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EN
Purpose: The aim of the work was to present the automation of the mass measurement process as a factor that can significantly affect the quality and speed of analyzes in pharmaceutical industry. Design/methodology/approach: In this study, two methods were presented for testing the mass uniformity of tablets whose weight ranged from 13 mg to 2580 mg. The first method involved determining the weight of 20 randomly selected tablets of pharmaceutical preparations by statically measuring the weight of these tablets. In the second method, an automatic tablet feeder type PA-04/H was used, in which, as a result of vibration, successive tablets were automatically moved via a special chute onto the weighing pan. Findings: No significant differences were found in the weight measurements performed by the manual and automatic methods. The largest differences were noted at the 0.5% level. All tablets tested met the United States Pharmacopeia requirements for their mass uniformity. For orally disintegrating tablets, the largest percentage deviations in weight from the mean value were -4.47% for tablet F6, - 4.26%, for tablet F1 and 3.31% for tablet F2. The differences in accuracy and precision between the automatic and manual methods were insignificant. Research limitations/implications: Mass measurement by the manual method is one of the most frequently performed measurements in the laboratory. The final result from this measurement method may be subject to error caused, for example, by human error, i.e. reading, writing or calculation error. For this reason, process automation is increasingly being used, which eliminates the possibility of error to a large extent. Practical implications: The automation of weight measurement reduces the effort required for product inspection. Thus, it can be an important factor in the process of optimization and product quality management. Originality/value: The description of the research method and its results can be a valuable guideline for people who deal with product quality control in the pharmaceutical industry. It has been shown that automation to be effective does not have to be complicated but well designed.
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