Reconfigurable manufacturing systems (RMSs), which possess the advantages of both dedicated serial lines and flexible manufacturing systems, were introduced in the mid-1990s to address the challenges initiated by globalization. The principal goal of an RMS is to enhance the responsiveness of manufacturing systems to unforeseen changes in product demand. RMSs are cost-effective because they boost productivity, and increase the lifetime of the manufacturing system. Because of the many streams in which a product may be produced on an RMS, maintaining product precision in an RMS is a challenge. But the experience with RMS in the last 20 years indicates that product quality can be definitely maintained by inserting in-line inspection stations. In this paper, we formulate the design and operational principles for RMSs, and provide a state-of-the-art review of the design and operations methodologies of RMSs according to these principles. Finally, we propose future research directions, and deliberate on how recent intelligent manufacturing technologies may advance the design and operations of RMSs.
Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems (CPS), which mark the advent of the fourth stage of industrial production (i.e., Industry 4.0). The widespread application of CPS in manufacturing environments renders manufacturing systems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.
This paper presents a survey of recent advancements and upcoming trends in motion control technologies employed in designing multi-actuator hydraulic systems for mobile machineries. Hydraulic systems have been extensively used in mobile machineries due to their superior power density and robustness. However, motion control technologies of multi-actuator hydraulic systems have faced increasing challenges due to stringent emission regulations. In this study, an overview of the evolution of existing throttling control technologies is presented, including open-center and load sensing controls. Recent advancements in energy-saving hydraulic technologies, such as individual metering, displacement, and hybrid controls, are briefly summarized. The impact of energy-saving hydraulic technologies on dynamic performance and control solutions are also discussed. Then, the advanced operation methods of multi-actuator mobile machineries are reviewed, including coordinated and haptic controls. Finally, challenges and opportunities of advanced motion control technologies are presented by providing an overall consideration of energy efficiency, controllability, cost, reliability, and other aspects.
An inverse dynamic model of a high-speed parallel robot is established based on the virtual work principle. With this dynamic model, a new evaluation method is proposed to measure the power consumption of the robot during pick-and-place tasks. The power vector is extended in this method and used to represent the collinear velocity and acceleration of the moving platform. Afterward, several dynamic performance indices, which are homogenous and possess obvious physical meanings, are proposed. These indices can evaluate the power input and output transmissibility of the robot in a workspace. The distributions of the power input and output transmissibility of the high-speed parallel robot are derived with these indices and clearly illustrated in atlases. Furtherly, a low-power-consumption workspace is selected for the robot.
Hydraulic servo system plays a significant role in industries, and usually acts as a core point in control and power transmission. Although linear theory-based control methods have been well established, advanced controller design methods for hydraulic servo system to achieve high performance is still an unending pursuit along with the development of modern industry. Essential nonlinearity is a unique feature and makes model-based nonlinear control more attractive, due to benefit from prior knowledge of the servo valve controlled hydraulic system. In this paper, a discussion for challenges in model-based nonlinear control, latest developments and brief perspectives of hydraulic servo systems are presented: Modelling uncertainty in hydraulic system is a major challenge, which includes parametric uncertainty and time-varying disturbance; some specific requirements also arise ad hoc difficulties such as nonlinear friction during low velocity tracking, severe disturbance, periodic disturbance, etc.; to handle various challenges, nonlinear solutions including parameter adaptation, nonlinear robust control, state and disturbance observation, backstepping design and so on, are proposed and integrated, theoretical analysis and lots of applications reveal their powerful capability to solve pertinent problems; and at the end, some perspectives and associated research topics (measurement noise, constraints, inner valve dynamics, input nonlinearity, etc.) in nonlinear hydraulic servo control are briefly explored and discussed.
This paper deals with the conceptual design, kinematic analysis and workspace identification of a novel four degrees-of-freedom (DOFs) high-speed spatial parallel robot for pick-and-place operations. The proposed spatial parallel robot consists of a base, four arms and a 1½ mobile platform. The mobile platform is a major innovation that avoids output singularity and offers the advantages of both single and double platforms. To investigate the characteristics of the robot’s DOFs, a line graph method based on Grassmann line geometry is adopted in mobility analysis. In addition, the inverse kinematics is derived, and the constraint conditions to identify the correct solution are also provided. On the basis of the proposed concept, the workspace of the robot is identified using a set of presupposed parameters by taking input and output transmission index as the performance evaluation criteria.
This paper reviews recent developments in digital switched hydraulics particularly the switched inertance hydraulic systems (SIHSs). The performance of SIHSs is presented in brief with a discussion of several possible configurations and control strategies. The soft switching technology and high-speed switching valve design techniques are discussed. Challenges and recommendations are given based on the current research achievements.
Intelligent machining is a current focus in advanced manufacturing technology, and is characterized by high accuracy and efficiency. A central technology of intelligent machining—the cutting process online monitoring and optimization—is urgently needed for mass production. In this research, the cutting process online monitoring and optimization in jet engine impeller machining, cranio-maxillofacial surgery, and hydraulic servo valve deburring are introduced as examples of intelligent machining. Results show that intelligent tool path optimization and cutting process online monitoring are efficient techniques for improving the efficiency, quality, and reliability of machining.
The Inconel 718 alloy is widely used in the aerospace and power industries. The machining-induced surface integrity and fatigue life of this material are important factors for consideration due to high reliability and safety requirements. In this work, the milling of Inconel 718 was conducted at different cutting speeds and feed rates. Surface integrity and fatigue life were measured directly. The effects of cutting speed and feed rate on surface integrity and their further influences on fatigue life were analyzed. Within the chosen parameter range, the cutting speed barely affected the surface roughness, whereas the feed rate increased the surface roughness through the ideal residual height. The surface hardness increased as the cutting speed and feed rate increased. Tensile residual stress was observed on the machined surface, which showed improvement with the increasing feed rate. The cutting speed was not an influencing factor on fatigue life, but the feed rate affected fatigue life through the surface roughness. The high surface roughness resulting from the high feed rate could result in a high stress concentration factor and lead to a low fatigue life.
Brittle materials have been widely employed for industrial applications due to their excellent mecha-nical, optical, physical and chemical properties. But obtaining smooth and damage-free surface on brittle materials by traditional machining methods like grinding, lapping and polishing is very costly and extremely time consuming. Ductile mode cutting is a very promising way to achieve high quality and crack-free surfaces of brittle materials. Thus the study of ductile mode cutting of brittle materials has been attracting more and more efforts. This paper provides an overview of ductile mode cutting of brittle materials including ductile nature and plasticity of brittle materials, cutting mechanism, cutting characteristics, molecular dynamic simulation, critical undeformed chip thickness, brittle-ductile transition, subsurface damage, as well as a detailed discussion of ductile mode cutting enhancement. It is believed that ductile mode cutting of brittle materials could be achieved when both crack-free and no subsurface damage are obtained simultaneously.
Machinery fault diagnosis has progressed over the past decades with the evolution of machineries in terms of complexity and scale. High-value machineries require condition monitoring and fault diagnosis to guarantee their designed functions and performance throughout their lifetime. Research on machinery Fault diagnostics has grown rapidly in recent years. This paper attempts to summarize and review the recent R&D trends in the basic research field of machinery fault diagnosis in terms of four main aspects: Fault mechanism, sensor technique and signal acquisition, signal processing, and intelligent diagnostics. The review discusses the special contributions of Chinese scholars to machinery fault diagnostics. On the basis of the review of basic theory of machinery fault diagnosis and its practical applications in engineering, the paper concludes with a brief discussion on the future trends and challenges in machinery fault diagnosis.
With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time–frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.
A novel data-driven method based on Gaussian mixture model (GMM) and distance evaluation technique (DET) is proposed to predict the remaining useful life (RUL) of rolling bearings. The data sets are clustered by GMM to divide all data sets into several health states adaptively and reasonably. The number of clusters is determined by the minimum description length principle. Thus, either the health state of the data sets or the number of the states is obtained automatically. Meanwhile, the abnormal data sets can be recognized during the clustering process and removed from the training data sets. After obtaining the health states, appropriate features are selected by DET for increasing the classification and prediction accuracy. In the prediction process, each vibration signal is decomposed into several components by empirical mode decomposition. Some common statistical parameters of the components are calculated first and then the features are clustered using GMM to divide the data sets into several health states and remove the abnormal data sets. Thereafter, appropriate statistical parameters of the generated components are selected using DET. Finally, least squares support vector machine is utilized to predict the RUL of rolling bearings. Experimental results indicate that the proposed method reliably predicts the RUL of rolling bearings.
The application of electrified railway directly promotes relevant studies on pantograph-catenary interaction. With the increase of train running speed, the operating conditions for pantograph and catenary have become increasingly complex. This paper reviews the related achievements contributed by groups and institutions around the world. This article specifically focuses on three aspects: The dynamic characteristics of the pantograph and catenary components, the systems’ dynamic properties, and the environmental influences on the pantograph-catenary interaction. In accordance with the existing studies, future research may prioritize the task of identifying the mechanism of contact force variation. This kind of study can be carried out by simplifying the pantograph-catenary interaction into a moving load problem and utilizing the theory of matching mechanical impedance. In addition, developing a computational platform that accommodates environmental interferences and multi-field coupling effects is necessary in order to further explore applications based on fundamental studies.
City clusters and metropolitan areas in China are flourishing in the midst of the deepening urbanization in the country, thereby resulting in the emergence of intercity rail transit. Intercity railways connect mainline and urban railways for an integrated regional transportation system that underpins and leads the development of city clusters and metropolitan areas. This study explores the development mode and service characteristics of intercity rail transit, as well as proposes overviews on this system and prospects of its future technology in China.