Synthesis of Rice Processing Plants. I. Development of Simplified Models

Phongpipatpong, M.; Douglas, Peter

doi:10.1081/drt-120025499

Cited by 2 publications

(9 citation statements)

References 11 publications

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“…To date, many studies on optimization of rice processing revolve around rice milling operations, particularly drying . A few other studies focus on synthesis and optimization of rice processing plants excluding the utility system . Note that most studies on modeling and optimization of biomass-based cogeneration system have not considered rice husk logistic network.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of a Rice Mill Utility System with Rice Husk Logistic Network

Lim

Hashim

Manan

et al. 2011

Ind. Eng. Chem. Res.

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Thermal energy for drying and electricity for milling operations typically comprise a significant 55% of a rice mill operating cost. Optimal design of rice mill utility system that efficiently utilizes rice husk biomass has potential to increase profitability of rice milling industry. This paper presents a mathematical approach for simultaneous optimal planning of rice husk logistic network as well as optimal design of a rice mill utility system that efficiently utilizes rice husk supplied from various locations in order to satisfy the electricity and drying requirements of the rice mill throughout the year. A mixed integer linear programming (MILP) problem was formulated to determine: (1) the optimal logistic network for the rice husk supply, (2) the economic scale of the rice husk cogeneration system, and (3) an optimal utility supply network for a series of dryers consisting of a combination of cyclonic husk furnace (CHF) and cogeneration systems. Solution to the MILP problem yields an optimal utility system configuration consisting of a specified network of rice husk logistic network, a 15 tons boiler for the cogeneration system and 8 units of CHFs to satisfy the rice mill heat and power requirements. Compared to the baseline, the optimal utility network manages to reduce 18.5% of the total rice mill annualized cost which include the costs of capital, fuel, and electricity.

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Section: Introductionmentioning

confidence: 99%

Optimal Design of a Rice Mill Utility System with Rice Husk Logistic Network

Lim

Hashim

Manan

et al. 2011

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…No single drying model can represent the drying process of rice grain over a wide range of drying operation. Here, we select three drying models from the literature ,, to cover various ranges of drying operation. These particular models were selected because they were formulated in terms of the same operating variables (drying temperature, relative humidity of drying air, and drying time) and because they were derived from Page’s model, which has the general form MR = M t − M e M i − M e = exp ( − k t N ) where MR is the moisture ratio, M t is moisture content of grain at any time (% db), M i is initial moisture content of the grain (% db), M e is the equilibrium moisture content of the grain (% db), t is the drying time, and k and N are drying parameters.…”

Section: Generalized Disjunctive Programming Modelmentioning

confidence: 99%

“…Phongpipatpong and Douglas aimed for models that are valid over a wide range of drying operation and simple to use in the synthesis problem. Thus they have first simplified the basic Page’s model by setting N = 1 and M e = 0 to MR = M t M i = exp ( − k t ) …”

Section: Generalized Disjunctive Programming Modelmentioning

confidence: 99%

“…On the other hand, empirical models are developed by fitting experimental data with simple mathematical functions, often in exponential form. ,,,− They use simple mathematical functions and make no assumptions about the underlying mechanisms; thus, they are easier to implement than theoretical models. However, empirical models are valid only for the particular range of operating conditions for which they were developed.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the synthesis problem considered in this study has two objectives: One objective is to find the optimum drying configuration and operating conditions that maximize the head rice yield, and the second objective is to minimize the energy consumed during drying operations. Two objective functions, previously developed by Phongpipatpong and Douglas, are considered in this paper: to maximize rice quality and to minimize the energy consumed during the drying operations.…”

Section: Introductionmentioning

confidence: 99%

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Generalized Disjunctive Programming for Synthesis of Rice Drying Processes

Younes

Wongrat

Elkamel

et al. 2010

Ind. Eng. Chem. Res.

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Rice drying synthesis is an essential operation that has to be done carefully and cost-effectively. Fast drying can cause fissuring, which lowers the market value of the rice grains. Multipass drying systems are therefore used to bring the moisture content to desired levels gradually. To determine the best configuration of units and their corresponding operating conditions that maximize rice quality and minimize energy consumption, empirical models are used. However, empirical models have limited ranges of validity. Moreover, different mathematical models are possible for the same synthesis problem. This paper proposes a generalized disjunctive programming (GDP) framework for the synthesis problem of rice drying in order to increase the overall range of applicability of the empirical models and establish a consistent solution strategy. The proposed framework is investigated and tested on several case studies. Different drying strategies resulted from solving the synthesis problem with different empirical models, providing us with a broader vision of the mechanism of rice drying processes. The results indicate that the GDP framework can facilitate the modeling of the synthesis problem and increase the efficiency of optimization algorithms.

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Synthesis of Rice Processing Plants. I. Development of Simplified Models

Cited by 2 publications

References 11 publications

Optimal Design of a Rice Mill Utility System with Rice Husk Logistic Network

Optimal Design of a Rice Mill Utility System with Rice Husk Logistic Network

Generalized Disjunctive Programming for Synthesis of Rice Drying Processes

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