Structures and Mechanical Properties of Some Dual-Phase Steels with Low Manganese Content

Current Trends in Metallic Materials for Body Panels and Structural Members Used in the Automotive Industry

The development of lightweight and durable materials for car body panels and load-bearing elements in the automotive industry results from the constant desire to reduce fuel consumption without reducing vehicle performance. The investigations mainly concern the use of these alloys in the automotive industry, which is characterised by mass production series. Increasing the share of lightweight metals in the entire structure is part of the effort to reduce fuel consumption and carbon dioxide emissions into the atmosphere. Taking into account environmental sustainability aspects, metal sheets are easier to recycle than composite materials. At the same time, the last decade has seen an increase in work related to the plastic forming of sheets made of non-ferrous metal alloys. This article provides an up-to-date systematic overview of the basic applications of metallic materials in the automotive industry. The article focuses on the four largest groups of metallic materials: steels, aluminium alloys, titanium alloys, and magnesium alloys. The work draws attention to the limitations in the development of individual material groups and potential development trends of materials used for car body panels and other structural components.

Using Regression Analysis for Automated Material Selection in Smart Manufacturing

In intelligent manufacturing, the phase content and physical and mechanical properties of construction materials can vary due to different suppliers of blanks manufacturers. Therefore, evaluating the composition and properties for implementing a decision-making approach in material selection using up-to-date software is a topical problem in smart manufacturing. Therefore, the article aims to develop a comprehensive automated material selection approach. The proposed method is based on the comprehensive use of normalization and probability approaches and the linear regression procedure formulated in a matrix form. As a result of the study, analytical dependencies for automated material selection were developed. Based on the hypotheses about the impact of the phase composition on physical and mechanical properties, the proposed approach was proven qualitatively and quantitively for carbon steels from AISI 1010 to AISI 1060. The achieved results allowed evaluating the phase composition and physical properties for an arbitrary material from a particular group by its mechanical properties. Overall, an automated material selection approach based on decision-making criteria is helpful for mechanical engineering, smart manufacturing, and industrial engineering purposes.