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Abele E.,Institute of Production Management | Schutzer K.,Laboratory for Computer Application in Design and Manufacturing | Bauer J.,Institute of Production Management | Pischan M.,Institute of Production Management
Production Engineering | Year: 2012

Industrial robots are used in a great variety of applications for handling, welding and milling operations. They represent a cost-saving and flexible alternative for machining applications. A reduced pose and path accuracy, especially under process force load due to the high mechanical compliance, restrict the use of industrial robots for further machining applications. Test results showed that these deviations range up to 0. 6 mm. In this paper, a method is presented to determine the resulting path deviation of the robot under process force by using a structured light scanner. The obtained data is compared with the CAD (Computer Aided Design) data of the machined part within a developed software module. Additionally, the developed module provides functions for manipulation, registration of STL (Surface Tessellation Language) surface point clouds and a postprocessor for program translation. The comparison is performed using a dexel discretization of each data set. Based on this comparison the robot path is adapted to improve the machining quality. This method can be applied to 3- and 5-axis machining operations. The results show that the deviation can be reduced to 0. 1 mm. © 2012 German Academic Society for Production Engineering (WGP).

Adolph S.,Institute of Production Management | Kubler P.,Institute of Industrial Manufacturing IFF | Metternich J.,Institute of Production Management | Abele E.,Institute of Production Management
Procedia CIRP | Year: 2016

The increase of customized products and the associated decrease in batch size as well as a rising variance of required parts lead to more complex material supply processes. Additionally, the customer places an increasing emphasis on meeting delivery dates as well as on shorter delivery times which both require especially reliable and efficient logistics processes. One approach to increase the efficiency is the transfer of lean thinking to logistics processes, which implies a reduction of waste. Currently, only basic approaches to apply lean production methods to logistics exist. Literature review shows that they are insufficient as they don't detect reasons for waste systematically and give advices to reduce it. The focus of this article is therefore the development of a tool for quantifying value-added shares in material supply as a main task of logistics. First, it is examined to what extent logistics activities can generally be classified as value-adding. Subsequently, the Overall Equipment Effectiveness (OEE) analysis, which is so far used to evaluate the efficiency of production systems, is transferred to commissioning as one part of the material supply process. The value-added shares of commissioning are identified and reasons for losses are discussed. Finally, a case study in the Process Learning Factory CiP validates the approach. Through the application of this tool, it is possible to identify losses and thus increase the efficiency of logistics processes. © 2015 The Authors.

Albrecht F.,Institute of Production Management | Faatz L.,Institute of Production Management | Abele E.,Institute of Production Management
Procedia CIRP | Year: 2013

The increasing length and interconnectedness of process chains caused by a rising product complexity forces companies to operate in an environment with a growing number of change drivers interfering in their day-to-day business. These new business conditions characterized by a rising intensity and multidimensionality of changes do not allow covering all potential developments by the flexibility of the production economically. This circumstance requires new approaches for process planning and investment decisions for companies. This article introduces an integrated planning approach to evaluate the changeability of interlinked production processes ex ante using material flow simulation and scenario analysis. Based on the results process chains can be configured robust to future requirements, because changeability enablers for a quick and efficient adoption can be installed systematically. A major advantage of simulating multiple stages of a production process is not only that the changeability of single processes is evaluated, but also the interdependencies within the entire process chain are considered in the evaluation and the configuration of improved processes. © 2013 The Authors.

Abele E.,Institute of Production Management | Pfeiffer G.,Institute of Production Management | Jalizi B.,Institute of Production Management | Bretz A.,Institute of Production Management
Production Engineering | Year: 2016

Machine tools are generally used with process parameters that are as productive as possible yet stable. One way to raise productivity is to increase the process parameters like cutting speed or depth of cut (DOC). However, this approach will lead to process instabilities sooner or later. An increased rotational speed of the spindle will excite higher eigenfrequencies depending on the tools teeth count. In combination with higher cutting forces resulting from a deeper DOC, the process can become instable because of chatter or other oscillations and vibrations of the machine tool. This paper describes the identification of a critical eigenfrequency and corresponding eigenmode. An active damper was then developed to mitigate the negative effect this critical eigenfrequency has including a robust controller which protects the process from instabilities through changing eigenfrequencies caused by changing machine positions. It will also enable increased process parameters for a higher productivity of the machine tool. A simulation environment of the active damping system with a classic control and a robust μ-control was developed. The damper was applied to the machine tool and tested. © 2016, German Academic Society for Production Engineering (WGP).

Tisch M.,Institute of Production Management | Hertle C.,Institute of Production Management | Cachay J.,Institute of Production Management | Abele E.,Institute of Production Management | And 2 more authors.
Procedia CIRP | Year: 2013

As a next challenge, in terms of enhancing employees' improvement abilities with the use of Learning Factories, existing education and training programs are remodeled by the means of a competency-oriented, scientific-founded didactic concept. Therefore, based on a multi-level study on Learning Factories focusing on their design and use, a systematic approach to further develop quasi-real, effective learning environments in the field of manufacturing systems is conceived. As a result competency-oriented Learning Factories meeting the industries' requirements can be implemented with the use of fewer input resources and an increased success in applied competencies in real situations. © 2013 The Authors.

Pischan M.,Institute of Production Management
Advanced Materials Research | Year: 2013

The production process (drilling and reaming) causes burrs at the intersection of cross holes. The removal of these burrs is crucial especially for security relevant parts like hydraulic valves in aircrafts. Burrs lead to undefined flow conditions and blocking of these valves. Until now, burrs of internal contours are often removed by manual processes. Security relevant systems are especially deburred by time consuming manual deburring processes. In some cases, this process requires up to 50% of the manufacturing time. To automate the deburring process industrial robots can be used. Typical applications are deburring [1] and fettling [2] of cast parts. There are only a few approaches for sensitive workpieces with high accuracy demands [3]. This paper presents an approach to optimize the deburring process for cross holes in titanium using industrial robots and a special deburring tool. The best suited tool for the application is selected after investigating several different deburring tools. All relevant parameters are optimized by experimental investigations to minimize the process time. The results are evaluated by measuring the secondary burr and the chamfer width respectively. © (2013) Trans Tech Publications, Switzerland.

Enke J.,Institute of Production Management | Kraft K.,Institute of Production Management | Metternich J.,Institute of Production Management
Procedia CIRP | Year: 2015

The enhancement of job-related competencies is important for the competiveness of companies. For establishing these competencies, learning factories offer a basis for self-controlled and informal learning. Core elements of learning factories are learning modules with different foci. To develop the needed competencies a proper design of learning modules is fundamental. An instrument to systematically analyze and create learning modules is the competency transformation. The presented learning objective taxonomy supports the formulation of competencies for the transformation chart. Furthermore, it enables a comparison between actual and target states of learning modules. Thus, recommendations for improvements can be made. © 2015 The Authors.

Albrecht F.,Institute of Production Management | Kleine O.,Fraunhofer Institute for Systems and Innovation Research | Abele E.,Institute of Production Management
Procedia CIRP | Year: 2014

Today, the planning and optimization of changeable production systems (CPS) has become a top priority item for the strategic management in most industries. Research has already provided a whole bunch of supposedly effective, mainly technical solutions that enhance the changeability of production systems. However, to actually select solutions for CPS, decision-makers do also need tools for their ex-ante evaluation. These are still missing - especially to assess the impact of organizational measures. Further, it appears that decision-makers have difficulties in coping with the dynamic complexity implied by CPS in planning activities. CPS are complex socio-technical systems - both in terms of their structure and their dynamic behavior - and so must be the underlying planning problems. Thus, any planning approach and in particular its related decision support tools must not only fit the dynamic complexity of the planning problem as a formal requirement, but must at the same time foster the decision-maker's understanding of the underlying managerial problem, i.e. it must foster managerial insight. Therefore, this paper aims at closing this gap and proposes an integrated planning approach based on a hybrid Discrete Event Simulation (DES) and System Dynamics (SD) framework. Both simulation methods are interlinked by an integrated planning approach sharing the same conceptual model and a common set of parameters and key performance indicators (KPI). The DES is applied (1) for an in-depth analysis of the effects of any measures to improve the changeability, based on KPIs relevant to the decision-maker, and (2) to verify the major parameters utilized in the SD model. However, the DES can only be applied for a given structural state of the system. Consequently, SD is utilized to investigate its dynamic behavior when it changes from one structural state to the other. The planning approach was successfully applied in an industry context, where it proved its ability to actually leverage the decision quality in current practice to manage CPS. © 2014 Elsevier B.V.

Kellenbrink C.,Institute of Production Management | Herde F.,Institute of Production Management | Eickemeyer S.C.,An Der University 2 | Kuprat T.,An Der University 2 | Nyhuis P.,An Der University 2
Procedia CIRP | Year: 2014

The condition of complex capital goods deteriorates during their operation. In light of scarce resources and the high residual value of used goods at the end of a life cycle, the primary goal is to restore or "regenerate" as many parts of the goods as possible so that their functional characteristics can be maintained or even improved. The characteristics of this regeneration-e.g., different repair paths or a high variance concerning the functionality of goods-create difficult challenges when planning regeneration processes. Due to the characteristics, planning approaches known for the remanufacturing of often low-value goods are not applicable for the regeneration. In this article we present the primary problems of the corresponding planning tasks and solution-targeted approaches to solve these problems. More precisely, we develop an embracing capacity and load-adjustment method for these regeneration processes, considering different planning horizons. In addition, we present a framework that demonstrates how to identify the most profitable regeneration requests. Furthermore, we concentrate on the selection of different regeneration modes that can be applied to regenerate capital goods. Finally, we address design options for capacity and load adjustment in the regeneration processes and the pool management. All planning and control approaches together represent a holistic planning approach for regeneration processes. © 2014 The Authors. Published by Elsevier B.V.

Schlechtendahl J.,Institute for Control Engineering of Machine Tools and Manufacturing Units ISW | Eberspacher P.,Institute for Control Engineering of Machine Tools and Manufacturing Units ISW | Schraml P.,Institute of Production Management | Verl A.,Institute for Control Engineering of Machine Tools and Manufacturing Units ISW | Abele E.,Institute of Production Management
Procedia CIRP | Year: 2016

The need to increase resource and energy efficiency for a sustainable production has led to saving potential analyses and afterwards saving strategies in a multitude of disciplines: product design, supply chain management, process chain design, production process development, energy-optimal machine or component control and even machine tool and component design. Each of those strategies resulted in numerous improvements, however, they still lack reciprocal consideration. To overcome this deficit, a machine-independent energy control system to include any control- or operation-based energy optimizer will be introduced in this paper. It is based on real-time control information from the machine and software-based energy demand optimizers targeting the machining process, the machine tool components control as well as the overlaying production process. The control system itself ensures the correct cooperative operation of the three optimizer types, to enable the much needed reciprocal consideration of the optimizer's effects. © 2016 The Authors.

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