Lifecycle Management Research Articles

Regulatory Considerations for Stability Studies of Co-Processed Active Pharmaceutical Ingredient.

A co-processed active pharmaceutical ingredient (CP API) is the combination of an active pharmaceutical ingredient (API) with non-active component(s). This technology has been demonstrated to offer numerous benefits, including but not limited to improved API properties and stability. The infrastructure requirements are such that the manufacture of a CP API is typically best suited for an API facility. CP API has been regulated as either an API or as a drug product intermediate (DPI). This variability in the designation has led to ambiguities on the regulatory CMC expectations in the CP API including the stability of CP API and CP API containing products which, in turn has hampered the broader application of this technology in the pharmaceutical industry. This difference in designation also resulted in challenges to the lifecycle management of the regulatory documentation for the CMC information of the CP API.This white paper represents the proposals for the regulatory requirements on stability studies related to CP API and to drug product containing CP API by the CP API Working Group (WG) of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ). Additionally, considerations and the WG's recommendations on the stability studies of CP API from different manufacturing sites or processes and post-approval changes for product containing CP API are described.

From Traditional to Transformational: Leveraging Digital Twins for Advanced Testing in Life Insurance

The Life Insurance industry is undergoing a profound digital transformation, transitioning from traditional, static methodologies to agile, data-intelligent ecosystems capable of adapting to dynamic customer demands and stringent regulatory complexities. At the forefront of this shift is the adoption of digital twins—high- fidelity virtual replicas of physical systems, processes, and assets—specifically for testing and optimizing Life Insurance platforms. This paper provides a deep dive into the role of Digital twins in the Life Insurance domain, exploring their powerful applications in underwriting, policy lifecycle management, and claims processing. By accurately simulating complex, real-world scenarios, Digital twins enable predictive testing environmentsthat refine system resilience, preemptively identify risk exposures, and ensure operational continuity. Through this sophisticated digital infrastructure, insurers gain a transformative tool for enhancing precision, boosting reliability, and driving efficiency in core insurance processes. This research investigates the architecture, applications, and strategic trajectory of Digital twins as next generation testing mechanisms reshaping Life Insurance. Keywords: Digital Twin, Life Insurance, Underwriting, Policy Lifecycle Management, Claims Processing, Virtual Simulation, System Resilience, Operational Efficiency, Data-Driven Testing, Digital Transformation, Predictive Modeling, Testing Framework, Real-World Scenarios

Strategic Innovation Management: A Framework for Digital Product Portfolio Optimization

Abstract—This research introduces a framework for managing digital product portfolios in rapidly evolving markets. By examining the intersection of strategic management and digital innovation, we present a structured approach to portfolio optimization that enhances value creation while minimizing technology risk. The study draws on real-world implementations across multiple industries, demonstrating how organizations can effectively balance innovation initiatives with resource constraints. Our findings reveal that organizations implementing this framework achieved a 40% improvement in portfolio performance and significantly reduced technology risk. The paper provides practical guidelines for executives and product leaders to evaluate, prioritize, and optimize digital product portfolios while maintaining strategic alignment with enterprise objectives. Keywords— Digital Product Portfolio, Strategic Innovation Management, Portfolio Optimization, Technology Risk Management, Digital Transformation, Innovation Strategy, Resource Allocation, Product Lifecycle Management, Multigeneration product planning

A new reliability-based procedure for life-cycle management of new and existing constructions

A new reliability-based procedure for life-cycle management of new and existing constructions

Towards sustainable cognitive digital twins: A portfolio management tool for waste mitigation

The rapid integration of Cognitive Digital Twins (CDTs) across various industries has revolutionized operational practices, leading to enhanced efficiency and improved decision-making capabilities. However, this technological advancement is accompanied by significant environmental implications, particularly regarding the management of electronic waste (e-waste) and digital waste. While e-waste primarily concerns the disposal of obsolete hardware, digital waste encompasses inefficiencies, redundancies, and unnecessary consumption of computational resources in the digital environment. This paper emphasizes the importance of understanding the lifecycle impacts of CDTs and advocates for the implementation of sustainable practices in their management. To address these challenges, we introduce Digital Twin Portfolio Management (DTPM) as a systematic framework for optimizing the CDT ecosystem. We also present the Digital Twin Triple Bottom Line as a framework for assessing the technical, economic, and environmental impacts of CDT implementations, ensuring that organizations can identify inefficiencies and align their operations with broader sustainability objectives. The findings elucidate the various types of waste generated by CDTs, establishing a critical link between digital asset management and environmental sustainability. Additionally, the study advocates for improved APM practices tailored to the unique challenges posed by CDTs, contributing valuable insights to the evolving discourse on IT portfolio management. Future research directions are also discussed, including the need for expanded case studies and longitudinal investigations to enhance the generalizability and understanding of CDT lifecycle management.

Application of circular economy principles to midstream infrastructural sector: A review of strategies for waste minimization and recycling

Circular economy in midstream operations promotes resource reuse, waste reduction, and sustainable pipeline life cycle management. The transition toward a sustainable oil and gas industry needs to be enabled through the adoption of this concept, especially in the midstream sector, where environmental impact is high. This review focuses on practices in the waste minimization and recycling strategy of midstream infrastructure, including material recycling, reuse of processing debris and the conversion of waste into valuables. It underlines potential lifecycle environmental savings and resource efficiency, besides emphasizing on how innovative approaches are important in mitigating the ecological footprint of midstream activities. It also points out the knowledge gaps on practical integration of the circular economy principles within this very industry and came up with actionable recommendations for industry stakeholders. Through the analysis of the most recent published literatures and case studies of successful implementation, it has been indicated that many companies that use these techniques have succeeded in reducing waste output by over 30%. Conclusively, full scrutiny by this review has helped to attain a holistic approach towards sustainability in the oil and gas industry through wider adoption of recycling and sustainable practices in midstream operations.

Artificial Intelligence as a tool for enhancing Building Information Modeling (BIM)

Building Information Modeling (BIM) has revolutionized the Architecture, Engineering, and Construction (AEC) industry, transforming how building lifecycle data is managed and visualized. By consolidating physical and functional characteristics into a shared digital model, BIM facilitates collaboration, minimizes rework, and streamlines planning and execution. In sustainability, BIM supports "Green BIM" practices that reduce carbon footprints by enabling energy modeling and lifecycle analysis. However, despite these advances, BIM faces interoperability issues, largely due to proprietary software formats, leading to isolated data silos that impede efficient data exchange across platforms. The integration of Artificial Intelligence (AI) into BIM introduces groundbreaking solutions to these challenges. AI enhances BIM through automation of design validation, clash detection, and real-time data analysis, transforming BIM into an adaptive system capable of proactive decision-making. AI applications, including predictive maintenance, generative design, and real-time construction monitoring, promise higher safety standards, reduced errors, and improved lifecycle management. However, AI-enhanced BIM adoption is hampered by technical, ethical, and financial challenges, such as data quality, privacy concerns, and high implementation costs. Addressing these obstacles with standardized data protocols, workforce upskilling, and collaborative frameworks can maximize the potential of AI-driven BIM, advancing sustainability, efficiency, and resilience within the construction industry.

Evaluation of product lifecycle management and digital twin integration in aviation field

In today's world, digital transformation is becoming increasingly crucial in industry. The Digital Twins and simulations become much more important with growing complexity of products, the need to accelerate product development processes while reducing costs. The increasing value of Digital Twins is prompting organizations in the aviation industry to actively utilize them in research and development efforts. However, due the idea of difficulties of using Digital Twins in the industries, product developers don’t have a clear idea where to begin. This article provides readers with a general overview of the current situation by offering an examination of the aviation sector. Initially, the concept of Digital Twin, its evolution, and relevant studies are explored, followed by an examination of the impact of creating Digital Twins for companies operating in aviation on the product development process. In this study, unlike other published works, the concept of Digital Twin is explained under three subheadings. These include the Design Digital Twin for design steps, the Production Digital Twin for manufacturing processes, and the Performance Digital Twin for post-delivery work related to the product. The final section of the study evaluates the contribution of Product Lifecycle Management (PLM) systems to the process of creating Digital Twins and the advantages they provide to companies in product development processes. The present research work does not contain any studies performed on animals/humans subjects by any of the authors.

A governance framework model for cloud computing: role of AI, security, compliance, and management

The rapid adoption of cloud computing has transformed how organizations manage their IT resources, necessitating robust governance frameworks to address the complexities and risks inherent in cloud environments. This review proposes a comprehensive governance framework model that integrates the roles of artificial intelligence (AI), security, compliance, and management to enhance the effectiveness of cloud operations. AI plays a critical role in optimizing resource allocation and improving decision-making processes within cloud governance. By leveraging machine learning algorithms, organizations can achieve dynamic resource management, predictive analytics, and automated compliance monitoring, which enhance operational efficiency and reduce human error. Furthermore, the integration of AI in security management facilitates real-time threat detection and response, allowing organizations to proactively mitigate risks associated with data breaches and cyberattacks. Security is a paramount concern in cloud governance, given the shared responsibility model between cloud providers and clients. This framework emphasizes the implementation of comprehensive security measures, including data encryption, identity management, and incident response protocols, to safeguard sensitive information and maintain customer trust. Compliance with regulatory requirements is essential in ensuring organizational accountability and minimizing legal risks. The proposed governance model incorporates automated compliance checks and reporting mechanisms, ensuring adherence to industry-specific regulations such as GDPR and HIPAA. Moreover, effective management of cloud resources is crucial for optimizing performance and controlling costs. The governance framework outlines best practices for lifecycle management, cost optimization, and resource allocation, enabling organizations to achieve their strategic objectives. This governance framework model underscores the importance of integrating AI, security, compliance, and management for a holistic approach to cloud governance, providing organizations with the necessary tools to navigate the complexities of cloud computing while maximizing its benefits.

A business process management lifecycle framework for continuous improvement towards operational excellence: lessons learned from a longitudinal study in a Brazilian organisation

Purpose The purpose of this study is to offer a business process management (BPM) framework with information and insights on designing, implementing, using and assessing business processes for continuous improvement towards operational excellence. Design/methodology/approach An action research is carried out over two and a half years on the BPM evolution of a Brazilian entertainment organisation. Findings Research provides a novel procedural framework towards improving the understanding of how a complete lifecycle approach for BPM can be implemented for continuous improvement, embracing the critical success factors for each lifecycle phase to achieve operational excellence. Information technology and project management are critical success factors resulting in project barriers. Strategic alignment, top management support, collaborative environment, methods and methodology, and focus on users and culture are acknowledged as main enablers. Findings reinforce the importance of an organisation analysis phase to begin the BPM development and highlight the assessment and improvement phase to respond to organisational environment dynamism. Practical implications Practitioners can benefit from the lessons learnt and the proposed framework, which serves as a rigorous methodology to achieve operational excellence in their real-world settings. Originality/value This paper goes beyond the well-known design and analysis phases of BPM development, generally studied with an individual focus, offering a complete lifecycle approach for continuous improvement, analysing each phase, from the drawing board to its use and evaluation. It counts on an original longitudinal study rather than a single-time assessment study.

Gwydion: Efficient auto-scaling for complex containerized applications in Kubernetes through Reinforcement Learning

Containers have reshaped application deployment and life-cycle management in recent cloud platforms. The paradigm shift from large monolithic applications to complex graphs of loosely-coupled microservices aims to increase deployment flexibility and operational efficiency. However, efficient allocation and scaling of microservice applications is challenging due to their intricate inter-dependencies. Existing works do not consider microservice dependencies, which could lead to the application’s performance degradation when service demand increases. As dependencies increase, communication between microservices becomes more complex and frequent, leading to slower response times and higher resource consumption, especially during high demand. In addition, performance issues in one microservice can also trigger a ripple effect across dependent services, exacerbating the performance degradation across the entire application. This paper studies the impact of microservice inter-dependencies in auto-scaling by proposing Gwydion, a novel framework that enables different auto-scaling goals through Reinforcement Learning (RL) algorithms. Gwydion has been developed based on the OpenAI Gym library and customized for the popular Kubernetes (K8s) platform to bridge the gap between RL and auto-scaling research by training RL algorithms on real cloud environments for two opposing reward strategies: cost-aware and latency-aware. Gwydion focuses on improving resource usage and reducing the application’s response time by considering microservice inter-dependencies when scaling horizontally. Experiments with microservice benchmark applications, such as Redis Cluster (RC) and Online Boutique (OB), show that RL agents can reduce deployment costs and the application’s response time compared to default scaling mechanisms, achieving up to 50% lower latency while avoiding performance degradation. For RC, cost-aware algorithms can reduce the number of deployed pods (2 to 4), resulting in slightly higher latency (300μs to 6 ms) but lower resource consumption. For OB, all RL algorithms exhibit a notable response time improvement by considering all microservices in the observation space, enabling the sequential triggering of actions across different deployments. This leads to nearly 30% cost savings while maintaining consistently lower latency throughout the experiment. Gwydion aims to advance auto-scaling research in a rapidly evolving dynamic cloud environment.

Using dynamic release modeling to predict historic and current macro- and microplastic releases

Confronting the pervasive challenge of plastic pollution, our study pioneers a dynamic release model to quantify the historic and current plastic emissions. Utilizing Dynamic Probabilistic Material Flow Analysis (DPMFA) coupled to a release model, we comprehensively tracked emissions of macro- and microplastics in Switzerland from 1950 to 2022, covering 35 product categories and 183 release pathways for seven polymers (LDPE, HDPE, PP, PS, EPS, PVC, PET). The plastic usage exhibited a “Peak Plastic” around the year 2010 with a subsequent decrease in per capita use of plastics from 120±5 to 107±5 kg/cap in 2022. Over the considered timeframe, 27±1 kg/cap of macroplastics and 4 ± 1 kg/cap of microplastics were released to the environment, with the most substantial contributions coming from LDPE and PET. The overall emission factor was 0.66±0.07 % for macroplastics and 0.010±0.01 % for microplastics. The model can provide a crucial framework for crafting targeted interventions toward sustainable plastic lifecycle management.

Analyzing the impact of holistic building design on the process of lifecycle management of building structures

This research examines how Holistic Building Design (HBD) affects Lifecycle Management of Building Structures in the ever-changing construction market. HBD includes adaptability, environmental sustainability, maintenance, and disaster preparation. It is a key idea in the present boom in resilient and sustainable building techniques. A surprising dearth of quantitative empirical research on HBD’s impact on LMBS considering the field’s growing importance. This study uses a quantitative method to explore the relationship between essential HBD components and LMBS outcomes especially Extended Service Life (ESL) and Optimized Performance and Value (OPV) are critical factors to address this information gap. The quantitative study polled 171 construction industry professionals and utilized Structural Equation Modelling to examine the data. This approach was selected for its ability to explore complex relationships between variables and constructs. HBD components Adaptability and Retrofitting (AAR), Environmental Considerations and Sustainability (ECS), Maintenance and Inspection Programs (MIP), and Resilience and Disaster Preparedness (RDP) profoundly influenced the Enhanced Service Life (ESL) and Optimized Performance and Value (OPV) elements of LMBS. Building adaptation and retrofitting, maintenance and inspection programs, and other activities increased building value and lifespan. These findings have major theoretical and practical implications. The work potentially fills a research gap by providing actual evidence on HBD-LMBS linkages. Practically, the results advise construction industry specialists to use HBD ideas for sustainable building management. Finally, our work illuminates the vital roles of HBD components in LMBS and paves the way for ecologically friendly building approaches.

Systematic Review of Battery Life Cycle Management: A Framework for European Regulation Compliance

Batteries are fundamental to the sustainable energy transition, playing a key role in both powering devices and storing renewable energy. They are also essential in the shift towards greener automotive solutions. However, battery life cycles face significant environmental challenges, including the harmful impacts of extraction and refining processes and inefficiencies in recycling. Both researchers and policymakers are striving to improve battery technologies through a combination of bottom–up innovations and top–down regulations. This study aims to bridge the gap between scientific advancements and policy frameworks by conducting a Systematic Literature Review of 177 papers. The review identifies innovative solutions to mitigate challenges across the battery life cycle, from production to disposal. A key outcome of this work is the creation of the life cycle management framework, designed to align scientific developments with regulatory strategies, providing an integrated approach to address life cycle challenges. This framework offers a comprehensive tool to guide stakeholders in fostering a sustainable battery ecosystem, contributing to the objectives set by the European Commission’s battery regulation.

Revisiting a Faculty Career Management Life Cycle Model: Anticipating and Navigating Career Transitions in Academic Medicine

Career management models are valuable tools for faculty pursuing a career in academic medicine. These models help faculty transition through various stages of their careers, including commonly pursued academic advancements from assistant professor to full professor, as well as less common transitions like moving from full-time to part-time status, taking sabbaticals, going on medical leave, or assuming executive leadership roles. The success of faculty members across these stages is influenced by both environmental factors and individual-level characteristics. Recognizing career stages and transitions, as well as the impact of personal and environmental factors on career growth, is crucial. The proposed Faculty Career Self-Management Model (FCSM) provides a visual and descriptive framework to guide individual faculty and the professionals who support them in understanding, preparing for, and navigating career stages and professional transitions to build and sustain meaningful careers in academic medicine. The FCSM serves as a framework to explore, develop, and share best practices in supporting faculty vitality across the career lifespan.

Recent developments in the mechanical properties and recycling of fiber‐reinforced polymer composites

AbstractFiber‐reinforced polymer composites (FRPCs) have become integral to various industries due to their exceptional strength‐to‐weight ratio, corrosion resistance, and versatility. Recent advancements in the properties and recycling of FRPCs reflect significant progress in performance and sustainability. This paper reviews the latest developments in FRPC technology, highlighting innovations in material formulation, including advancements in fiber types, matrix materials, and hybrid composites that enhance mechanical properties. Furthermore, this review emphasizes the modification of matrices by incorporating graphene, which aims to improve the chemical bonding and mechanical interlocking between fiber and matrix. Additionally, it addresses recent breakthroughs in recycling technologies, focusing on methods such as chemical recycling, mechanical recycling, and developing eco‐friendly matrices. Integrating these advancements aims to improve the lifecycle management of FRPCs, reduce environmental impact, and support the transition towards a circular economy. This review underscores the balance between enhancing composite performance and promoting sustainable practices, paving the way for more environmentally responsible applications of FRPCs.Highlights The different types of fiber‐reinforced polymer composites have been thoroughly reviewed. How does graphene affect the mechanical behavior of fiber composite laminates? Provide a systematic correlation and comparison between fabrication methods, materials, and properties. The recycling methods for fiber‐reinforced polymer composites have been deliberated.

Decision-Making Model for Life Cycle Management of Aircraft Components

This paper presents a novel decision-making framework for the life cycle management of aircraft components, integrating advanced data analytics, artificial intelligence, and predictive maintenance strategies. The proposed model addresses the challenges of balancing safety, reliability, and cost-effectiveness in aircraft maintenance. By using real-time health monitoring systems, failure probability models, and economic analysis, the framework enables more informed and dynamic maintenance strategies. The model incorporates a comprehensive approach that combines reliability assessment, economic analysis, and continuous re-evaluation to optimize maintenance, replacement, and life extension decisions. The optimization method on the base of genetic algorithm (GA) is employed to minimize total life cycle costs while maintaining component reliability within acceptable thresholds. The framework’s effectiveness is demonstrated through case studies on three distinct aircraft components: mechanical, avionics, and engine. These studies showcase the model’s versatility in handling different failure patterns and maintenance requirements. This study introduces a data-driven decision-making framework for optimizing the life cycle management of aircraft components, focusing on reliability, cost-effectiveness, and safety. To achieve optimal maintenance scheduling and resource allocation, a GA is employed, allowing for an effective exploration of complex solution spaces and enabling dynamic decision-making based on real-time data inputs. The GA-based optimization approach minimizes total life cycle costs while maintaining component reliability, with the framework’s effectiveness demonstrated through case studies on key aircraft components. Key findings from the case study demonstrate significant cost reductions through optimization, with mechanical components showing a 10% more reduction in total life cycle costs, avionics components achieving a 14% more cost reduction, and engine components demonstrating a 7% more decrease in total costs. The research also presents an optimized dynamic maintenance schedule that adapts to real-time component health data, extending component lifespans and reducing unexpected failures. The framework effectively addresses key industry challenges such as no fault found events while minimizing unexpected failures and enhancing the overall reliability and safety of aircraft maintenance practices. Sensitivity analysis further demonstrates the model’s robustness, showing stable performance under varying failure rates, maintenance costs, and degradation rates. The study contributes a scalable approach to predictive maintenance, balancing safety, cost, and resource allocation in dynamic operational environments.

Principles for Sustainable Integration of BIM and Digital Twin Technologies in Industrial Infrastructure

As industries evolve towards greater digitalization, integrating Building Information Modeling (BIM) and digital twin technologies presents a unique opportunity to enhance sustainability in industrial infrastructure. This paper formulates a comprehensive set of principles aimed at guiding the sustainable integration of these technologies within the context of modern industrial facilities, often referred to as “Factories of the Future”. The principles are designed to address critical sustainability challenges, including minimizing environmental impact, optimizing resource efficiency, and ensuring long-term resilience. Through a detailed examination of lifecycle management, data interoperability, and collaborative stakeholder engagement, this work provides a strategic framework for leveraging digital technologies to achieve sustainability goals. The principles outlined in this paper not only promote greener industrial practices but also pave the way for innovation in the sustainable development of industrial infrastructure. This framework is intended to serve as a foundation for future research and practical application, supporting the global shift towards more sustainable industrial operations.

Comparative life cycle assessment and route optimization modeling of smart versus conventional municipal waste collection: Environmental impact analysis in an urban context

This study conducts a life cycle assessment comparing smart and conventional municipal waste collection systems over a 10-year period in a medium-sized urban area, employing the IMPACT 2002+ method and simulation modeling. The smart waste collection system demonstrated significant environmental advantages across key impact categories. Global Warming Potential was reduced by 45.7 % (19,209,995 kg CO₂ eq vs. 35,370,480 kg CO₂ eq) through optimized route planning and reduced fuel consumption. Human health impacts improved substantially, with the smart system showing a net positive effect (-9.7756731 DALY) compared to the conventional system's detrimental impact (23.574054 DALY). Ecosystem quality impacts decreased by 37.3 % (15,662,705 vs. 24,999,196 PDFm²yr), while resource depletion was 46 % lower in the smart system, despite increased mineral extraction for electronic components. The simulation revealed a 52 % reduction in vehicle distance traveled (38,535.36 vs. 80,282.00 km/month). While demonstrating clear environmental benefits, the study identifies challenges in electronic component lifecycle management and mineral resource recovery. Future research should prioritize developing recyclable components, integrating renewable energy sources, and optimizing end-of-life management strategies. These findings provide practical guidance for municipalities transitioning to smart waste collection systems, particularly in medium-sized urban areas. Real-world implementations in cities like Amsterdam and Barcelona have shown similar improvements, with route efficiency gains of 35–40 %, validating the potential of smart waste management technologies in urban sustainability initiatives.

Product lifecycle management as a sustainable approach within the Moroccan social and solidarity economy sector

Product Lifecycle Management (PLM) is a crucial strategy that presents a range of benefits at both technical and organizational levels. It involves the integration of collaborative methods that facilitate the sharing, centralization, and harmonization of product information, while also streamlining the processes of information exchange. This study serves as an initial endeavor to introduce PLM within the cottage industry by examining the integration of PLM and the resulting organizational transformations. The research follows a structured three-step methodology. Initially, a comprehensive literature review was conducted to explore the concept under investigation. Subsequently, a survey is carried out within the Moroccan social economy sector to identify prevalent challenges. The survey sample comprises 500 workshops from diverse regions and sectors. An analysis of the results using SPSS and Excel software reveals that organizational and management issues constitute the primary obstacles faced by the sector, representing 40% of the total challenges. Notably, production-related challenges emerge as the most significant, accounting for 68.89% of the total challenges in the sector. In the final step, the ceramics sector is chosen as the focal industry, and a VBA Excel-based tool is developed to address the identified issues. This tool incorporates four essential functionalities -user management, order management, complaints management, and cost management- that are currently lacking in the sector, facilitating organizational change management. The proposed functionalities are subsequently implemented by two pilot ceramics companies. The outcomes of this implementation reveal various barriers that could hinder collaborative efforts post-implementation.