Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
Session Overview
Session
SES 4.1: Digital Product and Process Development
Time:
Wednesday, 28/Jun/2017:
9:00am - 10:00am

Session Chair: Milton Borsato
Location: Aula Convegni (first floor)

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Presentations

161. Quality-predictive CAM simulation for NC milling

Christian Brecher, Frederik Wellmann, Alexander Epple

Laboratory for Machine Tools and Production Engineering (WZL) of RWTH Aachen University, Germany

Milling processes are primarily rated by productivity and resulting product quality. However, while modern CAM and NC simulation systems are capable of predicting productivity indicators (e.g. cycle times), no explicit forecast of the resulting product quality with respect to individual workpiece tolerances is possible, yet. On that account, a first-time-right approach is introduced, which enhances the physics-based modelling behind existing simulations by describing the impact of machine tool, fixture, cutting tool and technology parameters on part quality. It is shown that influences of workpiece deformation, tool deflection and geometrical precision can be represented context-sensitively for prismatic part machining.


18. Virtual maintenance simulation for socially sustainable serviceability

Margherita Peruzzini1, Fabio Grandi1, Marcello Pellicciari1, Claudia Campanella2

1University of Modena and Reggio Emilia, Italy; 2CNH Industrial, Ergonomics – HMI, Design Analysis & Simulations, Viale delle Nazioni 55, 41100 Modena, Italy

In order to achieve more sustainable development processes, industries need not only to improve energy efficiency and reduce costs, but also to increase the operators’ wellbeing to promote social sustainability. In this context, the present research focuses on the definition of a methodology based on human-centred virtual simulation to improve the social sustainability of maintenance tasks by enhancing system design and improving its serviceability. It is based on the operators’ involvement and the analysis of their needs from the early design stages on virtual mock-ups. The methodology proposed merges a protocol analysis for human factors assessment and an immersive virtual simulation where human-centred serviceability simulations can be used during design phases. To demonstrate the effectiveness of the proposed method, an industrial use case has been carried out in collaboration with CNH Industrial.


158. A 4M approach for a comprehensive analysis and optimization of manual assembly lines

Claudio Favi1, Michele Germani2, Marco Marconi2

1Università degli Studi di Parma, Italy; 2Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, Ancona, Italy

Different Design-for-X (DfX) methods have been developed in recent years to support the design process and the product engineering stage. Methods and tools for efficient Design-for-Assembly (DfA) are well-known techniques, widely used throughout many large industries. DfA supports in the reduction of product manufacturing costs and it potentially leads greater benefits than a simple reduction in assembly time.

DfA techniques have been developed since the early 1980’s and among them the most famous one is certainly the Boothroyd and Dewhurst method (B&D), widely accepted and used in industrial contexts. The B&D method allows measuring the complexity of assemblies and deriving quantitative results. However, this method is rather laborious and, in most cases, it only focuses on the product design, missing to provide a holistic overview of the assembly line, workstations, assembly tasks, etc.

In this context, this paper proposes a more comprehensive approach to overcome the above-mentioned weak points and to optimize the assemblability of complex mechanical products, by taking into account all the aspects involved in the manual assembly. The proposed 4M design for assembly approach is based on the examination (recording) and analysis of each single task of an existing manual assembly line. The 4M concurrently considered by the approach are: (i) Method – Assembly issues related to the product and components design and geometry; (ii) Machine – Assembly issues related to the workstation layout, tools arrangement and ergonomics aspects; (iii) Man – Assembly issues related to the workers, which includes ambiguous assembly instructions, skills and experiences, training, etc.; (iv) Material – Assembly issues related to the tools and equipment used for the manual assembly operations.

The step beyond the current state of the art is the clear identification and classification of manual assembly issues by means of a systematic approach able to split these issues in four specific categories (Method, Machine, Man and Material). In this way, the re-design process is assisted and designers are guided during the decision-making process for the optimization of assembly time and costs. The final goal of this work is the concurrent improvement of the product design, the workstation and equipment ergonomics, as well as the assembly tasks.

Within this work, a complex assembly product (electric spindle motor) has been selected to validate the proposed approach. At first, the product and relative assembly line have been analysed following the proposed 4M approach, in order to highlight the most relevant issues. Successively, different re-design actions have been implemented to mitigate the criticalities related to product design (Method), workstation (Machine), assembly operations and instructions (Man) and tools (Material). The results obtained with the new product configuration have been finally compared with the performances of the original design configuration. Important improvements have been highlighted in terms of relevant parameters of the assembly process, such as assembly time, number of needed assembly operations, takt time of the assembly line and overall manufacturing costs.



 
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