This study aims to identify a model for building a resilient supply chain in a company testing engine oil
samples. Unstructured face-to-face and structured remote interviews were used as the research methods. The
proposed contextual research procedure allows for the elucidation of the content of the components of the final
resilient supply chain model and may facilitate theory building on the basis of future multiple case studies.
As a result of the research, it was found that at the level of the described chain, its strength and continuity of
flow are based on the durability of relationships with suppliers, speed, trust, and information sharing, the role of
which has been explained in relation to the nature of the supply chain. Due to the nature of the chain, building
its resistance on the basis of agility, which is most often indicated in model approaches, has no justification in
this case. It was also established that in this process, 4.0 technologies such as the internet of things (IoT), machine
learning, artificial intelligence, and cloud technologies are more important for management at the level of
the entire corporation than at the level of the tested chain. The analysis covered the supply chain embedded in
the industry, which (according to the author’s knowledge) was not discussed in the context of logistics processes
in world literature. Therefore, the results of the work undertaken are of great cognitive value.