CSP-based Study on Distributed PDM and Consistency Control Technique for Aero-Subcontract Production

To carry out the share of product data between different PDM (product data management) systems, this paper provides a domain ontology model of PDM system which is based on ontology and constructed by Protege3.1. This model consults the framework of PDM system in STEP PDM schema, uses the UML class figure to describe the relationship between the system classes. Finally by data mining the mass data of PDM, ontology libraries can be fully exploited and used, information and knowledge can be acquired for analyze and decision-making of enterprise

Product data modelling and management has become an increasingly feature for enterprises in order to strengthen their competitive position. Modelling can be regarded as a requirement analysis, whilst management is a means to apply powerful application to product data. This data describes the status of a product during the whole product life cycle as well as the transformation of one state to another. Operations performed in one phase of the product will definitely have impact on later phases and the product itself. It is of interest to analyse this impact and to extract methods to assist the designer of a product in order to improve the quality of a product. Based on an internal analysis of European research projects, this paper shows how product data management is used during the product life cycle of a product and how it can improve a products quality. The goal is to derive support strategies for the designer based upon the data structure and knowledge representation used within these projects. It describes an approach to measure product data structures and design knowledge representations. Different levels of complexity concerning the managed product knowledge in design support systems have been identified as well as different design support strategies.

Product Data Management (PDM) systems and their offspring, Collaborative Product Development and Product Lifecycle Management technologies, aim to bring engineering enterprises together, allowing seamless interoperability between different departments and throughout the extended enterprises. However, there are a number of shortcomings in the current crop of commercially available systems, such as the lack of design knowledge sharing, links with Enterprise Resource Planning systems, knowledge management tools and a generic standard for PDM system implementation. This paper presents a proposed software solution to some of the above problems. In particular, the paper describes methodologies being developed that are aimed at overcoming the lack of analysable product information at the conceptual stage of product design and manufacturing evaluation, along with the integration of such a concept design tool within a distributed environment. A leading PDM system is used to manage all the information and knowledge that is made available to internet/intranet users in a controlled manner. The international standard for exchange of product data model (STEP) is implemented to enable the integration of the design environment with manufacturing and enterprise resource management systems. In addition, the paper also introduces three other recent/ongoing projects, being carried out at Cranfield University, in the application of PDM, knowledge management and STEP standard for integrated manufacturing businesses.

How to ensure the information published is accurate and cannot be modified in the heterogeneous Network Environment,this is a difficult program to provide ticketing services through Middleware. This paper expounds the connection middleware design that between collaborative services platform and heterogeneous ticketing system, studies the interface specification and protocol specification of connection middleware and different subjects of heterogeneous ticketing system, realizes the function of ticket of collaborative services platform as well as maximizes the system's security and compatibility.

PDMAR (Production Data Management and Reporting) is software to manage oil and gas operation and production data. It supports integration of automation system and business network that providing fast and accurate production information. It includes production database, data acquisition from automation level, data entry modules, oil and gas allocation modules, formula builder, expert system, data validation, security, asset management modules, link to other applications, and integrated reporting and data browser. It provides customizable configuration modules that enable user to create and modify table that appropriate with their field condition. PDMAR uses commercial RDBMS to store data. It uses latest Microsoft .NET Framework technology and web services to keep pace on speed, efficient, and effective data storage and transfer. They would browse daily report that contains daily production, operation, latest well test, HSE status, oil and gas allocation, chemical storage, transportation, utilities, etc through web interface easily. Data interfacing are performed automatically from major commercial historian database as well as oil and gas production software. PDMAR has been installed in many onshore and offshore facilities. With optimized data transfer, operator will transfer data in less time. Data link between control layer and management level automates field operator's job thus give more reliable and precise data capture. For remote and distributed well field, mobile system that incorporated with handheld device help operator to record important data to main database using automatic synchronization. Engineer and management use less time to analyze production and operation data than before. They receive daily production report in precise time every morning through email and website. They now focuses on analyze data than collecting data before. There is only one validated data version that is used for daily report.

High-variety production like mass customization is facing the challenge of effective variety management, which needs to deal with numerous variants of both product and process in order to accommodate diverse customer requirements. To utilize commonality underlying product diversity and process variation, it has been widely accepted as a practice to develop product families, in which a set of similar variants share common product and process structures and variety differentiates within these common structures. Based on such variety implication, this paper proposes a data structure, called generic Bill-of-Materials-and-Operations (BOMO), by unifying Bills- of-Materials (BOM) and routing data into a single set in order to synchronize multiple perspectives on variety such as customer ordering, product engineering, and operations planning. A generic structure is accordingly developed for characterizing variety effectively. The merits of the generic BOMO for integrated product and production data management are detailed in terms of order processing, engi neering change control, production job planning, cost accounting, as well as integrated material and capacity planning. An implementa tion of the proposed generic BOMO methodology in customized souvenir clock manufacturing is also reported.

Among the well-known enterprise application software modules, product data management (PDM) and enterprise resource planning (ERP) have played major roles in the design and production departments respectively. Among those, PDM helps design engineers to manage the product data and product development process, and ERP acts as the main tool for order, production and inventory related processes. There are a few duplicated functions among these systems such as BOM management. However, very few works addressed building a bridge among the systems. On the other hand, an agent-based approach has been applied in the collaboration of shop floor equipment for some time. Basically, each agent acts like a machine controller that can take charge of the respective equipment and communicate with other agents as well. This research applies similar concepts to bridge the gaps between PDM and ERP systems and to support the collaboration activities of the two systems. A three-stage framework was proposed to develop the agent-based collaboration system. In the concept stage, the modelling tools such as VAD and eEPC were used to capture collaboration requirements between PDM and ERP. In the design stage, a UML-based analysing method MaSE was used to develop the agent-based system. Also, an agent development tool ZEUS was used to generate agent code. Finally, in the implementation stage, a PDM/ERP collaboration system was developed to support the designer in making decisions about the replacement parts requirement analysis.

Production Data Management and Surveillance in Shale Operations presents both the benefits and challenges of field data management in shale production operations. The examination of the lifecycle of field production data the paper offers will lead us to explore issues of surveillance, predictive analytics, enterprise data availability, data quality, integration, and regulatory compliance from the perspective of unconventional resource operators. The paper also includes case studies that detail the implementation and lessons learned from five shale oil and gas producers. Factory drilling in unconventional plays leads to highly paced operations and a large number of wells, which in turn leads to the generation of an enormous amount of field data that must all be captured, processed and turned into actionable information for surveillance, operational accounting and HSEQ compliance. This data, much of which is collected by field personnel at the well site, includes fluid volumes and operating conditions as well as run tickets, tank battery inventories, sales volumes, equipment status, and chemical usage. Also, increased sensitivity to environmental issues around shale plays requires operators to closely manage water, emissions and other environmentally impactful measurements, all of which must be collected, monitored and reported. Maintaining the quality of the gathered data is paramount as poor data can lead to costly consequences, from under- optimized production to fines for inaccurate reporting. Integrating surveillance processes with the field systems will promote consistency and accuracy. In conjunction, tools that provide asset-specific variances, alerts and visualizations will help identify operational issues immediately, allowing for swift alignment of the field team with corporate goals. Raw production measurements collected in the field are processed to produce allocated production volumes at each well and zone. These allocated volumes are then put to use by different departments across the operator’s enterprise, in their planning, forecasting, operations management, revenue accounting, marketing, regulatory and partner reporting. Field information and production data lie at the heart of operations management for all operators. Production Data Management and Surveillance in Shale Operations submits multiple case studies on the collection, analysis and distribution of this data, along with the best practices employed in shale plays.

The Internet, Web, and Globalization are inducing new product development paradigms such as crowd sourcing, mass collaboration, and open innovation. Engineering, design, and manufacturing organizations who adopt these paradigms will need to address the product data integration problem because complex product data will be associated with these emerging product development paradigms in the socio-sphere. In particular, product data will be dispersed globally and will be encoded in many different formats. Moreover, mechanical, electrical, and software data for complex products are currently handled in separate product data management systems with no automated sharing of data between them or links between their data. This is a significant drawback with regard to supporting collaborative and integrated product design. Unfortunately, this drawback will become worse for platforms seeking to utilize product design in the socio-sphere. Consequently, advances in product data management will be needed in order for companies to fully realize the benefit of adopting such socio-sphere product development platforms. Semantic computing is one technological family well suited to solve a variety of the challenges associated with product development in the socio-sphere. As such, this chapter presents a theory of semantic association systems along with a description of its application to product data integration in the socio-sphere.

The product service enables companies to provide their products and services with least negative environment effects, and to keep and reuse valuable resources for their next products and services. To support the integrated and collaborative development of the product service, this paper proposed architecture of the extended Product Data Management (PDM) that can integrate design of products and planning of manufacturing process and customer services, based on the consistent and comprehensive PDM databases. The architecture enables design, manufacturing, and service engineers to express their products and services efficiently, with sharing the consistent product data, engineering changes, and both economical and environmental evaluations on their design alternatives. The architecture was implemented with a prototype PDM system, and validated through an example product. The result shows that the PDM architecture can support the integrated design for products, manufacturing process, and customer services, and provide a collaborative product service development environment for the design, manufacturing and service engineers.

Requirements and strategies for the retention of automotive product data

Enterprise modelling and system support

Product Data Management (PDM) systems can help companies save a significant amount of time and money in large-scale product development. Searching similar CAD models of products is a key to facilitate the management of product data. This paper discusses 3D model searching techniques and PDM in the application domain of mechanical CAD. For mechanical CAD models, both geometrical information and topological information are important for similarity assessment. We proposed two shape signatures to describe the geometry and the topology of a mechanical CAD model, respectively. A Relevance Feedback (RF) mechanism is introduced to combine the two dissimilarity distances measured by the two signatures. Experiments are conducted to evaluate the performance of the proposed method.

With the infusion of information technologies into product development and production processes, effective management of product data is becoming essential to modern production enterprises. When an enterprise-wide Product Data Manager (PDM) is implemented, PDM designers must satisfy the requirements of individual users with different job functions and requirements, as well as the requirements of the enterprise as a whole. Concern must also be shown for the interrelationships between information, methods for retrieving archival information and integration of the PDM into the product development process. This paper describes a user-driven approach applied to PDM design for an agile manufacturing pilot project at Sandia National Laboratories that has been successful in achieving a much faster design-to-production process for a precision electro mechanical surety device.

Conventional Product Data Management (PDM) supports aspects of information management but don’t promote the application of target oriented design methodologies like ‘Axiomatic Design’. For Manufacturing System Design PDM has to manage the actual targets, to direct a target-oriented procedure, and to manage objects for evaluation. Targets result from customers and manufacturers. The definition of ‘Functional Requirements’ and ‘Design Parameters’ has to be organized between different core competencies at different times and places. The goal is the configuration of a PDM framework supporting distributed collaborative manufacturing system design in a ‘Axiomatic Design’ oriented way. Based on an axiomatic approach, the implementation of this methodology in a distributed PDM framework is presented. For this, the necessary procedure and controls of ‘manufacturing system design’, information architecture and data interfaces to other software tools are considered and then the paper describes necessary metamodel.