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Development of cultivation schema and automated gully convey-spacing system for multilayer plant factory

DC Field Value Language
dc.contributor.advisorRhee Joong Yong-
dc.contributor.authorAlireza Ashtiani Araghi-
dc.date.accessioned2017-07-13T17:45:45Z-
dc.date.available2017-07-13T17:45:45Z-
dc.date.issued2015-02-
dc.identifier.other000000025825-
dc.identifier.urihttps://hdl.handle.net/10371/121113-
dc.description학위논문 (박사)-- 서울대학교 대학원 : 바이오시스템·소재학부, 2015. 2. 이중용.-
dc.description.abstractCultivation of leafy vegetables with hydroponic gullies in multilayer plant factories is one of the initiatives used to increase the plant production in artificially controlled indoor environments. Multistage mobile or dynamic cultivation with variable row spacing between gullies, used in single-layer cultivation, is another option to increase the average crop density and more efficient utilization of available area. Employment of dynamic cultivation in multilayer growing units can further increase the plant production rate, if an appropriate cultivation plan is adopted and executed during the process. To this end, developing a model for i) evaluating the performance of multilayer dynamic cultivation plans and comparing their performances with alternative static option, and ii) finding the details of the procedure used for executing the evaluated cultivation plan is a major objective in the first part of this study. Indices such as plant production rate, turning point day, and total number of produced plants during a certain period of time were defined and used to measure the performance of cultivation plans. Using the Labview programming, the model is then converted into a simulation module with visual input-output panel which represents a cultivation schema after the end of each simulation. In this way, a cultivation schema includes the characteristics and performance of a cultivation plan as well as the procedure to execute it. The visual panel was used to obtain the cultivation schemas of all dynamic and static cultivation plans applicable for continuous crop production in total eight cultivation layers during a maximum 180-day period. Various input conditions such as dissimilar clustering conditions, zigzag and square planting arrangements, and two crop types (Romaine and Korean lettuce cultivars) with different canopy growth behaviors were used in different simulations. A combinational cultivation plan including a dynamic plan with 1-2-3 clustering optimized with one static-dynamic hybrid layer, and two independent static layers was selected as the best cultivation plan with highest plant production for zigzag planting of Romaine lettuce. The increase in total plant production by this plan was found to be 7.5% (232 lettuce heads) higher than the alternative static plan, although the last crop output of this plan was supplied 10 days later than the static option. The best plan for cultivation of Korean lettuce in total eight cultivation layers was a dynamic plan with 3-5 clustering with one optimized hybrid static-dynamic layer. Comparing to static plan, the increase in total plant production by this plan was about 19% (512 lettuce heads) in 168 days. These results indicated that employment of multilayer dynamic cultivation for increasing the plant production is less beneficial for the crops with lower growth rate of canopy diameter, e.g., Romaine lettuce, while opposite of this is true about the crops with faster horizontal growth, e.g., Korean lettuce. Results of simulations revealed that the dynamic plans with inappropriate clustering conditions, excessive row spacing, and improper timing of growth stages would cause inefficiency in the utilization of crop growing area and has no preference over the less cumbersome and cheaper to implement static option. It was also found that multilayer dynamic cultivation is not an advantageous option for increasing the total plant production in short term (1-2 months) cultivation periods. Moreover, adopting a greater number of growth stages in executing a dynamic cultivation plan was not the determinant factor for enhancing the amount of plant production.
The purpose of the second part of this study is to design and develop an automated system with reduced manufacturing costs and new technical features for gully handling operation e.g., row spacing operation and controlled gully conveying, based on the procedure of executing the plans given by the cultivation schema. Obtaining a flexible and precise automated row spacing operation in different cultivation layers of the growing unit and providing bi-directional controlled conveying of gullies in vertical direction are the key objectives in this design. The developed automated gully convey-spacing system consists of three sub-systems including, i) a couple of 4-layer growing units equipped with gully load/unloading mechanisms, ii) an autonomous vehicle, and iii) the gully supplier. Different types of actuators, sensors, and a PLC extended with special modules as the controller unit of the system were employed. Since adjustment of row spacing values between the gullies in cultivation layers is the most critical functional objective of the automated system, the automated scheme of this operation was examined before using in the real operation through motion analysis of system virtual prototype by CAE simulation. No deviation from determined target row spacing values was observed at the end of simulations and thus, results of the motion analysis confirmed the effectiveness of the schemes proposed for row spacing operation in all defined spacing modes. Moreover, results of the experiments conducted to evaluate the ability of system in executing automated row spacing operation indicated that the average error in positioning of the gullies was 5.4, 5 and 8.5 % in spacing modes 1, 2, and 3, respectively. Experiments for testing the system functionality and the control schemes developed for other automated operations of the system such as layer targeting, manipulators locking, and displacement of gullies between different cultivation layers were also conducted with successful results. Using the output data obtained from the simulation module-cultivation schema in part one, a case study was also carried out to analyze and estimate the performance and operation time of the system during an integrated automated operation for executing the optimal cultivation plan of the Korean lettuce in total eight cultivation layers. Results of time analysis of system operation in different working days showed that an estimated time of 9 hours of automated operation is required for handling 220 gullies in eight cultivation layers. This operation time can be considerably reduced if faster linear actuators with higher duty cycles, and higher speeds of vertical gully conveying are used in the current developed system. Lower initial costs and easier control of the system due to less number of motors and actuators for running the automated operation in all growing units caused by centralization of all power sources in a single autonomous vehicle, and the ability to create a wide range of accurate row spacing values at any cultivation layer of the growing unit, simply through tuning of related parameters in the control program are some of new features of the developed automated system.
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dc.description.tableofcontentsAbstract
List of content
List of Figures
List of Tables
Nomenclature
Abbreviations

1.INTRODUCTION
1.1. Soilless culture and hydroponics
1.2. Automation
1.3. Multilayer and multistage cultivation
1.4. Necessity of research
1.5. Scope and objectives

2. REVIEW OF THE LITERATURE
2.1. Background of plant factory
2.2. Classification of plant factories
2.3. Crop mobility and spacing operation
2.4. Mechanical designs and systems for variable plant spacing
2.5. Effect of multistage cultivation and plant spacing

3.PART I- OBTAINING THE CULTIVATION SCHEMA FOR CONTINUOUS CROP PRODUCTION IN MULTILAYER GROWING UNITS
3.1.Introduction
3.2.Materials and methods
3.2.1.Layout and methods of multilayer cultivation
3.2.1.1.Static cultivation
3.2.1.2.Dynamic cultivation
3.2.2.Dimensional relations in multistage dynamic cultivation with square and zigzag planting
3.2.3.Time interval between crop outputs
3.2.4.Plant production rate(PPR)
3.2.5.Turning point day(TPD)
3.2.6.Modeling and simulation of cultivation plans
3.2.6.1.Modeling of cultivation plan
3.2.6.2.Description of the model
3.2.6.3.Simulation module with visual panel for obtaining the cultivation schema
3.2.6.4.Evaluation and optimization of multilayer cultivation plans by simulation results
3.2.6.5.Estimating the growth equations of canopy diameter
3.3.Results and discussion
3.3.1.Selecting the best fitted curve for canopy diameter growth
3.3.2. Effect of different clustering conditions on simulation results
3.3.3. Effect of gully width and length of cultivation layer on simulation results
3.3.3.1. Gully width
3.3.3.2. Length of cultivation layers
3.3.4. Combination of dynamic and supplementary static plans
3.3.5. Optimization of area utilization by hybrid static-dynamic layers
3.3.6. Selecting the optimal cultivation plan for each lettuce cultivar based on the simulation results
3.3.7. Numerical distribution of gullies
3.3.8. Schedule of crop displacement in dynamic plans
3.4.Conclusions

4.PART II- DEVELOPMENT OF AUTOMATED SYSTEM FOR MULTILAYER CULTIVATION WITH ADJUSTABLE GULLY ROW SPACING
4.1.Introduction
4.2.Materials and methods
4.2.1. Design criteria and assumptions
4.2.2. Design, development and control of the system
4.2.2.1.Sub-systems, working units and mechanisms
4.2.2.2. PLC, special modules and controller circuits
4.2.2.3.Sensors and actuators of the system
4.2.2.4.Design of human-machine interface(HMI)
4.2.2.5.Stepper motor control by PLC positioning modules
4.2.2.6.Selection of control method for positioning of linear actuators
4.2.2.6.1. Position control using internal hall sensors
4.2.2.6.2. Position control using analog distance sensors
4.2.3.Motion analysis of automated row spacing operation by virtual prototyping
4.2.3.1.Configuration of automated row spacing operation and relevant motion
4.2.3.2.Loading cycles and spacing modes
4.2.3.3. CAE simulation and motion analysis
4.2.4. Methods and control logics in the experiments of automated operation
4.2.4.1. Layer targeting
4.2.4.2. Manipulator locking
4.2.4.3. Loading-unloading of gullies and row spacing operation
4.2.4.4. Displacement of gullies from horizontal conveying line into a layer
4.2.4.5. Layer to layer displacement of gullies
4.2.4.6. Device allocation in control programs and signal trend monitoring graphs
4.2.5. Analysis of integrated operation of the automated system
4.2.5.1. Crop circulation and order of automated operations in different working days
4.2.5.2. Analysis of automated row spacing operation
4.3. Results and discussion
4.3.1. Motion analysis of lower and upper bars during serial loading cycles in simulated row spacing operation
4.3.2. Motion analysis of gully displacement in different spacing modes of simulated row spacing operation
4.3.3. Positioning of linear actuators
4.3.4. Noise Reduction in distance sensors by filter processing
4.3.5. Evaluation tests of automated operation
4.3.5.1.Layer targeting of bottom set manipulators
4.3.5.2.Locking of top set manipulators
4.3.5.3. Controlled loading-unloading of gullies in different spacing modes
4.3.5.4. Displacement of gullies from horizontal conveying line to layer 3
4.3.5.5. Displacement of gullies between layers 2 and 3
4.3.5.6. Functional problems in the operation of the automated system
4.3.6. Estimated performance of system operation by time analysis
4.4. Conclusions

5. SUMMARY AND FURTHER WORK

REFERENCES

Appendix A.1. Block diagram of the simulation VI for square planting
Appendix A.2. Block diagram of the simulation VI for zigzag planting
Appendix B.1. Details of regression analysis for different canopy growth models in Romaine lettuce
Appendix B.2. Details of regression analysis for different canopy growth models in Korean lettuce
Appendix C.1. PLC program-ladder diagram for layer targeting
Appendix C.2. PLC program-ladder diagram for manipulator locking
Appendix C.3. PLC program-ladder diagram for automated gully loading
Appendix C.4. PLC program-ladder diagram for automated displacement of gullies from horizontal conveying line to layer 3
Appendix C. 5. PLC program-ladder diagram for automated displacement of gullies from layer 3 to layer 2

Korean abstract
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dc.formatapplication/pdf-
dc.format.extent8381439 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectautomation-
dc.subjecthydroponic gully-
dc.subjectmultilayer growing unit-
dc.subjectprogrammable logic controller-
dc.subjectsimulation module-
dc.subjectstatic and dynamic cultivation-
dc.subject.ddc660-
dc.titleDevelopment of cultivation schema and automated gully convey-spacing system for multilayer plant factory-
dc.typeThesis-
dc.description.degreeDoctor-
dc.citation.pages279-
dc.contributor.affiliation농업생명과학대학 바이오시스템·소재학부-
dc.date.awarded2015-02-
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