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The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

This paper aims to optimize the maintenance scheduling of emergency rescue wagons in railway companies using a genetic algorithm (GA). It offers an integrated model for simultaneously solving maintenance planning, preventive maintenance, prognostic information and resource planning from which optimal levels of the system performance in terms of cost and repair time could be determined.

This study initially evaluates the previous types of research in presenting the optimal model of the rescue train wagon for maintenance and repair planning and lists the identified criteria based on experts' opinions using fuzzy analytic hierarchy process (FAHP) and stepwise weight assessment ratio analysis (SWARA) techniques. Then, the final weight of the desired criteria is calculated. Later, the final decision matrix is evaluated by the experts. The final normal decision matrix is formed to select the optimal maintenance and repair planning plan based on the GA. Finally, two strategies including joint optimization strategy of preventive maintenance planning are compared with the independent preventive maintenance planning strategy.

According to the primary results, three primary parameters, including technology, human damage caused by negligence and the average failure rate, should be considered for launching the GA model. Based on the results of the second part; by comparing the preventive maintenance planning strategy independently, the joint optimization strategy reduces the total cost of production up to 8.25%. Comparison results show that the total cost of joint optimization production is less than independent preventive maintenance and repair planning. Moreover, the value of total process time in joint optimization strategy was reduced by 1.2% compared to independent preventive maintenance (PM) planning (from 137.90 to 136.20 h).

The novelty of this paper lies on the application of the GAs to develop an optimized PM scheduling to localize the maintenance planning for maximizing productivity, avoid train accidents, reduce costs and increase efficiency and capacity.

Heating, ventilating, air-conditioning and cooling (HVAC) systems are crucial in daily health-care facility services. Design-related defects can lead to maintenance issues, causing service disruptions and cost overruns. These defects can be avoided if a link between the early design stages and maintenance feedback is established. This study aims to use experts’ experience in HVAC maintenance in health-care facilities to list and evaluate the risk of each maintenance issue caused by a design defect, supported by the literature.

Following semistructured interviews with experts, 41 maintenance issues were identified as the most encountered issues. Subsequently, a survey was conducted in which 44 participants evaluated the probability and impact of each design-caused issue.

Chillers were identified as the HVAC components most prone to design defects and cost impact. However, air distribution ducts and air handling units are the most critical HVAC components for maintaining healthy conditions inside health-care facilities.

The unavailability of comprehensive data on the cost impacts of all design-related defects from multiple health-care facilities limits the ability of HVAC designers to furnish case studies and quantitative approaches.

This study helps HVAC designers acquire prior knowledge of decisions that may have led to unnecessary and avoidable maintenance. These design-related maintenance issues may cause unfavorable health and cost consequences.

The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights.

The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered.

As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets.

The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.

This paper aims to develop a dynamic civil facility degradation prediction model to forecast the reliability performance tendency and remaining useful life under imperfect maintenance based on the inspection records and the maintenance actions.

A real-time hidden Markov chain (HMM) model is proposed in this paper to predict the reliability performance tendency and remaining useful life under imperfect maintenance based on rare failure events. The model assumes a Poisson arrival pattern for facility failure events occurrence. HMM is further adopted to establish the transmission probabilities among stages. Finally, the simulation inference is conducted using Particle filter (PF) to estimate the most probable model parameters. Water seals at the spillway hydraulic gate in a Taiwan's reservoir are used to examine the appropriateness of the approach.

The results of defect probabilities tendency from the real-time HMM model are highly consistent with the real defect trend pattern of civil facilities. The proposed facility degradation prediction model can provide the maintenance division with early warning of potential failure to establish a proper proactive maintenance plan, even under the condition of rare defects.

This model is a new method of civil facility degradation prediction under imperfect maintenance, even with rare failure events. It overcomes several limitations of classical failure pattern prediction approaches and can reliably simulate the occurrence of rare defects under imperfect maintenance and the effect of inspection reliability caused by human error. Based on the degradation trend pattern prediction, effective maintenance management plans can be practically implemented to minimize the frequency of the occurrence and the consequence of civil facility failures.

The United Nations has demonstrated a commitment to preserving the ecosystem through its 2030 sustainable development goals agenda. One crucial objective of these goals is to promote a healthy ecosystem and discourage practices that harm it. Building materials production significantly contributes to the emissions of greenhouse gases. This poses a threat to the ecosystem and prompts a growing demand for sustainable building materials (SBMs). The purpose of this study is to investigate SBMs to determine their utilization in construction operations and the potential impact their application could have on construction productivity.

A systematic review of the existing literature in the field of SBMs was conducted for the study. The search strings used were “sustainable” AND (“building” OR “construction”) AND “materials” AND “productivity”. A total of 146 articles were obtained from the Scopus database and reviewed.

Bio-based, cementitious and phase change materials were the main categories of SBMs. Materials in these categories have the potential to substantially contribute to sustainability in the construction sector. However, challenges such as availability, cost, expertise, awareness, social acceptance and resistance to innovation must be addressed to promote the increased utilization of SBMs and enhance construction productivity.

Many studies have explored SBMs, but there is a dearth of studies that address productivity in the context of SBMs, which leaves a gap in understanding. This study addresses this gap by drawing on existing studies to determine the potential implications that using SBMs could have on construction productivity.

General aviation aircraft has a wide range of applications, and effective cost management is one of the hot spots in the research of general aviation manufacturers. The purpose of this paper is to build a flexible engineering method to predict maintenance cost of general aviation aircraft.

To establish a reasonable general aviation aircraft maintenance cost prediction model, it is necessary to analyze the influencing factors and extract the main components of maintenance cost. The maintenance cost is divided by engineering method, and the estimation model of each component cost is established. Then, the general aviation aircraft maintenance cost model is obtained. The results show that the relative error of this method is between 13% and 20%, which has a good estimation accuracy and can be effectively used to estimate the maintenance cost of general aviation aircraft.

The maintenance cost plays an important role in the life cycle cost of general aviation aircraft. Accurate cost prediction method is of great significance to the optimal design of general aviation aircraft. However, there are few prediction models suitable for maintenance cost, the proposed approach is meaningful and quite desirable.

To some extent, this method overcomes the shortage of the work on maintenance cost prediction for general aviation aircraft. The model established in this paper has certain generality, which can provide some reference for general aviation aircraft design and operation enterprises.

To achieve efficient operation and maintenance (O&M) management, this study seeks to identify critical success factors (CSFs) affecting service delivery factors of O&M services at stratified residential buildings. The purpose of this study is to yield measurable data for developing an effective O&M framework to enhancing its performance. In future research, this study will further investigate the relationship between the CSF and service performance factors.

This study adopts a combination of qualitative and quantitative techniques that yields conclusive study findings while improving the research’s validity and dependability. Two series of instruments were conducted in an effort to refine the efficient O&M framework variables. Instruments used in addressing the research gap were a questionnaire survey and focus group discussion (FGD). Analysis of data was completed via the Statistical Package for the Social Sciences (SPSS) programme for quantitative data and thematic analysis for qualitative data.

This study concludes that the CSFs directly affect the performance of O&M. Questionnaire survey and FGD findings have refined the CSF into three main categories, namely, building characteristics, O&M management and community participation. FGD experts further suggested that service performance factors can be measured against SERVQUAL service qualities such as reliability, tangible, responsiveness, assurance and empathy.

Future research may consider the inclusion of financial elements in the O&M service delivery.

This study presents a fresh insight into the CSFs that construct an efficient O&M framework through rigorous steps of data collection and analysis. This study proposes impactful guidance for policymakers, practitioners and residents on the significance of all parties’ involvement to support the management of residential buildings, where the current practice of O&M constantly faces complex issues. This study derives novice strategies that should correspond to the growing issues and challenges in managing residential buildings. The deeper insight into the role of O&M represents a direction for the future development of facilities management progress and stratified residential building sectors.

The airlines cancel their flights frequently because of factors that they do not have any control over. Spare aircraft can potentially address some of the issues caused by cancelled flights. This paper aims to offer an exploratory study into the financial and operational viabilities of spare aircraft for airlines.

Mathematical models are proposed to evaluate the financial and operational metrics under different scenarios. The models are applied to Delta, Spirit and Southwest Airlines with different business models. All data are extracted from US Bureau of Transport Statistics, Cirium Diio Mi and CAPA databases. The IBM Cplex solver was used to execute the binary linear program models.

The research revealed that factors such as airline network size, hub and spoke structure and average weekly flight cancellations are crucial in establishing the need for spare aircraft. For the number of weekly cancellations, there exist break-even values that reasonably justify spare aircraft.

Models can be customized and applied to other modes of transportations.

This study is the first to consider the use of spare aircraft in airlines from both financial and operational perspectives within the scope of the mathematical model. The analyses identify financial break-even points for a number of spare aircraft and their home base locations for three airlines. Operational utilization of spare aircraft is studied and contrasted with financial metrics.

The provision of an accessible and inclusive built environment is both a common regulatory requirement for architects and facilities managers, and a critical issue of equitable access for people with disability. Post Occupancy Evaluation (POE) is key to ensuring appropriate building accessibility is provided and maintained. Improved Building Information Modelling (BIM) integration with Facilities Management (FM) will enable more effective POE over time. This study aims to define and demonstrate the practicability and utility of a particular configuration of emerging BIM and related digital technologies, applied in the field.

A field study approach is applied to investigate the practicability and utility of the technology configuration and POE procedures. A proposed technology configuration is applied to evaluate 21 accessible bathrooms across three university buildings in Sydney, Australia. First, a checklist of technical functionality for a POE of accessible bathrooms particular to the field study FM context is established. The checklist is based on a review of recent literature, relevant standards, best practice guidelines, expert opinions, and the organisational requirements. Then, a technical and procedural approach to POE and BIM integration with FM is defined and applied in the field. Finally, a quantitative analysis of the results is presented and discussed relative to both the particular and general FM contexts.

The use of low-cost BIM and related technologies can usefully be applied in the field to promote a more progressive integration of BIM with FM and provide enhanced baseline models for ongoing POE. A rudimentary risk assessment of key accessible bathroom features (in the context of this field study) identified that the Toilet: toilet rolls location is unsatisfactory across all bathrooms surveyed and represents an immediate and high-risk failing. Other high-risk issues highlighted in this study included: Approach: access; Entrance: door fittings and security; and Layout: hazards.

This study offers a blue-print for building practitioners to adopt and progressively integrate low-cost BIM and related technologies with extant FM systems. The study also promotes an improved approach to effective POE practice in general, and to the assessment of accessible bathrooms in particular.

Recent reviews highlight key barriers to BIM integration with FM and significant limitations to current POE practice. Proposals for BIM integration with FM tend to focus on the comprehensive use of BIM. This study demonstrates the practicability and utility of a more progressive approach to BIM adoption and integration with FM in general. The study is also novel in that it shows how low-cost BIM and related technologies can be used as a baseline reference for ongoing POE. Building practitioners can adopt and adapt the technology configuration and approach to support a range of POE applications. This field study has identified immediate and high-risk potential failings of the accessible bathrooms provided on one university campus in Sydney, Australia.