This paper aims to develop a tool for measuring the clients’ maturity in smart maintenance supply networks. The assessment tool is developed and validated for corporate facilities management organizations using case studies and expert consultation. Based on application of the assessment tool in five cases, conclusions are presented about the levels of maturity found and the strengths and limitations of the assessment tool itself. Also, implications for further research are proposed.
MULTIFILE
The adoption of new technologies requires people to work differently and adopt new ways of thinking. This, however, is complicated because social conventions in professional disciplines are deeply rooted and have a long history. An extreme case as an exemplar was studied to investigate social change in a maintenance network. With concepts from stewardship theory and entrepreneurship literature, the case study is used to develop a preliminary model for managing social change in maintenance networks. The model presented is a first attempt to link stewardship theory to the practice of maintenance management. It will be refined and validated in future research and can complement other theories, such as agency theory and transaction cost economics, in explaining socio-technical phenomena in construction management. The practical contribution of this research to the construction management field is that it deepens our understanding of the clients’ leadership role.
Optimization of aviation maintenance, repair, and overhaul (MRO) operations has been of high interest in recent years for both the knowledge institutions and the industrial community as a total of approximately $70 billion has been spent on MRO activities in 2018 which represents around 10% of an airline’s annual operational cost (IATA, 2019). Moreover, the aircraft MRO tasks vary from routine inspections to heavy overhauls and are typically characterized by unpredictable process times and material requirements. Especially nowadays due to the unprecedent COVID-19 crisis, the aviation sector is facing significant challenges, and the MRO companies strive to strengthen their competitive position and respond to the increasing demand for more efficient, cost-effective, and sustainable processes. Currently, most maintenance strategies employ preventive maintenance as an industrial standard, which is based on fixed and predetermined schedules. Preventive maintenance is a long-time preferred strategy, due to increased flight safety and relatively simple implementation (Phillips et al., 2010). However, its main drawback stems from the fact that the actual time of failure and the replacement interval of a component are hard to predict resulting in an inevitable suboptimal utilization of material and labor. This has two repercussions: first, the reduced availability of assets, the reduced capacity of maintenance facilities, and the increased costs for both the MRO provider and the operator. Second, the increased waste from an environmental standpoint, as the suboptimal use of assets, is also associated with wasted remaining lifetime for aircraft parts which are replaced, while this isn’t yet necessary (e.g., Nguyen et al., 2019).The recently introduced, condition-based maintenance (CBM) and predictive maintenance (PdM) data-driven strategies aim to reduce maintenance costs, maxi-mize availability, and contribute to sustainable operations by offering tailored pro-grams that can potentially result in optimally planned, just-in-time maintenance meaning reduction in material waste and unneeded inspections.
In order to stay competitive and respond to the increasing demand for steady and predictable aircraft turnaround times, process optimization has been identified by Maintenance, Repair and Overhaul (MRO) SMEs in the aviation industry as their key element for innovation. Indeed, MRO SMEs have always been looking for options to organize their work as efficient as possible, which often resulted in applying lean business organization solutions. However, their aircraft maintenance processes stay characterized by unpredictable process times and material requirements. Lean business methodologies are unable to change this fact. This problem is often compensated by large buffers in terms of time, personnel and parts, leading to a relatively expensive and inefficient process. To tackle this problem of unpredictability, MRO SMEs want to explore the possibilities of data mining: the exploration and analysis of large quantities of their own historical maintenance data, with the meaning of discovering useful knowledge from seemingly unrelated data. Ideally, it will help predict failures in the maintenance process and thus better anticipate repair times and material requirements. With this, MRO SMEs face two challenges. First, the data they have available is often fragmented and non-transparent, while standardized data availability is a basic requirement for successful data analysis. Second, it is difficult to find meaningful patterns within these data sets because no operative system for data mining exists in the industry. This RAAK MKB project is initiated by the Aviation Academy of the Amsterdam University of Applied Sciences (Hogeschool van Amsterdan, hereinafter: HvA), in direct cooperation with the industry, to help MRO SMEs improve their maintenance process. Its main aim is to develop new knowledge of - and a method for - data mining. To do so, the current state of data presence within MRO SMEs is explored, mapped, categorized, cleaned and prepared. This will result in readable data sets that have predictive value for key elements of the maintenance process. Secondly, analysis principles are developed to interpret this data. These principles are translated into an easy-to-use data mining (IT)tool, helping MRO SMEs to predict their maintenance requirements in terms of costs and time, allowing them to adapt their maintenance process accordingly. In several case studies these products are tested and further improved. This is a resubmission of an earlier proposal dated October 2015 (3rd round) entitled ‘Data mining for MRO process optimization’ (number 2015-03-23M). We believe the merits of the proposal are substantial, and sufficient to be awarded a grant. The text of this submission is essentially unchanged from the previous proposal. Where text has been added – for clarification – this has been marked in yellow. Almost all of these new text parts are taken from our rebuttal (hoor en wederhoor), submitted in January 2016.
‘Dieren in de dijk’ aims to address the issue of animal burrows in earthen levees, which compromise the integrity of flood protection systems in low-lying areas. Earthen levees attract animals that dig tunnels and cause damages, yet there is limited scientific knowledge on the extent of the problem and effective approaches to mitigate the risk. Recent experimental research has demonstrated the severe impact of animal burrows on levee safety, raising concerns among levee management authorities. The consortium's ambition is to provide levee managers with validated action perspectives for managing animal burrows, transitioning from a reactive to a proactive risk-based management approach. The objectives of the project include improving failure probability estimation in levee sections with animal burrows and enhancing risk mitigation capacity. This involves understanding animal behavior and failure processes, reviewing existing and testing new deterrence, detection, and monitoring approaches, and offering action perspectives for levee managers. Results will be integrated into an open-access wiki-platform for guidance of professionals and in education of the next generation. The project's methodology involves focus groups to review the state-of-the-art and set the scene for subsequent steps, fact-finding fieldwork to develop and evaluate risk reduction measures, modeling failure processes, and processing diverse quantitative and qualitative data. Progress workshops and collaboration with stakeholders will ensure relevant and supported solutions. By addressing the knowledge gaps and providing practical guidance, the project aims to enable levee managers to effectively manage animal burrows in levees, both during routine maintenance and high-water emergencies. With the increasing frequency of high river discharges and storm surges due to climate change, early detection and repair of animal burrows become even more crucial. The project's outcomes will contribute to a long-term vision of proactive risk-based management for levees, safeguarding the Netherlands and Belgium against flood risks.
The digitalization of railroad infrastructure is aimed at the improvement of maintenance and construction activities. Currently, inspections are done manually, with a domain expert classifying objects. This is a challenging task, considering the Netherlands has more than 3,400 km of railways that need to be inspected and maintained.
