Search

The Unilever Food Safety Assurance system for refined oils and fats is based on risk assessments for the presence of contaminants or pesticide residues in crude oils, and refining process studies to validate the removal of these components. Crude oil risk assessments were carried out by combining supply chain visits, and analyses of the contaminant and pesticide residue levels in a large number of crude oil samples. Contaminants like poly-aromatic hydrocarbons and hydrocarbons of mineral origin, and pesticide residues can largely be removed by refining. For many years, this Food Safety Assurance System has proven to be effective in controlling contaminant levels in refined vegetable oils and fats.

Modification of the solid phase lines of naturally occurring oils and fats is required to produce optimal hardstocks for fat continuous products like margarines, spreads and shortenings. Trans-free hardstocks are produced by combination of the trans-free modification techniques: full hydrogenation, interesterification, and fractionation together with the choice of the feedstock. The introduction of trans-free hardstocks in domestic margarines since 1995 has drastically reduced the daily trans intake by European consumers.

The opinion of nutritional science on the effect of trans fatty acids on blood cholesterol has drastically changed during the last decade. As a reaction to these new findings, the European margarine industry decided in the mid nineties to eliminate trans containing components from their margarine fat phase compositions. This excluded practically the use of partially hydrogenated oils and fats. Trans-free margarines have been introduced with optimised fat crystal structures stabilising a maximum of water in oil emulsion with a minimum of solid fat phase. These fat crystal structures are formed by fat phase components obtained from interesterification and/or fractionation of non-hydrogenated and/or fully hydrogenated feedstocks.

The ‘Constituent Roadmap of Product Design’ (CRPD) is a framework that is applied to track the designers’ knowledge of a product design as it progresses during development. The Constituent Roadmap of Product Design was introduced in late 2015 and relies heavily on Axiomatic Design; it uses Axioms 1 and 2 to model understanding of the product- and manufacturing-design by the designer. A central theme when applying the Constituent Roadmap is a procedure of regularly updating the ‘Check Matrix’. The Check Matrix is a table that continuously monitors the designer's knowledge position. Correct application of the check matrix is bound to a number of behavioural characteristics that need to be taken into consideration, e.g.: (i) in a decomposed system, it is not possible that a knowledge score at a certain hierarchical level exceeds that of one of its sublevels. A lack of knowledge is, similar to information in design, the sum of its subordinate knowledge deficits. (ii) on the other hand, the score in the check matrix indeed may exceed that of its lower levels during the process of zigzagging, as zigzagging is a process that advances top-down through the hierarchy of the product design. This paper explains how to apply the check matrix under various circumstances without violating the hierarchical dependencies of good practice in design.

The ipRGCs in the human eye mediate several effects on people, such as alertness and circadian rhythms. The spectral, temporal and spatial characteristics of light influence the magnitude of these effects. To facilitate the anticipation of the ipRGC-influenced light (IIL) responses in building design, new simulation tools are needed. This paper presents an extension to the open-access simulation tool Lark, available as a plugin to Grasshopper for Rhino. The proposed extension includes a set of additional options, components, and templates that incorporate currently available knowledge on the IIL responses. The applicability of the extension is demonstrated in a simulation workflow.