Product Lifecycle Management as Data Repository for Manufacturing Problem Solving

This article discusses implementation of a new product lifecycle management (PLM) system at Parker Hannifin Corp.’s aerospace group. This group employs 6100 across its 18 design centers located around the world, where engineers create parts for commercial aircraft, including helicopters, and many military aircrafts. Managers within the Parker Hannifin aerospace group had been tracking digital documents with a document-management system since the early 1990s. The group recently upgraded its PLM system and is working on supplier access to design documents stored within the system. The new PLM system was rolled out in 2008. The Enovia MatrixOne system is from the same vendor that supplies the company’s main computer-aided design system, which is Catia from Dassault Systèmes of Paris. Regardless of how that project plays out, Parker Hannifin is now miles ahead of where it was only a few years ago when it comes to managing design documents and related data. The smoothing of any chinks among suppliers and in maintaining legacy information has all been worth the upgrade.

Industrial companies collaborating to develop new products need to implement an effective management of their design processes and product information. Unfortunately, PLM (Product Lifecycle Management) systems, which are dedicated to support product design activities, are not efficient as it might be expected. Indeed, product design processes are continuously changing, are sometimes emergent and non deterministic whereas PLM systems, based on workflow technology, don’t support process flexibility. Needs in terms of process support flexibility are necessary to facilitate the coupling with the business enactment. Furthermore, Service Oriented Architectures (SOA) enhances flexibility and adaptability of composed solutions. Systems based on SOA have the ability to inherently being evolvable. This paper proposes an approach to deal with product design process flexibility in PLM systems by making profiles from SOA. The objective is to specify, design and implement product design processes in a very flexible way so that business changes are rapidly considered in PLM solutions.

Effects of product lifecycle management systems on new product development performance

Product lifecycle management (PLM) is the activity of managing a product throughout its lifecycle – “from cradle to grave,” “from sunrise to sunset” (Stark J (2005) Product Lifecycle Management – 21st Century Paradigm for Product Realization. Springer, London). The management of product lifecycles is important since it involves all entities that exist along the value and supply chains of firms. Product lifecycle management systems (PLMS) have emerged as a potent resource used by firms to manage multiple activities required to develop, model, track, and manage manufactured products, including sales, maintenance, and product retirement. This research has been motivated by the massive investments (in the order of several million rupees) on acquiring PLMS and launching PLMS initiatives by various organizations in India, and the consequent need to analyze and assess their PLMS deployment maturity. Obviously, they (organizations) should want to know their PLMS deployment maturity with respect to both their present standing and relative to the industry. Assessment of PLMS deployment maturity of an organization serves as a good reference point to rate the success of its operations and the quality of its products. Venugopalan et al. (2009. A framework for assessing the maturity of product lifecycle management practices. In: Proceedings of PDMA India IV annual international conference NPDC 2009: new product development – challenges in meltdown times, Chennai, India, December 17–19 2009. pp. 159–171) have proposed a framework for assessing the deployment maturity of PLMS, and the same has been adapted for this study. It has been used to assess the perspectives of PLMS deployment maturity between PLMS users and PLMS service providers by means of preparing and administering a custom-designed questionnaire, and collating and analyzing the responses using appropriate statistical techniques. This will also enable organizations to benchmark their PLMS deployment maturity relative to others. This work analyzes the deployment maturity of PLMS components of 29 Indian organizations using nonparametric statistical tests.

The ship-to-ship (STS) transfer of cargo operations are increasingly safe procedures, nevertheless they remain difficult and complex operations. The adverse effects of a potential accident demands a detailed and thorough work on risk and safety analysis for the transfer operations. In the light of the above, the Process Failure Mode and Effects Analysis (PFMEA) which is a branch of the traditional Failure Mode an d Effects Analysis (FMEA), is applied in combination with a Fuzzy Inference System (FIS) methodology to evaluate different risk scenarios of STS transfer of cargo operations. Although PFMEA is currently applied mainly to manufacturing processes, the aim of the paper is to implement this methodology to the ship-to-ship transfer of cargo. A significant advantage of the PFMEA is the analytical review of the STS operations. Nevertheless, serious drawbacks such as the fact that different combinations of the three implemented risk constituents may lead to the same Risk Priority Number (RPN) or the determination of the relative importance among the three risk factors of the PFMEA namely the likelihood of occurrence (O), the severity of a failure (S), and the ability to detect the potential failure (D), make the PFMEA weak and ineffective. To deal with the aforementioned weaknesses a fuzzy inference system (FIS) based on Mamdani's methodology, is applied as a remedy. The objective of this paper is to assess and evaluate different hazardous scenarios in an STS transfer operation implementing the PFMEA in combination with a FIS. To do so, a team of experts with relative experience with respect to STS transfer operations evaluated certain hazardous scenarios that have derived by the study of several guidelines and recommendations regarding these operations. The paper concludes with interesting insights emerged by the aforementioned tasks.

Development of products has been organized around product lifecycle management (PLM) systems during the past decade in leading industries. In mechatronics, where product structures are very complex and inhomogeneous, it is urgent to apply high level information technology for engineering purposes. The new style of engineering, where engineers work in remote workplaces and communicate through sophisticated model of product is especially important for mechatronics. Communication among engineers through product model is one of the problem areas because the changed demands for product development can not be fulfilled by using of direct communication. Current product models describe product information. Information is not enough to understand, revise and change of earlier decisions by engineers who receive these product models. The problem is that current product models are not suitable for description of background of decisions on product information. As a contribution to establish a solution for this problem, this paper introduces a new modeling that uses human intent and other content of information in product model at the creation background description for decisions. The new modeling is proposed as an extension to current PLM systems. Main purpose of the proposed modeling is to enhance communication among engineers. The paper explains changed engineering activities in recent model based product development. Following this, the proposed new communication is detailed and discussed. Next, a concept for a new virtual space for products is introduced. Finally implementation of the proposed modeling in the form of extension to current modeling in PLM systems is explained and tasks for research in the proposed modeling for the next future are outlined.

PLM (product lifecycle management) is the management of the enterprise's products all the way across their lifecycles in the most effective way. However, at present, the PLM system in the market is not very appropriate to the small and medium-size enterprises. This paper presents a workflow engine-driven universal PLM system framework, which is constructed by four layers: client layer, application layer, business logic layer, data layer. The workflow engine-driven universal PLM system framework can be directly used as the PLM system, or can be used to customize the autonomy PLM system for the small and medium-size enterprises. The workflow engine-driven universal PLM system framework is implemented by Java enterprise edition and service-oriented architecture, which has the advantage of lightweight, cross-platform, and so on.

Dynamic behavior analysis is the area of investigation in the product lifecycle management (PLM) system. Behavioral modeling approach of a system is used to define dynamic behavior of a system. There is a big list of modeling approaches proposed by the researchers of various disciplines to simplify the analysis of system so that it is used as standard for system development in the real world. The cyber-physical system (CPS) is the next generation of system where the physical system acts smartly with the power of computing. Therefore, modeling of CPS is gaining popularity in the industrial design. This paper starts with the discussion of behavioral modeling era of a system and CPS respectively. Then, the survey of the state of the art of system behavioral modeling and CPS behavioral modeling is provided in which most of the approaches are reviewed PLM system. The system modeling survey is conducted based on the work done in the late 20th century to the recent years of 21st century. The CPS modeling survey is conducted based on the work done in the recent years of 21th century as this technology and modeling approach is emerging. Based on the discussion and survey, conclusion and future work will be explained.

As the globalization is at its peak and innovative products are at high demand, firms are forced to work in a collaborative manner. The product data must be lively available to all the collaborated partners. Although on-premise Product Lifecycle Management (PLM) systems are offering the collaborations and product data management throughout the product's lifecycle, the Internet of Things (IoT) era offers more connectivity at a lesser cost. Though most large manufacturing firms have established the on-premise PLM systems, yet face some difficulties related to maintenance and upgradations of in-house information technology (IT) infrastructure. Hence, cloud PLM is under consideration for adoption among many large manufacturing firms. However, there are several challenges associated with cloud PLM adoption decision. This work intends to find out the challenges which large manufacturing firms face while deciding to adopt cloud PLM. The empirical investigations have been attempted to find out the relations among the challenges faced and to provide the guideline on how to find out the core challenges which needs to be attended before adopting cloud PLM in large manufacturing firms.

Manufacturing data and information are produced and used during the lifecycle of product development. Product lifecycle management (PLM) systems provide a suitable platform for managing them. For a...

Product Lifecycle Management (PLM) is a current need for companies to be competitive in the global market. PLM became a necessity to work collaboratively with least time and cost for the best quality production. PLM offerings are not only limited to 3D designing and visualization but also extended to data management, digitization, and virtual manufacturing. PLM is a management approach which manages the related product information in each phase of the product's lifecycle. Various companies and systems suppliers consider PLM as software systems only while it is a broad business management concept. Due to this ambiguity, most companies fail to understand and implement it properly. PLM is actually a concept which is backed up by PLM systems as the enormous product-related data needs technological support to manage. Implementation of PLM systems is complementary to the institutionalization of the PLM concept. Hence, present study reviews success factors to PLM performance and empirically analyzes causal success factors. This work will be helpful to the managers in industries to utilize this unique approach to manage their products.

The rapid evolution of CAD technologies and their integration with product lifecycle management (PLM) systems poses significant challenges for experienced designers. Transitioning to new software often requires relearning workflows and adopting unfamiliar functionality, which can lead to productivity disruptions and frustration. To address this, the company ARTECH GmbH proposes an innovative e-learning course tailored for experienced designers, specifically designed to foster their mastery of new systems. This paper explores the development and deployment of a training course designed to balance technical training with empathy for users' professional expertise and learning styles. The course uses human-centred methods to address the unique needs of experienced designers, recognizing their existing skills and emphasizing adaptive strategies rather than rote learning. Core training components include self-paced modules, interactive tutorials, and project-based learning, all aligned with real-world design challenges integrated with PLM systems. A key focus of the course is the integration of the user experience throughout the lifecycle of products and services. Designers will be guided to understand how new CAD tools affect collaboration, prototyping and the eventual lifecycle management of designs. By simulating multi-user, multi-modal scenarios, the course promotes collaborative design thinking and enhances designers' ability to consider multiple perspectives and criteria in their workflows. I

This article studies the role of product lifecycle management (PLM) in industrial engineering. The basic concepts of PLM—product data management, engineering change management, and product structure management—were also discussed. PLM provides data and management capabilities to reduce the non-value-added tasks required of engineers. It also increases engineering productivity, provides insight into engineering efforts, and improves product quality and customer satisfaction. Companies are receiving significant value and return from their PLM investments. Many companies begin implementing PLM by establishing a single source of product data, or product record. Most PLM solutions offer sophisticated interfaces to many design automation and office applications, which reduce the need to capture, store, and validate product data. Product designs are maintained as assemblies and parts in the PLM system, and that arrangement allows engineers easy searching when they are looking, for example, for legacy components, with software providing a critical control and value portion of the product. With PLM, disparate engineering teams work more collaboratively.

Introduction: To achieve competitive advantage, a company must permanently innovate and change its products, process and management systems faster than competitors. In manufacturing companies, as new products become the focus in competition, the new product development (NPD) process become increasingly important to these businesses. NPD process can be improved by boosting product lifecycle knowledge management. In this paper, how to carry out this improvement is described through a case study of a naval shipbuilding firm, Navantia. Methods: In the detailed case study, the improvement needs are identified from a knowledge management based approach and the solutions developed are described. These solutions are provided by a Product Lifecycle Management (PLM) system by means of its tools and its integration with other management systems used in Navantia. Results: The integration of knowledge in the company has lead to access and sharing information time reduction; errors reduction; improvements in the communication among employees and with partners, customers and suppliers; and design time and product costs reduction. Discussion: This case provides several keys to a successful implementation of a PLM system, such as making a reasoned analysis of the needs of the company from a strategic knowledge management based approach, the gradual integration of existing tools with the system PLM and the involvement of different actors in the company, both at organizational and interorganizational level.

A product information modeling framework for product lifecycle management