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Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.

The purpose of this paper is to target on individual perceptions of BIM practice in terms of BIM benefits, critical success factors (CSFs) and challenges in Chongqing which represented the less BIM-developed metropolitan cities in China.

Adopting a questionnaire-survey approach followed by statistical analysis, the study further divided the survey population from Chongqing into subgroups according to their employer types and organization sizes. A further subgroup analysis adopting statistical approach was conducted to investigate the effects of employer type and organization size on individual perceptions.

Subgroup analysis revealed that governmental employees held more conservative and neutral perceptions toward several items in BIM benefit, CSFs and challenges. It was inferred that smaller organizations with fewer than 100 full-time employees perceived more benefits of BIM in recruiting and retaining employees, and considered more critical of involving companies with BIM knowledge in their projects.

This study contributed to the body of knowledge in managerial BIM in terms that: it extended the research of individual perceptions toward BIM implementation by focusing on less BIM-mature regions; it contributed to previous studies of influencing factors to BIM practice-based perceptions by introducing factors related to organization type and sizes; and it would lead to future research in establishing BIM climate and culture which address perceptions and behaviors in BIM adoption at both individual and organizational levels.

Personal lifestyle, work environments and work-related factors can significantly affect occupant productivity. Although many studies examine the affecting factors of occupant productivity in offices, explorations for the home-based work environment, which is designed mainly for living purposes, are still scarce. Moreover, current pandemic has made work from home a new normal for workers around the world. Therefore, it is important to identify key causal factors of occupant productivity when working from home.

This study employed descriptive analysis and regression analysis method to explore the relationship among personal lifestyle, indoor environmental quality and work-related factors toward occupant productivity. A questionnaire including a comprehensive list of key measures was designed and 189 valid responses were collected from more than 13,000 participants.

Results show that a healthy lifestyle, the perceived satisfaction of visual and acoustic environment, communication, interest in work, workload, flexible schedule and privacy positively affect occupant productivity when working from home, while coffee consumption, outside views and windows have negative effect.

Opportunities to enhance occupants' home-based work productivity include developing a healthy lifestyle by taking advantage of flexible schedule, equipping a working room at home with advanced and intelligent environment control systems, and improving communication, workload and schedule by changing the policy of companies.

There is a growing requirement for a rating system of building information modelling maturity (BIMM) to compare the effectiveness of modelling processes in construction projects. The literature related to BIMM contains theoretical proposals and description of their maturity models. However, the research efforts are limited and lacking substantial theoretical and empirical justifications. This paper is a unique attempt to integrate previous models by performing empirical investigations of key factors for measuring BIMM in construction projects. The paper aims to discuss these issues.

A national survey was designed to extract the perception of 124 BIM-related practitioners and academicians about the conceptual model. Then, exploratory and confirmatory factor analyses were employed to identify and test the key factors underlying the 27 areas.

A principal component factor analysis of the collected data had suggested a five-factor model, which explained 69.839 per cent of the variance. The construct validity of the model was further tested by confirmatory factor analysis. The results indicated that all factors were important in measuring BIMM; however, compared with the factors of technology and people, more emphasis was put on the factors of process and information.

The key value of the paper is to increase the understanding of multi-dimension nature of BIMM through empirical evidence and to provide practitioners and researchers with the insight regarding particular emphasis on the factors related to modelling process and information.

The purpose of this paper is to understand the natural wind field characteristics of the tunnel entrance section and analyzing the aerodynamic performance of high-speed railway trains (HSRTs) under natural winds.

Three typical tunnel entrance section sites, namely, tunnel–bridge in a dry canyon (TBDC), tunnel–bridge in a river canyon (TBRC) and tunnel–flat ground (TF), are selected to conduct a continuous wind field measurement. Based on the measured wind characteristics, the natural winds of the TBDC and TF sites are reconstituted and imported into the two corresponding full-scale computational fluid dynamics models. The aerodynamic loads of the HSRT running on TBDC and TF with reconstituted winds are simply analyzed.

The von Kármán spectrum can be used to describe the wind field at the tunnel entrance section. In the reconstituted natural wind condition, a time-varying feature of wind speed distribution and leeward side vortex around the HSRT caused by the wind speed fluctuation is found. The fluctuating amplitude of aerodynamic loads at the TBDC infrastructure is up to 97.9% larger than that at the TF infrastructure.

The natural wind characteristics at tunnel entrance sections on the high-speed railway are first measured and analyzed. A numerical reconstitution scheme considering the temporal and spatial variation of natural wind speed is proposed and verified based on field measurement results. The aerodynamic performance of an HSRT under reconstituted natural winds is first investigated.

The purpose of this paper is to explore the key factors that affect consumer redemption intention toward mobile coupons recommended in social network sites (SNS).

A research model that integrates recommendation trust, positive utilities, and negative utilities of coupon redemption is developed. With the important role of trust in social recommendation taken into consideration, the key drivers of recommendation trust were analyzed in the model. Data were collected from 210 users with mobile coupon recommendation experience in one of the largest SNS (i.e. WeChat) in China. The authors used partial least squares technique to analyze the model.

Recommendation trust and positive utilities (economic benefits and perceived enjoyment) positively affect the intention of mobile coupon redemption. Perceived risk, as a negative utility, negatively influences coupon redemption intention. In addition, swift trust (structure assurance, perceived similarity, trust propensity, and expertise of the recommender), knowledge-based trust (familiarity with the retailers), and emotion-based trust (social tie strength) are key drivers that promote recommendation trust.

While prior research investigated mobile coupon redemption behavior in which coupons were issued by merchants, limited research analyzed consumer responses toward mobile coupons in social recommendation. This study examines the effects of recommendation trust, positive utilities, and negative utilities on mobile coupon redemption in the context of social recommendation and recognizes the key drivers of recommendation trust.

At present, electrical heating clothing is widely used to keep ourselves warm at low temperature. The purpose of this paper is to explore the heat transfer performance of electrical heating fabric and the thermal comfort of human skin at low temperature.

The combined model of skin-electrical heating fabric system was established to simulate human skin tissue wearing electrical heating clothing. A series of simulation experiments are designed on the basis of verifying the effectiveness of the combined model. The temperature distribution inside the combined model and on the skin surface under different heating powers is simulated and analyzed. At the same time, the influence of ambient temperature on the thermal performance of electrical heating fabric was explored.

The skin model with blood vessels reflected the temperature change of human skin wearing electrical heating clothing. The higher the heating power of the electrical heating fabric was, the greater the temperature of the skin surface changed, the faster the temperature rose and the longer the time required to reach the stable state would be. After the heating element was electrified, it had the greatest effect on the average temperature of the epidermis and dermis, had smaller effect on the average temperature of subcutaneous layer and had little effect on the temperature of blood vessels. When the heating power was the same, the higher the ambient temperature was, the more obvious the heating effect of electrical heating fabric was. Electrical heating fabrics with different heating powers were suitable for different ambient temperature ranges.

A reasonable and effective evaluation method for the thermal comfort of electrical heating fabric was provided by establishing the skin model and combined model of the skin-electrical heating fabric system. It provides a reference for the design and application of electrical heating clothing.

This paper aims to focus on studying the addition of nano-tungsten disulfide (WS₂) on fretting wear performance of ultra-high-molecular-weight-polyethylene (UHMWPE).

In this study, the effect of WS₂ content on fretting wear performance of UHMWPE was investigated. The fretting wear performance of the UHMWPE and WS₂/UHMWPE nanocomposites were evaluated on oscillating reciprocating friction and wear tester. The data of the friction coefficient and the specific wear rate were obtained. The worn surfaces of composites were observed. The transfer film and its component were analyzed.

With the addition of 0.5% WS₂, the friction coefficient and specific wear rate increased. With the content increased to 1% and 1.5%, the friction coefficient and specific wear rate decreased. The lowest friction coefficient and specific wear rate were obtained with the addition of 1.5% nano-WS₂. Continuingly increasing content, the friction coefficient and wear rate increased but lower than that of pure UHMWPE.

The research indicated the fretting wear performance related to the content of nano-WS₂ with the incorporation of WS₂ into UHMWPE.

The result may help to choose the appropriate content.

The main originality of the research is to reveal the fretting behavior of UHMWPE and WS₂/UHMWPE nanocomposites. It makes us realize the nano-WS₂ had an effect on the fretting wear performance of UHMWPE.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2020-0151/

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters conveniently and achieve high measurement accuracy.

A stiffness and kinematic measurement principle of the integrated system is proposed, which considers the influence of robot weight and load weight on measurement accuracy. Then an error model is derived based on the principle that the coordinate of sphere center is invariant, which can simultaneously identify the parameters of joint stiffness, kinematic and hand-eye relationship. Further, considering the errors of the parameters to be calibrated and the measurement error of 3D camera, a method to generate calibration observation data is proposed to validate both calibration accuracy and parameter identification accuracy of calibration method.

Comparative simulations and experiments of conventional kinematic calibration method and the stiffness and kinematic calibration method proposed in this paper are conducted. The results of the simulations show that the proposed method is more accurate, and the identified values of angle parameters in modified Denavit and Hartenberg model are closer to their real values. Compared with the conventional calibration method in experiments, the proposed method decreases the maximum and mean errors by 19.9% and 13.4%, respectively.

A new measurement principle and a novel calibration method are proposed. The proposed method can simultaneously identify joint stiffness, kinematic and hand-eye parameters and obtain not only higher measurement accuracy but also higher parameter identification accuracy, which is suitable for on-site calibration.

The purpose of this paper is to present a neural network approach to control performance assessment.

The performance index under study is based on the minimum variance control benchmark, a radial basis function network (RBFN) is used as the pre‐whitening filter to estimate the white noise sequence, and a stable filtering and correlation analysis method is adopted to calculate the performance index by estimating innovations sequence using the RBFN pre‐whitening filter. The new approach is compared with the auto‐regressive moving average model and the Laguerre model methods, for both linear and nonlinear cases.

Simulation results show that the RBFN approach works satisfactorily for both linear and nonlinear examples. In particular, the proposed scheme shows merits in assessing controller performance for nonlinear systems and surpasses the Laguerre model method in parameter selection.

A RBFN approach is proposed for control performance assessment. This new approach, in comparison with some well‐known methods, provides satisfactory performance and potentials for both linear and nonlinear cases.