Design of a neuro-fuzzy–regression expert system to estimate cost in a flexible jobshop automated manufacturing system

We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty.     

Mathematical programming approach to optimize material flow in an AGV-based flexible jobshop manufacturing system with performance analysis

An automated manufacturing system (AMS) is a complex network of processing, inspecting, and buffering nodes connected by system of transportation mechanisms. For an AMS, it is desirable to be capable to increase or decrease the output with the rise and fall of demand. Such specifications show the complexity of decision making in the field of AMSs and the need for concise and accurate modeling methods. Therefore, in this paper, a flexible jobshop automated manufacturing system is proposed to optimize the material flow. The flexibility is on the multi-shops of the same type and also multiple products that can be produced. An automated guided vehicle is applied for material handling. The objective is to optimize the material flow regarding the demand fluctuations and machine specifications. An illustrative example is presented to test the validity of the proposed mathematical model.     

Recent Approaches in the Development of Encapsulated Delivery Systems for Probiotics

The concept of probiotics has been well-known for more than a century. The availability and survival of the consumed probiotics in the colon has not been proved convincingly and needs further studies and clarification. It was not known whether the fastidious probiotics could reach the targeted site of action due to gastrointestinal stress. However, probiotics must sustain themselves in high number, survive during passage through the stomach to the intestine, and react symbiotically with the host when they reach the colon. This review consolidates some of the recent findings and new strategies on the development of a delivery system for targeted colonic delivery of probiotics.     

Effects of Acidity and Method of Preparation on Nucleate Pool Boiling of Nanofluids

Past research has shown contradicting trends in the rate of heat transfer during pool boiling of nanofluids, which could be attributed either to their stability or to their method of preparation or to both. An experimental study has been conducted to investigate the effects of electrostatic stabilization and preparation method of nanofluids on their pool boiling rate of heat transfer. Nanofluids made from water and alumina nanoparticles at 0.1 vol% concentration were used. The effect of electrostatic stabilization was investigated by changing the pH value from 6.5, neutral, to 5, acidic. The effect of preparation method has been investigated by using nanofluids prepared from dry particles and from ready-made suspensions. Compared with water, all nanofluids investigated resulted in deterioration in the rate of heat transfer during pool boiling. Neutral nanofluids made from ready-made suspensions and from dry particles resulted into almost the same deterioration in the rate of heat transfer of 49% and 45%, respectively, with respect to that of pure water. The most significant effect of electrostatic stabilization was found in the case of acidic nanofluids made from dry particles, which resulted in deterioration in the rate of heat transfer of 31%. However, acidic nanofluids made from ready-made suspensions resulted in a deterioration of 46%, which is almost the same as that of suspension-made and dry particles-made nanofluids. These results indicate that electrostatic stabilization using acid addition is most effective with nanofluids made from dry particles.     

Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings

Dynamic facility layout problem deals with the problem of arranging and rearranging the layout plan of a system throughout several periods. In each period, the material handling costs are different from the past period due to the change in the market demand and product mix. In this paper, the uncertainty that exists in transportation values’ forecast is modeled by fuzzy theory. In this paper, departments have unequal areas. This means that in each period, departments can be placed only in certain places due to different spacing requirements. In addition, closeness rating matrix is considered in order to model the goodness of different layout plans with regard to qualitative factors according to decision maker. Accordingly, fuzzy dynamic facility layout problem with unequal areas and closeness rating matrix is considered that aims to minimize the uncertain material handling costs as well as the shifting costs, and maximize closeness rating with regard to space requirements of unequal area departments. A number of fuzzy algorithms are developed in order to deal with the problem. A number of ranking criteria from the literature are implemented in order to compare the performance of the developed algorithms.     

Binary tree time adaptive self-organizing map

An adaptive hierarchical structure called “Binary Tree TASOM” (BTASOM) is proposed, which resembles a binary natural tree having nodes composed of Time Adaptive Self-Organizing Map (TASOM) networks. The standard TASOM is almost as slow as the standard SOM and has a fixed number of neurons. The BTASOM is proposed to make the TASOM fast and adaptive in the number of its neurons. The BTASOM is the first proposed hierarchical structure that uses a binary tree topology with TASOM networks. The number of levels of the BTASOM and the number of its nodes are adaptive to the accuracy demanded by the application through user-defined parameters. Two versions of the BTASOM are used here: the first version in which every node has only one neuron, and the second version in which every node has exactly two neurons. Both versions are tested with different distributions, stationary and nonstationary, for data representation. The experiments show that the BTASOM can work with both stationary and nonstationary environments while increasing the adaptability and speed of the standard TASOM. Several performance measures demonstrate the superiority of the proposed BTASOM in comparison with some other hierarchical SOM-based networks for clustering and input space approximation.     

The effect of inlet parameters on the performance of packed tower-regenerator

An investigation on the operation of packed tower for the regeneration of liquid desiccant is presented. A theoretical model demonstrating the effect of the system parameters is described. The experimental results are plotted to illustrate the effect of air and liquid parameters on the output variables. The regeneration process is shown to be highly dependent on the air inlet conditions, namely, temperature, humidity and flow rate. Also, the effects of the liquid temperature, concentration and flow rate is discussed. Data obtained were correlated to estimate the rate of water evaporation (regeneration rate) from values of variables that influence the rate of mass transfer in the column.     

The role of the industrial engineer in developing expert systems

The most popular area of Artificial Intelligence application today is in expert systems. This paper contains a discussion of expert systems, otherwise known as knowledge-based systems and knowledge systems. The principal components of an expert system, and the evolution of expert systems are presented. The suitability of a task to an expert system is proposed. When a task is suitable for an expert system application, the system must be developed by a knowledge engineer. The methodology that the knowledge engineer must go through to develop an expert system is demostrated. Industrial engineers have formal training in many areas which can be useful when assumming the role of knowledge engineer. These areas of industrial engineering and how they are beneficial is discussed. What the future may hold in store is also pondered.     

Preparation of porous PLLA/PCL blend by a combination of PEO phase and NaCl particulate leaching in PLLA/PCL/PEO/NaCl blend

In this study, the ternary blends containing microporosity based on poly(l-lactic acid) (PLLA), poly(ε-caprolactone) (PCL) and polyethylene oxide (PEO) were prepared using an internal mixer via a polymer leaching technique. The particulate leaching is the most widely used technique to create porosity. To introduce macroporosity besides micropores, NaCl particulates were incorporated into the ternary blends at 40–80 wt % and macropores were formed by particulate leaching. Samples porosity were evaluated by calculating the ratio of porous scaffold density (ρ*) to the non-porous material density (ρ _s). The results showed that with an increase in NaCl particulate content, the amount of porosity increased and the distribution of pore size was gradually transformed from monomodal into bimodal form. The porosity plays a key role in governing the compression properties. Mechanical properties are presented by Gibson–Ashby model. Compressive modulus decreased with an increase in NaCl particulate concentration due to the increase in porosity and thinning of pore wall that caused rupture at these weaker spots. Blending and forming of the bio-scaffold can be made using conventional polymer processing equipment. This process seems promising for a large-scale production of porous bio-scaffold of many sizes through an economic method.     

Investigating Factors Affecting Water-In-Diesel Fuel Nanoemulsions

In this work, water-in-diesel fuel nanoemulsions were prepared with mixed nonionic surfactants. Several mixtures of sorbitan monooleate and polyoxyethylene (20) sorbitan monooleate, with different Hydrophilic–Lipophilic Balance (HLB) values (9.6, 9.8, 10, 10.2 and 10.4) were prepared to achieve the optimal HLB value. Three mixed surfactant concentrations were prepared at 6, 8 and 10 wt% to identify the optimum concentration. Five emulsions with different water contents: 5, 6, 7, 8 and 9 % (wt/wt) were prepared using a high energy method under the optimum conditions (HLB = 10 and mixed surfactant concentration = 10 %). The effect of the HLB value, mixed surfactant concentration and water content on the droplet size has been studied. The interfacial tension and thermodynamic properties of the individual and the blended emulsifiers were investigated. Droplet size of the prepared nanoemulsions was determined by dynamic light scattering and the nanoemulsion stability was assessed by measuring the variation of the droplet size as a function of time. From the results obtained, it was found that the mean droplet size was formed between 49.5 and 190 nm depending on the HLB value, surfactant concentration and water content of the blended emulsifiers.