The Determination Risk Level of Manufacturing Process Based on IF-TOPSIS and IF-Fuzzy Logic Rules

Abstract

In a dynamic and uncertain environment, maintaining a high level of business process (BP) reliability represents a key long-term objective for organizations. The manufacturing process, as the most critical business process in manufacturing enterprises, is emphasized due to its potential to cause significant disruptions across other BPs if it fails. This paper proposes a two-stage model. In the first stage, failures leading to lean waste are evaluated and ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) combined with interval-valued intuitionistic fuzzy numbers (IVIFNs), referred to as IF-TOPSIS. The model is grounded in the Failure Mode and Effect Analysis (FMEA) framework. In the second stage, a modified fuzzy logic system with IVIFN-based rules is applied to determine the risk level of the manufacturing process. This approach is based on the property of symmetry in the decision-making process, ensuring that criteria are treated in a balanced manner and inference rules are applied consistently. A case study based on real-life data demonstrates that the obtained results identify measures that can enhance business strategy and reduce failure rates. Thus, the model is validated and shown to contribute to lean waste reduction. It can be concluded that the proposed methodology provides clear and practical guidance to enterprise management, as well as to all sectors and individuals involved in ensuring a reliable manufacturing process, for defining failure priorities and implementing preventive measures.