“Product Templates” A Parametric Approach to Mass Customization

Design changes are frequently encountered in the product development process. The complexity of the design changes is multiplied when the product design involves multiple engineering disciplines. Very often, a simple change in one part may propagate to its neighboring parts, therefore, affects the entire product assembly. Both parts and assembly must be regenerated for a physically valid product model, at the same time, the regenerated product model must meet designer’s expectations. When a product is being developed in a Concurrent Design and Manufacturing (CDM) environment, the design changes are usually implemented first by altering geometry of the product represented in computer-aided design (CAD) solid models. If the product solid model is not parameterized properly, the changes in geometry often lead to invalid parts or assembly. At the part level, the changes may yield a solid model with invalid geometric features if it is not properly parameterized. In this case, the entire product assembly is in vain. Even when individual parts of the product are regenerated correctly, parts may still penetrate to their neighboring parts or leave excessive gaps among them, if the solid model is not properly parameterized at the assembly level. In this paper, solid modeling and assembly techniques implemented in two major CAD tools, Pro/ENGINEER and SolidWorks, will be discussed. A set of guidelines will be proposed for the designers to parameterize the solid models in order to capture the design intents more effectively in the product virtual mockup. These guidelines at both part and assembly levels will support designers to successfully conduct product design in the CDM environment. A number of examples, including a slider-crank mechanism and its crankshaft, a single-piston airplane engine and its components, as well as a number of simpler parts are presented to illustrate and demonstrate the parameterization method and guidelines proposed for both Pro/ENGINEER and SolidWorks.

The processes applied on the pixels by the image processing methods provide us information about images. Image processing is a computer programming area which can be used in computer integrated industrial applications and it is one of the research areas of reverse engineering. In this study, a new system in which color digital images are interpreted by using image processing method was developed. The purpose of this study is to improve a system to interpret the images, which are taken with a hand camcorder or digital camera, and to obtain point clouds by evaluating with image processing and to convert these point clouds surface or solid model in a computer aided design program. In accordance with these purposes, the three dimensional point clouds are obtained from a rectangular prism shaped object in the specified area. These point clouds can easily be converted into three dimensional solid or surface models in a Computer Aided Design (CAD) program. In this reverse engineering study, the developed system is explained and sample parts are given.

At the start of my Ph.D. in 1980, I caught a glimpse, purely by chance, of the emerging field of computer-aided design (CAD). It intrigued and fascinated me to such an extent that I ended up scrapping my original plans, switching schools and changing my research area. Even though my new school, Ohio State, was one of only a handful of schools with computing facilities dedicated to CAD, I ran into stiff resistance when I expressed my desire to get a Ph.D. in CAD. I was told that CAD was hardly an intellectually challenging field worthy of a Ph.D. dissertation. I was directed to consider mainstream mechanical engineering areas, such as solid mechanics, vibrations, kinematics, and dynamics. The closest I could get to CAD was to do my dissertation in FEA, which allowed me to do at least part of my work in computing and visualization.When I began my academic career at Arizona State, I thought I was finally free to pursue my true love. But I soon realized that we were still a fringe group; faculty in traditional fields, such as thermofluids and solid mechanics, took a dim view of computational research. The proposed thesis plan for my first graduate student (Expert System for Conceptual Synthesis of Frame Structures) was rejected by the Graduate Chair, who remarked “This is not mechanical engineering.” He viewed it as purely a computer program without any regard for the fact that we needed to explicate, structure, and represent experiential knowledge for structural synthesis not found in any textbook on the subject.Of course, I was not alone in facing this predicament. Fortunately, for misfits like us there was an ASME Division that welcomed us. Originally named the Computer Engineering Division (CED), and later known as Computer & Information Engineering (CIE) Division, it was approved in 1979 and began operating in 1980. Unlike academia, industry was well aware of the potential of computing and information technologies to revolutionize product design and manufacturing. Visionaries from computer industry (CDC, IBM, DEC, Applicon), an infant software industry (SDRC, CV, Swanson), and a variety of OEMs (GM, GE, McDonnell-Douglas) led a grassroots effort to convince ASME of the importance of mechanical engineers active participation in these evolving areas through the creation of a new Division. The first CED newsletter in 1981 boldly heralds “…the dawn of an era that is certain to be dominated by computer technology. All projections indicate that mechanical engineers, more than any other professional group, will be more involved in the utilization of this (computer) technology.” They saw MEs playing as important a role in the IT revolution as their far predecessors had in the industrial revolution—a prediction that was to come true.Prof. Ali Seirig was appointed the first Chair of CED. I am in awe of the progress this new Division made in just the first two years. Twenty-four technical committees were set up and an annual conference was initiated in 1981. This conference was unique in that it was associated with an exhibition of the latest hardware and software from leading vendors. This element was critical in keeping the ASME community well informed about the current state of engineering computing. It is, therefore, not surprising to see that this Division was heavily industry dominated—21 out of 24 Technical Committee Chairs were from industry. Sadly, today industry participation in CIE has sagged. Did CIE change because industry participation diminished, or did industry reduce its participation because CIE became less relevant to their needs? We can only speculate about the reasons.CED soon became the fastest growing Division within ASME. The CED/CIE conference and exhibition attracted participants from a wide range of areas, not just CAD/CAM and FEA but kinematics, robotics, heat transfer, and fluid mechanics. This diverse community only had one thing in common, the application of computational methods to problems in their respective fields. As traditional conferences and journals gradually came around to seeing computational methods as valuable contributions in their own fields, they became more accepting of papers of this nature. Thus began the return of computational researchers back to their own discipline communities, shrinking the size of CIE conferences. Finally, in 1994, the CIE conference was colocated with Design Engineering Technical Conferences (DETC).The founders of CED debated the type of journal they needed to have. They felt that given the rapid evolution of computing technologies, an archival journal like an ASME Transactions was not appropriate. At the same time, they wanted their journal to be more technical than a trade magazine. They ended up creating a “hybrid” quarterly publication called CIME (Computers in Mechanical Engineering), with Ali Seirig as its editor. This magazine was produced in full color and was very informative about the latest developments in engineering software. In the words of the editor, CIME was “user-oriented” not “research oriented.” Unfortunately, this philosophy did not command much respect in academia and eventually CIME was merged into ASME’s monthly magazine Mechanical Engineering.And so it came to be that unlike all other ASME conferences and Divisions, CIE did not have any associated journal. Over the years, CIE leaders made several attempts at getting a Transactions journal approved, but to no avail. Reasons for rejection ranged from “computing technologies have no archival value” to the failure to sustain CIME magazine.In 2000, a small group of CIE Division “activists” decided to make another push for a journal. Yong Se Kim, David Lee, Simon Szykman, and David Rosen were the principals in this effort. They came up with a strategy based on lessons from past failures. That included building alliances with three other Divisions (Design, Manufacturing, and Systems & Controls), and demonstrating that an editorial board could be formed with well known researchers who had extensive publication records. I became aware of this effort when I received a call out of the blue, asking me the intriguing question “How would you like to be the Chief Editor of an ASME Transactions?” Of course, the very next sentence brought me down to earth quickly “…the problem is that the journal doesn’t yet exist – will you help us get it approved by ASME?” Thus began my involvement with this journal. We put together an impressive editorial board that included two NAE members and research leaders in each of our targeted areas. Phil Divitero, ASME Director of Publications, immediately saw the marketing potential of this journal, and became a key ally. Bahram Ravani, DED Chair, gave valuable advice on writing our proposal to ASME. Art Erdman, himself a CIE pioneer, happened to be the Chair of ASME Publication Committee, which had authority of approving new journals, which gave us a much needed sympathetic ear on the committee to make our case. In a café in Chicago, before our presentation, we brainstormed various names for the journal and settled on Journal of Computing & Information Science in Engineering (JCISE). The journal was approved and began publishing in the first year of the new millennium, 2001. The CIE Division finally had an archival journal of its own with three cosponsoring Divisions. In 2005, after much lobbying and deliberation, the Design Engineering Division became an equal partner with CIE—an important step in going mainstream.From the very beginning we decided to focus sharply on computational methods for mechanical product development. This set us apart from journals from private publishers that accepted everything and anything related to computing—from gaming to geology, from biology to every branch of engineering. We did not want to dilute our journal with such a wide and general scope. We stipulated that every paper submitted to JCISE must demonstrate applications of its techniques to mechanical design, mechanical analysis, product manufacturing, or quality assurance. Through several iterations we settled on eight major categories to include within the scope of our journal: solid modeling (including parametrics), computational geometry (including reverse engineering), computational metrology (including CMM and tolerance modeling), haptics and virtual reality, engineering informatics, simulation (including FEA, meshing, and optimization), AI/Knowledge based systems, and computer aided manufacturing. Given the practical nature of our field, we also decided to publish papers along two tracks: Research and Application. The latter has subcategories of Software Reviews, Technology Reviews, Tech Notes, and Industry Pilot Projects. The idea was to keep the journal relevant to industry as well as academia. We instituted a three-level rigorous review process for appointment of Associate Editors. We owe it to the founding editorial board for setting sound policies that resulted in quick recognition of JCISE as an archival publication of high quality. That group consisted of Paul Wright, David Rosen, Nick Patrikalakis, Deba Dutta, Susan Urban, Martti Mantyla, Dana Nau, S. Jayaram, Pradeep Khosla, Harry Cheng, and Ravi Rangan. Since we see ourselves as being at the intersection of computer science and mechanical engineering, it was appropriate to have about half of the AEs from each field, and we managed to do so.ACM (Association for Computing Machinery) approached us in 2001 to become an official cosponsor—an offer we gladly accepted in order to strengthen the linkage with our computer science colleagues. From 2001 to 2004, we published a special issue annually drawn from the best papers of the ACM Solid Modeling conferences. Unfortunately, this conference series became too broad, and it was difficult to accommodate their best papers in JCISE without violating our objective of serving the engineering community; this annual tradition of ACM special issues had to be discontinued.ISI included JCISE in its data collection in 2004; after 3 years of this process, the first Impact Factors for JCISE became available in 2007 (for the 2004–2006 period). With respect to ISI Impact Factors, JCISE ranks in the top third of all ASME Transactions; it is better than many long established journals in CAD/CAM and AI areas. Our Impact Factor has continued to improve each year. How meaningful are such statistics in gauging the quality of a journal is debatable. More meaningful metrics are in the offing and we hope they will supplant bean counters of today.When we opened shop in 2000, ASME did not have any web based tool for paper submission and review management. Being the journal focused on computing and information science, we refused to conduct paper reviews the old fashioned way and began developing eLane. With the help of one of our associate editors, Susan Urban, a database expert, and one of her brilliant students, Anish Shah (no relation), we designed and implemented eLane over a period of 3 years. For the past 10 years, we have hosted, maintained, and continuously improved eLane to support not only JCISE but also other journals, such as Research in Engineering Design, and CIE, DTM, and NSF Grantees conferences. eLane blazed a new trail and guided ASME to develop its own “Journal Tool.” Data security and confidentiality is a critical issue in online systems. I am particularly indebted to one of our founding associate editors, Simon Szykman, who provided valuable advice on security aspects of the system by constantly trying to enter the system through unintended holes. It is no surprise that Simon went on to become the first Director of the Cyber-Security group at US Department of Homeland Security and is now the CIO of the Department of Commerce.With Bahram Ravani taking over as the new chief editor of JCISE, we have begun the process of gradually migrating from eLane to ASME’s Journal Tool. Although the Journal Tool still lacks some functionality available in eLane, the reasons for migration are that this will provide greater visibility to JCISE through ASME websites, set JCISE at par with other Transactions, make it easier to transfer papers between ASME journals and, most importantly, have 24/7 support from ASME’s IT professionals.My tenure as chief editor is ending as it started, with a special issue providing snapshots of each of the technology areas within our scope. In both cases, I put together a wish list of papers and expert groups to co-author the state of art reviews. I had hoped to have every area covered, but some papers did not materialize this time around. Nevertheless, this special issue will be a good reference for most, if not all of the areas JCISE covers. For V1 N1, I invited each of our founding Associate Editors to write state-of-the-art surveys of their fields in collaboration with other experts in their respective areas. This special issue contains survey papers not only in some well-established CIE areas but also in a few emerging fields.Computational methods and information technologies related to engineering product development have come a long way. CAD, CAM, FEA, CFD, VR, Reverse Engineering, Computational Metrology, Optimization, and many other simulation techniques are now pervasive in industry. Even traditional fields, such as thermal science, fluid mechanics, and solid mechanics, have embraced numerical methods and computer visualization. What started on the fringes is now the mainstream. We owe it to the founders of the CED/CIE Division who saw this potential more than 30 years ago. Let us recognize Ali Seireg (Wisconsin), J. Callahan (McDonnell Douglas), V. Tipnis, T. Shoup (Santa Clara), D. Dietrich (Swanson), L. Hulbert (Battelle), E. Heer (NASA), S. Rhode (GM), R. Fulton (Georgia Tech), J.Cokonis (GE), R. Arvikar (Bell Labs), J. Lemon (SDRC), D. Riley (U. Minnesota), and R. Raghavan (Foster Wheeler).A high quality archival journal is extremely important to any research community. A conference alone cannot be sufficient. Conferences, at least in engineering, serve the purpose of quick dissemination of work in progress. Having an archival journal aids the maturation of a research community. Not all conference papers are suitable for archival in a journal. An additional complication in computing and IT is the rapid rate of development and consequent obsolescence of ideas and methods. What then should we archive? There certainly are many techniques in our field that have withstood the test of time. B-Rep solid models, B-splines, and NURBS, regularized Boolean algorithms, Attributed Adjacency Graph based feature recognition, and bipartite graphs for constraint solving are but a few examples. But most research is incremental, and it is important to archive snapshots of major milestones in each area. NURBS did not just come about suddenly. There were B-splines, rational B-splines before the idea of nonuniform knot spacing.JCISE associate editors serve 3 year terms, renewable for an additional 3. In addition to the founding group of AEs, I want to take this opportunity to thank all our current and past AEs. They are the ones that do the bulk of the work and get the credit for maintaining our high quality. I am very grateful to the following individuals: J. Michopoulos, K. Saitou, A. Goel, I. Grosse, K. Law, X. Qian, J. Oliver, S. McMains, S. Gao, A. Fischer, J. Vandenbrande, C. Geiger, Y. Kitamura, C. McMahon, A. Joneja, S. K. Gupta, R. Crawford, K. Lee, J. Corney, N. Dorighi, L. Joskowicz, and S. Callahan.I am sure that our new chief editor, Bahram Ravani, will take JCISE to new heights. My very best wishes to JCISE readers, authors, and reviewers. For me, this has been a labor of love.

PurposeThis paper aims to introduce a process chain spanning from scanned data to computer-aided engineering and further required simulations up to the subsequent production. This approach has the potential to reduce production costs and accelerate the procedure.Design/methodology/approachA parametric computer-aided design (CAD) model of the flyer wearing a wingsuit is created enabling easy changes in its posture and the wingsuit geometry. The objective is to track the influence of geometry changes in a timely manner for following simulation scenarios.FindingsAt the final stage, the two-dimensional (2D) pattern cuts were derived from the developed three-dimensional (3D) wingsuit, and the results were compared with the conventional ones used in the first stages of the wingsuit development.Originality/valueProposing a virtual development process chain is challenging; apart from the fact that the CAD construction of a wingsuit flyer – in itself posing a complicated task – is required at a very early stage of the procedure.

In this chapter, we address various issues related to data processing for rapid prototyping. In contrast to traditional material removal processes, rapid prototyping techniques build a part by incrementally adding materials layer by layer (Kruth 1991, Barequet and Kaplan 1998), so they are also called layer-based manufacturing or layered manufacturing. The processes are fully automatic and offer a number of competitive advantages over traditional manufacturing processes. Hence, they are particularly useful for rapid product development. The entire process for model prototyping is illustrated in Figure 5-1 and can be summarized as follows: CAD modeling: The first step in rapid prototyping is to prepare a computer-aided design (CAD) model of the object to be fabricated using layer based manufacturing processes. For most of the available RP technologies, a solid model with complete topological and geometric information is required. STL interfacing: STL is the de-facto standard for the rapid prototyping industry. It is a file format for approximately defining an object using triangular facets. When a CAD model is available, the entire part geometry is converted into STL format based on a tolerance for accuracy control. Part orientation: Before processing for prototyping, a RP engineer needs to figure out the specific orientation in which the prototype model will be produced. Part accuracy, the amount of supporting material required and ease of post-processing are important factors influencing part orientation determination. Support generation: Depending on the specific RP process to be used, one may need to further define support structures for supporting down-facing areas during part build-up. Support generation can be done on the basis of a STL model or the original CAD model. Model slicing and tool path generation: In contrast to material removal manufacturing technologies, rapid prototyping technologies refer to a class of layer-based material increase manufacturing processes. The digital model of the object and related support structures need to be sliced layer by layer. For each layer, a set of surface contours is obtained and a tool path is defined within the material area for model production in a layer-wise fashion. Model production on a RP machine: The produced tool path is sent to a RP machine for building up the prototype model, including support, layer by layer. Post-processing: Depending on the RP process involved, a post-processing step might be needed for post-curing in the case of stereolithography, for infiltration and furnace sintering in the case of SLS, and/or for removing the support structures and surface polishing in the cases of most other RP processes.

This paper presents an intuitive and natural gesture-based methodology for solid modelling in the Augmented Reality (AR) environment. The framework of Client/Server (C/S) is adopted to design the AR-based computer aided design (CAD) system. The method of creating random or constraints- based points using gesture recognition is developed to support modelling. In addition, a prototype system of product 3D solid modelling has been successfully developed, we have compared it with traditional CAD systems through several basic design modeling tasks. Finally, analysis of questionnaire feedback survey shows the intuitiveness and effectiveness of the system, and user studies demonstrate the advantage of helping accomplish the product early design and creating and manipulating the 3D model in the AR environment.

Data exchange between different computer-aided design (CAD) systems is a major problem inhibiting information integration in collaborative engineering environments. Existing CAD data format standards such as STEP and IGES enable geometric data exchange. However, they ignore construction history, features, constraints, and other parametric-based CAD data. As a result, they are inadequate for supporting modification, extension and other important higher-level functionality when accessing an imported CAD model from another CAD system. Achieving such higher-level functionality therefore often requires a time-consuming, error-prone, tedious process of manually recreating the model in the target CAD system. Based on techniques adapted from programming language research, this paper presents an approach to exchanging parametric data between CAD systems using formally-defined conversion semantics. We have demonstrated the utility of our approach by developing a prototype implementation that automates the conversion of 2D sketches between two popular CAD systems: Pro/ENGINEER and SolidWorks. We present examples showing that our approach is able to accurately convert parametric CAD data even in cases where models were constructed using operations from the source CAD system that have no direct counterpart in the target CAD system. Although the case study focuses on 2D interoperability, our approach provides formal foundations for supporting 3D and semantic interoperability between CAD systems.

Chapter 3 - Computational domains

Feature recognition is the key to the computer-aided design (CAD) and computer-aided manufacturing (CAM) integration to build a computer-integrated manufacturing system. There are two approaches to CAD feature recognition: platform-dependent and platform-independent. In the platform-independent approach, the part’s geometrical data are extracted from a neutral file such as DXF, IGES, or STEP. In contrast, the platform-dependent approach extracts the information of the design features directly from a design-by-feature solid model through the object-oriented model of a part. This paper explains a platform-dependent approach which is implemented to translate design features into manufacturing information. This approach begins with simplification using the suppression of fillets, and clustering non-intersecting design features is done. Then, the rule-based method is employed in order to recognize machining features. Finally, the needed manufacturing information such as tool accessing direction, dimensions, material removal regions, and geometrical and topological data is recognized. The application of the proposed system would be exhibited in generating machine path code for rapid prototyping and CNC machines and providing a database for computer-aided process planning. The proposed system was implemented on Autodesk Inventor and successfully tested for many complex 3D models.

Switching Functions Based Geometric Modeling Language and its Application to Numerical Control Program Verification

In order to face the competition, traditional manufacturing companies are required to digitise the products by applying computer-aided design (CAD) for infusing innovative features in them. In the context of this realisation, a case study on digitising a traditional product by name 'desiccant compressed air dryer' (DCAR) by applying CAD technology which is presented in this paper was carried out. The procedures adopted to create the CAD models of six subassemblies of DCAR and its assembly by using a CAD software package namely Creo Parametric 2.0 are described. Then the advantage of digitising the traditional products using the CAD technology is described. The article is concluded by stating that utilising this kind of facilities that are available in CAD software packages will enable traditional manufacturing companies to become agile by quickly adding amazing features that will delight the customer.

Chapter 2 - Geometric Modeling

A case is made that introducing CAD-based geometry prematurely in the aircraft design process actually hinders multidisciplinary design. Consequently, a design process which allows a designer to quickly build and analyze aerospace configurations without CAD or computational meshing specialists is proposed. This allows higher fidelity analyses to be applied at conceptual design and decreases the turnaround time for trade studies and optimizations. The basic premise of conceptual geometry modeling is presented and discussed. Key features and capabilities which are essential for a successful geometry modeler are identified. Desktop Aeronautics' conceptual geometry modeler, RAGE, is described, with emphasis on recent progress and advances in the tool. A preliminary graphical-user-interface is presented along with an application programming interface. Extensibility of the RAGE modeler is discussed along with the importance of this feature. The applicability of RAGE to simple trade studies is demonstrated in an example problem. The precision of the RAGE modeler is also demonstrated on a complex aircraft design. Future plans for the geometry modeler are also discussed. I. Background In the conceptual phase of aircraft design, there is often a wide range of geometric configurations that the designer wishes to consider, analyze, and assess. A designer’s intuition and creativity are crucial to a successful conceptual design, yet are easily inhibited by the modeling and analysis process itself, particularly if high-fidelity analysis is warranted. If the time between inception and assessment of a candidate design is relatively long, a designer may be forced to limit the number of concepts considered. New data revealed in a design iteration may suggest or require significant changes to the geometry configuration. Since the majority of considered design configurations will eventually be discarded, an ideal conceptual design process should involve a highly efficient and easy to use geometry modeler. Significant changes should be allowed without tedious re-work of the geometry model. Exporting the model for analysis should require little effort and have the capability to be automated. Therefore, any modeling application used in this process should be flexible and not restrict the designer’s choice of user interface, analysis method, and design optimization environment. Most current design processes in the aerospace industry rely heavily on computer-aided-design (CAD) applications. As a general design tool, CAD is a powerful geometry modeler capable of precisely representing practically any shape. Unfortunately, this generality is realized at the cost of requiring specialized training to efficiently and effectively use the software. Also, a CAD model is often not easily modified, especially if significant re-work of the geometry is necessary. This can lead to the premature freeze of an aircraft design due to employing excessively high-fidelity geometry modeling too early in the design process. Parametric CAD modeling could address this issue, but creating a well-designed parametric CAD model is difficult. Not only does it require an extremely skilled operator, but also the designer must have some insight into what parameterization may ultimately be desired. Modifying a parametric CAD model is often more difficult than modifying a conventional CAD model. Significant changes, such as adding or removing cross-sections, may invalidate the parameterization in some cases. In most organizations, CAD modeling (whether it be parametric or conventional) is often assigned to a dedicated CAD specialist. Since the conceptual designer is usually not a CAD specialist, the latter must communicate his design intent to the former, often using sketches, dimensions, and word of mouth. When the CAD specialist interprets the sketches, any part or detail not precisely defined usually requires judgment and artistic license. This interpretation may result in loss of design intent and indeterminate iteration between the CAD specialist and designer to obtain a satisfactory result. Because this process is iterative, CAD operators often must recreate similar geometry

This paper describes a structural design system for 3D drawing dies based on functional features using a minimum set of initial information. In addition, it is also applicable to assign the functional features flexibly before accomplishing the design of a solid model for the main parts of a drawing die, such as upper die, lower die, and blank holder. The initial information includes blank sizes, work strokes, die faces, punch open lines, and press data. The proposed system integrated the design knowledge of drawing die into functions of 3D computer-aided design (CAD) software to automate design and to shorten design time. This design system is constructed on a PC and integrated with a Pro/ENGINEER CAD system including feature selector, shape calculator, model generator, design coordinator, and user interface. The proposed system is demonstrated using the example of designing a drawing die for the roof panel of a vehicle within 1 h. The results reveal that it can dramatically improve the design quality and can save both time and costs with excellent design quality.

Abstractα/β type titanium alloys, such as Ti-6Al-4V and Ti-6Al-7Nb, have been used for orthopedic implant materials because of their combination of biocompatibility, corrosion resistance and mechanical properties. However, toxicity of alloying elements is a concern.In this project, it is proposed to design the new type of titanium alloys composed of non-toxic elements, such as Ti, Al, and Fe with lower modulus of elasticity and greater corrosion resistance. To find the optimal ratio of components in the Ti-Al-Fe system is important. The composition of the alloy determines its properties. Using combinatorial approach the optimal ratio can be found relatively easily.Direct metal deposition (DMD) is a novel precise manufacturing process for fabricating metal parts directly from Computer Aided Design (CAD) solid models. The DMD process allows making several layers of different composition on one substrate. One sample includes several Ti-xAl-yFe alloys at once. This combinatorial library dramatically reduces the time and cost of the investigation.The structure, mechanical and electrochemical properties of each new composition was studied using scanning electron microscopy (SEM) with energy-dispersive X-ray fluorescence analyzer (EDAX ZAF®), and electrochemical polarization method.