Asset Life Cycle Research Articles

Supporting construction stakeholders with the circular economy: A trans-scaler framework to understand the holistic approach

Although the construction sector is one of the least digitized sectors, the last decade has been a period that some qualify as the 4th industrial revolution, notably with the adoption of Building Information Modelling (BIM). However, the construction industry is still one of the most resource-intensive sectors, generating Megatons of waste every year. To decrease the impact of the construction on the environment, authorities are getting interested in adopting a circular economy (CE) approach, including servitization. Although there is an emulsion around the circular economy approach, organisational tools to help construction practitioners to move to a CE approach are dramatically lacking. The purpose of the paper is to develop a BIM-based trans-scalar theoretical framework to support practitioners in their understanding and the implementation of the CE approach. The trans-scalar theoretical framework is established with data extracted from a research portfolio fuelled by three main databases, Scopus, RIBA (Royal Institute of British Architects) Plan of Work and BIM standards. First, the RIBA framework and the information delivery cycle were adjusted to incorporate the sustainable end-of-life, as a phase in the CE context. Based on theoretical foundations, the main contribution of this paper is the trans-scalar theoretical framework developing and clarifying what are the main asset lifecycle phases (including the end-of-life), their related stakeholders, and the interplays between them, in the UK context. The paper also organizes holistically two scales, the asset lifecycle phases and the material flow, whether new or recovered, in the context of BIM and CE. Some future areas of research are presented, including how the BIM-based trans-scalar theoretical framework could be improved with inputs from construction experts.

Architecting a BIM-Based Digital Twin Platform for Airport Asset Management: A Model-Based System Engineering with SysML Approach

Airports play an essential role within the transportation and infrastructure sectors. As modernizing and expanding airport infrastructures receive a higher priority, addressing inefficiencies in capital expenditures (CapEx) and operational expenses (OpEx) through transformative digital ecosystems is gaining an increasing level of interest. Building information modeling (BIM) can form a basis to enable an end-to-end digital delivery platform, where airport life cycle data can be utilized for actionable insights. This study proposes a scalable, novel BIM-based modularized platform architecture based on model-based system engineering (MBSE) principles with systems modeling language (SysML) for optimal collection, integration, management, and utilization of airport critical asset data. This platform architecture aims at acting as a metaframework that enables an airport digital twin through cohesive and structured view of asset life cycle information for insightful actions by major airport stakeholders. Research methodology features an online survey and focus group discussions for data collection; mixed method analysis for data analysis; MBSE with SysML for data mapping; and prototype demonstration and an expert opinion survey for validation. Adopting a scalable BIM-based digital platform is anticipated to result in boosts in business value of airport infrastructures by sustaining value generation in operations and decreasing upfront costs for technology implementation.

A STUDY ON CRYPTOCURRENCY-IT IS THE TIME FOR BANKS SHOULD INVOLVE WITH CRYPTO ASSETS

“In today’s time internet is proved to be the hub for economic activities. It makes life of the human being easy and stress-free. Nowadays people are taking keen interest in trading of stocks and cryptocurrency, around 83% of Indians are aware of stock trading and 16% of them own it. In 2018 government motivated the public to get involve them self in stock & crypto trading but on other hand RBI banned banks to have anything with virtual currency. Meanwhile world took huge step in adoption of cryptocurrency and now it’s time for bank to get evolved itself with crypto assets as these assets removal of intermediaries, fees and other roadblocks to large transaction, creating a faster and less expensive global payment network. Crypto assets will give more exposure to financial system by providing an alternative to traditional assets and taking the financial access to wider range. It will provide the transparency throughout the asset lifecycle. To avoid any left behind bank should adopt cryptocurrency rather than treating it as an enemy.” Keywords: Cryptocurrency, Trading, financial system, Roadblocks, Lifecycle, Global payment network, Bank.

Nested Lifecycles-Improving the Visibility of Product Lifespans in Smart Factories

Within the smart factory environment, we have a complex system of systems composed of Industry 4.0/digital technologies and assets with varying lifespans. Different degrees of innovation maturity and different lifespans of integrated assets within the industrial internet of things (IIOT) are considered problematic and lead to different perspectives on asset lifecycles as they impact significantly on the asset lifespans. This leads to the loss of a clear end-of-life phase defined in existing Product Lifecycle Management (PLM) models. Through an integrative literature review, this study introduces the concept of nested lifecycles that takes a systems perspective to asset management, and considers subsystems with different lifespans that must be managed holistically by different actors with different perspectives. Additionally, this study provides a framework to derive strategies for lifecycle management by allowing the nested lifecycles to be clearly identified and then addressed. From the theoretical perspective, the notion of nested lifecycles provides a novel viewpoint for the asset management and PLM research community. From the managerial perspective, the proposed framework will help managers identify why and where collaboration between different actors may create difficulties due to their varying outlooks and training.

Tacit knowledge and a multi-method approach in Asset Management

This paper has two main objectives. The first one is to reflect on the validity of data in analysis and projections that underpin the engineering asset management of organizations, considering, on the one hand, a certain resistance or even inadequate use of data and information of a subjective nature and; on the other hand, a consolidated reliance on quantitative approaches and decisions based on data series. The second objective is to contextualize the applicability of combining qualitative data based on experts’ experience and on the tacit knowledge built in organizations, with approaches based essentially on quantitative data, according to the data availability and the decision scenario over the asset life cycle. We present two application of an approach combining quali and quanti data. One example interrelates Statistics with Psychology and the other combines elicitated data about asset indicators with parameters deterministically calculated. Both applications aiming at providing more realistic indicators and supporting the Asset Management process to make more assertive decisions.

Best Practices in Establishing Business Case for Implementing Blockchain Solution in Aerospace

<div class="section abstract"><div class="htmlview paragraph">The aircraft asset life cycle processes are rapidly being digitalized. Many novel technologies enabled processes of recording these electronic transactions are being emerged. One such technology for recording electronic transactions securely is Blockchain, defined as distributed ledger technologies which includes enterprise blockchain. Blockchain is not widely used in the aerospace industry due to lack of technical understanding and questions about its benefits. Assessment and establishment of business case for implementing blockchain based solution is needed. The aerospace industry is very conservative when it comes to technology adoption and hence it is difficult to change legacy processes. Additionally, the industry is very fragmented. The technology is advancing at a faster rate and applies across geographies under various regulatory oversight which makes blockchain based solution implementation challenging.</div><div class="htmlview paragraph">G-31 electronic transactions for aerospace standards committee of SAE International has conducted a study on determination of cost benefits from implementing a blockchain solution. This study resulted in development of Aerospace Recommended Practice (ARP) 6984 and was published recently. This recommended practice lays out a methodology for qualifying and quantifying the benefits of replacing or augmenting a legacy process with a blockchain solution. This paper presents summary and overview of this study and provides a teaser for ARP 6984.</div></div>

A Study on The Intention to Use Total Cost of Ownership System in Tenaga Nasional Berhad

This research aims to discover factors that influence behavioural intention among Tenaga Nasional Berhad (TNB) Grid employee to adopt Total Cost of Ownership (TCO) system as a new technology in daily operation. TCO system is expected to improve and optimize OPEX of TNB Grid. This research adopted Technology Acceptance Model (TAM) by Davis et al. (1989) as the framework of the study. Despite utilising perceived usefulness and perceived ease of use as the dimension, this research study extends the investigation by incorporating perceived risks as per model by Khasawneh (2015). This research study is based on the data collected from a survey questionnaire that investigates factors that influence behavioural intention to accept TCO system among TNB Grid employee. The quantitative method is used to gather the information in the non-contrived study setting to provide a natural environment of the TNB Grid. The stratified random sampling method is used whereby the target population; employees dealing with the entire asset lifecycle management of high voltage equipment, is divided into meaningful segments such as job’s position, office location, department and years of service. The research discovered there are strong relationship between perceived usefulness, perceived ease of use and perceived risks with the behavioural intention to adopt TCO system among TNB Grid employees. The research also highlighted the important element to be considered by TNB in developing the efficient TCO system which is the ease-of-use system. The positive attitude will drive behavioural intention to use the system if the user perceives ease of use.

Development of a System Dynamics Simulation for Assessing Manufacturing Systems Based on the Digital Twin Concept

Historically, manufacturing system researchers and managers have often failed to consider all the areas, factors, and implications of a process within an integrated manufacturing model. Thus, the aim of this research was to develop an integral modeling approach for manufacturing processes in order to assess their status and performance. For this purpose, a novel conceptual model consisting of an integral definition of areas and flows is applied. As a result, manufacturing systems can be modeled, considering all related flows and decision-making options in the respective areas of production, maintenance, and quality. As a result, these models serve as the basis for the integral management and control of manufacturing systems in digital twin models for the regulation of process stability and quality with maintenance strategies. Thus, a system dynamics simulation model is developed for a metallurgical process. The goal of the simulation model is to provide a digital manufacturing system regulated with different maintenance, quality, and production strategies in order to secure quality and delivery service. The results show how the monitoring of all flows together with the optimal strategies in the quality and maintenance areas as a result of a regulated system can enable companies to increase their profitability and customer service level. In conclusion, the applied simulation case study allows better decision making, ensuring continuous optimization along the manufacturing asset lifecycle and providing a unique selling proposition for equipment producers and service engineering suppliers, as well as for production and assembly companies.

Maintenance Digital Twin using vibration data

Maintenance represents a critical aspect of manufacturing systems. Its optimization may lead companies to save costs related to production losses and can extend the whole lifecycle of assets or components. This paper aims at proposing a methodology for evaluating the behavior of systems for maintenance purpose by means of analysis carried out on real vibration data collected in the work environment. To this purpose, a digital twin approach has been developed and the statistical method of the control charts has been integrated to conduct the analysis about the vibration data. The methodology has been applied to a real case study in order to analyze the behavior of an electric motor used in the industrial sector and the results show that the method is effective in predicting possible failures that can lead to apply preventive maintenance actions.

Process Digital Twin and Its Application in Petrochemical Industry

Digital twin (DT) is drawing significant attention both from the academia, industry and government. However, people from different fields have different understandings and cognitions about DT. In addition, most of the DT application scenarios discussed belong to discrete manufacturing and are not suitable for process manufacturing. Petrochemical industry is a typical process manufacturing with multi-scale hierarchical and functional structure in space and time. This contribution focuses on topics on the application of DT in petrochemical industry including: 1) The specific DT definition by process industry. 2) The three key elements and design of chemical DT. 3) Features and application scenarios of chemical DT from the view of model precision, model scale and asset life cycle. 4) The Four P’s maturity framework of chemical DT, and 5) Prospects for the development of chemical DT.

Application study of a classification and encoding system in meticulous management of Zhengzhou Metro enterprises

In views of management of the entire life cycle of enterprise assets, it is necessary to systematically design an encoding system to distinguish and track the attribute changes of assets. Based on the integration analysis of classification encoding scheme and management information dimension, this paper designs and describes an asset classification and its encoding system, including asset encoding, attribute signature and location encoding structure definition. An important concept of cost accounting and its processing flow path performed in finance about entire life cycle of goods and material had been described too with the increment and uniqueness of transaction flow evidences. The encoding system takes account of the application requirements of information meticulous management for material purchasing, inventory, assets, equipment maintenance, cost accounting, etc. in aspects of data collection, data sharing and collaborative processing.

Development of Shale Gas in Brazil: A Business-Oriented Analysis

Brazil figures amongst the top 10 countries with greatest technically recoverable shale gas resources around the globe. However, shale gas business has not yet taken off. This paper aims to provide a business-oriented analysis on the drivers and opportunities for developing shale gas in the country. Methodology consists of going through critical non-technical factors (above the surface issues) of each one of the Brazilian basins with technically recoverable shale gas resources. Results show that from a business perspective the potential development of unconventionals in Brazil over the next decade or so will most likely be linked with the production declining faced in some conventional gas fields, and hence, a mechanism to extend asset life cycle and sustain existing jobs. Keywords: Brazil; Oil and gas exploration; Unconventional resources; Unconventional gas; Shale gas; Brazilian sedimentary basins; Market development. DOI: 10.7176/RHSS/12-2-04 Publication date: January 31 st 2022

XAI Sustainable Human in the Loop Maintenance

The field of Explainable Artificial Intelligence (XAI) is a relatively new approach to AI, with the aim to provide black box algorithms with human intelligible narrative functionality. It is most often in end-of-life considerations of the asset lifecycle that sustainability issues are encountered. Modern maintenance practice requires a holistic understanding of lifecycle and options for sustainable asset treatments. human in the loop solutions offer a way to leverage both machine and human skill sets to provide the next level of automaton solutions for industrial maintenance activities. This paper presents a framework for human in the loop Intelligent and Sustainable Maintenance. In bridging the gap between machines and humans XAI leverages the best of both worlds to provide a new level of agility to cyber assisted maintenance activities and full lifecycle consideration of assets; a notion that is necessary throughout the organization in the achievement of sustainability goals set by governments around the world in the achievement of a net zero carbon emission economy.

Informing Value: industry analysis for complex process facility digital twins

The organizational capability of a firm to create, integrate and maintain cyber versions of complex physical systems known as Digital Twins is a key enabler for joining the 4th Industrial Revolution. This article highlights the business case for firms in the petrochemical process industry to manage digital twins as valuable business assets based on academic and business literature, webcast and live presentations, and the professional experiences of the author. A digital twin maturity model is provided to differentiate how each level of data integration contributes to informing. Three digital twin asset valuation models are introduced to illustrate how digital twins can inform value in different contexts. Findings include how knowledge is generated from digital twins, and how an informing attribute of decision making referred to here as ‘insight value’ can be realized from maintaining digital twins over the full asset lifecycle. Many software applications and tools have become available for firms to adopt this innovative technology; however, integration with the diverse and often siloed systems that serve as data sources have been hampered by inconsistent data governance, data exchange requirements, and interface standards. This article, the first in a series of three, explores on-going efforts to mitigate this problem of practice as interest in application of this innovative technology reaches the tipping point where industry-wide adoption drives greater efficiency and improves decision making throughout the complex facility lifecycle.

Improvement of oil and gas production infrastructure as an effective tool for maintaining basic oil and gas production

The modern world is a complex mechanism in which each process, direction, sphere of activity, despite visual differences, ultimately creates a single complex element aimed at ensuring human life. One of the key processes occurring on the planet is the extraction of hydrocarbons. The article proposes to consider a solution that will contribute to ensuring the efficiency of oil and gas production processes, will extend the life cycle of mature oil and gas production assets of the Russian Federation (hereinafter referred to as the RF) and extend their economic profitability. Economic and technological efficiency from infrastructure reengineering measures is individual for each region, and directly depends on the volume of oil, water production and the state of the ground infrastructure. The described areas of infrastructure reengineering, in aggregate, represent an effective tool for optimizing operating and capital costs, increasing the reliability of technological equipment, removing infrastructure restrictions, which will contribute to the achievement of the set task - maintaining oil production at mature assets. Keywords: facilities for oil treatment; gas compression; reservoir pressure maintenance; power supply; engineering networks; operating costs; reengineering.

Assessing the Maturity of the Asset Lifecycle Management in the Case of the Massachusetts Bay Transportation Authority (MBTA)

Asset management is a central capability that organizations have to perform well. Asset management is concerned about the management of assets that are valuable or potentially valuable to an organization. This article focuses on asset management as it is performed in the railway transit industry. The past decade has seen a number of positive changes in the way that transit agencies manage their assets. While many transit agencies have introduced asset management approaches, work still needs to be done in the area of how we assess the maturity of asset management programs. This article proposes a framework for assessing the maturity of asset management programs, especially those that are used to manage individual assets according to their lifecycles. To illustrate the value of the proposed asset management maturity framework, we describe the asset management transformation at a transit agency and use the proposed framework to document the gains of the improvement effort.

An Actor–Network Approach to Developing a Life Cycle BIM Maturity Model (LCBMM)

Building information modelling (BIM) has considerable potential for addressing sustainability issues in construction, but its benefits can be constrained by the failure to adopt BIM across the full project life cycle. Systematic whole-of-life BIM adoption can be supported by maturity models, but most models are limited by a lack of theoretical grounding, socio-technical dichotomies and the failure to adequately consider the full asset life cycle, often by overlooking the operations phase. This study aims to (1) develop a BIM maturity model that addresses these limitations by (2) using an in-depth analysis of an early adopter case study, thus addressing the lack of empirical research in BIM adoption experiences. A single interpretive research study was conducted to qualitatively analyse a US-based university. The data were gathered through interviews, field visits and document analysis. Actor–network theory (ANT) concepts scaffolded the analytical approach. The findings show that a complex BIM socio-technical network emerged, developed and converged during the project management stage but struggled to achieve durability as an ongoing solution to facilities management. By analysing the elements of success and failure across each stage, the researchers distilled five key lessons to achieve whole-of-life BIM maturity and proposed a life cycle BIM maturity model (LCBMM) supported by a practice guide.

The efficacy analysis method of input–output for substations based on LCC theory

Along with the deepening of the power system reform, the input and output evaluation and analysis of asset became more and more important. Arounding the goal of comprehensive optimization of safety, efficiency and cost throughout the life cycle of assets, this paper constructed a quantitative evaluation model for asset input–output analysis, and put forward an input–output analysis method combining the boston matrix method and the equivalent analysis method. Actual substations’ input cost and output efficiency analysis verified the method feasibility, which could provide decision-making support for optimizing power grid asset management strategies and enhancing asset value operation benefits.

Prioritisation Assessment and Robust Predictive System for Medical Equipment: A Comprehensive Strategic Maintenance Management.

The advancement of technology in medical equipment has significantly improved healthcare services. However, failures in upkeeping reliability, availability, and safety affect the healthcare services quality and significant impact can be observed in operations' expenses. The effective and comprehensive medical equipment assessment and monitoring throughout the maintenance phase of the asset life cycle can enhance the equipment reliability, availability, and safety. The study aims to develop the prioritisation assessment and predictive systems that measure the priority of medical equipment's preventive maintenance, corrective maintenance, and replacement programmes. The proposed predictive model is constructed by analysing features of 13,352 medical equipment used in public healthcare clinics in Malaysia. The proposed system comprises three stages: prioritisation analysis, model training, and predictive model development. In this study, we proposed 16 combinations of novel features to be used for prioritisation assessment and prediction of preventive maintenance, corrective maintenance, and replacement programme. The modified k-Means algorithm is proposed during the prioritisation analysis to automatically distinguish raw data into three main clusters of prioritisation assessment. Subsequently, these clusters are fed into and tested with six machine learning algorithms for the predictive prioritisation system. The best predictive models for medical equipment's preventive maintenance, corrective maintenance, and replacement programmes are selected among the tested machine learning algorithms. Findings indicate that the Support Vector Machine performs the best in preventive maintenance and replacement programme prioritisation predictive systems with the highest accuracy of 99.42 and 99.80%, respectively. Meanwhile, K-Nearest Neighbour yielded the highest accuracy in corrective maintenance prioritisation predictive systems with 98.93%. Based on the promising results, clinical engineers and healthcare providers can widely adopt the proposed prioritisation assessment and predictive systems in managing expenses, reporting, scheduling, materials, and workforce.

New FMEA Risks Ranking Approach Utilizing Four Fuzzy Logic Systems

Process equipment and plant maintenance problems are complex in the oil refinery business, since effective maintenance needs to ensure the reliability and availability of the plant. Failure Mode and Effects Analysis (FMEA) is a risk assessment tool that aims to determine possible failure modes, and to reduce the ratio of unknown failure modes, by identifying business-critical systems and the risks of their failures. For the identified failure modes, FMEA determines risk mitigation action(s). The goal is to prevent failure and keep assets and plants running at peak performance by providing fully integrated operations, maintenance, turnarounds, modifications, and asset integrity solutions, during all phases of the asset life cycle. This research was based on FMEA use/application in refineries’ units, and proposes the new fuzzy FMEA risk quantification approach method: “four fuzzy logic system”. The model included a pre-assessment, by sets of fuzzy logic systems, that examined the input parameters that affected the variables of severity, occurrence, and detectability. The proposed model prioritized risks better and addressed the drawbacks of the conventional FMEA method.