Framework for the Integration of Service and Technology Strategies

Organised by: Cranfield UniversityAfter sales service is a highly profitable business for manufacturers of technology-driven products. Due to this fact competitors want to share in high profit margins. At the same time after sales business has to deal with an increasing range of variants of products and technologies, shorter life cycles and changing customer demands. In spite of these manifold challenges, often neither after sales departments are involved in the early product development stage nor are customer demands and technical parameters considered in the service development processes entirely. Therefore an integration of service and technology strategies is necessary. This paper presents a framework for this integration that visualises the complex interdependencies and interfaces between service as well as product and motor vehicle workshop technologies.Mori Seiki – The Machine Tool Compan

Self-supporting End Effectors: Towards Low Powered Robots for High Power Tasks

AbstractNew tasks for industrial robots often require high stiffness or entail high reaction forces, which are currently provided by the robot structure itself. This leads to heavy and expensive robot structures: designed for the main task, but oversized for positioning and movement tasks.We propose a new approach to resolve these contradicting requirements: supporting the end effector directly against the workpiece or its surroundings, thus diverting the reaction forces away from the robot structure. We demonstrate this approach in a joining application and present design methods for self-supporting robotic tools as well as potential industrial applications of this technique

Real-time Monitoring of High-speed Spindle Operations Using Infrared Data Transmission

AbstractHigh-performance cutting is carried out with high cutting and feed speeds. Particularly, the use of heavy cutting tools (e.g. in planing machines), it is important to monitor the clamping and balance condition of the mounted tool, as well as the process forces. Therefore, a real-time monitoring system for high-speed operations based on the IrDA protocol was developed. It could be shown that infrared data transmission systems allow shorter reaction times compared to conventional wireless LAN applications. The presented monitoring system provides a reaction time of 7.14 ms at a bandwidth of 42.5 kHz and a data rate of 4.1 MBit/s

A framework for future CAM software dedicated to additive manufacturing by multi-axis deposition

International audienceDeposition processes, such as Wire & Arc Additive Manufacturing (WAAM), have important perspectives in industry, due to their capacity to produce large near-shape parts with high productivity. Beyond process-material issues, deposition path planning is one of the major challenges to allow a wide use of these processes using multi-axis machines or robots. Early CAM software solutions dedicated to multi-axis additive manufacturing have been already commercialised. However, few elementary deposition strategies are currently available. In this article, the possibilities of multi-axis deposition and the developments needed to improve deposition path generation are highlighted through the analysis of a hollow half-sphere as a case study. Deposition strategies are experimentally tested on two different robotised polymer deposition systems. Based on the comparison of the trials, the issues related to the portability of technology from a specific machine setup to a different one are discussed. Finally, a framework for future Computer-Aided Multi-Axis Additive Manufacturing (CAMAAM) software is proposed

Technical Performance and Energy Intensity of the Electrode-Separator Composite Manufacturing Process

AbstractEnergy storage is one of the key technological factors that determine the success of a sustainable future. Especially green mobility concepts for electric or hybrid electric vehicles highly depend upon storage technologies with high energy density and light-weight materials. At the same time, innovative production processes should be conceived that ensure energy and resource efficient manufacturing of these energy storage devices. This paper focuses on the technical as well as dynamic energetic performance analysis and evaluation of an innovative electrode-separator composite manufacturing process of lithium-ion batteries for automotive applications. The technical performance indicators such as battery capacity and the energy intensity of the manufacturing process are highly dependent upon process parameters, machine and product design. Hence, in-depth process knowledge must be acquired to understand interdependencies between all system components. Thus, the manufacturing process is analysed in terms of its dynamics, and correlations between process parameters, process energy demand and final product properties are assessed. The resulting knowledge is important for the subsequent design of large-scale products and processes involved design, as well as for characterisation of the manufacturing process for life cycle inventory databases or life cycle costing calculations

Detection of wear parameters using existing sensors in the machines environment to reach higher machine precision

This paper presents methods to plan predictive maintenance for precision assembly tasks. One of the key aspects of this approach is handling the abnormalities during the development phase, i.e. before and during process implementation. The goal is to identify abnormalities which are prone to failure and finding methods to monitor them. To achieve this, an example assembly system is presented. A Failure Mode and Effects Analysis is then applied to this assembly system to show which key elements influence the overall product quality. Methods to monitor these elements are presented. A unique aspect of this approach is exploring additional routines which can be incorporated in the process to identify machine specific problems. As explained within the paper, the Failure Mode and Effects Analysis shows that the resulting quality in a case study from a precision assembly task is dependent on the precision of the rotational axis. Although the rotational axis plays a significant role in the resulting error, it is hard to explicitly find a correlation between its degradation and produced parts. To overcome this, an additional routine is added to the production process, which directly collects information about the rotational axis. In addition to the overall concept, this routine is discussed and its ability to monitor the rotational axis is confirmed in the paper

Partial Additive Manufacturing: Experiments and Prospects with Regard to Large Series Production

AbstractAdditive manufacturing meets the demand for highly customized and flexible production. However, the physical limitation of the material application rate causes that large volume production of such workpieces is not attractive yet. In order to push additive manufacturing towards large volume production, the impact of this limitation has to be minimized while the advantages have to be maintained. For this purpose, it is proposed in this article to combine partial additive manufacturing with other production technologies. In such a production concept, standardized base workpieces are made in large volume production first and then finalized by additive manufacturing. The finalization step adds the variant specific key features to the workpiece. This proposal is detailed by discussing the suitability of specific workpieces and outlines of the processing route. An experimental feasibility study of this principle is reported, where Fused Deposition Modeling is used to add geometric features to a base workpiece. This case study includes the development of a robot-based setup for the deposition of material with 6 degrees of freedom. This case study is used to illustrate and discuss the fundamental aspects of the conjunction of additive manufacturing with other production processes

Development of an automated assembly process supported with an artificial neural network

A central problem in automated assembly is the ramp-up phase. In order to achieve the required tolerances and cycle times, assembly parameters must be determined by extensive manual parameter variations. Therefore, the duration of the ramp-up phase represents a planning uncertainty and a financial risk, especially when high demands are placed on dynamics and precision. To complete this phase as efficiently as possible, comprehensive planning and experienced personnel are necessary. In this paper, we examine the use of machine learning techniques for the ramp-up of an automated assembly process. Specifically we use a deep artificial neural network to learn process parameters for pick-and-place operations of planar objects. We describe how the handling parameters of an industrial robot can be adjusted and optimized automatically by artificial neural networks and examine this approach in laboratory experiments. Furthermore, we test whether an artificial neural network can be used to optimize assembly parameters in process as an adaptive process controller. Finally, we discuss the advantages and disadvantages of the described approach for the determination of optimal assembly parameters in the ramp-up phase and during the utilization phase

Investigation of integral endless fibre reinforced aluminium-polyamide 6 hybrid joints

Joining processes or connecting elements of structural components are generally used for integration into the automotive body structure. Joining operations cause a locally increased tension profile due to local punctual loads. Thus, a continous and homogenous load path of components to be joines is preferred. Therefore, glass fibre fabrics were imbedded in aluminium-polyamide 6 components by various moulding processes. Along the process chain of aluminium casting and injection moulding, integral endless fibre- reinforced aluminium-polyamide-6 vcomposites were manufactured. Tensile tests of Al-PA6 Test specimens with glass fibres were performed. For the aluminium casting process, low pressure die casting (LPDC) was used. The aluminium melt is moved, against gravity by pressurized nitrogen inducing high quality casting with low porosity, depressions and szhrinkage defects. The grip at the aluminium fibre interface results from microscopic undercuts between metal and fibre. In a second process step, glass fibres and aluminium parts were inserted into the injection moulding machine in which the glass fibres were infiltraded with PA6. Present investigations address non-destructive testing by microcomputer tomography (yCT) to investigate the infiltration of the glass fibres. For destructive methods bytensile testing, the breaking load is affected by the number of layers, infiltration behabiour, fibre orientation and AL-PA6- interface