Lean philosophy: implementation in a forging company

This research addresses the implementation of lean philosophy in a forging company with a focus on radial forging production flow lines. Here, the prime motive is to evolve and test several strategies to eliminate waste on the shop floor. In this research, a systematic approach is suggested for the implementation of lean principles. This paper describes an application of value stream mapping (VSM). Consequently, the present and future states of value stream maps are constructed to improve the production process by identifying waste and its sources. Furthermore, Taguchi’s method of design of experiments is pursued here to minimize the forging defects produced due to imperfect operating conditions. A noticeable reduction in set-up time and work-in-process (WIP) inventory level is substantiated. Finally, we conclude with a discussion of managerial implications and the future scope of research.     

Prediction of spectral reflectance factor distribution of automotive paint finishes

It is necessary to determine the accurate reflectance of painted surfaces for the review of paint finishes by computer graphics (CG) before actual painting of the exterior color of automobiles, and for quality control during production and inspection processes. We have optimized a method for measuring reflectance by using a statistical technique. We have found that the reflectance of a painted surface is best measured at an incident angle of 60° and at five aspecular angles of 10°, 18°, 28°, 40°, and 90°. Our method makes it possible to accurately reproduce reflection characteristics of paint finishes containing special flake pigments, such as pearl mica. Also it was proved that our method can apply not only to solid and metallic coatings but to all painted surfaces. © 2005 Wiley Periodicals, Inc. Col Res Appl, 30, 275–282, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.20125     

Simultaneous HPLC quantification of total cholesterol,tocopherols and β-carotene in Barrosã-PDO veal

A simple, rapid and sensitive procedure for the simultaneous determination of total cholesterol, tocopherols and β-carotene in meat is described. The method involves a direct saponification of the meat, a single n-hexane extraction and the analysis of the extracted compounds by normal-phase HPLC, using fluorescence (tocopherols) and UV–Vis photodiode array (cholesterol and β-carotene) detections in tandem. Rates of recovery of spiked meat samples were 93% for cholesterol, 83–86% for (α-, β- and -γ) tocopherols and 89% for β-carotene. Repeatabilities were high (CV < 6%) for all determined compounds, except for δ-tocopherol. This tocopherol, which is not usually present in meat, showed a much lower recovery percentage (73%) and repeatability (12.8%). This methodology was applied for the quantification of total cholesterol, tocopherols and β-carotene in three muscles (longissimus thoracis, longissimus lumborum and semitendinosus) of the Portuguese traditional Barrosã-PDO veal, obtained from autochthonous calves fed extensively during summer (with the least abundant green pastures) and slaughtered in early autumn (October). Barrosã-PDO veal showed median contents of total cholesterol (0.50–0.56 mg/g) and, depending on the analysed muscle, moderate to high contents of α-tocopherol (3.3–3.9 μg/g) and β-carotene (0.07–0.09 μg/g), suggesting an high sensorial and hygienic quality.     

文本分类中训练集相关数量指标的影响研究

针对训练集对分类性能的影响,从训练集的文本数、类别数以及特征项数这三项数量指标出发进行研究。使用多因素方差分析方法及多种语料库定量探讨该三项数量指标对分类性能的影响规律。结果发现特征项数对分类性能的影响在不同的文本数和类别数时是不同的,分类性能受训练集的这三项指标的交互影响,通过对训练集的这三项指标进行优化,提出了从分类算法、特征项选择法以外提高分类性能的途径。在真实数据上的实验结果表明,该方法可有效提高分类性能。     

An investigation on the hot extrusion process of magnesium alloy sheet

This study investigates the hot extrusion of magnesium alloy sheets at various temperatures, material, speed and lubricant. A multi-speed method is applied to extrude a magnesium alloy sheet at a high extrusion ratio. The experimental results are analyzed to optimize the processing conditions, increase the tensile strength and reduce the extrusion load on the magnesium alloy thin sheet. Nowadays, most magnesium alloy products are manufactured by industrial die casting. Hot extrusion is seldom used to finish magnesium products because the extrusion speed, temperature and extrusion load significantly effect the properties of the product. In this study, the Taguchi experimental method with the orthogonal array is applied. ANOVA is used to investigate how parameters affect the extrusion process. All possible mechanical properties of the product are analyzed to obtain the optimal process parameters. In addition, magnesium alloys with different compositions are experimentally tested to determine the mechanical properties of the extruded product and obtain the relationship between the process parameters and the properties of the material.     

Optimal job sequence determination and operation machine allocation in flexible manufacturing systems: an approach using adaptive hierarchical ant colony algorithm

In this paper, an Adaptive Hierarchical Ant Colony Optimization (AHACO) has been proposed to resolve the traditional machine loading problem in Flexible Manufacturing Systems (FMS). Machine loading is one of the most important issues that is interlinked with the efficiency and utilization of FMS. The machine loading problem is formulated in order to minimize the system unbalance and maximize the throughput, considering the job sequencing, optional machines and technological constraints. The performance of proposed AHACO has been tested over a number of benchmark problems taken from the literature. Computational results indicate that the proposed algorithm is more effective and produces promising results as compared to the existing solution methodologies in the literature. The evaluation and comparison of system efficiency and system utilization justifies the supremacy of the algorithm. Further, results obtained from the proposed algorithm have been compared with well known random search algorithm viz. genetic algorithm, simulated annealing, artificial Immune system, simple ant colony optimization, tabu search etc. In addition, the algorithm has been tested over a randomly generated problem set of varying complexities; the results validate the robustness and scalability of the algorithm utilizing the concepts of ‘heuristic gap’ and ANOVA analysis.     

Investigation of machining characteristics in rotary ultrasonic machining of alumina ceramic

Alumina ceramic is well documented as a much-demanded advanced ceramic in the present competitive structure of manufacturing and industrial applications owing to its excellent and superior properties. The current article aimed to experimentally investigate the influence of several process variables, namely: spindle speed, feed rate, coolant pressure, and ultrasonic power, on considered machining characteristics of interest, i.e., chipping size and material removal rate in the rotary ultrasonic machining of alumina ceramic. Response surface methodology has been employed in the form of a central composite rotatable design to design the experiments. Variance analysis testing has also been performed with a view to observing the consequence of the considered parameters. The microstructure of machined rod samples was evaluated and analyzed using a scanning electron microscope. This analysis has revealed and confirmed the presence of plastic deformation that caused removal of material along with brittle fractures in rotary ultrasonic machining of alumina ceramic. The validity and competence of the developed mathematical model have been verified with test results. The multi-response optimization of machining responses (material removal rate and chipping size) has also been attempted by employing a desirability approach, and at an optimized parametric setting the obtained experimental values for material removal rate and chipping size were 0.4166?mm³/s and 0.5134?mm, respectively, with a combined desirability index value of 0.849.     

Exploring entrepreneurship in the academic environment

The entrepreneurial university has taken a prodigious influence globally, and studies show the expedient value of entrepreneurship in universities performing innumerable activities alongside their main objectives of teaching and research. Universities worldwide are adopting entrepreneurship teaching through creating models and methods. Collaboration of research, industry, and government entities is crucial to fulfill innovative systems in the academic environment. This study evaluates academic faculty and their impact on entrepreneurial education by focusing on their work experience, position, involvement in technical projects, international work experience, and private sector experience. Analysis of Variances (ANOVA), Least Significant Difference (LSD) assessments are conducted to support the results of our hypotheses and the variables of the entrepreneurial education impact by understanding the interpersonal aspects of faculty within academic organizations.     

Identification and optimization of key process parameters in noncontact laser scanning for reverse engineering

This Extended Technical Note shows that the final accuracy level of reverse engineered surfaces depends on scanning distance and scanning angle of the laser beam, hence it also depends on the morphology of the scanned objects. On scanning strongly curved objects, such as the ones with free form surfaces, the distance and impact angle of the laser beam are changing continuously during the scanning process. On the basis of these, two critical parameters are specified for the design model, which make it possible to predict these two factors in advance, depending on the morphology of the scanned object. First, a mathematical-statistical design model of the scanning process is generated, which relies on ANOVA (analysis of variance) and DOE (design of experiments). In the next step, a fitness function is optimized by the genetic algorithm (GA) program. This optimization improves the accuracy of the final scanned surfaces, in terms of the minimum standard deviation values of reverse engineered 3D surface model. The proposed approach was confirmed in a case study, which is presented at the end of this Technical Note.     

Studies on the Reduction of Coefficient of Variation: A Case Study

In a spinning mill, yarn is the final product. Linear density expressed in terms of count is one of the important characteristics of yarn. Because variability of textile strands increases as the linear density increases, the variability in the count is often measured in terms of coefficient of variation (CV)%. The yarn with a high CV% of count leads to a higher end breakage rate during the spinning and subsequent weaving/knitting operations, and consequently, results in lesser productivity and poorer appearance quality of the woven/knitted fabric. When this woven/knitted fabric is dyed, uneven shades are generated. Because the production of yarn involves processing of raw cotton in multimachines at multistages, possible sources that lead to a high CV% of count are many. Enrick's (1960) analysis procedure, which is based on the modification of the range method for analysis of variance, is used conventionally for detecting the stages where excessive “between-machine” differences are present. When the CV% of count is inflated due to the generation of systematic variation in any machine or introduction of high variability by any machine, this inflation remains undetected when using Enrick's procedure. The case study presented here demonstrates that a step-by-step analysis of linear densities of different stage-outputs starting from yarn to card sliver, using appropriate nested design models along with Duncan's multiple range test, is very useful in detecting all possible sources of a high CV% of count of yarn.