Development of a function block designer for collaborative process planning
ABSTRACT The research objective is to develop methodologies and framework for collaborative process planning and scheduling, supported by a real-time monitoring system in distributed environments. A function block enabled collaborative process planning approach is proposed to handle various dynamic changes during process plan generation and execution. This paper focuses on collaborative process planning, particularly on the development of a function block designer As function blocks can sense environmental changes, it is expected that a so generated process plan can adapt itself to the changes with dynamically optimized solutions for plan execution and process monitoring.
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ABSTRACT: Process planning and scheduling are two of the most important functions in the manufacturing system. Traditionally, process planning and scheduling were regarded as separate tasks performed sequentially, where scheduling was implemented after process plans had been generated. However, their functions are usually complementary. If the two systems can be integrated more tightly, greater performance and higher productivity of manufacturing system can be achieved. In this paper, a new hybrid algorithm (HA) based approach has been developed to facilitate the integration and optimization of these two systems. To improve the optimization performance of the approach, an efficient genetic representation, operator and local search strategy have been developed. Experimental studies have been used to test the performance of the proposed approach and to make comparisons between this approach and some previous works. The results show that the research on integrated process planning and scheduling (IPPS) is necessary and the proposed approach is a promising and very effective method on the research of IPPS.International Journal of Production Economics 08/2010; 126(2):289-298. DOI:10.1016/j.ijpe.2010.04.001 · 2.08 Impact Factor
Conference Paper: Function Block Application in ARM-based Field Intelligent Instruments[Show abstract] [Hide abstract]
ABSTRACT: The design and implementation of function block application (FBA) in intelligent instruments is the core to the implementation of control function from intelligent field instruments. Function blocks represent the basic automatic function implemented by function block application. In this paper, the features of function block in intelligent field instruments based on ARM processor are analyzed, method and scheme for design and implementation of function block application in ARM-based intelligent instrument are proposed, which are based on function block parameters-type description, data partition and storing structure in intelligent instruments. 4 data-storing segments are allocated in static memory of intelligent instrument, which are instruction segment, input segment, output segment and contained parameters segment. Static pointers to respective data-storing segments are created, with which any parameters information used in function block application can be found quickly combined with the data and information stored in instruction segment, by which the connection and communication between function blocks are implemented. A implementation method for the operation mode of multi FBA (MFBA) based on map of data segment and memory allocation in intelligent instruments to virtual registers is proposed. The structure and implementation in C++ for the instruction code in instruction segment are also presented. The experimental and operational results show the design and implementation scheme for function block application in intelligent instruments with ARM kernel are scientific and reasonable, stable and efficient in operation.Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on; 08/2007
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ABSTRACT: In traditional approaches, process planning and scheduling are carried out sequentially, where scheduling is done separately after the process plan has been generated. However, the functions of these two systems are usually complementary. The traditional approach has become an obstacle to improve the productivity and responsiveness of the manufacturing system. If the two systems can be integrated more tightly, greater performance and higher productivity of a manufacturing system can be achieved. Therefore, the research on the integrated process planning and scheduling (IPPS) problem is necessary. In this paper, a new active learning genetic algorithm based method has been developed to facilitate the integration and optimization of these two systems. Experimental studies have been used to test the approach, and the comparisons have been made between this approach and some previous approaches to indicate the adaptability and superiority of the proposed approach. The experimental results show that the proposed approach is a promising and very effective method on the research of the IPPS problem.Expert Systems with Applications 06/2012; 39(8):6683–6691. DOI:10.1016/j.eswa.2011.11.074 · 1.97 Impact Factor