Industrial recycling and reusing are becoming more and more important due to the environmental and economic pressures. They involve disassembly activities to retrieve all the parts or selected parts of a product after its current end-of-life. An information modeling for the disassembly and the optimal disassembly sequence generation based on the information model becomes critical. Most of the currently available information models emphasize on the use of deterministic information or crisp logic, which means, the information is known a priori, and the logic related to them is either true or false. However, this scenario is not true in the real world. If we consider concepts like operation cost and part value as for example, in real life, the disassembly operation cost will be varying according to the efficiency and experience of the operator. The value of the retrieved part is also not a constant number; it is dependent on the condition of the part retrieved. Along with it, the logic developed on this uncertain information is fuzzy. For example, a part might be good, very good, fairly good, poor, and etc. Words like "very", "fairly" can't be represented in the crisp logic which requires either a 'true' or a 'false' value. So, this paper proposes a modified, fuzzy logic- based ontology to represent and further use the uncertain information in a disassembly process, Case studies have been included to illustrate the concept.