Advances in Industrial and Manufacturing Engineering最新文献

The aim of this paper is to analyze the relation between magnetic and mechanical properties during and after forming processes. For this purpose, several tensile tests were carried out on sheet metal samples up to a defined plastic strain. The specimens were left in the clamping device in order to relieve the force in several steps until the specimen was completely relieved. As a consequence, the gradual relief leads to a reduction of internal stress states. During the forming process, the initial magnetic relative permeability and magnetic anisotropy of the sample were measured several times. Both properties are related to the mechanical states in the material through the effects of magnetic embrittlement and magneto-elasticity. The plastic strain of the specimens was determined by optical measurements and the stresses in the measurement range during the tensile test was determined with the help of a subsequent numerical simulation. This made it possible for the first time to measure the magnetic properties of samples with different plastic strain and different stress states. The evaluation shows that there is a strong correlation between permeability and plastic strain as well as anisotropy and stress. Based on these findings, it has been confirmed, that the determination of the plastic strain by a soft sensor is possible.

The implementation of control systems in metal forming processes improves product quality and productivity. By controlling workpiece properties during the process, beneficial effects caused by forming can be exploited and integrated in the product design. The overall goal of this investigation is to produce tailored tubular parts with a defined locally graded microstructure by means of reverse flow forming. For this purpose, the proposed system aims to control both the desired geometry of the workpiece and additionally the formation of strain-induced α′-martensite content in the metastable austenitic stainless steel AISI 304 L. The paper introduces an overall control scheme, a geometry model for describing the process and changes in the dimensions of the workpiece, as well as a material model for the process-induced formation of martensite, providing equations based on empirical data. Moreover, measurement systems providing a closed feedback loop are presented, including a novel softsensor for in-situ measurements of the martensite content.

To produce cold-rolled steel strips with specific mechanical properties and surface roughness typically temper rolling is adopted. In most cases, a uniform roughness pattern on the strip surface is mandatory. Due to the wear of the textured work rolls, their surface roughness ($Ra$) continuously reduces during the process, which should be accounted for process control. However, conventional temper rolling systems fail to guarantee a uniform surface roughness. In this work, the influence of strip tension on the imprinting of surface roughness during temper rolling is analyzed based on a multi-scale FE modeling concept to explore new ways for surface roughness control. This is done in simulation where, a macroscopic rolling model incorporating strip tension is coupled to a mesoscopic imprinting model and both models are validated using copper rolling trials. The influence of different thickness reductions, strip tensions and incoming strip's surface roughness on imprinting is modeled and compared. The numerical results reveal that a higher strip tension decreases the roughness transfer, which presents potential to control the roughness transfer ratio without changing other process parameters like the prescribed thickness reduction in the future.

Manufacturing industry faces new challenges with the emergence of the need for the production of small batches of personalized parts. Such production methods demand for a capability to integrate multiple machining operations in one manufacturing process to reduce setup and calibration time and tooling costs. This requirement is especially challenging for difficult-to-machine materials such as glass, since there exist only a limited number of glass machining technologies and further these technologies often require specialized tooling. Glass cutting is among the crucial machining operations, which is frequently required for glass products.

The presented study discusses free-form micro-cutting by Spark Assisted Chemical Engraving (SACE), determining cut parameters, in terms of tool feed-rate F and depth-of-cut p in function of machining voltage. A simple model is discussed allowing to predict the maximal product $F\cdot p$ which can be used to cut glass by SACE. The presented data and model allow to reduce the time-consuming trial and error process in determining appropriate cutting parameters. An interesting finding is that lowest cutting times can be achieved with tools of 100-μm diameter. Cut surface roughness of initial cuts can be reduced by deploying subsequently incremental finishing (polishing) passes performed at lower machining voltage, lower tool feed rates and higher angular tool rotation. It is demonstrated that very smooth cut surfaces (Rz ~ 1 μm) can be achieved.

Additive manufacturing (AM) has revolutionized the local production realization of highly customizable items. However, the high process complexity - inherent to AM operations - renders uncertain the quality performance of the final products. Consequently, there is often a need to assess the unique fabrication capabilities of AM against the reoccurring issues of process instability and end-product inconsistency. Improvement opportunities may be identified by empirically exploring the complex phenomena that regulate the quality performance of the final products. Thus, focused quality-screening and process optimization studies should additionally take into account the special need for speedy, practical and economical experimentation. Robust multi-factorial solvers should predict effect strength by relying on small samples while possibly dealing with non-linear and non-normal trends. We propose a nonparametric modification to the classical Taguchi method in order to enable the generation of rapid and robust screening/optimization predictions for an arbitrary 3D-printing process. The new methodology is elucidated in a recently published dataset that involves the difficult Taguchi screening/optimization application of a fused deposition process. We compare differences in the predicted effect-strength magnitudes between the two approaches. We comment on the practical advantages that the new technique might offer over the traditional Taguchi-based improvement analysis. The emphasis is placed on the ‘assumption-free’ aspect, which is embodied in the new solver. It is shown that the proposed tool is agile. It could also reliably support a customized 3D-printing process by offering robust and faster quality improvement predictions.

Quality control systems are inevitable in the production of safety-relevant, textile composites. In the industry, predominantly optical measuring procedures, so-called Machine Vision Systems (MVS), became generally accepted. A critical quality feature of textile structures is the carrying capacity of loads, which requires an orientation of the fibre in the direction of the load. To control the braiding angle, which determines the orientation of the fibre in braids, a feedback control system can be used. The deviation from the target angle is directly correlated to the time span between the formation and the measurement of the braiding angle, the so-called dead band. Therefore, the objective is to reduce the dead band by measuring the braiding angle with a MVS near the braiding point. This work describes and evaluates an approach to minimize the dead band by utilising a mathematical description of the braiding process to determine the origin of the braiding angle while tackling the difficulty of the convergence zone in the braiding process.

To investigate the impact of the sudden shift to online education triggered by the COVID-19 pandemic, a survey was conducted among international mechanical engineering students, specializing in manufacturing technology, at the TU Dortmund University. The surveyed students, were exposed to differently structured online courses from different institutes, as well as dynamic developments in each online course, over the semester and thus were able to effectively assess the pros and cons of the different teaching styles. To get the viewpoints of both the involved parties on how a successful online education course needs to be structured, a similar survey was also conducted among manufacturing engineering professors involved in Germany. The survey, a combination of Likert-scale and free-text questions, tackled the aspects of motivation to teach and learn, ensuring effective teaching and learning, and proper assessment of the learning outcomes in an online education system. The results show that both parties initially struggled with the transition, but later adapted quickly to the new style of online teaching that was inspired by the conventional flipped classroom concept. Certain structures and approaches to online teaching, such as pre-recorded lectures; interactive Q&A sessions; quizzes for self-assessment, are preferred by students and teachers alike. Aspects where the viewpoints differed could be explained by the difference in age and the experience in using digital equipment. A challenge specific to online engineering education is on offering laboratory experiences to students. Possible solutions such as virtual labs, remote labs and digital-live labs that aid in overcoming this challenge are presented. Finally, based on the survey results and the author experiences on digital laboratories, best practice guidelines are presented that will help the readers in the design and deployment of online engineering courses.

The cutting process is an important stage of the industries which are dealing with cutting of small pieces from large items in such a way so that the wastage should be minimum. In this study, we present an effective model for solving one-dimensional cutting stock problem (1D-CSP) using sustainable trim based on Cesàro means of order $\lambda$ ($\lambda$ is real $>-1$), with the provision of cutting at most two order lengths at a time, which is acceptable in many practical cases. Additionally, we present the comparison of the model with Residual Greedy Rounding (RGR) and CUT. It is shown that increased sustainable trim decreases the total trim loss by providing greater variety of stock lengths, which can be effectively used in future orders.

In order to develop competitive all-solid-state batteries, cost efficient and highly scalable manufacturing methods need to be identified and evaluated. In this work, the scalable production of a polymer solid electrolyte (SPE) separator was investigated to gain deep knowledge on how the process parameters influences product quality and reproducibility. In detail, a sustainable, solvent-free manufacturing route for the fabrication of SPE films based on a PEO based block copolymer through a novel, highly scalable film casting process was developed. The scalability, energy consumption and the SPE separator properties film thickness, density, ionic conductivity, polymer degradation and lithium salt distribution were evaluated in comparison to a reference calendering process. Compared to the considered reference process, the developed film casting process showed improved precision at higher throughputs regarding a constant film thickness below 30 μm and SPE density. The novel film casting process showed a significantly lowered energy consumption, which is of major importance with respect to production costs and sustainability. At the same time, the electrochemical performance was preserved with an ionic conductivity of approx. 0.2 mS cm⁻¹ at 80 °C as well as a rate capability of approx. 60 mAh g_LFP⁻¹ at 1C discharge rate.