Abstract:
Effective fault management in production processes and ensuring product
quality is crucial for manufacturing companies to retain and attract customers. While
Failure Mode and Effect Analysis (FMEA) is used for the identification and
evaluation of faults in manufacturing processes to their reoccurrence, its
effectiveness can be limited when dealing with complex issues. In the manufacturing
industry, processes are often interconnected so ignoring their interrelationships can
undermine the authenticity of research outcomes. This study integrates the
traditional FMEA model with fuzzy Decision-Making Trial and Evaluation
Laboratory (Fuzzy DEMATEL) method and cloud model theory (CMT) to overcome
the limitations of traditional FMEA in handling complex interrelationships and
uncertainties among production faults. This novel integrated approach undertakes
the tasks in four distinct steps: First, traditional FMEA is used to identify and rank
potential failures based on Risk Priority Numbers (RPN). Second, CMT is applied
on the prioritized faults with higher RPN values to process random and uncertain
judgments effectively. Third, the DEMATEL method is expanded using fuzzy logic,
enabling the identification of crucial faults and their interrelationships. Fourth,
validation of the approach is carried out using a case study of a Tobacco
manufacturing company in Pakistan, showcasing its benefits and usefulness for realworld scenarios. This novel approach identified the faults and classified them into 6
causes and 10 effects separately. The relationship diagram reveals that fault F9 is the
most severe cause and fault F11 is the most impacted effect. This research helped
managers identify the most vulnerable areas within the manufacturing process,
enabling them to take preemptive actions. As a result, the manufacturing processes
become more efficient and effective, significantly reducing losses due to interrelated
faults and ultimately enhancing overall competitiveness while reducing customer
complaints.
