Fertilizer deposition as a function of angular velocity and inclination of the helical dosing mechanism

ABSTRACT The establishment of grain crops in Brazil is an important industrial process in the agricultural chain, requiring the correct deposition of granular fertilizer over the sowing furrow and more efficient, precise, and sustainable assessments in the operation, which can be achieved with the statistical process control. This study aimed to assess the effect of the angular velocity on different inclinations of the helical metering mechanism on the granular fertilizer deposition. An automated electronic bench was used to assess the deposition quality of granular fertilizers considering different angular velocities (1.11, 1.94, and 2.77 m s-1) and longitudinal and transverse inclinations (+15, +7.5, 0, −7.5, and −15°), with the helical doser by overflow. Flow data were collected and submitted to descriptive statistics and statistical process control. The metering mechanism showed expected variations, with acceptable performance under process control. The values of the flow rates of the granular fertilizer increased as velocity increased, standing out longitudinal inclinations of +7.5 and +15°, providing higher fertilizer depositions.

Synchronization-Free Multivariate Statistical Process Control for Online Monitoring of Batch Process Evolution

Synchronization of variable trajectories from batch process data is a delicate operation that can induce artifacts in the definition of multivariate statistical process control (MSPC) models for real-time monitoring of batch processes. The current paper introduces a new synchronization-free approach for online batch MSPC. This approach is based on the use of local MSPC models that cover a normal operating conditions (NOC) trajectory defined from principal component analysis (PCA) modeling of non-synchronized historical batches. The rationale behind is that, although non-synchronized NOC batches are used, an overall NOC trajectory with a consistent evolution pattern can be described, even if batch-to-batch natural delays and differences between process starting and end points exist. Afterwards, the local MSPC models are used to monitor the evolution of new batches and derive the related MSPC chart. During the real-time monitoring of a new batch, this strategy allows testing whether every new observation is following or not the NOC trajectory. For a NOC observation, an additional indication of the batch process progress is provided based on the identification of the local MSPC model that provides the lowest residuals. When an observation deviates from the NOC behavior, contribution plots based on the projection of the observation to the best local MSPC model identified in the last NOC observation are used to diagnose the variables related to the fault. This methodology is illustrated using two real examples of NIR-monitored batch processes: a fluidized bed drying process and a batch distillation of gasoline blends with ethanol.

Multiphasic screening of priority chemical compounds in drinking water by process control and human health risk

Background The residual chemical pollutants in drinking water may cause adverse effects on human health. Chemical compounds potentially affecting human health have been widely explored, while the multiphasic evaluation of chemical compounds by process control and human health risk is still rarely reported. In the present study, we used multiphasic criteria to assess the health risk including effluent concentration, accumulation index, purification index for the removal efficiency during the drinking water treatment processes, carcinogen classification based on the International Agency for Research on Cancer standards, non-carcinogenic health hazards and carcinogenic risk. Results Among the monitored chemicals, 47 and 44 chemical compounds were detected in raw water and treated water, respectively. The generation and removal of chemical compounds implied that the migration and transformation of chemicals during the purification processes affected the effluent concentration, posing a direct potential health risk. Of these compounds, 41 contaminants’ profiles were screened as priority chemical compounds (PCCs). Conclusions The top eight PCCs with high carcinogenic risk were highlighted. Some effective steps, such as protecting the raw water sources, improving the removal performance and reducing the disinfection by-products during the purification process by introducing advanced treatment technologies, were suggested to maintain drinking water security. Collectively, our findings provided novel scientific supports for the sustainable management of drinking water to promote human health. Graphical Abstract