## 1 Introduction  
This paper presents a systematic review of the literature on the machinability of additively manufactured Ti6 Al4V alloy, focusing on energy consumption, the qualification process of machined parts for assembly, and the effects of the tool wear rate. The review specifically addresses AM-based techniques for producing Ti6 Al4V components and examines post-processing methods to evaluate machining performance responses, including tool wear rate, surface quality, chip morphology, and the optimization of cutting parameters. Additionally, it explores the application of the Johnson-Cook (J-C) model as a finite element analysis (FEA) tool to predict flow stress, cutting forces, and temperature fields during turning operations to achieve the desired final surface quality. The article begins by analyzing the properties, applications, advantages, and disadvantages of Ti6 Al4V alloy as the material of focus. The AM techniques reviewed include selective laser melting, laser metal deposition, electron beam melting, gas tungsten arc welding, the plasma arc welding process, and direct metal deposition. The machinability of the titanium alloy covered includes cutting tool material, tool geometry, tool wear rate, chip morphology, specific cutting energy, surface roughness, cutting forces, optimization processes, and qualification of machined parts for assembly. AM is a promising technology that is capable of manufacturing metallic parts in a layer-by-layer manner. AM has vast advantages of reducing lead time, cost, and energy consumption both in process energy consumption and wholistically due to material saving, stocking decrease, and assembly line reduction. The motivation behind AM is the need to automate machines to minimize waste material, reduce energy consumption, and improve material efficiency [1]. Moreover, the overall decline in component weights, especially in aerospace and automotive structural parts, significantly reduces energy consumption during their service period. The lack of surface finishing is the only challenge of metal AM processed factors, which leads to post-processing (end-machining) requirements, especially at mating surfaces in an assembly. Manufacturing is energy-intensive, and techniques are developed to reduce energy consumption, especially in machining. Manufacturing accounts for 60% of the total energy used in the industry [2; 3; 4]. However, the cited references did not account for the energy consumption specifically associated with the machining process for titanium alloy. This review will help in understanding the amount of energy consumed by the machining process. Despite its advantages, the post-processing of AM parts still consumes power and needs to be investigated and optimized. The energy used in machining processes typically comes from various sources, such as electricity and fossil fuels, which can often be carbon-intensive. Reducing energy consumption decreases the demand for these energy sources, thus leading to lower carbon emissions. The machining process involves the removal of unwanted material from a workpiece to achieve the desired surface finish. It is a critical and versatile method utilized across various industries, including the aerospace, automotive, and electronics fields. Machining processes are essential for the production of precise and complex components, ranging from simple parts to intricate prototypes. Machining plays a central role in the manufacturing of a wide array of products, from everyday items like screws and bolts to critical components in industries like aerospace and medical devices. It is a versatile and indispensable manufacturing process that continues to evolve with advances in technology and materials, enabling the creation of increasingly complex and precise parts [5]. Apart from the poor surface finishing and low dimensional accuracy of AM titanium alloy, the mechanical and geometrical requirements of the aerospace industry are the main reasons for adopting the end-machining process as the most common approach to finish AM parts [6].