Ghulam Ameer Mukhtar

This study investigates the prospect of using rapid prototyping, particularly additive manufacturing, in Pakistan’s construction and manufacturing sectors, aiming to encourage R&D by the analysis of technical feasibility of this technology and collaboration between civil and industrial engineering. To solve this puzzle, we collected data from field experts, academia researchers, and license holders of this technology. Further, analytical hierarchy process (AHP), a sub-branch of multicriteria decision-making method (MCDM), was used to gauge the systematically by prioritizing selection criteria for solving the problem. AHP makes the methodical process more accurate and organized, which helped us to proposed a feasibility study for the technology’s success in Pakistan’s construction and manufacturing industries. The findings show a 79.4% probability, which indicates interaction among both engineering disciplines. Furthermore, a sensitivity analysis was conducted to enhance the dependability of the AHP model, which assists in sound decision making during ambiguous conditions. Apart from economic technical aspects, sustainability plays a very crucial role in the evaluation process. This text shows the environmental effects and sustainability implications associated with the assimilation of rapid prototyping technologies. This supports the integration of rapid prototyping in Pakistan, contributing to discussions on technological innovations in emerging nations. This will also lay a foundation for future interdisciplinary collaboration and technological enrichments in both engineering domains.

This study combines additive manufacturing, discrete event simulation, and central composite design to address the challenges of enhancing throughput and tackling bottlenecks in prosthodontic services Particularly in ambulatory surgical units (ASUs). By performing systematic experiments and optimizing parameters, we aimed to smoothen workflow and improve bottlenecks. The findings reveal a noticeable increase in throughput, with the optimized model exhibiting a throughput of 2.35833 compared to 0.975 for the base model and 1.03333 for the alternative model. A balanced workload for servers was observed, with utilization rates ranging from 31.1407% to 88.4426%. Our approach significantly improves system performance by increasing the throughput of the system and addresses critical issues of workload distribution in prosthodontic service delivery.

This study investigated the use of the linear regression algorithm (LRA) for estimating the cost of tungsten inert gas (TIG) welding of dissimilar metals, specifically, stainless steel 304 and aluminum 2024. Various cost analysis parameters, including weld time, power cost rate, labor cost, filler rod cost, and shielding gas cost, were considered. LRA was employed to develop a predictive model for welding costs based on these parameters. The model was then used to optimize welding parameters by identifying the combination that minimized overall welding costs. The results demonstrate that LRA effectively identified a more cost-effective parameter set compared to traditional methods. This highlights the potential of LRA in enhancing the cost-effectiveness of TIG welding processes. The findings have practical implications for field engineers and researchers, enabling the identification of optimal parameters for cost estimation and significant cost savings.