Abstract
The present state of competition within the plastic composite industry calls for efficiency to be competitive. However, in the drilling of carbon-fiber-reinforced plastic (CFRP) composites, the process engineer still lacks knowledge of the priority of parameters as parameters are chosen at random, and resources are deployed without justification on their importance and strength. Consequently, production crises and productivity losses persist. In this article, the analytic hierarchy process (AHP) method is deployed to evaluate the weights of criteria in a CFRP composite drilling operation. The establishment of the decision, alternatives, and criteria is accomplished, and pairwise comparisons are conducted to allow the computation of the importance weight of each criterion. The weight is then established. The proposed approach was illustrated with experimental data from the literature with a plastic drilling case. Six criteria were chosen as crucial in determining the drilling parameters of CFRP composites. The results reveal the following: thrust force (0.413), torque (0.253), eccentricity (0.151), surface roughness (0.115), delamination at entry (0.037) and delamination at exit (0.030). In a validation exercise to ascertain the consistency of the analysis, a consistent analysis was obtained. The novelty of the article is using the AHP approach on the drilling of CFRP composites. Practically, these results impact operator training, indicating that attention should be focused on thrust force control. The industrial applications of CFRP composites include the basic structures of automobiles, ships, and airplanes.
Highlights
At present, the plastic composite industry survives based on sustainable practices, the maintenance of a broad product range, insistence on quality outputs, timely product delivery to customers, and competitive pricing of plastic composite products (Teuber et al, 2016; Youssef et al, 2019)
Step 3: Establish priority among criteria using pair-wise comparison In this step, a pair-wise comparison table is created while each criterion is compared with another to form a cell value
Step 5: Calculate the criteria weight The criteria weight is the average total of each row element
Summary
The plastic composite industry survives based on sustainable practices, the maintenance of a broad product range, insistence on quality outputs, timely product delivery to customers, and competitive pricing of plastic composite products (Teuber et al, 2016; Youssef et al, 2019). Parametric selection has attained worldwide acceptance as a phenomenon that guides the justifiable allocation of a resource based on an important process (Shayan et al, 2013; Kulkarni and Ramachandran, 2018; Afolayan et al, 2020; Raghunathan et al, 2021). In the drilling of fiber-reinforced plastic composites, the process engineer still lacks knowledge of prioritizing and selecting parameters within the drilling domain (Shayan et al, 2013; Kulkarni and Ramachandran, 2018). The most important parameters to devote substantial resources in decisionmaking and cost-cutting in wasteful expenditures are identified and implemented. This could be achieved by choosing a suitable multi-criteria tool for determining the weights of criteria.
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