Latest Developments in Industrial Hybrid Machine Tools that Combine Additive and Subtractive Operations

Hybrid machine tools combining additive and subtractive processes have arisen as a solution to increasing manufacture requirements, boosting the potentials of both technologies, while compensating and minimizing their limitations. Nevertheless, the idea of hybrid machines is relatively new and there is a notable lack of knowledge about the implications arisen from their in-practice use. Therefore, the main goal of the present paper is to fill the existing gap, giving an insight into the current advancements and pending tasks of hybrid machines both from an academic and industrial perspective. To that end, the technical-economical potentials and challenges emerging from their use are identified and critically discussed. In addition, the current situation and future perspectives of hybrid machines from the point of view of process planning, monitoring, and inspection are analyzed. On the one hand, it is found that hybrid machines enable a more efficient use of the resources available, as well as the production of previously unattainable complex parts. On the other hand, it is concluded that there are still some technological challenges derived from the interaction of additive and subtractive processes to be overcome (e.g., process planning, decision planning, use of cutting fluids, and need for a post-processing) before a full implantation of hybrid machines is fulfilledSpecial thanks are addressed to the Industry and Competitiveness Spanish Ministry for the support on the DPI2016-79889-R INTEGRADDI project and to the PARADDISE project H2020-IND-CE-2016-17/H2020-FOF-2016 of the European Union's Horizon 2020 research and innovation program

Techno-Economic Analysis of Hybrid Layered Manufacturing

Subtractive manufacturing (CNC machining) has high quality of geometric and material properties but is slow, costly and infeasible in some cases; additive manufacturing (RP) is just the opposite. Total automation and hence speed is achieved in RP by compromising on quality. Hybrid Layered Manufacturing (HLM) developed at IIT Bombay combines the best features of both these approaches. It uses arc welding for building near-net shapes which are finish machined to final dimensions. High speed of HLM surpasses all other processes for tool making by eliminating NC programming and rough machining. The techno-economic viability of HLM process has been proved through a real life case study. Time and cost of tool making using HLM promises to be substantially lower than that of CNC machining and other RP methods. Interestingly, the material cost in HLM was also found to be lower. HLM is a cheaper retrofitment to any 3 or 5 axis CNC milling machine or machining center.Mechanical Engineerin

Assessment of Automated Fiber Placement for the Fabrication of Composite Wind Tunnel Blades

Composite wind tunnel blades are frequently fabricated by hand layup of prepreg fabrics. Though well proven, this fabrication method is laborious and expensive. The study described in this paper used the Integrated Structural Assembly of Advanced Composites (ISAAC) facility at the NASA Langley Research Center to explore whether automated fiber placement (AFP) could reduce manufacturing time and cost for production of wind tunnel blades. Two blades, taken from two NASA wind tunnels, were investigated as representative geometries. Computer-aided design models of the blade surfaces were created, and AFP process planning and programming were employed to study the manufacturability of the shapes. A placement/cure tool was manufactured for the chosen blade surface from thermoplastic material using an additive manufacturing process. The present study revealed that the AFP head geometry, primarily the heater configuration of the ISAAC system, is the primary constraint that limits the ability to manufacture the selected wind tunnel fan blades using AFP

Towards the Fabrication Strategies for Intelligent Wire Arc Additive Manufacturing of Wire Structures from CAD Input to Finished Product

With the increasing demand for freedom of part design in the industry, additive manufacturing (AM) has become a vital fabrication process for manufacturing metallic workpieces with high geometrical complexity. Among all metal additive manufacturing technologies, wire arc additive manufacturing (WAAM), which uses gas metal arc welding (GMAW), is gaining popularity for rapid prototyping of sizeable metallic workpieces due to its high deposition rate, low processing conditions limit, and environmental friendliness. In recent years, WAAM has been developed synergistically with industrial robotic systems or CNC machining centers, enabling multi-axis free-form deposition in 3D space. On this basis, the current research of WAAM has gradually focused on fabricating strut-based wire structures to enhance its capability of producing low-fidelity workpieces with high spatial complexity. As a typical wire structure, the large-size free-form lattice structure, featuring lightweight, superior energy absorption, and a high strength-weight ratio, has received extensive attention in developing its WAAM fabrication process. However, there is currently no sophisticated WAAM system commercially available in the industry to implement an automated fabrication process of wire or lattice structures. The challenges faced in depositing wire structures include the lack of methods to effectively identify individual struts in wire structures, 3D slicing algorithms for the whole wire structures, and path planning algorithms to establish reasonable deposition paths for these generated discrete sliced layers. Moreover, the welded area of the struts within the wire structure is relatively small, so the strut forming is more sensitive and more easily affected by the interlayer temperature. Therefore, the control and prediction of strut formation during the fabricating process is still another industry challenge. Simultaneously, there is also an urgent need to improve the processing efficiency of these structures while ensuring the reliability of their forming result

Repair of metallic components using hybrid manufacturing

Many high-performance metal parts users extend the service of these damaged parts by employing repair technology. Hybrid manufacturing, which includes additive manufacturing (AM) and subtractive manufacturing, provides greater build capability, better accuracy, and surface finish for component repair. However, most repair processes still rely on manual operations, which are not satisfactory in terms of time, cost, reliability, and accuracy. This dissertation aims to improve the application of hybrid manufacturing for repairing metallic components by addressing the following three research topics. The first research topic is to investigate and develop an efficient best-fit and shape adaption algorithm for automating 3D models\u27 the alignment and defect reconstruction. A multi-feature fitting algorithm and cross-section comparison method are developed. The second research topic is to develop a smooth toolpath generation method for laser metal deposition to improve the deposition quality for metallic component fabrication and repair. Smooth connections or transitions in toolpath planning are achieved to provide a constant feedrate and controllable deposition idle time for each single deposition pass. The third research topic is to develop an automated repair process could efficiently obtain the spatial information of a worn component for defect detection, alignment, and 3D scanning with the integration of stereo vision and laser displacement sensor. This dissertation investigated and developed key technologies to improve the efficiency, repair quality, precision, and automation for the repair of metallic components using hybrid manufacturing. Moreover, the research results of this dissertation can benefit a wide range of industries, such as additive manufacturing, manufacturing and measurement automation, and part inspection --Abstract, page iv

Process planning for an Additive/Subtractive Rapid Pattern Manufacturing system

This dissertation presents a rapid manufacturing process for sand casting patterns using a hybrid additive/subtractive approach. This includes three major areas of research that will enable highly automated process planning; a critical need for a rapid methodology. The first research area yields a model for automatically determining the locations of layers, given the slab height, material types and part geometry. Layers are chosen such that it will avoid catastrophic failures and poor machining conditions in general. First, features that are possible thin material machining positions are defined, and methods for detecting these feature positions from an STL model are studied. Next, a layer thickness calculation model is presented according to positions of these features. The second area focuses on tools and parameters for the subtractive side of processing each layer. A tool size and machining parameter selection model is presented that can automatically select tool sizes and machining parameters, given layer thickness, part geometry, and material types. Machining strategies and related machining parameters are studied first. Then the method for Stepdown parameter calculation is presented. Finally, an algorithm based on both accessibility and machining efficiency is proposed for the selection of tool sizes for the rough cutting operation, finish cutting operation and optional semi-rough cutting operation. The final research area focuses on a cutting force analysis for thin material machining with additional layer thickness & tool size interaction. Popular cutting force models are reviewed, and a suitable model for cutting force calculation in this process is evaluated. Then, a cantilever beam model is used to analyze the thin material machining failure problem, and a minimum layer thickness model is presented. Third, a combined layer thickness & tool size model is constructed based on the machining tool deflection under cutting forces. This rapid pattern manufacturing process and related software has been implemented, and experimental data is presented to illustrate the efficacy of this system and its process planning methods