|Title:||Sub-real time data exchange for dispersed manufacturing systems|
|Subject:||Hong Kong Polytechnic University -- Dissertations|
Manufacturing resource planning -- Data processing
Production management -- Data processing
Real-time data processing
|Department:||Department of Industrial and Systems Engineering|
|Pages:||xiii, 210 leaves : ill. (some col.) ; 30 cm|
|Abstract:||Dispersed manufacturing systems are popular in the present era. Under such circumstances, the connections between worldwide-dispersed activities are often made by telephone, e-mail and facsimile, etc. thus overcoming to some extent physical geographical barriers. It is very clear that knowledge of fabrication statuses is very important to a world-class manufacturer because the fluctuations in the fabrication processes directly affect the logistic associated operations. However, there are substantial obstacles to getting a good understanding about plant operations at a remote decision-making center As a consequence, only incomplete details are gathered and it is usually difficult to avoid variations in interpretation arising from the data filtering processes. Such a scenario surely has a negative influence on a system. The objective of this research is to develop a generic approach that can be applied, with little configuration, in order to look at a plant and determine how efficiently it is functioning. The ultimate target is to achieve transparency of the fabrication processes so that distant clusters can interact efficiently. The current fabrication monitoring methods can be classified into two main types: offline and on-line monitoring. The former is based on predetermined data for estimating and predicting the results during the fabrication process. This system, based on such predicted information, enables decisions to be made but it does not reflect the fabrication conditions in a real-time manner. The second one is based on on-line information as one of the inputs of the analysis system. The system compares the on-line information and the recorded data to reflect the real-time conditions of the fabrication process. However, it does not directly tell the healthiness of the process, but it suggests "what to do" scenarios, for example whether to use the Rea;-I-CIM or the fluid flow approach. The approaches discussed in this research area are usually very complex, and difficult to explain clearly. In traditional approaches such as the CIM, the complicated hardware/software integration and the signal conditioning take up a significant amount of resources. Moreover, this all results in a dedicated system which is only suitable for a particular application and engineers have to start from scratch every time when faced with a different application. The new approach takes into consideration both the hardware and the mathematical model, simultaneously. Subsequently, a methodology to monitor a plant which needs little configuration, has been developed. The developed methodology makes use of simple counting devices attached at the transition points along a fabrication line to count the number of entities that pass. With the help of the specially formulated mathematical model, both the quantitative and qualitative issues can be monitored. The corresponding problematic locations can also be indicated. All this is important managerial information and thus, it provides a useful tool for bridging fabrication processes an management sites at distant locations. However, it does not mean that the new model will replace other technologies; it only gives a macro view of the fabrication process. Test cases were established to observe the behaviors of the methodology in responding to various scenarios. To facilitate the investigations, simulation software was employed to simulate a flow line with fluctuations caused by predetermined reasons. The results showed that it could detect problems such as the poor quality of materials, machine breakdowns, process slowdowns, etc. also the corresponding problematic locations could also be indicated by watching the varying trends. All these factors make up important managerial information so it provides a useful tool for linking the management site to distantly located clusters of manufacturing sites.|
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