Hierarchical control of complex manufacturing processes

The need for changing the control objective during the process has been reported in many systems in manufacturing, robotics, etc. However, not many works have been devoted to systematically investigating the proper strategies for these types of problems. In this dissertation, two approaches to such problems have been suggested for fast varying systems. The first approach, addresses problems where some of the objectives are statically related to the states of the systems. Hierarchical Optimal Control was proposed to simplify the nonlinearity caused by adding the statically related objectives into control problem. The proposed method was implemented for contour-position control of motion systems as well as force-position control of end milling processes. It was shown for a motion control system, when contour tracking is important, the controller can reduce the contour error even when the axial control signals are saturating. Also, for end milling processes it was shown that during machining sharp edges where, excessive cutting forces can cause tool breakage, by using the proposed controller, force can be bounded without sacrificing the position tracking performance. The second approach that was proposed (Hierarchical Model Predictive Control), addressed the problems where all the objectives are dynamically related. In this method neural network approximation methods were used to convert a nonlinear optimization problem into an explicit form which is feasible for real time implementation. This method was implemented for force-velocity control of ram based freeform extrusion fabrication of ceramics. Excellent extrusion results were achieved with the proposed method showing excellent performance for different changes in control objective during the process --Abstract, page iv

Implementation of Distributed Control System for Rice Mill Using C#

The paper presents the distributed control system for rice mill using C# language. The real-time manufacturing system can be implemented by utilizing the signal from the real time control units that is more operative than other old-fashioned control systems in the extent of modern industrial days. The software-based Distributed Control System (DCS) is novel fashionable than any other conventional control systems in the state-ofthe-art manufacturing developments. This research study emphasizes on the implementation of the DCS-based rice mill using visual C#.net. The Industrial Ethernet (IE) is realized between the top level controller for the operator and the controlled station for the remote devices. The model of client-server approach is more appropriate for the automation and manufacturing research purposes. In this study, the computer graphical simulation of the complete control development is depicted in real-time status quo by visual C# language under Visual Studio 2008 software. The parallel ports in the computers of remote terminal level and the master terminal level controllers have been interconnected with port interface coding by visual C# program

Inteligencia computacional embebida para la supervisión de procesos de microfabricación

En este artículo se presenta el desarrollo e implementación de una estrategia de supervisión de un proceso de microfabricación. El método propuesto está basado en técnicas de Inteligencia Artificial, embebidas en una plataforma de tiempo real para la monitorización inteligente de procesos. La contribución se centra fundamentalmente en dos modelos para la estimación en proceso (on-line) de la rugosidad superficial (Ra), a partir de la mínima información sensorial posible. El primero de estos modelos está basado en un algoritmo para el modelado híbrido incremental (HIM), cuyos parámetros óptimos se obtienen a partir de un método estocástico, representado por el temple simulado. El segundo está basado en un algoritmo de agrupamiento borroso generalizado (GFCM), incorporado en un sistema de inferencia de una estructura neuroborrosa. Esta estrategia se embebe en una plataforma para una ejecución en tiempo real y en paralelo junto con el resto de estrategias y métodos. Finalmente, se hace una validación en una plataforma experimental, utilizada como soporte tecnológico, lo cual permite el aprovechamiento mutuo de las experiencias alcanzadas y la mejora de los resultados obtenidos. Este resultado científico y técnico, supone un salto cualitativo importante sin precedentes en la investigación industrial en el campo de la microfabricación

CAM-Rob postprocessor based on a fuzzified redundancy resolution scheme

This work highlights the applicability of different redundancy resolution schemes to the postprocessing stage from a computer-aided manufacturing (CAM) system to an industrial redundant workcell. The inverse kinematic problem for redundant manipulators is not straightforward and, therefore, it is commonly solved using an iteratively approach based on redundant resolution schemes at the velocity level. In this work, two conceptions of redundancy resolution schemes are evaluated and a novel fuzzy inference system is developed to improve the performance during the toolpath tracking in order to avoid singularities and to maintain a preferred reference posture. For this purpose, the fuzzy inference engine properly adjusts the weight of each joint in the calculation of the performance criterion vectors. The proposed approach is validated in the real prototyping of a windmill blademold using a KUKA KR15/2manipulator mounted on a linear track and synchronized with a rotary table. To the authors knowledge, the proposed method and the results shown are novel in the context of postprocessing techniques from CAM systems to industrial robots devoted to milling works. With the same guidelines, the postprocessor programmed inside the CAM system is expected to be easily applicable not only to other industrial robots, but also for different applications such as welding or painting labors.This research is partially supported by the Technical University of Valencia (PAID-00-09-3092, PAID-05-11-2640), project PROMETEO 2009/063 of Generalitat Valenciana and research project DPI2009-14744-C03-01 of the Spanish Government.Andrés De La Esperanza, FJ.; Gracia Calandin, LI.; Tornero Montserrat, J. (2012). CAM-Rob postprocessor based on a fuzzified redundancy resolution scheme. International Journal of Advanced Manufacturing Technology. 62(5):705-718. https://doi.org/10.1007/s00170-011-3836-yS705718625Andres J, Gracia L, Tornero J (2011) Calibration and control of a redundant robotic workcell for milling tasks. Int J Comp Int Manuf 24(6):561–573Patel RV, Shadpey F (2005) Control of redundant robot manipulators: theory and experiments. Springer, New YorkHartenberg RS, Denavit J (1955) A kinematic notation for lower pair mechanisms based on matrices. Trans ASME J App Mech 77:215–221Andres J, Gracia L, Tornero J (2009) Inverse kinematics of a redundant manipulator for CAM integration. An industrial perspective of implementation, Proceedings of the 2009 IEEE International Conference on Mechatronics, MalagaWhitney DE (1969) Resolved motion rate control of manipulators and human prostheses. IEEE Trans Man-Machine Syst 10(2):47–53Whitney DE (1972) The mathematics of coordinated control of prosthetic arms and manipulator, ASME J. Dyn Sys Meas Cont 94(4):303–309Angeles J (2003) Fundamentals of robotic mechanical systems: theory, methods and algorithms. Springer, New YorkHuo L, Baron L (2008) The joint-limits and singularity avoidance in robotic welding. Industrial Robot 35(5):456–464Liégeois A (1977) Automatic supervisory control of the configuration and behavior of multibody mechanisms. IEEE Trans Syst Man Cybern SMC-7:245–250Gracia L, Andres J, Tornero J (2009) Trajectory tracking with a 6R serial industrial robot with ordinary and non-ordinary singularities. Int J Cont Auto Syst 7(1):85–96Angeles J, López-Cajún CS (1992) Kinematic isotropy and the conditioning index of serial robotic manipulators. Int J Robot Res 11(6):560–570Khan WA, Angeles J (2006) The kinetostatic optimization of robotic manipulators: the inverse and the direct problems. J Mech Des 128(1):168–178Siemens Corp (2009) NX Documentation. In: {$UGII_base_dir}\UGDOCMaza JI, Ollero A (2000) Herramienta MATLAB-Simulink para la simulación y el control de robots manipuladores y móviles, Actas de las XXI Jornadas de Automática, Sevilla, SpainRoger Jang JS, Gulley N (2008) Fuzzy logic toolbox: user’s guide; revised for version 2.2.7. The Math Works, Inc.Qdesign SRL (2007) CAD-CAM off line programming for industrial robots. ROBOmove on line help v. 2.0 [online]. Available from: http://www.qdrobotics.com/eng/robomove.php . Accessed 28 Nov 2011Andrés J, Gracia L, Marti H, Tornero J (2009) Toolpath postprocessing for three axes milling in redudant robotic workcells by means of fuzzy integration in a CAM platform, Proceedings of the IEEE International Conference on Mechatronics, Malaga, Spai

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Implementation and testing of a CAM postprocessor for an industrial redundant workcell with evaluation of several fuzzified Redundancy Resolution Schemes

This paper describes the implementation of a postprocessor to adapt the toolpath generated by a CAM system (NXTM) to a complex workcell of eight joints (namely, a KUKA KR15/2 manipulator mounted on a linear track and synchronized with a rotary table), devoted to the rapid prototyping of 3D CAD-defined products. Previously, it evaluates several Redundancy Resolution Schemes at the joint-rate level for the configuration of the postprocessor, dealing not only with the additional joints but also with the redundancy due to the symmetry on the milling tool. The use of these redundancies is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. In addition, two proper fuzzy inference engines actively adjust the weight of each joint in these tasks. The postprocessor is validated in a real prototyping of a Valencian Falla.This research is partially supported by the Technical University of Valencia (PAID-00-09), project PROMETEO 2009/063 of Generalitat Valenciana and research project DPI2009-14744-C03-01 of the Spanish Government.Andrés De La Esperanza, FJ.; Gracia Calandin, LI.; Tornero Montserrat, J. (2012). Implementation and testing of a CAM postprocessor for an industrial redundant workcell with evaluation of several fuzzified Redundancy Resolution Schemes. Robotics and Computer-Integrated Manufacturing. 28(2):265-274. https://doi.org/10.1016/j.rcim.2011.09.008S26527428

AN ON-LINE INTELLIGENT ADAPTIVE CONTROLLER FOR MANUFACTURING OPERATIONS BASED ON AN OPEN ARCHITECTURE

In the development of the unattended and self-adjust machining system, where the human operator must be replaced by a Computer Numerical Control, the control system should properly process information with its varying environment in an intelligent way. The intelligent CNC must be able to recognize, in real time, major problems of operation connected to the machining process like chipping problems or tool breakage. To do that, the CNC intelligent system must be able to receive, process, and analyze inputs from multiple types of external sensor attached to it. This approach can only be possible on the base of an Open Architecture. The author of this paper proposes the use of fuzzy logic to develop an intelligent adaptive controller for manufacturing operations based on an open architecture that must be able to face problems of control, monitoring and fault diagnosis in real time

Monitorización inteligente en tiempo real del acabado superficial de micro-piezas basado en el modelado híbrido incremental

Este trabajo propone la aplicación de una estrategia de modelado híbrido incremental (HIM) para la estimación en tiempo real de la rugosidad superficial en procesos de micromecanizado. Esta estrategia comprende fundamentalmente dos pasos. En primer lugar, se obtiene un modelo híbrido incremental representativo del proceso de micromecanizado. El resultado final de este modelo es una función de dos entradas (avance por diente cuadrático y vibración media cuadrática (rms) en el eje Z) y una salida (rugosidad superficial). En segundo lugar, se evalúa el modelo híbrido incremental en tiempo real para obtener la rugosidad superficial. El modelo se corrobora experimentalmente mediante su integración en un sistema embebido de monitorización en tiempo real del acabo superficial. La evaluación del prototipo demuestra una tasa de éxito en la estimación de la rugosidad superficial del 83%. Estos resultados son la base para el desarrollo de sistemas embebidos en la monitorización del acabo superficial de micro-piezas en tiempo real y el posterior desarrollo de una herramienta a nivel industria

Adaptive control optimization in micro-milling of hardened steels-evaluation of optimization approaches

Nowadays, the miniaturization of many consumer products is extending the use of micro-milling operations with high-quality requirements. However, the impacts of cutting-tool wear on part dimensions, form and surface integrity are not negligible and part quality assurance for a minimum production cost is a challenging task. In fact, industrial practices usually set conservative cutting parameters and early cutting replacement policies in order to minimize the impact of cutting-tool wear on part quality. Although these practices may ensure part integrity, the production cost is far away to be minimized, especially in highly tool-consuming operations like mold and die micro-manufacturing. In this paper, an adaptive control optimization (ACO) system is proposed to estimate cutting-tool wear in terms of part quality and adapt the cutting conditions accordingly in order to minimize the production cost, ensuring quality specifications in hardened steel micro-parts. The ACO system is based on: (1) a monitoring sensor system composed of a dynamometer, (2) an estimation module with Artificial Neural Networks models, (3) an optimization module with evolutionary optimization algorithms, and (4) a CNC interface module. In order to operate in a nearly real-time basis and facilitate the implementation of the ACO system, different evolutionary optimization algorithms are evaluated such as particle swarm optimization (PSO), genetic algorithms (GA), and simulated annealing (SA) in terms of accuracy, precision, and robustness. The results for a given micro-milling operation showed that PSO algorithm performs better than GA and SA algorithms under computing time constraints. Furthermore, the implementation of the final ACO system reported a decrease in the production cost of 12.3 and 29 % in comparison with conservative and high-production strategies, respectively