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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]

This paper presents a research that investigates solutions and algorithms for determining the optimum machine layout served by autonomous material handling system, like mobile robot or automated guided vehicle. Unlike previous works which solved the layout problem by optimizing the distance between facilities, in this paper the machine layout is addressed based on optimizing the travel time of the material handling system. The proposed approach can include boundary kinematic constraints of vehicle while optimizing the objective function such as velocity, acceleration, orientation, and trajectory curvature. The nonlinear constrained model is transformed to unconstrained problem using penalty method. Then, a simulated annealing-based algorithm is used to search for the optimum locations of machines among all possible feasible layouts. The simulation results showed that the proposed approach was efficient enough to use in real factories due to including a vehicle path planner integrated in an overall layout design scheme that involves searching of vehicle control parameters. [ABSTRACT FROM AUTHOR]

With the development of casting process and its numerical simulation technique, many demands of realism and clearness in post-processing have arisen. This paper introduces the implicit surface to post-processing for the results of casting simulation so as to meet these demands. In this paper, a robust and fully automatic algorithm is proposed for extracting the implicit surface in the signed distance function calculated from the import stereolithography files. Then several applications of implicit surface in the post-processing of casting simulation are listed in two categories. The applications in the first category include fast rendering of massive data, section view in arbitrary direction, visualization of residual liquid, and casting deformation, giving clear and pretty visualization of the results in simulation, and making it possible for engineers and process designers to look through the opaque mold, gain insights to casting process, and locate possible defects. The applications in the second category involve thickness distribution and modulus calculation, which offer important characteristics of castings and facilitate the optimization of casting processes. [ABSTRACT FROM AUTHOR]

The understanding and prediction of the generated surface topography are very important in milling process. This paper presents a surface topography model and an on-line simulation method of surface topography considering tool wear in a multi-axis milling process. First, the cutting edge equation is established by dividing the cutting edge into a series of cutting edge elements considering tool wear influence and tilt angle of tool axis on each discrete cutting edge element, and an algorithm is proposed to determine the range of divided position angle. Then, the sculptured surface workpiece is divided into a series of elements along the feed direction with the same or less than discrete precision of cutting edge. The intersection points between the discrete cutting edge elements and the planes of both sides of each divided element on workpiece can be obtained based on the established cutting edge equation in the cutting process. The left cutting trajectory points on workpiece are got by reserving the points with the minimum coordinate value in the Z-axis direction under the same coordinate value in the X-axis and Y-axis direction among the intersection points and points on workpiece. Thus, surface topography model can be constructed based on the established cutting edge equation, the determined range of position angle, discrete cutting edge elements, and divided element on workpiece surface. Finally, an on-line simulation algorithm is proposed to simulate the generation process of surface topography in multi-axis milling operation. Experimental work and validation of the established model are performed on a five-axis milling center by using stainless steel 0Cr17Ni12Mo2 and cemented carbides milling cutter. The results about the topography generation of the constructed B-spline surface show that the predictions of the established surface topography model correlate well with the experimental results. [ABSTRACT FROM AUTHOR]

The multi-point tool positioning algorithms produce much larger machining strip width than the single-point algorithms and apparently reduce the actual machining time. This paper presents a tool positioning algorithm for multi-point machining of sculptured surface, which is excellent at dealing with both of concave and convex surfaces. The proposed method is based on the middle-point error control (MPEC) method, which means the connection point between cutter and surface corresponds to the middle point of error distribution curve. Usually, only one cut contact (CC) point can be obtained with this method. Thus, the proposed method improved the MPEC method for achieving two CC points. At first, the shape of error distribution curve is investigated, and its asymmetry is evaluated. Secondly, the error distribution curve becomes symmetrical after the cutter is rotated with a roll angle, and the cutter is separated with surface at the same time. Finally, the minimum tilt angle is found, and two CC points are obtained without gouging. Machining experiment is conducted to verify the proposed method, and the result reveals that the machining strip width is increased apparently and the tool position is almost unchanged after the adjustment with proposed method. Simulation, measurement, and analysis are also given in the part of the experiment. [ABSTRACT FROM AUTHOR]

In this paper, the berth allocation problem with stochastic vessel handling times is formulated as a bi-objective problem. To solve the resulting problem, an evolutionary algorithm-based heuristic and a simulation-based Pareto front pruning algorithm is proposed. Computational examples show that the proposed approach provides solutions superior to the ones where the expected value of the vessel handling times is used. [ABSTRACT FROM AUTHOR]

Due to the continuous growth in the application of networks in manufacturing, quality of service (QoS) has become an important issue. In this paper, the concept of QoS for manufacturing networks is discussed. To provide overall performance assurance for manufacturing networks, a service framework integrating the QoS mechanisms of the networked resource service management function and the communication networks is proposed. The novel framework maps an application to resource services and then to communication networks, adopts an intelligent optimisation algorithm for QoS management of resource services, and provides QoS schemes for data transfer across communication networks. A prototype implementation has been realised and a set of simulation experiments conducted to evaluate the validity of the framework. The results obtained demonstrate the ability of the framework to satisfy the various performance requirements posed by such applications and provide efficient overall performance assurance for manufacturing networks. [ABSTRACT FROM AUTHOR]

A mixed-model assembly line is a type of production line where different models of a product are assembled on. Mixed-model assembly lines can respond to unanticipated changes in product demands quickly without keeping so many inventories. Designing mixed-model assembly line involves solving the traditional problems of the assembly line design (consists of balancing problem, determining cycle time, and the number and sequence of stations) in addition of determining the sequence of products in assembly line. The main goal of this paper is presenting a method in order to determine the sequence of products in mixed-model assembly line by considering Just-in-Time systems. Moreover, supplying some required components from feeding lines is considered. A mathematical model is presented which is capable of specifying the sequence of products in the mixed-model assembly line by considering main criteria and keeping feeding lines balanced. Mathematical model can be used for solving small-size problems. Because the combinatorial nature of sequencing problems typically provides an intractable search space for problems of 'real world' size, the search heuristics of simulated annealing and ant colony algorithms are presented and used to find solutions for several problem sets. Experimentations show that the simulated annealing approach outperforms the ant colony approach in objective function performance. [ABSTRACT FROM AUTHOR]

This research addresses the m-machine no-wait flowshop scheduling problem with the objective of minimizing the number of tardy jobs. The problem is known to be NP-hard even for the two machines, and literature reveals that no heuristics have been developed for this problem. In this paper, we propose an efficient heuristic based on simulated annealing, where we first adapt the single-machine optimal algorithm to our problem to develop two new heuristics, NOTA and NOTM. An improved simulated annealing heuristic, called SA-GI, is then developed by feeding the best performing heuristic among NOTA, NOTM, and EDD into the simulated annealing algorithm. A second proposed heuristic, called SA-IP, further improves the SA-GI solution by using insertion and pair-wise exchange techniques. Based on the computational experiments, the overall relative percentage errors of the heuristic SA, SA-GI, and SA-IP are 8.848, 8.428, and 0.207, respectively. The computational times of the three heuristics are close to each other, and the largest average time is less than one second, and hence, the computational time is not an issue. Therefore, the heuristic SA-IP is the best one. [ABSTRACT FROM AUTHOR]

A new method for real-time prediction of uncertain network transmission time delays and a method for closed-loop control of manufacturing and industrial plants through networks are introduced. The proposed delay prediction method is based on the multilayer perceptron neural model. In order to minimize the number of neurons in the first layer of the network and hence reducing the computational burden in a real-time implementation, a method for determination of the Markov order of the time delay sequence is presented. Using the predicted delay, and a zero-order hold equivalent discrete-time model of the plant, a time varying state feedback control algorithm with a real-time gain updating strategy is proposed. A sufficient condition for closed-loop stability is also derived using the switching theorem for linear systems. The proposed method is shown, through two industrial networked case studies, namely, a DC motor driving a transportation roller for paper sheets and a milling machine. Simulation studies depict the efficacy of the proposed method in controlling such challenging problems. [ABSTRACT FROM AUTHOR]

Virtual enterprise is a temporary network of independent companies or enterprises that can quickly bring together to fulfill a value-added task. With the development of Web service technologies, the enterprise business systems can be encapsulated as Web services. Establishing a virtual enterprise is actually a process of Web services composition. As more and more Web services are available, many Web services with different quality of service (QoS) can be found for tasks of the composite Web service. Thus, a significant research problem in Web service composition is how to select the correct Web services for tasks such that the composite Web service gives the best overall quality. In this paper, we propose an approach to achieve Web services selection efficiently with excellent comprehensive quality. Firstly, a comprehensive evaluation model based on generic QoS (GQoS) and domain QoS (DQoS) of composite Web service is established. Secondly, a novel optimization algorithm named culture max-min ant system (C-MMAS) is constructed to solve the problem of Web service selection based on DGQoS. Simulations show that when used in Web service selection, C-MMAS is better than ant colony optimization algorithm and MMAS in efficiency. [ABSTRACT FROM AUTHOR]

This paper presents an optimized path generation algorithm for direction parallel milling, which is commonly used in the roughing and finishing stages. First, a geometrically efficient tool path generation algorithm using an intersection points graph is introduced. Second, the generated tool path is modified as an optimized tool path that maintains a constant material removal rate to achieve a constant cutting force and avoid chatter vibration, and the results are verified. Additional tool path segments are appended to the basic tool path through a pixel-based simulation technique. The algorithm is implemented for two-dimensional contiguous end milling operations with flat end mills, and cutting tests are conducted by measuring the spindle current, which reflects the changing machining situations, to verify the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Abrasive waterjet machining (AWJM) is a non-conventional process. The mechanism of material removing in AWJM for ductile materials and existing erosion models are reviewed in this paper. To overcome the difficulties of fluid–solid interaction and extra-large deformation problem using finite element method (FEM), the SPH-coupled FEM modeling for abrasive waterjet machining simulation is presented, in which the abrasive waterjet is modeled by SPH particles and the target material is modeled by FE. The two parts interact through contact algorithm. The creativity of this model is multi-materials SPH particles, which contain abrasive and water and mix together uniformly. To build the model, a randomized algorithm is proposed. The material model for the abrasive is first presented. Utilizing this model, abrasive waterjet penetrating the target materials with high velocity is simulated and the mechanism of erosion is depicted. The relationship between the depth of penetration and jet parameters, including water pressure and traverse speed, etc., are analyzed based on the simulation. The results agree with the experimental data well. It will be a benefit to understand the abrasive waterjet cutting mechanism and optimize the operating parameters. [ABSTRACT FROM AUTHOR]

Injection molding process parameters such as injection temperature, mold temperature, and injection time have direct influence on the quality and cost of products. However, the optimization of these parameters is a complex and difficult task. In this paper, a novel surrogate-based evolutionary algorithm for process parameters optimization is proposed. Considering that most injection molded parts have a sheet like geometry, a fast strip analysis model is adopted as a surrogate model to approximate the time-consuming computer simulation software for predicating the filling characteristics of injection molding, in which the original part is represented by a rectangular strip, and a finite difference method is adopted to solve one dimensional flow in the strip. Having established the surrogate model, a particle swarm optimization algorithm is employed to find out the optimum process parameters over a space of all feasible process parameters. Case studies show that the proposed optimization algorithm can optimize the process parameters effectively. [ABSTRACT FROM AUTHOR]

In computer numerical control machine tools, using machining simulation to prevent collision becomes more and more popular due to its efficiency and low cost. However, if the entire digital model of the machining setup does not exist, the simulation is not applicable. As a result, the operator has to manually check the numerical control program, which is a time-consuming and error-prone process. In this paper, an on-machine vision system is presented to quickly construct the digital model based on the actual machining setup. The total construction for a complex setup can be done within a few minutes. Several key technologies have been developed. First, a 2D edge feature detection algorithm has been designed which will extract the edges of the object of interest by processing both the real and virtual images. Second, a stereo vision system is developed which will obtain the three-dimensional (3D) edge data of the object of interest. A new algorithm is presented to solve correspondence, which is the key problem of the stereovision system. Furthermore, the 3D object recognition algorithm is developed to let the system intelligently search for the matched solid model in the database and import it into the virtual environment with an accurate pose. Finally, experiments are carried out to test the developed system. [ABSTRACT FROM AUTHOR]

The simulation of the cutting process becomes a key aspect on production optimization. The search for optimal cutting parameters by simulation can be a very effective way of reducing the tuning time of the process and can demonstrate potential cost reduction. As the simulation of the microscopic behavior of the cut is still difficult to perform, most of the prediction techniques are based on mechanistic models of the cutting forces, whose parameters are deduced from experimental tests. The runout of the tool can be a parasite effect that lowers the precision of the identification of the cutting forces parameters. This paper shows the improvement of an identification algorithm given by the modeling of radial runout effect on the undeformed chip thickness. Two different models of cutter runout have been used and tested on experimental measurement performed on a static dynamometer. The adequacy between simulation and experiment is good and allows reliable prediction of cutting forces for different cutting conditions. [ABSTRACT FROM AUTHOR]

This paper describes a new approach based on ant colony optimization (ACO) metaheuristic and Monte Carlo (MC) simulation technique, for project crashing problem (PCP) under uncertainties. To our knowledge, this is the first application of ACO technique for the stochastic project crashing problem (SPCP), in the published literature. A confidence-level-based approach has been proposed for SPCP in program evaluation and review technique (PERT) type networks, where activities are subjected to discrete cost functions and assumed to be exponentially distributed. The objective of the proposed model is to optimally improve the project completion probability in a prespecified due date based on a predefined probability. In order to solve the constructed model, we apply the ACO algorithm and path criticality index, together. The proposed approach applies the path criticality concept in order to select the most critical path by using MC simulation technique. Then, the developed ACO is used to solve a nonlinear integer mathematical programming for selected path. In order to demonstrate the model effectiveness, a large scale illustrative example has been presented and several computational experiments are conducted to determine the appropriate levels of ACO parameters, which lead to the accurate results with reasonable computational time. Finally, a comparative study has been conducted to validate the ACO approach, using several randomly generated problems. [ABSTRACT FROM AUTHOR]

In this paper, an online grey forecasting run-to-run control system was proposed with the integration of run-to-run control system, recursive least-squares (RLS) algorithm, and grey forecasting model (GFM). One of the objectives of this study is to explore the possibility and feasibility of applying GFM to run-to-run control system in copper chemical mechanical polishing. Under the condition of limited experiment data, GFM is excellent at estimating and forecasting error of the next batch online. To keep the process under control, the controllers are then employed to adjust the process parameters in order to compensate the error. In addition, the RLS algorithm is used to construct dynamically a system estimation matrix for the purpose of stating precisely the relationship between process quality and process parameters, and to consequently improve processing performances. From the computer simulation and the experiment results, the proposed new method developed in this study was able not only to confine the processing performances’ error within the range of 5% but also to supplement, when the process parameters are saturated, the control capability through adjusting other unsaturated process parameters, thus maintaining good processing performances. [ABSTRACT FROM AUTHOR]

In this paper, finding the maximum dynamic load carrying capacity of flexible joint manipulators in point-to-point motion is formulated as an optimal control problem. The computational methods are classified as indirect and direct methods. This work is based on the indirect solution method of optimal control problem. The application of Pontryagin’s minimum principle to this problem results in a two-point boundary value problem (TPBVP) solved numerically. Two algorithms are developed on the basis of the solution of the TPBVP. The first one is used to plan the optimal path for a given payload, and the other one is exploited to find the maximum payload and corresponding optimal path. The main advantage of the proposed method is that the various optimal trajectories are obtained with different characteristics and different maximum payload. Therefore, the designer can select a suitable path among the numerous optimal paths. In order to illustrate the power and efficiency of the proposed method in the presence of flexibility in joints, a number of simulation tests are performed for a two-link manipulator. Then, the effect of flexibility on the maximum payload value is investigated and compared with rigid one. Finally, for the sake of comparison with previous results in the literature, simulation is performed for a rigid-joint three-link manipulator, and a reasonable agreement is observed between the results. [ABSTRACT FROM AUTHOR]

The majority of mechanical parts are manufactured by milling machines. Hence, geometrically efficient algorithms for tool path generation and physical considerations for better machining productivity with guarantee of machining safety are the most important issues in milling tasks. In this paper, we present an optimized path-generation algorithm for zigzag milling, which is commonly used in the roughing stage as well as in the finishing stage, based on an incomplete two-manifold mesh model, namely, an inexact polyhedron that is widely used in recent commercialized CAM software systems. First of all, a geometrically efficient tool path generation algorithm using an intersection points-graph is introduced. Although the tool path obtained from geometric information has been successful to make a desirable shape, it seldom considers physical process concerns like cutting forces and chatter. In order to cope with these problems, an optimized tool path that maintains constant MRR in order to achieve constant cutting forces and to avoid chatter vibrations at all times is introduced and the result is verified. Additional tool path segments are appended to the basic tool path by using a pixel-based simulation technique. The algorithm was implemented for two-dimensional contiguous end-milling operations with flat end mills and cutting tests were conducted by measuring the spindle current, (which reflect machining situations) to verify the significance of the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, inventory management of time-sensitive materials using RFID data is studied using simulation. Based on the production data obtained from a manufacturing company, three inventory management models that rely on RFID data for tracking and dispatching of time-sensitive materials on a shop floor is presented. The complexity of the models ranges from statically-set, fixed baseline inventory models to dynamic, forecast-integrated inventory control schemes. This study compares the inventory models on the basis of service level, cost, inventory and waste reduction, and decision-making complexity. A comparative analysis of the models is presented in a simulation environment, which also demonstrates the overall benefits and effectiveness of RFID technologies in providing low-cost manufacturing solutions, reduced inventory levels, and lower overall waste. The forecast-integrated inventory model is developed based on a trend-adjusted exponential smoothing algorithm, with two smoothing parameters, α and β, used as coefficients for the average production demand and its trend, respectively. The study shows that the desired level of system performance can be achieved by adjusting the values of the smoothing parameters. [ABSTRACT FROM AUTHOR]

In tandem AGV systems, the shop floor is partitioned into a group of non-overlapping zones, where each is served by a single dedicated vehicle. In this paper, a two phase algorithm for partitioning tandem AGV systems is proposed. The proposed algorithm serves a number of objectives including minimizing the total handling cost, minimizing the maximum workload in the system and minimizing the number of between-zones trips. The algorithm is equipped with parameters to enable the user to select one of these objectives or to optimize a combination of them. The performance of the algorithm regarding the objective of minimizing the material handling cost is evaluated by experimental design. The experiment is based on comparing the solutions obtained by the proposed algorithm with best solutions obtained by a ‘rationalized exhaustive enumeration’ procedure for a group of randomly generated problems. The analytical results showed that the proposed algorithm obtains an average of 99.53% efficiency, and that none of the considered factors has a main significant effect on the performance of the algorithm in regards to the objective of minimizing the total material handling cost, however, a few of the interaction effects are significant. [ABSTRACT FROM AUTHOR]

This paper develops an octree-based algorithm for machining simulation. Most commercial machining simulators are based on the Z-map model, which has several limitations in terms of achieving a high level of precision in five-axis machining simulation. Octree representation being a three-dimensional (3D) decomposition method, an octree-based algorithm is expected to be able to overcome such limitations. With the octree model, the storage requirement is reduced. Moreover, recursive subdivision is processed in the boundaries, which reduces useless computations. The supersampling method is the most common form of antialiasing and is typically used with polygon mesh rendering in computer graphics. The supersampling technique is being used to advance the efficiency of the octree algorithm. [ABSTRACT FROM AUTHOR]

The main point of this paper is to provide a simple and efficient threshold value for the threshold accepting (TA) algorithm to attempt an optimal solution for the regular grid travelling salesman problems (TSPs) in a reliable way. This new algorithm is named the single value threshold accepting algorithm (SVTA). The number of the threshold value is one and its value is: [(2-√2)g*10,0001/10,000 where g is the grid size and [x] is the smallest integer not less than a real number x. For the regular-grid TSPs, g can be set as 1/√n where n is the problem size. It is shown empirically, with 100 independent simulations performed with 441 cities, in 16 different cases, that the SVTA is far superior to (at least five times faster on average than) the previous double threshold accepting (DTA) with respect to the speed of finding a global optimal reliably. Particularly in the case of the 441 cities, the proposed algorithm is at least 21 times faster and rises up to 96 times on average and optimistically 284 times faster than the previous one. Important insight is provided that reveals how the formula works and why it works successfully. [ABSTRACT FROM AUTHOR]

The positioning accuracy and positioning time of CNC systems have recently been the main performance criteria for industrial applications. The acceleration/deceleration modes, especially the deceleration modes, have an important effect on them. In this paper, firstly, some problems of the conventional linear deceleration algorithm are analyzed. Then an improved linear acceleration/deceleration algorithm is introduced. In this algorithm, the deceleration point is predicted exactly, and then the deceleration point error is compensated for at higher feedrates. Furthermore, a higher resultant maximum acceleration than that in the conventional scheme is selected to shorten the acceleration/deceleration time. Compared with the conventional linear acceleration and deceleration algorithm, the system performance has been significantly improved. Finally, the performance is confirmed by several simulations and experiments. [ABSTRACT FROM AUTHOR]