• Title/Summary/Keyword: Production optimization

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Improvement of Amidase Production by a Newly Isolated Delftia tsuruhatensis ZJB-05174 Through Optimization of Culture Medium

  • Wang, Yuan-Shan;Xu, Jian-Miao;Zheng, Ren-Chao;Zheng, Yu-Guo;Shen, Yin-Chu
    • Journal of Microbiology and Biotechnology
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    • v.18 no.12
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    • pp.1932-1937
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    • 2008
  • The R-amidase production by a newly isolated strain of Delftia tsuruhatensis ZJB-05174 was optimized in this paper. Effects of factors such as carbon sources, nitrogen sources, and inducers on amidase production were investigated. The medium composition was optimized using central composite designs and response surface analysis. The optimal medium components for enhanced amidase production were found to be as follows: glucose, 8.23 g/l; yeast extract, 11.59 g/l; 2,2-(R,S)-dimethylcyclopropane carboxamide, 1.76 g/l; NaCl, 1 g/l; ${KH_2}{PO_4}$ 1 g/l; and ${K_2}{HPO_4}$ 1 g/l. A maximum enzyme production of 528.21 U/l was obtained under the optimized conditions, which was 4.7 times higher than that obtained under initial conditions.

Decision Support System by using Tunable Simulation for Optimally Mixed Systems (조정 가능한 시뮬레이션을 사용하여 최적 혼성 시스템을 찾아내기 위한 의사 결정 지원시스템 구축)

  • Kim, Sung-Soo
    • IE interfaces
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    • v.10 no.3
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    • pp.209-216
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    • 1997
  • This mixed push and pull production system defines that all stages are not ordered by either of the production systems. Some stages are ordered by a push-type production system and the other stages are ordered by a pull-type production system. A decision support system is built by using a combination of optimization program and the "tunable" SIMAN discrete-event simulation for the implementation of an optimally mixed production system. Finding this optimal system requires 6 CPU hours for the case study on a Pentium. Both the simulation and optimization model are validated with a case study of Phoenix company that manufactures transmitters. This paper uses survey from experts in this company for evaluation and validation of this system.

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Optimization of Solid-State Fermentation for Improved Conidia Production of Beauveria bassiana as a Mycoinsecticide

  • Pham, Tuan Anh;Kim, Jeong-Jun;Kim, Keun
    • Mycobiology
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    • v.38 no.2
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    • pp.137-143
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    • 2010
  • The production of conidia of entomopathogenic Beauveria bassiana by solid-state fermentation was studied for the development of a biocontrol agent against aphid Myzus persicae. The optimal conditions for conidia production on polished white rice were 40% moisture content, $25^{\circ}C$ culture temperature, 2-day-old seeding culture grown in 3% corn meal, 2% rice bran, 2% corn steep powder medium, initial conidia concentration of $10^7$ conidia/g in the wet rice, 10% inoculum size, and use of a polyethylene bag as a container. The polyethylene bag containing inoculated rice was hand-shaken every 12 hr during fermentation. Using optimal conditions, the maximum conidia production obtained was 4.05 g conidia/100 g dry rice after 14 days of cultivation, a rate 2.83 times higher than conidia yield of pre-optimization.

Optimization of injection molding process for car fender in consideration of energy efficiency and product quality

  • Park, Hong Seok;Nguyen, Trung Thanh
    • Journal of Computational Design and Engineering
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    • v.1 no.4
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    • pp.256-265
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    • 2014
  • Energy efficiency is an essential consideration in sustainable manufacturing. This study presents the car fender-based injection molding process optimization that aims to resolve the trade-off between energy consumption and product quality at the same time in which process parameters are optimized variables. The process is specially optimized by applying response surface methodology and using non-dominated sorting genetic algorithm II (NSGA II) in order to resolve multi-object optimization problems. To reduce computational cost and time in the problem-solving procedure, the combination of CAE-integration tools is employed. Based on the Pareto diagram, an appropriate solution is derived out to obtain optimal parameters. The optimization results show that the proposed approach can help effectively engineers in identifying optimal process parameters and achieving competitive advantages of energy consumption and product quality. In addition, the engineering analysis that can be employed to conduct holistic optimization of the injection molding process in order to increase energy efficiency and product quality was also mentioned in this paper.

Application of Factorial Experimental Designs for Optimization of Cyclosporin A Production by Tolypocladium inflatum in Submerged Culture

  • Abdel-Fattah, Y.R.;Enshasy, H. El;Anwar, M.;Omar, H.;Abolmagd, E.
    • Journal of Microbiology and Biotechnology
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    • v.17 no.12
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    • pp.1930-1936
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    • 2007
  • A sequential optimization strategy based on statistical experimental designs was employed to enhance the production of cyclosporin A (CyA) by Tolypocladium inflatum DSMZ 915 in a submerged culture. A 2-level Plackett-Burman design was used to screen the bioprocess parameters significantly influencing CyA production. Among the 11 variables tested, sucrose, ammonium sulfate, and soluble starch were selected, owing to their significant positive effect on CyA production. A response surface methodology (RSM) involving a 3-level Box-Behnken design was adopted to acquire the best process conditions. Thus, a polynomial model was created to correlate the relationship between the three variables and the CyA yield, and the optimal combination of the major media constituents for cyclosporin A production, evaluated using the nonlinear optimization algorithm of EXCEL-Solver, was as follows (g/l): sucrose, 20; starch, 20; and ammonium sulfate, 10. The predicted optimum CyA yield was 113 mg/l, which was 2-fold the amount obtained with the basal medium. Experimental verification of the predicted model resulted in a CyA yield of 110 mg/l, representing 97% of the theoretically calculated yield.

Efficient Interleukin-21 Production by Optimization of Codon and Signal Peptide in Chinese Hamster Ovarian Cells

  • Cho, Hee Jun;Oh, Byung Moo;Kim, Jong-Tae;Lim, Jeewon;Park, Sang Yoon;Hwang, Yo Sep;Baek, Kyoung Eun;Kim, Bo-Yeon;Choi, Inpyo;Lee, Hee Gu
    • Journal of Microbiology and Biotechnology
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    • v.29 no.2
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    • pp.304-310
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    • 2019
  • Interleukin-21 is a common ${\gamma}$-chain cytokine that controls the immune responses of B cells, T cells, and natural killer cells. Targeting IL-21 to strengthen the immune system is promising for the development of vaccines as well as anti-infection and anti-tumor therapies. However, the practical application of IL-21 is limited by the high production cost. In this study, we improved IL-21 production by codon optimization and selection of appropriate signal peptide in CHO-K1 cells. Codon-optimized or non-optimized human IL-21 was stably transfected into CHO-K1 cells. IL-21 expression was 10-fold higher for codon-optimized than non-optimized IL-21. We fused five different signal peptides to codon-optimized mature IL-21 and evaluated their effect on IL-21 production. The best result (a 3-fold increase) was obtained using a signal peptide derived from human azurocidin. Furthermore, codon-optimized IL-21 containing the azurocidin signal peptide promoted $IFN-{\gamma}$ secretion and STAT3 phosphorylation in NK-92 cells similar to codon-optimized IL-21 containing original signal peptide. Collectively, these results indicate that codon optimization and azurocidin signal peptides provide an efficient approach for the high-level production of IL-21 as a biopharmaceutical.

Optimization of DMAIC for production system developer task : Focused on Battery Manufacturing (DMAIC 방법론의 생산시스템 개발자 과제 최적화 모델링: 배터리 제조 중심으로)

  • Shin Chul Park;Joo Yeoun Lee;Myoung Sug Jung
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.2
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    • pp.153-167
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    • 2024
  • DMAIC is the most familiar problem-solving methodology to battery manufacturing-related engineers, but continuous problems such as task delay, insufficient performance, and partial optimization are occurring due to indiscriminate application to various tasks of battery production system developers. In order to secure an "optimized model for DMAIC methodology" that can effectively respond to battery production system developers' tasks, a three-stage research model was used to derive the required characteristics of the production system developer task methodology, analyze the suitability of DMAIC, and conduct optimization modeling by supplementing the shortcomings. It was confirmed that the DMAIC methodology can be more suitable by applying the "system structural seven-step methodology", which is the result of this study, to developer tasks. It is expected that it will be applied to various industrial fields in the future by making it easier to learn and allowing differentiated operations according to the characteristics of various industries.

Optimization of Mass cultivation Media for the Production of Biomass and Natural Colourants from Two Marine Cyanobacteria by a Mathematical Design of Experiments

  • Sekar, S.;Priya, S.Sri Lavanya;Roy, P.Wesley
    • Journal of Plant Biotechnology
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    • v.2 no.3
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    • pp.157-163
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    • 2000
  • Optimization of chemicals in the large scale sea water medium and inoculum for biomass and natural colourants production in the marine cyanobacteria, Phomidium tenue BDU 46241 (phycoerythrin producer) and P.valderianum BDU 30501 (phycocyanin producer) was carried out by experiments in L8 orthogonal array. Mathematical analysis revealed the significance of these factors. The factor(s) that critically control the yield varied with the organism and the end-product further, the desirable level of these factors between the normal and a higher level tested was identified and improved media were evolved. In both cyanobacteria, higher level of $K_2$$HPO_4$, $NaNO_3$ and inoculum with normal level of ferric ammonium citrate was found to be desirable for biomass production and additionally, higher level of $MgSO_4$ for pigment production. The level of other factors varied with the organism and the end-product. Confirmation experiments showed that the clues obtained based on mathematical experimentation are valid. In P.tenue, the medium optimized for biomass production increased the yield of biomass by 495% and the medium optimized for phycoerythrin production increased the yield of biomass by 408% with 30% increase in phycoerythrin content of the biomass. Similarly in P.valderianum, the medium optimized for biomass production increased the yield of biomass by 224% and the medium optimized for phycocyanin production increased the yield of biomass by 143% with 44% increase in phycocyanin content of the biomass.

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Optimal Buffer Allocation in Multi-Product Repairable Production Lines Based on Multi-State Reliability and Structural Complexity

  • Duan, Jianguo;Xie, Nan;Li, Lianhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.4
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    • pp.1579-1602
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    • 2020
  • In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.

The Development of Production Simulation Methodology by Optimization Technique and It's Application to Utility Expansion Planning (최적화 기법에 의한 발전시뮬레이션 방법론의 개발 및 전원확충계획 문제에의 적용)

  • Song, K.Y.;Oh, K.H.;Kim, Y.H.;Cha, J.M.
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.793-796
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    • 1996
  • This study proposes a new algorithm which performs a production simulation under various constraints and maintains computational efficiency. In order to consider the environmental and operational constraints, the proposed algorithm is based on optimization techniques formulated in LP form In the algorithm, "system characteristic constraints" reflect the system characteristics such as LDC shape, unit loading order and forced outage rate. By using the concept of Energy Invariance Property and two operational rules i.e. Compliance Rule for Emission Constraint, Compliance Rule for Limited Energy of Individual Unit, the number of system characteristic constraints is appreciably reduced. As a solution method of the optimization problem, the author uses Karmarkar's method which performs effectively in solving large scale LP problem. The efficiency of production simulation is meaningful when it is effectively used in power system planning. With the proposed production simulation algorithm, an optimal expansion planning model which can cope with operational constraints, environmental restriction, and various uncertainties is developed. This expansion planning model is applied to the long range planning schemes by WASP, and determines an optimal expansion scheme which considers the effect of supply interruption, load forecasting errors, multistates of unit operation, plural limited energy plants etc.

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