Deeper Insights into Product Development Through Data Visualization Techniques

Product Data Management (PDM) systems provide a means for sharing and controlling documents in collaborative product development. PDM are used in industrial applications for long-term archival of product information, to enhance collaboration and communication throughout the design process, support distributed design teams through advanced document sharing, track changes in product information, and control design documents ranging from requirements information to CAD. However, undergraduate mechanical engineering students typically graduate with limited or no exposure to PDM systems. This paper investigates the benefits and challenges associated with modern PDM systems. Moreover, the need for PDM systems in undergraduate education are discussed and means for integrating this technology is presented. A survey of engineering institutions in the U.S. is completed to understand the current usage in academic settings. Specifically, this paper describes appropriate course and project support of PDM systems.

The objective of this chapter is to provide an introduction to Product Data Management (PDM) systems in the PLM environment. The chapter will help readers working in PLM Initiatives understand the importance of PDM systems and participate in activities related to PDM systems. The chapter also aims to give students who are studying PLM a basic understanding of the components of PDM systems.

This article discusses that many companies are installing a companywide product data management (PDM) system, also known as an engineering data management system. These systems do several things, besides acting as a central data repository. Much of the data that overwhelms companies comes from engineers using a variety of software applications, such as computer-aided design, manufacturing, or engineering programs. The PDM systems manage engineering data that may come from a myriad of sources and applications but pertain to the development of one product. The chosen PDM system would have to track the design and manufacture of each part that would be assembled to form the finished printer. It would have to tell users what stage in the process each part had reached. But it would also have to serve as a virtual warehouse for all digital versions of a part and product, including older versions that could not be lost because they might be needed for reference at any time.

Product development process analysis and improvement are very important to enterprises, but most Product Data Management (PDM) systems are not good at them. This paper presents a method that integrates Design Structure Matrix (DSM), Genetic Algorithm (GA) and Expert System (ES) techniques to intelligently analyze and improve the product development process managed by PDM systems. Based on DSM representation, GA orders the sequence of activities in process with ES's guiding to get a reasonable and optimal sequence. Based on theoretical research results, the Computer-Aided Process Improvement (CAPI) system was developed and was integrated to PDM.

Automobile, aerospace, and other industrial manufacturers have evolved over the years to use a multitude of computer-aided design (CAD) and product data management (PDM) systems and have long depended on single-vendor solutions to support their enterprise-wide engineering activities. Increased product complexity, distributed authoring environments, and the need for tighter team integration with partners and suppliers have created challenges and new opportunities for information technology (IT) vendors to be able to integrate systems from multiple independent software vendors (ISVs) to form a coherent Enterprise PDM system. This paper will describe, in detail, a case study and solution of an IBM Research project called Hedwig. Hedwig investigates creating robust solutions for Product Life-Cycle Management (PLM). We focus on several research issues, including information federation, data mapping, synchronization, and web services connections. We describe a working system that allows access to several heterogeneous PDM systems that are used in the automotive and aerospace industries.

From the view of task modeling of project process in product data management (PDM) system, a user-task allocation model is put forward based-on product breakdown structure for distributed collaborative product design. The constraints model of function mapping was established between product structure and task breakdown structure. The colored Petri net was introduced into PDM system as the modeling tool to realize product structure model-driven project task management mode and to execute dynamic visible design task scheduling. It is explored to apply multi-agent system to carry out intelligent task management and dispatching. The agent communication and task dispatching framework were implemented.

Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person-User-Role-Group“ net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.

There is nothing permanent except change. The only constant is change. Many engineering changes must be communicated to a broad range of stakeholders. The process is often labor intensive, paper laden, and error prone. Product data management (PDM) system and configuration management theory are the most popular system and theory for handling engineering changes today. In practice, when utilizing a product data management system, a planned effectivity must be filled in each engineering change request (ECR) during analyzing and evaluating phase of an engineering change. A change effectivity decision may be required to identify all of the required actions, the responsibility, and the timing from detail design phase to production phase in the life cycle of the product. This paper presents a specific product configuration, which is called engineering change decision bill of materials (ECD-BOM). The procedure for generating such a product configuration from product data management system is also provided. Import states of such product configuration into an advanced planning and scheduling (APS) system, planned effectivity of approved changed configuration items are then computed.

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 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.

Product data management (PDM) systems help to keep track of the masses of information needed to design, manufacture or build products and then to maintain them. They can be applied to a wide range of products and industries and across the whole spectrum of organizational functions. Benefits extend far beyond engineering design to include cost savings in manufacturing, reduced time to market and increased product quality. Defines and describes the type of features and functions that should be found in a PDM system and addresses the following: data vault and document management; workflow and process management; product structure management; classification; project management; communication and notification; data transport and translation; image services; system administration; and PDM environments.

Production engineers frequently use back allocation to estimate actual production volumes from wells based on frequent well test data or theoretical calculations using well and reservoir characteristics. PETRONAS executed a centralized production data management system from early days of production to establish a scalable and reliable workprocess among the organization. The production and operation data management system of the field supports data collection, QC, validation and production back allocation as well as production downtime optimization. The new system provides a means to visualize complex networks, verify the production streams, track gathering systems functionality through time and derive the allocation networks. The various downtime coding and quantifications, helped Petronas to quantify the root cause of production shortfalls and optimized the unwanted shut downs. The new system has improved the data quality and reliability and has made the data transparently available to the various stakeholders in the organization. After the new back allocation system became fully operational, Petronas started to realize the following benefits from this successful implementation. Determine the production quantities of each well and reservoir for production accounting.Quality check and approval for the test data before being used for further calculationsAbility to allocate production, where accurate measurements are not possible or cost effective.Ability to determine fluid flow quantities through every strategic point in the network The current paper describes the challenges and benefits of the subjected system implementation.

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.

An integrated development methodology of UG/NX and product data management (PDM) system is carried out based on the UG/NX secondary development technology, aiming at the needs of the PDM system to manage the product design information exported by CAD software tools and multi-user collaborative operation in the product design link, in order to unify the information and file format in the system and simplify user operation. The integrated system based on the Client/Server (C/S) architecture is designed and implemented to manage various product design documents and information. The basic model, software architecture, function flow and realization method of the integrated system are established and analyzed, and some key interfaces of the integrated system are completed. In addition, the architecture and functions of the integrated system are analyzed and evaluated, and the future development work is presented. This development methodology has certain reference application value in the CAD software secondary development, integrated system architecture establishment, functional flow construction as well as related system implementation.KeywordsUG/NX secondary developmentPDM system integrationC/S architecture system

Within the framework of Industry 4.0, the transition from stand-alone systems to an interconnected digital enterprise plays a crucial role. Increasing demands for flexibility, quality, and shorter product development cycles drive the adoption of advanced digital solutions such as product data management (PDM) systems, manufacturing execution systems (MES), advanced planning and scheduling (APS) tools, and the digital twin (DT) concept. At the same time, digitalisation trends (e.g., Smart Factory) reveal critical weaknesses of manufacturing companies, with insufficient planning and scheduling capabilities being one of the most common issues. While medium- and long-term planning is typically handled within ERP systems, operational scheduling is often still managed through inflexible spreadsheet-based solutions. APS systems are therefore gaining importance as effective tools with relatively fast return on investment, although their deployment requires alignment between ERP and MES layers as well as a thorough understanding of business and production processes. The combined implementation of PDM, APS, MES, and DT enhances decision-making, enables rapid adaptability to change, and supports the development of learning organisations. The article focuses on key principles and technologies of digital transformation with emphasis on data integration using selected tools.