Search results

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

The purpose of this research is to develop a time-cost optimization model to schedule repetitive projects while considering limited resource availability.

The model is based on the constraint programming (CP) framework; it integrates multiple scheduling characteristics of repetitive activities such as continuous or fragmented execution, atypical activities and coexistence of different modes in an activity. To improve project performance while avoiding inefficient hiring and firing conditions, the strategy of bidirectional acceleration is presented and implemented, which requires keeping regular changes in the execution modes between successive subactivities in the same activity.

Two case studies involving a real residential building construction project and a hotel refurbishing project are used to demonstrate the application of the proposed model based on four different scenarios. The results show that (1) the CP model has great advantages in terms of solving speed and solution quality than its equivalent mathematical model, (2) higher project performance can be obtained compared to using previously developed models and (3) the model can be easily replicated or even modified to enable multicrew implementation.

The original contribution of this research is presenting a novel CP-based repetitive scheduling optimization model to solve the multimode resource-constrained time-cost tradeoff problem of repetitive projects. The model has the capability of minimizing the project total cost that is composed of direct costs, indirect costs, early completion incentives and late completion penalties.

Interrupting work continuity provides a way to improve some project performance, but unexpected and harmful interruptions may impede the implementation. This paper aims to mitigate the negative impact caused by work continuity uncertainty based on the notion of robustness.

This paper develops a float-based robustness measurement method for the work continuity uncertainty in repetitive projects. A multi-objective optimization model is formulated to generate a schedule that achieves a balance between crew numbers and robustness. This model is solved using two modules: optimization module and decision-making module. The Monte Carlo simulation is designed to validate the effectiveness of the generated schedule.

The results confirmed that it is necessary to consider the robustness as an essential factor when scheduling a repetitive project with uncertainty. Project managers may develop a schedule that is subject to delays if they only make decisions according to the results of the deadline satisfaction problem. The Monte Carlo simulation validated that an appropriate way to measure robustness is conducive to generating a schedule that can avoid unnecessary delay, compared to the schedule generated by the traditional model.

Available studies assume that the work continuity is constant, but it cannot always be maintained when affected by uncertainty. This paper regards the work continuity as a new type of uncertainty factor and investigates how to mitigate its negative effects. The proposed float-based robustness measurement can measure the ability of a schedule to absorb unpredictable and harmful interruptions, and the proposed multi-objective scheduling model provides a way to incorporate the uncertainty into a schedule.

Repetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.

This paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.

Using soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.

The main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.

This study assists practitioners in determining the “most preferred” schedule once additional information is provided.

This paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.

The purpose of this paper is to determine the fundamental factors influencing the equity share in build‐operate‐transfer (BOT) investments in relation to the project risk profile.

The relationships between risk factors and equity participation into the capital structure of a BOT contract are examined using regression analysis of a dataset of toll road projects.

Results suggest that the inflation rate, the size of the investment, the construction period, the solidity of the vehicle company, and the organizational structure of the project are significant variables of the equity portion of financing.

The analysis may support project promoters by providing better understanding of the factors that might facilitate high debt leverages and by providing lending institutions with valuable information to integrate the method of determining the appropriate debt resources to be injected into a BOT project.

The paper contributes towards growing the body of knowledge regarding the way public‐private partnership initiatives are carried over and helps refine the capital structures of BOT projects.

This paper aims to present a sliding mode control method based on disturbance observer (DO) for improving the reaching law of permanent magnet synchronous motor (PMSM).

Aiming at the insufficiency of the traditional exponential reaching law used in sliding mode variable structure control, an exponential reaching law related to the speed error is proposed. The improved exponential reaching law can adaptively adjust the size of the constant velocity term in the reaching law according to the size of the speed error, so as to adaptively adjust the speed of the system approaching the sliding mode surface to overcome the control deviation and improve the dynamic and steady state performance. To improve the anti-interference ability of the system, a DO is proposed to observe the external disturbance of the system, and the observed value is used to compensate the system. The stability of the system is analyzed by Lyapunov theorem. The effectiveness of this method is proved by simulation and experiment.

Simulation and experiment show that the proposed method has the advantages of fast response and strong anti-interference ability.

The proposed method cannot observe the disturbance caused by the change of internal parameters of the system.

A sliding mode control method for PMSM is proposed, which has good control performance. The proposed method can effectively suppress chattering, ensure fast response speed and have strong anti-interference ability. The effectiveness of the algorithm is verified by simulation and experiment.

With the development of automation technology, the accuracy, bearing capacity and self-adaptation requirements of wheeled mobile robots are more and more demanding under various complex conditions, which will urge designers such shortcomings as the low accuracy, poor flexibility and weak obstacle crossing ability of traditional heavy haul vehicles and improve the wear resistance and bearing capacity of traditional omnidirectional wheels.

The optimal configuration for heavy payload transportation is obtained by building sliding friction consumption model of traditional wheels with different driving types based on Hertz tangential contact theory. The heavy payload omnidirectional wheel with a double-wheel steering and a coupled differential wheel driving is designed with the optimal configuration. The wheel consists of a differential gear train unit and a nonindependent suspension unit. Kinematics model of the wheel is established and relative parameters are optimized.

The prototype experiments show that the wheel has higher motion accuracy and environment adaptability. The results are consistent with the theoretical calculation, which show that the accuracy is more than 50% higher than that of differential prototype. The motion stability and the accuracy of the coupled differential omnidirectional wheel are better than those of the traditional omnidirectional wheels during the moving and obstacle crossing process under complex conditions, which verifies the correctness and advantages of the design.

Aiming at the specific application of heavy payload omnidirectional transportation, a new omnidirectional mobile mechanism with a two-wheel coupling drive structure and an adaptive mechanism is proposed. The simulation and experimental results show that it can realize the high-precision heavy-load omnidirectional movement, the effective contact with the ground and improve the adaptability to the rugged ground. It is flexible, simple and modular and can be widely applied to transportation, exploration, detection and other related industrial fields.

As the carrier of knowledge, intellectual capital plays a crucial role in technology capability. However, most of the previous studies focus on technological capability from a static perspective, rather than take dynamic technology capability into consideration. Based on this research gap, the purpose of this paper is to investigate the effects of intellectual capital and its sub-dimensions on dynamic technology capability, measuring by the factor scores of five technological input and output variables.

The authors combine the system dynamic method and empirical study to guarantee the internal and external validity. Specifically, the authors design the system dynamic model and simulation to analyze the system mechanism of intellectual capital and its sub-dimensions on dynamic technology capabilities from four cause and effect feedback loops. Then, the authors propose eight hypotheses based on this system dynamic model. In the empirical test phase, the authors employed a panel data set pertaining to Chinese manufacturing firms from 2007 to 2017, and adopted the fixed effect panel model according to Hausman test.

The authors find that intellectual capital efficiency (ICE) and its sub-dimensions (i.e. human capital efficiency, organizational capital efficiency and capital employed efficiency (CEE) have significantly positive impacts on dynamic technology capability. The results also show that the positive effects of ICE and OC on dynamic technology capability would be strengthened in state-owned enterprises compared with non-state-owned enterprises, while this moderation effect is weakened on the relationship between CEE and dynamic technology capability.

In this study, the authors first introduce the system dynamic method to explore the relationship of intellectual capital and dynamic technology capability, which is a valuable trial on combining system science and empirical study. Additionally, the authors continue to expand the dynamic technology capability from the intellectual capital perspective, and also find the moderating effect from the ownership aspect. It is beneficial to the theoretical development of intellectual capital and dynamic technology capability. Furthermore, the authors provide significant inspirations and implications for enterprise’s managers.

In high-tech markets, innovation is always generative and continuous both within the iteration in a product's development process and throughout the upgrade of multi-generational products. Inspired by this practical phenomenon, this study aims to explore the mechanism of innovation generativity and continuity to explain how future innovations benefit from current innovations.

The study conducted qualitative research to explore innovation generativity and continuity by investigating five electronic information enterprises. The authors employed the ambidexterity perspective to explore the research question.

The authors found innovation generativity has three dimensions: inheritance, metabolism and inspection. These three dimensions and their interactions are what forms the mechanism of innovation generativity and continuity. The authors also found many paradoxes that prompt enterprises to pursue innovation generativity and continuity, and through this innovation process, enterprises are able to attain continuous innovation.

This study theoretically uncovers “how” to carry out innovation generativity and continuity, as well as the antecedents and the outcome. The findings contribute to research on product innovation, continuous innovation and ambidexterity, and have implications for managers who seek to improve innovation generativity and continuity.

The occupational health risk associated with the production of prefabricated concrete components is often overlooked. This paper will use a damage assessment and cyclic mitigation (DACM) model to provide individualized exposure risk assessment and corresponding mitigation management measures for workers who are being exposed.

The DACM model is proposed based on the concept of life cycle assessment (LCA). The model uses Monte-Carlo simulation for uncertainty risk assessment, followed by quantitative damage assessment using disability-adjusted life year (DALY). Lastly, sensitivity analysis is used to identify the parameters with the greatest impact on health risks.

The results show that the dust concentration is centered around the mean, and the fitting results are close to normal distribution, so the mean value can be used to carry out the calculation of risk. However, calculations using the DACM model revealed that there are still some work areas at risk. DALY damage is most severe in concrete production area. Meanwhile, the inhalation rate (IR), exposure duration (ED), exposure frequency (EF) and average exposure time (AT) showed greater impacts based on the sensitivity analysis.

Based on the comparison, the DACM model can determine that the potential occupational health risk of prefabricated concrete component (PC) factory and the risk is less than that of on-site construction. It synthesizes field research and simulation to form the entire assessment process into a case-base system with the depth of the cycle, which allows the model to be continuously adjusted to reduce the occupational health damage caused by production pollution exposure.