A process model for concurrent design in manufacturing enterprise information systems.
ABSTRACT In manufacturing enterprise information systems, concurrent design process is one of the focuses of research on design process management. This study proposes a novel process model for concurrent design based on unified modelling language (UML) and polychromatic sets theory. Model primitives and constructs of UML activity diagram, concurrent design activities, and dynamic changes of concurrent design process are described in the polychromatic sets contour matrix. Based on polychromatic sets theory, the model reduction rules and algorithm are proposed. With the feature-based part design and process planning, a UML model of concurrent design process is developed and mapped into polychromatic sets contour matrix model. The dynamic change, model reduction, path search and time consumption of concurrent design process are analysed, and the direction for improving concurrent design process and shortening product development cycle is suggested.
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ABSTRACT: In order to address the resource service optimal-selection (RSOS) and composition problem in manufacturing grid (MGrid) system and provide high-quality service to users, an MGrid RSOS and composition framework (MGrid-RSOSCF) is investigated in this study. The process of RSOS and composition is divided into the following five steps in MGrid-RSOSCF: (1) decomposing the submitted manufacturing task into several subtasks (i.e. single resource service requested task) if the submitted task is a multiple resource service requested task; (2) searching out the qualified resource service for each decomposed subtask and generating the corresponding candidate resource service set; (3) retrieving, evaluating and comparing the quality of service (QoS) for each candidate resource service, and provide data for service optimal-selection and composition –if the submitted task is a single resource service requested task; (4) evaluating synthetically the overall quality of each candidate resource service and ranking them, and selecting the optimal one for the task – if the submitted manufacturing task is an multiple resource service requested task; (5) selecting one candidate resource service from each candidate resource service set and constructing a new composite resource service according to the submitted task requirements, and collecting all the possible resource service composite execution paths (RSCEP) and selecting the optimal paths to execute the task. The proposed MGrid-RSOSCF consists of five layers and each layer provides the corresponding necessary services and algorithms to address one problem mentioned above. The five layers are: (1) T-layer, responsible for MGrid task decomposition; (2) S-layer, responsible for resource service match and search; (3) Q-layer, responsible for QoS processing; (4) O-layer, responsible for evaluating and ranking the candidate resource service and (5) C-layer is responsible for resource service composition and optimal-selection. The case study and comparison of performances of the algorithms demonstrate that the proposed methods are sound on success rate and executing efficiency.Enterprise IS. 01/2012; 6:237-264.
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ABSTRACT: As quality requirements play a crucial role in supply chain management (SCM), enterprises require appropriate information architecture to address evolving supply chain needs. Information architecture for supply chain quality management has drawn much attention from the research community and the industry in recent years. Recent research explores the role of service-oriented architecture (SOA), RFID, agent, workflow management, and the Internet of Things (IoT) as an enabler of real-time quality management and control in the supply chain. This paper attempts to analyse the current state of the art in information management for supply chain quality management, reviewing the current research and development in information architecture for supply chain quality management, and highlighting some of the key technologies that have the potential to significantly improve the performance of supply chain quality management. It is our hope that this paper will motivate the supply chain quality management community in deploying the technologies along with their breakthroughs with the objective of realising automated supply chain quality management.International Journal of Production Research 01/2011; 49(1):183-198. · 1.46 Impact Factor
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