# Fuzzy-FMEA Theory Approach for Prioritizing Supply Chain Nervousness Factors
## 1 Introduction
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Problem Addressed** & **Methodology** \\ \hline
[1] & MRP nervousness & Order-up-to (OUT) policy and the proportional OUT policy (POUT). \\ \hline
[2] & Assessing internal nervousness in semiconductors SC planning system & Simulation-based analysis \\ \hline
[3] & Demand supply network nervousness & Experiential study \\ \hline
[4] & Evaluating the relationships between the different determinants of schedule nervousness & Statistical analysis \\ \hline
[5] & Studying the relationship between nervousness and the bullwhip effect & Vendor managed inventory (VMI) approach \\ \hline
[6] & Reducing demand nervousness & Mathematical modeling \\ \hline
[7] & System nervousness cost & Mathematical modeling \\ \hline
[8] & Exploring causes and effects of SCN in the MENA region & Delphi-based AHP \\ \hline
[9] & Identifying combinations of factors linked to GSCN & Delphi-FAHP \\ \hline
[10] & Examining setups added to production scheduling nervousness and costs & Wagner–Whitin algorithm \\ \hline
[11] & Scheduling stability and forecast errors & Simulation experiment \\ \hline
[12] & Reducing MRP system nervousness & Modified Wagner–Whitin algorithm \\ \hline
[13] & MRP nervousness & Simulation modeling \\ \hline
[14] & Investigating alternative strategies dealing with nervousness & Simulation experiments \\ \hline
[15] & Order nervousness & Simulation modeling \\ \hline
[16] & Lot-sizing rules and MRP nervousness & Simulation modeling \\ \hline
[17] & Nervousness in manufacturing firms & Simulation modeling \\ \hline
[18] & MRP nervousness & Simulation modeling \\ \hline
[19] & Cost-performance of the MRP system and forecast errors & Simulation modeling \\ \hline
[20] & Classifying nervousness-dampening procedures and their relative effectiveness & Static dampening procedure \\ \hline
[21] & Studying the schedule nervousness increased by uncertainty in the demand forecast & Empirical transfer function estimate (ETFE) \\ \hline
[22] & Reducing frequent revisions of the schedule, which leads to scheduling nervousness & Resource–task network (RTN) \\ \hline
[23] & Comparing the effectiveness of the planning policy for reducing demand uncertainty & Mixed-integer linear programming (MILP) \\ \hline
[24] & Quantifying nervousness in scheduling nervousness based on field observations & Mathematical modeling and analytical hierarchy process (AHP) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Sample of SCN-related work. To fulfill the needs of researchers and SC managers, this paper provides the basis for assessing several types of nervousness through an integrated framework addressing potential interruptions of logistics and SC systems. There are three novelties in this paper. First, SC-related nervousness elements are identified from the perspective of the entire SC. This includes multiple aspects such as interruptions, faults, and errors because of risks, uncertainties, vulnerabilities, and SC disruptions. Second, this study examines and considers more nervousness parameters. This will help better understand and model the SCN. Third, an integrated method is developed to effectively address the several types of uncertainty that exist in the SCN assessment. A joint fuzzy-FMEA-gray correlation method is used to incorporate an effective approach to nervousness assessment. The remainder of this paper is arranged as follows: Section 2 reviews the relevant literature and highlights research gaps. Section 3 presents the research methodology. A case study is presented in Section 4 with results and discussion. Section 5 presents the conclusions.