Manufacturing Process Design Research Articles

Structure-property-processing relationships in extruded liquid crystal polymer film

Liquid crystal polymers (LCPs) derive favorable mechanical, chemical, and electrical behavior from long-range molecular ordering. The microstructure gives rise to anisotropic bulk properties that are problematic for industrial applications, and thus the ability to model the polymer directionality is essential to the design of isotropic material manufacturing processes. This investigation proposes a modeling methodology to simulate the 3D director field in full-scale film extrusion geometries. Wide-angle x-ray scattering (WAXS) is used to validate the predicted orientation for a standard coat-hanger die, and is compared with macroscopic mechanical, thermal, and dielectric testing of LCP film to illustrate the morphological dependence of the polymer properties. The highly anisotropic orientation state resulting from cast film extrusion is both predicted by the model and confirmed experimentally, and this preferred orientation is shown to correlate with observed anisotropy in the bulk properties. Additionally, a practical implementation of the modeling tool is presented to simulate directionality in two alternative die geometries designed to improve bulk isotropy, and it is demonstrated that the model is capable of simulating the resulting order for large, irregular domains typical of industrial processing.

Optimal Design of Hot-Dip Galvanized DP Steels via Artificial Neural Networks and Multi-Objective Genetic Optimization

This modeling and optimization study applies a non-linear back-propagation artificial neural network, commonly denoted as BPNN, to model the most important mechanical properties such as yield strength (YS), ultimate tensile strength (UTS) and elongation at fracture (EL) during the experimental processing of hot-dip galvanized dual-phase (GDP) steels. Once the non-linear BPNN is properly trained, the most important variables of the continuous galvanizing process, including initial/first cooling rate (CR1), holding time at the galvanizing temperature of 460 °C (tg) and the final/second cooling rate (CR2), are obtained in an optimal way using an evolutionary approach. The experimental development of GDP steels in continuous processing lines with outstanding mechanical properties (550 < YS < 750 MPa, 1100 MPa < UTS and 10% < EL) is possible by using a combined hybrid approach based in BPNN and multi-objective genetic algorithm (GA). The proposed computational method is applied to the specific design of an actual manufacturing process for the first time.

Manufacturing process design of high-pressure graphite-blasting for mechanical production of turbostratic graphene

In this paper a manufacturing process is introduced to treat the bulk surfaces of surfaces via graphite powder blasting to directly produce an adherent layer of graphene. Subsequently, the study aims to correlate optical, thermal and electrochemical modifications with treatment parameters such as blasting pressure, nozzle distance and number of passes. After the treatment, the target surface has enhanced spectral, thermal and electrochemical properties because of the graphene’s turbostratic nature to adhesion to its surface. The thermal stability performance showed a consistent 5% increase relative to a bare aluminum substrate. A two-fold increase in corrosion resistance is seen in the sample compared to bare aluminum while diffuse absorbance values enhancement is around three-fold. This proposed manufacturing method provides straightforward and effective treatment at various degrees of automation. Since the deposited graphene substrate can cover a large area, it can be applied as a final layer on thermal collectors, PV panels and for other applications. It is possible to adopt this process to other well-established treatment plants without requiring high investments in the overhead expenses.

Mathematical and Trade Based Optimization : "Synthetic" Method and Three Industrial Cases

The linear process of design-engineeringmanufacturing is nowadays obsolete. Even DFX (Design For X) methodologies are often replaced by Simulation for XFD (X being also Design) approaches. Optimization is also often applied before design. For instance, engineering design optimization of mechanical structures is nowadays essential in the mechanical industry (automotive, aeronautics ...). But optimizing mechanical structures cannot be efficient without taking in account other phases of the design-manufacturing process. In some cases, optimization is only based on trade kwnowledge. Engineers must then design parts or assemblies that are a better compromise, between mechanical and functional performance, weight, manufacturing costs etc. In this paper, after giving an overview on the different disciplines in design optimization of mechanical structures, we propose some trends to take into account the trade knowledge in the optimization/design phases. We propose an integrated approach to optimization in a functional design process with a methodological point of view. We present three different industrial cases of optimization on three examples : one in mechanical structures optimization, on based only on trade knowledge and the third mixing calculus and knowledge

Implementation and validation of true material constitutive model for accurate modeling of thick-walled cylinder swage autofrettage

The fatigue life prediction and associated fail-safe design of autofrettaged tubes require accurate stress modeling of each specific high-strength thick-walled cylinder during and after the autofrettage process, which depends largely on the elastoplastic behavior of the original steel tubes. However, the complex material behavior is dominated by the Bauschinger effect. Modeling swage autofrettage of such steel tubes remains problematic. This is a crucial issue that has not been resolved by any available modeling software. Therefore, the modeling and design of the autofrettage process for current and future materials depends upon extending the capability of current software.This research aims to develop a user-programmable function (UPF), USERMAT, to realize a user-defined material model that features true material constitutive behavior with the corresponding algorithms for accurate stress analysis of high strength thick-walled cylinders during the autofrettage process. The material constitutive model to be implemented can be formulated with high accuracy via an available material characterization, which can adapt to both nonlinear and linear strain hardening during the initial tensile loading, while the elastic modulus can be reduced during reversed-loading. It also incorporates the Bauschinger effect as a function of the prior tensile plastic strain during the nonlinear compressive reversed-loading phase and fits the experimental data of the true material model. Swage autofrettaged thick-walled cylinder case studies were reported. The results for residual radial and hoop stress and for elastic strain components were compared with independent, available neutron diffraction measurements, and they are in good agreement. Developing and integrating such a UPF into a standard finite element analysis software package is potentially the most significant unsolved fundamental modeling issue relating to re-yielding, fracture and fatigue of modern autofrettaged cylinders and pressure vessels. It can not only provide a fundamental understanding of the deformation mechanism and stress development within the high strength steel tubes during the autofrettage process, but also provide guidance for the design and optimization of the autofrettage manufacturing processes and of material selection for high intensity pressure vessels, a potential market of billions of dollars.

A process knowledge representation approach for decision support in design of complex engineered systems

Process knowledge is of considerable significance to the digitalization and intelligentization of the manufacturing industry. Current research on the process knowledge representation of decision-making in engineering design has predominantly focused on either mathematical models of individual decisions at the micro-level or organizational models of group decision consensus at the macro-level. However, the management of complexity and uncertainty in the model-based realization of engineered systems is critical to achieving rational, comprehensive, and robust decisions, especially in terms of knowledge-intensive design. The efficiency and effectiveness of decisions in system design are intrinsically linked to the process, knowledge, and system concepts involved, necessitating a more flexible and systematic decision process representation scheme that supports both the management of complexity and uncertainty. Hence, in this paper, we propose a decision-centric design process representation scheme named the Phase-Event-Information X (PEI-X) diagram and its corresponding systematic design guidance method for designing decision workflows. Using the proposed method, designers have the ability to (1) model hierarchical decision processes that cover vertical and horizontal interaction patterns, and (2) exploit the synthesis of the “Formulating-Identifying-Reusing-Exploring” iterative process to extend the understanding and prediction of decision process behaviors in design. We achieve the aforesaid abilities through the implementation of a knowledge-based design guidance system for collaborative decision support and we demonstrate the efficacy by adopting a specific multi-stage manufacturing process design problem, hot rod rolling system design, and carry out an integrated design of materials, products, and related manufacturing processes.

Clinical outcomes and costs of conventional and digital complete dentures in a university clinic: A retrospective study

Statement of problemScientific data analyzing the clinical outcomes and costs of complete dentures fabricated by using conventional and computer-aided design and computer-aided manufacturing (CAD-CAM) processes are lacking. PurposeThe purpose of this retrospective study was to compare the treatment duration, financial costs, and postdelivery adjustments of CAD-CAM and conventional removable complete dentures. Material and methodsThirty-two edentulous participants (16 women, 16 men; age 35-85 years) who had received either CAD-CAM (n=16) or conventional (n=16) maxillary and mandibular removable complete dentures provided by prosthodontists with a minimum of 2 years of experience were evaluated. The CAD-CAM denture systems were either DDS-AV (AvaDent Digital Dental Solutions) (n=11) or DD-IV (Wieland Digital Denture) (n=5). The total treatment period (days) was recorded at 3 different time points (T0: preliminary alginate impression; T1: denture delivery; T2: last scheduled postdelivery adjustment). Adjustments during the follow-up (after T2) were noted and included the removal of areas of excessive pressure, relining, or repairs. The costs of the dental treatment and the laboratory fees were calculated. The Wilcoxon rank sum tests were used for statistical analysis (α=.05). ResultsNo statistically significant difference regarding the treatment duration between digitally and conventionally fabricated removable complete dentures was found: T0-T1 (P=.889); T1-T2 (P=.675); T2- T3 (P=.978). No significant difference was found in the number adjustments for areas of excessive pressure, relines, or repairs (P=.757, P=1.000, P=1.000) during the period. Laboratory costs of CAD-CAM removable complete dentures were significantly lower than those of conventional removable complete dentures (P<.001), but clinical fees were similar between groups (P=.596), resulting in a reduction in the overall total costs for the CAD-CAM removable complete dentures (P=.011). Regarding the number of clinical visits, neither the group (conventional/CAD-CAM (P=.945)/DDS-AV/DD-IV [P=.848]) nor the interaction group (conventional/CAD-CAM and DDS-AV/DD-IV)/period (P=.084/P=.171) showed any significant differences. ConclusionsCAD-CAM removable complete dentures can be considered a viable alternative to conventional removable complete dentures regarding treatment duration, clinical and follow-up visits, adjustments, and maintenance requirements.

적층제조설계기법을 이용한 위성용 경량화 전개장치 구조물 개발

Additive manufacturing technology in metals allows for the design and fabrication of integrated satellite structures that reduce part counts and improve performance. This paper, proposes the application of the design for additive manufacturing (DfAM) process in the space environment. The small lightweight deployment mechanism structure was investigated for the strength and stiffness performance. The weight reduction was maximized through shape optimization by applying a topology optimization technique. In addition, a validation of the deployment mechanism structure design was confirmed under strength and vibration conditions through structural analysis. The mechanical properties of Ti64 Grade23 were compared and evaluated by the test of specimens and products manufactured using the power bed fusion (PBF) method.

Perancangan Proses Manufaktur Mesin Kompos Cair dari Sampah Buah

Many people use rotten / unfit fruit to make liquid compost with fruit aroma to fertilize their plants, processing fruit that is not suitable for use which will be reprocessed to reduce fruit waste in anticipation of health problems, especially when rotten fruit is thrown away Careless places will cause problems for public health however, their tools are not efficient for processing the fruit because the cutting process is still using a kitchen knife so that the production of fruit which is made into liquid compost is slow in production, so a liquid compost machine from fruit waste is needed to speed up production making compost and making more production and processing faster. The purpose of this study was to design a manufacturing process based on the design drawings of a liquid compost machine from fruit waste. The method used is Design for Manufacturing and Assembly (DFMA). The output of this method is a Standard Operational Procedure (SOP) document and an Operation Process Chart (OCP). Based on the calculation results of the liquid compost machine manufacturing process design, the net estimate of manufacturing process time is 392 minutes with a total of 66 activities consisting of operation, assembly and inspection activities.

Hot Forging Process Design and Initial Billet Size Optimization for Manufacturing of the Talar Body Prosthesis by Finite Element Modeling

In hot forging industry, the process design and the billet size determination are very crucial steps because those steps directly influence both the product quality and material utilization. The purpose of this paper was to propose a technique used to design the hot forging process for the manufacturing of the talar body prosthesis. The talar body prosthesis is one of the artificial bones, which its geometry is a free form shape. In this study, the Finite Element Modeling (FEM) was used as a tool to verify the proposed design before implementation in a production line. In addition, an initial billet was determined the optimum size in the FEM by varying the mass ratio factor, the diameter, and the length. It was found that the mass ratio factor is a very useful guideline since the optimum size is quite close to the provided size from the guideline. The FEM results showed that the dimensions of the initial billet significantly affect the complete metal filling in the die cavity. Moreover, the optimum size between the diameter and length can reduce the material waste in the hot forging process of the talar body prosthesis. Finally, the experimental results of the hot forging process showed that the proposed process design with the optimum size of the initial billet is achieved in order to manufacture the talar body prosthesis and the material utilization of the new proposed process is improved from the traditional process by 2.6 times.

Additive manufacturing of polymeric scaffolds for biomimetic cell membrane engineering

Additive manufacturing based on direct laser writing two-photon polymerization facilitates the fabrication of microstructures with full 3D design freedom. Here, this fabrication technique is exploited for engineering scaffolds accurately mimicking the shape and size of three types of human cells. The human cell models employed in the study were chosen to include a range of dimensions and different identifiable features to highlight the versatility of this fabrication approach, yet other cell shapes can easily be fabricated in similar manner. The design and fabrication parameters for the additive manufacturing process were optimized to obtain polymeric scaffolds with biomimetic shapes. After fabrication, the cell scaffolds were converted to polymer-cushioned model cell membranes through layer-by-layer functionalization with a cationic polymer and a lipid bilayer. Scaffold functionalization was verified using confocal laser scanning microscopy. Polymer-cushioned model cell membranes supported on 3D scaffolds mimicking the shape of human cells are particularly suitable for membrane interaction studies where membrane curvature plays an important role. The aim of this study is to demonstrate the engineering of biomimetic cell membranes by high-resolution additive manufacturing combined with surface functionalization. The interdisciplinary approach highlights the value of additive manufacturing as technological solution for challenges encountered in biomedical studies.

Incorporating process physics phenomena in formation of digital twins: laser welding case

Manufacturing process design and implementation can benefit from the adaptation of Digital Twins. However, the explanatory power coming by physics models presents a strong contradiction with the demand of rapid decision making required for their control and optimization. In the context of laser welding applications, this work investigates three physics-based modelling methods (namely direct Stefan method, apparent heat capacity method and Enthalpy method) along with sensorial data towards the formation of a knowledge database in order to aid the development of a Digital Twin. Also, the methodology for creating such a Digital Twin is discussed incorporating the best result(s) and method(s). This Digital Twin is proved useful in optimizing the process itself but also monitoring, through selection of sensors.

CAD/CAM/CNC in Manufacturing - Current Trends in Manufacturing (System) Engineering

The Success with the application of CAD/ CAM/ CNC machine tools are at a faster rate. CAD/ CAM in manufacturing system can be obtained to make sure that the machines and people are utilized to the greatest possible extent. This paper not only gives an approach for CAD/ CAM but also show how CNC is incorporated with the manufacturing system. That is CAD/ CAM with the integration of the Computer with the CNC machine tools. Today, manufacturing Sector like Automobile, Railway, Aircraft Component requires accuracy with the application of CAD/CAM must be interfaced to achieve technology-based improvement in manufacturing and to get successive improvements in productivity and quality. CAD/ CAM interface has also been developed for the development of computer Aided process planning (CAPP) and Design for manufacturing and assembly (DFMA) techniques. These techniques allow the manufacturing function to influence the design process and to ensure that designers are aware of the effects of various design features on the ease of manufacture of a part. In this paper, we concentrate on the issues and challenges incurred in the conversion from manual process to CAD/ CAM for quick response to customers by shortening the product cycle. The success of CAD/ CAM/ CNC systems depends upon the total integration of hardware and software functions in the overall information flow. The industrial productivity must be improved and maintained to meet the challenges of global market.

A Rapid Fabrication Methodology for Payload Modules, Piloted for the Observation of Queen Honey Bees (Apis mellifera) in Microgravity

Abstract Microgravity experiment modules for living organisms have been instrumental to space research, yet their design remains complex and costly. As the private space sector enables more widely available payloads for researchers, it is increasingly necessary to design experimental modules innovatively so that they are proportionately accessible. To ease this bottleneck, we developed a rapid fabrication methodology for producing custom modules compatible with commercial payload slots. Our method creates a unified housing geometry, based on a given component layout, which is fabricated in a digital design and subtractive manufacturing process from a single lightweight foam material. This module design demonstrated a 25–50% reduction in chassis weight compared with existing models, and is extremely competitive in manufacturing time, simplicity, and cost. To demonstrate the ability to capture data on previously limited areas of space biology, we apply this methodology to create an autonomous, video-enabled module for sensing and observing queen and retinue bees aboard the Blue Origin New Shepard 11 (NS-11) suborbital flight. To explore whether spaceflight impacts queen fitness, results used high-definition visual data enabled by the module's compact build to analyze queen-worker regulation under microgravity stress (n = 2, with controls). Overall, this generalizable method for constructing experimental modules provides wider accessibility to space research and new data on honey bee behavior in microgravity.

Experimental-numerical validation of the curing reaction of snap-cure polymer systems for component families of small batch sizes and high diversity

The efficient production of component families of small batch sizes and high diversity requires numerical analyses of manufacturing processes, especially for complex shaped components made of fibre-reinforced thermosets. In the case of snap-cure systems, curing takes place in a very short time and the exothermic reaction can lead to accumulation of heat and inhomogeneous curing. In order to achieve a reliable production of composite components, a numerical analysis of the curing process is necessary. Especially the practice-oriented and timesaving determination of the thermal conditions during the curing process is essential for the industrial application. Therefore, an experimental-numerical approach to predict the curing process was presented, which includes the analytical as well as the experimental determination of numerous thermal and thermochemical material parameters and models for snap-cure thermosets. The experimentally determined material parameters and models for the description of the material and structural behaviour are validated and evaluated by numerical simulations. In addition, the developed finite element models were used for the manufacturing process design of a complex component demonstrator.

Teaching Manufacturing Processes from an Innovation Perspective

The manufacturing innovation that underlies advanced products comes about through rational, reasoned design, motivating the need for a manufacturing engineering curriculum within higher education that teaches methodologies for designing manufacturing processes. As an alternative to conventional manufacturing process courses, the authors propose learning outcomes and methods for teaching process design and innovation. Proposed learning outcomes for new process design courses include describing key relationships and directionality between product and process design functions, determining whether a component can be made with a process, selecting process sequences for products based on cost and/or environmental impact, specifying new process designs when needed, and choosing between product/process alternatives. Examples of instructional materials and approaches that are being developed to help meet these outcomes are discussed.

Automation of Maintaining a Smart Reference Book of Tool Setups for the Development of Control Programs for CNC Machine

The article is devoted to the problems of increasing the efficiency of technological preparation production through the development and implementation of an electronic database of tool setups. In the paper describes the advantages and disadvantages of the existing process for the development of NC-programs, and a methodology for automating the process of conducting tool setups, allowing to reduce the laboriousness of designing manufacturing processes for machining of parts on CNC machines. And also, the calculation results are given the economic efficiency of the project and the prospects for its development.

Infinite Approaching Superlubricity by Three-Dimensional Printed Structures.

The rapid development of three-dimensional (3D) printing technology opens great opportunities for the design of various multiscale lubrication structures. 3D printing allows high customization of arbitrary complex structures and rapid prototyping of objects, which provides an avenue to achieve effective lubrication. Current experimental observations on superlubricity are limited to atomically smooth clean surfaces, extreme operating conditions, and nano- or microscales. With the in-depth exploration of 3D printed lubrication, construction of multifunctional 3D structures with refined dimensions spanning from micronanoscale to macroscale is increasingly regarded as an important means to approach superlubricity and has aroused great scientific interest. To document recent advances in 3D printing for structural lubrication, a detailed literature review is provided. Emphasis is given on the design and lubrication performance of geometric and bioinspired lubrication structures with characteristic dimensions. The material requirements, merits, drawbacks, and representative applications of various 3D printing techniques are summarized. Potential future research trends aiming at the design strategy and manufacturing process of 3D printed lubrication structures are also highlighted.

Uncertainty assessment for measurement and simulation in selective laser melting: a case study of an aerospace part

&lt;p class="Abstract"&gt;&lt;span lang="EN-US"&gt;In this work, the additive manufacturing process selective laser melting is analysed with the aim of realising a complex piece for aerospace applications. In particular, the effect of the manufacturing process and of the following thermal treatments on the dimensions of the workpiece is evaluated. The study is based on a hybrid approach including a simulation of the whole manufacturing process by advanced software packages and the dimensional measurements of the realised pieces taken by a coordinate measuring machine (CMM). The integrated use of simulation and measurements is carried out with the aim of validating the simulation results and of identifying the operational limits of both approaches; this analysis is based on metrological evaluation of the results of both the simulation and the tests, taking into account the uncertainty of the data. In addition, the main causes of uncertainty for the simulation activity and the experimental data have been identified, and the effects of some of them have also been experimentally evaluated. Based on the experimental validation, the simulation seems to predict the absolute displacement of the supports of the piece in a satisfactory way, while it is unable, in the actual configuration, to assess the conformity of the surface to its very tight shape tolerances. Conformity assessment of the surface should be carried out by CMM measurement. Integrated use of simulation and experimental results is expected to strongly improve the accuracy of simulation results for the effective and accurate design and control of the additive manufacturing process, including dimensional control and thermal treatments to mitigate induced thermal stresses.&lt;/span&gt;&lt;/p&gt;

Quantitative risk-based inspection approach for high-energy piping using a probability distribution function and modification factor

Risk-based inspection (RBI) offers the most cost-effective operation and maintenance strategy for minimizing overall risks and making financial and safety improvements within a power plant. Risk assessment may also benefit decision-making with regards to plant design and equipment manufacturing processes. The purpose of this study is to propose a quantitative RBI methodology that can be applied to a high-energy piping system operating at elevated temperatures and high pressures in power plants. Three major steps involved are: (i) using generic mean time to failure (MTTF), specified as the expected lifetime of the equipment obtained from a theoretical equation; (ii) adding a modification factor that identifies the specific conditions that can influence the failure rate; and (iii) incorporating individual inspection locations as a factor in risk evaluation.Probability-of-failure (POF) assessment was conducted using a Weibull distribution with MTTF and the modification factor. In addition, consequence-of-failure (COF) assessment was conducted based on financial consequences in terms of downtime costs per day and the length of downtime due to failure. The main steam piping system in a thermal power plant was selected as the case study unit. The actual inspection locations where damage to components could frequently occur were defined as risk evaluation targets for the RBI. The generic MTTF for the main steam piping system was evaluated using the Larson-Miller parameter (LMP) equation for creep rupture time. Piping system stress analysis was conducted to obtain the stress applied to the LMP. An equation for the modification factor applied to the main steam piping system was also proposed based on five subfactors.