Investigation of the altered influence of physical stress by the use of ergonomically optimized forging tongs

Work-related illnesses and the resulting employee absences can have a major impact on productivity and competitiveness, especially in small and medium-sized enterprises. Particularly in the forging industry, the manual handling of forged parts leads to high physical stress and thus to frequent illnesses of the musculoskeletal system, especially of the hand-arm system. One possibility to counteract this circumstance is the use of ergonomic forging tongs. In the study presented here, the influence of ergonomic forging tongs on the physical stress of forging employees was investigated by simulation and experiment and compared to conventional forging tongs. Within the simulation and the experimental investigation, forging parts and forging tongs were varied. In the simulation, an ergonomics assessment of the forging situation could be evaluated using the Ergonomic Assessment Worksheet. In the experimental study, gripping force measurements and calorie measurements were used to determine the impact of handling the forging tongs on the forging employees. The results show that the use of the new ergonomically optimized forging tongs can lead to a significant physical relief for the forging employees. The knowledge gained from the ergonomically developed concepts can also be transferred in other industries

Automated design of multi-stage forging sequences for die forging

Forgings are produced in several process steps, the so-called forging sequence. The design of efficient forging sequences is a very complex and iterative development process. In order to automate this process and to reduce the development time, a method is presented here, which automatically generates multi-stage forging sequences for different forging geometries on the basis of the component geometry (STL file). The method was developed for closed die forging. The individual modules of this forging sequence design method (FSD method) as well as the functioning of the algorithm for the generation of the intermediate forms are presented. The method is applied to different forgings with different geometrical characteristics. The generated forging sequences are checked with FE simulations for the quality criteria form filling and freedom from folds. The simulation results show that the developed FSD method provides good approximate solutions for an initial design of forging sequences for closed die forging in a short time

Virtual Element Method for Cross-Wedge Rolling during Tailored Forming Processes

In this work we present an application of the virtual element method (VEM) to a forming process of hybrid metallic structures by cross-wedge rolling. The modeling of that process is embedded in a thermomechanical framework undergoing large deformations, as outlined in [1, 2]. Since forming processes include mostly huge displacements within a plastic regime, the difficulty of an accurate numerical treatment arises. As shown in [3], VEM illustrates a stable, robust and quadratic convergence rate under extreme loading conditions in many fields of numerical mechanics. Numerically, the forming process is achieved by assigning time-dependent boundary conditions instead of modeling the contact mechanics yielding to a simplified formulation. Based on the two metallic combinations of steel and aluminum, different material properties are considered in the simulations. The purpose of this contribution is to illustrate the effectiveness of such a non-contact macroscopic framework by employing suitable boundary conditions within a virtual element scheme. A comparison with the classical finite element method (FEM) is performed to demonstrate the efficiency of the chosen approach. The numerical examples proposed in this work stem out from the DFG Collaborative Research Centre (CRC) 1153 “Process chain for the production of hybrid high-performance components through tailored forming”

Part Based Mold Quotation With Methods Of Machine Learning

The dominating mass-manufacturing process of today is plastic injection molding. This production process uses economies of scale because parts are produced in seconds at marginal cost of plastics. However, upfront investment costs for the tooling of molds are the basis for deciding if a mold is tooled and hence if a part is viable for mass-production. If tooling costs are too high, a product may not viable for production. If tooling costs are estimated too low by the tool shop, contract implications may arise. Because injection molds differ in their complexity, price estimations for the tooling of molds are an ongoing quest. There are various methods for estimating the costs of injection molds such as rule based, analytical or data driven approaches. The advantage of data driven approaches is the ability of adjusting to historical production data as well as readjusting while training on new batches of recent data. The focus of our research was to support the quotation process of tool shops. To this end, we studied a data driven machine learning approach. The goal of this research is to develop a method with humanlike quotation accuracy, achieve standardization, factor in historic quotation data and shorten quotation process times. The machine learning approach developed is based on geometry data of parts and additional meta-information. Within this research, a system was developed to interact with live production systems of an electronic part producing tool shop. The method developed was trained and validated on production data in a case study. To enhance the quotation process, the method developed was embedded into a server-based application with a web user interface and interfaces to live production systems for the automation of processes

Contact Temperature Measurements on Hybrid Aluminum–Steel Workpieces in a Cross-Wedge Rolling Process

The Collaborative Research Center 1153 is investigating a novel process chain for manufacturing high-performance hybrid components. The combination of aluminum and steel can reduce the weight of components and lead to lower fuel consumption. During the welding of aluminum and steel, a brittle intermetallic phase is formed that reduces the service life of the component. After welding, the workpiece is heated inhomogeneously and hot-formed in a cross-wedge rolling process. Since the intermetallic phase grows depending on the temperature during hot forming, temperature control is of great importance. In this paper, the possibility of process-integrated contact temperature measurement with thin-film sensors is investigated. For this purpose, the initial temperature distribution after induction heating of the workpiece is determined. Subsequently, cross-wedge rolling is carried out, and the data of the thin-film sensors are compared to the temperature measurements after heating. It is shown that thin-film sensors inserted into the tool are capable of measuring surface temperatures even at a contact time of 0.041 s. The new process monitoring of the temperature makes it possible to develop a better understanding of the process as well as to further optimize the temperature distribution. In the long term, knowledge of the temperatures in the different materials also makes it possible to derive quality characteristics as well as insights into the causes of possible process errors (e.g., fracture of the joining zone)

Throughput Analysis for Layout Optimisation of Modular Conveyor Systems

In this paper, objective functions for the optimisation of modular conveyor systems will be introduced. Modular conveyor systems consist of conventional as well as modular conveyor hardware, which are arranged in form of matrix-like layouts. The aim of an ongoing research project is to provide small and medium-sized enterprises with a user-friendly decision support for the selection and planning of modular conveyor systems. For this purpose, the conveyor systems should be evaluated according to the objectives throughput and space requirement. Therefore, mathematical equations have been developed, which enable a fast and precise evaluation of layouts. The paper focuses mainly on the efficient calculation of the throughput. The result quality of the evaluation equations regarding the throughput was proven by a simulation of example systems

Development of a Method for Decision Support on Participation in Capacity Sharing for Manufacturing SMEs

A volatile, non-transparent market environment leads to fluctuations in the load on production capacities in the manufacturing sector, which are reflected within production in the over- or underutilization of machines and persons. Small and midsized enterprises (SMEs) are expecting increasing volatility, which is accompanied by an increase in the frequency of market and economic cycles. For SMEs it is difficult to cope with these fluctuations. Capacity sharing platforms can be a solution for this challenge. Platforms are available in different forms, but not used by companies often, because of prevailing scepticism in different fields. Therefore, a methodology will be developed to provide a decision support for or against platform usage. Additionally, the platform type choice will be supported, and the changes of logistic and economic indicators will be considered. With this information companies can make a qualitative decision, and the existing inhibitions can be alleviated

Potential of process information transfer along the process chain of hybrid components for process monitoring of the cutting process

The production of hybrid components involves a long process chain, which leads to high investment costs even before machining. To increase process safety and process quality during finishing, it is necessary to provide information about the semi-finished parts geometry for the machining process and to identify defect components at an early stage. This paper presents an investigation to predict variations in dimension and cavities inside the material during cross-wedge rolling of shafts based on measured tool pressure. First, the process is investigated with respect to the variation in diameter for three roll gaps and two materials. Subsequently, features are generated from the hydraulic pressures of the tools and multi-linear regression models are developed in order to determine the resulting diameters of the shaft shoulder. These models show better prediction accuracy than models based on meta-data about set roll gap and formed material. The features are additionally used to successfully monitor the process with regard to the Mannesmann effect. Finally, a sensor concept for a new cross-wedge rolling machine to improve the prediction of the workpiece geometry and a new approach for monitoring machining processes of workpieces with dimensional variations are presented for upcoming studies

Robotergesteuerte Prozessautomatisierung (RPA): Reifegradmodell zur Identifizierung RPA geeigneter Prozesse hinsichtlich der Dimension Daten

For the introduction of RPA in a company, the first step is to identify suitable business processes. For this purpose, the processes are evaluated with regard to various selection criteria, such as complexity or case-sensitiv-ity. Another criterion for the selection and evaluation of processes is the data on which the process is based. In this paper, a maturity model is presented, which subdivides the selection criterion data into the 5 assessable categories digitisation level, data quantity, data variance, data for-mat and data responsibility.Für die Einführung von RPA im Unternehmen müssen in einem ersten Schritt geeignete Unternehmensprozesse identifiziert werden. Hierzu werden die Prozesse hinsichtlich verschiedener Auswahlkriterien bewertet, wie z. B. Komplexität oder Fallhäufigkeit. Ein weiteres Kriterium zur Auswahl und Bewertung von Prozessen sind die dem Prozess zugrundeliegenden Daten. In diesem Paper wird ein Reifegradmodell vorgestellt, welches das Auswahlkriterium Daten in die 5 bewertbaren Kategorien Digitalisierungsgrad, Datenmenge, Datenvarianz, Datenformat und Datenverantwortung untergliedert

Investigation of the prediction accuracy of a finite element analysis model for the coating thickness in cross-wedge rolled coaxial hybrid parts

The Collaborative Research Centre 1153 (CRC 1153) "Process chain for the production of hybrid high-performance components through tailored forming" aims to develop new process chains for the production of hybrid bulk components using joined semi-finished workpieces. The subproject B1 investigates the formability of hybrid parts using cross-wedge rolling. This study investigates the reduction of the coating thickness of coaxially arranged semi-finished hybrid parts through cross-wedge rolling. The investigated parts are made of two steels (1.0460 and 1.4718) via laser cladding with hot-wire. The rolling process is designed by finite element (FE)-simulations and later experimentally investigated. Research priorities include investigations of the difference in the coating thickness of the laser cladded 1.4718 before and after cross-wedge rolling depending on the wedge angle β, cross-section reduction DA, and the forming speed v. Also, the simulations and the experimental trials are compared to verify the possibility of predicting the thickness via finite element analysis (FEA). The main finding was the ability to describe the forming behavior of coaxially arranged hybrid parts at a cross-section reduction of 20% using FEA. For a cross-section reduction of 70% the results showed a larger deviation between simulation and experimental trials. The deviations were between 0.8% and 26.2%. © 2019 by the authors