A statistical quality-driven approach to in-polymer additive analysis

Abstract

Traditionally the relationship between processing conditions has been investigated in a linear fashion. Thus relationships between process settings such as processing temperature, shear rate inter alia and product properties such as melt flow properties, color and aging were determined directly and empirical correlation's developed. Additives have been shown to influence polymer properties also, but definition of quantitative relationships involving additive parameters has been elusive. A reason for this fact is that the amount of additive charged to a polymer under processing is not necessarily the parameter which should be measured but it has traditionally been the easiest to measure – ideally the level of residual active stabilizer is of real interest. Hence effects of additives have traditionally been described in qualitative or semiquantitative terms at best. In this paper we describe a quality-driven approach to the in-polymer determination of additives using poly(propylene) and LLDPE as illustrative examples. This process is referred to as “Six Sigma Quality”. The idea is not solely to develop an optimized test in a specific instance but to develop an approach to test optimization and test method refinement which can be applied at several levels to solve problems of additive determination in a variety of polymers.