Includes references The main objective of this study was to model and simulate a reduced three-dimensional (3D) model for designing the driving system of an automatic vacuum packer. The 3D reduced model consisted of a pressing board sub-model, a taping sub-model, and a vibrating board sub-model. The reduced 3D model was parameterised using the variable of pouch thickness. The sub-models were driven by three virtual motors. To fulfil the required processing capacity of 6 pouches min-1 (pouch size of 45 cm by 35 cm; 5 kg-1 pouch) of the vacuum packer, three rotational motions for the motors were properly designed. When sub-models were driven according to the developed motions, the rated powers of the motors were estimated to be 100, 25, and 90 W, respectively. A real prototype of the vacuum packer was manufactured and controlled according to the developed motions to validate the simulation results. The motors determined by simulating the reduced 3D model drove the three units of the real prototype successfully. The developed motions of the motors satisfied the required operating sequences of the vacuum packer with a processing capacity of 6.7 pouches min-1. Vacuum-packaging tests showed that the success rate of the vacuum packer was 92.6%.
Biosystems engineering, 2010 Aug., v. 106, issue 4, p. 352-366.
global sensitivity measure, single axle grain cart dynamic system model, carts, equipment design, tractors, axles, dynamic models, velocity, and equipment performance
Includes references Tractor and towed implement system models have become increasingly important for model-based guidance controller design, virtual prototyping, and operator-and-hardware-in-loop simulation. Various tractor and towed implement models have been proposed in the literature which contain uncertain or time-varying parameters. Sensitivity analysis was used to identify the effect of system parameter uncertainty/variation on system responses and to identify the most critical parameters of the lateral dynamics model for a tractor and single axle grain cart system. Both local and global sensitivity analyses were performed with respect to three tyre cornering stiffness parameters, three tyre relaxation length parameters, and two implement inertial parameters. Overall, the system was most sensitive to the tyre cornering stiffness parameters and least sensitive to the implement inertial parameters. In general, the uncertainty in the input parameters and the system output responses were related in a non-linear fashion. With the nominal parameter values for a Mechanical Front Wheel Drive (MFWD) tractor, a single axle grain cart, and maize stubble surface conditions, a 10% uncertainty in cornering stiffness parameters caused a 2% average uncertainty in the system responses whereas a 50% uncertainty in cornering stiffness parameters caused a 20% average uncertainty at 4.5 m s−1 forward velocity. If a 5% average uncertainty in system responses is acceptable, the cornering stiffness parameters must be estimated within 25% of actual/nominal values. The output uncertainty increased as the forward velocity was increased.
Sørensen, C.G., Jørgensen, R.N., Maagaard, J., Bertelsen, K.K., Dalgaard, L., and Nørremark, M.
Biosystems engineering, 2010 Jan., v. 105, issue 1, p. 119-129.
HortiBot, robots, user interface, prototypes, equipment performance, plant nurseries, design, and agricultural machinery and equipment
Includes references Current service robots have relatively primitive behaviours and limited interaction with the environment. Technological foresights have indicated that the next generation of service robots will demonstrate a high degree of autonomy and reliability, have minimal impact on the environment, and will interact in a flexible way with the user. It is necessary therefore, to determine the functional requirements for a future energy-efficient robotic bioproduction system from the perspective of various stakeholders, together with the development of a high-level framework for designing and prototyping the common functionalities of mobile robots. This study presents technical guidelines for the design of a plant nursing robot. The methodology uses Quality Function Deployment (QFD) functionalities involving the identification of relationships between identified user requirements and the derived design parameters. Extracted important user requirements included: 1) adjustable to row distance and parcel size, 2) profitable, 3) minimize damage to crops, and 4) reliable. Lower ratings were attributed to requirements such as: 1) affection value, prestige, 2) look attractive, 3) out of season operations, and 4) use of renewable energy. Subsequent important derived design parameters included: 1) PreparedForModularTools, 2) ControlableByExternalModules, 3) SemiAutonomous, and 4) Local- and GlobalPositioningSystem. The least important design parameters included: 1) OpenStandardSoftware, 2) Well-builtAppearance, 3) WheelsWithInfiniteSteeringRotation, and 4) InternalSafetySystem. The study demonstrates the feasibility of applying a systematic design technique and procedures for translating the ‘consumer's voice’ into the design and technical specifications of a robotic tool carrier to be used in bioproduction.