Tool path accuracy enhancement through geometrical error compensation

Kinematic and geometric errors of CNC machine tools, introduce large deviations in the real path traveled by the cutting tool. Tool path deviation reduces geometrical and dimensional accuracy of the machined features of the component. Tool path modification is an effective strategy to increase accuracy of the machined features. An improved error estimation model based on kinematic transformation concepts has been developed and used to calculate the volumetric overall error. These calculations are applicable for each arbitrary target positions of the machine's work space. Also a NC Program editor software has been developed in order to manage the calculations, modifications and to generate the new compensated NC program. The compensation procedure includes: fragmentation of nominal tool path to small linear elements, translating nominal position of elements to real positions using the Kinematics error model, finding compensated positions using the error compensation algorithm, converting newly generated elements to new tool paths using the packing algorithms and finally editing old NC program using NC code generator algorithm. Experimental tests showed 4-8 times accuracy improvement for linear, and S-pline tool paths deviations.     

Integrating analytical network process and fuzzy logic to prioritize the strategies - A case study for tile manufacturing firm

SWOT analysis is the most important tool for decision makers in strategic management process, because it enables the managers to discover and collect the facts that resulted from internal and external analysis. This analysis can be a good base for strategy formulation, but it is not non-defect. It includes no means of analytically determining the importance of factors or assessing the fit between SWOTS factors and decision alternatives and is mainly based on the qualitative analysis. Many researchers develop different techniques to quantify the SWOT analysis, but these methods are not comprehensive. In this study, we develop a fuzzy method model for quantitative weighing of SWOT strategies. The decision maker’s imprecise information is regarded by fuzzy numbers in this model. To consider dependency among factors and sub-factors, we use ANP technique in our research. We demonstrate our model with a case study example and compare results of our research with prior research.     

Networked control of industrial automation systems—a new predictive method

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

Optimization in measurement of MVC and active stiffness in wrist using the quick release method

The quick release method was used for measurement of Biomechanical parameters in the wrist joints. Wrist joint was previously studied in many researches for its biomechanical characteristics. However, more automation in measurement process has been discussed. In this research, a new test rig with a specified control unit was fabricated. Measurement of parameters in few seconds after the release was considered in the design of the new test rig. Based on reliability tests performed, the fabricated test rig showed firmly reliable measurements for maximum voluntary contraction, and active stiffness. These were true for both cases of left and right wrists during flexion and extension.     

An improved mixed integer linear formulation and lower bounds for minimizing makespan on a flow shop with batch processing machines

This paper considers a flow shop scheduling problem with batch processing machines. Each batch processing machine has a limited capacity and can process a group of jobs, each of them having a different known capacity requirement, simultaneously. Job processing time on each machine is known and arbitrary. The processing time of a batch on each machine is the longest processing time of all jobs in the batch. We improve the only existing mixed integer linear formulation (MILF) of the problem through significant reduction in size complexity of the model. Results justify that the improved MILF is clearly more efficient in reducing the required time for obtaining optimal makespan of small-size problems, in comparison with the existing MILF. Motivated by relaxing variety of the problem assumptions, several valid lower bounds on the optimal makespan are also proposed that can furtheraccelerate obtaining optimal solution through proposed MILF. Robustness evaluation of each bound under the different problem settings is reported through computations.     

Investigation of deep drawing concept of multi-point forming process in terms of prevalent defects

Multi-point forming is a novel flexible process that is economically suitable for both rapid prototyping and batch production of sheet metal parts. This technique is established based on altering rigid dies by matrices of adjustable punch elements. In this paper, the basic principle of this technique is implemented on deep drawing process. A reconfigurable die was constructed to investigate the multi-point deep drawing process. AA 2024-O Aluminum alloy was designated as test material. The formed specimens were evaluated in terms of dimpling defect, rupture, thickness distribution and dimensional accuracy. The onset of rupture was predicted by integrating the forming limit diagram of employed material with finite element Code. The predicted results were in a reasonable agreement with the experimental tests. It was found that for complete elimination of dimpling defect and acquiring maximum drawing depth, the proper allocation of elastic layer parameters such as thickness and hardness was crucial. The conducted investigations indicated that, in general, dimensional accuracy of formed parts was acceptable. However, for areas with sharp changes in geometry such as corners and side walls, deviation from desired geometry was evident. This phenomenon was remarkably dominant for manufactured parts utilizing softer elastic layer.     

The Effects of One and Double Heat Treatment Cycles on the Microstructure and Mechanical Properties of a Ferritic–Bainitic Dual Phase Steel

Metallurgical and Materials Transactions A - In this study, samples with ferritic–bainitic dual phase structures consisting of 62 pct bainite were obtained from the AISI 4140 steel...     

Effect of Loading History on Stress Corrosion Cracking of 7075-T651 Aluminum Alloy in Saline Aqueous Environment

An experimental study of stress corrosion cracking (SCC) was conducted on 7075-T651 aluminum alloy in a chromate-inhibited, acidic 3.5 pct sodium chloride aqueous solution using compact tension specimens with a thickness of 3.8 mm under permanent immersion conditions. The effects of loading magnitude, overload, underload, and two-step high-low sequence loading on incubation time and crack growth behavior were investigated. The results show that the SCC process consists of three stages: incubation, transient crack growth, and stable crack growth. The incubation time is highly dependent on the load level. Tensile overload or compressive underload applied prior to SCC significantly altered the initiation time of corrosion cracking. Transition from a high to a low loading magnitude resulted in a second incubation but much shorter or disappearing transient stage. The stable crack growth rate is independent of stress intensity factor in the range of 10 to 22 MPa ?{textm} . sqrt {text{m}} .     

Optimum weight design of fiber composite plates in flexure based on a two level strategy

This paper offers a method for weight optimization of multilayer fiber composite plates under the action of lateral loadings. The objective is to design a fiber composite plate of minimum thickness which can sustain multiple static loadings applied normal to its surface without exhibiting failure based on Tsai-Hill criterion in any of its layers. In this investigation, fiber orientation angles are treated as discrete variables, which can vary only by pre-assigned increments, while thicknesses of layers are treated as continuous variables. The optimization procedure is based on a two stage strategy; in the first of which only the fiber orientation angles for the layers are treated as variables, and in the second, only the layer thicknesses. A powerful criterion based on a load factor has been defined to find the best angle for a new layer in the first stage, and the method of center points has been used for thickness optimization in the second stage. After any angle and thickness optimization has been done, a new layer is added to the thickness and the procedure is repeated for other new layers. The end of the two stage procedure is signaled whenever the thickness of the new layer in the optimization process approaches zero; meaning that no new layers would improve the set of layers already found. In this way at the end of the optimization procedure the plate thickness would be made of a minimum number of layers whose fibers are optimally oriented, and whose thicknesses are minimal. A poor choice of layers in the stack produce near zero thickness for the respective layer, and are thus deleted from the set. A repeat process is performed after each cycle, to modify layer angles in order to compensate for errors due to approximations involved. The priorities exercised in the choice of new layers for inclusion in the set and exclusion of all the un-necessary ones, allow an optimal state of stacking sequence to be achieved. Several examples are given to demonstrate the operation of the algorithm.     

Automatic segmentation of digitized data for reverse engineering applications

Reverse engineering is the process of developing a Computer Aided Design (CAD)model and a manufacturing database for an existing part. This process is used in CAD modeling of part prototypes, in designing molds, and in automated inspection of parts with complex surfaces. The work reported in this paper is on the automatic segmentation of 3-Dimensional (3-D) digitized data captured by a laser scanner or a Coordinate Measuring Machine (CMM) for reverse engineering applications. Automatic surface segmentation of digitized data is achieved using a combination of region and edge based approaches. It is assumed that the part surface contains planar as well as curved surfaces that are embedded in a base surface. The part surface should be visible to a single scanning probe (21/2D object). Neural network algorithms are developed for surface segmentation and edge detection. A back propagation network is used to segment part surfaces into surface primitives which are homogenous in their intrinsic differential geometric properties. The method is based on the computation of Gaussian and mean curvatures of the surface. They are obtained by locally approximating the object surface using quadratic polynomials. The Gaussian and mean curvatures are used as input to the neural network which outputs an initial region-based segmentation in the form of a curvature sign map. An edge based segmentation is also performed using the partial derivatives of depth values. Here, the output of the Laplacian operator and the unit surface normal are computed and used as input to a Self-Organized Mapping (SOM) network. This network is used to find the edge points on the digitized data. The combination of the region based and the edge based approaches, segment the data into primitive surface regions. The uniqueness of our approach is in automatic calculation of the threshold level for segmentation, and on the adaptability of the method to various noise levels in the digitized data. The developed algorithms and sample results are described in the paper