{"id":25279,"date":"2026-02-04T08:48:40","date_gmt":"2026-02-04T08:48:40","guid":{"rendered":"http:\/\/141.23.68.248\/wp\/?page_id=25279"},"modified":"2026-02-05T17:49:55","modified_gmt":"2026-02-05T17:49:55","slug":"lca-multi-objective-analysis-3","status":"publish","type":"page","link":"http:\/\/141.23.68.248\/wp\/?page_id=25279","title":{"rendered":"LCA &amp; Multi-Objective Analysis 3"},"content":{"rendered":"\n<p>The material inventories and corresponding environmental indicators presented in the tables are compiled from established literature sources and commonly used life-cycle databases. Each table represents a specific system component and reflects its characteristic material composition, expressed per functional unit (either per cubic meter or per square meter of construction). By defining material quantities, energy demand, emissions, and costs separately for each subsystem, the analysis captures differences in material intensity and environmental burden across the integrated system. This component specific representation is essential for the life-cycle assessment, as it allows maintenance actions applied to different systems to be translated into differentiated environmental and economic impacts, enabling a consistent and transparent comparison of alternative maintenance strategies within the multi-objective optimization framework.<\/p>\n\n\n\n<p>The NSGA-II Pareto front shown in the <em>figure 2.c<\/em> represents the core outcome of the multi-objective evaluation for Strategy 3, as it captures the fundamental relationship between operational performance and economic impact at the system level. The horizontal axis quantifies the total system interruption duration, which aggregates all maintenance-related service disruptions over the full-service life, while the vertical axis represents the total life-cycle cost resulting from the associated maintenance actions and material usage. Each point corresponds to a feasible integrated maintenance configuration generated within the defined strategy constraints, whereas the highlighted Pareto-optimal solutions identify those alternatives for which no improvement in one objective can be achieved without worsening the other.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><a href=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"927\" src=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-1024x927.png\" alt=\"\" class=\"wp-image-25814\" style=\"width:589px;height:auto\" srcset=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-1024x927.png 1024w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-300x272.png 300w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-768x696.png 768w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-520x471.png 520w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2-740x670.png 740w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/4-2.png 1420w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption class=\"wp-element-caption\"><em>Figure 2.c : pareto front described by the total interruption duration and the cost<\/em><\/figcaption><\/figure><\/div>\n\n\n<div style=\"height:27px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>The distribution of points reveals that the most efficient solutions are concentrated within a relatively narrow interruption range, roughly between 90 and 105 days, while the associated costs span a noticeably wider interval, from approximately 2.7 million EUR to about 3.0 million EUR. This behavior is particularly important because it demonstrates that, under the material-logistics-driven integration logic of Strategy 3, cost is not a simple linear function of interruption duration. Instead, small changes in how maintenance actions are grouped and supplied can lead to substantial cost differences while producing similar levels of service disruption. This highlights the strong influence of material consolidation effects and intervention composition on overall system performance.<\/p>\n\n\n\n<p>The shape of the Pareto front further indicates the presence of distinct structural shifts in maintenance configurations rather than a smooth, continuous trade-off. For example, solutions around 90 days of interruption tend to be associated with higher costs close to 3.0 million EUR, reflecting more tightly clustered, material-intensive interventions. In contrast, configurations near 100 days achieve significantly lower costs of approximately 2.7 million EUR, suggesting that slightly relaxed temporal coordination enables more efficient material usage and reduced logistical overhead. Beyond approximately 120 days of interruption, costs rise rapidly and exceed 3.2 million EUR, indicating that excessive fragmentation or extension of maintenance activities leads to inefficient system behavior and diminishing economic returns.<\/p>\n\n\n\n<p>From a system perspective, this figure is critical because it shows that Strategy 3 does not aim to minimize interruption or cost in isolation but instead creates a decision space where multiple balanced solutions exist. The Pareto front provides decision-makers with a transparent framework to understand how different maintenance organizations affect the overall system, rather than forcing the selection of a single \u201cbest\u201d solution. Importantly, the presence of a well-defined Pareto front confirms that the strategy successfully introduces meaningful variability into the solution space while maintaining structural feasibility. Overall, this result demonstrates that material-logistics-based integration has a measurable and non-trivial impact on both operational disruption and life-cycle cost. The Pareto front therefore plays a central role in interpreting the effectiveness of Strategy 3, as it links the abstract maintenance concept directly to quantifiable system-level outcomes and underpins the comparative assessment carried out in the subsequent analysis.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><a href=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"549\" src=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-1024x549.png\" alt=\"\" class=\"wp-image-25816\" style=\"width:759px;height:auto\" srcset=\"http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-1024x549.png 1024w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-300x161.png 300w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-768x412.png 768w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-1536x823.png 1536w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-2048x1097.png 2048w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-520x279.png 520w, http:\/\/141.23.68.248\/wp\/wp-content\/uploads\/2026\/02\/5-2-740x397.png 740w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><figcaption class=\"wp-element-caption\"><em>Figure 3.d : overall accumulated impact<\/em><\/figcaption><\/figure><\/div>\n\n\n<p>The parallel-coordinates diagram in <em>figure 3.d<\/em> provides a compact system-level view of how alternative integrated maintenance strategies perform across a wide set of decision variables and outcome indicators simultaneously. Each vertical axis represents one parameter in the optimization problem, ranging from subsystem-specific maintenance actions on the left (such as surface repair, major repair, and replacement frequencies) to system-level performance indicators on the right, including total interruption duration, minimum spacing between interventions, energy demand, emissions, and total cost. Each line corresponds to one complete maintenance plan evaluated within Strategy 3, allowing the full \u201cfingerprint\u201d of each alternative to be inspected rather than judging performance based on a single metric. The separation between Pareto-optimal solutions (solid red lines) and non-optimal alternatives (dashed blue lines) is particularly important, as it visually highlights which combinations of maintenance decisions achieve a balanced performance across operational, environmental, and economic dimensions. In this way, the figure functions not only because of visualization but also as a diagnostic tool, revealing how optimal system behavior emerges from coordinated decisions rather than isolated subsystem optimization.<\/p>\n\n\n\n<p>Moving the figure toward the right, the system-level indicators demonstrate how this balanced maintenance choices translate into operational, environmental, and economic outcomes. The vertical positions of the Pareto-optimal lines show that favorable performance is obtained when interruption duration, spacing between interventions, and life-cycle impacts remain within controlled ranges simultaneously. The presence of multiple Pareto-optimal trajectories crossing each other indicates that there is no single dominant maintenance configuration; instead, different solutions achieve optimality by compensating across variables. For example, a configuration with slightly higher maintenance intensity in one subsystem may still remain optimal if this is offset by reduced interventions elsewhere or improved coordination of material-intensive actions. This compensation effect is visible through the crossing of optimal lines along the performance axes and confirms that system-level optimality emerges from coordinated decision-making rather than isolated optimization.<\/p>\n\n\n\n<p>The distribution of non-Pareto solutions further reinforces this interpretation. Many non-optimal configurations exhibit extreme vertical deviations on individual axes, suggesting maintenance plans that appear favorable when assessed in isolation but fail once combined system effects are considered. Some solutions show lower environmental impacts or costs but are associated with unfavorable interruption characteristics, while others reduce downtime at the expense of disproportionate material use. The exclusion of these solutions from the Pareto set highlights the importance of integrated evaluation and demonstrates that Strategy 3 successfully filters out maintenance configurations that undermine logistical efficiency or system robustness.<\/p>\n\n\n\n<p>Overall, the figure confirms that Strategy 3 produces a structured yet flexible solution space in which optimal maintenance plans are characterized by moderation, coordination, and trade-off management across subsystems. The vertical patterns along the axes illustrate how material-aware alignment of maintenance actions leads to system-level solutions that are operationally feasible, environmentally defensible, and economically competitive. This analysis provides strong evidence that logistics-based integration is an effective mechanism for achieving balanced long-term maintenance performance in complex civil systems.<\/p>\n\n\n\n<div style=\"height:100px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"has-text-align-right\"><a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24918\" data-type=\"link\" data-id=\"http:\/\/141.23.68.248\/wp\/?page_id=24918\">Integration Scenario 4 &gt;&gt;<\/a><\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p class=\"has-text-align-center\"><a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24763\" data-type=\"link\" data-id=\"http:\/\/141.23.68.248\/wp\/?page_id=24763\">Home<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24247\" data-type=\"link\" data-id=\"http:\/\/141.23.68.248\/wp\/?page_id=24247\">System Definition<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24291\" data-type=\"page\" data-id=\"24291\">Scenario 1<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24746\" data-type=\"page\" data-id=\"24746\">Scenario 2<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24914\" data-type=\"page\" data-id=\"24914\">Scenario 3<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24918\" data-type=\"page\" data-id=\"24918\">Scenario 4<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24301\" data-type=\"link\" data-id=\"http:\/\/141.23.68.248\/wp\/?page_id=24301\">Discussion<\/a> | <a href=\"http:\/\/141.23.68.248\/wp\/?page_id=24303\" data-type=\"link\" data-id=\"http:\/\/141.23.68.248\/wp\/?page_id=24303\">Appendix<\/a><\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The material inventories and corresponding environmental indicators presented in the tables are compiled from established literature sources and commonly used life-cycle databases. Each table represents a specific system component and reflects its characteristic material composition,<a class=\"read-more\" href=\"http:\/\/141.23.68.248\/wp\/?page_id=25279\">Continue reading<\/a><\/p>\n","protected":false},"author":284,"featured_media":0,"parent":24925,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-25279","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/25279","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\/284"}],"replies":[{"embeddable":true,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=25279"}],"version-history":[{"count":6,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/25279\/revisions"}],"predecessor-version":[{"id":25944,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/25279\/revisions\/25944"}],"up":[{"embeddable":true,"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=\/wp\/v2\/pages\/24925"}],"wp:attachment":[{"href":"http:\/\/141.23.68.248\/wp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=25279"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}