An HACCP-Inspired Post-Evaluation Framework for Highway Preventive Maintenance: Methodology and Case Application

Abstract

With the increasing age and traffic load of highway networks in China, preventive maintenance has become a critical strategy for extending pavement service life and improving infrastructure sustainability. However, the lack of standardized post-evaluation systems has hindered the scientific assessment of maintenance effectiveness. This study proposes a systematic post-evaluation framework for highway preventive maintenance projects based on the Hazard Analysis and Critical Control Points (HACCP)-Inspired methodology (Applying Principles of Hazard Analysis and CCP Identification). Adopting a full life-cycle perspective, the framework identifies critical control points (CCPs) across pre-, mid-, and post-implementation phases, targeting six key dimensions: ecological and environmental hazards, resource utilization hazard, engineering safety risks, engineering quality risks, socioeconomic benefit hazards, and social living environment hazards. A multi-level evaluation indicator system is constructed using hierarchical clustering and weighted through the Analytic Hierarchy Process (AHP). The framework is applied to a preventive maintenance project on the Jinghuan Expressway in Tianjin, China, demonstrating strong practical applicability. The final evaluation score of 84.1 out of 100 confirms the technical adequacy of the project while revealing areas for improvement in clean energy adoption and substructure monitoring. This framework provides a robust basis for standardizing post-evaluation practices and promoting sustainable highway maintenance management.

1. Introduction

Highways, as a fundamental component of urban infrastructure, are a key indicator of a city’s overall development capacity and modernization level. Since the initiation of China’s Reform and Opening-Up policy, the country’s highway construction has experienced rapid growth. By the end of 2023, the total operational length of highways in China had reached 5.355 million kilometers, including 177,000 km of expressways—ranking first in the world. However, with increasing service age and rising traffic volumes, many early-constructed high-grade highways and a vast number of secondary and tertiary roads have entered a peak period of maintenance and repair, resulting in an increasingly heavy burden on road maintenance tasks [1].

Construction and maintenance of highways are complementary processes; timely maintenance is crucial to extending pavement service life [2,3]. In this context, preventive maintenance is particularly important; it targets pavements that are structurally sound or exhibit only minor signs of distress, aiming to slow deterioration and prevent the development of more severe damages [4,5]. Compared with traditional reactive maintenance, preventive maintenance is a proactive strategy that extends the service life of roads in good condition without enhancing their structural capacity, improves system performance, and significantly reduces lifecycle maintenance costs [6,7]. Consequently, China’s road management philosophy has evolved from a “repair-first” approach to a balanced “repair and maintenance” model, and more recently, to a strategy that prioritizes preventive maintenance. According to national statistics, the cumulative implementation of preventive maintenance in China has now reached 1.356 million kilometers. This paradigm shift has raised the standards for both the execution and evaluation of highway maintenance practices.

Post-evaluation of preventive maintenance refers to the comprehensive assessment of engineering effectiveness, technical decision-making, economic efficiency, and environmental and social impacts. It is a critical tool for accelerating the maturity of preventive maintenance technologies [8]. In 2018, the Ministry of Transport of China issued the Administrative Measures for Highway Maintenance Projects, which formally incorporated post-evaluation as part of maintenance fund management, highlighting its increasing importance [9]. Conducting timely, accurate, and efficient post-evaluation is not only aligned with the current level of preventive maintenance practices in China but also serves as essential support for achieving national “dual carbon” goals. Moreover, it plays a vital role in ensuring the scientific and rapid development of preventive maintenance.

Unlike conventional post-evaluation approaches that center on project duration, cost, or quality endpoints, this study adapts Hazard Analysis and Critical Control Points (HACCP)-Inspired method, applying only HACCP Principles 1–2 (hazard analysis and critical control point (CCP) identification) to a retrospective, technical post-evaluation of asphalt-pavement preventive maintenance. The goal is to identify process hazards and the decision points most likely to influence outcomes. A bottom-up agglomerative hierarchical-clustering procedure groups related control items at each project stage and reveals their internal logical relationships, thereby sharpening indicator selection and structure. Rather than being treated as independent targets, indicators such as the Pavement Condition Index (PCI), Subgrade Condition Index (SCI), or cost are embedded within the risk-pathway framework as diagnostic evidence tied to specific CCPs. This shift from results-based appraisal to process-oriented, risk-informed post-evaluation is the primary conceptual contribution. By combining expert judgment with quantitative scoring and visual diagnostics (spider charts and dendrograms), the framework provides a transparent and replicable basis for auditing preventive-maintenance projects and extends the methodological toolbox for highway-maintenance management.

2. Literature Review

2.1. Current Research Status of Preventive Maintenance Technologies

Preventive maintenance practices were initiated earlier in developed countries, where extensive research has been conducted and technologies have been widely applied in real-world projects. Countries such as the United States and members of the European Union have developed highly mature preventive maintenance systems. In the early 1990s, the United States was among the first to propose the concept of preventive maintenance, marking a significant departure from traditional reactive road maintenance strategies. Commonly adopted techniques in the U.S. include chip sealing, cape sealing, fog sealing, and the ultra-thin wearing course technology [10,11,12,13,14]. In Australia, research has primarily focused on ultra-thin overlays. A widely adopted approach in Western Australian urban roads involves milling the surface layer, placing a stress-absorbing membrane interlayer, and applying a 3 cm ultra-thin overlay. This method offers effective repair outcomes with added benefits such as noise reduction and waterproofing, while maintaining relatively low maintenance costs. South Africa, characterized by low annual rainfall, has prioritized surface sealing technologies which not only extend pavement service life but also enhance skid resistance and reduce noise [15]. In France, the emphasis has been on thin and ultra-thin overlay techniques, targeting functional improvements such as skid resistance, noise reduction, and driving comfort, again with relatively low maintenance expenditures [16,17,18,19].

In contrast, China began exploring preventive maintenance later. However, significant progress has been made in recent years, both in terms of technical capabilities and implementation scale. Since the mid-to-late 1990s, increasing attention has been paid to preventive maintenance, with domestic efforts drawing on international experience while adapting to the specific conditions of Chinese road networks [20]. The release of the Technical Specifications for Highway Maintenance (JTJ 073-96 [21]) by the Ministry of Transport in 1996 explicitly mandated preventive maintenance for asphalt pavements. Since then, many provinces have actively advanced preventive maintenance initiatives. For instance, Shanghai has long been a leader in this field, introducing slurry seal and micro-surfacing technologies in the late 1990s. By 2005, its research outcomes in pavement preventive maintenance were internationally recognized [22]. In 2000, Shandong Province introduced chip sealing techniques along with corresponding asphalt distributors and pavers, promoting surface treatment methods on a large scale. Over the next five years, various techniques such as crack sealing, micro-surfacing, slurry seal, and thin overlays were extensively adopted. Similarly, Jiangsu Province has promoted slurry seal technology since 2002, with more than 300 km implemented annually across the province, achieving excellent results. In Shaanxi Province, pilot sections using thin overlays and chip seals were constructed starting in 2003. These experiences informed the subsequent province-wide promotion of preventive maintenance techniques. By 2005, micro-surfacing, emulsified asphalt slurry seals, and modified asphalt thin overlays were incorporated into expressway maintenance, supported by the issuance of the Technical Guidelines for Highway Maintenance in Shaanxi Province (DBJTJ/T-002-2005 [23]), which specified the applicable conditions, material requirements, and construction processes for these techniques [24,25]. In addition, several provinces have made notable advances in the development and application of innovative preventive maintenance technologies. Examples include low-noise micro-surfacing, ultra-thin wearing courses, and SMC warm-mix ultra-thin overlays, which have been successfully applied in engineering practice [26,27,28,29,30].

2.2. Current Research Progress on Post-Evaluation of Preventive Maintenance

The United States [31] was among the earliest countries to initiate post-evaluation practices. The first use of post-evaluation can be traced back to the New Deal programs of the 1930s. Later, during the “War on Poverty” initiative, large-scale investments in public welfare projects led to growing public and congressional concerns regarding capital utilization and economic efficiency. Consequently, post-evaluation approaches focusing on investment benefits were widely applied. The World Bank [32] formally established a dedicated post-evaluation agency in 1970 and developed a comprehensive post-evaluation procedure, which included self-evaluation, self-evaluation audit, synthesis, re-evaluation, and feedback. Both qualitative and quantitative evaluation methods were incorporated into this framework.

China began piloting post-evaluation in the 1980s [33], primarily to assess the use of construction funds, management effectiveness, and accumulated experience. Subsequent evaluation guidelines clearly defined the objectives, content, and methodologies of post-evaluation. In 1990, the Ministry of Transport [34] held a symposium on post-evaluation of highway construction projects in Beijing, initiating the first formal application of post-evaluation in the sector. Based on the evaluation of four selected expressway projects, the Ministry developed standard procedures for compiling post-evaluation reports, thereby ushering in a procedural era for the post-evaluation of highway and other infrastructure projects in China.

Wang et al. [35] provided an overview of China’s highway maintenance management, and conducted post-evaluation of decision-making in asphalt pavement maintenance, establishing a comprehensive evaluation framework. Ma et al. [36] employing a panoramic analysis approach from a three-dimensional perspective, they formulated an evaluation framework based on the “value–goal–indicator–standard” logic and proposed specific evaluation standards and methodologies. Wang et al. [37] considering the context of Beijing, analyzed the structure and connotation of highway maintenance performance and used methods such as membership function analysis, correlation analysis, and discrimination analysis to select performance indicators across quality, schedule, cost, and management dimensions, ultimately constructing a 15-indicator performance evaluation system for Beijing’s highway maintenance. Xu et al. [38], from an engineering and technical perspective, proposed a stage-based post-evaluation framework covering the pre-, mid-, and post-implementation phases, and developed corresponding technical evaluation indicators and composite indices.

Given the lack of established methods for post-evaluation of preventive maintenance, Hu et al. [8] highlighted its importance and proposed a framework based on project-level post-evaluation practices. They developed qualitative and quantitative indicators across five dimensions: engineering technology, management, economic benefits, environmental impact, and social impact. Wang et al. [39] classified evaluation indicators into two categories: pavement condition indicators (to determine appropriate intervention timing) and performance evaluation indicators (to assess effectiveness). Zhang et al. [40], adhering to principles of quantifiability, measurability, and variability, proposed pavement condition indices such as PCI (Pavement Condition Index) and RQI (Ride Quality Index), and performance evaluation indicators including △PCI, service life (N), and deferred major rehabilitation years (T). He developed an evaluation methodology for road service performance and economic benefits of preventive maintenance from a network-level perspective, offering a foundation for post-evaluation of provincial or similar preventive strategies. Tang et al. [41], through literature review and expert interviews, established a hierarchical indicator system for post-evaluation of expressway preventive maintenance, covering technical and economic aspects. Li et al. [42] conducted field investigations of pavement distress patterns and their causes on an expressway before and after preventive maintenance interventions. By comparing pre- and post-maintenance inspection data, they assessed project outcomes in terms of ride quality, rutting depth, and skid resistance. Wang et al. [43], integrating post-evaluation principles from highway construction projects with the characteristics of preventive maintenance, proposed a dedicated post-evaluation index system.

Based on the literature reviewed above, the methodological differences among representative studies in terms of indicator selection and weighting approaches were further summarized to clarify the innovation of the proposed framework. The comparative results are presented in

Table 1. Comparison of Indicator and Weight Determination Methods in Existing Post-Evaluation Frameworks.

Evaluation Type	References	Indicator Determination Method	Weight Determination Method
Existing post-evaluation systems	Ma et al. [36]	Panorama analysis method	Not addressed
	Wang et al. [37]	Expert interviews	Expert judgment
	Xu et al. [38]	Expert interviews	Expert judgment
Existing preventive maintenance systems	Hu et al. [8]	Expert interviews	Not addressed
	Wang et al. [39]	Expert interviews	Not addressed
	Zhang et al. [40]	Economic-based indicators	Not addressed
	Tang et al. [41]	Expert interviews	Decision function
	Wang et al. [43]	Expert interviews	Not addressed
This study		HACCP-Inspired	Analytic Hierarchy Process (AHP)

.

Many post-evaluation studies emphasize project duration, cost, or quality endpoints and often rely on subjective surveys or expert judgment for indicator selection and weighting. In contrast, this study adopts an HACCP-Inspired method, applying only HACCP Principles 1–2, hazard analysis and critical control point (CCP) identification, to the post-evaluation of preventive maintenance for asphalt pavements. This yields a CCP-centered, process-oriented framework that clarifies risk nodes across pre-, mid-, and post-implementation phases and embeds diagnostic indicators (e.g., PCI, SCI, and cost) within specific hazard–CCP pathways rather than treating them as standalone targets. To derive quantitative weights, not specified by Principles 1–2, the Analytic Hierarchy Process (AHP) is integrated, and bottom-up agglomerative hierarchical clustering is applied to group related control items and reveal their internal relationships.

2.3. Framework Selection and HACCP-Inspired Indicator Development

2.3.1. Comparative Analysis of Multiple Evaluation Methods

Existing frameworks for infrastructure evaluation can be broadly grouped into four categories.

Architectural systems such as HQE (High Quality Environmental), GSAS (Global Sustainability Assessment System), ASGB (Assessment Standard for Green Building), and DGNB (German Sustainable Building Council) [44,45,46,47,48,49,50,51] emphasize ecological, economic, and social dimensions with life-cycle perspectives. While mature and widely applied, their building-specific orientation limits direct use in highway preventive maintenance, though concepts such as ecological quality and process rigor are instructive.

Management frameworks include ESG (Environment–Social–Governance), BSC (Balanced Scorecard), NESS (Necessity–Economy–Society–Service), and CIPP (Context–Input–Process–Product) [52,53,54,55]. These provide comprehensive strategic indicators and process-oriented evaluation, but they are designed for organizations rather than engineering systems, and thus lack specificity for technical post-evaluation.

Risk management methods such as FMEA (Failure Mode and Effects Analysis), RBS (Risk Breakdown Structure), and ISO 31000 [56] offer structured risk identification, classification, and governance. FMEA excels in early-stage defect analysis, RBS in hierarchical categorization, and ISO 31000 in organizational integration [57,58,59]. However, they generally neglect full-process, node-specific, and dynamically adjustable evaluation requirements needed in preventive maintenance.

Food safety systems provide closer analogies. The 4T model (Traceability, Transparency, Testability, Timeliness) improves information completeness and accountability, but its application to transport projects shows that traceability alone is insufficient for managing complex engineering risks. HACCP (Hazard Analysis and Critical Control Point), in contrast, is a process-oriented and proactive system that identifies hazards, defines CCPs (Critical Control Points), and establishes monitoring and corrective actions. Compared with FMEA, RBS, and ISO 31000, HACCP offers greater systematicity and responsiveness through node-based control and adaptive feedback [60,61,62].

2.3.2. Overview of the HACCP Method

HACCP was developed in the 1960s by Pillsbury with NASA and the U.S. Army for space-food safety and was standardized by the Codex Alimentarius (1997). Many countries subsequently mandated HACCP in food industries. Beyond food systems, HACCP has inspired risk-management practices in reclaimed-water reuse, flood-risk governance, and urban drainage, among others [63,64,65,66,67].

HACCP comprises seven principles: (1) hazard analysis; (2) identification of critical control points (CCPs); (3) critical limits; (4) monitoring; (5) corrective actions; (6) verification; and (7) documentation. Scope note: because the objective of this study is a retrospective post-evaluation, only Principles 1–2 (hazard analysis and CCP identification) are applied. Real-time control elements in Principles 3–7 are not implemented.

Typical hazards across pre-, mid-, and post-implementation stages (ecological/environmental, resource utilization, engineering safety, engineering quality, socioeconomic benefit, and social living environment) are identified, and a CCP decision tree is used to screen controllable nodes. These two steps yield a hazard–CCP map that structures subsequent indicator mapping and quantitative analysis for post-evaluation.

Construction of the post-evaluation indicator system (six steps).

(1) Stage division and hazard taxonomy. The project lifecycle is partitioned into pre-, mid-, and post-implementation stages, with six hazard types defined for each stage.

(2) Task objectives and hazard analysis. Through expert consultation and case analysis, 12 task objectives (5 pre-, 3 mid-, 4 post-) are identified, and task-specific hazards are enumerated.

(3) CCP determination and control measures. Using the HACCP-Inspired decision tree, each task is evaluated to determine whether its hazards can be mitigated by management or engineering measures; all 12 tasks are confirmed as CCPs, and associated measures are proposed (prospective recommendations in a post-evaluation setting).

(4) Extraction of key control items (KCIs). Procedural measures are refined into operable, quantifiable KCIs that serve as Level-3 indicators.

(5) Expert scoring for diagnostic profiling. Each KCI is assessed across six Level-1 dimensions using a six-level (0–5) scale (0 = no impact, 5 = significant impact).

(6) Agglomerative hierarchical clustering (AHC). Based on the score matrix, Euclidean distances are computed and Ward’s linkage is applied to group KCIs; results are visualized as a dendrogram. Clusters reveal key influencing factors, which are adopted as Level 2 indicators.

The Agglomerative Hierarchical Clustering (AHC) method was employed in this study and proceeds through the following steps [68,69]: a. Cluster Object Definition: Each Key Control Item corresponding to a CCP is treated as an independent initial sample for clustering; b. Score Matrix Construction: Expert evaluations are conducted to score each key control item across six dimensions (EEH, RUH, ESR, EQR, SBH, SLEH). These scores are standardized to form an evaluation matrix. c. Distance Calculation: Based on the score matrix, the Euclidean distance between any two key control items is computed to construct the distance matrix. d. Clustering Criterion Selection: The Ward’s method is adopted as the linkage criterion. In each iteration, the two clusters that result in the smallest increase in within-cluster variance are merged. e. Dendrogram Construction: The final clustering results are visualized using a dendrogram. In the diagram, the vertical lines represent the merging distances between different key control items. Shorter lines indicate higher similarity. The horizontal axis shows the dissimilarity values, with smaller values reflecting stronger similarity and larger values indicating greater differences between the merged clusters or items.

Through these steps, a multi-level indicator framework is established, ranging from tasks, control points, and control items to key influencing factors, providing a systematic and quantifiable basis for the post-evaluation of highway maintenance projects.

2.4. Scientometric Analysis of Related Literature

A scientometric analysis was conducted using VOSviewer 1.6.20, drawing on the body of literature reviewed in this study, which represents the core research on highway preventive maintenance and HACCP. Figure 1 presents the keyword co-occurrence network, which reveals several distinct clusters representing the research landscape of highway preventive maintenance.

The largest cluster centers on Preventive Maintenance and Asphalt Pavement, with high-frequency terms such as Road Engineering, Expressway, and Pavement Maintenance. This reflects the mainstream technical focus on asphalt-based materials, maintenance timing, microsurfacing, fog seal, and related engineering measures.

A second cluster emphasizes Highway Engineering and Construction Projects, linked with Highway Construction Works, Asphalt Mixture, Construction Waste, and Financial Management. This cluster highlights managerial and economic aspects, including quality inspection, construction technology, and safety management.

A third cluster captures methodological frameworks, where Post-evaluation, Analytic Hierarchy Process, Effect Evaluation, and Indicator System are strongly connected. These keywords underline the growing interest in quantitative evaluation and decision-support tools in highway maintenance research.

Of particular relevance is the HACCP-related cluster, including HACCP, Critical Control Point, Hazard Analysis, and links to the Dairy Industry and Ministry of Health. This cluster appears relatively isolated from the mainstream highway maintenance literature, reflecting HACCP’s origin in food safety and its limited adoption in transportation infrastructure. Its peripheral position in the network underscores both the novelty and the research gap that this study seeks to address by introducing an HACCP-inspired evaluation framework.

Overall, the mapping analysis demonstrates that while preventive maintenance and pavement engineering dominate the field, systematic post-evaluation frameworks—particularly those inspired by HACCP—remain underexplored. This finding reinforces the originality and significance of our proposed HACCP-inspired post-evaluation system for highway preventive maintenance.

2.5. Limitations of Current Post-Evaluation Systems for Highway Preventive Maintenance Projects

In recent years, the concept of “preventive maintenance as the primary strategy, with corrective maintenance as a supplement” has been widely accepted and promoted in China. Consequently, preventive maintenance projects have gained increasing attention in both theory and practice. A number of scholars have made valuable contributions to the development of post-evaluation frameworks for such projects, exploring various indicator systems and evaluation methods from technical, economic, and management perspectives.

However, despite this progress, several critical limitations remain in the existing body of work, particularly regarding the systematization, standardization, and feedback mechanisms of post-evaluation practices:

(1) Fragmented and inconsistent frameworks. While some post-evaluation frameworks have been proposed, they often rely heavily on subjective expert opinions and lack a unified theoretical basis. Many studies focus on static, post hoc evaluation without fully capturing the dynamic characteristics and phased nature of preventive maintenance activities.

(2) Lack of standardized and institutionalized procedures. Currently, there is no widely accepted or standardized methodological system for post-evaluation across regions and project types. Evaluation criteria, data sources, and methodological rigor vary significantly, making cross-project comparisons difficult and limiting the broader applicability of results.

(3) Insufficient integration of risk control and feedback logic. Most existing frameworks focus primarily on performance outcomes, while overlooking the potential value of embedding risk identification, process monitoring, and correction mechanisms into the evaluation structure. This results in limited support for continuous improvement and decision optimization in future projects.

Given these gaps, there is an urgent need to construct a more integrated, process-oriented, and adaptable post-evaluation system. Our study aims to address this need by introducing an HACCP-Inspired method with embedded control logic and dynamic feedback loops, supplemented by AHP-based weighting to enhance indicator robustness and objectivity.

3. Determination of Technical Evaluation Indicators for Highway Preventive Maintenance Projects

3.1. Hazard Analysis of Preventive Maintenance Implementation

In accordance with the principles of the HACCP-Inspired evaluation framework, this section conducts a comprehensive hazard identification and assessment of highway preventive maintenance projects. From the perspective of the full life cycle, the preventive maintenance process is divided into three phases: pre-implementation, mid-implementation, and post-implementation. Each phase is analyzed to identify potential hazards and assess their severity, providing a reliable foundation for the determination of critical control points. Based on the characteristics of preventive maintenance in each phase, this study identifies the following key hazard types across the process: Ecological and Environmental Hazards, Resource Utilization Hazard, Engineering Safety Risks, Engineering Quality Risks, Socioeconomic Benefit Hazards, and Social Living Environment Hazards.

3.1.1. Hazard Classification in Maintenance Projects

(1) Ecological and Environmental Hazards (EEH)

Throughout the life cycle of highway maintenance projects, ecological and environmental hazards may include: a. Noise pollution: The use of heavy equipment such as mixers, pavers, and pneumatic drills generates intermittent and high-decibel noise that contributes to environmental noise pollution; b. Impact on flora and fauna: Maintenance activities may cause direct or indirect harm to surrounding plant and animal species, affecting their populations, diversity, and activity ranges. In severe cases, species unable to adapt to the altered environment may perish; c. Air pollution: Diesel-powered machinery emits large volumes of exhaust gases. In addition, construction activities generate dust, and asphalt heating and mixing release hazardous compounds such as phenols, and total hydrocarbons, posing respiratory and environmental risks. Other potential environmental impacts include light pollution, water contamination, soil degradation, and improper disposal of solid waste.

(2) Resource Utilization Hazards (RUH)

Key resource-related hazards across the project lifecycle include: a. Labor inefficiency: Poor on-site coordination can lead to overcrowding, downtime, or idle labor, resulting in wasted human resources; b. Material waste: Ineffective maintenance plans may hinder the recycling or reuse of construction materials, leading to excessive consumption; c. Excessive energy use: Irrational energy use during construction not only strains national energy reserves but also increases carbon emissions, threatening both ecological sustainability and long-term economic growth.

(3) Engineering Safety Risks (ESR)

Safety risks arise when engineering practices lack standardization or enforcement. These may include: fragmented or ineffective safety management systems, insufficient safety protocols throughout the construction process, poor execution of safety plans, inadequate investment in safety measures, low worker competency, and limited awareness or adoption of modern safety technologies.

(4) Engineering Quality Risks (EQR)

Quality risks may result from unqualified contractors, insufficient construction experience, rushed project schedules, shallow planning, poor decision-making, lack of advanced construction materials or equipment, and outdated or poorly executed technical processes. These issues can lead to compromised engineering standards and long-term performance deficiencies.

(5) Socioeconomic Benefit Hazards (SBH)

Socioeconomic risks include: a. Limited participation of private capital, leading to inadequate project funding; b. Unfair bidding practices, such as local protectionism or collusion, which undermine market competitiveness; c. Design flaws and frequent design changes that increase workload and project costs; d. Inefficient technical measures during construction that inflate costs and reduce project quality and schedule adherence.

(6) Social Living Environment Hazards (SLEH)

Maintenance activities may negatively affect local residents’ living conditions in several ways: a. Construction noise may disturb daily routines and working environments; b. Emissions from asphalt fumes can degrade local air quality; c. After project completion, increased traffic volume and vehicle speed can raise ambient noise levels, disrupting surrounding communities.

3.1.2. Hazard Analysis in Maintenance Projects

(1) Pre-Implementation Phase Hazard Analysis

The pre-implementation phase consists of five core tasks based on the life cycle theory: maintenance plan formulation, material properties, equipment provision, personnel configuration, and technical preparedness.

Taking maintenance plan formulation as an example, potential hazards in this phase are analyzed as follows: Inaccurate maintenance timing may result in premature intervention, leading to unnecessary expenditure, or delayed maintenance, rendering the intervention ineffective and wasting both resources and funds. Inappropriate selection of maintenance strategies may also lead to risks. For instance, applying HAP fog seal technology to road sections requiring enhanced skid resistance may worsen the situation. Although the technique provides good waterproofing, it reduces skid resistance, ultimately failing to improve pavement performance, misusing funds, and even potentially damaging the local ecological environment. Insufficient consideration of local traffic needs, such as neglecting the travel demands of nearby residents, may exacerbate traffic congestion. Inefficient organizational planning may lead to cost overruns, failing to control overall maintenance expenditures.

Therefore, the main types of hazards associated with the maintenance plan formulation stage include: Ecological and Environmental Hazards, Resource Utilization Hazard, Engineering Safety Risks, Engineering Quality Risks, Socioeconomic Benefit Hazards, Social Living Environment Hazards. For each task, associated potential hazards are identified, as summarized in

Table 2. Hazard Analysis for the Pre-Implementation Phase.

No.	Task Objective	Hazard Types	Potential Hazard Factors	Risk Identification Basis
1	Maintenance plan formulation	EEH, RUH, ESR, EQR, SBH, SLEH	Incomplete analysis of historical pavement data; poor design safety/economy; inappropriate maintenance timing; poor sectioning; unreasonable measure selection; lack of local traffic demand consideration; disorganized planning leading to cost overruns.	[22,70,71]
2	Material properties	RUH, ESR, EQR, SBH	Use of unqualified materials; lack of standard inspection; long-distance material transportation.	[72,73]
3	Equipment provision	RUH, ESR, EQR, SBH	Inadequate communication, power, lighting, and safety facilities; irregular maintenance of machinery; inefficient use; lack of pre-operation checks.	[72,74]
4	Personnel configuration	ESR, EQR, SBH	Unqualified technical staff; poor skill mastery; lack of motivation and discipline.	[72,75]
5	Technical preparedness	EEH, RUH, ESR, EQR, SBH	Incomplete technical preparation; insufficient staff training; increased risk of construction safety and quality issues.	[72,76]

.

(2) Mid-Implementation Phase Hazard Analysis

The mid-implementation phase includes three main objectives: construction process control, quality control, and safety protection.

Taking safety protection as an example, several potential hazards may arise during this phase of highway maintenance projects. These include inadequate establishment of specialized safety protocols, insufficient safety training and awareness campaigns, and a lack of safety vigilance among workers, which may result in improper equipment operation, leading to machinery overturning or material ejection. Additionally, poor traffic control measures at the construction site and unclear division of responsibilities may expose personnel to serious safety risks. Furthermore, deficiencies in emergency response planning, such as incomplete emergency protocols and insufficient first-aid knowledge, can prevent timely and effective responses to on-site incidents.

Therefore, the main types of hazards associated with the safety protection stage include: Engineering Safety Risks, Engineering Quality Risks, and Socioeconomic Benefit Hazards. For each task, associated potential hazards are identified, as summarized in

Table 3. Hazard Analysis for the Mid-Implementation Phase.

No.	Task Objective	Hazard Types	Potential Hazard Factors	Risk Identification Basis
1	Construction process control	EEH, RUH, ESR, EQR, SBH	Improper coordination of labor and equipment; poor organization; inadequate safety training; weak supervision; poor schedule and cost control; increased project costs and reduced social benefits.	[72,76,77]
2	Quality control	ESR, EQR, SBH, SLEH	Inadequate inspection of contract compliance and material quality; failure in on-site verification and acceptance; surface defects such as unevenness and poor compaction; quality failures impacting public satisfaction; budget overruns.	[72,76,78]
3	Safety protection	ESR, EQR, SBH	Incomplete safety protocols; lack of emergency plans; traffic management failures; equipment misuse; storage safety issues; fire hazards due to poor prevention measures.	[72,75,76]

.

(3) Post-Implementation Phase Hazard Analysis

The post-implementation phase comprises four key objectives: technical performance indicators, financial management, resource utilization, and environmental protection.

Taking Environmental protection as an example, several potential hazards may arise during this stage of highway maintenance projects. These include the emission of greenhouse gases such as CO₂ and NO₂ during raw material processing, asphalt mixture preparation, and construction activities, which can pollute the atmosphere, harm workers’ health, and reduce the quality of life for nearby residents. Additionally, noise generated by construction machinery can cause noise pollution, disrupting residents’ daily lives. During nighttime operations, the lighting equipment used by construction machinery may lead to light pollution, negatively affecting the growth and survival of local flora and fauna.

Therefore, the main types of hazards associated with the environmental protection stage include: Ecological and Environmental Hazards, Resource Utilization Hazard, Socioeconomic Benefit Hazards, and Social Living Environment Hazards. For each task, associated potential hazards are identified, as summarized in

Table 4. Hazard Analysis for the Post-Implementation Phase.

No.	Task Objective	Hazard Types	Potential Hazard Factors	Risk Identification Basis
1	Technical indicators	ESR, EQR, SBH, SLEH	Untimely/inaccurate performance testing; poor road condition data; lack of load-bearing capacity monitoring causing structural damage and traffic interruption.	[77,79]
2	Financial management	ESR, EQR, SBH	Poor fund allocation and disbursement; lack of cost control; excessive overspending; salary arrears; inadequate cost awareness among staff; material waste and inefficient logistics.	[22,70,71,77]
3	Resource utilization	EEH, RUH, EQR, SBH	Low adoption of energy-saving equipment; use of high-energy temporary facilities.	[22,70,71,77]
4	Environmental protection	EEH, RUH, SBH, SLEH	Emissions from machinery (e.g., asphalt pavers, chip spreaders); GHG emissions from production; noise pollution; light pollution from nighttime construction; increased traffic emissions and noise affecting local residents’ well-being.	[22,70,71,77]

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3.2. Identification of Technical Critical Control Points in Preventive Maintenance Projects

Based on the hazard analysis conducted in the previous section, it is evident that various risks, ranging from ecological and environmental impacts, resource inefficiencies, engineering safety hazards, and quality defects to socioeconomic disruptions and deterioration of the living environment, may significantly affect the overall evaluation outcomes of preventive maintenance projects. Specifically, ecological and resource-related hazards can cause irreversible damage to local ecosystems; safety and quality hazards can threaten the well-being of workers and road users; and socioeconomic risks may disrupt market order and delay project schedules. Therefore, it is imperative to implement rigorous quality control and identify critical control points (CCPs) within the technical aspects of maintenance engineering.

A critical control point refers to a specific stage, step, or procedure in the maintenance process where effective preventive, eliminative, or mitigating measures can be applied to reduce the associated hazards to an acceptable level. The identification of these points is guided by a critical control point decision tree (Figure 2).

3.2.1. Critical Control Points in the Pre-Implementation Phase

To identify CCPs during the early implementation phase of highway maintenance engineering, a CCP decision tree was applied to systematically assess key steps, procedures, and activities. The evaluation process is summarized in

Table 5. Identification of Critical Control Points in the Pre-Implementation Phase.

No.	Task Objective	Q1	Q2	Q3	Q4	Identified as CCP
1	Maintenance plan formulation	Yes	Yes	N/A	N/A	Yes
2	Material performance	Yes	Yes	N/A	N/A	Yes
3	Equipment provision	Yes	Yes	N/A	N/A	Yes
4	Personnel configuration	Yes	Yes	N/A	N/A	Yes
5	Technical preparedness	Yes	Yes	N/A	N/A	Yes

.

Based on the CCP identification process, five CCPs were determined for the pre-implementation phase: Maintenance plan formulation; Material performance; Equipment provision; Personnel configuration; and Technical preparedness. By applying effective preventive or control measures to address the potential hazards associated with these CCPs, risks related to ecological environment, resource consumption, construction safety, and project quality can be significantly reduced or eliminated.

Taking the “Maintenance plan formulation” as an example, the process of determining its corresponding critical control measures is analyzed in detail. The critical control measures for this CCP refer to the set of preventive actions or control indicators established to reduce the likelihood of various risks during this phase, including engineering safety hazards, ecological and environmental impacts, inefficient resource utilization, construction quality issues, socioeconomic losses, and adverse effects on the living environment. In designing a maintenance plan, three key technical factors must be thoroughly considered: the predominant pavement distress type and its severity, road classification, and traffic volume. The design process should strictly adhere to relevant technical standards, such as the Highway Performance Assessment Standards (JTG 5210-2018) [79], Specifications for Maintenance Design of Highway Asphalt Pavement (JTG 5421-2018) [70], and Technical Specifications for Maintenance of Asphalt Pavement (JTG 5142-2019) [71]. Additionally, economic, construction-related, and environmental considerations must be incorporated into the planning process. Specifically, maintenance timing must be determined with precision to avoid resource waste caused by premature or delayed interventions. Pavement sections should be accurately clustered based on condition and functional needs to ensure targeted maintenance. The chosen treatment strategy must be tailored to the specific type of pavement distress to ensure that the implemented measures effectively eliminate defects and substantially improve pavement quality. Lastly, the overall organizational plan must be rationally structured, with accurate repair cost estimation to avoid budget overruns.

This study analyzes the five critical control points identified in the pre-implementation phase. Based on their associated hazard types, and in alignment with the principles of sustainable development, targeted mitigation measures are proposed with a focus on efficiency, energy conservation, safety, and environmental protection. These measures are then refined and consolidated into the key control strategies for the pre-implementation phase of highway maintenance projects, as summarized in

Table 6. Critical Control Measures in the Pre-Implementation Phase.

No.	Critical Control Point	Control Measures
1	Maintenance plan formulation	Precisely determine the timing of maintenance; accurately cluster maintenance sections to enable targeted interventions; select optimal maintenance measures to ensure defect resolution and quality improvement; fully consider local travel needs; ensure rational overall project design.
2	Material performance	Conduct standardized technical tests for all materials; select suppliers with reasonable transport distances to ensure logistics efficiency.
3	Equipment provision	Perform routine checks according to technical specifications; operate machinery strictly as prescribed; conduct pre-operation adjustments and maintenance inspections.
4	Personnel configuration	Prepare construction personnel in line with technical requirements; enhance training on methods and procedures.
5	Technical preparedness	Apply proven, innovative, or newly derived technical methods; provide comprehensive training to improve operational proficiency.

.

3.2.2. Critical Control Points in the Mid-Implementation Phase

Using the CCP decision tree, each step, procedure, or task in the mid-implementation phase of highway maintenance was systematically evaluated to identify key CCPs. The determination process is presented in

Table 7. Identification of Critical Control Points in the Mid-Implementation Phase.

No.	Task Objective	Q1	Q2	Q3	Q4	Identified as CCP
1	Construction process control	Yes	Yes	N/A	N/A	Yes
2	Quality control	Yes	Yes	N/A	N/A	Yes
3	Safety protection	Yes	Yes	N/A	N/A	Yes

.

Based on the identification procedure, three CCPs were determined for the mid-implementation phase: Construction process control, Quality control, and Safety protection. Implementing effective preventive measures for these CCPs can significantly reduce or eliminate hazards related to the ecological environment, resource consumption, engineering safety, and construction quality.

Taking “Safety protection” as an example, the determination process for its critical control measures is elaborated below. These measures aim to mitigate engineering safety risks, quality defects, and socioeconomic losses during this stage. First, specialized safety protocols should be established, and training and awareness campaigns should be conducted to ensure safe practices on-site. In addition, construction site traffic management must be strengthened. Second, comprehensive emergency response plans must be formulated to ensure prompt and effective action in the event of safety incidents during construction.

This study further analyzes the three CCPs identified for the mid-implementation phase. In addition to meeting baseline requirements for construction quality and safety, targeted solutions are proposed with an emphasis on environmental protection, energy efficiency, the adoption of new materials and equipment, and innovations in management systems. These measures are refined into a set of key control strategies summarized in

Table 8. Critical Control Measures in the Mid-Implementation Phase.

No.	Critical Control Point	Control Measures
1	Construction process control	Establish special management protocols and training; define construction zones clearly; enhance workflow continuity; optimize work sequences to control project timelines; implement digital construction management to improve efficiency and equipment utilization.
2	Quality control	Strictly verify construction parameters including layer thickness, smoothness, compaction, permeability, and skid resistance; adjust evaluation indicators as needed based on maintenance techniques; ensure compliance with applicable standards for new technologies.
3	Safety protection	Develop and enforce dedicated safety protocols; promote safety awareness and training; improve site safety measures and establish robust safety management mechanisms.

.

3.2.3. Critical Control Points in the Post-Implementation Phase

Using the CCP decision tree, each task, step, or procedure involved in the post-implementation phase of highway maintenance was assessed to identify its criticality. The identification process is presented in

Table 9. Identification of Critical Control Points in the Post-Implementation Phase.

No.	Task Objective	Q1	Q2	Q3	Q4	Identified as CCP
1	Technical indicators	Yes	Yes	N/A	N/A	Yes
2	Financial management	Yes	Yes	N/A	N/A	Yes
3	Resource utilization	Yes	Yes	N/A	N/A	Yes
4	Environmental protection	Yes	Yes	N/A	N/A	Yes

.

According to the results of the CCP identification process, all task objectives in the post-implementation phase qualify as critical control points. Therefore, four CCPs are confirmed for this phase: Technical indicators, Financial management, Resource utilization, and Environmental protection. Effective preventive and control measures targeting the potential hazards associated with these CCPs can significantly mitigate risks related to environmental degradation, inefficient resource use, construction safety, and quality assurance.

Taking Environmental protection as an example, the process of determining its critical control measures is elaborated as follows. These measures aim to reduce the likelihood of risks such as resource inefficiency, environmental degradation, negative socioeconomic impacts, and disturbances to the living environment. Specifically, construction wastewater should be treated in accordance with relevant regulations; waste materials must be collected and stored centrally; and noise and light pollution from machinery should be strictly managed. During the operation phase, no-honking zones should be designated, and vehicles failing emission standards must be prohibited from operating. Additionally, nighttime vehicle lighting should be strictly monitored and controlled.

This study further analyzes the four CCPs identified in the post-implementation phase. Based on the specific types of hazards associated with each CCP, a series of targeted measures emphasizing environmental protection and management innovation were proposed. These refined strategies are presented in

Table 10. Critical Control Measures in the Post-Implementation Phase.

No.	Critical Control Point	Control Measures
1	Technical indicators	Continuously monitor road performance to ensure alignment with design expectations. Key indicators include: Subgrade Condition Index (SCI), Pavement Quality Index (PQI), Pavement Condition Index (PCI), Ride Quality Index (RQI), Rut Depth Index (RDI), Bump Index (PBI), Pavement Wear Index (PWI), Skid Resistance Index (SRI), Pavement Structural Strength Index (PSSI), Bridge Condition Index (BCI), and Traffic Facility Index (TCI).
2	Financial management	Establish standardized funding management procedures; ensure reasonable allocation, disbursement, and supervision of funds; prevent cost overruns and project violations; enforce cost control mechanisms during construction preparation.
3	Resource utilization	Promote renewable energy use and material recycling; increase the adoption of clean energy sources such as wind and solar; encourage hybrid renewable energy applications.
4	Environmental protection	Manage construction wastewater per regulations; centralize and dispose of solid waste promptly; use machinery compliant with emissions standards; implement noise and light pollution controls; enhance roadside greening efforts.

.

3.3. Determination of Evaluation Indicators

3.3.1. Key Control Items in the Pre-Implementation Phase

The five CCPs identified in the pre-implementation phase, maintenance plan formulation, material properties, equipment provision, personnel configuration, and technical preparedness, were analyzed and condensed under the principles of scientific rigor, simplicity, and optimization. The resulting key control items are presented in

Table 11. Key Control Items in the Pre-Implementation Phase.

No.	Critical Control Point	Key Control Items
1	Maintenance plan formulation	Timing Determination for Maintenance Clustering of Maintenance Sections Selection of Maintenance Scheme Consideration of Traffic Accessibility Needs Overall Organizational Design
2	Material properties	Technical Testing of Aggregates Technical Testing of Asphalt Testing of Other Material Properties
3	Equipment provision	Equipment Inspection and Maintenance Standardized Use of Equipment Completeness of Equipment Deployment
4	Personnel configuration	Personnel Allocation Technical Training for Personnel
5	Technical preparedness	Maturity of Applied Technology Technological Advancement Innovativeness of Technology

.

All control items were scored to evaluate their influence on construction-related indicators (Figure 3). Subsequently, hierarchical clustering analysis was performed in Python 3.11, and the corresponding dendrogram is presented in Figure 4.

The clustering results grouped the Key Control Items into two major categories: (1) Key Control Items related to material, equipment, personnel, and technique were grouped under “Preparation for Maintenance Construction”. (2) Key Control Items related to plan timing, sectioning, and design were grouped under “Determination of Maintenance Strategy”. Thus, the key influencing factors for the pre-implementation phase were determined as: Preparation for Maintenance Construction and Maintenance Scheme Determination.

3.3.2. Key Control Items in the Mid-Implementation Phase

The mid-implementation phase includes three CCPs, process control, quality control, and safety protection. After consolidating the relevant technical measures, the key control items were extracted as summarized in

Table 12. Key Control Items in the mid-Implementation Phase.

No.	Critical Control Point	Key Control Items
1	Construction process control	Development of Specialized Management Protocols Standardized Construction Practices Construction Continuity Construction Efficiency Construction Schedule Control
2	Quality control	Structural Layer Thickness Inspection Compaction Degree Testing Surface Evenness Testing Permeability Testing Skid Resistance Testing Other Quality Parameter Testing
3	Safety protection	Development of Specialized Safety Protocols Safety Training for Construction Personnel Traffic Management at Construction Sites Preparation of Emergency Safety Plans

.

All items were assigned scores and subjected to clustering analysis using Python, as illustrated in Figure 5 and Figure 6.

The clustering results grouped the Key Control Items for the mid-implementation phase into two major categories: (1) Key Control Items related to safety protection and process control were grouped under “Construction Process Control”; (2) Key Control Items related to construction quality supervision were grouped under “Construction Quality Control”. Considering their shared relevance to on-site implementation, both categories were integrated and generalized as “Maintenance Construction Process”. Thus, the key influencing factor for the mid-implementation phase was determined as: Maintenance Construction Process.

3.3.3. Key Control Items in the Post-Implementation Phase

The four CCPs in the post-implementation phase, technical indicators, financial management, resource utilization, and environmental protection, were each analyzed, and their key control items were defined and consolidated as shown in

Table 13. Key Control Items in the Post-Implementation Phase.

No.	Critical Control Point	Key Control Items
1	Technical indicators	Subgrade Condition Assessment Pavement Condition Assessment Bridge and Tunnel Structure Assessment Roadside Facility Condition Assessment
2	Financial management	Rationality of Fund Utilization Financial Audit
3	Resource utilization	Material Recycling and Reuse Utilization of Renewable Energy Use of Clean Energy Application of Energy-Saving Equipment
4	Environmental protection	Soil and Water Environment Protection Solid Waste Management Control of Noise and Light Pollution Landscape Greening

.

All post-implementation key control items were scored and clustered using Python, with results presented in Figure 7 and Figure 8.

The analysis revealed three distinct clusters: (1) Indicators related to natural resource efficiency and environmental sustainability were grouped under “Environmental Protection and Resource Utilization”. (2) Quantitative technical indicators (Subgrade Condition Assessment, Pavement Condition Assessment, etc.) were grouped as “Technical Indicator Evaluation”. (3) Financial performance metrics were grouped as “Maintenance Fund Management”. Accordingly, the key influencing factors in the post-implementation phase were: Technical Indicator Evaluation, Maintenance Fund Management, and Environmental Protection and Resource Utilization.

3.4. Establishment of the Evaluation System

Based on the identified key control items in the pre-implementation, mid-implementation, and post-implementation phases of preventive maintenance, a comprehensive post-evaluation system was constructed. The system was developed in accordance with the principles of comprehensiveness, operability, comparability, and sustainability, and adopts a life-cycle perspective covering the entire process of highway maintenance project execution.

The system aims to ensure construction quality and safety, maintain highway safety, comfort, and durability, and guarantee the normal operation and usage of roads. Additionally, it seeks to improve traffic efficiency, promote economic benefits, and safeguard the convenience and safety of public travel.

Accordingly, the evaluation framework includes six primary categories of indicators: Timing Determination and Scheme Selection for Maintenance, Preparation for Maintenance Construction, Maintenance Construction Process, Technical Indicator Evaluation, Maintenance Fund Management, and Environmental Protection and Resource Utilization. These six dimensions form the foundation of the Highway Preventive Maintenance Technical Post-Evaluation System, as summarized in

Table 14. Technical Post-Evaluation Indicator System for Highway Preventive Maintenance Projects.

Level 1 Indicator	Level 2 Indicator	Level 3 Indicator	Level 4 Indicator
Highway Preventive Maintenance Technology	Maintenance Scheme Determination	Timing Determination for Maintenance	—
		Selection of Maintenance Scheme	—
		Clustering of Maintenance Sections	—
	Preparation for Maintenance Construction	Material properties	Technical Testing of Aggregates
			Technical Testing of Asphalt
			Testing of Other Material Properties
		Equipment Inspection and Maintenance	—
		Personnel Allocation	—
		Technical Preparedness	—
	Maintenance Construction Process	Construction Process Control	Development of Specialized Safety Protocols
			Construction Schedule Control
		Construction Quality Control	—
	Technical Indicator Evaluation	Subgrade Condition Assessment	Subgrade Condition Index (SCI)
		Pavement Condition Assessment	Pavement Quality Index (PQI)
			Pavement Condition Index (PCI)
			Ride Quality Index (RQI)
			Rutting Depth Index (RDI)
			Bump Index (PBI)
			Pavement Wear Index (PWI)
			Skid Resistance Index (SRI)
			Pavement Structural Strength Index (PSSI)
		Bridge and Tunnel Structure Assessment	Bridge Condition Index (BCI)
		Roadside Facility Condition Assessment	Traffic Facility Condition Index (TCI)
	Maintenance Fund Management	Rationality of Fund Utilization	—
	Environmental Protection and Resource Utilization	Resource Utilization	Utilization of Renewable Energy
			Recycling of Old Pavement Materials
		Environmental Protection	—

.

4. Case Study: Engineering Application of the Evaluation System

4.1. Project Overview

The selected case for evaluation is the Tianjin section of the Jinghuan Expressway (G112), a key national trunk road running from Langfang City in Hebei Province in the west to the Tianjin–Tangshan border in the east, with a total length of 106.22 km. This segment serves as an important east–west freight corridor through the central part of Tianjin and carries substantial traffic volumes, particularly heavy and overloaded trucks. Except for a small portion in Ninghe District, the entire section is classified as a Class I Highway.

In recent years, the sharp increase in heavy-duty and oversized freight vehicles has led to significant pavement deterioration. The northbound carriageway of the segment from Kehuang Road to Jingbin Road underwent maintenance in 2021. In 2022, the southbound carriageway was selected for preventive maintenance. According to the official pavement condition assessment report, the Pavement Quality Index (PQI) for the segment is 88, the Pavement Condition Index (PCI) is 77 (classified as “Fair”), and the Pavement Structural Strength Index (PSSI) is 88 (classified as “Good”). Based on these ratings, a targeted rehabilitation strategy was implemented to restore road functionality and extend its service life. This study adopts this real-world project as a case application of the Technical Post-Evaluation System for Highway Preventive Maintenance, aiming to assess the performance and technical effectiveness of the engineering practices employed.

4.2. Indicator Scoring Framework

Based on the previously established Technical Post-Evaluation Index System and the corresponding indicator interpretation and scoring rules, this study constructs a scoring conversion framework, using a full score of 100 points as the evaluation benchmark.

To ensure practical applicability and operational efficiency in real-world project assessment, the scoring system follows a hierarchical aggregation method:

(1) The weights of the Level 3 indicators are shown in

Table 15. Weights and Scores of Technical Post-Evaluation Indicator System for Highway Preventive Maintenance Projects.

Level 1 Indicator	Level 2 Indicator	Weight	Score	Level 3 Indicator	Weight	Score	Level 4 Indicator	Weight	Score
Highway Preventive Maintenance Technology	Maintenance Scheme Determination	0.251	25	Timing Determination for Maintenance	0.072	7	—	—	—
				Selection of Maintenance Scheme	0.144	14.5	—	—	—
				Clustering of Maintenance Sections	0.036	3.5	—	—	—
	Preparation for Maintenance Construction	0.047	5	Material properties	0.024	2.5	Technical Testing of Aggregates	0.008	0.5
							Technical Testing of Asphalt	0.008	0.5
							Testing of Other Material Properties	0.008	1.5
				Equipment Inspection and Maintenance	0.006	0.5	—	—	—
				Personnel Allocation	0.003	0.5	—	—	—
				Technical Preparedness	0.013	1.5	—	—	—
	Maintenance Construction Process	0.088	9	Construction Process Control	0.058	6	Development of Specialized Safety Protocols	0.029	3
							Construction Schedule Control	0.029	3
				Construction Quality Control	0.029	3	—	—	—
	Technical Indicator Evaluation	0.433	43	Subgrade Condition Assessment	0.119	12	Subgrade Condition Index (SCI)	—	—
				Pavement Condition Assessment	0.222	22	Pavement Quality Index (PQI)	0.02775	3
							Pavement Condition Index (PCI)	0.02775	3
							Ride Quality Index (RQI)	0.02775	2.5
							Rutting Depth Index (RDI)	0.02775	3
							Bump Index (PBI)	0.02775	2.5
							Pavement Wear Index (PWI)	0.02775	2.5
							Skid Resistance Index (SRI)	0.02775	2.5
							Pavement Structural Strength Index (PSSI)	0.02775	3
				Bridge and Tunnel Structure Assessment	0.06	6	Bridge Condition Index (BCI)	—	—
				Roadside Facility Condition Assessment	0.032	3	Traffic Facility Condition Index (TCI)	—	—
	Maintenance Fund Management	0.151	15	Rationality of Fund Utilization	0.151	15	—	—	—
	Environmental Protection and Resource Utilization	0.03	3	Resource Utilization	0.02	2	Utilization of Renewable Energy	0.01	1
							Recycling of Old Pavement Materials	0.01	1
				Environmental Protection	0.01	1	—	—	—

; the detailed weight calculation procedure is provided in Appendix A.2.

(2) Where a Level 3 indicator has Level 4 sub-indicators, its weight is equally apportioned among the Level 4 indicators.

(3) The weight of a Level 2 indicator equals the sum of the weights of its Level 3 indicators.

(4) The weight of a Level 1 indicator equals the sum of the weights of its Level 2 indicators.

(5) The weights are converted into percentage-based scores, and the final comprehensive evaluation score is obtained by aggregating all Level 1 scores.

In practical engineering evaluation, some indicators may be non-applicable. For example, in purely preventive pavement maintenance, indicators related to subgrade condition may not be relevant. In such cases, the final adjusted score is calculated using the following normalization formula:

$$\mathrm{Final}\mathrm{Score}=\left({\displaystyle \frac{S_{\mathrm{actual}}}{S_{\mathrm{applicable}}}}\right)\times 100$$

(1)

To standardize this process, the post-evaluation system adopts a percentage-based structure with 0.5-point granularity for fine adjustments. The resulting score allocation for each indicator is summarized in Table 15.

It should be noted that the scores presented in Table 15 are the theoretical maximum values assigned to each indicator based on the evaluation framework and weighting methods outlined in Appendix A.2. These reflect the ideal full scores under perfect implementation conditions. In contrast,

Table 16. Evaluation Score of Maintenance Scheme Determination.

Level 2 Indicator	Level 3 Indicator	Maintenance Description	Score
Maintenance Scheme Determination (25 pts)	Timing Determination for Maintenance (7 pts)	Pavement condition data show a PQI score of 88 and a PCI score of 77. The surface damage level is Fair. If maintenance is not conducted in time, further deterioration may occur, resulting in increased costs and significant impacts on road functionality. Based on standards, PQI = 88 meets the timing requirement; PCI = 77 is slightly below the requirement. Overall assessment: Good. Score: 7 × 85% = 6.	6
	Selection of Maintenance Scheme (14.5 pts)	According to the Specifications for Maintenance Design of Highway Asphalt Pavement (JTG 5421-2018), functional maintenance is recommended for this project. In practice, milling and resurfacing was adopted for the surface layer, while patch repairs (either surface or base layer) were implemented at specific damaged locations. The overall strategy complies with the standard, though localized patching decisions were insufficiently justified. Overall assessment: Excellent. Score: 14.5 × 90% = 13.	13
	Clustering of Maintenance Sections (3.5 pts)	According to the Specifications for Maintenance Design of Highway Asphalt Pavement (JTG 5421-2018), it suggests dividing road sections by kilometers, with finer segmentation for special sections. In this project, sections were generally divided by kilometers, meeting the requirement, but some special segments were not subdivided in detail. Overall assessment: Good. Score: 3.5 × 85% = 3.	3

,

Table 17. Evaluation Score of Preparation for Maintenance Construction.

Level 2 Indicator	Level 3 Indicator	Maintenance Description	Score
Preparation for Maintenance Construction (5 pts)	Material properties (2.5 pts)	The technical specifications of raw materials used in the pavement structure must comply with the Technical Specifications for Construction of Highway Asphalt Pavements (JTG F40-2004 [72]), and all materials delivered to the site must undergo quality testing. Approval based solely on supplier reports or inspection certificates is not permitted. This project met all requirements. Full score awarded.	2.5
	Equipment Inspection and Maintenance (0.5 pts)	Adequate provision of water, electricity, construction equipment, materials, and essential living supplies must be ensured. This project met all relevant requirements. Full score awarded.	0.5
	Personnel Allocation (0.5 pts)	This content was not included in the project documentation. No score assigned.	—
	Technical Preparedness (1.5 pts)	The project adopted mature and conventional technologies. According to the evaluation standard, this item is rated as “Fair.” Score: 1.5 × 65% = 1.	1

,

Table 18. Evaluation Score of Maintenance Construction Process.

Level 2 Indicator	Level 3 Indicator	Maintenance Description	Score
Maintenance Construction Process (9 pts)	Construction Process Control (6 pts)	For construction safety, prior to commencement of the Jinghuan Expressway maintenance project, the supervising engineer, technical personnel, and project leader conducted technical briefings, quality briefings, and safety education for all workers. Personnel responsibilities were clearly defined. The entire construction process strictly followed relevant provisions in the Technical Specifications for Construction of Highway Safety Facilities (JTG F71-2006 [80]). The project was completed within the scheduled timeline. Full score awarded.	6
	Construction Quality Control (3 pts)	The construction quality of this project was not adequately controlled, lacking temperature monitoring, asphalt content tests, and total gradation inspections of aggregates. According to the evaluation standard, this item is rated as “Fair.” Score: 3 × 65% = 2.	2

,

Table 19. Evaluation Score of Technical Indicator Evaluation.

Level 2 Indicator	Level 3 Indicator	Level 4 Indicator	Score Description	Score
Technical Indicator Evaluation (43 pts)	Subgrade Condition Assessment (12 pts)	—	—	—
	Pavement Condition Assessment (22 pts)	PQI (3 pts)	Based on pavement condition survey, rated as “Fair”; score = 3 × 65% = 2.	2
		PCI (3 pts)	Based on pavement condition survey, rated as “Fair”; score = 3 × 65% = 2.	2
		RQI (2.5 pts)	Based on pavement condition survey, rated as “Fair”; score = 3 × 65% = 2.	1
		RDI (3 pts)	Based on pavement condition survey, rated as “Fair”; score = 3 × 65% = 2.	3
		PBI (2.5 pts)	Based on pavement condition survey, this item received full score.	2.5
		PWI (2.5 pts)	Based on pavement condition survey, this item received full score.	2.5
		SRI (2.5 pts)	Based on pavement condition survey, this item received full score.	2
		PSSI (3 pts)	—	—
	Bridge and Tunnel Structure Assessment (6 pts)	—	—	—
	Roadside Facility Condition Assessment (3 pts)	—	—	—

,

Table 20. Maintenance Fund Management.

Level 2 Indicator	Level 3 Indicator	Maintenance Description	Score
Maintenance Fund Management (15 pts)	Rationality of Fund Utilization (15 pts)	The project complied with official fund allocation procedures. Detailed audit reports were provided. The project met all regulatory requirements. Therefore, this item received a full score.	15

and

Table 21. Evaluation Score of Environmental Protection and Resource Utilization.

Level 2 Indicator	Level 3 Indicator	Level 4 Indicator	Maintenance Description	Score
Environmental Protection and Resource Utilization (3 pts)	Resource Utilization (2 pts)	Utilization of Renewable Energy (1 pt)	No clean energy was used in this project. Therefore, this item received a score of 0.	0
		Recycling of Old Pavement Materials (1 pt)	All milled old pavement materials were fully recovered, achieving a 100% recycling rate. This item received a full score.	1
	Environmental Protection (1 pt)	—	Measures were implemented for noise control, air quality protection, water environment protection, solid waste management, and ecological conservation. The project complied with relevant regulations and thus received a full score.	1

show the actual assessment results from the Jinghuan Expressway project. These were determined using real project data, inspection results, and implementation records, and were calculated according to the scoring criteria provided in Appendix A.1.

4.3. Case Evaluation and Discussion

Following the indicator system and scoring methodology outlined in Section 5.2, this section applies the technical post-evaluation framework to assess the performance of the preventive maintenance project on the Jinghuan Expressway (Tianjin section). Each Level 3 and Level 4 indicator was evaluated according to the established scoring standards, and detailed justifications were provided based on actual engineering records, inspection results, and design documentation. The evaluation results are summarized in Table 16, Table 17, Table 18, Table 19, Table 20 and Table 21.

In summary, Total Applicable Score is 78.5 points, Actual Score Achieved is 66.0 points, and the final evaluation score for this maintenance project is 84.1 out of 100, indicating a favorable technical outcome with effective project planning, material control, and performance improvement. However, the absence of innovation in clean energy adoption and incomplete subgrade/bridge-related assessments slightly limited the project’s overall technical coverage.

This case study demonstrates that the proposed evaluation system is applicable and practical in real-world preventive maintenance projects. The system allows for flexible exclusion of non-relevant indicators while maintaining comparability through score normalization. The detailed evaluation reveals several key insights: (1) Maintenance planning and scheme selection had the greatest impact on project effectiveness, reflecting the importance of timing and diagnostic accuracy; (2) Technical preparedness and material control remain critical, but variability in scoring suggests that many projects may overlook formal verification procedures; (3) The relatively low score in environmental and resource dimensions reveals a common gap in current engineering practice, where recycling is implemented, but renewable energy and emission reduction strategies are still underutilized. These findings reinforce the need to strengthen sustainability-oriented practices and promote standardized evaluation methods across similar national-level projects.

5. Discussion

5.1. Methodological Adaptability and Current Limitations

The post-evaluation framework for highway maintenance projects developed in this study, based on the HACCP-Inspired approach, represents a novel attempt both domestically and internationally. Given its exploratory and innovative nature, it is necessary to discuss the rationality of the methodological integration and clarify its applicable boundaries.

First, regarding the number of CCPs defined, this study identifies 12 CCPs corresponding to 12 task objectives, segmented across the three stages of the project lifecycle (pre-, mid-, and post-implementation). However, this number is neither fixed nor universally optimal. Variations in natural conditions, technical standards, regulatory systems, and data availability across different regions necessitate adaptive adjustment of CCP selection in practical applications. For instance, in ecologically sensitive areas, environmental monitoring CCPs should be emphasized [81], whereas in urban trunk roads, greater attention should be paid to noise control, construction safety, and financial efficiency [82]. In response, the need for CCP frameworks to remain adaptable and expandable, rather than rigidly applied, is highlighted.

Second, concerning the rationality of integrating the HACCP-Inspired and AHP methods, this study argues that the two are functionally complementary. HACCP-Inspired focuses on identifying potential risk nodes throughout the process and proposes systematic intervention strategies. However, it lacks a mechanism for prioritizing or weighting indicators. To enhance the quantifiability and operational feasibility of the evaluation results, the AHP is introduced to perform structured indicator weighting through hierarchical analysis. This integration effectively combines expert judgment with structured decision-making tools. Therefore, the proposed framework adopts an “HACCP-Inspired, AHP-assisted” structure that balances subjective and objective inputs, offering strong internal consistency in logic and methodology.

Nonetheless, the integrated methodology has some limitations. For instance, AHP may suffer from judgment bias when the expert sample size is small or when significant opinion divergence exists [83]. Meanwhile, HACCP-Inspired, though widely validated in the food sector, requires further empirical validation when applied across domains to engineering evaluation contexts [84]. Future research may explore incorporating additional weighting techniques such as fuzzy comprehensive evaluation or the entropy weight method to enhance the robustness and flexibility of the evaluation framework.

In summary, this study provides an exploratory attempt to apply an HACCP-Inspired method to the post-evaluation of highway preventive maintenance. While we recognize the importance of further supporting the stated limitations with broader references and comparing outcomes with alternative approaches, the present work is positioned as a methodological proposal and validation rather than a systematic review. The current discussion already highlights adaptability, methodological limitations (e.g., expert dependence in AHP and cross-domain applicability of HACCP), and future directions (e.g., fuzzy evaluation [85], entropy weighting [86], Bayesian networks [87]).

5.2. Future Research Directions

To further enhance the scientific rigor, intelligence level, and applicability of the evaluation system developed in this study, future research can explore the following four key directions:

(1) Empirical validation across multiple regions and project types, and expansion of the task objective framework. The current empirical study is based on a highway preventive maintenance project in Tianjin, demonstrating the feasibility of the proposed evaluation system. Future work should involve multi-center comparative studies across projects in diverse regions, selected for their representativeness in terms of climate conditions, road classification, and maintenance complexity. This would allow for testing of the system’s generalizability and scalability under different natural and socioeconomic contexts.

It is also worth noting that the present indicator system adopts a technology-oriented structure, focusing primarily on technical control nodes during the construction process. However, elements related to cost estimation, budget management, and contract preparation are not yet sufficiently covered [88]. Moreover, the system does not systematically consider task requirements under complex scenarios such as extreme weather or emergency events. Future studies could, therefore, refine the framework by identifying the common characteristics of task objectives across the pre-, mid-, and post-implementation stages based on multi-project evidence. A standardized task checklist that integrates both technical and managerial dimensions may then be established, leading to the development of a transplantable and modular indicator system with improved systematicity and applicability.

(2) Integration of dynamic feedback and intelligent control mechanisms. Although this study proposes a process-oriented static evaluation framework, it has not yet incorporated real-time feedback mechanisms. Future research could explore the integration of digital twin technologies by leveraging sensor data and construction monitoring information to build dynamic evaluation models [89,90]. This would enable real-time perception and automated control of key control point states, thereby enhancing the system’s responsiveness and level of intelligence.

(3) Expansion and refinement of green performance indicators. Under the context of China’s “dual carbon” strategy, there is an urgent need to incorporate more quantifiable metrics to evaluate the green performance of maintenance projects [91,92]. The current system adopts a relatively coarse approach to resource utilization and ecological protection [93]. In future iterations, more detailed indicators could be introduced, such as carbon footprint per unit maintenance length, proportion of green energy usage, and energy efficiency levels of construction equipment. This would strengthen the evaluation system’s policy relevance and its guidance for green transition in infrastructure maintenance.

(4) Enhancement of hazard identification methods and uncertainty management [94]. While this study has systematically identified six major hazard categories and their associated factors through literature review and case analysis, certain latent or emergent risks may still be overlooked due to limited case samples and data accessibility. For example, cascading effects triggered by extreme weather events or impacts of geological hazards on infrastructure stability are difficult to capture through conventional methods [95,96]. Future research may consider incorporating uncertainty modeling techniques such as fuzzy logic and Bayesian networks to expand risk identification dimensions and assess system vulnerabilities under compound hazard scenarios.

6. Conclusions

This study develops a comprehensive, lifecycle-based post-evaluation framework for highway preventive maintenance projects, with a specific focus on asphalt pavements. Grounded in the HACCP-Inspired methodology, the framework systematically identifies and analyzes potential hazards across the pre-, mid-, and post-implementation phases of maintenance. Through hierarchical clustering and indicator scoring, twelve critical control points were distilled and categorized into six key evaluation dimensions: Maintenance Scheme Determination, Preparation for Maintenance Construction, Maintenance Construction Process, Technical Indicator Evaluation, Maintenance Fund Management, and Environmental Protection and Resource Utilization.

Based on these dimensions, a multi-level post-evaluation system was constructed and empirically validated through a case study of the Jinghuan Expressway project in Tianjin. The evaluation results demonstrated that the proposed system is practical, scalable, and adaptable to real-world preventive maintenance scenarios. The project scored 84.1 out of 100, reflecting a technically effective outcome with well-executed maintenance planning, material control, and performance improvements. However, limitations such as insufficient integration of renewable energy practices and partial omission of substructure assessments indicate areas for further enhancement.

The findings underscore the critical role of timely scheme determination, rigorous construction control, and sustainability considerations in achieving high-quality maintenance outcomes. The evaluation system not only provides a scientific basis for assessing preventive maintenance performance but also supports more standardized, transparent, and sustainable management practices across China’s highway infrastructure sector. Future research should further integrate dynamic behavioral data, expand applicability across diverse road types, and explore coupling with digital twin technologies for real-time evaluation and feedback.