Romo Gamboa, Rubén
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Romo Gamboa, Rubén
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Romo Gamboa, Rubén
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rromog
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58172021400

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Artificial Bee Colony Algorithm to Optimize the Safety Distance of Workers in Construction Projects

2024 , Eric Forcael , Ibzan Carriel , Alexander Opazo-Vega , Moreno Abril, Francisco , Duzgun Agdas , Romo Gamboa, Rubén , Orozco, Francisco

This paper presents the results of a simulation model regarding the productivity and safety working space for construction workers through the floors of a building using swarm intelligence (SI), a field of artificial intelligence (AI), and specifically using artificial bee colony (ABC) optimization. After designing the algorithm used to build the simulation model, the simulation was used in an actual building project by comparing the travel times of workers conventionally transporting material with another group working on routes optimized by the algorithm. Thus, the proposed algorithm provides routes combining shorter travel times and correct distances between workers when transporting materials in a construction site, handling the interference between crews. After validating the algorithm on-site, no statistically significant differences were found between the travel times of workers and the times delivered by the algorithm. Additionally, the travel times using the routes obtained through the algorithm were significantly lower than those made by workers who moved freely without a predefined route. In summary, the algorithm proposed may help construction practitioners maintain safe movements that respond to hazard contexts imposed by any restriction that demands a safety distance.

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Statistical Analysis of Lean Construction Barriers to Optimize Its Implementation Using PLS-SEM and PCA

2024 , Romo Gamboa, Rubén , Alejo-Reyes, Avelina , Orozco, Francisco

The construction industry performs many tasks scheduled and related to other activities. Companies must optimize their operations, increase efficiency, eliminate waste, and deliver better products to their customers. As a result, this study aims to identify the main challenges associated with the implementation of the Lean Construction model in small and medium-sized construction companies and optimize the implementation of this process using statistically-focused mathematical models. This study was conducted using the partial least squares (PLS-SEM) method and also carried out the principal component analysis to optimize Lean barriers so that they can be properly implemented in the construction industry. The most important obstacles are displayed, as well as the relationships with other factors. Significant relationships have been discovered between the barriers to Lean construction adoption, especially with regard to corporate culture, communication, training, leadership, and the influence of mentality on business and employee adaptability. Construction executives and managers can make well-informed policy and strategic decisions by having a thorough understanding of the main barriers to Lean implementation. This information enables them to focus on the implementation of Lean technologies in projects, to increase market competitiveness, reduce waste and enhance overall work efficiency.

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Towards a Model That Sees Human Resources as a Key Element for Competitiveness in Construction Management

2023 , Romo Gamboa, Rubén , Orozco, Francisco , Eric Forcael , Moreno Abril, Francisco

The construction industry is continuously affected by external and internal agents that modify and define its competitiveness. Changing markets, currency fluctuations, and tremendous competition have made the issue of competitiveness increasingly important. The literature highlights factors that determine the competitiveness of construction firms, including easy-to-measure elements, such as financial, sales, return on investment, etc., while other elements are not as easily measurable, such as customer satisfaction, employee satisfaction, loyalty, and leadership, among many others. Within these factors, Human Resources (HR) has occupied a central place in the last decade, due to the enormous impact that labor has on project execution. This research mainly focuses on the study of HR and its components to reach a deeper understanding of the impact that HR has on the competitiveness of construction companies. After defining the most relevant variables, an interrelationships model was proposed with the Partial Least Square (PLS) technique. These HR variables impact the competitiveness variables: cost, utility, time, quality, Staff retention, and Health & Safety. The PSL analyses met the evaluation criteria using the structural model, confirming its viability. It was found that there are three important variables related to competitiveness: (i) leadership, (ii) innovation, and (iii) competitiveness.

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