Chapter 29
Digital Operations and Maintenance: From Delivery Completion to Lifetime Management
Compiled by Guangdong Fortune Stone New Material Co., Ltd.
Key Points
- Delivery is not the endpoint; operations and maintenance is the starting point. If delivery is regarded as the end, problems can only be responded to passively, inevitably leading to unclear responsibilities, delayed repairs, and damaged reputation. The goal of full life cycle asset management is not “minimum cost” but “maximum value,” requiring coordinated consideration of initial cost, operating cost, and disposal cost, while balancing appearance value, functional value, and asset appreciation.
- Maintenance is divided into three types: passive repair, preventive maintenance, and predictive maintenance. The core value of digital operations and maintenance is the shift from “passive repair” to “predictive maintenance.” IoT enables real-time monitoring through the perception layer, transmission through the network layer, analysis through the platform layer, and remote management through the application layer, transforming exterior wall operations and maintenance from “manual inspection” to “real-time monitoring.” Digital twins provide a visual decision-making foundation for predictive maintenance through digital modeling and virtual-real interaction.
- Digital operations and maintenance can be summarized as “three major values, three major tools, three levels, and three paths”: the three major values are quality traceability, early warning maintenance, and data accumulation; the three major tools are the building health record system, the intelligent monitoring system, and the maintenance management platform; the three levels are passive response, proactive prevention, and predictive maintenance; the three paths are from single-point tools to system platforms, from project pilots to comprehensive promotion, and from data accumulation to data-driven.
29.1 The “Three Major Values” of Digital Operations and Maintenance
29.1.1 Quality Traceability
Core content: Construction data for every piece of flexible stone is traceable. When problems occur, causes can be quickly identified and responsibility clearly determined.
Traceability data: Material batch—which batch of materials, which supplier, which production date; construction date—which day, which team, which construction personnel; environmental data—temperature, humidity, and wind speed during construction; acceptance records—who accepted, acceptance data, acceptance conclusions.
In terms of quality traceability, the performance data corresponding to the enterprise’s independently developed series of flexible stone emulsion technologies can serve as core parameters of the quality traceability database. The interface stability data of the non-migratory flexible stone emulsion technology, the -30°C flexibility and 3500h weather resistance data of the high-flexibility flexible stone emulsion technology, and the stain resistance data (whiteness recovery rate ≥80%) of the inorganic silicone resin modified acrylic emulsion topcoat technology for flexible stone can all be incorporated into the quality traceability database, achieving full-dimensional traceability of “batch—performance—location—time.”
Table 29-1 Quality Traceability Data List
| Traceability Dimension | Data Content | Data Source | Application Scenario |
|---|---|---|---|
| Material batch | Batch number, supplier, production date | Material traceability system | Quality problem traceability |
| Construction date | Construction time, team, personnel | Process check-in system | Construction problem traceability |
| Environmental data | Temperature, humidity, wind speed | Environmental monitoring system | Environmental problem traceability |
Case: The editorial team implemented quality traceability management during technical services for a project. One year after delivery, local hollowing occurred in the flexible stone. Through the digital operations and maintenance system, it was quickly located that the environmental humidity during construction at that location exceeded the standard, and the bonding agent did not fully cure; the construction team confirmed that they were rushing the schedule that day and did not wait for humidity to drop to the standard range before construction. After quickly identifying the cause through quality traceability, repairs were completed in a timely manner. This case shows that quality traceability transforms problem localization from “flipping through ledgers and asking those involved” to “system queries and data speaking,” with clear responsibility determination and rapid maintenance response.
29.1.2 Early Warning Maintenance
Core content: Sensors monitor flexible stone status in real time, automatically issue early warnings when data is abnormal, and perform maintenance in advance to prevent problems from expanding. The core logic of early warning maintenance is “early warning is cheaper than repair, and prevention saves more than rework.”
Early warning data: Bonding strength changes—monitor bonding strength change trends through sensors; surface temperature changes—monitor surface temperature changes through temperature sensors; moisture content changes—monitor moisture content changes through humidity sensors; displacement changes—monitor wall displacement through displacement sensors.
In terms of early warning maintenance, the 3500h weather resistance data of the enterprise’s independently developed high-flexibility flexible stone emulsion technology can serve as a benchmark for exterior wall life prediction. The stain resistance data of the inorganic silicone resin modified acrylic emulsion topcoat technology for flexible stone can serve as a threshold reference for surface contamination early warning. The interface stability data of the non-migratory flexible stone emulsion technology can serve as a benchmark for bonding strength monitoring.
Table 29-2 Early Warning Maintenance Data List
| Early Warning Type | Monitoring Data | Early Warning Threshold | Treatment Measure |
|---|---|---|---|
| Hollowing risk | Bonding strength change | Decrease of 20% | Grouting treatment |
| Detachment risk | Displacement change | Exceeds 0.5 mm | Emergency treatment |
| Water seepage risk | Moisture content change | Exceeds 10% | Waterproofing treatment |
| Temperature anomaly | Surface temperature | Exceeds 80°C | Inspection and treatment |
Case: The editorial team established an early warning maintenance mechanism during technical services for a project, monitoring wall status in real time through sensors. One day, the system warned of an abnormal increase in moisture content in a certain area. Operations and maintenance personnel arrived on site to investigate and found aging sealant at one location, which was immediately replaced, avoiding water seepage that could cause flexible stone hollowing and detachment. This case shows that digital operations and maintenance is equivalent to installing a “physical examination instrument” for the building, detecting hidden dangers before problems occur, with maintenance costs far lower than post-event rework.
29.1.3 Data Accumulation
Core content: Operations and maintenance data continuously accumulates to form a building “health record.” Data supports subsequent renovation decisions and provides a basis for the design, material selection, and construction of similar projects.
Accumulated data: Maintenance records—time, content, and cost of each maintenance; problem records—time, cause, and treatment plan of each problem; environmental data—long-term temperature, humidity, and wind speed data; performance data—long-term bonding strength and moisture content data.
Table 29-3 Data Accumulation List
| Data Category | Data Content | Accumulation Frequency | Application Scenario |
|---|---|---|---|
| Maintenance records | Time, content, cost | Each maintenance | Maintenance optimization |
The value of data accumulation is “the more it is used, the more valuable it becomes”: single operations and maintenance data can only solve current problems, while continuously accumulated data can reveal aging patterns, optimize maintenance cycles, and guide subsequent renovation decisions. The building health record is not a static record book, but an asset that appreciates over time.
29.2 The “Three Major Tools” of Digital Operations and Maintenance
29.2.1 Building Health Record System
Function: Record building full life cycle data, supporting query, analysis, and export.
Data source: Design data, construction data, operations and maintenance data. Various data are archived by functional module, forming a complete digital archive of the building “from birth to the present.”
Table 29-4 Building Health Record System Architecture
| Module | Data Content | Data Source | Application Scenario |
|---|---|---|---|
| Design module | Design drawings, material selection | Design stage | Design query |
| Construction module | Construction records, acceptance data | Construction stage | Construction traceability |
| Operations and maintenance module | Maintenance records, problem records | Operations and maintenance stage | Maintenance management |
| Analysis module | Data analysis, trend prediction | Full cycle | Decision support |
29.2.2 Intelligent Monitoring System
Function: Sensors monitor wall status in real time, automatically issue early warnings when data is abnormal, and support remote viewing and mobile push notifications.
In terms of intelligent monitoring, the enterprise’s independently developed inorganic silicone resin modified acrylic emulsion topcoat technology provides stain resistance (whiteness recovery rate ≥80%) and 3500h weather resistance data, which can serve as important references for setting surface contamination early warning thresholds and life prediction benchmarks in the intelligent monitoring system. This technology improves the weather resistance of the flexible stone topcoat to 3500h, providing a more stable material foundation for long-term data accumulation in the intelligent monitoring system.
Table 29-5 Intelligent Monitoring System Architecture
| Monitoring Type | Sensor | Monitoring Data | Early Warning Threshold |
|---|---|---|---|
| Temperature monitoring | Temperature sensor | Surface temperature | Exceeds 80°C |
| Humidity monitoring | Humidity sensor | Moisture content | Exceeds 10% |
| Displacement monitoring | Displacement sensor | Displacement amount | Exceeds 0.5 mm |
| Vibration monitoring | Vibration sensor | Vibration frequency | Abnormal vibration |
29.2.3 Maintenance Management Platform
Function: Automatic dispatch and automatic tracking of maintenance tasks, electronic and traceable maintenance records, and association of maintenance data with building health records.
Table 29-6 Maintenance Management Platform Functions
| Function Module | Content | Advantage | Application Scenario |
|---|---|---|---|
| Task dispatch | Automatic dispatch, automatic tracking | Rapid response | Problem handling |
| Record management | Electronic maintenance records | Traceable | Maintenance management |
| Data analysis | Maintenance data analysis | Optimize maintenance decisions | Decision support |
| Archive association | Association with building health records | Data sharing | Full cycle management |
Case: The editorial team configured three major digital operations and maintenance tools during technical services for a project: the building health record system records building full life cycle data; the intelligent monitoring system monitors wall status in real time through sensors; the maintenance management platform achieves closed-loop management of maintenance tasks through automatic dispatch and automatic tracking. After project delivery, operations and maintenance management achieved digitalization, the property management party had real-time control of wall status, and maintenance response efficiency significantly improved. This case shows that digital operations and maintenance is not “installing surveillance” but “installing a brain”—real-time data analysis and real-time problem handling.
29.3 The “Three Levels” of Digital Operations and Maintenance
29.3.1 Passive Response
Content: After problems occur, respond and handle quickly through the system.
Tools: Maintenance management platform, building health record system.
Goal: Rapid response, rapid handling.
Table 29-7 Passive Response Level
| Element | Content | Tool | Goal |
|---|---|---|---|
| Problem reception | Receive problems | Maintenance management platform | Rapid response |
| Problem diagnosis | Diagnose causes | Building health record | Rapid diagnosis |
| Problem handling | Handle problems | Maintenance management platform | Rapid handling |
29.3.2 Proactive Prevention
Content: Regular inspections and regular maintenance, performing maintenance before problems occur.
Tools: Intelligent monitoring system, maintenance management platform.
Goal: Prevention first, reduce problems.
Table 29-8 Proactive Prevention Level
| Element | Content | Tool | Goal |
|---|---|---|---|
| Regular inspection | Regularly inspect wall status | Intelligent monitoring system | Discover problems |
| Regular maintenance | Regularly maintain walls | Maintenance management platform | Prevent problems |
| Early warning handling | Timely handling after early warning | Intelligent monitoring system | Avoid problems |
29.3.3 Predictive Maintenance
Content: Predict maintenance needs through data analysis and perform maintenance before problems occur.
Tools: Intelligent monitoring system, building health record system, maintenance management platform.
Goal: Predictive maintenance, optimal cost.
Table 29-9 Predictive Maintenance Level
| Element | Content | Tool | Goal |
|---|---|---|---|
| Data collection | Collect monitoring data | Intelligent monitoring system | Data accumulation |
Case: The editorial team advanced operations and maintenance digitalization at three levels during technical services for a project: at the passive response level, established problem reception and rapid diagnosis processes; at the proactive prevention level, implemented regular inspections and early warning handling; at the predictive maintenance level, analyzed aging trends based on continuously accumulated monitoring data and arranged maintenance plans in advance. After project delivery, operations and maintenance management achieved an upgrade from “passive” to “proactive” and then to “predictive.” This case shows that digital operations and maintenance is not “patching and repairing” but “lifetime management.”
29.4 The “Landing Path” of Digital Operations and Maintenance
29.4.1 From “Single-Point Tools” to “System Platform”
Start: First launch single-point tools, such as the maintenance management platform. Advance: Connect data to form a system platform, such as maintenance + monitoring + archives. Mature: Full-process digitalization, such as design + construction + operations and maintenance.
Table 29-10 Landing Path of Digital Operations and Maintenance
| Stage | Content | Goal | Time |
|---|---|---|---|
| Start | Single-point tools | Data electronization | 1–3 months |
| Advance | System platform | Data integration | 3–6 months |
| Mature | Full-process digitalization | Data-driven | 6–12 months |
29.4.2 From “Project Pilots” to “Comprehensive Promotion”
Pilot: Select 1–2 projects to pilot digital operations and maintenance tools. Verification: Verify the effectiveness and applicability of the tools. Promotion: Summarize pilot experience and promote comprehensively.
Table 29-11 Promotion Path of Digital Operations and Maintenance
| Stage | Content | Goal | Key Action |
|---|---|---|---|
| Pilot | 1–2 projects | Verify effectiveness | Data collection |
| Verification | Effectiveness evaluation | Confirm applicability | Experience summary |
| Promotion | Comprehensive promotion | Large-scale application | Training and promotion |
29.4.3 From “Data Accumulation” to “Data-Driven”
Accumulation: Continuously accumulate operations and maintenance data. Analysis: Analyze data and identify patterns. Drive: Use data to drive decisions, optimize maintenance, and improve quality.
Table 29-12 Three Levels of Data-Driven
| Level | Content | Goal | Key Action |
|---|---|---|---|
| Accumulation | Continuously accumulate data | Data completeness | Data entry |
| Analysis | Analyze data patterns | Discover patterns | Data analysis |
| Drive | Use data to drive decisions | Decision optimization | Data application |
Case: The editorial team recommended that the project party advance digital operations and maintenance in three steps: first, launch the maintenance management platform to achieve electronization of maintenance data; second, connect monitoring data and archive data to achieve data integration; third, connect design data and construction data to achieve full-process digitalization. Some project parties asked whether it could be done in one step. The editorial team’s advice was: digitalization is not “one-step到位” but “step by step”; only by walking each step steadily can you reach the destination. Being eager for quick success and blindly spreading out can easily lead to data quality loss of control and idle tools.
Decision Reference for Facade Retrofit Offices
I. Applicable Object Determination: This chapter applies to the digital construction of operations and maintenance management after delivery of various facade retrofit projects. Before decision-making, first determine the project scale and operations and maintenance needs: for single buildings or smaller facade retrofit projects, a lightweight solution of “maintenance management platform + manual inspection” can be adopted; for district comprehensive renovation or multi-building complexes, a system platform solution of “intelligent monitoring system + building health record system” can be adopted. Then determine the data foundation: whether the project has digital records of the construction process (process check-in, material traceability, acceptance traceability); the completeness of the data foundation determines the implementation depth and startup speed of digital operations and maintenance.
II. Key Decision Indicators: Core indicators of digital operations and maintenance include three dimensions—quality traceability dimension: material traceability completeness should reach 100%, and acceptance record completeness should reach 100%; early warning maintenance dimension: sensor monitoring data upload frequency should meet set requirements, and early warning response time for Level I should not exceed 24 hours; data accumulation dimension: maintenance records and problem records should achieve 100% electronic archiving. Operations and maintenance acceptance standards are consistent with the unified standards in Chapter 19: bonding strength ≥0.4 MPa, hollowing rate ≤5%, flatness ≤3 mm. Building health record data analysis should cover three core types of information: maintenance frequency, problem types, and aging trends.
III. Solution Comparison Recommendations: Operations and maintenance digitalization solutions should be selected according to the principle of “lightweight first, then heavy; pilot first, then promotion.” In the initial stage, priority should be given to the maintenance management platform to achieve electronization of maintenance data, and then gradually introduce the intelligent monitoring system and building health record system. System selection should meet three conditions: data traceability cannot be tampered with, meeting quality traceability requirements; simple operation interface, property personnel can use after training; open data interfaces, capable of connecting with construction-stage digital systems. Performance data involving enterprise independent R&D technologies, such as the 3500h weather resistance of high-flexibility flexible stone emulsion and the stain resistance of inorganic silicone resin modified topcoat technology (whiteness recovery rate ≥80%), can be incorporated into the building health record as benchmark parameters for life prediction and contamination early warning.
IV. Cost and Schedule Reference: The lightweight solution has relatively low cost, mainly including maintenance management platform rental or procurement fees, QR code sign production fees, and personnel training fees; the system platform solution has relatively high cost, including intelligent sensor procurement and installation, platform development or procurement fees, network transmission fees, and system operations and maintenance fees. Sensor installation can be implemented in the post-delivery operations and maintenance stage without occupying the construction schedule; system launch and personnel training take about 0.5–1 month. Operations and maintenance digitalization investment should be evaluated on a full life cycle basis, balancing reduced rework, extended service life, and improved asset value. System operations and maintenance fees and sensor replacement fees should be included in the annual operations and maintenance budget.
V. Implementation Risk Warnings: The three major risks are data distortion risk, delayed early warning handling risk, and system idleness risk. Data distortion—prohibit proxy check-in and retroactive check-in, set timestamps and location verification in the system to ensure data authenticity; delayed early warning handling—establish a closed loop of “early warning—dispatch—handling—review—closure,” clarify response time limits for early warnings at all levels, and handle Level I early warnings within 24 hours; system idleness—clarify data update responsibility and frequency, incorporate system usage rate into operations and maintenance assessment, and prevent “building but not using.” The ultimate effect of digital operations and maintenance should be based on physical testing, and acceptance standards are consistent with the unified standards in Chapter 19: bonding strength ≥0.4 MPa, hollowing rate ≤5%, flatness ≤3 mm.
Reflections on Stone, Insights on Fortune
Delivery is not the endpoint; operations and maintenance is the starting point. In the past, after project delivery, the building was “out of contact,” and problems could only be responded to passively—responsibilities unclear, repairs untimely, reputation damaged. Digital operations and maintenance, through the three major values of quality traceability, early warning maintenance, and data accumulation, and the three major tools of building health records, intelligent monitoring, and maintenance management, pushes operations and maintenance management from passive response to proactive prevention and then to predictive maintenance. Digital operations and maintenance is not “installing surveillance” but “installing a brain”—real-time data analysis and real-time problem handling. Every maintenance record, every problem traceability, and every set of monitoring data adds thickness to the building’s “health record” and accumulates a basis for the next round of facade retrofit decisions. Let the building move from “finished upon completion” to “lifetime management,” and let each repair be more precise and cheaper than the last—this is the true value of digital operations and maintenance.
References
[1] GB 50210—2018, Standard for Construction Quality Acceptance of Building Decoration[S].
[2] GB 50300—2013, Unified Standard for Constructional Quality Acceptance of Building Engineering[S].
[3] JG/T 311—2011, Flexible Facing Brick[S].
[4] GB/T 1865—2009, Paints and Varnishes—Artificial Weathering and Exposure to Artificial Radiation—Exposure to Filtered Xenon-Arc Radiation[S].
[5] T/CECS 728—2020, Technical Standard for Comprehensive Renovation of Old Urban Residential Areas[S].
[6] Related general clauses in Chapters 17, 18, 19, 26, and 28 of this book.