Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common mo...Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common models used for various decision-making processes is an effective approach. From this point of view, a batch system common model as described by a Petri net is proposed. In this article, a fault diagnosis technique for batch processes is presented using information about fault propagation and the possibilities of integration of fault analysis and controller synthesis are discussed on the basis of the Petri net based common models.展开更多
Spent Coffee Ground (SCG) is characterized by high organic content, in the form of insoluble polysaccharides bound and phenol compounds. Phenol compounds are toxic to nature and <span style="font-family:Verdan...Spent Coffee Ground (SCG) is characterized by high organic content, in the form of insoluble polysaccharides bound and phenol compounds. Phenol compounds are toxic to nature and <span style="font-family:Verdana;">are</span><span style="font-family:Verdana;"> a cause of environmental pollution. Composting method of this study is aerobic static batch composting with temperature control with adding activators of some fungi such as </span><i><span style="font-family:Verdana;">Aspergillus sp</span></i><span style="font-family:Verdana;">, and </span><i><span style="font-family:Verdana;">Penicillium sp. </span></i><span style="font-family:Verdana;">The purpose of the research is to fill the research gap from previous studies of spent coffee grounds compost, which requires a long time in composting, so that if it is used directly on the soil and plants, the positive effect also requires a long time. The result of composting for 28 days with this method is that mature compost has black crumb and normal pH, with characteristics of C/N ratio below 10: C1 (7.06), C2 (6.99). This value is far from the control with a C/N ratio of 8.33. Decompose rate of macromolecule are above 40% for lignin and 70% for cellulose. Implementation of compost in radish plants, resulting Germination Index above 80% which indicates that the compost is ripe: control (92.39%), C1 (183.88%), C2 (191.86%). The results of the analysis with FTIR also showed that the compost was mature and stable, and rich in minerals. So, it can be concluded </span><span style="font-family:Verdana;">that</span><span style="font-family:Verdana;"> this composting method can speed up composting time and optimize the results of compost produced.</span>展开更多
Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinea...Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.展开更多
Wet granulation-a unit operation involving mixing polymeric binders with powdered formulations-is well established in the pharmaceutical industry,playing a major role in the manufacturing of oral solid dosage forms an...Wet granulation-a unit operation involving mixing polymeric binders with powdered formulations-is well established in the pharmaceutical industry,playing a major role in the manufacturing of oral solid dosage forms and improving the physical properties of granules(size,density,shape factor,etc.)before tableting.The foaming properties of aqueous polymeric binders prove useful for binder delivery within the mixing vessel,with foamed binders leading to enhanced process efficiency(binder distribution,drying time,and temperature)and product quality(heat-sensitive components)during granulation.Given the importance of this stage in producing oral solid dosage forms,understanding the relationship between critical process parameters and critical quality attributes is essential.The process analytical technology(PAT)framework enables process design,analysis,and control and facilitates process development via in-line spectroscopy combined with multivariate data analysis to yield critical product information during the unit operation.Herein,we used in-line NIR spectroscopy to monitor granule size in foam granulations of a pharmaceutical compound.The mean granule diameter was predicted using a partial least squares regression(PLSR)model(with a prediction error of 11.8μm)and combined with a batch statistical process control(BSPC)approach for the temporal monitoring of granule size during three foam granulations.展开更多
文摘Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common models used for various decision-making processes is an effective approach. From this point of view, a batch system common model as described by a Petri net is proposed. In this article, a fault diagnosis technique for batch processes is presented using information about fault propagation and the possibilities of integration of fault analysis and controller synthesis are discussed on the basis of the Petri net based common models.
文摘Spent Coffee Ground (SCG) is characterized by high organic content, in the form of insoluble polysaccharides bound and phenol compounds. Phenol compounds are toxic to nature and <span style="font-family:Verdana;">are</span><span style="font-family:Verdana;"> a cause of environmental pollution. Composting method of this study is aerobic static batch composting with temperature control with adding activators of some fungi such as </span><i><span style="font-family:Verdana;">Aspergillus sp</span></i><span style="font-family:Verdana;">, and </span><i><span style="font-family:Verdana;">Penicillium sp. </span></i><span style="font-family:Verdana;">The purpose of the research is to fill the research gap from previous studies of spent coffee grounds compost, which requires a long time in composting, so that if it is used directly on the soil and plants, the positive effect also requires a long time. The result of composting for 28 days with this method is that mature compost has black crumb and normal pH, with characteristics of C/N ratio below 10: C1 (7.06), C2 (6.99). This value is far from the control with a C/N ratio of 8.33. Decompose rate of macromolecule are above 40% for lignin and 70% for cellulose. Implementation of compost in radish plants, resulting Germination Index above 80% which indicates that the compost is ripe: control (92.39%), C1 (183.88%), C2 (191.86%). The results of the analysis with FTIR also showed that the compost was mature and stable, and rich in minerals. So, it can be concluded </span><span style="font-family:Verdana;">that</span><span style="font-family:Verdana;"> this composting method can speed up composting time and optimize the results of compost produced.</span>
基金Supported by the National Natural Science Foundation of China(61573052)
文摘Control of the fed-batch ethanol fermentation processes to produce maximum product ethanol is one of the key issues in the bioreactor system.However,ethanol fermentation processes exhibit complex behavior and nonlinear dynamics with respect to the cell mass,substrate,feed-rate,etc.An improved dual heuristic programming algorithm based on the least squares temporal difference with gradient correction(LSTDC) algorithm(LSTDC-DHP) is proposed to solve the learning control problem of a fed-batch ethanol fermentation process.As a new algorithm of adaptive critic designs,LSTDC-DHP is used to realize online learning control of chemical dynamical plants,where LSTDC is commonly employed to approximate the value functions.Application of the LSTDC-DHP algorithm to ethanol fermentation process can realize efficient online learning control in continuous spaces.Simulation results demonstrate the effectiveness of LSTDC-DHP,and show that LSTDC-DHP can obtain the near-optimal feed rate trajectory faster than other-based algorithms.
文摘Wet granulation-a unit operation involving mixing polymeric binders with powdered formulations-is well established in the pharmaceutical industry,playing a major role in the manufacturing of oral solid dosage forms and improving the physical properties of granules(size,density,shape factor,etc.)before tableting.The foaming properties of aqueous polymeric binders prove useful for binder delivery within the mixing vessel,with foamed binders leading to enhanced process efficiency(binder distribution,drying time,and temperature)and product quality(heat-sensitive components)during granulation.Given the importance of this stage in producing oral solid dosage forms,understanding the relationship between critical process parameters and critical quality attributes is essential.The process analytical technology(PAT)framework enables process design,analysis,and control and facilitates process development via in-line spectroscopy combined with multivariate data analysis to yield critical product information during the unit operation.Herein,we used in-line NIR spectroscopy to monitor granule size in foam granulations of a pharmaceutical compound.The mean granule diameter was predicted using a partial least squares regression(PLSR)model(with a prediction error of 11.8μm)and combined with a batch statistical process control(BSPC)approach for the temporal monitoring of granule size during three foam granulations.
