Advances in Industrial and Manufacturing Engineering最新文献

This paper introduces a novel sheet test specimen that plastically deforms under biaxial stretching when subjected to uniaxial loading in conventional testing machines. The specimen was designed using finite element simulation and consists of a two-dimensional reticular structure with interconnected arms in the form of triangles that converge at the center and are connected to full-width sheets at the specimen's ends. Accumulation of damage at the center is ensured through spherical cups that are milled at opposite sheet surfaces. Experimental strain loading paths obtained by digital image correlation confirm the capability of the novel sheet test specimen to provide biaxial stretching strain paths. This is achieved under friction-independent conditions and without requiring complicated multiaxial setups and machines, provided appropriate values of the inner and outer angles of the interconnected arms are used.

Computerized Numeric Control (CNC) plays an essential role in highly autonomous manufacturing systems for interlinked process chains for machine tools. NC-programs are mostly written in standardized G-code. Evaluating CNC-controlled manufacturing processes before their real application is advantageous due to resource efficiency. One dimension is the estimation of the energy demand of a part manufactured by an NC-program, e.g. to discover optimization potentials. In this context, this paper presents a Machine Learning (ML) approach to assess G-code for CNC-milling processes from the perspective of the energy demand of basic G-commands. We propose Latin Hypercube Sampling as an efficient method of Design of Experiments to train the ML model with minimum experimental effort to avoid costly setup and implementation time of the model training and deployment.

The impact of the stress state on damage evolution, fracture behavior, and product performance is well understood for proportional loading. However, many complex sheet forming operations involve non-proportional loading, which affect the material's hardening and fracture characteristics. This study investigates the influence of a loading direction change on damage evolution in a dual phase steel DP800. Specimens are pre-strained by tensile tests and subsequently loaded in either the same or orthogonal direction to the initial pre-strain direction by additional tensile tests and bending tests. Damage quantification by scanning electron microscopy reveals lower damage evolution after an orthogonal change of loading direction in contrast to monotonic loading directions. The load paths, defined as a history of triaxiality and Lode parameter during loading, are identified numerically under consideration of kinematic hardening. Since kinematic hardening leads to higher triaxialities after orthogonal changes, the load path is not the dominant influence on damage. A possible explanation for the experimental results is the void characteristics after tensile load. After the pre-straining in tensile test, voids are oriented orthogonally to the tensile direction and located between hard martensitic phases. The influence of this morphology on subsequent void growth is illustrated by a simulation verifying that an orthogonal change of loading direction results in void shrinkage, while monotonic loading directions lead to further void growth.

The problem of overloading was characterized as a factor of load history in the modern resource assessment methodology. The signs by which a loading cycle can be considered an overload were defined. A correlation was obtained between the failure mechanics approach and the damage accumulation approach to survivability prediction. An experimental and analytical method of its adjustment has been developed based on the regularities of the impact of loads on the accumulated damage. Its use in obtaining models of damage accumulation in 40Cr and 35CrMnSi steels was shown. New experimental data were obtained on the behavior of the accumulated damage function in the stress localization zones during bending, and an explanation of its non-monotonicity under the influence of operational factors was found.

Material extrusion (MEX) of metallic components is an indirect additive manufacturing (AM) process that is recently gaining a lot of attention in the industry. This multi-step process with debinding and sintering, provides an inexpensive safe alternative, that is effective, flexible and office-friendly for several corporations compared to other metal AM techniques. However, optimizing the manufacturing parameters of the MEX process is still challenging due to the lack of research on their impact on the mechanical and surface properties of the fabricated materials.

For this purpose, this paper investigates how various processing parameters impact the mechanical properties and surface roughness of 17-4 PH stainless steel parts produced by MEX. The parameters analyzed include layer thickness, build orientation, number of contours, and aging thermal treatment for 1 h at $482°C$ (H900). A Taguchi design of experiments (DoE) was employed to conduct the parametric analysis and the results were post-evaluated via the analysis of variance (ANOVA). The experimental results show that H900 treatment increases the micro-hardness by ∼50 HV_0.3 and contributes in augmenting the ultimate tensile strength (UTS) by ∼200 MPa. The build orientation and its interaction with the layer thickness have the highest impact on the surface roughness. Moreover, the amount of enclosed porosity is higher in the samples with lower layer thickness. The absorbed impact energy ($W_{abs}$) is relatively low due to the enclosed porosity content and is not linked to the analyzed processing parameters. The best mechanical properties were obtained for parts built with solid infills, 0° build orientation, 0.125 mm layer thickness, two contours, and H900 as a post-treatment.

The manufacturing of three-dimensional sheet metal components, such as car body parts, heavily relies on deep drawing. With the increasing demand for lightweight measures in the automotive industry due to CO₂ limitation requirements, various methods are currently employed to reduce the weight of deep drawn components. However, these methods often overlook the potential for influencing the stress-strain dependent damage state within the component, even though it can greatly affect its performance in subsequent applications, and thus offers lightweight potentials. Friction between the deep drawing tools and the sheet metal is a key factor influencing the stress-strain state, and hence, represents a lever that can be utilized to manipulate the damage state in the component. This paper focuses on the numerical analysis of the dependence of damage on friction during deep drawing. Therefore, a rectangular geometry with an asymmetrical material flow is numerically investigated. A friction ratio is introduced with different constant friction coefficients for the corner of the tools and the straight sides. The established load paths at a chosen reference point are then considered in the form of selected stress and strain characteristics and the numerically predicted damage state is compared. The results are used to derive a recommended friction ratio that leads to less damage in the corner of the geometry. Afterwards strip drawing tool surfaces are modified to manipulate their friction properties using machine hammer peening. Subsequently, the influence of the structures of the strip drawing tool surfaces is quantified using strip drawing tests. The identified contact normal stress dependent friction coefficients are then implemented in the numerical simulation and the established numerical predicted damage state is examined to gain a more comprehensive understanding of how the friction ratio and the structure of the tool surfaces influence the damage state.

The paper proposes a method and technique that allow, using a minimum sample (3 units) from a batch (30 units) of real gears, to obtain stochastic information about the actual distribution of the gear grinding allowance both on the left and right flanks of the gear gaps for all gears in the batch. The proposed gear grinding allowance stochastic model is based on the representation of the distribution of the gear grinding allowance along the gear periphery as a superposition of a sinusoidal component with a random amplitude and a random component of the white noise type. The conditions for the equivalence of the stochastic characteristics of real (measured) and virtual (not actually measured) gears are formulated, namely the ratio between the amplitude of the sinusoidal component and the average amplitude of the high-frequency harmonic components of the gear grinding allowance distribution along the gear periphery. The gear grinding allowance stochastic model adjusted according to the proposed method makes it possible to predict the distribution of the gear grinding allowance on the left and right flanks of the gear gaps for a batch of gears and, taking into account the information obtained (replacing the experimental data), both evaluate the existing technology and optimize the gear grinding allowance value. As a result, it becomes possible to assess the quality of the technological process of manufacturing the gear, taking into account the effect random deformations to gear grinding allowance at the stage of their heat treatment (hardening), which is performed before the gear grinding operation. In turn, optimization of the grinding allowance (based on its actual distribution along the periphery of the gear) makes it possible to reduce both defects in burns (with increased allowance) and defects in unground teeth (with insufficient allowance).

After closure, voids need to be healed through bonding and interface dissolution to restore the mechanical properties and produce a sound product. For the prediction of void healing and the respective process optimization, a void healing criterion, spanning all three phases is needed. While hot rolling is generally suited for void healing, with large deformations at hydrostatic pressure as well as high temperatures, not all regions in the workpiece offer the same void healing conditions. Due to gradients of these metrics e. g. along the normal direction, a space-resolved approach is needed. Previously, a practical void healing criterion combining void closure and subsequent recrystallization has been proposed and applied to exemplary hot rolling processes. Besides a broader application of the criterion, adding the process parameters roll diameter and temperature, the present paper mainly aims for the experimental validation of this criterion. In bonding trials, a positive influence of temperature and strain on the bond strength has been found. While no clear correlation of the holding time on the bond strength was detectible without concurrent contact pressure the experiments suggested a saturation strain as an indicator for void healing instead. Accordingly, the criterion has been revised and a strain-based criterion proposed, applied, and compared to the previously introduced recrystallization-based void healing criterion.

As recent trends in manufacturing engineering disciplines show a clear development in the sustainable as well as economically efficient design of forming processes, monitoring techniques have been gaining in relevance. In terms of monitoring of product properties, most processes are currently open-loop controlled, entailing that the microstructure evolution, which determines the final product properties, is not considered. However, a closed-loop control that can adjust and manipulate the process actuators according to the required product properties of the component will lead to a considerable increase in efficiency of the processes regarding resources and will decrease postproduction of the component. For most forming processes, one set of component dimensions will result in a certain set of product properties. However, to successfully establish closed-loop property controls for the processes, a systematic understanding of the reciprocity of the dimensions after forming and final product properties must be established. This work investigates the evolution of dimensional accuracy as well as product properties for a series of forming processes that utilize different degrees of freedom for process control.

Adherence to customer due dates is the yardstick for the performance of manufacturing companies. In the era of same-day delivery, consumers expect reliable delivery of ordered goods and short delivery times. Also, in the field of business-to-business supply, it is evident that adherence to delivery dates is a fundamental logistical objective for companies. Contract manufacturers, in particular, are confronted with significant challenges: strong fluctuations in customer demand, shorter requested delivery times, and high competitive pressure require appropriate organisation, planning and control of production. However, companies often miss their schedule reliability targets and fail to identify the right causes for these failures. This raises the question of what factors influence the failure to meet schedule reliability targets, how to identify such factors, and what options are available to counteract them. This contribution addresses this issue and focuses on ways to analyse the emerging lateness at work systems in production areas as a deviation of the actual form the planned throughput time. We present existing approaches to analysing the lateness behaviour at work systems and extend the current theory of logistical modelling to determine the three drivers of the so-called relative lateness – planning influences, variance of work-in-process (WIP) and sequence deviations – at work systems systematically. Through this analysis, we enable the practical applicator to initiate target-oriented countermeasures to improve the schedule reliability of their work systems with acceptable analysis expenditure.