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CNC systems with the vision function have become very valuable for intelligence machine tools because machine vision is a fast-growing intelligent feature for machines. A novel vision-oriented open CNC system was developed in this study and used in profile grinding machines for the precise machining of parts with contour surfaces, such as complex molds and cutting tools. The system is an innovation to the conventional profile grinding method and enabled the profile error to be visually detected and compensated during the machining process. In this study, a novel design methodology for a machine-vision-oriented CNC system was proposed. An Ethernet-based hardware architecture was constructed for the vision-oriented CNC system. The software characteristics of the developed CNC system were analyzed, including a new type of multi-thread software architecture, a seamless handover approach for multi-thread accessing of the memory space, the integration of the human-machine interface with image processing, and virtual-axis-based online error compensation. The running efficiency test of the software development platforms, time-consumption analysis of the measurement and control in the vision-oriented CNC system, and verification of the effectiveness of the developed vision-oriented CNC system were performed. The results indicate that the proposed vision-oriented open CNC system can effectively fuse image processing with motion control, meet the efficiency requirement, and improve the machining precision of profile grinding. The results are also valuable for developing other machine-vision-based intelligent machine tools. [ABSTRACT FROM AUTHOR]

In this paper, a novel integrated framework for design and optimization of a machine tool structure is presented, which can greatly improve the design quality and efficiency by combining knowledge-based design and multi-stage optimization with the CAD/CAE integration technique. To realize this framework, a topology architecture model has been developed to integrate the configuration design and geometric modeling knowledge as well as the static and dynamic evaluation knowledge of machine tools with a specific topology architecture type; an analysis feature model is proposed for the integration between commercial CAD and CAE software, in which analysis features can be automatically converted to a script code for finite element analysis (FEA) through feature mapping. Based on the topology architecture model and feature-based CAD/CAE integration methodology, a two-stage design optimization process is proposed to perform the conceptual structural design of machine tools. In the first stage, the principal parameters which critically affect the performance of an entire machine are determined; then, the static and dynamic stiffness matching designs are performed to obtain the reasonable stiffness and weight of each structural part and functional component based on the stiffness model and dynamic model. In the second stage, the arrangement of ribs is determined by inferring the design knowledge; FEA is used to evaluate the performances of structural parts, and the response surface method (RSM) is applied to optimize the structural parameters to approach the stiffness and mass close to the allocated values obtained from the first stage. Re-design of a four-axis horizontal machining center with a box-in-box architecture was carried out to illustrate the design procedure in detail and to verify the feasibility and efficacy of the proposed framework. By applying the proposed framework, the total weight of the entire machine is minimized while sufficient stiffness is maintained. The results also show that the proposed framework facilitates the conceptual structural design and optimization process of machine tools. [ABSTRACT FROM AUTHOR]

In deep drawing process, excessive mass flow causes wrinkling and insufficient mass flow causes fracture. Blank holder has direct influence on mass flow into die cavity. In this study, the effect of pulsating blank holder by using a new mechanical system has been investigated for improving the formability of aluminum alloy. Also, this paper presents a systematic methodology for developing second-order statistical model to show the relationship between drawing depth and input variables (frequency of blank holder, amplitude of blank holder movement, and velocity of punch movement). The obtained model was used to analyze the effect of input parameters on performance of pulsating blank holder. The results show that the pulsating blank holder in comparison with static one can increase significantly the limiting drawing ratio of deep drawing process about 11.53%. The optimized drawing depth value is subsequently obtained from the mathematical model. [ABSTRACT FROM AUTHOR]

Friction conditions are very critical in metal forming because they can lead to important thinning in the final manufactured product. The value of the friction coefficient is then of particular importance for performing predictive finite element (FE) simulation of forming operations. Classically, numerical simulations are run with values of the friction coefficient found in technical database where the Coulomb's coefficient has been evaluated with the pin-on-disk test. Moreover, the friction coefficient is often used as a set up parameter for running FE simulations. The pin-on-disk test is not automatically suitable for characterizing the friction coefficient in tube hydroforming. The 'corner filling' test has been developed for tube hydroforming and several authors have developed analytical models for representing this test. Among them, the authors have chosen to exploit the Orban-Hu model. This model permits to build graphs. On those graphs, experimental data are overlaid in order to evaluate the friction coefficient. Thus, a friction coefficient ( μ) of 0.4 has been found by the proposed method against the value of about 0.1 found in technical database. FE simulations with 3D shell and 3D solid models have been performed with the two values of the friction coefficients. The conclusion is that FE simulations with 3D shell model permit definitely better predictions for thickness evaluation. Moreover, running the simulations with μ = 0.4 leads to a more critical representation of the minimal thickness in the final component. Finally, an experimental method is proposed for the evaluation of the friction coefficient without advanced numerical methods. [ABSTRACT FROM AUTHOR]

Elementary indentation processes are relatively simple compression processes and they are quite extended in many fields of the industry. Nevertheless, the concatenation of these processes is a new approach and has interest from a technological point of view. Incremental forming processes can be carried out in CNC machines with more flexibility, lower force requirements and simpler tools than in conventional forging processes. The purpose of this work is the analysis of the three-dimensional geometry resulting from the multiple indentation process. Based on the surface rugosity parameters defined in the specification standard ISO 4287, the state of the 3D-formed surface by several types of tools is studied and a predictive evaluation model has been developed in order to quantify, by means of shape parameters Sa and SM, the topography of the expected surface and the amount of material displaced depending on the technological and geometrical characteristics of the process. [ABSTRACT FROM AUTHOR]

When directly fabricating mechanisms by powder bed fusion (PBF) process, the processability of mechanism is an important factor in a successful fabrication and is studied in this paper. The reference structures due to PBF process are presented; design guidelines of non-assembly mechanisms for PBF process are then suggested to improve the processability. Apart from the design guidelines, the relationship between processability and process strategy is investigated. Lastly, two cases are presented, a universal joint and a rocker-slider mechanism, which are directly fabricated by selective laser melting. Results show that they can be successfully fabricated. The PBF process provides a new methodology that allows more design freedom and faster fabrication of mechanisms. The directly fabricated mechanisms would have better quality and better performance when reasonably designed. [ABSTRACT FROM AUTHOR]

The hole-making process in composite parts today is required to be more accurate and efficient, which can affect the in-service life and decrease manufacturing cost. Thus understanding the key factors affecting their qualities is of vital importance to develop effective machining strategies. To this end, this study proposes a model with response surface methodology (RSM) based on the Taguchi method to evaluate the influence of drilling parameters on delamination by compound core-special drills. The model with RSM includes three steps: (1) design and experiments, (2) response surface modeling through regression, and (3) optimization. A series of experiments were conducted to test the proposed model. It was found that the key factors affecting drilling-induced delamination include: cutting velocity ratio, feed rate, inner drill type, and inner drill diameter. Therefore, some experimental implications can be proposed accordingly. [ABSTRACT FROM AUTHOR]

Before making a due date commitment to our customer, we need to estimate the cycle times of jobs. For this reason, many of the most-advanced methods classify jobs, before or after estimating the cycle times. However, job classification is not directly helpful to optimize the performances of these estimation methods. To solve this problem, a job-classifying and data-mining approach is proposed in this study to improve the performance of cycle time estimation by optimizing the results of job classification. In addition, some association rules are also extracted from the estimation results to facilitate the practical application of the proposed methodology. According to the results of a case study, the job-classifying and data-mining approach achieved a better estimation performance and could produce some useful estimation rules. [ABSTRACT FROM AUTHOR]

During the operations of an agricultural tractor, front axle and front axle support encounter the worst load conditions of the whole tractor. If the design of these components is not verified by systematic engineering approach, the operators of the tractor may face with sudden failures. This paper aims to develop a verification method, which involves testing an agricultural tractor on a special test track and agricultural field and together with the computer aided engineering analysis, in order to prevent such failures in the lifetime of the agricultural tractor. For this purpose, a strain gage data acquisition system has been designed to measure the strain values on the component in order to determine maximum principle stresses for the calculation of overload safety on the agricultural field and stress data for the prediction of fatigue life on a radial washboard test track. The cycle number of these stress data for the fatigue analysis has been established by rainflow cycle counting method. Total fatigue damage for the front axle support has been calculated considering damage accumulation hypothesis defined by Miner. [ABSTRACT FROM AUTHOR]

Analytical ways to reach the best decisions are the most preferable issues in many business platforms. During the decision processes, besides the measurable variables, there exist qualitative variables, especially if the decision is based on a selection problem. Analytic hierarchy process (AHP) and analytic network process (ANP) are two of the best ways to decide among the complex criteria structure in different levels using qualitative variables. When there are interactions between the criteria in different levels of the hierarchy, then AHP cannot be used because of their one-way direction of hierarchy; the ANP has been developed for this kind of need. In this study, a fuzzy ANP method is developed for a multi-criteria facility location selection problem where the criteria set includes interactions with each other on the hierarchy structure. Besides the fuzzy ANP model development and implementation on facility location, sensitivity analysis was also originally performed to indicate the upper and lower bounds for the importance levels of alternative locations. [ABSTRACT FROM AUTHOR]

A new method of testing of the accuracy of coordinate measuring machine (CMM) articulating heads was developed and verified. This procedure consists of the measurement of a test sphere, and requires only a basic configuration of the coordinate measuring machine. A new parameter describing the repeatability of angular positioning by CMM articulating probing system was defined. [ABSTRACT FROM AUTHOR]

Runout is a composite tolerance that is usually specified to ensure proper alignment and rotational accuracy for axially symmetric features. The procedure for evaluation of runout defined in American Society of Mechanical Engineers (ASME) Y14.5M-1994 [] and International Organization for Standardization (ISO)/TR 5460-1985(E) [] depicts the rotation of a part around its datum axis while a dial gauge measures the variations in the feature's surface. These standards do not address the evaluation of runout using modern measurement technologies using discrete point clouds that dominate the metrology industry. This research presents a comprehensive methodology for evaluating runout tolerance using discrete data that closely replicates the requirements specified by the ASME and ISO standards. This work builds upon previous work by the authors, reported in Turek et al. [] and presents a comprehensive methodology for evaluating circular and total runout for flat, tapered, and cylindrical features using discrete data. The methodology was tested using simulated datasets and the analysis reaffirmed the results reported in Turek et al. [] regarding the choice of minimum circumscribing cylinder as the preferred datum axis evaluation technique. Subsequently, the approach presented in this paper was applied to discrete data acquired from two manufactured parts. The results obtained were compared with traditional runout measurements acquired with a dial gauge. This comparison required the filtering of the discrete data to compensate for the finite radius of the dial gauge tip, and led to the development of a novel filtering technique to appropriately compare results. The results using the filtered data closely match the results obtained from the dial gauge, confirming the accuracy of the presented runout assessment algorithms. This work presents a first step in assessing runout using discrete data and justifies the use of modern metrology techniques in runout evaluation. [ABSTRACT FROM AUTHOR]

The problem of grouping of parts into part-families and that of machines into machine-cells has attracted the attention of many researchers particularly for medium variety of parts with medium production volume requirement, which traditionally required their production in batches for achieving economics of production. This kind of grouping, consequently offering benefits of mass production, was aimed to have independent cells processing ideally almost different sets of part-types. For this purpose, a number of approaches are available from various kinds of heuristics to mathematical programming formulations. Evolutionary methods such as neural network, genetic algorithm, and simulated annealing have also been tried and have been found to provide better grouping solutions with much less computational complexity. In the present paper, ant colony optimization approach with number of newer strategies, incorporating more generalised framework of ants' behaviour, has been applied to the parts and machines grouping problems taken from the literature. The results obtained from their application were found to be encouraging and thus establish the usefulness of the proposed approaches. Average performance of Tabu search with multiple ants was found to be the best and thus the parameter values for this approach were also determined using design of experiments methodology. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a near optimal buffer allocation plan specifically developed for a remanufacturing system with finite buffers and server vacations. During server vacations, the server stops service for a random amount of time during which arrivals continue to occur. The term server vacation may be used for cases where the server leaves the primary queuing system to work on alternative duties for a random duration every time the server becomes idle (e.g., server could leave to work on additional tasks that he is responsible for or perform preventive maintenance on equipments). The remanufacturing system considered here consists of three modules, viz., the disassembly and testing modules for returned products and the remanufacturing module. In order to analyze the system, we propose an algorithm that uses an open queueing network, decomposition principle, and expansion methodology. The buffer allocation algorithm distributes the given number of available buffer slots among the remanufacturing system stations to optimize the system's performance. The algorithm has been thoroughly tested using a variety of experimental conditions. The results show that the performance of the algorithm is consistent, robust, and produces excellent results. [ABSTRACT FROM AUTHOR]

In the welding and assembling process planning for body-in-white, case retrieval can make full use of the existing knowledge and the experience of experts. Firstly, considering primary features, secondary features, and feature relations, a comprehensive feature model for parts is established. Secondly, a three-stage search strategy is implemented to calculate the similarities between a new part and old cases. Topological feature, geometric feature, and material feature similarities are calculated respectively in different stages. Corresponding thresholds are set to reduce the search space of next stage. This layered searching strategy can improve retrieval efficiency. Finally, a case study indicates the effectiveness of this methodology. [ABSTRACT FROM AUTHOR]

Tool condition monitoring, mainly tool breakage detection for high-speed machining (HSM), is an important problem to solve; however, the techniques or types of sensors applied in other research projects present certain inconveniences. In order to improve tool breakage monitoring systems, a simple, effective, and fast method is presented herein. This method is based on the discrete wavelet transform (DWT) and statistical methodologies. The effectiveness of the method is based on the measurements of the feed-motor current signals using inexpensive sensors. It is well-known that during the cutting process, the motor current is related to the tool condition. The current consumption changes when the tool is broken as compared to when the tool is in normal cutting condition. This difference can be obtained from the waveform variances between the signals in order to ascertain the tool condition. The algorithms of this research project consist of obtaining compressed signals from the I feed-motor current signals applying the DWT. Then from these compressed signals, we detect the asymmetries between them. The arithmetic mean value is applied to asymmetries of consecutive machining lengths to reduce noise in the data having a mean value of a series of asymmetries; also, a normal cutting threshold is set up in order to make decisions regarding the tool conditions so as to detect tool breakage. Therefore, this research project shows a low-cost monitoring system that is simple to implement. [ABSTRACT FROM AUTHOR]

Efforts to manage end-milling cutter-tool life depend upon the accuracy of the information used in the assessment of the work done. This presents a problem in many instances because the measurement of cutting-related parameters is difficult, especially when the operations being undertaken do not form part of a repeated manufacturing cycle. This paper presents a methodology utilising ultrasonic sensors for the real-time monitoring of the depth of cut arising during end-milling operations. The paper outlines the architecture of a tool condition monitoring system based upon state of the art microcontrollers. It then considers how depth of cut information can be integrated into such a system in order to support effective end-mill tool-life management functions. [ABSTRACT FROM AUTHOR]

Modeling and optimization of cutting parameters are one of the most important elements in machining processes. The present study focused on the influence machining parameters on the surface roughness obtained in drilling of AISI 1045. The matrices of test conditions consisted of cutting speed, feed rate, and cutting environment. A mathematical prediction model of the surface roughness was developed using response surface methodology (RSM). The effects of drilling parameters on the surface roughness were evaluated and optimum machining conditions for minimizing the surface roughness were determined using RSM and genetic algorithm. As a result, the predicted and measured values were quite close, which indicates that the developed model can be effectively used to predict the surface roughness. The given model could be utilized to select the level of drilling parameters. A noticeable saving in machining time and product cost can be obtained by using this model. [ABSTRACT FROM AUTHOR]

embly line balancing has gotten a considerable place in industrial importance. Hence, a lot of researchers are interested in this subject and several papers have been published until now. Many exact, heuristic, meta-heuristic, and hybrid approaches have been used to solve this type of problems. Different rules are applied for line balancing such as rank positional weight (RPW). Assembly line balancing problems are considered mostly in definite status, while the nature of manufacturing systems is accompanied with uncertainty. In this paper, we propose a model based on RPW algorithm considering uncertain time parameters for stochastic assembly line balancing. Also, two other methodologies of normal distribution integration and Monte Carlo simulation are developed. The effectiveness of the proposed model and validity testing with respect to other two approaches are illustrated using numerical examples. [ABSTRACT FROM AUTHOR]

Supplier selection plays a key role in an organization because the cost of raw material constitutes the main cost of the final product. Selecting an appropriate supplier is now one of the most important decisions of the purchasing department. This decision generally depends on a number of different criteria. The objective of this paper is to propose a data envelopment analysis methodology that considers both undesirable outputs and imprecise data simultaneously. The proposed model is applied in supplier selection problem. A numerical example demonstrates the application of the proposed method. [ABSTRACT FROM AUTHOR]

Setup planning is an important part of process planning that has been widely investigated by various researchers. However, the output of the traditional setup planning approaches is limited and insufficient for the upstream process planning activity, fixture design. In this work, a setup planning system is developed that provides sufficient inputs to the fixture designer in terms of recommended depth of cut and feed, fuzzy clamping forces, near optimal locator and clamp layout, and sizes of the locators and clamps. The fixture designer can further optimize the fixture plan by taking these inputs. The methodology is illustrated with the help of an example. [ABSTRACT FROM AUTHOR]

novel methodology was developed and implemented for error characterization, evaluation, and its quantification in a rotary joint of multi-axis machine tools by using a calibrated double ball bar (DBB) system as a working standard. This methodology greatly simplified the measurement setup and accelerated the error quantification. Moreover, the methodology is observed to be highly economical by reducing the tooling and instrumentation. However, considerable time and little more efforts are required in measuring and computing the errors. The developed methodology is capable of evaluating the five degrees of freedom (DOF) errors including two radial errors, one axial error, and two tilt errors out of six DOF error components of rotary joints. A DBB system with point accessory was used for direct measurement by change of length at multi-points and various locations, whereas mathematical modeling technique was implemented, and equation solvers were exercised for error evaluation and its quantification. Validation and authentication of the methodology and results obtained were carried out by simulation process prior to implementing the methodology on rotary joints of a five-axis turbine blade grinding machine. The results obtained from 'A' and 'B' rotary joints of the turbine blade grinding machine were presented by applying cubic spline technique for error modeling and its further utilization. The methodology was found extremely pragmatic, quite simple, efficient, and easy to use for error characterization and its quantification in rotary joints of multi-axis machine tools. [ABSTRACT FROM AUTHOR]

This research deals with tool compensation and postprocessor development for numerical control application. The content consists of three main activities. First, derives a cutting location expression of the tool for compensation and machining stability use. Second, establishes an analytical methodology to develop a kinematics transformation algorithm (KTA) for the specific type machine with a swivel spindle head and two rotary tables. And last, defines correspondent between workpiece and the cutter to attain the aim of three-dimensional tool compensation and presents postprocessors under KTA for two types of five-axis machine centers in examples. [ABSTRACT FROM AUTHOR]

Design for manufacture usually implies applying various guidelines derived from previous experience to improve part design so it is more compatible with the capabilities of the selected process, resulting in better quality and lower cost. The guidelines can be formulated as dimensionless criteria, enabling quantitative evaluation of a particular aspect of part design. There is, however, no good way to compare two or more designs for all aspects, considering that they may not be equally important. In this work, we employ analytical hierarchy process to determine the relative weights of various criteria for castability evaluation. The criteria are categorised in a three-level hierarchy, with the middle level comprising mould, feeding and gating groups. The prioritisation of criteria along with consistency checking of pair-wise comparisons enables a systematic evaluation of alternative product designs for manufacturability. The methodology is illustrated by modifying the product and tooling design of a grey iron bracket casting and estimating the improvement in manufacturability. The results are supported by experiments. [ABSTRACT FROM AUTHOR]

The envelope theory provides a solid mathematical tool for accurate computations and design of milling tools that generate helical surfaces such as disk or end mill tools. Given an analytical description of the helical surface to be generated, and considering that the machined surface and milling tools are reciprocally enwrapping during the generation motions, one can deduce equations for the milling tool profile. However, this usually involves transcendent equations that require significant computational resources for their solution. More importantly, analytical representations of the surfaces to be generated are not always available, as in the case of measured discrete surfaces. To alleviate the issue, polynomial approximations of the entire helical surface or only of a spatial curve along the surface can be used as already published in previous works. The present study focuses on the methodology of finding the simplest polynomials when only a small number of points are known or measured from the surface to be generated. The numerical simulation and real examples show that third degree Bezier polynomials are suitable approximations for many practical situations. In such cases, not only computation complexity is highly reduced but also the measurement process is significantly simplified. The paper presents a methodology for the design of disk-cutting tools reciprocally enwrapping cylindrical helical surfaces of constant pitch when the helical surface generatrix is known in discrete form. The suggested method is using a small number of points belonging to the helical surface to be machined. Due to the use of a low-order Bezier polynomials representation of the helical surface generatrix, a small approximation error is introduced as shown in our numerical examples. Using as a reference the analytical representation of the generatrix, the exact axial section of the disk tool can be computed and compared to the axial section obtained using the methodology described in this paper. The approximation errors seem to be acceptable for many technical applications. Numerical simulations and examples were performed using a Java-based implementation of the suggested algorithm. [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]

This investigation presents the use of Taguchi and response surface methodologies for minimizing the burr height and the surface roughness in drilling Al-7075. The Taguchi method, a powerful tool to design optimization for quality, is used to find optimal cutting parameters. Response surface methodology is useful for modeling and analyzing engineering problems. The purpose of this paper was to investigate the influence of cutting parameters, such as cutting speed and feed rate, and point angle on burr height and surface roughness produced when drilling Al-7075. A plan of experiments, based on L27 Taguchi design method, was performed drilling with cutting parameters in Al-7075. All tests were run without coolant at cutting speeds of 4, 12, and 20 m/min and feed rates of 0.1, 0.2, and 0.3 mm/rev and point angle of 90°, 118°, and 135°. The orthogonal array, signal-to-noise ratio, and analysis of variance (ANOVA) were employed to investigate the optimal drilling parameters of Al-7075. From the analysis of means and ANOVA, the optimal combination levels and the significant drilling parameters on burr height and surface roughness were obtained. The optimization results showed that the combination of low cutting speed, low feed rate, and high point angle is necessary to minimize burr height. The best results of the surface roughness were obtained at lower cutting speed and feed rates while at higher point angle. The predicted values and measured values are quite close to each other; therefore, this result indicates that the developed models can be effectively used to predict the burr height and the surface roughness on drilling of Al-7075. [ABSTRACT FROM AUTHOR]

Assembly sequence design for a mechanical system can have significant impact on manufacturing cost and product quality. Traditionally, such a design process is largely based on experience and best practices, often ineffective and non-optimal as the system becomes complex. This paper proposes a new, systematic method for automatic assembly sequence design and optimization. Key elements include assembly modeling, sequence planning, locating scheme optimization, dimensional quality evaluation, and optimization. First, a directed graph and an assembly matrix are employed to describe the assembly relation of a system. Then, the feasible assembly sequences are generated through layered subassembly detection of adjacency matrices, filtered by engineering constraints. To evaluate quickly the assembly quality and compare the influences of different locating point schemes, a linear 3D variation propagation analysis model with deterministic locating principle is introduced. The optimal locating scheme is then selected using a genetic algorithm with the least variation propagation. Finally, the assembly dimensional quality for different sequences is evaluated and the optimal assembly sequences are achieved through genetic algorithms. A case of automotive body side assembly is presented to illustrate the whole methodology. [ABSTRACT FROM AUTHOR]

Users in enterprise information systems want to efficiently search the information that they need. Although several searching approaches have been proposed so far, they still have the limitation in finding the semantically similar information that users need. To overcome the limitation, it is essential to consider the semantics of user keyword and terms (concepts) stored in the ontology repository and continuously update the ontology repository for information searching. To this end, in this study, an ontology mapping-based search methodology (OntSE) is proposed. The OntSE consists of three phases: ontology building, ontology mapping, and ontology updating. Its objective is to find the terms which have the same semantics with user’s keywords, based on multidimensional similarity and Bayesian network. To show the benefits of the proposed methodology, a case study has been carried out. [ABSTRACT FROM AUTHOR]

The time-dependent scheduling problems have received considerable attention recently. However, machine availability, an important and practical consideration, is usually neglected. Motivated by this observation, we introduce a single-machine scheduling problem where deteriorating jobs and an availability constraint are considered. Our objective is to minimize the total completion time. In this paper, we derived optimal and near-optimal solutions for the problem, and we also gave a simulation study to show that our algorithm successfully yields the optimal solution for instances with less than 20 jobs in less than a minute. Our computational experiment also showed that the mean error percentage of the proposed heuristic algorithm for all test instances is less than 1.3% and drops to zero as the number of jobs increases. [ABSTRACT FROM AUTHOR]

The manufacture of microproducts differs from that of conventional products in many ways, not only in the sizes, but also in issues concerning the effects of material properties, tools, and manufacturing equipment. There was a need for a new design methodology and associated design tools to aid designers in assessing the design of their microproducts by considering new micromanufacturing capabilities and constraints. A knowledge-based design advisory system (DAS) was, therefore, developed in MASMICRO in which the knowledge-based system with dedicated assessment modules and knowledge representatives based on the ontology was created to implement the distributed design and manufacturing assessment for micromanufacturing. The modules address the assessment on geometrical features relating to manufacturability, manufacturing processes, selection of materials, tools, and machines, as well as manufacturing cost. The Microsoft C# programming language, ASP.NET web technology, Prolog, and Microsoft Access database were used to develop the DAS. The test on the DAS prototype system was found to provide an increase of design efficiency due to more efficient use of design and manufacturing knowledge and afforded a web-based collaborative design environment. [ABSTRACT FROM AUTHOR]

This paper deals with the prediction of heat transfer coefficient of steel bars subjected to Tempcore process. A nonlinear mathematical model, in terms of process variables, is developed using response surface methodology. Three significant control parameters are considered. Central composite design of experiments is structured and conducted using finite element method to formulate the predictive nonlinear model. Statistical analysis and experimental results suggest that the proposed model could be used for predicting heat transfer coefficient with adequate accuracy. The knowledge of heat transfer coefficient makes it possible to predict temperature evolution in the steel rods. As the temperature distribution affects the mechanical properties of steel rods, the proposed methodology can be effectively employed in controlling the quality of products. [ABSTRACT FROM AUTHOR]

Taguchi method was known in many industries as an off-line quality control methodology to improve the performance of products or processes at low cost. Although it was effective at improving quality, the statisticians pointed to inefficiencies in the method for highly nonlinear problems and complexity of the product design, the results were often less than satisfactory. Therefore, recently mathematical model and computer simulation are the other alternatives for robust design. However, Taguchi method and computer simulation have their own advantages and disadvantages. So, this idea motivates the approach of combining both advantages together to promote the more effectiveness of robust design. This paper proposes the approach to apply computer-aided engineering (CAE) with genetic algorithm (GA) and Taguchi method in dynamic robust parameter design. Firstly, we use computer simulation, CAE, to obtain the data instead of conducting whole real experiment. Next, a statistical approach, linear regression is used to model the unknown functions, and then GA, heuristics search approach, is employed to find the appropriate setting of controllable factors on the basis of the quality loss function. The effect of noise factors which is the important philosophy of robust design is also considered by utilizing the outer orthogonal array. The objective is to minimize the average quality loss instead of maximizing SN ratio. In addition, to enhance the capability of the proposed approach, the two-step method is applied to screen out the dispersion factors significantly affecting the quality variation and the adjustment factors significantly affecting the sensitivity of the Taguchi’s dynamic system for the case of changing products or processes’ requirements in the future. This proposed is applied to the example “Foam design of automobile’s dashboard”. [ABSTRACT FROM AUTHOR]

This paper describes a methodology of variation risk analysis for microsystems using analytical modelling and simulation, a key characteristic (KC) method and statistical analysis considering MEMS fabrication tolerances. This methodology is applied to an innovative design for a micro co-ordinate measuring machine (CMM) probe utilising piezoelectric actuation and sensing currently being developed at the National Physical Laboratory. Analytical modelling is used to investigate the individual effects of dimensional parameters on the sensors’ open-circuit voltage output, which is a KC of the micro CMM probe. A computer simulation is performed using the finite-element method and compared with the analytical model. The KC variation is predicted and the variation contribution of the probe manufacturing processes is presented. This KC is mainly influenced by the thickness of the piezoelectric layer associated with the composite sol gel deposition process. Variation risk analysis results can be used to implement a variation risk mitigation strategy. [ABSTRACT FROM AUTHOR]

One of the main difficulties in developing a testing-and-diagnosis system for micro-manufacturing devices and machines is that the measurement process can require a high number of sensors, and is often too complex, in order to avoid external disturbances under normal working conditions, and the sensors are also not easy to allocate due to the minimal space available. At the present time, modern techniques of control-system engineering can be applied to propose a model-based testing and diagnosis methodology that reduces the number of the required sensors, due to a priori knowledge of the system expressed in terms of mathematical relationships between the physical variables. The Mechatronic Variable Estimation Library was created as a tool to estimate the value of “unknown” variables and parameters of the micro-device or machine using only a few sensors, reducing in this way the cost of the testing system and making the product of interest for industrial applications. [ABSTRACT FROM AUTHOR]

This paper proposes a modified shifting bottleneck heuristic (MSBH) for the reentrant job shop scheduling problem (RJSSP) with makespan minimization objective. Recently, the reentrant job shop has come into prominence as a new type of manufacturing shop. The principle characteristic of a reentrant job shop is that a job may visit certain machines more than once during the process flow, whereas in the classic job shop, each job visits a machine only once. The shifting bottleneck heuristic (SBH) is one of the most successful heuristic approaches for the classical job shop scheduling problem, which decomposes the problem into a number of single-machine subproblems. This paper adapts the SBH for the RJSSP and proposes a new sequencing heuristic for the single-machine maximum lateness subproblem considering the reentrant jobs in order to handle large-size RJSSPs. It also uses a subproblem criticality measure that further shortens the implementation time. The proposed MSBH is tested by using instances up to 20 machines and 100 jobs, and it is illustrated that good quality solutions can be obtained in reasonable computational times. A real-life application of the MSBH is also given as a case study to evaluate its performance. [ABSTRACT FROM AUTHOR]

Due-date determination problems have gained significant attention in recent years due to the industrial focus in the just-in-time philosophy. This paper considers a machine scheduling problem where jobs should be completed at times as close as possible to their respective due dates, and hence, both earliness and tardiness should be penalized. It is assumed that earliness and tardiness (ET) penalties will not occur if a job is completed within the due window. However, ET penalties will occur if a job is completed outside the due window. The objective is to determine a schedule that minimizes sum of the earliness and tardiness of jobs. To achieve this objective, three hybrid metaheuristics are proposed. The first metaheuristic is a hybrid algorithm which combines elements from both simulated annealing (SA) as constructive heuristic search and a variable neighborhood search (VNS) as local search improvement technique. The second one presents a hybrid metaheuristic algorithm which composed of a population generation method based on an ant colony optimization (ACO) and a VNS to improve the population. Finally, a hybrid metaheuristic approach is proposed which integrates several features from ACO, SA, and VNS in a new configurable scheduling algorithm. A design of experiments approach is employed to calibrate the parameters and operators of the algorithm. Computational experiments conducting on 252 randomly generated problems compare the results with the VNS algorithm proposed previously and show that the procedure is capable of producing consistently good results. [ABSTRACT FROM AUTHOR]

Selection of the suitable material handling equipment (MHE) is a very difficult task for the manufacturing companies because of the considerable capital investment required. There are many tangible and intangible factors for choosing the suitable MHE. Multiple criteria decision making (MCDM) has been found to be a useful approach to analyze these conflicting factors. The evaluation of MHE alternatives within the frame of various subjective criteria and the weights of the criteria are usually expressed in linguistic terms. This makes fuzzy logic a more natural approach to this kind of problems. This paper proposes a combined MCDM methodology for evaluation and selection of MHE types for a company in the steel construction industry in Istanbul, Turkey. Fuzzy analytic network process (FANP) is utilized for assigning weights of the criteria for MHE selection and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) is used to determine the most proper system alternative using the criteria weights attained by FANP. The selection is based on the compatibility between MHE and production characteristics. Objective is to select the most efficient MHE considering also the cost efficiency. The study was followed by the sensitivity analyses of the results. [ABSTRACT FROM AUTHOR]

In order to compete effectively in the global market, a company must have a network of competent suppliers. To create and maintain such a network and to improve various capabilities that are necessary for the buying organization to meet its increasing competitive challenges, the buying firms may engage in supplier development. To improve the supplier capabilities, the buying organizations have to consider various supplier development factors such as supplier base, communication with suppliers, direct involvement of suppliers, etc. Their significance and the role in supplier development process are also to be considered. These factors not only affect the supplier development process but also influence each other. However, the methodologies used in supplier development literature analyze the factors independently. This paper attempts to overcome the above, by analyzing the interrelationship between the supplier development factors. The Interpretive Structural Modeling (ISM) approach has employed to develop the structural relationship among supplier development factors and also tried to define the levels of different factors based on their driver/dependence power and their mutual relationships. Finally, the ISM result is compared with empirical study and a case study. [ABSTRACT FROM AUTHOR]

5-axis milling is widely used in machining of parts with free-form surfaces and complex geometries. Although in general 5-axis milling increases the process capability, it also brings additional challenges due to complex process geometry and mechanics. In milling, cutting forces, tool deflections, and chatter vibrations may reduce part quality and productivity. By use of process simulations, the undesired results can be identified and overcome, and part quality and productivity can be increased. However, machining conditions and geometry, especially the tool–work engagement limits, are needed in process models which are used in these simulations. Due to the complexity of the process geometry and continuous variation of tool–work engagement, this information is not readily available for a complete 5-axis milling cycle. In this study, an analytical method is presented for the identification of these parameters from computer-aided manufacturing data. In this procedure, depths of cut, lead, and tilt angles, which determine the tool–workpiece engagement boundaries, are directly obtained the cutter location file analytically in a very fast manner. The proposed simulation approach is demonstrated on machining of parts with relatively complex geometries. [ABSTRACT FROM AUTHOR]

This paper presents a new formalized reasoning method for assembly sequences generation which reduces the solution space dramatically. Firstly, a polychromatic sets (PS) matrix is introduced to describe the relations between the part-match and freedom; Secondly, the polychromatic sets matrix of entirety and element are used to describe the relations between the parts and assembly constraints; assembly constraint models and connector assembly models are constructed in this phase; then, the solution method for constraint equations is given; and the reasoning algorithm of feasible sequence is presented. Finally, an application case is studied to demonstrate the effectiveness of the method. [ABSTRACT FROM AUTHOR]

Enterprise resource planning (ERP) system selection is very important for a company as it completely affects production and service methodology of enterprises. Moreover, ERP selection is getting increasingly difficult because of a large variety of ERP software solutions available. The current study aims to select the most appropriate software between two elected candidates after some analysis for the final decision by using a technique with analytic hierarchy process (AHP) support in a factory which is planning to use ERP software that fits its functions. [ABSTRACT FROM AUTHOR]

In flow-shop manufacturing scheduling systems, managers attempt to minimize makespan and manufacturing costs. Job overlaps are typically unavoidable in real-life applications as overlapping production shortens operation throughput times and reduces work-in-process inventories. This study presents an ant colony optimization (ACO) heuristic for establishing a simple and effective mechanism to solve the overlap manufacturing scheduling problem with various ready times and a sequentially dependent setup time. In the proposed approach, the scheduling mechanism and ACO heuristics are developed separately, thereby improving the performance of overlapping manufacturing flow by varying parameters or settings within the ACO heuristics and allowing for flexible application of manufacturing by altering scheduling criteria. Finally, the experimental results of the scheduling problem demonstrate that the ACO heuristics have good performance when searching for answers. [ABSTRACT FROM AUTHOR]

This paper presents a STEP AP203–214-based machinable volume identifier (MVI) to identify the finish-cut machinable volume in prismatic parts by deducting the rough-machined part from the final part. The MVI provides an intermediate link between rough and finish machining computer-aided process planning system for automatic generation of process plans while machining prismatic parts. To calculate the machinable volumes of manufacturing features, the MVI utilizes the output of the feature identifier which contains the information about the dimensional details, edge loops, edges, vertices, coordinate points, and location planes of the features. In this research, a total of 234 features have been considered; out of which, 32 are normal and 202 are tapered. To calculate the machinable volumes for these features, generalized methodologies are developed for 17 basic feature types, each having a varying number of specific features. Initially, the pattern strings are generated for the front and back face of the rough-machined feature and final feature. Then, MVI uses the predefined syntactic pattern strings stored in the strings database and checks with the generated strings of the feature to determine the shape of the machinable volume stored in the volumes database. After determining the shape, one relevant methodology or more (for features having combination of more than one taper) are selected from among the 17 “feature type” specific methodologies developed for finish-cut machinable volume identification. In this article, methodology is presented for one basic feature type which covers 14 features and explained through one case study. The final output from this module is stored as a text file with full dimensional details of machinable volumes for later use inside the machining planning module. The proposed MVI can be used in Computer Integrated Manufacturing Industries as an intermediate linker to achieve a robust manufacturing environment. [ABSTRACT FROM AUTHOR]

This paper is the first of two which present a methodology for determining the dimensional specifications of all the component parts and sub-assemblies of a product according to their dimensional requirements. To achieve this goal, two major steps are followed, each of which is described in a paper. In the first paper, all relationships necessary for finding the values of dimensions and tolerances are represented in a matrix form, known as a Dimensional Requirements/Dimensions (DR/D) matrix. In the second paper, the values of individual dimensions and tolerances are determined by applying a comprehensive solution strategy to satisfy all the relationships represented in the DR/D matrix. The methodology is interactive and suitable for use in a concurrent engineering (CE) environment. The graphical tool presented in this paper will assist a CE team in visualizing the overall D&T problem and foreseeing the ramifications of decisions regarding the selection of dimensions and tolerances. This will assist the CE team to systematically determine all the controllable variables, such as dimensions, tolerances, and manufacturing processes. [ABSTRACT FROM AUTHOR]

Conventional threading operations involve two distinct machining processes: drilling and threading. Therefore, it is time consuming for the tools must be changed and the workpiece has to be moved to another machine. This paper presents an analysis of the combined process (drilling followed by threading) using a single tool for both operations: the tap-milling tool. Before presenting the methodology used to evaluate this hybrid tool, the ODS (operating deflection shapes) basics is shortly described. ODS and finite element modeling (FEM) were used during this research to optimize the process aiming to achieve higher stable machining conditions and increasing the tool life. Both methods allowed the determination of the natural frequencies and displacements of the machining center and optimize the workpiece fixture system. The results showed that there is an excellent correlation between the dynamic stability of the machining center-tool holder and the tool life, avoiding a tool premature catastrophic failure. Nevertheless, evidence showed that the tool is very sensitive to work conditions. Undoubtedly, the use of ODS and FEM eliminate empiric decisions concerning the optimization of machining conditions and increase drastically the tool life. After the ODS and FEM studies, it was possible to optimize the process and work material fixture system and machine more than 30,000 threaded holes without reaching the tool life limit and catastrophic fail. [ABSTRACT FROM AUTHOR]

Dimensioning and tolerancing (D&T) is a multidisciplinary problem which requires the fulfillment of a large number of dimensional requirements. However, almost all of the currently available D&T tools are only intended for use by the designer. In addition, they typically provide solutions for the requirements one at time. This paper presents a methodology for determining the dimensional specifications of the component parts and sub-assemblies of a product by satisfying all of its requirements. The comprehensive solution strategy presented here includes: a strategy for separating D&T problems into groups, the determination of an optimum solution order for coupled functional equations, a generic tolerance allocation strategy, and strategies for solving different types of D&T problems. A number of commonly used cost minimization strategies, such as the use of standard parts, preferred sizes, preferred fits, and preferred tolerances, have also been incorporated into the proposed methodology. The methodology is interactive and intended for use in a concurrent engineering environment by members of a product development team. [ABSTRACT FROM AUTHOR]

To overcome deficiency in the global capacity of a single dispatching rule, it is vital to select a dispatching rule in real time for dynamic scheduling. Among the studies addressing the method for selecting dispatching rules, few have no requirements for domain knowledge or accurate training example, which is hard to acquire from the real production system. In this paper, a new learning algorithm, along with the presentation of an adaptive scheduling control policy, is proposed to obtain the dynamic scheduling knowledge effectively, and different dispatching rules are selected to schedule the jobs in the machine buffer according to the current transient state of the system. Case studies are given to illustrate the validity of the scheduling control policy. [ABSTRACT FROM AUTHOR]

Multi-response optimisation has become an increasingly important issue in complex industrial processes, particularly in situations where more than one correlated responses must be assessed simultaneously. This study discusses the optimisation of a multi-response thermosonic copper wire-bonding process, used in the semiconductor assembly industry. Since nine process parameters were adopted as control factors for this experiment, the design of the experiment was based on the Taguchi method as per L12 orthogonal array. Three responses, assumed to be correlated, were considered for each experimental trial. In order to take into account correlations among responses, a specific method for analysis was used, drawing on multi-criterion methodology based on Taguchi’s quality loss function, principal component analysis and grey relational analysis. Finally, experimental confirmation was carried out to identify effectiveness of the method. It has been shown that the generic approach in the analysis for correlated responses provides better results than traditional method of analysis, in terms of optimal parameter design that meets the specifications of all three responses, for the observed process optimisation. [ABSTRACT FROM AUTHOR]

In computer-aided manufacturing domain, the selection of cutters significantly affects the machining time. However, it is difficult for humans to determine the optimal or near-optimal set of cutting tools, in particular for complex parts with multiple features. Traditionally, every feature is machined one-by-one, and no cutter sharing is taken into consideration. To perform machining operations efficiently, both the number and size of cutters should be selected carefully. Therefore, this paper proposes a new approach to determine optimal cutting tool sequences for machining multiple features in a single setup, which has been implemented and integrated with a feature-based process planning system for the generation of a numeric control code. To seek a general approach to compute the coverable area of each cutter for machining arbitrary region shapes in the case of multiple cutters combination, a new algorithm is introduced by improving the scan line-based polygon filling algorithm. To do so, the features with the nonpolygon profiles have to be approximated as polygons according to the requirement of the tolerance. The proposed method has been verified by experiments. [ABSTRACT FROM AUTHOR]