Narrow Results

Design/methodology/approach: Converting data into information and its diffusion along all organization units has become a vital survival skill. At this point, an ERP system provides an invisible network among a company’s internal and external stakeholders and plays a strategic role. Moreover, ERP systems offer some advantages. For example, integrating financial, customer, and order information, speeding up production processes, and reducing stock level and order lead time. Therefore, we propose an integrated spherical fuzzy-analytical hierarchy process (SF-AHP) and spherical fuzzy-combinative distance-based assessment (SF-CODAS) framework to prioritize the best ERP software provider for the defense industry.

Purpose: Despite having the advantages mentioned above, some crucial aspects must be considered while selecting an ERP package. Factors such as high cost, difficulty in installation, and security threats can be very challenging. The latter issue needs special care in the defense industry. This study aims to design an evaluation framework for the ERP selection problem in the sector.

Findings: One of the pivoting defense companies in Turkey is chosen as a case study. Seven ERP systems are evaluated with the proposed model. The results show that the proposed model can be successfully implemented in a defense company context. Furthermore, a sensitivity analysis proves the robustness of the approach to varying threshold parameters in CODAS and different fuzzy weighting approaches.

Originality/value: The defense professionals prioritize a different set of selection criteria than conventional manufacturing firms. The study provides a rare holistic framework for the defense industry using a hybridized SF-AHP-CODAS technique. Thus, the study may serve as reference work for the researchers and decision-makers during the digitalization journey of defense firms.

Manufacturing industries are rapidly growing with varying customer needs, and efficient quality control tools are widely used to optimize product/process performances. This paper highlights the modified quality control module to optimize the milling performances of polymer nanocomposites. The carbon fabric and reduced graphene oxide reinforced (CF/rGO) polymer composites are machined at varying process constraints. The experimentation was designed according to Taguchi’s orthogonal array. The Milling performances were optimized using a multi-criterion decision-making (MCDM) tool based on a combination distance-based assessment (CODAS) optimization method. The desired value of surface roughness (Ra) and cutting force (Fc) is examined during the machining of the developed polymer. CODAS optimization module efficiently combined the various contradictory parametric outcomes into a single objective assessment value (Hi), which could not be possible by utilizing the usual conventional Taguchi method. Specifically, the optimal machining conditions were found to be rGO wt.%—1, speed—2000rpm, feed—80mm/min, DoC—1.5mm. Overall, the findings demonstrate the practicality of the recommended MCDM tool, which outperformed the usual conventional Taguchi method. The optimal assessment score of CODAS was noted as 1.904, which confirms the better viability of the current MCDM approach. This study contributes to the advancement of efficient quality control tools that can be widely used to optimize product/process performances in manufacturing industries.

Multi Criteria Decision making (MCDM) problems have been handled with fuzzy sets in order to obtain results in uncertain environment. Picture fuzzy sets (PFSs) is relatively new method for MCDM problems. COmbinative Distance-based ASsessment (CODAS) is a MCDM method and it is used in literature. In this study, a new method is called Picture Fuzzy CODAS is proposed.