The time delay and potential for particle changes between sampling and analysis make the traditional particle size analysis approach challenging for process optimization and improvement. Traditional offline particle size analyzers are used in the quality control laboratory to measure particle properties with accuracy however, care must be taken to prepare the sample to allow for a consistent measurement. Particle size and count, as well as chemical composition, are important to characterize effectively for the successful development, transfer and operation of processes in numerous industries. Understanding how process parameters influence key transformations, such as nucleation, growth and breakage, allows scientists to develop and manufacture crystals that will have the desired attributes and be efficient to bring to market. In a pharmaceutical compound, bioavailability and efficacy are often related to particle size with smaller particles frequently desired for their enhanced solubility and dissolution characteristics.Ĭrystal size distribution can be optimized and controlled by carefully choosing the correct crystallization conditions and process parameters. Similarly, the final crystal size can also directly influence the quality of the final product. Crystal size and shape directly influence key steps downstream of the crystallizer, with filtration and drying performance being particularly susceptible to changes in these important attributes. While crystals have many important attributes, the crystal size distribution likely has the greatest impact on the quality and effectiveness of the final product (and the process needed to deliver it). User skills and knowledge (theory of applications, technologies, methods, tips and tricks).Time reduction quick adjustment and scalability of methods.Sustainable design (futureproof modular design long lasting).Shift to the next level measurement process (from manual to automated, or to on-line measurement automation).Reduction in operating costs Total cost of ownership Maintenance cost reduction.Productivity (released time from the team) Uptime Optimize processes.Preventive maintenance Minimize downtime.Connectivity Software solutions Data flow from one instrument to another.
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