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Zhong R.Y.,University of Hong Kong | Huang G.Q.,University of Hong Kong | Dai Q.Y.,Guangdong University of Technology | Zhang T.,Huaiji Dengyun Auto Parts Holding Co.
Journal of Intelligent Manufacturing | Year: 2014

Radio frequency identification (RFID) has been widely used in manufacturing field and created a ubiquitous production environment, where advanced production planning and scheduling (APS) might be enabled. Within such environment, APS usually requires standard operation times (SOTs) and dispatching rules which have been obtained from time studies or based on past experiences. Wide variations exist and frequently cause serious discrepancies in executing plans and schedules. This paper proposes a data mining approach to estimate realistic SOTs and unknown dispatching rules from RFID-enabled shopfloor production data. The approach is evaluated by real-world data from a collaborative company which has been used RFID technology for supporting its shopfloor production over seven years. The key impact factors on SOTs are quantitatively examined. A reference table with the mined precise and practical SOTs is established for typical operations and suitable dispatching rules are labled as managerial implicities, aiming at improving the quality and stability of production plans and schedules. © 2012 Springer Science+Business Media New York. Source


Yan Q.,Guangdong University of Technology | Song Y.,Guangdong University of Technology | Gao W.,Guangdong University of Technology | Kong H.,Huaiji Dengyun Auto Parts Holding Co.
Zhongguo Jixie Gongcheng/China Mechanical Engineering | Year: 2010

The transitional surfaces of a engine valve neck were processed with abrasive belt polishing method and the polishing characteristics of the transitional surfaces were analyzed, then the motion model and the contact state model were established. In the polishing process, the polishing linear velocity of the transitional surfaces changed drastically and the contact state between the abrasive belt wheel and the workpiece was variational, these will affect the processing stability and the machined surface quality. The contact state and the change rule between the engine valve transitional surface and the elastic belt wheel were studied, and the variation curve of the material removal in the polishing process was calculated theoretically, which is approximately in accordance with the experimental results. Source


Zhong R.Y.,Applied Technology Internet | Zhong R.Y.,Shenzhen University | Huang G.Q.,Applied Technology Internet | Lan S.,Applied Technology Internet | And 3 more authors.
Advanced Engineering Informatics | Year: 2015

Radio frequency identification (RFID) technology has been used in manufacturing industries to create a RFID-enabled ubiquitous environment, in where ultimate real-time advanced production planning and scheduling (APPS) will be achieved with the goal of collective intelligence. A particular focus has been placed upon using the vast amount of RFID production shop floor data to obtain more precise and reasonable estimates of APPS parameters such as the arrival of customer orders and standard operation times (SOTs). The resulting APPS model is based on hierarchical production decision-making principle to formulate planning and scheduling levels. A RFID-event driven mechanism is adopted to integrate these two levels for collective intelligence. A heuristic approach using a set of rules is utilized to solve the problem. The model is tested through four dimensions, including the impact of rule sequences on decisions, evaluation of released strategy to control the amount of production order from planning to scheduling, comparison with another model and practical operations, as well as model robustness. Two key findings are observed. First, release strategy based on the RFID-enabled real-time information is efficient and effective to reduce the total tardiness by 44.46% averagely. Second, it is observed that the model has the immune ability on disturbances like defects. However, as the increasing of the problem size, the model robustness against emergency orders becomes weak; while, the resistance to machine breakdown is strong oppositely. Findings and observations are summarized into a number of managerial implications for guiding associated end-users for purchasing collective intelligence in practice. © 2015 Elsevier Ltd. All rights reserved. Source


Yu W.,Guangdong University of Technology | Cheng Y.,Guangdong University of Technology | Sun Y.,Guangdong University of Technology | Xiao S.,Guangdong University of Technology | And 2 more authors.
Zhongguo Jixie Gongcheng/China Mechanical Engineering | Year: 2011

A precise spray forming device for hot forging dies was designed and fabricated based on spray forming principles. The key design points and working characteristics of the device were introduced. A high-frequency induction furnace was used to melt metals. The intermediate pot was removed and melted metals flowed out and atomized from the furnace to save energy. The novel atomizing nozzle was restrictive and vertical with a single chink and six auxiliary holes. Ceramic molds and water-cooling receiver were adopted in deposition system. The nozzle could be moved up and down in Z direction and the stage could be moved in X direction and rotated around Z axis. By the nozzle eccentricity and combination of three motions, spray formed dies with square or round cavities could be formed. The primary experiments show that the device has some advantages such as simple structure, low cost, heating fast and general etc., suitable for research work on precise spray forming of small work pieces. Source


Zhong R.Y.,Applied Technology Internet | Zhong R.Y.,Shenzhen University | Huang G.Q.,University of Hong Kong | Lan S.,University of Hong Kong | And 3 more authors.
International Journal of Production Economics | Year: 2015

Abstract Radio frequency identification (RFID) has been widely used in supporting the logistics management on manufacturing shopfloors where production resources attached with RFID facilities are converted into smart manufacturing objects (SMOs) which are able to sense, interact, and reason to create a ubiquitous environment. Within such environment, enormous data could be collected and used for supporting further decision-makings such as logistics planning and scheduling. This paper proposes a holistic Big Data approach to excavate frequent trajectory from massive RFID-enabled shopfloor logistics data with several innovations highlighted. Firstly, RFID-Cuboids are creatively introduced to establish a data warehouse so that the RFID-enabled logistics data could be highly integrated in terms of tuples, logic, and operations. Secondly, a Map Table is used for linking various cuboids so that information granularity could be enhanced and dataset volume could be reduced. Thirdly, spatio-temporal sequential logistics trajectory is defined and excavated so that the logistics operators and machines could be evaluated quantitatively. Finally, key findings from the experimental results and insights from the observations are summarized as managerial implications, which are able to guide end-users to carry out associated decisions. © 2015 Elsevier B.V. Source

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