Critical Review on Magnetically Impelled Arc Butt Welding: Challenges, Perspectives and Industrial Applications

Magnetically Impelled Arc Butt (MIAB) welding is a cutting-edge joining method that replaces the conventional welding procedures such as resistance, friction, flash and butt welding. It is a solid-state process that uses a rotating arc to heat up the butt ends of tubes, being followed by a forging process that completes the joining of the workpieces The magnetic flux density and the current interact to develop the Lorentz force that impels the arc along the faying surfaces. This process is found to produce high tensile strength and defect-free welds in ferrous materials and for this reason, it is predominantly employed in automobile applications for joining metallic tubes. Also, this joining procedure can be applied in the fabrication of boilers, heat exchangers, furnace piping in petrochemical industry and other safety-critical high-pressure machinery parts. The MIAB method has several advantages such as a shorter welding cycle, lower input energy requirement and lower loss of material. Compared to other solid-state welding processes, the MIAB welding has an important advantage in terms of cost-efficient welds with better control and reliability. Moreover, there are researchers who have investigated the joining of non-ferrous dissimilar materials using this welding procedure. The studies have been focused on process parametric analysis that involves optimizing and forecasting the magnetic field and thermal profile distribution. This review article provides competitive insights into various design features, computational methods, tests and material characterization, technical issues and workarounds, as well as automation aspects related to the MIAB-welding process. This work will prove to be a quick reference for researchers, useful to identify the research gaps and conflicting ideas that can be further explored for advancements in joining the similar and dissimilar materials.

Model of Production System Evaluation with the Influence of FDM Machine Reliability and Process-Dependent Product Quality

This paper investigates the Job Shop Scheduling Problem (JSSP) with FDM (Fused Deposition Modeling) machine unavailability constraints due to Predictive Maintenance (PdM) tasks, under the objective of minimizing the makespan, total tardiness and machine idle time. The Ant-Colony Optimization (ACO) algorithm is elaborated to deal with the JSSP. The reliability characteristics of the critical machine (FDM) influence the product as well as the production system quality. PdM periods are estimated based on historical data on failure-free times of the FDM machine components and deviations from the standards established for the key process parameters: infill density, layer thickness and extruder temperature. The standards for the key process parameters are identified based on investigation of the mechanical properties of printed elements. The impact of failure time and the number of nonstandard measurements of parameters on the quality of the Job Shop System (JSS) are observed. Failure rate of the FDM machine is corrected with the probability of a stoppage in the future period due to the “outlier” in measurements of any key parameters of the additive process. The quality robustness of production schedules increases with the disturbance-free operation of the FDM up to the peak value. After reaching the peak value the quality robustness decreases. The original issue of this paper is a model of scheduling production and maintenance tasks in a job shop system with an FDM machine as a bottleneck using ACO. Additionally, an original FDM-reliability model is also proposed. The model is based on weighted p-moving averages of the observed number of deviations from the norms, established for key process parameters such as fill density, layer thickness and extruder temperature.