Product Lifecycle Information Research Articles

Life cycle management of critical refurbishable parts of ship equipment

To ensure the product life cycle (PLC), foreign and domestic information technologies have been developed that mainly ensure the stages of design and manufacture of products, but they do not allow for automation of the design of technologies for restoration and strengthening of parts. The relevance of restoration of critical parts of ship equipment is due to dependence on foreign supplies of equipment and spare parts (SP), as well as sanctions from unfriendly states, which complicated the acquisition of SP, and the need for import independence arose. The paper shows that life cycle management of a restored part has a significant impact on the efficiency of marine fleet operation, and provides stages and main sub-stages of the life cycle of restored parts of ship equipment. Restoration of parts is considered appropriate if the required durability and savings are ensured compared to manufacturing or purchasing a new part. The concept of life cycle management of restored parts is provided. Life cycle management of restored parts includes planning, control and management of all stages, as well as decision-making to ensure the durability of the part through the use of advanced materials and coating formation technologies. The stage of the life cycle of the restored part, determining the service life of the part, the economic efficiency of its restoration and subsequent operation, is the technological process that ensures the optimal chemical composition, mechanical and structural parameters of the coating. All the properties of the restored part are laid down at the stage of designing the technological process. The prospects of using the life cycle management of the restored part are shown using the example of restoring precision parts of the fuel equipment of marine diesel engines. The use of various technologies for the same type of restored precision parts allows obtaining coatings with different chemical composition, mechanical properties, structure and, accordingly, different values of durability and cost price to ensure the specified service life of the tribological unit at an acceptable price.

The Concept of Building an Integrated Digital Ecosystem to Improve the Quality of Products and Services of Defense Industry Enterprises

Research and development of systems for managing material, technical, and intellectual resources are key directions for improving manufacturing processes in the modern world. In recent years, the question of integrating various management systems has become particularly relevant due to the widespread adoption of quality management systems and their certification to meet current regulatory requirements. This study attempts to merge the advantages of using product lifecycle information support technologies, such as data and information management, with the concept of digital twins, including virtual design, digital product modeling, and real-time analysis. The analysis covers the constituent elements of the generalized product design and manufacturing process, addressing the construction of an integrated digital ecosystem to enhance the quality of products and services in the defense-industrial complex. This ecosystem is based on the integration of technologies for continuous product information support using their digital twins and an integrated quality management system. It is shown that the approach to evaluating the effectiveness of purposeful processes should be complemented by a risk-oriented model, which includes response scenarios to potential adverse effects of the operation of the purposeful organizational-technical system. A structural scheme and formalized description of a generalized product information support model are presented, allowing for the integration of specific quality indicators into a unified strategic outcome. Ultimately, a concept for building an integrated digital ecosystem for defense-industrial enterprises is proposed, aimed at enhancing the overall quality of products and services.

A modular ontology modeling approach to developing digital product passports to promote circular economy in the built environment

The significant impact of the built environment on resource consumption and waste production has led to calls for a shift towards a circular economy model that maximizes the efficient use of resources. This study explores the use of digital product passports (DPPs) to improve how we manage products throughout their lifecycle. However, dealing with the complexity and large volume of data in DPPs can be challenging in terms of effective information management and utilization. We address this issue by adopting a modular ontological approach to systematically capture product lifecycle information from its origin to its end-of-life phase. To ensure interoperability and reusability of the ontology, we annotate key concepts and relationships using International Organization for Standardization (ISO) standards that promote circular economy. Our research led to the development of several ontology modules derived from literature reviews and interviews conducted with industry and academia experts who specialize in sustainability. These modules were then integrated to create a digital product passport ontology. The study demonstrates the feasibility of using a modular ontology approach to manage the complex information inherent in DPPs paving the way for more sustainable management practices in the built environment sector.

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

The primary aim of this study is to explore and understand the potential benefits and applications of the Digital Product Passport (DPP) system within the modern manufacturing industry. To achieve this, we developed a unique methodology, model, and a template for creating a DPP, identifying the key characteristics essential for effective implementation. Our approach involved an analysis of the literature and the formulation of a unified DPP framework, tailored to enhance supply chain transparency and support sustainable manufacturing practices. The empirical findings from our research demonstrate the DPP’s impact on supply chain transparency, providing crucial product lifecycle information that bolsters decision-making and facilitates optimal resource management. Additionally, our study suggests that the DPP model, when applied to sectors such as electronics manufacturing, promises transformative results. This research underpins the pivotal role of DPPs in the future of manufacturing, highlighting their potential to catalyze a shift towards greater transparency and sustainability. Actionable guidelines are provided for manufacturers considering the adoption of this innovative system.

On the development of a smart architecture for a sustainable manufacturing-remanufacturing system: A literature review approach

Remanufacturing is a circular manufacturing (CM) strategy that emerges as a sustainable manufacturing approach to recover the value of end-of-life products. It is a challenging process that requires to overcome intrinsic remanufacturing barriers or challenges, while addressing sustainability concerns, and achieving business model (BM) objectives. The lack of product life cycle information (PLCI) is the main source of these issues, generating significant inefficiencies and negative impacts in CM operations. Smart and industry 4.0 (I4.0) technologies have the ability to recover, process, and analyze PLCI. In fact, research is ongoing and suggested approaches are focused on implementing CM strategies using I4.0 to address reverse logistic issues, and to develop new BMs for CM. However, questions remain about on how to structure and configure these technologies as a smart architecture (SA) that simultaneously addresses: 1) remanufacturing barriers and challenges; 2) sustainability; and 3) BMs in the context of CM. The present study addresses this question by conducting a systematic literature review (SLR) to discuss current approaches, identify challenges and opportunities, and to improve understanding of SAs for CM strategies. Based on these SLR findings, this study proposes a novel conceptual design of a SA for a sustainable manufacturing-remanufacturing system towards Industry 5.0. As well, the proposed SA covers novel elements, such as a sustainable stakeholders focus, a modular customizable structure integrated in BM, and a blockchain quality and remanufacturability certificate, that are typically omitted or only partially considered by other studies. Finally, a case study based on an electric motor is used to illustrate the relevance, capabilities, and utilization of the proposed architecture.

A Comprehensive Security Architecture for Information Management throughout the Lifecycle of IoT Products

The Internet of things (IoT) is expected to have an impact on business and the world at large in a way comparable to the Internet itself. An IoT product is a physical product with an associated virtual counterpart connected to the internet with computational as well as communication capabilities. The possibility to collect information from internet-connected products and sensors gives unprecedented possibilities to improve and optimize product use and maintenance. Virtual counterpart and digital twin (DT) concepts have been proposed as a solution for providing the necessary information management throughout the whole product lifecycle, which we here call product lifecycle information management (PLIM). Security in these systems is imperative due to the multiple ways in which opponents can attack the system during the whole lifecycle of an IoT product. To address this need, the current study proposes a security architecture for the IoT, taking into particular consideration the requirements of PLIM. The security architecture has been designed for the Open Messaging Interface (O-MI) and Open Data Format (O-DF) standards for the IoT and product lifecycle management (PLM) but it is also applicable to other IoT and PLIM architectures. The proposed security architecture is capable of hindering unauthorized access to information and restricts access levels based on user roles and permissions. Based on our findings, the proposed security architecture is the first security model for PLIM to integrate and coordinate the IoT ecosystem, by dividing the security approaches into two domains: user client and product domain. The security architecture has been deployed in smart city use cases in three different European cities, Helsinki, Lyon, and Brussels, to validate the security metrics in the proposed approach. Our analysis shows that the proposed security architecture can easily integrate the security requirements of both clients and products providing solutions for them as demonstrated in the implemented use cases.

Product Lifecycle Information Flow in E-waste Handling: a Means to Increase Circularity?

Electronic waste (e-waste) is a growing waste stream. In Europe, e-waste is regulated by the Waste Electrical and Electronic Equipment (WEEE) Directive. Each manufacturer or importer is responsible for the end-of-life (EoL) treatment of the equipment it handles, although this task is usually outsourced to producer responsibility organizations (PROs) that collect and treat the e-waste. The WEEE regime has been criticized for focusing on waste handling according to the traditional linear economy, while, in a circular economy, the goal is to eliminate waste. Information sharing helps improve circularity, and digital technology is seen as enabling information transparency and visibility in the supply chain. However, there is need for empirical studies demonstrating the use of information in supply chains to improve circularity. We conducted a case study of a manufacturer, including its subsidiaries and PROs in eight European countries, in which we investigated the product lifecycle information flow related to e-waste. Our findings indicate that product lifecycle information is available, but that it is provided for purposes other than e-waste handling. Actors are willing to share this information, but it is not regarded as useful for EoL treatment since the actors involved in EoL handling believe that using this information could lead to delays and poorer performance in e-waste handling. Our findings contradict the optimistic view of digital technology as improving circularity in circular supply chain management. The findings further give reason to question the implementation of digital technology to improve the product lifecycle information flow as long as the involved actors do not request this information.

Design of electric vehicles for Industry 4.0: the case of an Autonomous Mobile Robot

In Industry 4.0, electric vehicles for logistics are widely used, such as shuttles for transporting people and Autonomous Guided Vehicles for industrial equipment. Environmental impact analyses and eco-design guidelines are essential tools in the design phase, where choices have a decisive effect on the entire product life cycle. This work proposes a method and tool aiming to make industrial electric vehicle designers aware of their choices. The proposed tool allows the preventive analysis of the different life cycle phases to highlight the consumption of materials and energy required to optimize the use and the End of Life strategy. Furthermore, it is intended to support the designers who are not provided with much product lifecycle information to obtain an overall picture of how environmental impacts are spread throughout the lifecycle; this will help provide feedback on their choices a pave the way for a more sustainable use phase in the manufacturing plant. It is based on developing a simplified and modular structure where the main product parameters are included for each life cycle phase. The tool is validated in a case study regarding the customization of an Autonomous Mobile Robot, equipped also a robotic arm; the two are connected by a customized structure. The results, which focus both on environmental and economic perspectives, contribute to filling the existing gap in the environmental evaluation of the analyzed product segment; moreover, they highlight how the material and manufacturing phase may be outstanding over the use or End of Life. This is mainly due to the short distances covered during the useful lifetime, which only cover industrial plant areas.

Product design lifecycle information model (PDLIM)

In response to rapidly changing market and customer needs, product design and development (PDD) is evolving into a human-centred and data-driven design paradigm. The design environment gets more open often involving crowdsourcing and the design process becomes more complex, considering product family design along product whole lifecycle development, and needing more data support. Therefore, it is critical to effectively capture, share, and manage design-related information in such a complex design environment. From this perspective, it is a prerequisite to have a proper product design lifecycle information model (PDLIM) to guide information gathering, sharing and management. To the best of our knowledge, currently, there lacks such a PDLIM to support effective PDD, though digital twin (DT) technology shows a great potential of supporting product lifecycle information collection and management. In this paper, the overall structure of the proposed PDLIM is firstly developed to frame in all main product lifecycle stages and the corresponding key phases for structurally capturing and storing necessary data along a product lifecycle. Secondly, key design information items against the main product lifecycle stages and their corresponding key phases are explored from literature reviews and case study analyses. Thirdly, the necessity of the identified information items in the PDLIM is qualitatively evaluated by two case studies. Finally, the PDLIM is further evaluated by applying formal object-role modelling (ORM) to demonstrate how design information items are used and interacted in exemplary design interaction scenarios, and to approve that it can be formally described and managed as an information model. The evaluation results show that the PDLIM is feasible to be adapted in a crowdsourcing-combined PDD process for supporting design management, reviewing, quality control, and next round product redesign and improvement.

Description of the Determination Processes for the Typical Research and Development Intensity Normative Indicators

The article is devoted to description of the determination processes for the typical research and development (R&D) intensity normative indicators. In the theoretical part, the authors consider the standards system formation and labor costs norms for R&D. The main composit element (CE) hierarchy of the R&D technology is given. The scheme of the development algorithm for the R&D labor costs standards is drawn. The labor costs norming technique for research works is considered. The procedure for determining the labor costs normative volume for a standardized object is determined. In the research part, the article’s authors examined the automated system components used to determine labor intensity forecast indicators in the product life cycle information support. The process of determining the normative labor costs volume based on eight consecutive stages is presented. The database composition necessary for the product life cycle information support is described. Modules for projects’ planning and monitoring in the automated system framework are considered structurally. The modules’ composition used for the analysis of production systems and forecasting production economic indicators is determined. The regulatory requirements for the production’s modules for technological support and technical regulation are given as part of the automated system work for determining labor intensity forecast indicators in the product life cycle information support. The article concludes with an algorithm for estimating the R&D work clusters’ cost and the aircraft’s distributed systems creation and development.

Coordination of Supply Chain under Blockchain System-Based Product Lifecycle Information Sharing Effort

The study proposes a supply chain contractual coordination model based on the product lifecycle information sharing effort and consumers' price sensitivity to a product with the Blockchain system. This paper examined the following five scenarios: (1) centralized supply chain with Blockchain system-based product lifecycle information sharing investment; (2) Stackelberg leader retailer processed and invested Blockchain system scenario; (3) retailer processed the Blockchain system cost-sharing scenario; (4) retailer processed Blockchain system investment through bargaining the revenue-sharing model; (5) Blockchain system investment under the cost and revenue-sharing contract. The study used the game theory reverse induction method to compare the Nash equilibrium solutions under different decision-making scenarios and discussed the chain member’s constraint condition of Blockchain system investment. We simulated and analysed the products’ lifecycle information sharing effort cost factor, the influence of price sensitivity coefficient, and expected profits of the supplier and retailer. The study results show that the product lifecycle information sharing effort under the Blockchain system increases the profit of the whole chain and decreases with the increase of customer’s price sensitivity coefficient.

Analysis of production and organisational management efficiency of Chinese family intelligent manufacturing enterprises based on IoT and machine learning technology

ABSTRACT This paper analyses how to improve the production efficiency and organisational management level of Chinese family intelligent manufacturing enterprises under the environment of big data and information integration, and ultimately enhance the economic benefits of enterprises. By reforming the organisational structure of intelligent manufacturing enterprises, in the environment of intelligent manufacturing, product life cycle information can be real-time detected and shared through sensor networks. In addition, in the enterprise intelligent manufacturing evaluation system, the system is optimised based on the neural network model in machine learning.

Development and Utilization of a Framework for Data-Driven Life Cycle Management of Battery Cells

Advanced battery cells and modules are increasingly used in a variety of applications. Tracking the state of a cell along the product life cycle and in the consecutive life cycles poses a big challenge to the current battery manufacturing industry and OEMs. This is due to diverse types of influencing factors coming from raw materials, manufacturing, usage, product integration and end of life. The goal of this paper is to develop a framework that provides the capacity to survey and assess relevant data at different stages of a battery life cycle. Here we show a data driven framework for data acquisition of relevant product life cycle information. The acquired data is then handled within a data architecture for application of effective data analytics concepts. In our results, we demonstrate how the framework can be implemented for end of life of battery management. The framework focuses on making the information from each life cycle stage available to decision makers for application of possible data analytics concepts. Such organized processing of battery life cycle data can assist in the development of new business models and improvement of existing battery technologies and services.

Consolidation of product lifecycle information within human-robot collaboration for assembly of multi-variant products

Human-robot collaboration is a key technology for realising and optimising the assembly of multi-variant products. However, the long-term and economic operation of collaborative systems requires eligible methods for the consolidation of lifecycle information and the transfer of operational and product data from the shop-floor into planning systems and vice versa. The paper introduces a systematic approach for information management and exchange in the field of collaborative assembly, based on a service-oriented architecture including process and product data exchange through AutomationML, virtual commissioning, and manufacturing execution. The methodology is evaluated in a laboratory use case and a reconfigurable demonstrator system is realized.

ONTOLOGIES OF PRODUCT DATA QUALITY MANAGEMENT

While expanding of computer usage for Product Life-cycle information support, several challenges, caused by dependence of computer documents upon interpretation means, are arising. Product data quality (PDQ) challenge is discussed in this article. Absence of data quality defects is assumed as product data quality. Data quality defect, in turn, is existence of some computer product model features, impeding downstream handling of product model. Product data quality management is assumed as interleaved transactions for detection and healing of data quality defects. The principal tasks that facilitate improvement of product design documents' quality were outlined. Computer product data quality is considered as one of aspects of quality of product design documents represented in computer form. The following tasks have to be solved for data quality improvement: detect influence of data quality defects on downstream handling of computer documents, detect interrelationship of data quality defects, set sequence of product data quality transactions, detect product shape model deviation arisen due to model healing. The new integrated approach to product data quality issues is implemented. Free accessible materials and also results of R&D [1] and experience of multy-year exploitation and permanent improvement of APM Studio modules for quality check, healing and import of CAD models [2] were considered while outlining of principal tasks mentioned in this article.

Optimal sorting policies in remanufacturing systems: Application of product life-cycle data in quality grading and end-of-use recovery

The quality of used products returned to recovery facilities is often highly uncertain. Quality grading and sorting policies are immediate solutions that are used in remanufacturing systems to handle this source of variability in incoming products. The sorting policies offered in the literature so far are mainly based on external criteria such as market trends, corporate policies and assessment of the product’s physical condition. In this study, we offer a new sorting method based on both product’s internal factors such as future reusability of components, product identity data, and product health status as well as external factors such as market trends. The purpose of this paper is to improve decision making in remanufacturing operations by integrating the product life cycle information, particularly product usage phase data, into determining both optimal sorting policies and End-of-Life/End-of-Use (EoL/EoU) decisions. To achieve this, two related analyses are conducted: first, a reusability index is derived for each product unit based on the reusability of its components, product features, and the product usage phase information. Second, the reusability index is used as a quality measure to derive the optimal EoU decision for each product category. Clustering algorithms are employed to identify similar products that could go through the same recovery process. A data set of hard disk drive Self-Monitoring Analysis and Reporting Technology (S.M.A.R.T.) coupled with simulated data has been analyzed to illustrate the application of the model. The proposed framework helps decision makers include product identity data in the EoU recovery decision making under the quality heterogeneity.

Agent Based Simulation Optimization of Waste Electrical and Electronics Equipment Recovery

The profitability of electronic waste (e-waste) recovery operations is quite challenging due to various sources of uncertainties in the quantity, quality, and timing of returns originating from consumers' behavior. The cloud-based remanufacturing concept, data collection, and information tracking technologies seem promising solutions toward the proper collection and recovery of product life cycle data under uncertainty. A comprehensive model that takes every aspect of recovery systems into account will help policy makers perform better decisions over a planning horizon. The objective of this study is to develop an agent based simulation (ABS) framework to model the overall product take-back and recovery system based on the product identity data available through cloud-based remanufacturing infrastructure. Sociodemographic properties of the consumers, attributes of the take-back programs, specific characteristics of the recovery process, and product life cycle information have all been considered to capture the optimum buy-back price (bbp) proposed for a product with the aim of controlling the timing and quality of incoming used products to collection sites for recovery. A numerical example of an electronic product take-back system and a simulation-based optimization are provided to illustrate the application of the model.

A hybrid approach for performance evaluation and optimized selection of recoverable end-of-life products in the reverse supply chain

Performance evaluation and selection of end-of-life products have emerged as crucial issues for firms looking to adopt a product recovery strategy to achieve environmental responsibility while still meeting profit goals within the reverse supply chain. However, there is still a lack of a comprehensive methodology to address the issues because of the variety of decision factors involved and the inherent uncertainties associated with them. This research proposes and investigates a multiphase hybrid approach to identify the recoverable products that best meet the criteria set (such as technical feasibility, economic benefit, and environmental effect). The proposed method simultaneously considers multiple and conflicting goals, practical constraints, and information uncertainty. First, fuzzy logic and probability theory are utilized to estimate the quality condition of used products and subsequently conduct the cost-benefit analysis based on the product life-cycle information. Then, the modified preference ranking organization method for enrichment evaluations is used as a multi-criteria decision-making tool to quantifyand aggregate the linguistic evaluation items into recovery preference factors. Further, all the qualitative and quantitative data are incorporated in a goal programming model to achieve a compromise and satisfied solution. We present a numerical example to illustrate the effectiveness and superiority of the proposed approach. The results indicate that the proposed approach can provide strong and flexible support for product recovery decision-making within the reverse supply chain.

RFID-based integrated method for electromechanical products disassembly decision-making

Proper recovery of electromechanical products can prevent pollution, improve materials recycling rate and make economic benefits as well. However, a major obstacle is that the product lifecycle information essential for the recovery decision-making is difficult to be collected. This article shows how radio frequency identification (RFID) can be utilised to record and trace the lifecycle information, hence optimising disassembly process and improving recovery efficiency. The key factors of the integrated method are demonstrated: (1) an assembly–disassembly model is constructed purposefully due to characteristics of RFID; (2) a flexible encoding and storage approach using XML format is proposed uniquely for a universal usage of the limited memory space in RFID tags; and (3) a detailed iteration process for the automatic generation of a near-optimum disassembly sequence is illustrated. In addition, a set of related application programmes are developed, and the whole integrated method is verified by a case study. This integrated method is highly extensible, and it can be applied to various types of electromechanical products.

Efficient management of product lifecycle information through a semantic platform

Products generate a large amount of information during their lifecycle. Small and medium enterprises often lack an efficient management of such an amount of information. Several tools of product lifecycle management have been developed in the last years to address this issue, but they are rarely exploited by companies, especially SMEs. The aim of our work is to present a semantic platform to integrate data along the whole product lifecycle to allow semantic search and knowledge reuse. The integration of data is realised with a reference PLM ontology, containing the main concepts and relations to describe a PLM. This ontology has a modular structure, so that it can be easily extended to describe concrete product lifecycles. An example of a real application of the semantic platform in an industrial case is reported.