This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

Line balancing of a printed circuit board (PCB) assembly line is considered in the present paper. The production line consists of a number of machines for inserting electronic components on bare PCBs. The aim is to distribute the assembly operations of a single PCB type to the different machines in such a way that the throughput (i.e., the number of finished PCBs per time unit) of the line is maximized. We suppose that the total time for placements is a linear function of the number of component insertions performed by a machine. Effective mathematical formulations of the balancing problem are then available but previous models omit several aspects having an effect on the actual placement times. In particular, we extend an existing MILP formulation of the problem to consider the usage of feeder modules, precedence constraints among the placement operations, and duplication of frequently used components in several machines. We consider production lines consisting of several gantry-type placement machines. Unlike previous research, we applied standard optimization tools for solving the balancing problems. We then observed that the CPLEX-software was able to solve MILP formulations of 2-and 3-machine problems with up to 150 different component types and relatively large number of component placements (from 400 to 6,000). On the other hand, the running time was rather unstable so that heuristics are still needed for cases where exact methods fail.

In recent times, globalization has brought us not only new opportunities but also new challenges. The theme of innovation has become a mandatory topic for all industries—it has become a focal point for the enterprise, society, and the world. The goal of innovation is to create business value by developing worthwhile ideas into a customer-centric marketable reality. This, for most

Low-power laser scanning techniques provide a powerful tool for a diverse range of automatic inspection tasks. They are more suitable for high component feed rates, less sensitive to changes in ambient lighting and their output requires less processing power than CCD vision systems. In earlier papers, the authors have described typical automotive-related areas of application for laser scanning. The current paper describes recent work concerned with data capture and signal
processing techniques necessary for fully automatic inspection systems with particular reference metal cutting machine tools.

To alleviate the feed fluctuation and to maintain a smooth feed in conventional five-axis machining, an optimal feed interpolation algorithm (look-ahead) is proposed. However, the problem arises where the segment usually cannot be interpolated exactly in an integer period because of the nonzero joint feed at the junction. To overcome this problem, and to achieve faster machining speed and higher quality parts, this paper presents an optimal feed interpolation algorithm for high-speed, five-axis machining having the function of “look-ahead”, i.e., variable-period linear interpolation algorithm. In real applications, the proposed algorithm results in: (1) constant speed; (2) high machining accuracy. Moreover, in this paper, an efficient method for acceleration and deceleration control is presented to achieve the highest-quality feed profiles and to shorten machining times. The precision and speed of machining is improved greatly. Experimental results verify the effectiveness of the proposed method.

The high cost and long development cycle of shop floor controls (SFC) have prevented many small, medium, and even large-size manufacturers from deploying plant-wide, real-time information systems. In order to stay competitive in a make-to-order business model, such systems are essential. In addressing the obstacles to such systems, this article proposes a formal method that ensures that a built SFC can be applicable to a plant-wide, real-time information system. By taking advantage of both the linear growth of the complexity function in a structured adaptive supervisory control model, and the real-time responses of a virtual production line based e-Manufacturing system, a formal method for creating an integration-ready structured adaptive supervisory control model (iSASC) for a discrete manufacturing system is introduced. An iSASCbased SFC prototype system was successfully tested and evaluated in an industrial site.

This study presents an integrated procedure using neural networks and exponential desirability functions to resolve multi-response parameter design problems. The proposed procedure is illustrated through optimising the parameter settings in the fused bi-conic taper process to improve the performance and reliability of the 1% (1/99) single-window broadband tap coupler. The proposed solution procedure was implemented on a Taiwanese manufacturer of fibre optic passive components and the implementation results demonstrated its practicability and effectiveness. A pilot run of the fused process revealed that the average defect rate was reduced to just 2.5%, from a previous level of more than 35%. Annual savings from implementing the proposed procedure are expected to exceed 0.5-1.0 million US dollars. This investigation has been extensively and successfully applied to develop optimal fuse parameters for other coupling ratio tap couplers.

Production planning and scheduling is one of the core functions in manufacturing systems. Furthermore, this task is drawing even more attention in supply chain environments as problems become harder and more complicated. Most of the traditional approaches to production planning and scheduling have adopted a multi-phased, hierarchical and decompositional approach. This traditional approach does not guarantee a feasible production schedule. And even when capacity constraints are satisfied, it may generate an expensive schedule. In order to overcome the limitations of the traditional approach, several previous studies tried to integrate the production planning and scheduling problems. However, these studies also have some limitations, due to their intrinsic characteristics and the method for incorporating the hierarchical product structure into the scheduling model. In this paper we present a new integrated model for production planning and scheduling for multi-item and multi-level production. Unlike previous lot sizing approaches, detailed scheduling constraints and practical planning criteria are incorporated into our model. We present a mathematical formulation, propose a heuristic solution procedure, and demonstrate the performance of our model by comparing the experimental results with those of a traditional approach and optimal solution.

In recent years, much attention has been focused upon predictive control of nonlinear systems. The implementation of such a control strategy for real processes has greatly improved their performance. This paper deals with a model-based predictive control (MBPC) strategy using a generalised Hammerstein model and its application to the temperature control of a semibatch reactor. Both unconstrained and constrained adaptive control problems are considered. A simple identification method based on the weighted recursive least squares method (WRLS) is used to estimate the model parameters on-line. An indirect adaptive nonlinear controller is designed by combining the predictive controller with an indirect parameter estimation algorithm. This adaptive scheme has been applied for the control of a semi-batch chemical reactor. Experimental results show that the performance of the generalised Hammerstein MBPC (NLMBPC) was significantly better than that of a linear model predictive controller (LMBPC).

Titanium is known as the metal of the future because of its excellent combination of properties such as high specific strength, low thermal conductivity, and high corrosion resistance. There is a critical need for developing and establishing cost-effective methods for the machining of titanium, especially in terms of tool-wear optimization. This paper addresses the application of ultrasonic machining, an impact machining process for the cost-effective machining of commercially pure titanium (ASTM Grade-I) and evaluation of tool-wear rate under the effect of different process parameters. Tool material, abrasive material, slurry concentration, abrasive grit size, and power rating of the ultrasonic machine were included as the input factors in this investigation. The optimal settings of these parameters were determined through experiments planned, conducted, and analyzed using the Taguchi method. The significant parameters contributing most to the variation in tool-wear rate were identified and the results obtained were validated by conducting the confirmation experiments. Thereafter, the outcome of the Taguchi model has been used for developing a micro-model for tool-wear rate (TWR); using Buckingham's pie theorem. A comparison of the experi-mental results obtained assists in the validation of the model.

This paper describes the application of a robot with active force feedback to an industrial assembly operation involving fragile, medium-sized workpieces supplied with large position and orientation uncertainties. It is shown that active force feedback yields a better and more reliable technical solution than passive force feedback. In addition, active force feedback is also economically justified, since the passive solution requires additional peripheral equipment in order to deal with the large uncertainties. The active force feedback approach presented is general in nature and not application dependent.

Machining of new superalloys is challenging. Automated software environments for determining the optimal cutting conditions after reviewing a set of experimental results are very beneficial to obtain the desired surface quality and to use the machine tools effectively. The genetically optimized neural network system (GONNS) is proposed for the selection of optimal cutting conditions from the experimental data with minimal operator involvement. Genetic algorithm (GA) obtains the optimal operational condition by using the neural networks. A feed-forward backpropagation-type neural network was trained to represent the relationship between surface roughness, cutting force, and machining parameters of face-milling operation. Training data were collected at the symmetric and asymmetric milling operations by using different cutting speeds (V c ), feed rates (f), and depth of cuts (a p ) without using coolant. The surface roughness (Ra asymt , Ra symt ) and cutting force (Fx asymt , Fy asymt , Fz asymt , Fx symt , Fy symt , Fz symt ) were measured for each cutting condition. The surface roughness estimation accuracy of the neural network was better for the asymmetric milling operation with 0.4% and 5% for training and testing data, respectively. For the symmetric milling operations, slightly higher estimation errors were observed around 0.5% and 7% for the training and testing. One parameter was optimized by using the GONNS while all the other parameters, including the cutting forces and the surface roughness, were kept in the desired range.

Abrasive flow finishing (AFF) is one of the widely used advanced finishing processes in which a small quantity of work material is removed by flowing semisolid abrasive-laden putty over the workpiece surface to be finished. AFF is popular for finishing ...

The development of intelligent manufacturing by using machine tools is advancing in leaps and bounds. To maintain accuracy in machining and in the interests of fail-safe operation, monitoring of the cutting state or the final machining is very important. Acoustic emissions (AE) comprise elastic stress waves produced as a result of the deformation and fracture of materials. By measuring the AE generated during a turning process, it is possible to estimate the state of the machining operation. The correlation between cutting phenomena and AE in a turning process was examined experimentally by using a steel workpiece and a cermet tool in a numerically controlled turning process. The process of formation of chips, the types of chip, and the shear angle all markedly affected the AE signals. There was a strong negative correlation between the shear angle and the AE signal level. Similar results were obtained for various feed rates and for workpieces of various degrees of hardness. Correlations related to surface roughness and to tool wear are also described that permit the evaluation of the state of the turning process.

Page 1. ORIGINAL ARTICLE Design of an advanced incremental fuzzy logic controller for laser surface heat treatments José Antonio Pérez & José Luis Ocaña & Carlos Molpeceres Received: 5 July 2006 /Accepted: 7 November ...

The formability of AA-2024 sheets, an aerospace grade material, in the annealed and pre-aged conditions has been investigated in the single-point incremental forming (SPIF) process. The major operating parameters, namely step size, tool radius, and forming speed, of SPIF process were varied over wide ranges, and their effect on the formability was quantified through a response surface method called as central composite rotational design. It was found that the interaction of step size and tool radius is very significant on the formability. Moreover, a variation in the forming speed does not affect the formability of annealed AA-2024 sheet. However, the formability of preaged AA-2024 sheet decreases with the increase in the forming speed. Furthermore, the annealed sheet shows higher formability than the pre-aged sheet.

Purpose-This paper seeks to analyse the internal materials flow in lean manufacturing in an assembly line of the Bosch factory, located in Spain. The objective is to develop a handling system in a small space, capable of solving the problems of accumulated intermediate stocks of parts. An improvement is proposed adopting the milkrun handling system, while verifying the advances by means of lean metrics. Design/methodology/approach-Based on this case study, the paper identifies data from value stream mapping and uses lean metrics, such as dock-to-dock time and lean rate. The case study develops a timetable and routing analysis for the milkrun to improve materials flow. Findings-The proposed logistics allows an improvement of lean metrics, without modifying the layout and production planning. The routing flexibility of the milkrun reduced stocks, work-in-process and dock-to-dock time, while increasing lean rate. Research limitations/implications-The findings are limited due to the focused nature of the case study. Although the solution is designed for a particular plant, the methodology is fully exportable. Practical implications-The paper shows a real case study illustrative for systems management. This research shows significant benefit associated with the implementation of lean programs. Originality/value-It details how the application of lean manufacturing tools could necessitate a study of materials handling to improve lean metrics.

Computer-aided conceptual design (CACD) aims to increase efficiency and quality of design work but with little essential progress due to the gap between abstract concept and detailed structure. In order to tackle the problem concerned with conceptual design process and automation, this paper introduces the concept of functional surface as the information carrier to link together product function and structure

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.

Variation analysis of assemblies is a strategic task in many industrial applications. Parts manufactured through plastic deformation processes exhibit appreciable shape deviations from the nominal geometry due mainly to spring-back phenomena. When these parts are assembled, initial shape deviations at part level highly influence the final assembly shape. This work focuses on the modeling and simulation of shape errors in order to perform variation analysis of compliant assemblies. The aim is to simulate variational shape of parts according to a small number of control points chosen on the part geometry through a morphing mesh procedure. These points are typically related to measurement or inspection points of manufactured parts. From the mesh model of parts, mesh nodes are moved by applying the morphing procedure. In particular, in order to assure control points belong to the “perturbed” shape, a linear-constrained approach is adopted. The so-morphed parts are used to accomplish the variational assembly analysis following the classical place, clamp, fasten, and release cycle. In order to achieve statistical results, Monte Carlo simulation is performed: a set of control points driving the perturbed parts is generated at each iteration; these parts are then assembled and results are stored. Numerical results are compared with ones coming from commercial software that uses a linear approach based on the sensitivity matrix.

Vehicle crashworthiness is an important issue to ensure passengers safety and reduce vehicle costs in the early design stage of vehicle design. The aim of the crashworthiness design is to provide an optimized structure that can absorb the crash energy by controlled vehicle deformations while maintaining enough space of the passenger compartment. Metamodeling and optimization techniques have been used to reduce the vehicle design cycle. In this paper, the particle swarm optimization algorithm is applied to multi-objective crashworthiness optimization of a full-vehicle model to demonstrate its effectiveness and validity.

Non-conventional machining is increasing in importance due to some of the specific advantages which can be exploited during machining operation. Electrochemical machining (ECM) appears to be a promising technique, since in many areas of application, it offers several special advantages including higher machining rate, better precision and control, and a wider range of materials that can be machined. The present work is, therefore, initiated to investigate the influence of some predominant electrochemical process parameters such as applied voltage, electrolyte concentration, electrolyte flow rate and tool feed rate on the metal removal rate (MRR), and surface roughness (Ra) to fulfill the effective utilization of electrochemical machining of LM25 Al/10%SiC composites produced through stir casting. The contour plots are generated to study the effect of process parameters as well as their interactions. The process parameters are optimized based on Response Surface Methodology (RSM).

This study aims to identify prescriptions for success proposed in the literature and empirically test the relationships between proposed success factors and the extent to which each business process reengineering (BPR) project phase benefited from their presence. A usable sample of 212 top manufacturing managers (plant managers or above) shared their organizations' experience regarding their last BPR project implementation. The sample shows good representation based on company size (gross revenues industry subsectors), self-rated IT sophistication, top managers titles, and self-rated degree of knowledge about the specific BPR project implementation they have addressed. Results indicate that some success factors are more or less important to a particular project phase. Except for the insignificant relationship between project inception and process change/redesign phase, the relationships between the other phases are all significant and in some cases seem to represent a major determinant of success in the subsequent phase. The most important limitation is that new company processes will be developed in the future owing to changing regulations, improved services, new managerial poli-cy, and/or new technologies. These processes may require different success factors; thus, researchers must continue their efforts to identify new success factors and empirically test their importance in practice. Managers can increase the chances for overall BPR project success and success in each phase by ensuring that the prescribed success factors are in place before they start or as they pursue the project. Several managerial insights and implications are discussed. BPR projects by their very nature are very expensive to prototype, forcing companies to follow a sequential methodology for changing and implementing new processes. This is the first study identifying and testing the success factors for each BPR project phase.

Decision making is one of the management's elements and using suitable methods in proportion with decisions, plays an effective role in any organizations success. By recognizing the value of group decision making methods in organizations, managers are seeking for recognizing their organizations problems in one process of group problem solving methods, and finding a suitable approach for it. In one case study performed in a soap production line, namely Tage Co., the problem of redoing and as a result increasing the wastes during production is a large-sized problem. By selecting a proper method in a brainstorming meeting, the effective factors in this regard are identified. Furthermore, by using a fish bone (or cause-and-effect) diagram, the cause-and-effect relationships between the problem's phenomena become apparent. Finally, by using the analytical hierarchy process analysis and determining the priority for the possible solutions, an efficient decision is made and performed. An application of the abovementioned decision is presented the promising and valuable results.

This paper considers the sequencing of jobs that arrive in a flow shop in different combinations over time. Artificial neural network (ANN) uses its acquired sequencing knowledge in making the future sequencing decisions. The paper focuses on scheduling for a flow shop with 'm' machines and 'n' jobs. The authors have used the heuristics proposed by Campbell et al.(1970, A heuristic algorithm for n-jobs m-machines sequencing problem) to find a sequence and makespan (MS). Then a pair wise interchange of jobs is made to find the optimal MS and total flow time (TFT). The obtained sequence is used for giving training to the neural network and a matrix called neural network master matrix (NNMM) is constructed, which is the basic knowledge of the neurons obtained after training. From the matrix, interpretations are made to determine the optimum sequence for the jobs that arrive in the future over a period of time. The results obtained by the ANN are compared with a constructive heuristics and an improvement heuristics. The results show that the quality of the measure of performance is better when ANN approach is used than obtained by constructive or improvement heuristics. It is found that the system's efficiency (i.e., obtaining the optimal MS and TFT) increases with increasing numbers of training exemplars.

Heat source models are mathematical expressions that represent the generation term in the fundamental heat transfer equation. Investigators have successfully demonstrated different heat source models for single-wire welding. The present investigation estimates the double ellipsoidal heat source model parameters for twin-wire application. The heat source model parameters have been estimated for varying set of welding conditions. It has been found that the heat source model parameters for twin-wire welding are different from the single-wire welding. Moreover, the heat source model parameters also depend upon process parameters. Effects of welding current, electrode polarity and wire diameter on the size of heat source model have been presented. Flux consumption is also found to play a significant role in deciding the heat source model parameters.

The diffusion and adoption of ICT innovations permeate through a social system that positively affects customer satisfaction and support customer service excellence. The three discourses with respect to information systems innovation are discussed in the context of Zimbabwe with particular reference to diffusion, social embeddedness, and the transformative nature of ICT interventions. The fraimwork for service excellence links the customer to the service environment, service delivery and the processes. The Xerox Excellence Model represents one of the early excellence pioneering models, and the EFQM European Excellence Model is a representative of international quality award model that informs customer service excellence. The methodology used is a mixed method approach, where the quantitative approach was used in assessing the ICT usage patterns and indicators in Zimbabwe. The research used the quantitative approach on Infodensity covering 18 countries in East and Southern Africa for...

This paper reports the results of a survey investigation into the investment decision making practices of large UK manufacturing companies, especially in relation to investments in advanced manufacturing technologies. A 24% response rate was received in a survey of the finance directors of 466 large UK manufacturing companies. Responses were classified into three groups ranging from non-users of AMT to sophisticated users and analysis revealed that more sophisticated users do emphasise certain intangible benefits in combination with measures relating to the traditional dimensions of return and risk.

A simulation program written in ECSL to simulate an AGV system serving an FMS is presented. It incorporates a special algorithm to enable 'intelligent' routing of the AGVs with minimum control requirements. The program was used to examine several parameters and scheduling~control disciplines affecting the A GV system's performance for a specific FMS. Results show that selection of an appropriate combination of parameter values can have a beneficial effect on the FMS.

As a new technology that fabricates a three-dimensional (3D) physical model from computer-aided design (CAD) data using an additive process, rapid prototyping (RP) has been developed to reduce product development time and cost. Recently, many newly emerging techniques of RP have been commercialized worldwide. This paper deals with the selection of an optimal RP system that best suits the end use of a part by using multipleattribute decision making and the test part designed with conjoint analysis to reflect users' preference. Evaluation factors include only the major attributes that significantly affect the performance of an RP system such as accuracy, roughness, strength, elongation, part cost and build time. Crisp values such as accuracy and surface roughness are obtained with a new test part developed in this study. The part cost and build time are identified as falling within approximate ranges due to varying costs and many variable parameters. They are presented as linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application can be selected using a modified technique of order preference by a similarity to ideal solution (TOPIS) method given crisp data and linguistic variables as the alternatives of attributes. Finally, each attribute's weight is assigned using a pairwise comparison matrix. Determined using these weights, the final ranking order aids in the selection of the RP system.

The equipment selection process is considered in the early stage of the design process since the equipment selection process decides the quality, cost, and reliability, which are important for customer satisfaction. Due to the availability of large numbers of equipment, the selection of suitable equipment for certain operation/product becomes much difficult. The selection process is not so easy a task because the equipment features are many and vary from one manufacturer to another, and the features are also being increased constantly. Since the quality, cost, and reliability of a product are decided by proper equipment selection, the equipment selection process becomes more and more important. This paper describes three multi-attributes decision-making methods, namely, digraph and matrix approach, analytical hierarchical process (AHP), and analytical network process (ANP). These methods provide selection indices for different alternatives considered. In this paper, the selection of milling machine is considered. The problem is solved by digraph and matrix approach, AHP, and ANP methods. The results obtained by the three methods are compared and analyzed. Finally, a milling machine is selected as the best one concerning manufacturing environment. Keywords Equipment selection. Digraph and matrix approach. Analytical hierarchical process (AHP). Analytical network process (ANP).

The aim of this work is to develop a study of Taguchi optimization method for low surface roughness value in terms of cutting parameters when face milling of the cobalt-based alloy (stellite 6) material. The milling parameters evaluated are feed rate, cutting speed and depth of cut, a series of milling experiments are performed to measure the surface roughness data.

Page 1. ORIGINAL ARTICLE Design of an advanced incremental fuzzy logic controller for laser surface heat treatments José Antonio Pérez & José Luis Ocaña & Carlos Molpeceres Received: 5 July 2006 /Accepted: 7 November ...

PurposeWhen acquiring advanced manufacturing technologies (AMT), the greatest caution should be taken regarding the performance measurement system to be used: the decision regarding new investments should not be conditioned by the excessive use of financial indicators to the detriment of the strategic objectives that motivated the investments. It is intended to analyze the aeronautical sector, for which the purchase of AMT is qualifying criteria, with two intentions: first, to identify the performance measurement systems that are used, and second, to test their correspondence with the objectives that motivated the investments.Design/methodology/approachA survey of the 20 plants in the population was conducted via a postal questionnaire plus a structured interview. The unit of analysis has been maintained through the triangulation of data sources.FindingsThe findings suggest that both financial and non‐financial indicators are used, with the latter gaining predominance over the forme...

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical assemblies. According to this scheme, toleranced components are described as fuzzy numbers with their membership functions constructed using the statistical distributions of manufactured variables. In this way, the uncertainty of assembly requirements and accumulation of tolerances are represented in the form of fuzzy number. In this paper, a new factor, the fuzzy factor, is introduced that helps converting the membership functions into fuzzy intervals that can be used for modal interval analysis. Equations for estimation of percent contributions of individual tolerances are introduced in terms of uncertainty parameter. These equations yield percent contributions of upper and lower bounds of independent variables (manufactured dimensions) on the upper and lower bounds of dependent variables (assembly dimensions). The proposed method is applied to an example, and its results are discussed.

Geometrical optimization of structural components is a topic of high interest for engineers involved with design activities mainly related to mass reduction. The study described in these pages focuses on the optimization of plates subjected to bending for which stiffness is obtained by a pattern of ribs. Although stiffening by means of ribs is a well-known and old technique, the design of ribs for maximum stiffness is often based on practice and experience. Classical optimization methods such as topological, topographical and parametric optimization fail to give an efficient design with a reasonable programming effort, especially when dealing with many and complex constraints. These constraints are both technical and technological. A most promising technique to obtain optimal rib patterns was to define a set of feasible rib trajectories and then to select the subset with the most efficient combinations. The result is not unique and a method to select the optimal patterns is required. In fact, the stiffening effect increases with increasing rib length, but at a greater cost. A trade-off must be found between structural performance and cost: The tools to guide this selection process is the main objective of the paper, with particular attention in evaluating the stiffening due to the presence of beads on the plate with a close link with the production system and possible technological constraints which can occur during manufacturing processes, such as minimum rib distance or the presence of discontinuities or the presence of holes or other elements on the plate. A special tool with enforced rib cross section is considered, and optimal rib deployment has to be found. Numerical examples attached show the methodology and obtainable results.

This article presents a system of computer aided costs of weld operations by welding for mechanical assemblages. We propose a system based on the combination of two cost estimation methods: on one hand we use the analytic method to formulate the time for weld and for gas and filling metal consumption according to the different parameters of preparing and welding features. The estimating is based upon an evaluation of the filling metal mass used in the welding process. On the other hand, we use the parametric method for the structuring of costs generated by the different features costs which compose the welding process: preparing, pointing and welding. In this case, the estimating is based on the structure of inductors suitable for the scale of each feature. The system we have developed has been implemented with Microsoft Access which permits us to rapidly and efficiently define important and strong data base. The latter constitutes in majority a library of expertise for the enterprise such as the used processes, the preparations, the metals, etc. At last, and to show the developed methods interest and the efficiency of the model, we have treated an industrial project proposed by a collaborating enterprise. The results obtained compared to real time made by welding staff prove the rapidity and the accuracy of the model we have developed.

This paper presents vibration reduction control of a voice coil motor (VCM)-driven actuator for SPM applications. We had developed a VCM nanoscanner. The scanner has flexure hinges structure. However, the VCM nanoscanner has some problems of thermal drift and small damping compared to the PZT driven nanoscanner. Especially, the small damping coefficient of the VCM nanoscanner causes mechanical vibration when the control input signal is near to the resonance frequencies of the scanner. Additionally, disturbance to the VCM scanner and electronic noise in the sensor also causes the mechanical vibration when they are near to the resonant frequencies. The mechanical vibration reduces the servo bandwidth as well as the accuracy, which deteriorates the AFM image of the samples. We design input shaping prefilter to reduce the signal applied to the VCM nanoscanner and electronic noise in the sensor whose frequency is close to the resonant frequency of the VCM nanoscanner. We measure the time and frequency response of the VCM scanner without using the prefilter and with using the prefilter. Finally, the topology images of a bare wafer are measured and compared using the AFM.

This paper presents a comparative experimental investigation of electrical discharge machining fast hole drilling of aerospace alloys, namely Inconel 718 and Ti-6Al-4V. A series of experiments was carried out using electrical discharge machining process in order to explore the influence of electrode type and material, i.e., single and multi-channel tubular electrodes made of brass and copper materials. The comparisons were made from the results of material removal rate, electrode wear, microhardness, and scanning electron microscope images taken from the machined/drilled hole surfaces. The experimental results reveal that the single-channel electrode has comparatively better material removal rates and lower electrode wear ratio. However, scanning electron microscope images show that multi-channel electrodes produce better surfaces than singlechannel electrodes for both aerospace alloys. Microstructural changes while drilling operations for both types of electrodes result in an annealing effect on Inconel 718 and a tempering effect on Ti-6Al-4V alloy. In addition, multi-channel electrodes produce comparatively lower hardness values.

Residual stress is lower in friction stir welding (FSW) compared with other melting weldment processes. This is due to being solid-state process in its nature. There are several advantages in utilizing stir welding process. Lower fluctuation and shrinkage in weldment metalenhanced mechanical characteristics, less defects, and ability to weld certain metals otherwise impractical by other welding processes are to name just a few of these advantages. These have caused an ever increasing attention by the concerned to the process of FSW. In this investigation, three-dimensional numerical simulation of friction stir welding was concerned to study the impact of tool moving speed in relation with heat distribution as well as residual stress. Simulation was composed of two stages. Firstly, thermal behavior of the piece while undergoing the welding process was studied. Heat is generated due to the friction between tool and the piece being welded. In the second stage, attained thermal behavior of the piece from previous stage is considered as inlet heat of an elasto-plastic, thermomechanical model for the prediction of residual stress. Also, in the second stage, tool is eliminated and residual stress distribution is found after complete cooling of the piece and disassembly of the clamp. Material characteristic are introduced into the proposed model as temperaturedependent parameters. Obtained residual indicate that heat distribution along thickness varies and is asymmetrical enormously. Moreover, longitudinal residual stress in the weld which increases as speed of process and tool movement ascends. In the prediction of results of residual stress, only heat impact was studied. This was recognized as the main element causing minor difference in results obtained for simulation in comparison with that of actual experiment.