scholarly journals Engineering approach to allocate and evaluate performance influencing factors for ready mixed concrete batch plant under different effects

2018 ◽  
Vol 57 (4) ◽  
pp. 3237-3247 ◽  
Author(s):  
Remon Fayek Aziz
2020 ◽  
Vol 26 (10) ◽  
pp. 80-93
Author(s):  
Hussein T. Almusawi ◽  
Abbas M. Burhan

Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values. In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixed concrete (WRMC) plant production and dry ready mixed concrete (DRMC) plant production, in addition to determining the factors affecting productivity. The results showed that the artificial intelligence neural network is an effective technique to estimate the productivity of the dry and wet ready mixed concrete batch plant. The ANN model showed satisfying results of validation for both training and external datasets with the range of training dataset and poor results with the data that exceeds the range of training. At the same time, the skills of the operators, frequent failure of concrete, and lack of construction materials were the most important factor that affected productivity.


2021 ◽  
Vol 13 (4) ◽  
pp. 2354
Author(s):  
Liping Cao ◽  
Fenqi Zhou ◽  
Yuan Zhu

By employing ecological economics involving performance-influencing factors and third-party governance services that have the aim of reducing environmental pollution, a theoretical framework which includes object, subject, process that measures the performance of such services is analyzed on the basis of the idea of sustainability science (2.0). The research hypotheses regarding the relationships among service performance, multi-stakeholder subjects’ satisfaction, and the effect of process management are put forward; then, a three-dimensional performance measurement model, which includes performance, stakeholders, and the process of providing third-party governance services for addressing environmental pollution, is constructed based on the pressure–state–response (PSR) driving force model. At the same time, based on empirical data of the Shanghai municipality, the structural equation model (SEM) is used to empirically test the nine proposed research hypotheses. The empirical test results show that, except for the research hypotheses in regard to regulating variables and controlling variables, all of the research hypotheses passed the test. It means the direct performance, single subjective satisfaction, process management effects are performance-influencing factors. However, the stakeholders’ cooperation satisfaction partially influences the performance of third-party governance services regarding environmental pollution. Finally, through theoretical and empirical research, this paper proposes countermeasures and suggestions for improving the performance of third-party governance services regarding environmental pollution in Shanghai focusing on two aspects: one is the market governance mechanism innovation, and the other is regulations and standards innovation.


2016 ◽  
Author(s):  
Stephen C. Theophilus ◽  
Olayinka G. Abikoye ◽  
Andrew O. Arewa ◽  
Augustine O. Ifelebuegu ◽  
Victor Esenowo

ABSTRACT Numerous studies suggest that 80% of accidents in hydrocarbon processing industries are as a result of human factors (HFs). While a lot is known of human factor influence to process accident, the effects of performance influencing factors (PIFs) on human factors in process accidents is not yet well understood. This study examined HFs and PIFs which influences the propagation of undesired occurrences in hydrocarbon processing industries. An illustrative case study of the Tesoro refinery accident was analysed. To affirm consistency in judgments, Analytic Hierarchy Process AHP – a multi-criteria decision-making method was used in identifying HFs and PIFs of critical events. BPMSG AHP computer program was also used to validate results obtained from the manual calculations. Three critical events namely non-routine operations (Event 1), manual manipulation of several isolation block valves (Event 2) and automated start-up operations of Naphtha Hydro-Treating unit (Event 3) were identified. The ranking of PIFs revealed that Procedures, Level of Supervision, Task Characteristics, and Skill Level were major influencing factors to the event. Analysis of human factors revealed that Job Factors had the most significant influence (41%), while the Individual Factors and Organisational Factors had (31%) and (28%) influence respectively. The consistency index (CI) and consistency ratios (CR) of the PIFs were 0.174 and 0.193 for critical Event 1; 0.170 and 0.120 for critical Event 2; and, 0.037 and 0.033 for critical Event 3 respectively. This showed consistency in judgments of the study on PIFs selected for the critical events identified. The Tesoro refinery accident was due to latent organisational and cultural failures.


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