Statecharts for Distributed Product Data Management System Modelling

Product data management (PDM) has been accepted as an important tool for the manufacturing industries. In recent years, more and mor e researches have been conducted in the development of PDM. Their research area s include system design, integration of object-oriented technology, data distri bution, collaborative and distributed manufacturing working environment, secur ity, and web-based integration. However, there are limitations on their rese arches. In particular, they cannot cater for PDM in distributed manufacturing e nvironment. This is especially true in South China, where many Hong Kong (HK) ma nufacturers have moved their production plants to different locations in Pearl R iver Delta for cost reduction. However, they retain their main offices in HK. Development of PDM system is inherently complex. Product related data cover prod uct name, product part number (product identification), drawings, material speci fications, dimension requirement, quality specification, test result, log size, production schedules, product data version and date of release, special tooling (e.g. jig and fixture), mould design, project engineering in charge, cost spread sheets, while process data includes engineering release, engineering change info rmation management, and other workflow related to the process information. Accor ding to Cornelissen et al., the contemporary PDM system should contains manageme nt functions in structure, retrieval, release, change, and workflow. In system design, development and implementation, a formal specification is nece ssary. However, there is no formal representation model for PDM system. Theref ore a graphical representation model is constructed to express the various scena rios of interactions between users and the PDM system. Statechart is then used to model the operations of PDM system, Fig.1. Statechart model bridges the curr ent gap between requirements, scenarios, and the initial design specifications o f PDM system. After properly analyzing the PDM system, a new distributed PDM (DPDM) system is proposed. Both graphical representation and statechart models are constructed f or the new DPDM system, Fig.2. New product data of DPDM and new system function s are then investigated to support product information flow in the new distribut ed environment. It is found that statecharts allow formal representations to capture the informa tion and control flows of both PDM and DPDM. In particular, statechart offers a dditional expressive power, when compared to conventional state transition diagr am, in terms of hierarchy, concurrency, history, and timing for DPDM behavioral modeling.

A parallel matching algorithm based on order relation for HLA data distribution management

In distribution simulation based on High-level architecture(HLA),data distribution management(DDM)is one of HLA services for the purpose of filtering the unnecessary data transferring over the network.DDM admits the sending federates and the receiving federates to express their interest using update regions and subscription regions in a multidimensional routing space.There are several matching algorithms to obtain overlap information between the update regions and subscription regions.When the number of regions increase sharply,the matching process is time consuming.However,the existing algorithms is hard to be parallelized to take advantage of the computing capabilities of multi-core processors.To reduce the computational overhead of region matching,we propose a parallel algorithm based on order relation to accelerate the matching process.The new matching algorithm adopts divide-and-conquer approach to divide the regions into multiple region bound sublists,each of which comprises parts of region bounds.To calculate the intersection inside and amongst the region bound sublists,two matching rules are presented.This approach has good performance since it performs region matching on the sublists parallel and does not require unnecessary comparisons within regions in different sublists.Theoretical analysis has been carried out for the proposed algorithm and experimental result shows that the proposed algorithm has better performance than major existing DDM matching algorithms.

Detector control system for Daya Bay Reactor Neutrino Experiment

The Daya Bay Reactor Neutrino Experiment is to measure the smallest mixing angle θ13.The experiment contains three major experiment halls,Daya Bay near site,Linao near site and far site,and two major kinds of detectors,antineutrino detector which is to detect the antineutrinos by the inverse beta-decay reaction in Gd-LS,and muon detector which is to study and reject cosmogenic backgrounds.The goal of the detector control system(DCS)is to operate and detect the detectors and keep them running in safety.In consideration of the limited fund of this system and manpower of working on this system,the LabVIEW is chosen to develop the detector control system.The architecture of DCS adopts the distributed data management which is based on client-server model.The server part is to detect and operate parameters from hardware,save data to database and release data to clients,the client is to receive data from the server.The detector control system contains three parts:the hardware part,the local control system and the global control part.The local control system includes high voltage supply system,low voltage supply system,VME crate system,temperature and humidity system,gas pressure system,and so on.