EDUBox: finding suitable locations for offgrid mobile classrooms in the context of underserved communities

The refugee crisis and the COVID-19 pandemic continue to negatively impact access to education, and especially disproportionately affect underserved communities. Apart from access, such communities experience additional barriers including inadequate classroom infrastructure and suitable localization of such infrastructure. This paper aims to provide an analytical framework to identify the most suitable locations for mobile classrooms for underserved communities, thereby mitigating the lack of access to equitable education for underserved communities. To construct the analytical framework, we conduct a critical literature review to conceptualize the educational needs of underserved communities. Next, we proposed parameters that may be applicable for determining locationally metrics that match the educational needs of underserved communities. On this basis, we explore tools and methods applicable for suitability analysis and developed a geo-information framework that integrates an analytical hierarchy process tool to prioritize parameters decision-makers can apply to identify optimal areas to locate classroom infrastructure. This framework was applied to a use case of determining suitable location areas for an innovative mobile classroom (EDUBox) in Jordan. Using the framework, we demonstrate its applicability by identifying appropriate locations adapted to the tertiary and vocational education needs of underserved persons including refugee communities

More than 10 years of industry 4.0 in the Netherlands:an opinion on promises, achievements, and emerging challenges

The concept of Industry 4.0, as a means to move forward in the industrial ecosystem, has reached an important turning point. Where do we stand now in terms of industrial innovation and transition? This opinion paper provides an overview of the situation in the Netherlands, a reflection on what has been achieved by the Industry 4.0 paradigm, and the necessary way forward to solidify its implementation. Tentative results reveal that the pervasiveness of Industry 4.0 applications is sector-specific. This work provides industrial stakeholders and academics with useful suggestions and a possible path to move towards better integration of Industry 4.0 in company reality. In this opinion paper, we employ a mixed methods research methodology to argue that, based on our findings on industrial adaptation in The Netherlands, Industry 4.0 is the outcome of an evolutionary process and not of a revolution, as it is often claimed

The Added Value of Asset Management in Power Generation Plants in Developing Countries Context: a Case for Kenya

This dissertation explores and presents a framework for asset management of power generation facilities with a specific focus of managing such facilities in the developing countries context. The framework leverages on risk management phases proposed in the ISO 31010, and importantly, the phases propose a structured approach through which failure risks in assets are systematically identified, analyzed and consequently mitigated through formulating appropriate maintenance strategies. However, prior to implementing a risk management approach, understanding the risk concept in the context of maintenance decision making is important. From literature, however, such understanding is not straightforward which also influences the process of assessing asset failure risks. This is evident in Chapter 2 of this thesis dissertation where maintenance decision support structures so far developed seldom support robust assessment of failure risks in operable assets. Furthermore, from Chapter 2, several risk assessment methodologies are presented in asset management literature, yet a decision framework for selecting appropriate techniques while taking into account the business and operation context of the organization are lacking. This aspect is addressed in Chapter 3 where a selection methodology is developed, and based on the Analytic Network Process approach. The selection methodology takes into account practical decision making competencies necessary for performing risk assessment in the context of maintenance decision making. Apart from selection challenges, it was also apparent from literature that existing risk assessment methods were seldom dynamic in the sense that the risk assessment exercise rarely evolved with availability of new sources of risk. This aspect is addressed in Chapter 4 where a dynamic risk assessment methodology specific for maintenance decision making is developed. The methodology leverages on the hierarchical Bayes approach for updating risk assessment results with availability of new sources of risks. The practical perspective and applicability of the methodology is demonstrated through the application case of thermal power plant equipment failures. Chapters 5 and 6 evaluate a very important aspect in maintenance decision making – root cause analysis. From literature, the root cause analysis exercise is dominated by qualitative and semi-quantitative approaches which often are susceptible to decision makers’ bias. Yet, understanding the focal root causes of failure is important for developing effective risk mitigation strategies, or maintenance strategies. Thus in Chapter 5, a data exploration framework which leverages on maintenance data is developed. Importantly, the framework incorporates multivariate and cluster analysis techniques for exploring causal failure associations embedded in maintenance data. On the basis of the explored causal associations, causal maps are generated and used as the basis of identifying focal root causes of recurrent equipment failure. Chapter 6 extends the data exploration approach by incorporating association rule mining framework for extracting important causal association rules which are important for mapping the focal root causes of equipment failure. Chapter 7 extends the risk mitigation phase and explores human aspects which are responsible for maintenance errors, and embedded in maintenance data. Thus leveraging on the Reason’s model, error-provoking factors embedded in maintenance data is evaluated from which, managerial strategies are proposed for mitigating such factors. Chapter 8 presents a simulation modelling framework developed for quantifying the impact of alternative maintenance intervention strategies on power plant performance and spare part replenishment. The modelling framework considers a multi-echelon replenishment network, and further evaluates the added value of component recondition on part availability. Finally, Chapters 9 and 10 evaluate performance management aspects in maintenance decision making where a maintenance maturity model is developed for assessing maintenance capabilities within the organization. The performance management aspect also extends to a developed Hoshin-Kanri framework for deploying maintenance objectives to all organization levels – strategic, tactical and operational. Lastly, Chapter 11 presents the conclusions and contributions to the state of the art, as well as proposals for future research in the context of asset management, with focus of risk management.nrpages: 327status: publishe

ARAM2: een adaptieve risico-assessment methode

Het Centrum voor Industrieel Beleid van de KU Leuven heeft een rijke traditie inzake onderzoek in onderhoudsmanagement. In dit artikel geeft Peter Chemweno, doctoraatsstudent bij Prof. Liliane Pintelon, een korte samenvatting van een door hem ontwikkelde methode voor risico-assessment. Doel is een oplossing te vinden voor de huidige, vaak beperkte methodes voor storingsanalyse die in de praktijk gebruikt worden. Hiertoe wordt een geïntegreerde, holistische risico-management methode, ARAM² - Adaptive Risk Assessment Methodology for Maintenance Decision Support - voorgesteld. Het stap-voor-stap toepassen van deze methode ondersteunt het beslissingsproces voor een meer efficiënte en vooral meer effectieve onderhoudsstrategie.status: publishe

Simulating the impact of deferred equipment maintenance

Deferring the maintenance activity can often be detrimental to the asset’s operation. This is often the case where minimal repair actions are performed for severe failures. Here, deferring the maintenance activity ends up accelerating equipment deterioration, thereby resulting in more severe failures. In this paper, a discrete event simulation model for quantifying the effect of deferred maintenance on system performance such as production loss and observed failure rates is proposed. The simulation study incorporates four maintenance activities proposed in the ISO 14224 that include inspection, modify, extensive repair and corrective replacement. Each maintenance activity is evaluated based on its impact on the remaining useful life of the component. A real life case of a thermal power plant is discussed.status: publishe

Simulating the impact of repair strategies on repairable spare part provisioning in a multi-echelon replenishment system

In today’s industries, optimal spare parts provisioning performs a critical role towards sustaining the asset’s operational capabilities. This is often achieved through mitigating the impact of unnecessary downtime associated with sub-optimal replenishment lead times. In this regard, spare parts provisioning is mentioned as an important mitigation strategy, more so for repairable components. Here, spare part demand is initiated by equipment failure. Moreover, the repairable systems presume the possibility for component reconditioning thereby influencing the demand for new parts. Invariably, this influences the stocking policy implemented by the organization. Depending on the echelon the spare part is sourced, different transshipment policies may be adapted, though with varying cost impacts. In addition to the implemented policy, several maintenance aspects may influence spare part demand. These include the component’s reliability, spare part quality and the repair strategy. To realistically model such complexities associated with spare part replenishment in such instances, simulation approaches are often explored. In this study, a simulation modelling approach for spare part replenishment is proposed. The model evaluates the impact of alternative provisioning systems applicable for repairable systems. Moreover, the model mimics the effect of alternative repair strategies on system availability whereof several performance measures are defined. These measures include system reliability, system availability and replenishment cost. In addition, different replenishment strategies are implemented, e.g. regular and emergency replenishment. Of course, depending on the replenishment strategy adopted and also the echelon the part is sourced from, varying replenishment costs are often incurred. The simulation approach is implemented in the empirical case of thermal power plant engines. The results highlight the important influence of component reconditioning on the spare parts replenishment policy. Moreover, the component quality influences the number of feasible component reconditioning cycles, thus impacting the spare part stocking policy. Finally, the usefulness of the model for decision support is highlighted, more so in the context of joint maintenance and repairable inventory systems.status: accepte

Evaluating the impact of spare parts pooling strategy on the maintenance of unreliable repairable systems

In today’s industries, optimal spare parts provisioning plays a critical role towards sustaining the asset’s operational capabilities. In this context, spare parts pooling is increasingly mentioned as a plausible approach for optimizing spare parts management, more so for repairable systems. In this sense, several frameworks are proposed in literature, though largely analytical, thus limiting their capabilities with respect to modeling complex repairable systems. Moreover, the nature of interactions often account for aspects such as system reliability, imperfect component reconditioning, repair capacity and spare parts inventory that is multi-echelon in nature. To realistically model such complexities, simulation approaches are often explored. This paper presents a discrete event simulation modeling study. The simulation model mimics the impact of several aspects on unreliable repairable systems. The aspects include the repair capacity, component reconditioning process, and multi-echelon spare part provisioning strategy. Moreover, the influence of spare parts quality aspects is evaluated and demonstrated in the case study of critical system for a thermal power plant.no isbnstatus: publishe

Integrating challenge-based learning into a mobile classroom environment for Jordanian camp refugees: a position paper

Jordan hosts one of the largest refugee populations, many of whom still live in camps. Until now, they have had limited access to the labor market. One of the reasons for this is their limited ability to meet the demands of the labor market. The purpose of this article is to explore ways to better support refugees in Jordan to develop appropriate skills to improve their access to the labor market and their social well-being. To this end, relevant literature on the refugee situation in Jordan, the current labor market, and refugees' skill levels and development was reviewed. Based on this, an integrative framework for appropriate skills development for refugees in Jordan was developed using a mobile classroom and challenge-based learning. This framework is being implemented and tested in Jordan in the form of the Edubox learning environment

Asset maintenance maturity model as a structured guide to maintenance process maturity

The rising cost of doing business coupled with a fast changing competitive business environment is forcing organizations to consider adapting asset management strategies, not just as a cost saving measure, but also to remain competitive. Implementing an efficient and effective maintenance program is one way of achieving this desired competitiveness. However implementing such maintenance program is often not straightforward due to the lack of a structured decision support approach. Capability maturity models present such structured approach. This paper proposes a generic asset maintenance maturity model (AMMM) as a structured guide for implementing new maintenance programs, evaluating existing programs and finally directing continuous improvement activities likely to lead to high levels of asset maintenance efficiency and effectiveness. Central to the proposed model is the use of risk assessment methodologies at different phases during the evolution process of asset maintenance maturity in the organization.status: publishe