Great Price "Four main objectives for the future of chemical and process engineering mainly concerned by the science and technologies of new materials production [An article from: Chemical Engineering Journal]" for $10.95 Today

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Four main objectives for the future of chemical and process engineering mainly concerned by the science and technologies of new materials production [An article from: Chemical Engineering Journal] Overviews

This digital document is a journal article from Chemical Engineering Journal, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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Today the chemical and process engineering especially involving chemical reactor engineering has to answer to the changing needs of the chemical and related process industries such as petroleum, petrochemical, bituminous, pharmaceutical and health, agro and food, environment, iron and steel, building materials, paints, glass, surfactants, electronics, cosmetic and perfume, etc., and to meet market demands. So being a key to survival in globalisation of trade and competition, the evolution of chemical engineering is thus necessary. And to satisfy both, the market requirements for specific end-use properties of the products manufactured in (bio)chemical reactors and the social and the resource-saving and environmental constraints of the industrial-scale processes and technologies, it is shown that a necessary progress is coming via a multidisciplinary and time and length multiscale approach. In such a frame the future for the science and technologies of new materials can be summarized by four main objectives: (1) a total multiscale control of the process (or the procedure) to increase selectivity and productivity, i.e., nanotailoring of materials with controlled structure; (2) a design of novel equipment based on scientific principles and new operation modes and methods of production: process intensification; (3) product design and engineering: manufacturing end-use properties with a special emphasis on complex fluids and solids technology; (4) an implementation of the multiscale and multidisciplinary computational chemical engineering modelling and simulation to real-life situations: from the molecule to the overall complex production scale into the entire production site. Moreover, chemical and process engineering will also be increasingly involved and concerned with the application of life cycle assessment to new material design and production and its use but also to the plant and the equipment together with the associated services.

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Great Price "Heuristic approaches to determine base-stock levels in a serial supply chain with a single objective and with multiple objectives [An article from: European Journal of Operational Research]" for $7.95 Today

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Heuristic approaches to determine base-stock levels in a serial supply chain with a single objective and with multiple objectives [An article from: European Journal of Operational Research] Overviews

This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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This paper deals with the problem of determination of installation base-stock levels in a serial supply chain. The problem is treated first as a single-objective inventory-cost optimization problem, and subsequently as a multi-objective optimization problem by considering two cost components, namely, holding costs and shortage costs. Variants of genetic algorithms are proposed to determine the best base-stock levels in the single-objective case. All variants, especially random-key gene-wise genetic algorithm (RKGGA), show an excellent performance, in terms of convergence to the best base-stock levels across a variety of supply chain settings, with minimum computational effort. Heuristics to obtain base-stock levels are proposed, and heuristic solutions are introduced in the initial population of the RKGGA to expedite the convergence of the genetic search process. To deal with the multi-objective supply-chain inventory optimization problem, a simple multi-objective genetic algorithm is proposed to obtain a set of non-dominated solutions.

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Great Price "Danbury company aims at national presence.(DOING BUSINESS IN DANBURY)(Network Support Company L.L.C): An article from: Fairfield County Business Journal" for $5.95 Today

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Danbury company aims at national presence.(DOING BUSINESS IN DANBURY)(Network Support Company L.L.C): An article from: Fairfield County Business Journal Overviews

This digital document is an article from Fairfield County Business Journal, published by Westfair Communications, Inc. on June 27, 2005. The length of the article is 992 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

Citation Details
Title: Danbury company aims at national presence.(DOING BUSINESS IN DANBURY)(Network Support Company L.L.C)
Author: Bob Chuvala
Publication:Fairfield County Business Journal (Magazine/Journal)
Date: June 27, 2005
Publisher: Westfair Communications, Inc.
Volume: 44 Issue: 26 Page: 21(2)

Distributed by Thomson Gale

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An iterative sequential heuristic procedure to a real-life 1.5-dimensional cutting stock problem [An article from: European Journal of Operational Research] Review

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This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
This paper addresses a real-life 1.5D cutting stock problem, which arises in a make-to-order plastic company. The problem is to choose a subset from the set of stock rectangles to be used for cutting into a number of smaller rectangular pieces so as to minimize total production cost and meet orders. The total production cost includes not only material wastage, as in traditional cutting stock problems, but also production time. A variety of factors are taken into account, like cutter knife changes, machine restrictions, due dates and other work in progress limitations. These restrictions make the combinatorial structure of the problem more complex. As a result, existing algorithms and mathematical models are no longer appropriate. Thus we developed a new 1.5D cutting stock model with multiple objectives and multi-constraints and solve this problem in an incomplete enumerative way. The computational results show that the solution procedure is easy to implement and works very well.

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Design of separation process of azeotropic mixtures based on the green chemical principles [An article from: Journal of Cleaner Production]

Design of separation process of azeotropic mixtures based on the green chemical principles [An article from: Journal of Cleaner Production] Review

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This digital document is a journal article from Journal of Cleaner Production, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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This paper presents an integrated methodology for synthesis of separation process of azeotropic mixture based on the green chemical principles, which inherently incorporates environmental factors into the separation process synthesis. Characterization of the environmental impact of a chemical process is carried out on the basis of our established environmental impact database (containing nine indices). The superstructure is optimized more effectively and reliably by integrating the mathematical programming approach using multi-objective mixed integer non-linear programming techniques and heuristic approach. The complexity and size of synthesis search space were greatly reduced by applying the thermodynamic insights into the selection of separation techniques. The proposed methodology was highlighted through two industrial examples, one is the separation of azeotropic mixture of dimethyl carbonate and methanol, the other is the separation of azeotropic mixture of isopropanol and water.

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