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Journal articles on the topic 'Produkt Lifecycle Management'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Zscheile, Frank. "Digitaler Informations-Zwilling sichert dauerhaften Überblick." Konstruktion 70, no. 01-02 (2018): 50–51. http://dx.doi.org/10.37544/0720-5953-2018-01-02-50.

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Maschinen und Anlagen werden in ihrer Struktur immer komplexer; der Produktanteil von Elektronik und Software gegenüber reiner Mechanik steigt angesichts von Digitalisierung und Industrie 4.0 permanent an. Lässt man die Produkt-Informationen aller Komponenten einer Anlage über ihren gesamten Lebenszyklus in einem Produktdaten- und Dokumentenmanagementsystem (Product- and Document Lifecycle Management, PDLM) zusammenfließen, entsteht ein digitaler Informations-Zwilling der an den Kunden ausgelieferten Anlage.

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2

Ellenrieder, Stephan. "Wie intelligente, vernetzte Produkte von Anfang an entwickelt werden." Konstruktion 70, no. 04 (2018): 40–42. http://dx.doi.org/10.37544/0720-5953-2018-04-40.

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Das Internet der Dinge (Internet of Things, IoT) ist die nächste Generation des Product Lifecycle Management (PLM). Physikalische Daten werden durch IoT in die digitale Welt transportiert. Durch die Wahrnehmung und die darauf basierten Entscheidungen von Menschen bringt die erweiterte Realität (Augmented Reality, AR) im Gegenzug digitale Informationen zurück in die physikalische Welt. CAD und PLM sind die Vermittler, die diese beiden Gebiete zusammenhalten. Das alles macht aber nur dann Sinn, wenn die Realität in der Werkshalle betrachtet wird. Wie passt IoT in den Produktlebens- zyklus eines realen Produktes? Anhand eines Produktbeispiels des PTC-Kunden Bosch Rexroth wird beschrieben, wie ein vernetztes Produkt die Grundlage für die eigene Überarbeitung bietet und dazu beiträgt, neue Marktsegmente zu definieren und auch dank AR-Technologie eine bessere Verbindung zwischen Hersteller und Kunden zu schaffen.

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3

Seiler, Claus-Michael. "Product lifecycle management." WIRTSCHAFTSINFORMATIK 48, no. 6 (December 2006): 451. http://dx.doi.org/10.1007/s11576-006-0100-4.

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4

Thilmany, Jean. "Lifecycle Management." Mechanical Engineering 135, no. 03 (March 1, 2013): 38–41. http://dx.doi.org/10.1115/1.2013-mar-2.

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This article discusses the application of product life-cycle management (PLM) concepts in all types of manufacturing industries. PLM can handle product complexity whether a company designs a few items with many parts or a number of products that need to be localized to many communities around the globe. Fashion-driven industries are using PLM systems in new, idiosyncratic ways, and that means that they cannot simply purchase and implement an existing system the way an engineering company can. In fashion, PLM is used to keep abreast of trends and consolidate designs and inspirations. A study shows that the retail and apparel industries aren’t nearly as focused on product development as engineering companies are. For engineers, PLM is a way to centralize and to focus on product development and innovation. In retail and apparel, PLM is used to manage the supply chain more than product development.

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5

Hines, Peter, Mark Francis, and Pauline Found. "Towards lean product lifecycle management." Journal of Manufacturing Technology Management 17, no. 7 (October 2006): 866–87. http://dx.doi.org/10.1108/17410380610688214.

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6

Prajapati, Vandana, and Harish Dureja. "Product lifecycle management in pharmaceuticals." Journal of Medical Marketing: Device, Diagnostic and Pharmaceutical Marketing 12, no. 3 (April 19, 2012): 150–58. http://dx.doi.org/10.1177/1745790412445292.

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7

Meyer, Kyrill, Michael Thieme, and Christian Zinke. "Product-Service-Lifecycle." International Journal of Service Science, Management, Engineering, and Technology 4, no. 2 (April 2013): 17–33. http://dx.doi.org/10.4018/jssmet.2013040102.

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Product-related services are not sufficiently enough systematically and technically supported. Whereas sophisticated development and management systems for the entire lifecycle of products exist, the support of services is only insufficient. The authors’ developed a holistic concept as basis for IT support functions that are developed by practical reference processes.

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8

Fukushige, Shinichi, Masaki Nishioka, and Hideki Kobayashi. "Data-assimilated lifecycle simulation for adaptive product lifecycle management." CIRP Annals 66, no. 1 (2017): 37–40. http://dx.doi.org/10.1016/j.cirp.2017.04.102.

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9

Jia, Xiao Liang. "Research on Complex Product Lifecycle Quality Management Technology Based on 3D Product Model." Advanced Materials Research 346 (September 2011): 96–102. http://dx.doi.org/10.4028/www.scientific.net/amr.346.96.

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In connection with characteristics of complex product development, in order to solve problems of long product development cycle, multi-collaborative firms, difficult to control product quality in manufacturing firms, the approach of complex product lifecycle quality management technology based on the collaboration of 3D virtual product and physical product is put forward. The connotation of complex product lifecycle quality management technology based on 3D product model is analyzed. Complex product lifecycle quality management model based on 3D product model is founded also. Base on 3D virtual product model and PLM technology, key technologies on complex product lifecycle quality management are described in detail.

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10

Gandhi, Priyanka. "Product Lifecycle Management Importance and Approach." International Journal of Applied Information Systems 5, no. 6 (April 10, 2013): 28–30. http://dx.doi.org/10.5120/ijais13-450930.

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11

Pham, Duc T., Stefan S. Dimov ,, Rossitza M. Setchi ,, Bernard Peat ,, Anthony J. Soroka ,, Emmanuel B. Brousseau ,, Ammar M. Huneiti ,, et al. "Product Lifecycle Management for Performance Support." Journal of Computing and Information Science in Engineering 4, no. 4 (December 1, 2004): 305–15. http://dx.doi.org/10.1115/1.1818687.

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This paper shows how product lifecycle information can be utilized to assist people engaged in product lifecycle tasks, in particular those concerned with product support. A progression of product data management methods based on knowledge engineering techniques is presented to allow the creation and delivery of effective, personalized performance support information. The product data management methods discussed include semantic hypermedia authoring, automated construction of product documentation, automated diagnostic module construction, and adaptive product support generation. These methods are utilized to improve the performance of product lifecycle actors, while reducing the time, knowledge, and input required from them, through increased task support and automation.

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12

Courtney, M. "Keeping track [Product lifecycle management software]." Engineering & Technology 9, no. 12 (December 1, 2014): 64–66. http://dx.doi.org/10.1049/et.2014.1207.

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13

Ma, Yongsheng, and Jerry Y. H. Fuh. "Product lifecycle modelling, analysis and management." Computers in Industry 59, no. 2-3 (March 2008): 107–9. http://dx.doi.org/10.1016/j.compind.2007.06.005.

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14

Clermont, Philippe, and Bernard Kamsu-Foguem. "Experience feedback in product lifecycle management." Computers in Industry 95 (February 2018): 1–14. http://dx.doi.org/10.1016/j.compind.2017.11.002.

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15

Li, Jingran, Fei Tao, Ying Cheng, and Liangjin Zhao. "Big Data in product lifecycle management." International Journal of Advanced Manufacturing Technology 81, no. 1-4 (May 12, 2015): 667–84. http://dx.doi.org/10.1007/s00170-015-7151-x.

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16

Wang, Lei, Zhengchao Liu, Ang Liu, and Fei Tao. "Artificial intelligence in product lifecycle management." International Journal of Advanced Manufacturing Technology 114, no. 3-4 (March 22, 2021): 771–96. http://dx.doi.org/10.1007/s00170-021-06882-1.

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17

Rangan, Ravi M., Steve M. Rohde, Russell Peak, Bipin Chadha, and Plamen Bliznakov. "Streamlining Product Lifecycle Processes: A Survey of Product Lifecycle Management Implementations, Directions, and Challenges." Journal of Computing and Information Science in Engineering 5, no. 3 (September 1, 2005): 227–37. http://dx.doi.org/10.1115/1.2031270.

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The past three decades have seen phenomenal growth in investments in the area of product lifecycle management (PLM) as companies exploit opportunities in streamlining product lifecycle processes, and fully harnessing their data assets. These processes span all product lifecycle phases from requirements definition, systems design/ analysis, and simulation, detailed design, manufacturing planning, production planning, quality management, customer support, in-service management, and end-of-life recycling. Initiatives ranging from process re-engineering, enterprise-level change management, standardization, globalization and the like have moved PLM processes to mission-critical enterprise systems. Product data representations that encapsulate semantics to support product data exchange and PLM collaboration processes have driven several standards organizations, vendor product development efforts, real-world PLM implementations, and research initiatives. However, the process and deployment dimensions have attracted little attention: The need to optimize organization processes rather than individual benefits poses challenging “culture change management” issues and have derailed many enterprise-scale PLM efforts. Drawn from the authors’ field experiences as PLM system integrators, business process consultants, corporate executives, vendors, and academicians, this paper explores the broad scope of PLM, with an added focus on the implementation and deployment of PLM beyond the development of technology. We review the historical evolution of engineering information management/PLM systems and processes, characterize PLM implementations and solution contexts, and discuss case studies from multiple industries. We conclude with a discussion of research issues motivated by improving PLM adoption in industry.

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18

Grieves, Michael W. "Product Lifecycle Quality (PLQ): a framework within Product Lifecycle Management (PLM) for achieving product quality." International Journal of Manufacturing Technology and Management 19, no. 3/4 (2010): 180. http://dx.doi.org/10.1504/ijmtm.2010.031367.

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19

Demoly, Frédéric, Olivier Dutartre, Xiu-Tian Yan, Benoît Eynard, Dimitris Kiritsis, and Samuel Gomes. "Product relationships management enabler for concurrent engineering and product lifecycle management." Computers in Industry 64, no. 7 (September 2013): 833–48. http://dx.doi.org/10.1016/j.compind.2013.05.004.

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20

Menon, Karan, Hannu Kärkkäinen, Thorsten Wuest, and Jayesh Prakash Gupta. "Industrial internet platforms: A conceptual evaluation from a product lifecycle management perspective." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 233, no. 5 (April 2, 2018): 1390–401. http://dx.doi.org/10.1177/0954405418760651.

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Industrial Internet platforms have the ability to access, manage and control product-related data, information and knowledge across all the lifecycle phases (beginning of life, middle of life and end of life). Traditional product lifecycle management/product data management software have many limitations when it comes to solving product lifecycle management challenges, like interoperability for instance. Industrial Internet platforms can provide real-time management of data and information along all the phases of a product’s lifecycle. Platform openness in combination with the above-mentioned industrial internet platform characteristics helps solve the product lifecycle management challenges. This article describes the product lifecycle management challenges in detail from the existing literature and presents solutions using industrial internet platform openness and related dimensions as well as sub-dimensions. A wide pool of platforms is narrowed down to specific platforms that can solve the documented product lifecycle management challenges and allow the manufacturing companies to collaborate as well as enhance their business. We also present in detail managerial implications toward long-term and sustainable selection of industrial internet platform.

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21

Sudarsan, R., S. J. Fenves, R. D. Sriram, and F. Wang. "A product information modeling framework for product lifecycle management." Computer-Aided Design 37, no. 13 (November 2005): 1399–411. http://dx.doi.org/10.1016/j.cad.2005.02.010.

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22

Brindasu, Paul Dan, Livia Dana Beju, and Corina Baitoiu. "Designing Educational Materials Through Product Lifecycle Management." Balkan Region Conference on Engineering and Business Education 1, no. 1 (August 15, 2014): 73–78. http://dx.doi.org/10.2478/cplbu-2014-0016.

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AbstractThe paper analyses the situation of teaching materials in technical schools in Romania via a marketing research that takes into account stakeholders, the microenvironment, as well as the macroenvironment. The research has shed light on a number of problems that require a new approach to the design of educational tools. The paper proposes that this design of educational tools be performed through the product lifecycle management (PLM) perspective. All phases of the design and lifecycle of such products are analysed, and concrete solutions for realising each of these phases are proposed. Finally, some examples of educational products are presented, which have the purpose of aiding the teaching of technical drawing, and which have been devised using this very methodology.

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23

Sander, Stefan, Werner Puri, and Rolf-Dirk Kasan. "Anwendungsszenarien für Klassensysteme im Product Lifecycle Management." ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb 97, no. 10 (October 27, 2002): 532–39. http://dx.doi.org/10.3139/104.100580.

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24

Boschian, Valentina, Maria Pia Fanti, Giorgio Iacobellis, Walter Ukovich, and Noemi Augenti. "A Simulation Model for Product Lifecycle Management." IFAC Proceedings Volumes 46, no. 9 (2013): 1459–64. http://dx.doi.org/10.3182/20130619-3-ru-3018.00238.

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25

Wiesner, Stefan, Mike Freitag, Ingo Westphal, and Klaus-Dieter Thoben. "Interactions between Service and Product Lifecycle Management." Procedia CIRP 30 (2015): 36–41. http://dx.doi.org/10.1016/j.procir.2015.02.018.

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26

Pastukhov, A. V., E. A. Dorozhkina, and I. P. Leskovskii. "Product lifecycle management concept in modern industry." IOP Conference Series: Materials Science and Engineering 537 (June 17, 2019): 042075. http://dx.doi.org/10.1088/1757-899x/537/4/042075.

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27

Gomez, Javier M. Martínez, Joel Sauza Bedolla, Francesco Ricci, and Paolo Chiabert. "Validation process model for product lifecycle management." International Journal of Product Lifecycle Management 7, no. 2/3 (2014): 230. http://dx.doi.org/10.1504/ijplm.2014.065868.

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28

Ameri, Farhad, and Deba Dutta. "Product Lifecycle Management: Closing the Knowledge Loops." Computer-Aided Design and Applications 2, no. 5 (January 2005): 577–90. http://dx.doi.org/10.1080/16864360.2005.10738322.

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29

Hadaya, Pierre, and Philippe Marchildon. "Understanding product lifecycle management and supporting systems." Industrial Management & Data Systems 112, no. 4 (April 20, 2012): 559–83. http://dx.doi.org/10.1108/02635571211225486.

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30

Danesi, Frédéric, Nicolas Gardan, Yvon Gardan, and Michael Reimeringer. "P4LM: A methodology for product lifecycle management." Computers in Industry 59, no. 2-3 (March 2008): 304–17. http://dx.doi.org/10.1016/j.compind.2007.06.013.

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31

Kubler, Sylvain, Kary Främling, and William Derigent. "P2P Data synchronization for product lifecycle management." Computers in Industry 66 (January 2015): 82–98. http://dx.doi.org/10.1016/j.compind.2014.10.009.

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32

Srinivasan, Vijay. "An integration framework for product lifecycle management." Computer-Aided Design 43, no. 5 (May 2011): 464–78. http://dx.doi.org/10.1016/j.cad.2008.12.001.

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33

Zina, Souheïl, Muriel Lombard, Luc Lossent, and Charles Henriot. "Generic Modeling and Configuration Management in Product Lifecycle Management." International Journal of Computers Communications & Control 1, no. 4 (October 1, 2006): 126. http://dx.doi.org/10.15837/ijccc.2006.4.2314.

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The PLM (Product Lifecycle Management) is often defined as a set of functions and procedures which allows one to manage and to exploit the data defining at the same time the products and the processes implemented for their developments. However, the installation of a PLM solution remains a difficult exercise taking into account the complexity and the diversity of the customer requirements as well as the transverse utilization of this solution in all the company’s’ functions. The issues faced by both editors and integrators of PLM applications arise from the specific aspect of customers’ projects, even tough most functional needs are often generic. In this paper we are focused on product modeling in PLM applications, more particularly on configuration management that traces product evolutions throughout its lifecycle. we will insist on the links between the configuration needs and the multi-view approach models and we release problems related to PLM applications deployment. Our work concerns the PLM generic solutions based on the concept of generic models. This generic model takes into account the configurations specification associated to the managed product and can be extended to cover specific needs.

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34

Felic, Artur, Birgitta König-Ries, and Michael Klein. "Process-oriented Semantic Knowledge Management in Product Lifecycle Management." Procedia CIRP 25 (2014): 361–68. http://dx.doi.org/10.1016/j.procir.2014.10.050.

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35

Chen, Xiaoxia, Mélanie Despeisse, and Björn Johansson. "Environmental Sustainability of Digitalization in Manufacturing: A Review." Sustainability 12, no. 24 (December 9, 2020): 10298. http://dx.doi.org/10.3390/su122410298.

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The rapid development and implementation of digitalization in manufacturing has enormous impact on the environment. It is still unclear whether digitalization has positive or negative environmental impact from applications in manufacturing. Therefore, this study aims to discuss the overall implications of digitalization on environmental sustainability through a literature study, within the scope of manufacturing (product design, production, transportation, and customer service). The analysis and categorization of selected articles resulted in two main findings: (1) Digitalization in manufacturing contributes positively to environmental sustainability by increasing resource and information efficiency as a result of applying Industry 4.0 technologies throughout the product lifecycle; (2) the negative environmental burden of digitalization is primarily due to increased resource and energy use, as well as waste and emissions from manufacturing, use, and disposal of the hardware (the technology lifecycle). Based on these findings, a lifecycle perspective is proposed, considering the environmental impacts from both the product and technology lifecycles. This study identified key implications of digitalization on environmental sustainability in manufacturing to increase awareness of both the positive and negative impacts of digitalization and thereby support decision making to invest in new digital technologies.

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36

He, Li Na, Xin Guo Ming, Fan Bing Kong, Huai Liang Zuo, and Zhen Hua Yao. "Research on Airplane BOM Management Based on Single Source of Product Data." Applied Mechanics and Materials 232 (November 2012): 184–88. http://dx.doi.org/10.4028/www.scientific.net/amm.232.184.

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The core of airplane lifecycle data management is BOM management in the product lifecycle. Aiming at the problem of nonunique data source existing in airplane lifecycle, the paper proposes the airplane BOM management hierarchical system framework based on Single Source of Product Data ( SSPD) and the corresponding technology. The logical unified SSPD is constructed to guarantee the uniqueness of lifecycle data. According to the diversity and complexity of airplane，customer options management and BOM management based on SSPD, are discussed emphatically in the context.

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37

Pan, Xu Wei, Li Jun Fu, and Yi Ming Wu. "Product Family Lifecycle Information Integration Model and its Application." Applied Mechanics and Materials 58-60 (June 2011): 624–29. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.624.

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To solve the difficulties in managing lifecycle information on varieties of products in the customer demand diversity and personalization environment, a product lifecycle information management approach based on product family is put forward. A 3-Dimention Product Family Lifecycle Information Integration Model (PFLI2M) is proposed, which is composed of product main structure dimension, product dimension and lifecycle dimension, and the evolution process of the 3 dimensions is discussed. Based on the metadata method, unit information representation of PFLI2M is studied from the physical layer, logic layer, expression layer and the application layer. These methods are applied in lifecycle information management of sealing products.

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38

Liu, Gang, Rongjun Man, and Yanyan Wang. "A Data Management Approach Based on Product Morphology in Product Lifecycle Management." Processes 9, no. 7 (July 16, 2021): 1235. http://dx.doi.org/10.3390/pr9071235.

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In the product life cycle from conception to retirement, there are three forms: conceptual products, digital products and physical products. The carriers of conceptual products are requirements, functions and abstract structures, and data management focuses on the mapping of requirements, functions, and structures. The carrier of digital products is digital files such as drawings and models, and the focus of data management is the design evolution of product. Physical products are physical entities, and their attributes and states will change over time. Existing data model research often focuses on one or two forms, and it is even impossible to integrate three forms of data into one system. So, a new data management method based on product form is presented. According to the characteristics of the three product form data, a conceptual product data model, a digital product data model, and a physical product data model are established to manage the three forms of data, respectively, and use global object mapping to integrate them into a unified data model. The conceptual product data model has a single data model for a single business stage. The digital product data model uses the core data model as the single data source, and uses one stage rule filter to add constraints to the core data model for each business stage. The physical product data model uses the core data model to manage the public data of the physical phase, and the phase private data model focuses on the private data of each business phase. Finally, a case of Multi-Purpose Container Vessel is studied to verify the feasibility of the method. This paper proposes three product forms of product data management and a unified data management model covering the three product forms, which provides a new method for product life cycle data.

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39

Thilmany, Jean. "Project + Lifecycle Together." Mechanical Engineering 133, no. 02 (February 1, 2011): 36–37. http://dx.doi.org/10.1115/1.2011-feb-4.

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This article discusses the advantages of integrating project portfolio management (PPM) with product lifecycle management (PLM) software for project planning. Many engineering companies are now stepping forward to integrate their PPM and PLM systems for more close-up project planning. By tying the two systems, engineering firms are better able to manage time spent on specific projects, to get an overarching and realistic view of where the project stands, to stay on the schedule and to meet specific goals. The tied systems also allow engineers to get a broad view of the project that extends beyond their engineering piece. In engineering companies, where the project status is inevitably tied to the engineering department, closing the loop between theoretical plans and engineering progress can make for big budgetary savings and offer important insight into product planning. Many engineering companies that do not yet have a PPM system are now considering implementing one to plan their product mixes.

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40

Cui, Jiang, and Xiao Bing Xu. "An Ontology-Enabled Production in Product Lifecycle Management." Applied Mechanics and Materials 37-38 (November 2010): 112–15. http://dx.doi.org/10.4028/www.scientific.net/amm.37-38.112.

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The paper presents Production-in-product lifecycle management as a new approach to integrate functions and its operation and optimization towards its rebuilding or deconstruction and the restart of the arising cycle. Essential elements of Production-in-product lifecycle management are the suitable consideration of models used by digital tools for the presentation, analysis design iptimisatiom and control of production systems as well as the linkage of these models to the ‘real world’. Production-in-product lifecycle management to forms and essential element of a Digital Manufacturing approach that enhances competitiveness of industrial enterprises by the reduction of times and costs for product creation and order fulfillment. Thereby Digital Manufacturing may serve as one building block for a comprehensive Digital Enterprise.

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41

Xin, Yan, Ville Ojanen, and Janne Huiskonen. "Knowledge Management in Product-Service Systems – A Product Lifecycle Perspective." Procedia CIRP 73 (2018): 203–9. http://dx.doi.org/10.1016/j.procir.2018.03.306.

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42

Terzi, Sergio, Herve Panetto, Gerard Morel, and Marco Garetti. "A holonic metamodel for product traceability in Product Lifecycle Management." International Journal of Product Lifecycle Management 2, no. 3 (2007): 253. http://dx.doi.org/10.1504/ijplm.2007.016292.

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43

Sun, Xue Yan, Xing Yu Jiang, Shi Jie Wang, and Jia Qi Jin. "Product Lifecycle Oriented Quality Management System for Individualized Customization." Applied Mechanics and Materials 44-47 (December 2010): 4105–9. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.4105.

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To cope with the challenges of traditional quality management system applied in individualized customization, product lifecycle oriented quality management system model for individualized customization, and corresponding functional modules and framework were all put forward. This mode dealt mainly with constructing and running product lifecycle oriented quality management system for individualized customization, furthermore, some of key enabling technologies were studied in detail, including collaborative quality design based on CSCW, dynamic process quality control, quality evaluation oriented to product lifecycle. The corresponding prototype system is developed, which was introduced to demonstrate the rationality and validity of the method as an example of some Heavy Machinery Ltd. It provided an effective method with enterprise implementing individualized customization.

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44

Vasilyeva, Irina A., Valeria V. Kolosova, and Andrey A. Sazonov. "PRODUCT LIFECYCLE MANAGEMENT UNDER THE CONDITIONSOF PRODUCTION TRANSFORMATION." Bulletin of the Moscow State Regional University (Economics), no. 3 (2019): 50–58. http://dx.doi.org/10.18384/2310-6646-2019-3-50-58.

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45

Yoshino, Hiroyuki. "DDS as a tool of product lifecycle management." Drug Delivery System 20, no. 6 (2005): 648–55. http://dx.doi.org/10.2745/dds.20.648.

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46

Daniels, Matthew, Ivor Lanning, Pezhman Ghadimi, Cathal Heavey, Alan Ryan, and Mark Southern. "Product Lifecycle Management Requirements Gathering: Industrial Pilot Cases." IFAC Proceedings Volumes 46, no. 9 (2013): 1750–55. http://dx.doi.org/10.3182/20130619-3-ru-3018.00434.

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47

Bruno, Giulia, Dario Antonelli, and Agostino Villa. "A Reference Ontology to Support Product Lifecycle Management." Procedia CIRP 33 (2015): 41–46. http://dx.doi.org/10.1016/j.procir.2015.06.009.

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48

Karasev, V. O., and V. A. Sukhanov. "Product Lifecycle Management Using Multi-agent Systems Models." Procedia Computer Science 103 (2017): 142–47. http://dx.doi.org/10.1016/j.procs.2017.01.034.

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49

Sivusuo, Jaakko, and Josu Takala. "Management Changes in MRO Business through Product Lifecycle." Management and Production Engineering Review 7, no. 3 (September 1, 2016): 87–93. http://dx.doi.org/10.1515/mper-2016-0028.

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Abstract Nowadays organizations and entire industries have faced the challenges of globalization and rapid technological development. These changes have brought new kind of competition and it has shaped and mixed organizations traditional business logic. This research is based on multiple case studies where the focus is on management changes through product lifecycle management. Emphasis is on MRO (Maintenance, repair, overhaul) providers and how they implement dynamic capabilities through product life cycle management. MRO is abbreviation for Maintenance, repair and overhaul and it is a commonly used in Aerospace industry. The study identifies several products in various stages of the life-cycle and thus identify the essential changes related to management. The stages that study identifies are Learning phase, Productisation phase and PBL phase. These phases can be used for clarifying dynamic capabilities in MRO markets.

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Eickhoff, Thomas, Andreas Eiden, Jens Christian Göbel, and Martin Eigner. "A Metadata Repository for Semantic Product Lifecycle Management." Procedia CIRP 91 (2020): 249–54. http://dx.doi.org/10.1016/j.procir.2019.11.006.

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