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<\/a><\/p>\n\u00a0Flowchart 1.<\/p>\n
Life Span for our Integrated Maintenance :<\/h4>\n
Deciding lifespan for our integrated system, As we can see that maximum timeline of event retrofitting of column is 60 years. If we can analyse the other intervention are less then 60 years. We are deciding lifespan of our integrated system is 60 years. As other all interventions can be done multiple time within 60 years. Burner cleaning(BC) can be done 6 times. Pipe replacement (PR) can be done twice and Leak inspection (LI) can be done 12 times. So that 60 years will be perfect lifespan for our calculations. To make sure we refer to [1] Issarasak, Sittiporn & Chotipanich, Sarich & Pitt, Michael. (2021), which says that typica major replacement is done in residential building at 60 years.<\/p>\n
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Integrated Maintenance Strategies :<\/strong><\/p>\n We have two different systems that is residential building and district heating system through pipes and heat sources, we considerd an HVAC system to make our system more holistic but will not take it under our maintainence strategies. As we already discussed above about our goal, we hva decided two distinct maintenance strategies. First is corrective and another is preventive maintenance strategies.<\/p>\n Table 1.<\/p>\n \u00a0These are the seperate and combine timeline for each system when we are considering corretive maintenance strategy<\/p>\n <\/p>\n By Combining maintenance for system options , the different different duration of interventions are calculated. The sum of interventions shows that design option Pre cast column (PRC) for residential building and PET+Heatboiler of District heating system. In this context both the interventions for building and heating system are done concurrently. The reult shows 87 days of downtime in the span of 60 years.<\/p>\n <\/p>\n <\/p>\n Preventive maintenance is a used in construction industry to reduce chances of failure and unplanned downtime, which can effect the liveable condition such as for our building if the heating system is having downtime, it effects the comfort of people who are staying in that building. Preventive maintenance ensures that our systems to work properly and kept disruptions to a minimum. Pipe replacement (PR) and Major maintenance in the column (MJR) event are decided to be done 5 years before as planned in corrective maintenance to reduce downtime. Preventive maintenance strategy reduces the impact of Mean time to repair also.<\/p>\n Table 2.<\/p>\n These are the seperate and combine timeline for each system when we are considering Preventive maintenance strategy.<\/p>\n By Combining maintenance for system options while considering preventive maintenance strategy , the different different duration of interventions are calculated. The sum of interventions shows that design option Pre cast column (PRC) for residential building and PET+Heatboiler of District heating system. In this context both the interventions for building and heating system are done concurrently . The result shows 72 days of downtime which is 15 days lower then correctiuve maintenance strategy.<\/p>\n <\/p>\n In the context to explore more design space for more efficient combinations assumptions of\u00a0 ranges of maintenance events are made. Based on a set of preferences and defined ranges, a simulation checks all possible combinations to find the most efficient solution. Our goal to minimize system downtime over the entire lifecycle of our system, while on the other hand maximizing the duration between maintenance activities. We will be using Pareto frontier to enhance maintenance strategy for optimisizing the solutions.<\/p>\n Scanerio Space for our interventions :We will be genertating design space (grid = 5) . It will generate a grid of p0ssible event combinations for the building and heating system. We will explore these combinations of maitenance and select\u00a0 Pareto-Optimal solutions.<\/p>\n Creating design grid, to create all possible combinations of events within specidied ranges. The ranges are :<\/p>\n Table 3.<\/p>\n If we Look at the figure 1. The Pareto solution is derived to represent optimal trade-offs betweent conflicting objective which is\u00a0minimizing intervention duration (dur) and\u00a0maximizing the time between interventions (dist.inter).<\/p>\n Figure 1.<\/p>\n Discussion :\u00a0<\/strong><\/p>\n Upper Plot of Figure 1.<\/strong> : The blue line represents the Pareto frontier, representing the optimal trade-off between\u00a0\u00a0intervention duration and\u00a0\u00a0time between interventions.\u00a0Black dots represent the Pareto-optimal solutions\u00a0on the Pareto frontier. The upper plot highlights only optimal solution , which allows decision makers to directly focus on pur decided trade-offs. The upper plot is an ideal choice for decesion making when our focus is only on optimal scenarios. \n Key Point :\u00a0Pareto frontier shows ideal combinations, achieving them in real world application is maybe impossible due to certain limitations such as budget, manpower, time or something else. For practical feasiblity we may need to select the point near to the frontier that balances with our optimization goals.<\/p>\n \u00a0Figure 2.<\/p>\n \u00a0The colour plot in figure-2 expands on of the plot of figure-1 by adding categorical classifications which are represented by colours. the 193 dots called level represents ranking a built-in ranking system. Levels closer to Pareto frontier reprents better optimal solution\u00a0 and levels which are far from pareto frontier may represent suboptimal solutions.\u00a0 This classification\u00a0 a clearer understanding of which solutions are closer to the optimal trade-off (Pareto frontier) and which are not. It is a valuable tool for decision-making, offering both insights into overall trends and detailed classifications for prioritizing improvements.<\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n <\/p>\n [1].Issarasak, Sittiporn & Chotipanich, Sarich & Pitt, Michael. (2021). Influence of Building Characteristics and Building Lifespan on Condominium Operating Expenses. Nakhara : Journal of Environmental Design and Planning. 20. 114. 10.54028\/NJ202120114.\u00a0https:\/\/www.researchgate.net\/publication\/356730105_Influence_of_Building_Characteristics_and_Building_Lifespan_on_Condominium_Operating_Expenses<\/a><\/p>\n [2]. The importance of preventative maintenance in infrastructure management :\u00a0https:\/\/www.birdi.io\/blog-post\/the-importance-of-preventative-maintenance-in-infrastructure-management<\/a><\/p>\n x<\/span><\/p>\n x<\/span><\/p>\n x<\/span><\/p>\n |\u00a0Main Page<\/a>\u00a0|\u00a0Introduction<\/a>\u00a0|\u00a0Individual Systems<\/a>\u00a0|\u00a0Integration Context<\/a>\u00a0|\u00a0Integrated\u00a0Maintenance Strategies\u00a0|\u00a0Life Cycle Analysis<\/a>\u00a0|\u00a0Multi-Objective Optimization<\/a>\u00a0|<\/p>\n","protected":false},"excerpt":{"rendered":" Effective maintenance strategies are essential for solving the risk associated with the system failure and detoriation, particulary in the builing infrastructure system, which compromise numerous components requiring distinct maintenance activities. Our goal is by combiningContinue reading<\/a><\/p>\n","protected":false},"author":239,"featured_media":0,"parent":19364,"menu_order":0,"comment_status":"closed","ping_status":"open","template":"page-templates\/page_fullwidth.php","meta":{"footnotes":""},"class_list":["post-19379","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/19379","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/users\/239"}],"replies":[{"embeddable":true,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=19379"}],"version-history":[{"count":59,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/19379\/revisions"}],"predecessor-version":[{"id":22349,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/19379\/revisions\/22349"}],"up":[{"embeddable":true,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/19364"}],"wp:attachment":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=19379"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
\n<\/a><\/a><\/p>\n<\/a><\/p>\nCombined Maintenance:<\/h4>\n
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Combined Maintenance:<\/h4>\n
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Optimization of Maintenance:<\/h3>\n
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\nLower Plot of Figure 1. :\u00a0<\/strong>Unlike the upper plot, lower plots inclued boith optimal and suboptimal combinations. In the lower plot blue line represnts refrence benchmarks which will allow us to compare the other solutions against the optimal solutions. This plot is usefull for identifying inefficiencies in the system and solutions that we could imporove to approach optimal solution.<\/p>\n<\/a><\/p>\nRefrence :<\/h3>\n
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