Thermal error evaluation and modelling of a CNC cylindrical grinding machine

With the relentless quest for improved performance driving ever tighter tolerances for manufacturing, machine tools are sometimes unable to meet the desired requirements. One option to improve the tolerances of machine tools is to compensate for their errors. Among all possible sources of machine tool error, thermally induced errors are, in general for newer machines, the most important. The present work demonstrates the evaluation and modelling of the behaviour of the thermal errors of a CNC cylindrical grinding machine during its warm-up period.

Hygroexpansivity profiles on a commercial paper machine

Paper products show dimensional changes when subjected to moisture content modification. Hygroexpansivity was investigated in a commercial paper machine operating at 1256 m/min by a set of measurements on 75 g/m(2) reprographic bleached eucalyptus pulp paper samples. The present work shows hygroexpansivity development in different sections of the paper machine along the manufacturing direction. The measurement results demonstrate the effects of papermaking process operations on paper hygroexpansivity and lead to the confirmation of fiber orientation degree, drying restraint and shrinkage and paper tension as significant influencing factors. Structural, strength and elastic properties of paper were also measured as a function of machine direction position and presented for discussion purposes.

Minimizing total tardiness in a stochastic single machine scheduling problem using approximate dynamic programming

This paper addresses the non-preemptive single machine scheduling problem to minimize total tardiness. We are interested in the online version of this problem, where orders arrive at the system at random times. Jobs have to be scheduled without knowledge of what jobs will come afterwards. The processing times and the due dates become known when the order is placed. The order release date occurs only at the beginning of periodic intervals. A customized approximate dynamic programming method is introduced for this problem. The authors also present numerical experiments that assess the reliability of the new approach and show that it performs better than a myopic policy.

Influence of specimens' design and manufacturing process on microtensile bond strength to enamel: laboratory and FEA comparison

This study evaluated the effect of specimens' design and manufacturing process on microtensile bond strength, internal stress distributions (Finite Element Analysis - FEA) and specimens' integrity by means of Scanning Electron Microscopy (SEM) and Laser Scanning Confocal Microscopy (LCM). Excite was applied to flat enamel surface and a resin composite build-ups were made incrementally with 1-mm increments of Tetric Ceram. Teeth were cut using a diamond disc or a diamond wire, obtaining 0.8 mm² stick-shaped specimens, or were shaped with a Micro Specimen Former, obtaining dumbbell-shaped specimens (n = 10). Samples were randomly selected for SEM and LCM analysis. Remaining samples underwent microtensile test, and results were analyzed with ANOVA and Tukey test. FEA dumbbell-shaped model resulted in a more homogeneous stress distribution. Nonetheless, they failed under lower bond strengths (21.83 ± 5.44 MPa)c than stick-shaped specimens (sectioned with wire: 42.93 ± 4.77 MPaª; sectioned with disc: 36.62 ± 3.63 MPa b), due to geometric irregularities related to manufacturing process, as noted in microscopic analyzes. It could be concluded that stick-shaped, nontrimmed specimens, sectioned with diamond wire, are preferred for enamel specimens as they can be prepared in a less destructive, easier, and more precise way.

Adding value to the meat of spent laying hens manufacturing sausages with a healthy appeal

The aim of this study was to evaluate the viability of the use of spent laying hens' meat in the manufacturing of mortadella-type sausages with healthy appeal by using vegetable oil instead of animal fat. 120 Hy-line® layer hens were distributed in a completely randomized design into two treatments of six replicates with ten birds each. The treatments were birds from light Hy-line® W36 and semi-heavy Hy-line® Brown lines. Cold carcass, wing, breast and leg fillets yields were determined. Dry matter, protein, and lipid contents were determined in breast and leg fillets. The breast and legg fillets of three replicates per treatment were used to manufacture mortadella. After processing, sausages were evaluated for proximal composition, objective color, microbiological parameters, fatty acid profile and sensory acceptance. The meat of light and semi-heavy spent hens presented good yield and composition, allowing it to be used as raw material for the manufacture of processed products. Mortadellas were safe from microbiological point of view, and those made with semi-heavy hens fillets were redder and better accepted by consumers. Values for all sensory attributes were evaluated over score 5 (neither liked nor disliked). Both products presented high polyunsaturated fatty acid contents and good polyunsaturated to saturated fatty acid ratio. The excellent potential for the use of meat from spent layer hens of both varieties in the manufacturing of healthier mortadella-type sausage was demonstrated.

Architecture for machining process and production monitoring based in open computer numerical control

This paper proposes an architecture for machining process and production monitoring to be applied in machine tools with open Computer numerical control (CNC). A brief description of the advantages of using open CNC for machining process and production monitoring is presented with an emphasis on the CNC architecture using a personal computer (PC)-based human-machine interface. The proposed architecture uses the CNC data and sensors to gather information about the machining process and production. It allows the development of different levels of monitoring systems with mininium investment, minimum need for sensor installation, and low intrusiveness to the process. Successful examples of the utilization of this architecture in a laboratory environment are briefly described. As a Conclusion, it is shown that a wide range of monitoring solutions can be implemented in production processes using the proposed architecture.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Análise técnica e econômica de prestadores de serviços na colheita florestal

The objective of this Study was to describe the financial conditions of forestry contractors, concerning life quality aspects, condition of work and equipments, operational costs, and economic credit to invest in new technologies. Five companies had been analyzed, with an annual income between US$ 400,000.00 and US$ 1,720,000.00, with an average of US$ 950,000.00. The number of employees varied between 33 and 181, and the companies were classified in terms of size as: one small, two average, and two big. The main difficulties to invest in new machines were high financial taxes, more than 12% an year, and a lack of long term contracts to guarantee the payment capability. It was observed that the contractors did not consider the capital remuneration and a correct depreciation of machines, resulting in an average machine life higher than 10 years. The final conclusions were that the costs were above the paid values for the services, when computed the depreciation and capital remuneration, with negative results In the financial analyzes of three companies. Finally, the mechanization process increased the workers life quality, however, the annual income was around US$ 2,112.00 per worker, approximately 39% lower than the average Brazilian population.

A simulation-based evolutionary multiobjective approach to manufacturing cell formation

The purpose of this paper is to propose a multiobjective optimization approach for solving the manufacturing cell formation problem, explicitly considering the performance of this said manufacturing system. Cells are formed so as to simultaneously minimize three conflicting objectives, namely, the level of the work-in-process, the intercell moves and the total machinery investment. A genetic algorithm performs a search in the design space, in order to approximate to the Pareto optimal set. The values of the objectives for each candidate solution in a population are assigned by running a discrete-event simulation, in which the model is automatically generated according to the number of machines and their distribution among cells implied by a particular solution. The potential of this approach is evaluated via its application to an illustrative example, and a case from the relevant literature. The obtained results are analyzed and reviewed. Therefore, it is concluded that this approach is capable of generating a set of alternative manufacturing cell configurations considering the optimization of multiple performance measures, greatly improving the decision making process involved in planning and designing cellular systems. (C) 2010 Elsevier Ltd. All rights reserved.

Dynamic behavior analysis of drill-threading process when machining AISI Al-Si-Cu(4) alloy

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.

Industrial challenges in grinding

This keynote paper aims at analyzing relevant industrial demands for grinding research. The chosen focus is to understand what are the main research challenges in the extensive industrial use of the process. Since the automotive applications are the most important driving forces for grinding development, the paper starts with an analysis on the main trends in more efficient engines and the changes in their components that will affect the grinding performance. A view from 23 machine tool builders is also presented based on a survey made in interviews and during the EMO and IMTS machine tool shows. Case studies received by the STC G members were used to show how research centers and industries are collaborating. A view from the authors and the final conclusions show hot topics for future grinding research. (C) 2009 CIRP.

An efficient heuristic for total flowtime minimisation in no-wait flowshops

In this paper, we address the problem of scheduling jobs in a no-wait flowshop with the objective of minimising the total completion time. This problem is well-known for being nondeterministic polynomial-time hard, and therefore, most contributions to the topic focus on developing algorithms able to obtain good approximate solutions for the problem in a short CPU time. More specifically, there are various constructive heuristics available for the problem [such as the ones by Rajendran and Chaudhuri (Nav Res Logist 37: 695-705, 1990); Bertolissi (J Mater Process Technol 107: 459-465, 2000), Aldowaisan and Allahverdi (Omega 32: 345-352, 2004) and the Chins heuristic by Fink and Voa (Eur J Operat Res 151: 400-414, 2003)], as well as a successful local search procedure (Pilot-1-Chins). We propose a new constructive heuristic based on an analogy with the two-machine problem in order to select the candidate to be appended in the partial schedule. The myopic behaviour of the heuristic is tempered by exploring the neighbourhood of the so-obtained partial schedules. The computational results indicate that the proposed heuristic outperforms existing ones in terms of quality of the solution obtained and equals the performance of the time-consuming Pilot-1-Chins.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine`s capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine`s potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

Toxicity-directed approach of polyester manufacturing industry wastewater provides useful information for conducting treatability studies

A broader characterization of industrial wastewaters, especially in respect to hazardous compounds and their potential toxicity, is often necessary in order to determine the best practical treatment (or pretreatment) technology available to reduce the discharge of harmful pollutants to the environment or publicly owned treatment works. Using a toxicity-directed approach, this paper sets the base for a rational treatability study of polyester resin manufacturing. Relevant physical and chemical characteristics were determined. Respirometry was used for toxicity reduction evaluation after physical and chemical effluent fractionation. Of all the procedures investigated, only air stripping was significantly effective in reducing wastewater toxicity. Air stripping in pH 7 reduced toxicity in 18.2%, while in pH 11 a toxicity reduction of 62.5% was observed. Results indicated that toxicants responsible for the most significant fraction of the effluent`s instantaneous toxic effect to unadapted activated sludge were organic compounds poorly or not volatilized in acid conditions. These results led to useful directions for conducting treatability studies which will be grounded on actual effluent properties rather than empirical or based on the rare specific data on this kind of industrial wastewater. (C) 2008 Elsevier B.V. All rights reserved.