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Global competition forces the process industries to continuously optimize plant operation. One of the latest trends in efficiency and plant availability improvement is to set up fault diagnosis and maintenance systems for online industrial use. This paper presents a methodology for developing industrial fault detection and diagnosis (FDD) systems. Since model- or data-based diagnosis of all components cannot be achieved online on a large-scale basis, the focus must be narrowed down to the most likely faulty components responsible for abnormal process behavior. One of the key elements here is fault analysis. The paper describes and briefly discusses also other development phases, process decomposition and the selection of FDD methods. The paper ends with an FDD case study of a large-scale industrial board machine including a description of the fault analysis and FDD algorithms for the resulting focus areas. Finally, the testing and validation results are presented and discussed. [ABSTRACT FROM AUTHOR]

Uniform equal thickness layering is widely used in 3D printing, which cannot take into account the printing quality and printing efficiency. In this paper, a new adaptive layering algorithm based on multi-objective optimization is proposed for this problem. The algorithm comprehensively considers the surface features of the model, the slope and curvature of the contour, and establishes a multi-objective optimization model with print quality, print time, and feature constraints. And the Pareto optimal solution set of multi-objective optimization is solved by the improved non-dominated sorting genetic algorithm-II (NSGA-II), and the Pareto optimal solution that meets different printing requirements is selected by the Fuzzy-based weighted membership ranking method. Through comparative experiments, the method proposed in this paper reduces the volume error rate by 40.9% and the printing time by 33.3% compared with uniform layering, which can effectively improve the printing quality and printing efficiency. In addition, compared with the existing adaptive layering algorithms, it is also an algorithm with good comprehensive performance. [ABSTRACT FROM AUTHOR]

A novel collision detection algorithm of abrasive belt grinding blade integrated disk (blisk) based on improved octree segmentation is proposed, to improve the accuracy and efficiency of collision detection while ensuring dimensional accuracy and surface quality. The traditional collision detection algorithm model is described in detail, among them, the collision detection model of the abrasive belt is obtained by establishing its Oriented Bounding Box (OBB), and the collision detection model of the blisk is established by the octree segmentation. Then, an improved octree segmentation based on k-means clustering method can be presented by analyzing the important factors that affect the collision detection; on this basis, an algorithm of collision detection for abrasive belt grinding blisk is given. Finally, algorithm verification and experimental verification are carried out based on a blisk with certain type, respectively. Compared with the traditional collision detection algorithm, the results with algorithm verification illustrate that the accuracy and efficiency of algorithm in this paper have promoted by 45% and 18.60%, respectively; and the results with experimental verification demonstrate that the accuracy and efficiency of algorithm in this paper have improved by 45% and 18.44%, respectively. [ABSTRACT FROM AUTHOR]

Linear motion commands of multi-axis computer numerical control (CNC) machine tools need to be smoothed at the transition corners, because the velocity discontinuities at corners can result in fluctuations on machine tool motions and lead to poor surface quality. However, few studies have reported on the transition between non-line contour. The paper proposes a novel two-step local corner smoothing method for non-line contour transition, including path smoothing and feedrate scheduling. In path smoothing, a non-uniform rational B-spline (NURBS) curve is adopted to smooth the adjacent non-line contour of screw rotor section while constraining the cornering error with the set tolerance. The maximum deviation between the original trajectory and smoothed toolpath can be analytically calculated. In feedrate scheduling, a jerk-limited S-curve feedrate scheduling scheme is developed based on machine tool dynamics. Finally, in order to verify the correctness of the proposed method, a series of numerical simulations and actual machining and measurement experiments are conducted, and the simulations and experimental results have showed the good performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

The continuous short line segment processing method in CNC machining has the defect of frequent fluctuation of feedrate, which affects the quality and efficiency. For this problem, the local and global methods are common solutions. The local method is to insert transition curves at the corners to obtain a smooth toolpath, but this method does not essentially reduce the number of accelerations and decelerations, and it is difficult to insert transition curves between tiny straight sections. Although the global method can obtain smooth tool trajectories, the parametric interpolation method is not suitable for middle- and low-end CNC machine tools. The article proposes an adaptive tool path generation method with the original part contour as the research object and discretizes the NURBS curves into smooth trajectories consisting of large segments of straight lines and circular arcs. The article mimics the crawling characteristics of snakes and designs a double-headed snake algorithm based on the least squares method to implement this process. First, given the start and end points of the curve, two snakeheads search for the maximum linear and circular segments that satisfy the error constraint in the curve direction. The winner will then be selected as the candidate track segment through a competition mechanism. Finally, all trajectory segments are connected to obtain a smooth tool path. Experiments show that the toolpath data of the method in this paper are reduced by 75.56% compared with commercial CAM software when the contour error threshold is the same, and the contour error is reduced by more than one order of magnitude when the number of toolpath segments is equal. In addition, the method in this paper can obtain a smoother machining surface and more stable cutting force, thus achieving a win‒win situation of quality and efficiency. [ABSTRACT FROM AUTHOR]

In this paper, a new equidistant filling theory based on the level set function and a corresponding numerical algorithm based on the dynamic finite difference method were proposed. Firstly, a closed curve is defined as the zero-value contour of the level set function. Then, the level set equation, a partial differential equation, was built to get the level set function, and a dynamic finite difference method was proposed to solve the level set function. Secondly, three types of cross sections, simple polygon, multi-island polygon, and multi-hole polygon, were used to test the equidistant filling effect of the algorithm. The test results show that the proposed theory and algorithm in this paper solved the equidistant filling problem of these cross sections well. In addition, any complex section can be equidistant filled by the algorithm proposed. The calculation cost is significantly related to the number of the offsets, but not directly related to the section complexity. Finally, the remanufacturing of a typical crankshaft hot forging die proves that the algorithm proposed in this paper can effectively produce the remanufacturing repair path of a complex forging die. The surface of the remanufactured die is smooth, and there is no efects such as porosity and slag inclusion after machining. Compared with making a new die, the manufacturing cost can be saved more than 50%, and the efficiency of die manufacturing can be improved more than 60%. This is because the machining allowance of the die after additive manufacturing is very small, and it can be quickly repaired on site. [ABSTRACT FROM AUTHOR]

In today's design — manufacturing context, designers often modify existing 3D shapes (or design models) instead of creating a new design from scratch. This requires the ability to search an existing database of designs/3D models to identify and extract similar designs. Shape Retrieval Tools (SRTs) have been developed to provide an essential role in saving time and effort to retrieve and generate new designs. The capabilities of commercially available SRTs vary based on the form of the input design model, the search technique or algorithm used, the search/retrieval time, ease of use, and the quality of results. The focus of this paper is to study of their capabilities, performances, and differences and develop criteria to compare the effectiveness and performance of such Shape Retrieval Tools. Current search evaluation methods, such as precision and recall, are based on human interpretation of the results. This paper presents a holistic set of metrics for comparing the performance and effectiveness of SRTs, including data input options (to search), effectiveness of the search process, the associated retrieval time, overall ease of use, and additional data retrieval details. An algorithm is proposed to objectively analyze the search results based on the proposed Model Match Ratio (MMR), computed by the variance between the input and retrieved geometries. The search results are usually presented in a rank order list. A Precision Sequence Metric (PSM) is developed to evaluate the retrieved list by ranking the retrieved results based on the MMR for evaluating the quality of the search. The proposed evaluation algorithm was tested on several design models (and their subsequent retrieval results) involving three SRTs (Vizseek, Geolus, and CADENAS); the results of the comparison of the performance of these SRTs are discussed in this paper. [ABSTRACT FROM AUTHOR]

When the deviation between the actual pipelines and the ideal models cannot be neglected, the intersecting curve weld seam based on non-ideal models should be specially studied. This paper will introduce a novel method to quantify the deviation of the intersecting curve weld seam based on the non-ideal models. Weld location is a technical means for obtaining the actual position of weld seam, which may be used to obtain the location information of some key points on the intersecting curve. Combined with the information of weld location and the inherent characteristics of the intersecting curves, this paper analyzes the experimental results of actual intersecting curve welding, and all these works laid the foundation for the proposed algorithm. First of all, on the basis of previous studies, this paper introduces a kind of model for intersecting pipelines, which can cover most of the ways of coherence. Secondly, based on this model, the factors which may lead to the deviation of the theoretical intersecting curve from the actual intersecting curve are analyzed. Generally, there may be some connections or coupling between the sources of deviation. Against the above problem, the paper gives a solution to model each source of deviation and discuss the relationship among them, and then makes use of the information of weld location to quantify the main sources of deviation one by one, especially the quantification of the main pipes ovality. Finally, the correctness and flexibility of the algorithm are verified by the MATLAB simulation. [ABSTRACT FROM AUTHOR]

The potential benefits of Industry 4.0 have led to an increased interest in smart manufacturing. To facilitate the self-diagnosis and adaptive ability in smart milling system, a digital twin–driven intelligent algorithm for monitoring in-process milling parameters is proposed here. The algorithm can extract the radial width of cut, axial depth of cut, cutter runout parameters, and cutting constants in the end milling process at the same time only by using force sensor. It is an important breakthrough in this paper to converge two different force models to realize cyber-physical fusion for identifying milling parameters in the milling process. By using the convolution force model, digital twin technology can extract the approximate solution of milling parameters in the machining process in advance, so as to narrow the range of solution. Furthermore, the subsequent artificial intelligence algorithm can find the accurate solution of the current milling parameters in a short calculation time by cyber-physical fusion with the numerical force model considering cutter runout effect. Milling experiments are carried out to validate the proposed algorithm. It is shown that due to the complementary advantages of the convolution force model and numerical force model, the algorithm proposed in this paper can give consider to the identification accuracy and calculation efficiency. [ABSTRACT FROM AUTHOR]

Bridging the different parts together is considered a simple but effective strategy to reduce the number of piercing operations during laser cutting. However, fast bridging is never an easy task. In this paper, we present a near-linear bridging algorithm for the input parts with the shortest total bridge length. At first, the input part contours are discretized into a point cloud, then the point cloud is triangulated with the Delaunay standard. The shortest line segments between any two adjacent parts are found in the triangles connecting the two parts. These segments are finally extended into bridges. To solve the problem of the damages to the contour characteristics caused by the bridges, some restrictions are set on the screening of the discrete point cloud and the Delaunay triangles. This algorithm not only ensures the minimum total distance of all bridges, but also avoids the problem of generating bridge loops. Computational experiments show that the proposed bridging algorithm is much faster than that in existing commercial software. The feasibility and superiority of the algorithm are verified by actual lasering cutting experiments. [ABSTRACT FROM AUTHOR]

A multi-tolerance constraint-based registration algorithm for near-net-shape blades is proposed for problems of small machining allowance and positioning difficulties of near-net-shape blades. A global registration model based on the tolerance constraint of contour degree and a local registration model based on the constraints of position degree and torsion degree are established under multi-tolerance constraints. The registration algorithm proposed in this paper is verified using actual measurement data of a near-net-shape blade and its nominal model, and the solution process of the registration model is given. The analysis shows that the registration algorithm based on multi-tolerance constraints can effectively improve the registration accuracy of the near-net-shape blade. Registration parameters are optimized to make the out-of-tolerance value to be zero. Finally, based on the registration results, machining experiments are conducted on a near-net-shape blade. The results show that deviations of leading and trailing edge profiles are machined within the required limits. The proposed registration method is effective to improve the machining accuracy. [ABSTRACT FROM AUTHOR]

In the big data era, traditional data mining technology cannot meet the requirements of massive data processing with the background of intelligent manufacturing. Aiming at insufficient computing power and low efficiency in mining process, this paper proposes a improved K-means clustering algorithm based on the concept of distributed clustering in cloud computing environment. The improved algorithm (T.K-means) is combined with MapReduce computing framework of Hadoop platform to realize parallel computing, so as to perform processing tasks of massive data. In order to verify the practical performance of T.K-means algorithm, taking machining data of milling Ti-6Al-4V alloy as the mining object. The mapping relationship among cutting parameters, surface roughness, and material removal rate is mined, and the optimized value for cutting parameters is obtained. The results show that T.K-means algorithm can be used to mine the optimal cutting parameters, so that the best surface roughness can be obtained in milling Ti-6Al-4V titanium alloy. [ABSTRACT FROM AUTHOR]

Nowadays, most of the manufacturing industries rely on effective shop floor schedules to improve productivity and to optimize the makespan, production cost, tardiness, etc., which are usually considered in traditional scheduling problems. Recently, in response to the global initiatives for sustainability in manufacturing industries, an increasing number of shop floor schedules have taken energy consumption into account. However, few research works have considered traditional objectives, energy consumption, and other sustainability factors simultaneously in a shop floor schedule. In this paper, a many-objective optimization model for a flexible job shop scheduling problem considering makespan, total energy consumption, and three other indicators is formulated. Then, an improved electromagnetism-like mechanism algorithm is proposed to find the optimal or near-optimal solutions. Finally, a real-life case study is conducted to evaluate the proposed model and the algorithm. The results show that the many-objective model is effective for reducing energy consumption and improving sustainability in the shop floor. [ABSTRACT FROM AUTHOR]

The cutter-workpiece engagement (CWE) determination is an essential step in cutting force prediction, and it varies at each cutter location point. However, the calculation of CWE remains a challenge as a result of the complexity of freeform surface and tool movement in five-axis milling. An analytical method based on arc-surface intersection is presented in this paper. Based on the information of tool movement, feasible contact arc is obtained by splitting the cutter rotary surface into two parts. Tool swept surface of each tool path is constructed to avoid updating the in-process workpiece which is a time-consuming step in CWE extraction. And then, a torus patch approximation approach is adopted to speed up intersection calculation. All steps of the proposed method are realized by C++ program without activating any commercial software, which means this algorithm can be integrated into the cutting force model easily. Finally, experiments and application cases are carried out to illustrate the validity and effectiveness of the proposed method, and the comparison result shows that the computational efficiency has been improved about 40% in this paper. [ABSTRACT FROM AUTHOR]

A good stacking method can increase the packaging utility rate and reduce production costs. Much research has focused on 2D arrangements for rectangular, circular, or irregular shapes and regularly shaped 3D objects such as rectangular boxes. Genetic algorithms, simulated annealing, and other heuristic algorithms have been proposed. Recent research on the stacking of irregular-shaped 3D stone pieces has focused on balancing one stone piece on top of others to form one or more vertical towers, given the geometry of the stone pieces and the number of stone pieces available for the task. Stacking irregular-shaped 3D objects in a package is common in industry. However, there has been relatively little emphasis on the development of algorithms for stacking irregular-shaped 3D objects in a fixed-size container without prior knowledge of the stone geometries and the number of pieces available, with the goal of packing as many stone pieces as possible while maintaining stability. In this paper, three heuristic algorithms are proposed to solve the problem of nesting irregularly shaped stone pieces in layers within a container. All three algorithms use the following approach: (1) approximate the alignment of irregular shapes to a cluster of straight lines; (2) arrange stones one by one at the approximated angles using a step-by-step process; (3) for stability, consider the weight of the stone pieces based on pixel calculations. An automated real-time stacking system—including sensors, pneumatic suction cups, webcams, conveyor, robot, and programmable logic controller—was developed to evaluate the proposed algorithms using space utilization, stability, and cycle time as measures of performance. The developed algorithms and an existing stacking algorithm (bottom left most, or BLM) were tested using 25 sequences of 30 randomly ordered stone pieces. Results suggest that the developed algorithms effectively solve the stone piece packing problem. All three were significantly better than the BLM algorithm in terms of space utilization and stability, and there was no difference in cycle time. Algorithm 3 was better than Algorithms 1 and 2. [ABSTRACT FROM AUTHOR]

Machining contours on a large thin-walled part is a difficult task due to inevitable deformation of the actual part. The deformation of the contour can significantly influence the rigidity of the thin-walled part; thus, it is of importance to minimize the deformation of the contour compared with the design contour. This paper proposes a novel method to adaptively calculate the optimal contour on the deformed surface based on optimized parallel projection. The geometry data of free-form surface is obtained by on-machine measurement (OMM), and then, the actual surface is reconstructed using the measurement data. The reconstructed surface is matched with the design surface, and then, the design contour was projected onto the reconstructed surface to obtain the locating contour. The iterative nearest point (ICP) algorithm is used to adjust the design contour to match the locating contour. Finally, the projection direction is optimized to minimize contour deformation, and the adjusted contour is projected onto the reconstructed surface along the optimal direction to obtain the new contour. The effectiveness of this method is verified by machining and measuring experiments. [ABSTRACT FROM AUTHOR]

Assembly sequence planning is one of the most important processes in mass production. However, this process is currently impeded by the lack of feedback for the next process how to plan an excellent assembly line. In this paper, we introduce the priority graph model, develop the subassembly recognition method, and design the selection algorithm with feedback weights for assembly line design in topological sequencing. We show that the method can quickly plan a satisfactory sequence compared to heuristic algorithms. Due to the different weights from assembly line designers, satisfactory assembly sequences with different adaptability can be planned. This work has implications for co-design of assembly sequence planning and assembly line design. [ABSTRACT FROM AUTHOR]

This paper deals with the facility layout problem (FLP) in manufacturing systems, the main purpose of the paper is to solve the static facility layout problem as a quadratic assignment problem QAP using approximated approaches. We present Bio-geography Based Optimization meta-heuristic BBO and a parallel hybrid BBO with tabu search PBBO-TS algorithm to solve the facility layout problem. Parallel computing is implemented to diversify the search, to increase the performance of BBO algorithm, and to accelerate the speed of the running time. The proposed approaches were tested on QAPLIB benchmark instances and compared with some of the best performing sequential and parallel algorithms in the literature. The comparisons prove that the proposed algorithm PBBO-TS produce satisfactory results. In addition, the performance of the parallel implementation of the program is studied in terms of speedup and efficiency; the obtained results show that the parallel implemented system is scalable. [ABSTRACT FROM AUTHOR]

The high performance of aero-engines requires light-weight aero-engine blades, so hollow structures have been widely used in aero-engine blades. At present, the measurement of aero-engine blades is mainly carried out with coordinate measuring machines (CMM). This method can measure most of the aero-engine blades through direct contact. However, the complex surface, the chord width, and the large torsion of the profile of a hollow blade lead to measurement difficulties. In addition, the surface contact machining characteristics of belt grinding largely depend on the known data of the detected surface, so the CMM cannot efficiently obtain the belt grinding allowance data of a hollow blade and the application of hollow blades is limited in aviation. In this paper, a new method of obtaining belt grinding allowance data of a hollow blade based on blue light scanning was proposed according to complex surface structural characteristics of a hollow blade and surface contact characteristics of belt grinding. The point cloud information of a hollow blade was obtained through blue light there-dimensional scanning and then matched with an improved ICP algorithm considering the curvature change of the hollow blade, so as to obtain the belt grinding allowance of the hollow blade. Finally, the measurement method was verified by the belt grinding experiment with the hollow blade. The experimental results confirmed that the improved ICP algorithm was more accurate and that the measurement method could obtain the allowance data of the hollow blade. [ABSTRACT FROM AUTHOR]

Since the high-speed effects comprising centrifugal forces, gyroscopic moments, and rolling bearing thermal preload have considerable impacts on the dynamic behaviors of spindle units, it is of significance to study speed-varying characteristics of tool center point (TCP) dynamic behaviors. A semi-theoretical methodology is presented in this paper to identify the TCP speed-varying dynamic parameters, i.e., modal frequency, modal stiffness, and modal damping ratio. Cutting stability under an operational state is theoretically predicted and experimentally calibrated, in terms of axial limit stable cutting depth and chatter frequency. All the derived outcomes are subscribed into an optimization model whose objective is to minimize the deviations between predicted and calibrated cutting stability by searching the actual dynamic parameters of TCP. An integrated algorithm is designed to obtain the global optimized solutions so that the speed-varying dynamic parameters of TCP can be identified. A vertical machining center is selected as the platform to apply and validate the proposed methodology. The results indicate that speed dependent dynamic parameters of TCP can be accurately identified by adopting the proposed methodology, leading to accurate predictions of cutting stability with respect to the corresponding spindle speeds. Experimental validations presented in this paper also suggest that the identified speed-varying dynamic parameters can be used for predicting cutting stability at the adjacent speeds, where the relative errors are acceptable for engineering applications, achieving much more accurate cutting stability predictions than adopting TCP dynamic parameters under idle state. [ABSTRACT FROM AUTHOR]

The service performance and life of the aero-engine are directly affected by the blade machining accuracy. In the end milling of the flexible blade, the profile tolerance would usually be violated by the deflection errors induced by excessive static deformations under the action of milling force. In order to predict the blade deflection errors, this paper presents an iterative algorithm considering the coupling relationship between milling force and elastic deformation based on the milling finite element simulation model. Then a novel multipoint rod-shaped auxiliary support technology is proposed to suppress the blade deflection errors. Taking the influence of layout parameters on blade deflection errors into account, the layout of auxiliary support is optimized by a genetic algorithm. To verify the effectiveness of the proposed method, an auxiliary support mechanism is designed and manufactured, and the deflection errors suppression experiment is implemented. The measured results show that the prediction error of blade maximum deflection is 17.6%. Furthermore, the blade average deflection error on two measured curves reduces from 45.88 μm to 24.39 μm with the support of the designed mechanism. Thus, this auxiliary support mechanism and layout optimization method can achieve higher accuracy in blade milling. [ABSTRACT FROM AUTHOR]

The five-axis tool path generated by CAM software usually consists of a series of linear paths. The tangent direction at the corner of the adjacent line segment will suddenly change, and the curvature is also discontinuous, which will cause vibration and shock during the machining process. Thus, a global corner smoothing algorithm based on cubic NURBS interpolation is proposed to smooth the linear paths in this paper, so as to achieve G2 continuous for five-axis linear paths. The algorithm proposed does not require matrix operations to solve the control points, and it can also reduce the number of control points while satisfying the interpolation error. The algorithm is then used to generate smooth NURBS path for ceramic core burrs and blockage repair. The simulation and experiment show that the algorithm proposed can satisfy the error constraints, reduce the vibration of the motion axis, and improve the surface quality of laser cutting. [ABSTRACT FROM AUTHOR]

This paper presents a method of tool posture local collision-free area generation for 5-axis machining point clouds. Considering it is time-consuming and complicated to calculate the entire precise area, in this paper, discrete inclination angles are obtained in its available range, and the precise collision-free rotation angle ranges of each inclination angle are calculated to construct the collision-free area in 2-dimensional configuration space (C-space). In local gouging avoidance, an algorithm is presented to calculate the maximum equivalent tool radius with the local contour line of the point cloud near the cutter contact (CC) point, which defines the local gouging-free ranges of rotation angles and discrete inclination angles. In rear gouging avoidance, if the tool rotates by some specific angles, a rear gouging point will be outside the tool and the gouging is avoided. Based on the way, an algorithm is presented to calculate the gouging-free ranges for discrete inclination angles. Finally, the intersections of local and rear gouging-free rotation angle ranges define the collision-free area. This presented method applies to flat-end milling cutter and torus milling cutter, and two examples are given to illustrate the feasibility. [ABSTRACT FROM AUTHOR]

The well-behaved properties in workflow systems are very important for business processes. In this paper, a structured business process modelling approach by using free-choice Petri nets and workflow analysis techniques is proposed. This approach can be used to verify the soundness of workflow process specification for finding control-flow errors in the designs. For example, deadlock and dangling tasks in process models can be avoided by using this approach. However, for arbitrary Petri nets, the checking of sound properties is a NP-hard problem. This paper presents a structured business process modelling algorithm. This algorithm employs six well-behaved control structures, chaining rule and modified nesting rule to construct well-behaved process models. The resulting process models from this algorithm are free-choice workflow-nets, for which sound property can be decided in polynomial time. The proposed method is an extension of the workflow-net. The basic transformation rules in the workflow-net are subsets of the proposed nesting rule in this paper. The process models resulted from this structured business process modelling algorithm also have the advantages of modularity, readability and maintainability. [ABSTRACT FROM AUTHOR]

When a conflict or plan change occurs in the process of cloud service execution, if the initial scheme is not rescheduled in time, it can lead to a delivery delay and a series of nonlinear losses. The cloud service rescheduling (CSRS) problem is considered as a particularly hard combinatorial optimization problem with multi-participants, which is significantly different from traditional flow shop rescheduling problem. It is difficult to coordinate the relationship of service suppliers and construct a reward mechanism to encourage them to participate in the rescheduling. According to the various strategies of service suppliers that do or do not participate in the rescheduling, a game theory model was constructed. The main aim of this paper is to explore how to minimize the reward of suppliers and ensure that the game model develops in a desired direction. Hence, a novel hybrid approach using shuffled frog leading algorithm (SFLA) and Nash equilibrium (NE) theory was proposed to solve the CSRS problem. In addition, we carried out a case study to demonstrate that the SFLA and NE approaches can be implemented for realistically sized problem sets and that the cost savings are significant [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) program has been widely applied for damage assessment or monitoring the performances and the reliabilities of structures. Usually, structural damage is assessed by discriminating abnormal change from normal change in the structural dynamic behavior. This paper takes the SHM data from a real bridge as a study example and recognizes the trains which daily cross this bridge. The main aim of the current work is to improve the accuracy of structural damage detection. In this paper, symbolic data analysis (SDA) is introduced to extract hidden patterns from raw data, and principal component analysis (PCA) is performed to extract the most important properties of the signals and eliminate the influence of noise. A new representative is proposed in this paper and the recognition results obtained by the clustering algorithms with different representatives are compared. The results show that the new representative is robust to recognize the trains, and PCA is very useful to extract the properties of the signals as well as to reduce the influence of noise. [ABSTRACT FROM AUTHOR]

Localization plays an important role in manufacturing the curved thin-walled parts, which can determine the distribution of machining allowance and has great influence on the manufacturing accuracy. The registration algorithm is the most efficient way to locate the billet in the machining coordinate system of the machine tool by computing a transformation matrix. However, the localization of the curved thin-walled parts is complicated and challenging since the billets are individual, the shape and location of which are unknown. This paper attempts to develop an adaptive localization approach with the constraints of the profile and thickness based on on-machine measured data. The framework for constrained adaptive localization approach is illustrated, in which on-machine measurement, registration, isometric mapping and allowance optimization are involved. The details of the on-machine measurement for both the profile inspection and the thickness measurement are presented. An isometric mapping method is employed to build the separate point pairs between the measured points and the nominal shape of the part. A constrained optimization algorithm for the machining allowance is performed iteratively until meeting the constraints of the profile and thickness tolerance ranges. Finally, a case study of constrained adaptive localization was carried out, the results of which confirm the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

In the process of high-speed machining, there are sharp corners at the joint of short lines. The vibration of cutting tools at the sharp corners will be severe, which will reduce the quality of machining surface and machining efficiency. For this problem, impulse response technology is proposed and applied. However, there is inevitable time delay in impulse response technology, which leads to the uncertainty of the maximum contour error of the corner. In order to further generate accurate reference motion trajectories, an accurate interpolation and contouring control algorithm based on FIR filters for the corner transition is proposed in this paper. According to the continuous short lines information in the CNC system, the rectangular velocity pulse signal of the short line is obtained. Initial rectangular velocity pulse is filtered to obtain third-order trajectory. In order to realize the continuous feed motion of short lines, the maximum feed velocity of short lines is constrained. Under the constraint of the maximum velocity limited, the maximum contour error of the corner is controlled by changing the overlapping time, and the accurate mathematical expression of the maximum contour error is reached. By using the FIR filters, the acceleration and jerk curves are generated from velocity pulse profiles. Through the experiment and simulation analysis, the algorithm proposed in this paper can determine the maximum contour error of the corner to realize smooth transition and reduce the machining path time by 7–10%. The proposed algorithm is proposed to achieve G1 continuous acceleration and effectively improve the processing quality. [ABSTRACT FROM AUTHOR]

3D grinding temperature field can be simulated by the finite difference method. When the finite difference method is used to calculate the temperature field, the boundary conditions need to be considered. Unfortunately, the difference equations for internal nodes and boundary nodes are not the same. For cuboid computing domains, there are twenty-six types of boundary nodes. This reduces the calculation efficiency to a certain extent. An improved finite difference method for the 3D grinding temperature field was proposed to solve this problem in this paper. By adding auxiliary nodes, the boundary nodes are converted into internal nodes, and the difference equations of the boundary nodes and internal nodes are unified. In this paper, the improved algorithm was used to simulate the 3D grinding temperature field. The temperature distribution characteristics of the grinding temperature field were analyzed. Then, the effects of heat source type, space step size, and convective heat transfer coefficient on the temperature field were studied. The results show that the improved algorithm can well simulate the 3D grinding temperature field. Finally, compared with the original algorithm, the calculation results were completely consistent, and the efficiency is improved by about 20%. [ABSTRACT FROM AUTHOR]

The internal crack defect is prone to appear in the inner part of casting products during the production process due to the influence of casting craft and on-site environment. In order to ensure the internal quality of the casting products, nondestructive examination and defect detection technology should be used to detect the internal crack of the casting product. The existing defect detection technologies have some problems such as poor generalization and low accuracy. Therefore, an internal crack defect detection method based on the Relief algorithm and Adaboost-SVM is proposed in this paper. Firstly, casting image is preprocessed by grayscale transformation, bilateral filtering, and adaptive image segmentation. Secondly, HOG feature, invariant moment feature, and LBP feature are extracted, and sensitive feature set is selected by Relief algorithm. Finally, the Adaboost-SVM is used to construct the internal crack detection model to realize the crack detection with high generalization and accuracy. The effectiveness of the method is verified by the casting image dataset collected in the actual industrial field. The experimental result reveals that the proposed method could not only extract sensitive feature set but also has better classification performance and generalization ability than other common classifiers. [ABSTRACT FROM AUTHOR]

Green and sustainable manufacturing is an inevitable development trend of manufacturing in the future, wherein low-energy consumption is regarded as a significant component. As an emerging manufacturing service system, cloud manufacturing (CMfg) is characterized by wide distribution, large quantity and complicated calling method for manufacturing services. Therefore, the energy consumption in the execution of composition service should be considered. However, few works related to energy consumption are focused on service composition at present. In response, this paper proposes an energy-aware service composition and optimal selection (EA-SCOS) model to ensure high-quality and low-energy consumption during the tasks. The mathematical model of energy consumption based on quality of service (QoS) is established, wherein the evaluation methods for manufacturing energy consumption and logistics energy consumption are described in detail. In order to solve the EA-SCOS problem effectively, a state-of-the-art algorithm which has been successfully applied in other fields, named grey wolf optimizer (GWO), is introduced. In addition, two key improvements for GWO are proposed to ensure the accuracy of solution. Finally, the effectiveness and feasibility of improved GWO (IGWO) are verified by a comparative study with GWO, genetic algorithm (GA) and max–min ant system (MMAS). Simulation results show that the proposed model is valid for reducing service energy consumption. Moreover, the improved strategies have obvious, positive effect on the accuracy of solutions and the performance of IGWO for addressing EA-SCOS problem is obviously better than the other three algorithms. [ABSTRACT FROM AUTHOR]

Measurement path planning plays an essential role in on-machine measurement, which is often required to be time-saving and collision-free. This paper proposes a novel path planning methodology and develops an automatic collision avoidance strategy for measurement. Measurement points are generated by contour section sampling, grid mesh sampling, and locally dense sampling from the free-form surface based on the usage. Afterwards, a shortest-path algorithm and a non-interference path algorithm are developed to solve the sequence planning results. In order to simplify the calculation expense of collision-free paths, the safe-plane-based method (SPM) is introduced. Moreover, the optimized SPM is proposed to minimize the whole measurement path of SPM. The simulations show that the proposed methods can reduce the total measurement distance to nearly 15% than the zigzag method and the safe-plane-based method. [ABSTRACT FROM AUTHOR]

A new management algorithm to improve performance and reliability of an off-battery autonomous energy system consisting of DFIG based wind energy converter (WEC) and diesel generator (DG) is proposed in this paper. Among its several constraints, the most significant ones are the limitation of wind power penetration and rotor side converter safety due to both the load demand variation and wind speed fluctuation. The proposed algorithm consists in maximizing load connection to the DFIG-based WECS and limiting the use of DG to only priority load taking into account some criteria to respect. A decision is made up with reference to specific rules on the basis of the measured wind speed and the predicted load demand. A stator flux-oriented technique for rotor side converter is presented to regulate voltage and frequency at stator/load terminals. Different possible case studies are presented to show the effectiveness of the proposed algorithm. Simulation results obtained from a 250 KW DFIG based wind power system are given and discussed in this paper. [ABSTRACT FROM AUTHOR]

The smooth motion profile with less oscillation ensures the processing quality of machined parts. Meanwhile, keeping feedrate under its limit as high as possible can reduce the processing time and save cost. In this paper, a novel feedrate scheduling algorithm with acceleration lookahead is presented. Through the sin2 acceleration profile, the continuity of jerk can be guaranteed. Based on the 4-phase profile, the look-ahead function is also extended for acceleration, which avoids the frequent changing of acceleration when scheduling short segments. On a designed benchmark, the effectiveness of the proposed algorithm is verified and compared with the state-of-the-art. The algorithm is implemented on a laser patterning machine with the galvanometric scanners as its feed drive system. The results confirm the effectiveness of the presented scheduling method. [ABSTRACT FROM AUTHOR]

In this paper, a multiproduct multiperiod capacitated production system that has been organized as a flow shop is considered. The main novelty of the paper is proposing a more efficient mathematical model for the problem of integrating lot sizing and scheduling with sequence-dependent setups. In comparison to the former model, because of fewer continuous and binary decision variables and constraints in the proposed model, this model is very easier to solve. Comparison between two models proves the superiority of the proposed model. Two mixed integer programming-based approaches with rolling horizon framework have been used to solve this model. To evaluate the performance of the proposed model and solution method, problems of different scales have been studied. The used algorithms search the solution space for both lot-sizing and scheduling problems and find a combination of production planning and scheduling that is feasible and close to optimum. [ABSTRACT FROM AUTHOR]

This paper proposes and evaluates a near admissible heuristic search strategy and its application to a kind of flexible manufacturing system (FMS) scheduling in a Petri net framework. Petri nets can concisely model the strict precedence constraint, multiple kinds of resources, and concurrent activities. To cope with the complexities for scheduling of FMS with alternative routings, this paper proposes an admissible heuristic function based on the execution of P-timed Petri nets and presents an improved dynamic weighting A* strategy using the proposed heuristic function. The search scheme does not need to predict the depth of solution in advance and the quality of the search result is also controllable. Some numerical experiments are carried out to demonstrate usefulness of the algorithm. [ABSTRACT FROM AUTHOR]

Partner selection is a key issue in the development of an effective coalition formation mechanism for virtual enterprises (VE). Combinatorial reverse auction can be applied by a firm to select the best partners to minimize the cost in forming VE. The objectives of this paper are to propose architecture for selecting partners based on combinatorial reverse auction mechanism to minimize the cost of VE, develop algorithms to find a near-optimal solution efficiently, and implement a prototype system based on the proposed algorithms. We formulate the partner selection problem based on combinatorial reverse auctions and apply Lagrangian relaxation technique to solve the problem. Our partner selection solution algorithms include an algorithm for solving bidders' subproblems by exploiting their problem structures, a subgradient algorithm for solving the dual problem, and a heuristic algorithm for finding a near-optimal solution. In addition to theoretical development, we also implement a prototype system based on the proposed algorithms and web services technologies to verify the effectiveness of our methodology. [ABSTRACT FROM AUTHOR]

This paper discusses characteristics unique in the two-phase high-frequency-testing (HFT) environment in semiconductor manufacturing. We believe this paper is the first to define, formalize, and analyze the decision making problem associated with the two-phase HFT. Specifically, this paper defines the problem of minimizing the total HFT capacity usage by systematically finding the optimal number of preliminary HFT bin-1 chips subject to the main HFT, with the existence of the target service rate. We also propose a heuristic algorithm that exploits the special structure of the problem for efficiently obtaining a near-optimal solution. Finally, a numerical analysis and a case study have been conducted to gain more insights on the problem structure and the proposed algorithm. [ABSTRACT FROM AUTHOR]

Despite the potential benefits of additive manufacturing over traditional subtractive manufacturing, there are still several intrinsic problems that affect the accuracy and quality of the additive manufactured parts adversely, one of which is the undercut, i.e., the additive manufactured part cannot enclose the corresponding designed model fully, according to existing slicing methods. Therefore, the accuracy of the post-processed parts cannot be guaranteed as post processing is generally a process of subtractive manufacturing. In this paper, we propose a slicing algorithm to generate a new kind of layer contours. In this algorithm, not only the input model is intersected with a group of parallel slicing planes to get the layer contours but also the local geometry between two adjacent slicing planes of a layer is integrated into the final layer contours to prevent the undercut. Consequently, a non-negative error is guaranteed on the whole surface of the manufactured part in theory in order to ensure the final accuracy of the post-processed part. Several slicing results are given to demonstrate the validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper was motivated by the requirement of remote coordination for flexible manufacturing systems (FMS), in which certain requested commands may lead to undesired states. For such discrete event systems (DES), this paper applies a command filtering scheme for modeling and synthesis of filters using Petri nets so as to guarantee that the closed coordinated manufacturing system satisfies the requirements. Moreover, a systematic algorithm for the design and integration of modular command filters is proposed in order to cope with the complexity and realization issues in large-scale FMS. To show the practicability of the developed method, an application to an FMS with three product types is provided. The proposed approach contributes a promising tool for preventing undesirable actions from occurring in FMS which may be also applied to other types of DES if appropriately modified. [ABSTRACT FROM AUTHOR]

Queuing networks present as beneficial models for a category of problems emerging in modern manufacturing systems. As the optimal control problem for queuing networks in familiar to be difficult, an important topic of research during the last two decades has been the growth of difficult estimations, and the use of these estimations to control optimal controls. Flexible moderations are an important class of such estimations that have received much consideration in recent years. The central objective of this paper is to determine the utilization of flexible moderations in solving a diversity of scheduling problems. In this paper, we investigate the role of flexible moderations in solving classic job shop problems. For the job shop problem with the objective of minimizing makespan, we build a schedule that is guaranteed to be within a consistent of the optimal. In other words, we examine the job shop scheduling problem with the aim of minimizing holding costs. Recent results show that for this objective, the job shop problem does not have a polynomial time estimation plan; consequently, in terms of approximability, this is a harder objective than the makespan. Our main result is an algorithm, based on regular relaxation that presents lateral optimal schedules. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to introduce an algorithm which considers not only time factor but also cost, risk, and quality criteria to determine the critical path under fuzzy environment. In this algorithm first, decision makers allocate time, cost, risk, and quality to each activity. We are lacking in data and information, so in the proposed algorithm, the ratings of each activity and the weight of each criterion are described by fuzzy numbers and linguistic variables, which can be expressed in triangular fuzzy number. Linguistic variables are applied to represent the intensity of preferences of one criterion over another. Then, we add up triangular fuzzy numbers to determine the final evaluation value of each criterion for paths. Next, we use fuzzy TOPSIS, a technique for order preferences by similarity to an ideal solution, a method proposed by the authors in another paper, to choose the best alternative. Finally, numerical example is solved to illustrate the procedure of proposed method at the end of this paper. [ABSTRACT FROM AUTHOR]

Machine-part cell formation is used in cellular manufacturing in order to process large varieties, improve quality, and lower work-in-process levels, reducing manufacturing lead time and customer response time while retaining flexibility for new products. This paper presents a new and novel approach for obtaining machine cells and part families. In cellular manufacturing, the fundamental problem is the formation of part families and machine cells. The present paper deals with the self-organizing map (SOM) method, an unsupervised learning algorithm in artificial intelligence which has been used as a visually decipherable clustering tool of machine-part cell formation. The objective of the paper is to cluster the binary machine-part matrix through visually decipherable cluster of SOM color coding and labeling via the SOM map nodes in such a way that the part families are processed in that machine cell. The U-matrix, component plane, principal component projection, scatter plot, and histogram of SOM have been reported in the present work for the successful visualization of the machine-part cell formation. Computational result with the proposed algorithm on a set of group technology problems available in the literature is also presented. The proposed SOM approach produced solutions with a grouping efficacy that is at least as good as any results earlier reported in the literature and improved the grouping efficacy for 70% of the problems and was found to be immensely useful to both industry practitioners and researchers. [ABSTRACT FROM AUTHOR]

The objective of this paper is to develop a methodology to calculate the size of a cylindrical profile accurately per American National Standards Institute (ANSI) standards. The ANSI Y14.5.1M–1994 standard defines the size of a cylinder as the size of the largest ball rolling on a spine such that all points on the surface of the cylinder are external to it or the size of the smallest ball rolling on a spine such that all points on the surface of the cylinder are internal to it. Current methods of size evaluation reduce the complexity of the spine and model it as a straight line. In this paper, a methodology is presented to evaluate the control points of the spine modeled as an open uniform B-spline curve of a prespecified degree based on points collected on the surface of the cylinder. This provides a quantitative measure of the size of the cylinder in accordance with ANSI standards. The formulations to evaluate the maximum inscribing spine and the minimum circumscribing spine are presented as multilevel optimization problems. The outer level optimization is used to identify the optimal set of control points for the spline representing the path of the rolling ball. The inner level optimization is used to find the nearest point on the spline corresponding to every point in the dataset. The optimization formulation presented in this paper has been used to calculate the true size of cylinders for several published, simulated, and real datasets. These results are then compared to traditional estimates for size of a cylinder. The results indicate that the method presented for calculating the size of a cylinder conforms better to the ANSI standards as compared to other methods, such as the maximum inscribed, minimum circumscribed, and least squares cylinders, which have been traditionally used as indicators of size of a cylinder []. Further analysis is presented to observe the effect of sample size on the results of the algorithm. It is observed that with an increase in the sample size, the difference between the results of the presented algorithm and the traditional methods increases with the presented method providing more accurate estimates. [ABSTRACT FROM AUTHOR]

In recent years, several papers on machining processes have focused on the use of artificial neural networks for modeling surface roughness. Even in such a specific niche of engineering literature, the papers differ considerably in terms of how they define network architectures and validate results, as well as in their training algorithms, error measures, and the like. Furthermore, a perusal of the individual papers leaves a researcher without a clear, sweeping view of what the field’s cutting edge is. Hence, this work reviews a number of these papers, providing a summary and analysis of the findings. Based on recommendations made by scholars of neurocomputing and statistics, the review includes a set of comparison criteria as well as assesses how the research findings were validated. This work also identifies trends in the literature and highlights their main differences. Ultimately, this work points to underexplored issues for future research and shows ways to improve how the results are validated. [ABSTRACT FROM AUTHOR]

This paper presents a new method based on evolutionary algorithms—Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE)—for the sensitivity-based conceptual design and the tolerance allocation for mechanical assemblies. The approach I of this paper moves the nominal values of non-critical dimensions to a less sensitive portion, and the approach II deals with the allocation of cost-based optimal tolerances. An improved optimization model that considers three objective functions (minimization of the deviation of critical dimensions, manufacturing cost, and the quality loss), eight constraints, and six variables is proposed. To show the effectiveness of the proposed methods, the stepped bar assembly is considered as a numerical example. The results obtained from NSGA-II and DE are compared and analyzed. The results show that the proposed methods are much effective, cost, and time saving than the ones considered in literature. [ABSTRACT FROM AUTHOR]

Control charts are widely implemented in firms to establish and maintain statistical control of a process which leads to the improved quality and productivity. Therefore, designs of control charts have gained particular attention from the outset. Design of control charts requires that the engineer selects a sample size, a sampling frequency, and the control limits for the chart. In this paper, a possible combination of design parameters is considered as a decision-making unit which is identified by three attributes: hourly expected cost, detection power of the chart, and in-control average run length. Subsequently, optimal design of control charts is formulated as a multiple-objective decision-making problem. Moreover, the cost function is extended from single to multiple assignable causes because there exist multiple assignable causes in real practice. An algorithm using data envelopment analysis is applied to solve the multiple-objective decision-making (MODM) model. Some numerical and experimental analyses are provided to illustrate the algorithm procedure. Sensitivity analysis is carried out to investigate the robustness of the model, and comparisons with other related published papers are made. It is shown that the proposed MODM model can overcome some drawbacks attached to the previous models and approaches. [ABSTRACT FROM AUTHOR]

The objective of this paper is to propose and evaluate heuristic search algorithms for a two-machine flowshop problem with multiple jobs requiring lot streaming that minimizes makespan. A job here implies many identical items. Lot streaming creates sublots to move the completed portion of a production lot to second machine. The three heuristic search algorithms evaluated in this paper are Baker’s approach (Baker), genetic algorithm (GA) and simulated annealing (SA) algorithm. To create neighborhoods for SA, three perturbation schemes, viz., pair-wise exchange, insertion and random insertion are used, and the performance of these on the final schedule is also compared. A wide variety of data sets is randomly generated for comparative evaluation. The parameters for GA and SA are obtained after conducting sensitivity analysis. The genetic algorithm is found to perform well for lot streaming in the two-machine flowshop scheduling. [ABSTRACT FROM AUTHOR]

Vision-based control systems play an important role in modern robotics systems. An important task in implementing such a system is developing an effective algorithm for recognizing human actions and the working environment and the design of intuitive gesture commands. This paper proposes an action recognition algorithm for robotics and manufacturing automation. The key contributions are (1) fusion of multimodal information obtained by depth sensors and cameras of the visible range, (2) modified Gabor-based and 3-D binary-based descriptor using micro-block difference, (3) efficient skeleton-based descriptor, and (4) recognition algorithm using the combined descriptor. The proposed binary micro-block difference representation of 3-D patches from video with a complex background in several scales and orientations leads to an informative description of the scene action. The experimental results showed the effectiveness of the proposed algorithm on datasets. [ABSTRACT FROM AUTHOR]

Micro end milling has an outstanding capability in machining micro-scale structures of various materials. Prediction of cutting forces is significant on controlling quality and safety of machining process. This paper proposes a mechanic model to predict cutting forces in micro end milling process, which includes a novel algorithm of instant uncut chip thickness. This algorithm takes into account the geometric errors of machining system and trochoidal trajectory of cutting edge, which redefines cutting radii with consideration of the tool runout. A feasible technique to reduce the influence of tool runout is put forward by analyzing the redefined cutting radii. Since the existing method for cutting force coefficient identification is generally conducted using finite element simulation, it is difficult for some composite materials due to lack of the material properties. To overcome the above shortcomings, an experimental-based cutting force coefficient identification technique has been developed by groove milling. A number of experimental testing have been conducted to validate the developed cutting force model. Experimental results are in good agreement with theoretical predictions, which demonstrates the validity of proposed cutting force modeling. [ABSTRACT FROM AUTHOR]