Álvaro Vale e Azevedo*, António Cabaço*, M. João Falcão Silva*, Filipa Salvado*
* LNEC – National Laboratory for Civil Engineering, Lisbon, Portugal
Abstract #
This paper offers a comprehensive review of Maintenance and Asset Management, tracing their evolution over the past decades and examining significant scientific advancements, specifications, and standards. A key focus is the integration of Big Data, detailing its collection, management, and transmission to enhance decision-making, predictive maintenance, and asset performance. Additionally, the lecture addresses the digital transformation of the Architecture, Engineering, Construction, and Operations (AECO) sector, discussing innovative technologies and methodologies for improved efficiency, cost reduction, and sustainability. Future challenges within the AECO sector, such as technological, operational, and management issues, will also be analyzed. The paper aims to provide professionals with the knowledge and strategies needed to tackle these challenges and leverage opportunities presented by Big Data and digital transformation, ensuring the AECO sector remains at the forefront of technological innovation and operational excellence.
KEYWORDS
Maintenance; Asset Management; AECO Sector; Big Data Integration; Digital Transformation; Future Challenges
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Introduction #
The lecture aims to offer a comprehensive review of Maintenance and Asset Management, emphasizing their origin and evolution over the past several decades. This review will not only explore the historical progression of these fields but also examine the significant scientific developments that have emerged over time. Additionally, it will explore the various applicable specifications and standards that have been established to guide best practices within the industry.
One of the key elements to be discussed is the integration of Big Data within Maintenance and Asset Management. The lecture will elaborate on the foundations and concepts related to the collection, management, and transmission of Big Data. The ability to harness large volumes of data effectively can lead to significant advancements in decision-making processes, predictive maintenance, and overall asset performance optimization.
Furthermore, the digital transformation of the Architecture, Engineering, Construction, and Operations (AECO) sector will be a major theme. This transformation involves the adoption of innovative technologies and methodologies that revolutionize traditional practices. The work will present guidelines and strategies to effectively navigate this digital shift, ensuring that the sector can leverage new tools and techniques to enhance efficiency, reduce costs, and improve sustainability.
In the end the future challenges within the AECO sector concerning Maintenance and Asset Management will be identified and analyzed. These challenges are multifaceted, encompassing technological, operational, and management aspects that are essential to the ongoing and future success of the sector.
The work presented not only shed light on the historical and current state of Maintenance and Asset Management but also provide forward-looking insights. It aims to equip professionals in the AECO sector with the knowledge and strategies needed to address upcoming challenges and to take full advantage of the opportunities presented by Big Data integration and digital transformation, ensuring that the AECO sector remains at the forefront of technological innovation and operational excellence.
- Maintenance and Asset Management
- Origin and evolution
The assets of an organization, which can be tangible or intangible, are divided into different categories: financial, human, information, intangible, and physical assets. Focusing on physical assets, particularly buildings, holistic management is essential to maintain profitability and sustainability, addressing obsolescence and competitive pressure. Asset Management (AM), previously a financial term, now encompasses the management of physical assets, integrating various fields such as engineering, finance, risk management, logistics, and sustainability. AM has evolved since the 1980s and is now essential in multiple sectors, with increasing importance in engineering and maintenance (Salvado, et al., 2018; Rodrigues et al., 2015; Vale e Azevedo et. al, 2023).
Numerous studies highlight the importance of AM, from optimizing energy generation facilities to managing public infrastructures such as lighting and water networks. Specific methodologies have also been developed for different building types, such as schools. Physical asset management involves not only operation and monitoring but also adaptation to regulatory and quality requirements. Historically, AM has progressed from paper records to integration with organizational strategic objectives. Future technological integrations, like self-diagnosis and RFID, will enable efficient real-time communication of asset status, enhancing management and response to failures (AMBOK, 2014; Davies et al., 2011; Davies & Register, 2008).
Australia has undertaken public sector restructuring to enhance cost-effectiveness of assets. The holistic view of AM includes cost, risk, and performance analysis throughout asset lifecycles. Total Lifecycle Asset Management (TLAM) provides greater rigor, separating asset lifecycles into distinct phases from strategy to decommissioning, ensuring detailed planning and effective execution of AM activities (IAM, 2012).
International associations such as IPWEA, GFMAM, and ISEAM promote AM development, especially for built physical assets. Organizations are recognizing the importance of AM systems for strategic decision-making. Data repositories and control processes for maintenance activities are essential in AM. Applications like BUILDER, MAXIMO, and VFA support maintenance within AM, offering diverse tools for condition assessment, maintenance planning, and integrated activity management, representing the variety of techniques used in AM (Hassanain et al., 2003).
In summary, Physical Asset Management is essential for organizational efficiency and sustainability, involving an integrated, holistic approach to optimize costs, risks, and performance throughout asset lifecycles. The evolution of standards and technologies contributes to more effective management, aligning with organizational strategic objectives and fostering innovations in the sector (Salvado, et al., 2018; AMBOK, 2014).
Figure 1, adapted from IBM (2007), schematically illustrates the evolution of physical AM alongside corporate industrial thinking, leading to the recent ISO 55000 family of international standards.
Figure 1: Asset management evolution
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- Specifications and standards
In 2004, the Institute of Asset Management (IAM), in partnership with the British Standards Institute (BSI), developed PAS 55 (Publicly Available Specification 55), addressing issues such as performance, risk, and expenses throughout asset lifecycles to achieve strategic organizational planning. PAS 55 serves as a guidance framework for defining an optimized AM system and is divided into: i) PAS 55-1, identifying requirements and specifications necessary to optimize AM throughout its lifecycle; and ii) PAS 55-2, a practical guide detailing orientations or tools facilitating the application of PAS 55-1 requirements. A characteristic of PAS 55 is its specification compliance guidelines, allowing asset managers flexibility in implementation.
The ISO 55000 family of international standards, published in 2014, retained key elements contributing to the popularity and success of PAS 55, including: i) aligning organizational objectives with AM strategy, goals, plans, and activities; ii) lifecycle planning of assets; iii) risk management and a risk-based decision-making framework; and iv) integration and sustainability measures such as leadership, consultation, communication, skill development, and information management. Applying PAS 55 or ISO 55000 enables organizations to gain value perception, balancing financial, environmental, and social costs, risk, and quality (Vale e Azevedo et. al, 2020).
The British standard PAS 55, the ISO 55000 international standard family, and EU Directive 2014/24 reinforced the need for developing decision support models incorporating AM components to facilitate practical application.
Related to maintenance activities, the European standard EN 16646 introduces AM as a framework for maintenance activities, along with the relationship between the organizational strategic plan and the maintenance management system. It describes the interrelationships between the maintenance process and all other AM processes, addressing the role and importance of maintenance activities within the Asset Management system throughout its lifecycle.
- Big Data MANAGEMENT
Data management plays an essential role in building management activities, as it enhances the organization and standardization of data, information, and knowledge generated throughout the process. This function is vital to every organization because well-structured data management not only improves operational efficiency but also supports strategic decision-making. There is a growing recognition across industries that data is one of the most valuable resources an organization can possess. Effective data management seeks to control and leverage data assets to their fullest potential, ensuring data integrity, accessibility, and security (DAMA, 2017; Redman, 2018).
In the context of Big Data management (Figure 2), advanced techniques and tools are employed to handle and analyze vast amounts of data. This capability allows organizations to extract significant and relevant economic performance indicators, which are essential for the evolution of Maintenance and Asset Management practices. By harnessing the power of Big Data, companies can gain deeper insights into their operations, predict potential issues before they arise, and make more informed decisions that drive efficiency and growth (Kiron et. al, 2014; Marr, 2015).
Figure 2: Big Data management
To effectively address the anticipated challenges associated with managing Big Data, it may be necessary to employ specific tools designed to handle large volumes of information. These tools can provide advanced analytics capabilities, facilitate efficient data storage and retrieval, and ensure data integrity and security. By implementing such specialized tools, organizations can better navigate the complexities of Big Data management and fully leverage the insights derived from their data assets (Zikopoulos, and Eaton, 2012; Garlasu et. al, 2013).
In recent years, the National Laboratory for Civil Engineering (LNEC) has prioritized research aimed at integrating Big Data in Maintenance and Asset Management. This initiative is heavily based on the principles and practices of Big Data management. By leveraging advanced data analytics, LNEC seeks to enhance the accuracy and efficiency of performance assessments, ultimately contributing to the improvement of various processes and outcomes within the AECO industry in Portugal The research developed and under development, for Maintenance and Asset Management evolution based on Big Data management, comprises: i) Investment decision support; ii) integrated management and building operation and maintenance; iii) Building Information Modeling (BIM) and digital transformation; iv) Life Cycle Cost Assessment and circular economy (Vale e Azevedo et. al, 2019).
Investment decision support research includes a variety of analytical methods such as cost-benefit analysis, cost-effectiveness analysis, cost-utility analysis, multicriteria analysis, sensitivity and risk analysis, and overall economic assessment. These methods aid, based on Big Data, in making informed financial decisions by evaluating the economic implications of different investment options. Integrated management and building operation and maintenance encompasses facility management, asset management, project management, and risk management, focusing on developing and implementing comprehensive strategies to ensure effective management and operation of building facilities and assets throughout their life cycle. Building Information Modeling (BIM) and digital transformation involves, firstly, the use of BIM, particularly focusing on aspects such as Industry Foundation Classes (IFC) attributes, levels of Big Data information and detail, object parameterization, and monitoring data recording. Additionally, it covers the broader scope of digital transformation, which includes the development and utilization of information and management tools throughout all phases of the construction life cycle. Life Cycle Cost Assessment and circular economy addresses the economic evaluation of the entire life cycle costs associated with construction projects and promotes the principles of circular economy, including effective waste management practices. The aim is to minimize environmental impact and enhance sustainability by rethinking resource usage and waste generation (Akadiri and Olomolaiye, 2012; Eastman et. al, 2018).
- INTEGRATION OF Digital Transformation
With the advent of the World Wide Web, the reach, scope, scale, speed, and impacts of digitization changed dramatically. This rapid evolution led to an increased pressure on societal transformation processes as businesses, governments, and individuals alike had to adapt to an ever-changing digital landscape. Over the past decade, digitization has increasingly been utilized, not only as a technological advancement, but also as a strategic concept and rationale for a comprehensive governmental implementation of IT systems (Westerman et. al., 2014).
Digital transformation refers to the incorporation of digital technologies into every aspect of a business, fundamentally altering its operations and the way it delivers value to its customers. This expansive integration goes beyond mere technological upgrades; it requires a profound cultural shift within organizations. Companies must consistently challenge existing norms, engage in relentless experimentation, and embrace the possibility of failure as a critical aspect of the innovation process (Rogers, 2016; Vale e Azevedo et. al, 2024).
Using digital technologies, businesses can develop new processes or modify existing ones, adapt organizational cultures, and enhance customer experiences to meet the ever-evolving demands and requirements of the market. As information management migrates from paper-based systems to digital spreadsheets, and then to sophisticated smart applications, there arises a unique opportunity to reimagine and redesign these processes with advanced digital technology. This transformation is not merely about digital tools or platforms; it represents a holistic shift in how organizations operate and think. It necessitates a continuous adaptation to new digital realities, driving businesses and governments to rethink traditional methodologies and practices (Schwertner, 2017).
Essentially, digital transformation is about leveraging innovative technology to achieve greater efficiency, agility, and ultimately, superior value creation for all stakeholders involved. Through this ongoing process of digitization, organizations can not only keep pace with technological advancements but also proactively shape the future of their industries (Heinze, et al., 2018; Vale e Azevedo et. al, 2022).
The AECO industry plays a very significant role with an important impact in the global economy. This sector is responsible for the design, construction, and maintenance of the built environment, including buildings, infrastructure, and industrial facilities. Its impact is far-reaching, influencing not only economic growth but also societal development and environmental sustainability. In terms of economic contribution, the AECO sector generates substantial revenue and creates millions of jobs worldwide (European Commission, 2011; World Economic Forum, 2016).
From large-scale urban development projects to residential housing and commercial real estate, the industry sustains a wide range of businesses, from small subcontractors to multinational corporations. The ripple effect of this activity supports related industries such as manufacturing, supply chain logistics, and financial services. However, the representativeness of the sector is marked by the lack of productivity that is reflected in an inefficient image of both the process and the service delivered to the final customer (EU Regulation n.305/2011) (McKinsey Global Institute, 2017; Lucas and Aguiar, 2018).
In global terms, the AECO sector presents a medium level of digitization, although with a strong probability of rising through the implementation because of the 4th Industrial Revolution. Within the AECO sector, the construction sector is not the end of the list of sectors that implement digitization, as a process and methodology of use. The greatest difficulty to be overcome may be a transversal modernization of the sector which, as it represents the performance of different agents at different stages of the construction life cycle, implies using BIM as an integrated system for storing information (BuildingSMART International, 2017; coBuilder, 2021; CT197, 2021;).
The AECO sector is poised for a much-needed digital renovation. Confronted with persistent challenges such as inefficiencies in project execution, ongoing safety concerns, and stagnating labor productivity levels, the industry’s historically slow adoption of advanced technologies has arrived at a critical juncture. Embracing digital transformation is essential and entails revamping existing processes and integrating cutting-edge tools that leverage data. This data-driven approach aims to enhance communication, boost efficiency, elevate productivity, and significantly improve safety measures across the board (BCG, 2016).
The integration of digital technologies within the AECO sector stands to position key stakeholders for considerable profitable growth within this highly competitive industry, while simultaneously addressing pressing workforce issues. However, transforming the AECO sector encompasses more than the mere implementation of state-of-the-art technologies. It involves a comprehensive overhaul that, when executed correctly, can propagate improvements throughout interconnected processes. To achieve this transformation, companies must first undertake a thorough assessment of their current operational state. This initial step is critical in identifying areas of inefficiency and pinpointing where digital tools can make the most significant impact. Following this, a forward-looking strategy must be developed to delineate the desired future state of the business. This strategic planning involves setting clear, actionable goals and outlining the necessary steps to achieve them. The final phase of the transformation process involves mapping out a detailed journey from the current state to the envisioned future (PwC, 2019; Shapiro et al., 2019)
This roadmap should incorporate a timeline for implementation, resource allocation, and milestones to track progress. By following this structured approach, businesses in the AECO sector can ensure a smoother transition and maximize the benefits of digital transformation. Therefore, the digital renovation of the AECO sector promises to revolutionize the industry. Enhanced data utilization will lead to better decision-making, streamlined operations, and improved collaboration among all stakeholders. The focus on digital transformation is not just a technological upgrade but a strategic move towards a more efficient, productive, and safe working environment, fostering sustainable growth and innovation across the entire industry (Deloitte, 2020).
Digital transformation goes far beyond digitalizing analog functions. It enables a fundamental shift in how to operate so that it can compete in a digital world. Figure 3 presents the areas of transformation that are ultimately enabled by end-user adoption (Shapiro et al., 2019): i) Digital Business (to enable growth); ii) Digital Process (to improve efficiency and profitability); and iii) Digital Backbone (to facilitate usability for processes needs).
Figure 3: Digital transformation, adapted from (Shapiro et al., 2019)
- FUTURE CHALLENGES
Based on the previous sections, some future challenges aligned with Maintenance and Asset Management within the AECO sector are identified, namely: i) Integration of Big Data; ii) Data Security and Privacy; iii) Digital Transformation; iv) Standardization of Practices; v) Predictive Maintenance Implementation; vi) Sustainability and Environmental Impact; vii) Cost Management: viii) Workforce Training and Adaptation; ix) Interoperability of Systems; x) Change Management. The main strategies and actions to overcome these challenges are described in Table 1
Table 1: Challenges, strategies and actions for Management and Asset Management future evolution
| CHALLENGES | STRATEGIES | ACTIONS | |
| Integration of Big Data | Effectively collecting, managing, and transmitting large volumes of data to enhance decision-making and predictive maintenance | Implement a Robust Data Management and Analytics Platform |
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| Data Security and Privacy | Ensuring the security and privacy of sensitive data collected and used in Maintenance and Asset Management processes | Implement a Comprehensive Cybersecurity Framework |
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| Digital Transformation | Navigating the shift from traditional practices to innovative technologies and methodologies in the AECO sector | Develop a Clear and Phased Digital Transformation Roadmap |
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| Standardization of Practices | Establishing and adhering to universal specifications and standards for best practices in Maintenance and Asset Management | Establish and Implement Industry-Aligned Best Practices and Standards |
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| Predictive Maintenance Implementation | Developing and implementing predictive maintenance strategies using advanced analytics and data science techniques | Integrate Advanced Predictive Analytics Tools into Maintenance Processes |
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| Sustainability and Environmental Impact | Incorporating sustainable practices and reducing the environmental footprint of Maintenance and Asset Management activities | Implement a Comprehensive Sustainability Program |
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| Cost Management | Balancing the cost of implementing new technologies and methodologies with the potential savings and efficiency gains | Implement a Robust Budgeting and Monitoring System |
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| Workforce Training and Adaptation | Ensuring that the workforce is adequately trained to handle new tools, technologies, and methodologies introduced by digital transformation | Implement a Continuous Learning and Development Program |
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| Interoperability of Systems | Ensuring seamless integration and communication between various digital systems and platforms used in Maintenance and Asset Management | Adopt a Standardized Integration Framework |
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| Change Management | Managing organizational change to adopt new practices and technologies while maintaining operational continuity and stakeholder engagement | Develop and Implement a Comprehensive Change Management Plan |
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- FINAL REMARKS
This paper offers an in-depth review of maintenance and asset management, tracing their evolution and highlighting scientific advancements. It emphasizes the integration of Big Data and digital transformation within the AECO sector, providing practical guidelines for leveraging these technologies to enhance efficiency and sustainability. The work addresses future challenges, equipping professionals with strategies to navigate changes and capitalize on emerging opportunities, ensuring the AECO sector remains at the forefront of innovation and operational excellence.
The AECO sector must proactively address numerous future challenges in maintenance and asset management to ensure continued progress and competitiveness. Key areas requiring attention include the integration of Big Data, which promises significant advancements in decision-making and predictive maintenance, but also necessitates robust data security and privacy measures. The ongoing digital transformation demands not only the adoption of new technologies but also the standardization of practices across the industry. This standardization will facilitate smoother implementation of predictive maintenance techniques, further enhancing operational efficiency and asset longevity. Additionally, the sector must prioritize sustainability and environmental impact to meet regulatory requirements and societal expectations.
Furthermore, effective cost management remains essential, requiring adequate budgeting and continuous financial monitoring. Workforce training and adaptation are essential to equip employees with the skills needed to navigate new technologies and methodologies. Ensuring interoperability of systems will foster seamless communication and data exchange, enhancing overall efficiency. In conclusion, adept change management strategies will be vital in guiding organizations through these transitions, minimizing resistance and maximizing engagement. By addressing these challenges through targeted strategies and actions, the AECO sector can drive innovation, improve operational excellence, and maintain a sustainable trajectory, securing its place at the forefront of industry advancements.
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