Increasing competition in the international shipbuilding industry pushes the naval architect’s pressure to reduce the costs of design and manufacturing of new buildings. Using newly developed Additive Manufacturing (AM) methods in the framework of industry 4.0 revolution can offer new opportunities in the manufacturing of labour-intensive and complex parts. Wire Arc Additive Manufacturing (WAAM) is a promising candidate for the manufacturing of large-scale metal parts, especially complicated double-curved parts (e.g. bulbous bow, propeller, rudder, etc.), in a more design flexible and cost-effective way in the shipbuilding industry. This article reviews the new developments of WAAM technology and discusses the feasibility of application of WAAM in the shipbuilding industry in the framework of material availability and properties, design complexity and cost by giving current and possible future applications.

Functionally Graded Materials (FGMs) offer discrete or continuously changing properties/compositions over the volume of the parts. The widespread application of FGMs was not rapid enough in the past due to limitations of the manufacturing methods. Significant developments in manufacturing technologies especially in Additive Manufacturing (AM) enable us nowadays to manufacture materials with specified changes over the volume/surface of components. The use of AM methods for the manufacturing of FGMs may allow us to compensate for some drawbacks of conventional methods and to produce complex and near-net-shaped structures with better control of gradients in a cost-efficient way. Vat Photopolymerization (VP), a type of AM method that works according to the principle of curing liquid photopolymer resin layer-by-layer, has gained in recent years high importance due to its advantages such as low cost, high surface quality control, no need to support structures, no limitation in the material. This article reviews the state-of-art and future potential of using VP methods for FGM manufacturing. It was concluded that improvements in printer hardware setup and software, design aspects and printing methodologies will accelerate the use of VP methods for FGMs manufacturing.

This study was conducted to investigate the relationship between the fiber distribution and the permeability properties of the hydroentangled nonwoven fabrics in terms of air permeability and porosity. The fiber distribution and web properties of the hydroentangled nonwoven fabrics have significant influence on mechanical and physical performance of the finished products. Control of these properties during production, without physical testing, plays an important role in reducing response time to change the process parameters as well as production costs and material waste. In this study, an artificial intelligence method has been developed to predict the porosity and air permeability properties of hydroentangled nonwoven fabrics from their texture features. For this aim, two image processing algorithms were developed in order to measure the fabric porosity and to extract texture statistical features. For the prediction of the investigated fabric properties, an Artificial Neural Network (ANN) model was built. The investigated samples were composed of Polyester (PES) and Viscose (CV) fiber with different areal weights. High regression values were obtained between predicted and actual values for both porosity and air-permeability properties. According to ANN results, it was revealed that the air permeability and porosity properties of hydroentangled nonwovens can be predicted with high accuracy from their texture images.