Combination Of Process Variables Research Articles

Investigation and analysis on pulsed Nd:YAG laser micro-turning process of aluminium oxide (Al2O3) ceramic at various laser defocusing conditions

Laser micro-turning process is one of the latest promising laser material processing techniques which can be employed for generation of micro-turning surface of particular surface profile and dimensional accuracy on cylindrical workpiece. The present paper addresses the laser micro-turning process of cylindrical shaped 99 % pure aluminium oxide (Al2O3) ceramics of size 10 mm in diameter and 40 mm in length. The experiments have been conducted using response surface methodology design of experiments. The targeted depth was set at 100 μm. Laser average power, pulse frequency, workpiece rotating speed, air pressure and Y feed rate were considered as process variables. After each experiment, surface roughness (Ra) and micro-turning depth deviation have been measured. Empirical models of the responses have been developed based on the test results achieved during measurements of surface roughness and machined depth deviation. Analysis of variance was conducted. Multi-objective optimal parametric combination of process variables has been obtained for achieving least values of responses, i.e. surface roughness and depth deviation. To achieve further high-quality machined surface, machining was done at various defocusing conditions of laser beam and also by varying the number of laser scan passes. Other process parameters were kept constant at optimal parametric combination obtained in multi-objective optimization. From the experimental results, it was revealed that surface roughness decreases with increase in defocusing positions. With increase in number of passes up to a certain limit, surface roughness decreases. However, depth deviation increases with number of laser scan passes at all levels of defocus planes.

Effect of thermal-alkaline processing conditions on the quality level of corn oil

The objective of this study was to determine the best combination of process variables to produce nixtamalized corn flour (NCF) with the lowest level of lipid deterioration. The nixtamalization conditions used were calcium concentrations from 0.4 to 2.56 g Ca(OH)2/L in water and steeping times of 6.34 to 17.65 h. The cooking time was 40 min at 94°C. The cooked and steeped grains were washed and milled to obtain masa which was then dehydrated and milled until the NCF was obtained. Oil was extracted by means of hexane from each sample of processed corn. The level of least oil deterioration of nixtamalized samples was based on the following response variables: saponification, acidity, peroxides, iodine values and extinction coefficient measured at 270 nm (K270). The best nixtamalization conditions for obtaining the highest oil stability were found at Ca(OH)2 lower than 0.75% and steeping times less than 12 h.

Influence of pretreatment conditions on composition of liquid hydrolysate and subsequent enzymatic saccharification of remaining solids

AbstractIn the present work, the effect of dilute acid pretreatment was studied on the composition of liquid hydrolysate obtained after pretreatment by employing different combinations of process variables (temperature, time and acid concentration). The effect of pretreatment was also studied on subsequent enzymatic saccharification of remaining solids to obtain maximum yield of sugars. The efficiency of pretreatment was measured in terms of high‐xylose and low‐glucose yields, which was found most suitable at pretreatment conditions of 120°C, 120 min and 2% (v/v) acid concentration. With increased severity of pretreatment, xylose yield decreased with concomitant increase in glucose yield. The decrease in xylose yield was attributed to conversion into degradation products such as 5‐hydroxylmethyl furfural (HMF) and acetic acid. The percentage of enzymatic saccharification increased with increased pretreatment severity. Saccharification of biomass pretreated at 180°C, 7 min and 0.5% (v/v) acid concentration produced the maximum glucose yield of saccharification of 352 g/kg dry matter, compared to just 97 g glucose/kg dry matter in the case of untreated biomass. The same pretreatment conditions resulted in maximum total sugar yield of pretreatment and saccharification of 459 g/kg dry matter, which was more than 67% of the total potential sugars in biomass. © 2012 Canadian Society for Chemical Engineering

Effects of process variables and additives on mustard oil hydrolysis by porcine pancreas lipase

Selective hydrolysis of brown mustard oil (from Brassica juncea) with regioselective porcine pancreas lipase was studied in this work. Buffer and oil phase were considered as the continuous and dispersed phases, respectively. Effects of speed of agitation, pH of the buffer phase, temperature, buffer-oil ratio and enzyme concentration on hydrolysis were observed. The best combination of process variables was: 900 rpm, pH 9, 35 oC, buffer-oil ratio of 1:1 and enzyme concentration of 10 mg/g oil. These standard conditions led to 50% hydrolysis and selective production of 55% erucic acid in 6 h. Cations like Mg2+ and Ca2+ increased hydrolysis, but Cu2+ strongly inhibited it. Organic solvents decreased hydrolysis, though the decrease was minimum for isooctane. A mixed surfactant comprising of Span 80 and Tween 80 increased erucic acid production by 57% at a buffer-oil ratio of 0.2:1.

Reconstruction-based multivariate contribution analysis for fault isolation: A branch and bound approach

Identification of faulty variables is an important component of multivariate statistical process monitoring (MSPM); it provides crucial information for further analysis of the root cause of the detected fault. The main challenge is the large number of combinations of process variables under consideration, usually resulting in a combinatorial optimization problem. This paper develops a generic reconstruction based multivariate contribution analysis (RBMCA) framework to identify the variables that are the most responsible for the fault. A branch and bound (BAB) algorithm is proposed to efficiently solve the combinatorial optimization problem. The formulation of the RBMCA does not depend on a specific model, which allows it to be applicable to any MSPM model. We demonstrate the application of the RBMCA to a specific model: the mixture of probabilistic principal component analysis (PPCA mixture) model. Finally, we illustrate the effectiveness and computational efficiency of the proposed methodology through a numerical example and the benchmark simulation of the Tennessee Eastman process.

Commercially Sterilized Mussel Meats (Mytilus chilensis): A Study on Process Yield

The processing steps most responsible for yield loss in the manufacture of canned mussel meats are the thermal treatments of precooking to remove meats from shells, and thermal processing (retorting) to render the final canned product commercially sterile for long-term shelf stability. The objective of this study was to investigate and evaluate the impact of different combinations of process variables on the ultimate drained weight in the final mussel product (Mytilu chilensis), while verifying that any differences found were statistically and economically significant. The process variables selected for this study were precooking time, brine salt concentration, and retort temperature. Results indicated 2 combinations of process variables producing the widest difference in final drained weight, designated best combination and worst combination with 35% and 29% yield, respectively. Significance of this difference was determined by employing a Bootstrap methodology, which assumes an empirical distribution of statistical error. A difference of nearly 6 percentage points in total yield was found. This represents a 20% increase in annual sales from the same quantity of raw material, in addition to increase in yield, the conditions for the best process included a retort process time 65% shorter than that for the worst process, this difference in yield could have significant economic impact, important to the mussel canning industry.

Dynamic model for CHO cell engineering

Industrial CHO cell fed-batch processes have progressed significantly over the past decade, with recombinant protein titer consistently reaching the gram per liter level. Such improvements have largely resulted from separate advances in process and cell line development. Model-based selection of targets for metabolic engineering in CHO cells is confounded by the dynamic nature of the fed-batch process. In this work, we use a dynamic model of CHO cell metabolism to simultaneously identify both process and cell modifications that improve antibody production. Model simulations explored ca. 9200 combinations of process variables (shift temperature, shift day, seed density, and harvest day) and knockdowns (8 metabolic enzymes). A comprehensive examination of a simulated solution space showed that optimal gene knockdown clearly depends on the process parameters such as temperature shift day, shift temperature, and seed density. Knockdown of enzymes related to lactate production were the most beneficial; however, depending on the process conditions, modulating such enzymes yielded varying productivities, ranging from a reduction in final titer to greater than 2-fold improvement.

Optimization of Extrusion Process for Producing High Antioxidant Instant Amaranth (<i>Amaranthus hypochondriacus</i> L.) Flour Using Response Surface Methodology

The objective of this research was to determine the best combination of extrusion process variables for the production of a high antioxidant extruded amaranth flour (EAF) suitable to elaborate a nutraceutical beverage. Extrusion operation conditions were obtained from a factorial combination of process variables: Extrusion temperature (ET, 70℃ - 130?℃) and screw speed (SS, 100 - 220 rpm). Response surface methodology was employed as optimization technique; both the numeric and graphical methods were applied to obtain maximum values for response variables [Antioxidant capacity (AoxC) and water solubility index (WSI)]. The best combination of extrusion process variables was: Extrusion tem- perature (ET) = 130℃/Screw speed (SS) = 124 rpm. The raw amaranth flour (RAF) and optimized extruded amaranth flour (EAF) had an antioxidant activity of 3475 and 3903 μmol Trolox equivalents/100 g sample (dw), respectively. A 200 mL portion of the beverage prepared with 22 g of optimized EAF contained 3.16 g proteins, 1.09 g lipids, 17.39 g carbohydrates and 92 kcal. This portion covers 25.3% and 16.9% of the daily protein requirements for children 1-3 and 4 - 8 years old, respectively. A 200 mL portion of the beverage from optimized EAF contributes with 15.5% - 25.5% of the recommended daily intake for antioxidants, respectively. The nutraceutical beverage was evaluated with an average acceptability of 8.4 (level of satisfaction between “I like it” and “I like it extremely”) and could be used for health promotion and disease prevention as an alternative to beverages with low nutritional/nutraceutical value.

Artificial Neural Network application for predicting in-flight particle characteristics of an atmospheric plasma spray process

Thermal spray consists of a group of coating processes that are used to apply metal or non-metallic coatings to protect a functional surface or to improve its performance. There are some 40 processing parameters that define the overall coating quality and these must be selected in an optimized fashion to manufacture a coating that exhibits desirable properties. The proper combination of processing variables is critical since these influence the cost as well as the coating characteristics. Because of this high number of processing parameters, a major challenge is to have full control over the system and to understand parameter interdependencies, correlations and their individual effects on the in-flight particle characteristics, which have significant influence on the in service coating properties. This paper proposes an approach, based on the Artificial Neural Network (ANN) method, to play this role and illustrates the model's design, network optimization procedures, the database handling and expansion steps, and analysis of the predicted values, with respect to the experimental ones, in order to evaluate the network's performance.

Behavior of granite-epoxy composite beams subjected to mechanical vibrations

The capacity to damp mechanical vibrations is one of the most important properties of granite-epoxy composites, even superior to the cast iron one. For this reason, these materials have been adopted for manufacturing of tool machine foundations and precision instruments. This work presents a study concerning the behavior of particulate composite beams, based on granite powder and epoxy, subjected to mechanical vibrations. Composite samples were prepared with different combinations of processing variables, like the weight fraction of epoxy in the mixture and size distributions of granite particles. The damping behavior of the material was investigated adopting the logarithmic decrement method. Samples, in the form of prismatic beams, were excited in the middle point and the output signal was measured in a point located at the extremity. The obtained results showed that composite samples, with weight fractions of about 80% of granite and 20% of epoxy, presented damping properties approximately three times greater than gray cast iron.

Minimization of sink mark defects in injection molding process – Taguchi approach

Optimal setting up of injection molding process variables plays a very important role in controlling the quality of the injection molded products. It is all the most important to control attribute defects like sink marks. Sink marks are basically a “designed in” problem and hence it is to be attended during designs stages. Owing to certain conditions and constraints, sometimes, it is rather ignored during design stages and it is expected to be handled by molders with only instruction to ‘do the best’. Handling of numerous processing variables to control defects is a mammoth task that costs time, effort and money. This paper presents a simple and efficient way to study the influence of injection molding variables on sink marks using Taguchi approach. Using the Taguchi approach, optimal parameter settings and the respective sink depth were arrived. The sink depth based on the validation trials was compared with the predicted sink depth and they are found to be in good agreement. The results demonstrate the ability of this approach to predict sink depth for various combination of processing variables with in the design space. Keywords: Sink mark, plastic injection molding, Taguchi optimization, process optimization, attribute defects in injection molding

KERNEL EXTRACTION AND MACHINE EFFICIENCY IN DEHULLING PARBOILED AFRICAN BREADFRUIT (TRECULIA AFRICANA DECNE) WHOLE SEEDS

ABSTRACT Parboiling and dehulling are two closely associated primary operations preceding African breadfruit (Treculia africana) seed kernel extraction and subsequent utilization in any food form. Three process variable conditions for parboiling the seeds (quantity of parboiled seeds, parboiling temperature and parboiling time) for dehulling and kernel extraction were investigated using a central composite design. The objectives of the research were to maximize kernel and extraction yields and dehulling and machine efficiencies through process variable combinations. Maximum kernel mass (91.33%) was obtained at the center point process combination (12 kg, 80C and 13 min, respectively). Extraction yield and total recovered wastes were 94.08 and 7.31%, while dehulling and machine efficiencies were 72.62 and 96.97%, respectively. Models developed by response surface analysis for these responses ranged from 62 to 93%. Temperature effects on kernel mass, extraction yield and total wastes were both linear and quadratic.PRACTICAL APPLICATIONSDehulling operation, to a great extent, is dependent on parboiling process conditions. This research located the optimum combination of process variables that would lead to maximum kernel yield and machine efficiency using second‐order central composite design and response surface analysis. It also reported the ability of locally fabricated power‐driven commercial attrition mill, designed for grinding cereals and grain‐legumes, to thresh and dehull parboiled African breadfruit whole seeds. Because the seeds are extracted,parboiled and dehulled before their utilization in any food form, information obtained in this research would be needful not only to processors of African breadfruit seeds, but also to those processing grain‐legumes and other seeds requiring dehulling process before conversion into any food form.

Statistical quality control through overall vibration analysis

The present study introduces the concept of statistical quality control in automotive wheel bearings manufacturing processes. Defects on products under analysis can have a direct influence on passengers’ safety and comfort. At present, the use of vibration analysis on machine tools for quality control purposes is not very extensive in manufacturing facilities. Noise and vibration are common quality problems in bearings. These failure modes likely occur under certain operating conditions and do not require high vibration amplitudes but relate to certain vibration frequencies. The vibration frequencies are affected by the type of surface problems (chattering) of ball races that are generated through grinding processes. The purpose of this paper is to identify grinding process variables that affect the quality of bearings by using statistical principles in the field of machine tools. In addition, an evaluation of the quality results of the finished parts under different combinations of process variables is assessed. This paper intends to establish the foundations to predict the quality of the products through the analysis of self-induced vibrations during the contact between the grinding wheel and the parts. To achieve this goal, the overall self-induced vibration readings under different combinations of process variables are analysed using statistical tools. The analysis of data and design of experiments follows a classical approach, considering all potential interactions between variables. The analysis of data is conducted through analysis of variance (ANOVA) for data sets that meet normality and homoscedasticity criteria. This paper utilizes different statistical tools to support the conclusions such as chi squared, Shapiro–Wilks, symmetry, Kurtosis, Cochran, Hartlett, and Hartley and Krushal–Wallis. The analysis presented is the starting point to extend the use of predictive techniques (vibration analysis) for quality control. This paper demonstrates the existence of predictive variables (high-frequency vibration displacements) that are sensible to the processes setup and the quality of the products obtained. Based on the result of this overall vibration analysis, a second paper will analyse self-induced vibration spectrums in order to define limit vibration bands, controllable every cycle or connected to permanent vibration-monitoring systems able to adjust sensible process variables identified by ANOVA, once the vibration readings exceed established quality limits.

Application of a feasible formability diagram for the effective design in stamping processes of automotive panels

The objective of this study is to propose a method of process design that uses a feasible formability diagram, which denotes the safe region without fracture and wrinkle, for the effective and rapid design of stamping processes. To determine the feasible formability diagram, FE-analyses have been performed for combinations of process variables that correspond to the orthogonal array of design of experiments. Subsequently, the characteristic values for fracture and wrinkle have been estimated from the results of FE-analyses on the basis of the forming limit diagram. The characteristic values for all combinations within a whole range of process variables have been predicted through the training of an artificial neural network. The feasible formability diagram has been finally determined for all combinations of process variables. The stamping processes of automotive panels to support suspension module, such as the turret suspension and the wheel house, have been taken as examples to verify the effectiveness of process design through feasible formability diagram. A comparison of the FE-simulation results with the experimental results reveals that the design of stamping processes through feasible formability diagram is efficient and suitable for actual processes.

Nixtamalized Instant Flour from Corn (Zea mays L.) Meal: Optimization of Nixtamalization Conditions

ABSTRACTThe present investigation provides a new method for the nixtamalization process wherein corn endosperm fractions (corn meal) are treated in an alkaline solution that yields quality masa or instant masa flour like traditional nixtamalization process (alkaline cooking of corn with lime). The objective of this work was to determine the best combination of nixtamalization process variables for producing nixtamalized instant flour (NIF) from corn meal. Nixtamalization conditions were selected from factorial combinations of process variables including nixtamalization time (NT 8–22 min) and cooking temperature (CT 78–88°C). A central composite rotable experimental design was chosen. Lime concentration was 1% (10 g of Ca(OH)2/L of water) and ratio of corn meal to cooking medium was 1:4. At the end of each cooking, each treatment was steeped for 5 hr at room temperature (25°C). Nixtamalized corn meal was dried (55°C/12 hr) and milled to pass through 80 U.S. mesh to obtain NIF. Response surface methodology (RSM) was applied as an optimization technique over four response variables: masa firmness (MF), masa adhesiveness (MA), tortilla cutting force (CF), and tortilla tensile strength (TS). Predictive models for response variables were developed as a function of process variables. Conventional graphic methods were applied to obtain response variable values similar to the control (MASECA). Contour plots of each response variable applied superposition surface methodology to obtain a contour plot for observation and for selecting the best combination of nixtamalization time (NT 15 min) and cooking temperature (CT 83°C) for producing an optimized NIF from corn meal. Values of MF, MA, CF, and TS obtained from the predictive models were compared with those derived from experimental tests; a close agreement (coefficient of variance < 10%) between both values was observed.

On A New Approach for Self-optimizing Control Structure Design

Abstract Abstract In this paper, a new method for the identification of self-optimizing control structure designs (CSDs) based on generalized singular value decomposition (GSVD) is proposed. The method is primarily dedicated to find optimal CSDs where all controlled variables (CVs) are represented by a common set of linear combinations of process variables (PVs). It is shown that the implementation of the GSVD into iterative solution approaches is beneficial in order to find CSDs where an individual PV subset is mapped to each CV. The developments will be tested on a simple process.

English

  Twenty seven combinations of process variables were developed and used to produce crude extracts of Mycoplana dimorpha. Crude extracts containing 2,4-dichlorophenol degrading enzymes, were immobilized on sodium alginate beads and degradation studies was conducted in a packed bed column. The rate of degradation of 2,4-dichlorophenol by immobilized crude extracts of was measured at different time intervals and it was found that 82 to 86% of 2,4-dichlorophenol can be decomposed with different initial concentrations in 30 min. The Km and Vmax values were determined.   Key words: 2,4-Dichlorophenol, degradation, crude extract, Mycoplana dimorpha, immobilization, packed bed column.

A modified rule of mixture for the vacuum-assisted resin transfer moulding process simulation

The vacuum-assisted resin transfer moulding process (VARTM) offers many advantages over the traditional resin transfer moulding such as lower tooling cost, room temperature processing. Computer simulation has become a powerful tool for liquid composite moulding process design and optimisation. In the VARTM process simulation, due to the presence of HPM and flow channels, the conventional simulation will require 3-D geometric model and mesh generation. The extensive computation load and complexity of pre-processing limit the usage of simulation in the process design and optimisation. In this paper, a two-step method for improving the efficiency of VARTM process simulation is presented. First, a design of experiment approach was coupled with 2-D CVFEM (control volume finite element method) simulation to calculate the equivalent permeability and porosity for various process variable combinations. Based on the data from DOE, a modified rule of mixture for calculating the equivalent permeability and porosity was developed, with which the mould filling can be simulated in 2-D. Second, the algorithm for the through-thickness flow front construction was developed. The presented method was validated by comparing the result against that from the 3-D simulation. It shows that the accuracy is within 5% while the computation time saving is over 99%.

A practical approach to optimize the coating parameters to win customer confidence

An investigation is carried out to find the near-optimum parametric combination of process variables in zinc coating with considerations of multiple performance characteristics to produce defect-free (such as peel-off, white shading, brightness, blistering, and decolouring) components. The Taguchi L36 (23X313) orthogonal array-based experiment design is used in this study to optimize process parameters. The significance and percentage contributions of each process variable are evaluated using the signal-to-noise (S/N) ratio, ANOVA, response curve, and significance test with Fstatic. Confirmation tests are conducted to see eye to eye on the quality and reliability of the component for winning customer confidence. The study infers that Taguchi off-line quality control is a correct method for optimizing coating process variables with a minimum number of trial runs as compared with the full factorial design in the traditional surface-coating process. The durability of the component in question is confirmed by means of salt-spray testing for aesthetic requirements.

Optimized Nanosecond Pulsed Laser Micromachining of Y‐TZP Ceramics

Owing to the inherent difficulty of mechanically machining hard, ytrria‐stabilized tetragonal zirconia polycrstal (Y‐TZP) ceramics, laser processing has recently been investigated as an alternative. However, owing to the vast range of variables such as wavelength, focus position, pulse width, power, and repetition rate, finding the optimum processing conditions can be difficult. In this report, we examine the parameters for a nanosecond pulsed (60 ns) Nd:YAG laser. It was found that at room temperature, the absorption of Y‐TZP at 1064 and 532 nm is very low; however, it becomes highly absorbing above a “machining threshold” with a penetration depth of 1.6 μm above the threshold. In this condition, we have found the combination of processing variables that provides the optimum material removal rate (up to ∼2 mm3/min). Additionally, it was found that the pulse overlap has a significant influence on the efficiency of the processing and therefore the combination of scan speed and repetition rate must be carefully considered.