Modelling and analysis of FMS productivity variables by ISM,SEM and GTMA approach

Productivity has often been cited as a key factor in a flexible manufacturing system (FMS) performance, and actions to increase it are said to improve profitability and the wage earning capacity of employees. Improving productivity is seen as a key issue for survival and success in the long term of a manufacturing system. The purpose of this paper is to make a model and analysis of the productivity variables of FMS. This study was performed by different approaches viz. interpretive structural modelling (ISM), structural equation modelling (SEM), graph theory and matrix approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a model of productivity variables, and then it has been analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. CFA is carried by SEM. EFA is applied to extract the factors in FMS by the statistical package for social sciences (SPSS 20) software and confirming these factors by CFA through analysis of moment structures (AMOS 20) software. The twenty productivity variables are identified through literature and four factors extracted, which involves the productivity of FMS. The four factors are people, quality, machine and flexibility. SEM using AMOS 20 was used to perform the first order four-factor structures. GTMA is a multiple attribute decision making (MADM) methodology used to find intensity/quantification of productivity variables in an organization. The FMS productivity index has purposed to intensify the factors which affect FMS.     

Novel hybrid of clay,cellulose, and thermoplastics. I. Preparation and characterization of composites of ethylene–propylene copolymer

The present study is aimed to prepare hybrid materials by incorporating layered silicates and microcrystalline cellulose into thermoplastic polymer. Using ethylene–propylene (EP) copolymer as thermoplastic polymer matrix and maleated EP (MEP) copolymer as compatibilizer, three types of composites were prepared by (i) melt mixing of cellulose with thermoplastics [I], (ii) melt mixing of clay with thermoplastics [II], and (iii) melt mixing of cellulose with the thermoplastic clay nanocomposites [III]. They were characterized by X‐ray diffractometry (XRD), differential scanning calorimetry, thermogravimetric analysis, and Fourier transform infrared spectroscopy. Instron was used to measure the mechanical properties. The composites [II] and [III] that contain layered silicates were intercalated nanocomposites as confirmed by XRD and transmission electron microscopy. The improvement in tensile properties was observed in cellulose–fiber‐reinforced composites with increasing cellulose content. In nanocomposites [II] and [III], the tensile modulus was improved. The resistance of the cellulose composites [I] for water absorption decreased with increasing content of cellulose fibers. The incorporation of layered silicates reduced the water absorption of cellulose composites. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 2672–2682, 2007     

Flow through diffusion cell method: A novel approach to study in vitro enzymatic degradation of a starch‐based ternary semi‐interpenetrating network for gastrointestinal drug delivery

A ter‐polymeric semi‐IPN has been synthesized by aqueous polymerization of methacrylamide in the presence of polyethylene glycol (PEG) and natural polysaccharides starch, and its enzymatic degradation has been studied in the phosphate buffer medium of pH 6.8 at the physiological temperature 37°C. With the increase in content of enzyme in the external solution and starch in the hydrogel, the degradation is enhanced while the extent of degradation is lowered with the increase in the amount of PEG in the hydrogel. The initial water content also affects the degradability of the polymer matrix. The degradation follows Michaelis–Menten kinetics and K_M was found to be 3.92 × 10^?5 mol dm^?3. The hydrogel exhibits different degradation behavior when studied by “traditional degradation method” (TDM) and “flow through diffusion cell” (FTDC) method. The degradability is suppressed in FTDC method because of the absorption of amylase molecules onto filler particles. Finally the nature and size of the filler particles also affects the degradation behavior of hydrogels. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 2975–2984, 2006     

Effect of Steam Velocity on the Hydrothermal Oxidation/Volatilization of Silicon Nitride

The hydrothermal oxidation behavior of silicon nitride was studied as a function of vapor velocity in the range of 1–35 cm/s, at atmospheric pressure and ∼100% H₂O, using a custom-designed hydrothermal apparatus. At lower velocities, silicon nitride showed a marginal weight gain during early exposure times followed by a linear weight loss at longer exposure times. At higher velocities only linear weight loss was seen. The linear weight loss rates were determined from the weight change studies and they showed a square root dependence on velocity at higher flow rates. At the low flow rates a threshold velocity of ∼1 cm/s was observed for volatilization to initiate. The weight loss rates obtained in the apparatus at the higher steam velocities were comparable to those obtained in high pressure burner rigs, proving its viability as a good laboratory scale screening method for potential gas turbine materials.     

Magnetic Fluid Seals for Special Applications

Three magnetic fluid seals custom engineered to meet specific application objectives are discussed. These seals are: a belt edge seal, a large diameter seal and a centrifugal seal. Extensive experimental data were acquired on the first two seals to determine their performance characteristics. Some of these test results are compared with the theoretical expectations. Numerical computations are made on the centrifugal seal to Predict its sealing capabilites.     

An Improved genetic algorithm for the prediction of surface finish in dry turning of SS 420 materials

Determination of optimal cutting parameters is one of the most important elements in any process planning of metal parts. This paper presents a development of an improved genetic algorithm (IGA) and its application to optimize the cutting parameters for predicting the surface roughness is proposed. Optimization of cutting parameters and prediction of surface roughness is concerned with a highly constrained nonlinear dynamic optimization problem that can only be fully solved by complete enumeration. The IGA incorporating a stochastic crossover technique and an artificial initial population scheme is developed to provide a faster search mechanism. The main advantage of the IGA approach is that the “curse of dimensionality” and a local optimal trap inherent in mathematical programming methods can be simultaneously overcome. The IGA equipped with an improved evolutionary direction operator and a migration operation can efficiently search and actively explore solutions. The IGA approach is applied to predict the influence of tool geometry (nose radius) and cutting parameters (feed, speed, and depth of cut) on surface roughness in dry turning of SS 420 materials conditions based on Taguchi's orthogonal array method. Additionally, the proposed algorithm was compared with the conventional genetic algorithm (CGA), and we found that the proposed IGA is more effective than previous approaches and applies the realistic machining problem more efficiently than does the conventional genetic algorithm (CGA).     

A novel approach for analyzing fuzzy system reliability using different types of intuitionistic fuzzy failure rates of components

This paper addresses the fuzzy system reliability analysis using different types of intuitionistic fuzzy numbers. Till now, in the literature, to analyze the fuzzy system reliability, it is assumed that the failure rates of all components of a system follow the same type of fuzzy set or intuitionistic fuzzy set. However, in practical problems, such type of situation rarely occurs. Therefore, in the present paper, a new algorithm has been introduced to construct the membership function and non-membership function of fuzzy reliability of a system having components following different types of intuitionistic fuzzy failure rates. Functions of intuitionistic fuzzy numbers are calculated to construct the membership function and non-membership function of fuzzy reliability via non-linear programming techniques. Using the proposed algorithm, membership functions and non-membership functions of fuzzy reliability of a series system and a parallel systems are constructed. Our study generalizes the various works of the literature. Numerical examples are given to illustrate the proposed algorithm.     

Effect of CH4/H2 plasma ratio on ultra-low friction of nano-crystalline diamond coating deposited by MPECVD technique

Nano-crystalline diamond coatings were deposited on the silicon substrate using Microwave Plasma Enhanced Chemical Vapor Deposition (MPECVD). Experiments were performed by varying the H₂ content in CH₄/H₂ plasma during synthesis. Raman spectral analysis revealed that with decrease in hydrogen content in the CH₄ plasma, the I_D/I_G ratio decreases with the formation of smaller crystallites. Such a film possesses a large grain boundary fraction containing hydrogenated amorphous carbon (a-C:H). During tribological test, sufficient amount of hydrogen present in the grain boundary passivates the dangling σ-bond causing ultra-low friction and extremely low wear evident by improvement in microstructure.     

Tribological properties of ultrananocrystalline diamond films in various test atmosphere

Transformation from higher to ultra low friction coefficient was observed in ultrananocrystalline diamond film (UNCD) while changing the test atmospheric conditions. High friction coefficients were observed in dry argon and nitrogen atmosphere, however, low and ultra low friction coefficients were obtained in dry oxygen and in ambient atmospheric conditions, respectively. Wear rates follow the same trends as the friction coefficients. This fascinating behavior of friction and wear of UNCD film is explained by the chemical changes of sliding surfaces and extent of passivation of dangling covalent bonds.     

Effects of long-term pH elevation on the sulfate-reducing and methanogenic activities of anaerobic sewer biofilms

The dosage of alkali is often applied by the wastewater industry to reduce the transfer of hydrogen sulfide from wastewater to the sewer atmosphere. In this paper the activities of Sulfate Reducing Bacteria (SRB) and Methanogenic Archaea (MA) under elevated pH conditions (8.6 and 9.0) were evaluated in a laboratory scale anaerobic sewer reactor. Compared to those in a control reactor without pH control (pH 7.6 ± 0.1), the SRB activity was reduced by 30% and 50%, respectively, at pH 8.6 and pH 9.0. When normal pH was resumed, it took approximately 1 month for the SRB activity to fully recover. Methanogenic activities developed in the control reactor in 3 months after the reactor start-up, while no significant methanogenic activities were detected in the experimental reactor until normal pH was resumed. The results suggest that elevated pH at 8.6-9.0 suppressed the growth of methanogens. These experimental results clearly showed that, in addition to its well-known effect of reducing H₂S transfer from the liquid to the gas phase, pH elevation considerably reduces sulfide and methane production by anaerobic sewer biofilms. These findings are significant for the optimal use of alkali addition to sewers for the control of H₂S and CH₄ emissions. A model-based study showed that, by adding the alkali at the beginning rather than towards the end of a rising main, substantial savings in chemicals can be achieved while achieving the same level of sulfide emission control, and complete methane emission control.