Development and application of new composite materials as EDM electrodes manufactured via selective laser sintering

The cost of a part manufactured by electrical dischargeEDM machining (EDM) is mainly determined by electrode cost. The production of electrodes by conventional machining processes is complex, time consuming, and can account for over 50 % of the total EDM process costs. The emerging additive manufacturing (AM) technologies provide the possibility of direct fabrication of EDM electrodes. Selective laser sintering (SLS) is an alternative AM technique because it has the possibility to directly produce functional components, reducing the tool-room lead time and total EDM costs. The main difficulty of manufacturing an EDM electrode using SLS is the selection of an appropriate material, once both processes require different material properties. The current work focused on the investigation of appropriate materials that fulfill EDM and SLS process demands. Three new metal-matrix materials composed of Mo–CuNi, TiB₂–CuNi, and ZrB₂–CuNi were developed and characterized. Electrodes under adequate SLS conditions were manufactured through a systematic methodology. EDM experiments using different discharge energies were carried out, and the performance evaluated in terms of material removal rate and volumetric relative wear. The results showed that the powder systems composed of Mo–CuNi, TiB₂–CuNi, and ZrB₂–CuNi revealed to be successfully processed by SLS, and the EDM experiments demonstrated that the new composite electrodes are promising materials. The work also suggests important topics for future research work on this field.     

Design of a neuro-fuzzy–regression expert system to estimate cost in a flexible jobshop automated manufacturing system

We propose a cost estimation model based on a fuzzy rule backpropagation network, configuring the rules to estimate the cost under uncertainty. A multiple linear regression analysis is applied to analyze the rules and identify the effective rules for cost estimation. Then, using a dynamic programming approach, we determine the optimal path of the manufacturing network. Finally, an application of this model is illustrated through a numerical example showing the effectiveness of the proposed model for solving the cost estimation problem under uncertainty.     

Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective decision making

Selective laser melting (SLM) is a unique additive manufacturing (AM) category that can be used to manufacture mechanical parts. It has been widely used in aerospace and automotive using metal or alloy powder. The build orientation is crucial in AM because it affects the as-built part, including its part accuracy, surface roughness, support structure, and build time and cost. A mechanical part is usually composed of multiple surface features. The surface features carry the production and design knowledge, which can be utilized in SLM fabrication. This study proposes a method to determine the build orientation of multi-feature mechanical parts (MFMPs) in SLM. First, the surface features of an MFMP are recognized and grouped for formulating the particular optimization objectives. Second, the estimation models of involved optimization objectives are established, and a set of alternative build orientations (ABOs) is further obtained by many-objective optimization. Lastly, a multi-objective decision making method integrated by the technique for order of preference by similarity to the ideal solution and cosine similarity measure is presented to select an optimal build orientation from those ABOs. The weights of the feature groups and considered objectives are achieved by a fuzzy analytical hierarchy process. Two case studies are reported to validate the proposed method with numerical results, and the effectiveness comparison is presented. Physical manufacturing is conducted to prove the performance of the proposed method. The measured average sampling surface roughness of the most crucial feature of the bracket in the original orientation and the orientations obtained by the weighted sum model and the proposed method are 15.82, 10.84, and 10.62 μm, respectively. The numerical and physical validation results demonstrate that the proposed method is desirable to determine the build orientations of MFMPs with competitive results in SLM.     

Material bead deposition with 2 + 2 ½ multi-axis machining process planning strategies with virtual verification for extruded geometry

Process planning for hybrid manufacturing, where additive operations can be interlaced with machining operations, is in its infancy. New plastic- and metal-based hybrid manufacturing systems are being developed that integrate both additive manufacturing (AM) and subtractive (machining) operations. This introduces new process planning challenges. The focus of this research is to explore process planning solution approaches when using a hybrid manufacturing approach. Concepts such as localized AM build ups, adding stock to a CAD model or section for subsequent removal, and machining an AM stock model are investigated and illustrated using virtual simulations. A case study using a hybrid laser cladding process is used to demonstrate the opportunities associated with a hybrid solution. However, unlike machining, the process characteristics from system to system vary greatly. These are portrayed via a high power, high material deposition feed rate laser cladding system. There are unique challenges associated with AM processes and hybrid manufacturing. New tools and design rules need to be developed for this manufacturing solution to reach its potential.     

Producer’s behavior analysis in an uncertain bicriteria AGV-based flexible jobshop manufacturing system with expert system

Here, an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost is proposed. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An automated guided vehicle functions as a material handling device through the manufacturing network. To account for uncertainty, time is considered to be a triangular fuzzy number and apply an expert system to infer the cost. The expert system based on fuzzy rule backpropagation network to configure the rules for estimating the cost under uncertainty is proposed. A multiple linear regression model is applied to analyze the rules and find the effective rules for cost estimation. The objective is to find a path minimizing an aggregate weighted unscaled time and cost criteria. A fuzzy dynamic programming approach is presented for computing a shortest path in the network. Then, a comprehensive economic and reliability analysis is worked out on the obtained paths to find the optimal producer’s behavior. Finally, an application of the model is illustrated by a numerical example. The results show the effectiveness of our approach for finding an optimal path in a manufacturing system under uncertainty.     

Towards selective laser sintering of objects with customized mechanical properties based on ANFIS predictions

Recently, the adaptive network-based fuzzy inference system (ANFIS) has been used extensively in modeling of manufacturing processes to save both optimization time and manufacturing costs. ANFIS is a powerful iterative tool for optimizing non-linear and multivariable manufacturing operations. In the present study, ANFIS is used to predict the optimum manufacturing parameters in selective laser sintering (SLS) of cement-filled polyamide 12 (PA12) composite. For this purpose, a set of cement-filled PA12 test specimens is manufactured by SLS technique with 8 different values of laser power (4.5–8 Watt) and 8 different weight fractions of white cement (5 %–40 %). Mechanical characterization of cement-filled PA12 is carried out to evaluate the ultimate tensile strength (UTS), compressive strength, and flexural properties. The experimental data are then divided into two groups; one group for training the ANFIS model and the other group for checking the validity of the identified model. The built ANFIS model was validated experimentally and comparison with experimental results revealed mean relative errors of 2.92 %, 3.84 %, 4.75 %, and 3.31 % in the predictions of UTS, compressive strength, flexural modulus, and flexural yield strength, respectively.

     

Development and application of copper–nickel zirconium diboride as EDM electrodes manufactured by selective laser sintering

The production of electrical discharge machining (EDM) electrodes by conventional machining processes can account for over 50 % of the total EDM process costs. The emerging additive manufacturing (AM) technologies provide the possibility of direct fabrication of EDM electrodes. Selective laser sintering (SLS) is an alternative AM technique because it has the possibility to reduce the tool-room lead time and total EDM costs. The main difficulty of manufacturing an EDM electrode using SLS is the selection of an appropriate material. This work investigated the direct production of EDM electrodes by means of the SLS using a newly developed non-conventional metal–matrix composite material composed of a metallic matrix (CuNi) and an advanced ceramic (ZrB₂). The influence of important SLS parameters and material content on the densification behavior and porosity of the electrodes was investigated. EDM experiments were conducted to observe the electrodes behavior and performance. It was found that the ZrB₂-CuNi electrodes could be successfully manufactured by SLS. Interlayer bonding and porosity are directly influenced by the layer thickness. Smaller layer thicknesses improved bonding between layers and decreased the porosity of the parts. The laser scan speed has a significant effect on the densification behavior. The scan line spacing affects the pore structure by means of overlapping. The surface morphology of the samples was not affected by varying the scan line spacing. The ZrB₂-CuNi electrodes presented a much superior performance than SLS copper powder electrodes, but inferior to solid copper electrodes.     

Surface accuracy optimization of mechanical parts with multiple circular holes for additive manufacturing based on triangular fuzzy number

Surface accuracy directly affects the surface quality and performance of mechanical parts. Circular hole, especially spatial non-planar hole set is the typical feature and working surface of mechanical parts. Compared with traditional machining methods, additive manufacturing (AM) technology can decrease the surface accuracy errors of circular holes during fabrication. However, an accuracy error may still exist on the surface of circular holes fabricated by AM due to the influence of staircase effect. This study proposes a surface accuracy optimization approach for mechanical parts with multiple circular holes for AM based on triangular fuzzy number (TFN). First, the feature lines on the manifold mesh are extracted using the dihedral angle method and normal tensor voting to detect the circular holes. Second, the optimal AM part build orientation is determined using the genetic algorithm to optimize the surface accuracy of the circular holes by minimizing the weighted volumetric error of the part. Third, the corresponding weights of the circular holes are calculated with the TFN analytic hierarchy process in accordance with the surface accuracy requirements. Lastly, an improved adaptive slicing algorithm is utilized to reduce the entire build time while maintaining the forming surface accuracy of the circular holes using digital twins via virtual printing. The effectiveness of the proposed approach is experimentally validated using two mechanical models.     

Cost estimation system of dies manufacturing based on the complex machining features

Part manufacturing estimation cost is a critical and important task for industrial firms. Price evaluation helps the enterprise occupy a successful competitiveness in the market. In fact there are three main approaches for the manufacturing cost evaluation the analytic approach, the analogic approach and the parametric approach. This paper presents a cost estimation system of manufacturing dies based on a semi-analytic approach. The developed system uses a semi-analytic approach based on the principle of the analogic approach and analytic approach. This principle has recourse to the analogic approach to search for analogies between the shapes to be machined before grouping them into complex machining features [1]. For each feature parameter the system generates a process to be used as a sample and consequently a model of machining time. In a second stage and by using the analytic approach, the cutting time is determined either by removal rates of metal units for rough operation (cm³/min) or from the finishing operation surface (cm²/min) or by both production ways [1]. The after cutting return time is calculated through the equations developed for each machining type [2].     

Vehicle requirements model for automated guided vehicle systems

A simulation-based cost model is presented for determining the number of automated guided vehicles (AGVs) needed to meet the material handling requirements in a manufacturing system. The estimation of the number of vehicles is based on the sum of the idle-time costs of vehicles and machines, and the cost of waiting time of parts. While an increase in the number of vehicles reduces the waiting time of parts and the idle time of machines, it increases the idle time of vehicles. The application is illustrated using a hypothetical manufacturing system.     

The design of a semi-additive manufacturing shape using metal 3D printing for a partially strengthened mold based on a high-alloy tool steel powder

In this paper, describe the fabrication of high strength punch molds that can be applied to ultra-high strength sheet materials after processing. A method for improving the strength of the punching die by additive manufacturing (AM) of a high strength powder material using a metal 3D printer was proposed. Furthermore, a semi-additive technique was proposed to increase the punch strength through partial AM of specific parts of the punch that require high strength. A preprocessing process for predicting the semi-additive shape for the punch function portion is proposed for application of the AM technology of a metal 3D printer to this semi-additive technique. The preprocessing for determining the semi-additive shape consists of the predicting step of the punch strength based on the shear process of the sheet material, analyzing step the stress distribution of the punch, defining step the semi-additive range, designing step the semi-additive shape, and verifying step the additive interface strength. Based on this simulation, the range of shapes for the semi-additive was 1.21 mm and 2.62 mm for sheet material CP1180 and 1.3 mm and 3.2 mm for sheet material 22MnB5. The shape and range determined in the simulation process defines a semi-additive area (volume) for the 3D printing AM technique using a high-strength powder material, and a semi-additive punch was manufactured according to the defined area. The semi-additive punch (HWS powder material) fabricated in this study was performed a durability test for validity verification in the piercing process of high-strength sheet material (CR980). This validation test compared the state of the punch after 1000 piercing processes with a typical cold piercing punch (SKD11 solid material). From this test, the feasibility of the semi-additive punch was confirmed by showing a similar state of scratches and abrasion from the two punches. The simulation analysis processor for the additive shape and the additive range prediction for the semi-additive punch manufacturing presented in this paper can be useful for the additive manufacture of cutting and trimming punch mold.

     

An Intelligent Knowledge-Based System for Product Cost Modelling

An intelligent knowledge-based system for product cost modellingis presented in this paper. The developed system has the capability of selecting a material, as well as machining processes and parameters based on a set of design and production parameters; and of estimating the product cost throughout the entire product development cycle including assembly cost. The proposed system is applied without the need for detailed design information, so that it can be used at an early design stage, and, consequently, redesign cost and longer lead time can be avoided. Hybrid knowledge representation techniques, such as production rules, frame and object oriented are employed to represent manufacturing knowledge. Fuzzy logic-based knowledge representation is applied to deal with uncertainty in the knowledge of cost model to generate reliable cost estimation. This paper deals with cost modelling of both a machining component and an injection moulding component, which is a process that gives high production rates, excellent quality and accuracy of products, and low manufacturing cost. Based on the analysis of the moulded product life cycle, a computer-based cost model was developed which integrated the relationship between cost factors, product development activities, and product geometry. The estimated cost included the costs of material, mould and processing. The system has been validated through a case study.     

A methodology for precision additive manufacturing through compensation

Maturation of powder-bed additive manufacturing (AM) is essential for the business benefit the rapid adoption of AM offers to industry. One of the principal challenges in powder-bed AM is the mitigation of distortion due to material shrinkage and residual stresses induced during the build process. In order to address this, a new methodology for distortion compensation is developed and presented in this paper. The novelty of the methodology lies in the use of a mathematical model for pre-distorting the design geometry based on 3D optical scanning measurement data. The methodology has been applied to two industrial Inconel 718 components (a turbine blade and an impeller). It was experimentally demonstrated that distortion compensation is achievable using the proposed methodology. The results showed the compensation methodology reduced distortion from approximately ±300 μm to approximately ±65 μm for both components. In summary, the novel methodology can be used to deliver near-zero distorted parts for industry using powder-bed AM processes.     

基于模糊理论的产品成本估算模型的研究

分析了新产品和已有产品在功能结构上的相似性，根据已有产品的信息建立了产品成本样本库，引入模糊系统理论中贴近度和隶属函数等概念，结合基于专家知识经验创建产品特征模糊集合，提出了适用于不同设计阶段的成本估算模型。通过模糊映射机制挖掘产品后继设计阶段的产品功能结构的详细信息，探讨了减少成本估算误差的措施。介绍实现成本估算模型的框架流程，以齿轮减速箱为例进行了说明．     

3D printed tooling for vacuum-assisted resin transfer moulding

Three-dimensional printing (3DP) is widely considered to be one of the low-cost additive manufacturing (AM) processes. In this paper, the suitability of 3DP for making tooling for the vacuum-assisted resin transfer moulding (VARTM) process is considered. This combination has potential advantages, since VARTM has significant prototyping benefits if it can be combined with a fast and low cost tooling option. This paper presents a new process chain for the manufacture of closed mould composite parts using the VARTM process. It will be shown that 3DP tooling is significantly less accurate than CNC machined tooling, but there is a cost and time advantage to making tooling with 3DP. The mould life is also limited to typically 15 to 30 parts since significant wear occurs in the manufacturing process. Quantitative data are presented to show the effect of treating the mould surface to improve the surface roughness and to determine the mould life. An aspect often lacking in AM research is cost estimation. Here, the first cost model for rapid tooling for VARTM using 3DP moulds is presented and compared to actual results. It is shown that the model is suitable for design for manufacture analysis.     

Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data

The aim of this paper is to present a comprehensive methodology for evaluation and selection of advanced manufacturing technologies, incorporating both the economic and strategic aspects and the related imprecise as well as exact data into the decision making process. Initially, a data envelopment analysis (DEA) model that can take into account crisp, ordinal, and fuzzy data is introduced. Then, the developed framework is used for flexible manufacturing system (FMS) selection. The DEA approach is performed by employing capital and operating cost, required floor space and work-in-process (WIP) as the input variables, and using product flexibility, quality improvement and lead time reduction as the output variables. The assessment of FMS alternatives versus product flexibility and quality improvement are represented via ordinal data, while WIP and lead time reduction are stated using triangular fuzzy numbers. The proposed framework is illustrated through an application and comparative results are presented.     

Empirical investigation of environmental characteristic of 3-D additive manufacturing process based on slice thickness and part orientation

The significant amount of research has been done in improving the mechanical properties (compressive strength), dimensional accuracy (length, height and width), and build time of the components manufactured from the additive manufacturing process. In contrast to this, the research in the optimization of environmental characteristic i.e. energy consumption for the additive manufacturing processes such as selective laser sintering (SLS), and selective laser melting (SLM) needs significant attention. These processes intakes the significant portion of input laser energy for driving the laser system, heating system and other machine components. With world moving towards globalization of additive manufacturing processes, the optimization of laser energy consumption thus become a necessity from productivity and as well as an environmental perspective. Therefore, the present work performs the empirical investigation by proposing the optimization framework in modelling of laser energy consumption of the SLS process. The experimental procedure involves the computation of energy consumption by measuring the total area of sintering. The optimization framework when applied on the experimental data generates the functional expression for laser energy consumption which suggests that the slice thickness is a vital parameter in optimizing it. The implications arising from the study is discussed.     

Economics of additive manufacturing for end-usable metal parts

Additive manufacturing (AM) of metal parts combined with part redesign has a positive repercussion on cost saving. In fact, a remarkable cost reduction can be obtained if the component shape is modified to exploit AM potentialities. This paper deals with the evaluation of the production volume for which AM techniques result competitive with respect to conventional processes for the production of end-usable metal parts. For this purpose, a comparison between two different technologies for metal part fabrication, the traditional high-pressure die-casting and the direct metal laser sintering additive technique, is done with consideration of both the geometric possibilities of AM and the economic point of view. A design for additive manufacturing approach is adopted. Costs models of both processes are identified and then applied to an aeronautical component selected as case study. This research evidences that currently additive techniques can be economically convenient and competitive to traditional processes for small to medium batch production of metal parts.     

Determination of manufacturing technologies based on business strategies

This paper presents a new practical approach in relating manufacturing strategies to the choice of technologies. The methodology developed in this paper is based on possibilistic linear regression of fuzzy data sets^1–8. An example is shown for evaluating the technologies based on the given manufacturing strategies. This model, unlike most justification models which are based on cost alone, provides a framework for evaluation of the most suited technologies to fulfil the manufacturing strategies.     

Research on Injection Mould Intelligent Cost Estimation System and Key Technologies

The manufacturing cost of injection-moulded parts is mainly decided by the cost of the injection mould. Thus if we can ascertain the cost of the injection mould as early as possible, it will be a great contribution to an injection mould cost evaluation system and research on the economics of injected part manufacture. In this paper, related work on injection mould cost estimation has been discussed. A case-based reasoning (CBR) approach is used for evaluating the manufacturing cost of injection moulds. Case indexing, neural network-based case retrieval, knowledge-abundant case-adaptation and knowledge-absent case-adaptation strategies, and case learning are all considered. A comprehensive cost model including mould manufacturing costs, tax costs and general administrative costs is also discussed. The model is valuable for the price estimation of injection moulds. The application of the system is illustrated with an example.