Ali Keyvani

IMMA – intelligently moving manikins in automotive applications

INTRODUCTION Digital human modelling (DHM) has been introduced in the product and production development process to provide the possibility of early analysis and verification of human-product and human-production system interaction. Digital human modelling is relatively widely used within automotive industry (Paul et al., 2012). Digital human modelling can be used to analyse both human postures and motions. Several techniques have been explored for the generation of manikin motions. Neural networks, a structure that should imitate the human brain, and fuzzy logics, a logic that should imitate human reasoning, have been tested in combination (Hanson et al., 1999). Currently no commercial digital human modelling tool on the market uses this combination to generate motions. In Siemens’ ergonomics simulation and visualisation tools two approaches are currently used: a task-based simulation approach with inverse kinematics (Raschke et al., 2005), and an approach that modifies root motions gathered from real humans using motion capture systems (Park et al., 2008). Motion captured recorded motions are also used in EMA where base motions from a reference database, similar to base tasks in predetermined motion time systems, is put together into new unique motion combinations (Fritzsche et al., 2011). Even though these approaches are available, most commonly the manikin is manually manipulated joint by joint, which gives drawbacks such as that manual adjustment is time consuming and posture and motion results may vary, both within and between tool users (Lämkull et al., 2008). From an industrial point of view such variation within the process is not a sustainable way of working. Frequently the validity of the manually generated manikin postures and motions is questioned. Therefore, researchers and industry use motion capture systems in combination with ergonomics simulation and visualisation tools. Motion capture systems require typically a laboratory like environment and physical prototypes. Hence, in using such a set-up, several of the advantages with virtual design and manufacturing disappear or are reduced. Therefore there is a call for valid motion generators in digital human modelling tools in order to support proactive ergonomics (Chaffin, 2005).

Using methods-time measurement to connect digital humans and motion databases

To simulate human motions in DHM tools, using techniques which are based on real human data is one promising solution. We have presented a solution in this study to connect motion databases with DHM tools. We have showed that using a motion database with MTM-based annotations is a promising way in order to synthesize natural looking motions. A platform consists of a Motion Database, a Motion Generator, and a DHM tool was introduced and tested. The results showed successful application of the presented platform in the designed test case.

Schema for motion capture data management

A unified database platform capable of storing both motion captured data and information about these motions (metadata) is described. The platform stores large motion captured data in order to be used by different applications for searching, comparing, analyzing and updating existing motions. The platform is intended to be used to choose a realistic motion in simulation of production lines. It is capable of supporting and handling different motion formats, various skeleton types and distinctive body regions in a uniform data model. Extended annotating system is also introduced to mark the captured data not only in the time domain (temporal) but also on different body regions (spatial). To utilize the platform, sample tests are performed to prove the functionality. Several motion captured data is uploaded to the database while MATLAB is used to access the data, ergonomically analyze the motions based on OWAS standard, and add the results to the database by automatic tagging of the postures.

A Virtual Manufacturing Approach for Integrating Fixture Design with Process Planning

Computer Aided Process Planning has received more attention recently due to considerable progress in the aspects of both technology and theory. Beside the traditional trends and efforts to integrate the product design and process planning activities usually referred to as concurrent engineering, virtual manufacturing tools have opened new horizons to this domain. This paper describes how to combine an existing modular fixture design with process planning and simulation tools. The proposed concurrent architecture consists of a functional model and an operational workflow for the design of modular fixtures within the process-planning phase. Two different paradigms, the Variant and the Generative, are discussed in relation to the proposed architecture. Fixtures for Body in White lines are a crucial design problem in the automotive industry. Therefore, the proposed architecture has been tested and investigated in such an environment.