Parallel Manufacturing for Industrial Metaverses: A New Paradigm in Smart Manufacturing

To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social Systems (CPSSs) and the Internet of Minds (IoM) are regarded as its infrastructures and the "Artificial systems", "Computational experiments" and "Parallel execution" (ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R & D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation (KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations (DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case, especially the unmanned production line named FlexVega.      

Digital twin-based industrial cloud robotics: Framework,control approach and implementation

Industrial cloud robotics (ICR) integrates cloud computing with industrial robots (IRs). The capabilities of industrial robots can be encapsulated as cloud services and used for ubiquitous manufacturing. Currently, the digital models for process simulation, path simulation, etc. are encapsulated as cloud services. The digital models in the cloud may not reflect the real state of the physical robotic manufacturing systems due to inaccurate or delayed condition update and therefore result in inaccurate simulation and robotic control. Digital twin can be used to realize fine sensing control of the physical manufacturing systems by a combination of high-fidelity digital model and sensory data. In this paper, we propose a framework of digital twin-based industrial cloud robotics (DTICR) for industrial robotic control and its key methodologies. The DTICR is divided into physical IR, digital IR, robotic control services, and digital twin data. First, the robotic control capabilities are encapsulated as Robot Control as-a-Service (RCaaS) based on manufacturing features and feature-level robotic capability model. Then the available RCaaSs are ranked and parsed. After manufacturing process simulation with digital IR models, RCaaSs are mapped to physical robots for robotic control. The digital IR models are connected to the physical robots and updated by sensory data. A case is implemented to demonstrate the workflow of DTICR. The results show that DTICR is capable to synchronize and merge digital IRs and physical IRs effectively. The bidirectional interaction between digital IRs and physical IRs enables fine sensing control of IRs. The proposed DTICR is also flexible and extensible by using ontology models.     

Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces

A time-optimal motion planning method for robotic machining of sculptured surfaces is reported in this paper. Compared with the general time-optimal robot motion planning, a surface machining process provides extra constraints such as tool-tip kinematic limits and complexity of the curved tool path that also need to be taken into account. In the proposed method, joint space and tool-tip kinematic constraints are considered. As there are high requirements for tool path following accuracy, an efficient numerical integration method based on the Pontryagin maximum principle is adopted as the solver for the time-optimal tool motion planning problem in robotic machining. Nonetheless, coupled and multi-dimensional constraints make it difficult to solve the problem by numerical integration directly. Therefore, a new method is provided to simplify the constraints in this work. The algorithm is implemented on the ROS (robot operating system) platform. The geometry tool path is generated by the CAM software firstly. And then the whole machine moving process, i.e. the feedrate of machining process, is scheduled by the proposed method. As a case study, a sculptured surface is machined by the developed method with a 6-DOF robot driven by the ROS controller. The experimental results validate the developed algorithm and reveal its advantages over other conventional motion planning algorithms for robotic machining.     

PDE-based robust robotic navigation

In robotic navigation, path planning is aimed at getting the optimum collision-free path between a starting and target locations. The optimality criterion depends on the surrounding environment and the running conditions. In this paper, we propose a general, robust, and fast path planning framework for robotic navigation using level set methods. A level set speed function is proposed such that the minimum cost path between the starting and target locations in the environment, is the optimum planned path. The speed function is controlled by one parameter, which takes one of three possible values to generate either the safest, the shortest, or the hybrid planned path. The hybrid path is much safer than the shortest path, but less shorter than the safest one. The main idea of the proposed technique is to propagate a monotonic wave front with a particular speed function from a starting location until the target is reached and then extracts the optimum planned path between them by solving an ordinary differential equation (ODE) using an efficient numerical scheme. The framework supports both local and global planning for both 2D and 3D environments. The robustness of the proposed framework is demonstrated by correctly extracting planned paths of complex maps.     

Coverage path planning with targetted viewpoint sampling for robotic free-form surface inspection

Surface metrology systems are increasingly used for inspecting dimensional quality in manufacturing. The gauge of these measurement systems is often mounted as an end-effector on robotic systems to exploit the robots’ high degrees of freedom to reposition the gauge to different viewpoints. With this repositioning flexibility, a planning methodology becomes necessary in order to carefully plan the viewpoints, as well as the optimal sequence and quickest path to move the gauge to each viewpoint. This paper investigates coverage path planning for robotic single-sided dimensional inspection of free-form surfaces. Reviewing existing feasible state-of-the-art methodologies to solve this problem led to identifying an unexplored opportunity to improve the coverage path planning, specifically by replacing random viewpoint sampling strategy. This study reveals that a non-random targetted viewpoint sampling strategy significantly contributes to solution quality of the resulting planned coverage path. By deploying optimisation during the viewpoint sampling, an optimal set of admissible viewpoints can be obtained, which consequently significantly shortens the cycle-time for the inspection task. Results that evaluate the proposed viewpoint sampling strategy for two industrial sheet metal parts, as well as a comparison with the state-of-the-art are presented. The results show up to 23.8% reduction in cycle-time for the inspection task when using targetted viewpoints sampling.     

Receding horizon path planning for 3D exploration and surface inspection

Within this paper a new path planning algorithm for autonomous robotic exploration and inspection is presented. The proposed method plans online in a receding horizon fashion by sampling possible future configurations in a geometric random tree. The choice of the objective function enables the planning for either the exploration of unknown volume or inspection of a given surface manifold in both known and unknown volume. Application to rotorcraft Micro Aerial Vehicles is presented, although planning for other types of robotic platforms is possible, even in the absence of a boundary value solver and subject to nonholonomic constraints. Furthermore, the method allows the integration of a wide variety of sensor models. The presented analysis of computational complexity and thorough simulations-based evaluation indicate good scaling properties with respect to the scenario complexity. Feasibility and practical applicability are demonstrated in real-life experimental test cases with full on-board computation.     

Flexible telemanipulation based handy robot teaching on tape masking with complex geometry

Traditional robot teaching methods are cumbersome, tedious and difficult to scale for high-mix low-volume applications. The tape masking, a common process for surface protection before plasma spraying, spray painting and shot peening, is one of those domains where robotic automation lacks flexibility and reliability due to the complexity in task. Fortunately, it is still within the grasps of human-robot collaborative systems. This work presents a telemanipulation-based robot teaching framework that is able to let the robot manipulator cope with the taping tasks with complex workpiece geometries. The proposed framework allows quick calibration, variable motion mapping, and indexing so that the operators can easily set up and guide the robotic taping system to cover the tapes onto the layers and grooves of different workpieces. This framework enables the operators to change the motion mapping scale for both large-scale guidance and fine motion dexterous manipulation. Meanwhile, an indexing function makes it possible for the operators to re-map their poses from the edges of their comfortable regions. A portable VR system is applied in the telemanipulation system. With its six DoF motion precisely measured in real-time, the proposed motion remapping algorithms enable the operators to directly guide the robot in their selected scales. Experimental results show that the proposed framework facilitates robot programming on the manipulation of the complex workpieces that have multi-layer surfaces and grooves in between. It also reduces the teaching time comparing to other methods. This system and method improve teaching efficiency and convenience, which has potential value to be deployed in manufacturing.     

Coordinated path tracking of two vision-guided tractors for heavy-duty robotic vehicles

Heavy-duty robotic vehicles are increasingly required to transport and position large-quantity and large-scale objects in the manufacturing process. The load-carrying capacity of vehicles can be enhanced by configuring multiple automated guided tractors and coordinating their motions. A vision-guided tractor is developed by using an on-board camera in order to improve the guidance accuracy. Each tractor can recognize the guide paths, measure its path deviations and control the speeds of driving motors independently. A coordinated path tracking technique is proposed for two vision-guided tractors of a robotic vehicle, in order to make them move along a guide path accurately and smoothly. The finite area of the vision field, the actuation capacity of driving motors and the motion conflict of two tractors are considered as control constraints of path tracking. Six path deviation states and their relevant approaching trajectories are classified based on deviation properties and control constraints. The general law of mutual conversion of six approaching trajectories is analyzed. Other approaching trajectories should be converted into the tangent-arc trajectory that can eliminate two path deviations synchronously. Expected tracking distance is a coupled parameter that influences control efficiency, safety margin of trajectory conversion and coordination degree of two tractors. A fuzzy logic regulator is used in the leader-follower control strategy to adjust this parameter, by taking two path deviations and the difference of attitude angles of two tractors into account. Numerical simulation and prototype experiment show that two vision-guided tractors can move along the straight and curvilinear guide paths with high tracking accuracy, control efficiency and motion coordination, which enhanced the load-carrying capacity of robotic vehicles significantly.     

A cyber-physical robotic mobile fulfillment system in smart manufacturing: The simulation aspect

Incorporating mobile robots into the production shop-floor helps realize the concept of smart production, and it is considered one of the approaches to enhance manufacturing and operational efficiency and effectiveness by academics and industrial practitioners. This paper develops a cyber-physical robotic mobile fulfillment system (CPRMFS) for tool storage in smart manufacturing. The purpose is to enable Just-in-Time material transfer on the production shop-floor during manufacturing. A decentralized multi-robot path planning adopts graph neural networks (GNN) in the new proposed CPRMFS. We compare multiple classification algorithms for the mobile robots' action prediction, including proposing a spatial-temporal graph convolutional network (ST-GNN) under these circumstances. We also extend the research with the enhanced conflict-based search path planning algorithm. Compared with the existing literature, ST-GNN, under the enhanced conflict-based search, could obtain higher accuracy with an average value of 90% under different scenarios. The practical applicability of the proposed system with the further consideration of ST-GNN is further explained as a reference for manufacturing practitioners who looked out on a confrontation of introducing the mobile robot solutions in their manufacturing site with the goal of enhancing the operation processes.     

数控加工中路径规划与速度插补综述

数控技术在现代制造工业中被广泛使用,相关研究一直为学界和业界共同关注。数控技术的传统流程主要包含刀具路径规划和进给速度插补。为实现高速高精加工,人们通常将路径规划与速度插补中的若干问题转换成数理优化模型,针对工程应用问题的复杂性,采用分步迭代优化的思路进行求解,但所得的结果往往只是局部最优解。其次,路径规划与速度插补都是为了加工一个工件曲面,分两步进行处理虽然简化了计算,但也导致不能进行整体优化。因此,为了更好地开展路径规划与速度插补一体化设计与全局最优求解的研究,系统性地了解并学习已有的代表性工作是十分有必要的。所以将逐次介绍数控加工中刀具路径规划与速度插补的相关方法与技术进展,包括基于端铣的加工路径规划;刀轴方向优化;G代码加工以及拐角过渡;参数曲线路径的进给速度规划等国内外相关研究以及最新提出的一些新型加工优化方法。     

Technical investment planning of flexible manufacturing systems—The application of practice-oriented methods

Flexible manufacturing systems (FMS) exhibit a high degree of automation of the machining system and of the workpiece, and for the information flow systems. Therefore, these systems are amongst the most complex production installations and their technical investment planning must be undertaken with great care.This paper introduces a strategic planning procedure and describes auxiliary aids for the selection of the components and for structuring of the overall system. Computer programs for the selection of machine tools and for the simulation of the manufacturing process sequence are part of this procedure. The application of the methods is illustrated by means of several problem situations arising from industrial production companies; the examples show the practical usefulness of the developed auxiliary techniques. The planning accuracy possible by these methods reduces the investment risk associated with the use of these complex manufacturing systems.Also described is an integrated system for the technical investment planning of flexible manufacturing systems which comprises both existing methods and new auxiliary means for planning the machining systems and the technical/organizational overall concept.     

CATC — A Computer Aided Tolerance Control system

Computer utilization in manufacturing systems is increasing at a rapid rate. Developments thus far have been disjointed. Much work needs to be done in the area of integrating computer aided design and computer aided manufacturing (CAD/CAM). Tolerance control is an important component in the integration of CAD and CAM. Selection of design tolerances affects the build-ability of a product. The selection of manufacturing processes and sequence of processes affects process tolerance stacking. Unexamined process tolerance stacking leads to scrap and rework. A computer aided tolerance control (CATC) system is presented in this paper. This system is based on the tolerance chart technique. The CATC system is interactive and uses computer graphics for information display. The system can be used for computer aided process planning (CAPP) and for CAD/CAM integration.     

Variation management of key control characteristics in multistage machining processes considering quality-cost equilibrium

In multistage machining processes (MMPs), variations from key control characteristics (KCCs) continue to propagate and eventually accumulate to deviations in key product characteristics (KPCs). Therefore, the variation control of KCCs is significant to ensure the final product quality. In this paper, a variation management framework for KCCs in MMPs is established to address this issue. The new concept of variation management consists of process-oriented tolerancing and maintenance planning, and the optimal variation management strategy for each KCC is assigned based on its impact to the manufacturing system. The proposed framework deduces corresponding KCC variation distributions for previously unresearched locating schemes, thereby expanding the application scenarios of this method. For the quality specification constraints, geometric tolerances are integrated for the first time beside traditional dimensional tolerances, which expand the error scale of quality control. The modified Chebyshev goal programming (MCGP) approach is adopted to find the equilibrium point between quality and cost effectively. The superiority of the proposed method is verified by a case study of an automotive engine cylinder block MMP. The results show a remarkable improvement on the manufacturing system performance in terms of quality and cost.     

A framework for simulation-based engine-control unit inspection in manufacturing phase

This paper proposes a framework for electronic engine-control unit (ECU) inspection in manufacturing phase. Although various methodologies have been developed for the ECU verification at the development phase, the ECU verification in the manufacturing phase has rarely been brought into focus. ECUs in the manufacturing phase need the verification process in the unified way of the ECU software and hardware components by three major causes: 1) ECU software revision, 2) incomplete installation of software, and 3) quality variation of hardware. For the effective ECU verification in the manufacturing phase, we propose a simulation-based ECU testing methodology. The proposed framework configures virtual vehicle environment to simulate an ECU using a “virtual engine system (VES) model” that specifies the operations of every ECU function during a simulation. The proposed framework employs a reverse engineering approach to identify the operation state transition of an ECU function by reference vehicle states from vehicle experimental data. The main objective of this paper is to design a VES model-based inspection system that simulates an ECU without software modification in brief time for set-up and execution. The proposed framework has been implemented and successfully applied to a Korean automotive company.     

Adaptive genetic algorithm for advanced planning in manufacturing supply chain

A main function for supporting global objectives in a manufacturing supply chain is planning and scheduling. This is considered such an important function because it is involved in the assignment of factory resources to production tasks. In this paper, an advanced planning model that simultaneously decides process plans and schedules was proposed for the manufacturing supply chain (MSC). The model was formulated with mixed integer programming, which considered alternative resources and sequences, a sequence-dependent setup and transportation times.The objective of the model was to analyze alternative resources and sequences to determine the schedules and operation sequences that minimize makespan. A new adaptive genetic algorithm approach was developed to solve the model. Numerical experiments were carried out to demonstrate the efficiency of the developed approach. Received: June 2005 / Accepted: December 2005     

Service Platform for Robotic Disassembly Planning in Remanufacturing

Remanufacturing is being paid much attention due to environmental protection and resource re-utilization. Disassembly is an inevitable step of remanufacturing and it is always finished by the manual labor. Robotic disassembly helps to improve the automation of disassembly process, while robotic disassembly planning helps to improve the efficiency of robotic disassembly. However, the existing research on robotic disassembly planning seldom integrates the physical industrial robots and then provides convenient services for the users. In this paper, the framework of service platform for robotic disassembly planning in remanufacturing is studied. The database of the service platform is designed, and the data communication method between the software system and KUKA industrial robots is studied. After that, based on the physical facilities, this service platform is implemented using MyEclipse software. The developed service platform is convenient for the users to access the methods of robotic disassembly planning and the connected industrial robots can also execute the optimal disassembly solutions through the data communication method after the optimal disassembly solutions are obtained. Finally, case study based on an idler shaft is conducted to verify the developed service platform for robotic disassembly planning.     

A path conditioning method with trap avoidance

This work presents a sliding-mode method for robotic path conditioning. The proposal includes a trap avoidance algorithm in order to escape from trap situations, which are analogous to local minima in potential field-based approaches. The sliding-mode algorithm activates when the desired path is about to violate the robot workspace constraints, modifying it as much as necessary in order to fulfill all the constraints and reaching their limit surface at low speed. The proposed path conditioning algorithm can be used on-line, since it does not require a priori knowledge of the desired path, and improves the conventional conservative potential field-based approach in the sense that it fully exploits the robot workspace. The proposed approach can be easily added as an auxiliary supervisory loop to conventional robotic planning algorithms and its implementation is very easy in a few program lines of a microprocessor. The proposed path conditioning is compared through simulation with the conventional potential field-based approach in order to show the benefits of the method. Moreover, the effectiveness of the proposed trap avoidance algorithm is evaluated by simulation for various trap situations.     

Towards an automated robotic arc-welding-based additive manufacturing system from CAD to finished part

Arc welding has been widely explored for additive manufacturing of large metal components over the last three decades due to its lower capital cost, an unlimited build envelope, and higher deposition rates. Although significant improvements have been made, an arc welding process has yet to be incorporated in a commercially available additive manufacturing system. The next step in exploiting “true” arc-welding-based additive manufacturing is to develop the automation software required to produce CAD-to-part capability. This study focuses on developing a fully automated system using robotic gas metal arc welding to additively manufacture metal components. The system contains several modules, including bead modelling, slicing, deposition path planning, weld setting, and post-process machining. Among these modules, bead modelling provides the essential database for process control, and an innovative path planning strategy fulfils the requirements of the automated system. A user friendly interface has been developed for non-experts to operate the developed system. Finally, a thin-walled aluminium structure has been fabricated automatically using only a CAD model as the informational input to the system. This exercise demonstrates that the developed system is a significant contribution towards the ultimate goal of producing a practical and highly automated arc-welding-based additive manufacturing system for industrial application.     

带不等式路径约束最优控制问题的惩罚函数法

控制变量参数化（Control variable parameterization,CVP）方法是目前求解流程工业中最优操作问题的主流数值方法,但如果问题中包含路径约束,特别是不等式路径约束时,CVP方法则需要考虑专门的处理手段.为了克服该缺点,本文提出一种基于L1精确惩罚函数的方法,能够有效处理关于控制变量、状态变量、甚至控制变量/状态变量复杂耦合形式下的不等式路径约束.此外,为了能使用基于梯度的成熟优化算法,本文还引进了最新出现的光滑化技巧对非光滑的惩罚项进行磨光.最终得到了能高效处理不等式路径约束的改进型CVP架构,并给出相应数值算法.经典的带不等式路径约束最优控制问题上的测试结果及与国外文献报道的比较研究表明:本文所提出的改进型CVP 架构及相应算法在精度和效率上兼有良好表现.     

A multimodal teaching advisor for sensor-enhanced robotic systems in manufacturing

A multimodal teaching advisor (MTA) has been developed for sensor-enhanced robotic systems used in manufacturing. The MTA utilizes the work-site operator's know-how and robotic-systems information, including that from sensors, in a complementary manner. This system integrates information from various sources to carry out robotic tasks and presents this information through user interfaces that are easily understood by the operator. That is, the system integrates task specifications including tolerances, system constraints, sensory information, and operator- and robot-related information. The synthesized information is then presented in realtime to the operator at the work-site through a mobile multimodal interface. Experimental results show that this system can significantly improve total robotic system performance by ensuring a high-quality teaching task.