ISO 9276-4:2001/Amd 1:2017

Overview

ISO 9276-4:2001/Amd 1:2017 is an important amendment to the international standard ISO 9276-4, which focuses on the representation of results of particle size analysis, specifically in the characterization of classification processes. Published by the International Organization for Standardization (ISO), this 2017 amendment provides additional explanations and minor corrections that clarify and enhance the use and interpretation of particle size distribution data in classification workflows.

The standard serves specialists and industries relying on accurate particle size analysis through sieving and other characterization techniques. By refining the definitions, symbols, and formulas, the amendment ensures consistency and accuracy in how particle classification data is reported and assessed, supporting improved product quality and process efficiency.

Key Topics

• Classification Process Characterization: Detailed methodologies and definitions to describe and evaluate how particles are classified by size.
• Distribution Density Terminology: Replacement of “density distribution” with “distribution density” to align with precise technical language.
• Symbol and Term Clarity: Updates to terms such as “Partial classification efficiency” and corrections to symbols (e.g., replacing ф with φ) improve understanding in data representation.
• Mass and Number Balance: Clarified explanations of mass ratio and number ratio calculations for particles within specific size ranges, critical for accurate material balance.
• Grade Efficiency Curve: Enhanced guidelines for interpreting the equiprobable cut size and the median of classification grade efficiency curves, which directly relate to classifier performance.
• Cumulative Distribution Parameters: Clarifications in formulae for calculating parameters derived from cumulative distribution curves help ensure reproducibility and accuracy.
• Correction of Formulae: Mathematical corrections in evaluation formulas (e.g., replacing minus signs with plus signs) eliminate previous ambiguities.
• Bibliography and Reference Updates: Integration with related parts of the ISO 9276 series for comprehensive particle size analysis standards.

Applications

ISO 9276-4:2001/Amd 1:2017 is essential for industries and laboratories performing particle size analysis where classification processes play a crucial role. Typical applications include:

• Mining and Mineral Processing: Evaluating classifiers to optimize separation of ores and minerals by particle size.
• Pharmaceuticals: Ensuring precise particle size distribution in drug powders to control dissolution rates and bioavailability.
• Chemical and Material Engineering: Accurate classification of granular materials for quality control and product formulation.
• Environmental Testing: Characterizing soil and sediment particle size distributions for environmental assessment.
• Food Industry: Refining particle size classification in processes such as milling flour or cocoa powders to meet product specifications.

By adopting this amendment, organizations can improve the reliability of particle size classification data, leading to enhanced process control, better product consistency, and compliance with international best practices.

Related Standards

ISO 9276-4:2001/Amd 1:2017 works within a framework of standards related to particle size analysis, including:

• ISO 9276 Series: A collection of standards covering various aspects of particle size analysis representation.
• ISO 9276-2:2014: Provides methods for calculation of average particle sizes and moments from particle size distributions, referenced and updated within the amendment.
• ISO/TC 24 - Particle Characterization: The technical committee responsible for these standards, focusing on methods like sieving and other particle characterization techniques.

For further details and complementary standards, visit the official ISO website at www.iso.org.

Keywords: ISO 9276-4 amendment, particle size analysis, classification process characterization, grade efficiency curve, distribution density, particle classification efficiency, cumulative size distribution, particle size standards.