAW based WAAM process. This framework provides a blueprint for the monitoring and control strategies during the WAAM process and aims to identify and reduce defects using information fusion techniques.     

Self-supporting rhombic infill structures for additive manufacturing

Recent work has demonstrated that the interior material layout of a 3D model can be designed to make a fabricated replica satisfy application-specific demands on its physical properties, such as resistance to external loads. A widely used practice to fabricate such models is by layer-based additive manufacturing (AM), which however suffers from the problem of adding and removing interior supporting structures. In this paper, we present a novel method for generating application-specific infill structures on rhombic cells so that the resultant structures can automatically satisfy manufacturing requirements on overhang-angle and wall-thickness. Additional supporting structures can be avoided entirely in our framework. To achieve this, we introduce the usage of an adaptive rhombic grid, which is built from an input surface model. Starting from the initial sparse set of rhombic cells, via numerical optimization techniques an objective function can be improved by adaptively subdividing the rhombic grid and thus adding more walls in cells. We demonstrate the effectiveness of our method for generating interior designs in the applications of improving mechanical stiffness and static stability.     

基于GE Fanuc的MPS模块化生产制造系统设计

MPS系统是一种高生产率和可重构的生产制造系统,是时代发展的潮流。利用MPS系统的特点,选用GE Fanuc控制器对其进行进一步的改造。首先分析介绍MPS系统的结构设计及系统组成,并给出系统组成图;然后阐述所构成的各个工作单元的控制功能,并给出相应的程序流程图;最后以加工单元为例,根据给出的I/O分配表编写梯形图程序。运行结果表明,基于GE Fanuc的MPS系统具有较好的可行性,有很大的实际应用意义。     

Evaluations of operational control rules in scheduling a flexible manufacturing system

In this paper, computer simulation is used to evaluate the effects of various control rules on the performance of a flexible manufacturing system (FMS) operating under different manufacturing environment. Alternative routings are available, if the operation of a part can be performed by more than one machine. Three control rules, namely, dynamic alternative routings, planned alternative routings, and no alternative routings, are proposed to control the selection of alternative routings for each part. The effects of the universal loading station and also those of the dedicated loading station are investigated. In addition, the impact of buffer existence on the system’s performance is also examined by considering machines with and without local buffers. The effects of changing production ratios of different part types on the performance of various operational control rules are also investigated. Moreover, the effects of system having machine breakdown are also discussed. The simulation results indicate that the FMS with dedicated loading stations outperforms the FMS with universal loading stations in all aspects. The dynamic alternative routings generally produces the best results in system performance if the universal loading station is provided. The planned alternative routings generally gives the best system performance when both the dedicated loading stations and local buffers are available. The no alternative routings usually remains at the bottom of the rank, occasionally with some exceptions. Problems in actual implementation are also highlighted.     

A hierarchic approach to production planning and scheduling of a flexible manufacturing system

The paper deals with the problem of improving the machine utilization of a flexible manufacturing cell. Limited tool magazine space of the machines turns out to be a relevant bottleneck. A hierarchic approach for this problem is proposed. At the upper level, sets of parts that can be concurrently processed (batches) are determined. At the lower levels, batches are sequenced, linked, and scheduled. Methods taken from the literature are used for the solution of the latter subproblems, and an original mixed integer programming model is formulated to determine batches. The proposed methods are discussed on the basis of computational experience carried out on real instances.