The WORST CASE approach means an optimization of contact conditions which are SIMULANTS, TIMES and TEMPERATURE to have the worst conditions. The product, instead of being tested in the conditions in which i twill be used is tested in worse conditions, so as to be sure that the product will also comply with the state in which i twill be used.

This methodology is also complementaryto other approaches such as the TARGETED-UNTARGETED one.

“WORST CASE” is an approach used in the testing phase of product, in facr, instead of being tested under the conditions in which i twill be used, it is tested under worse conditions (WORST), so as to be sure that the product will also comply with the state where i twill be used. The three variables involved in this approach are:

  • FOOD SIMULANTS: These are substances that simulate the behaviour of food in the environment in which the product will be used. They are selected to represent the most critical situations.
  • TIMES: refers to the duration of exposure or use of the product to the most unfavorable conditions. Timing is important, as some issues may only emerge after a certain period of use or exposure.
  • TEMPERATURE: temperature can significantly affect the performance and stability of a product. Therefore the worst approach also considers the most extreme temperature conditions in which the product could be used.

The main objective of the WORST CASE approach is to ensure product safety and compliance in critical or adverse situation, even if these conditions do not necessarily represent typical use.

The “TARGETED-UNTARGETED” approach is a complementary methodology that focuses on specific objectives ( targeted) but also includes a broader and non-limited (untargeted) analysis to identify any unforseen effects. This broadens the prospective of the analysis and can reveal important information beyond the predefined specification.

In summary, the “WORST CASE” approach is an important strategy to ensure product compliance and safety, while the “TARGETED-UNTARGETED” approach adds a larger dimension to the analysis, allowing to identify possible problems not initially considered.