The impact of virtual simulation tools on problem-solving and new product development organization

doi:10.1016/j.respol.2005.03.016

Research Policy

Volume 34, Issue 9, November 2005, Pages 1305-1321

https://doi.org/10.1016/j.respol.2005.03.016 Get rights and content

Abstract

New product development nowadays makes heavy use of IT instruments such as virtual simulation tools. The main motivation for introducing virtual simulation tools in new product development is to speed up development and lower its cost. Virtual simulation tools, however, do much more. They introduce profound changes in the organization, including the nature of problem-solving, bearing the potential to increase new product development performance beyond cost and lead time reduction. Understanding these profound changes, we argue, holds the key to unlocking the potential of virtual simulation tools for improving new product development performance, including more innovative products. We support our argument with a case study from the European auto industry.

Section snippets

Virtual simulation tools can do much more than just speed up product development and lower its cost

Virtual simulation tools now play a very important role in new product development. They have been widely hailed to significantly cut development time and costs (Thomke, 1998a, Thomke, 2001a). Accordingly, virtual simulation tools are often introduced in new product development to reap precisely those benefits. In the academic literature, virtual experimentation is also often regarded as a way to overcome the cost and time limitations of physical experimentation methods. Limiting virtual

Introducing virtual simulation tools triggers profound changes in the organization, including the nature of problem-solving

There is ample evidence in the literature that introducing new technology into an organization triggers changes in the way tasks are accomplished, and thus in organizational processes (Barley, 1986, Barley and Kunda, 2001, Orlikowski, 1996, Orlikowski, 2002).² Technologies alter institutionalized

The case study

Within the literature that frames virtual development as a tool for improving NPD performances, Baba and Nobeoka (1998) was among the first papers to present a virtual simulation tool (3D-CAD) as an enabler of a peculiar form of problem-solving. However, the field research was carried out some years ago (1995) and the technology has improved so much by now that updating their analysis of the effects of virtual prototyping on the nature of problem-solving is needed. D’Adderio's (2001) paper on

Discussion

The basic premise that we started out from is that introducing virtual simulation tools in new product development is not trivial but triggers profound changes in the organization. Our case study has confirmed that and has shed light on some of the effects that introducing virtual simulation tools has on firms. To start with, our data confirms the impact of virtual tools on cost and speed of product development projects, in line with the literature. However, our case study has also evidenced

Conclusion

Throughout this article, we have maintained that virtual simulation tools trigger profound changes in the organization, including the nature of problem-solving. In the previous section, we have identified that virtual simulation tools have an important impact on the redefinition of the set of options to be taken into consideration in problem-solving. In particular through this causal mechanism, we have argued that virtual simulation tools provide the possibility of more innovative designs,

References (55)

W.J. Abernathy et al.
Innovation: mapping the winds of creative destruction
Research Policy
(1985)
A. Arora et al.
The changing technology of technological change: general and abstract knowledge and the division of innovative labour
Research Policy
(1994)
Y. Baba et al.
Towards knowledge-based product development: the 3-D CAD model of knowledge creation
Research Policy
(1998)
L. D’Adderio
Crafting the virtual prototype: how firms integrate knowledge and capabilities across organisational boundaries
Research Policy
(2001)
M. Iansiti
Technology integration: managing technological evolution in a complex environment
Research Policy
(1995)
E. McDonough et al.
The effects of cognitive problem-solving orientation and technological familiarity on faster new product development
Journal of Product Innovation Management
(1992)
R.R. Nelson
On the uneven evolution of human know-how
Research Policy
(2003)
P. Nightingale
A cognitive model of innovation
Research Policy
(1998)
G.P. Pisano
Learning-before-doing in the development of new process technology
Research Policy
(1996)
S.H. Thomke
Simulation, learning and R&D performance: evidence from automotive development
Research Policy
(1998)

S.H. Thomke et al.

The effect of ‘front-loading’ problem-solving on product development performance

Journal of Product Innovation Management

(2000)

J. West et al.

Experience, experimentation, and the accumulation of knowledge: the evolution of R&D in the semiconductor industry

Research Policy

(2003)

P.S. Adler et al.

Behind the learning curve: a sketch of the learning process

Management Science

(1991)

K. Arrow

The economic implications of learning by doing

The Review of Economic Studies

(1962)

S.R. Barley

The alignment of technology and structure through roles and networks

Administrative Science Quarterly

(1990)

S.R. Barley

Technology as an occasion for structuring: evidence from the observations of CT scanners and the social order of radiology departments

Administrative Science Quarterly

(1986)

S.R. Barley et al.

Bringing work back in

Organization Science

(2001)

R.E. Bohn

Measuring and managing technological knowledge

MIT Sloan Management Review

(1994)

L. D’Adderio

Inside the Virtual Product: How Organizations Create Knowledge Through Software

(2004)

K.M. Eisenhardt

Building theories from case study research

Academy of Management Review

(1989)

K. Henderson

On Line and On Paper—Visual Representations, Visual Culture, and Computer Graphics in Design Engineering

(1999)

R.M. Henderson et al.

Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms

Administrative Science Quarterly

(1990)

Iansiti, M., Clark K.B., 1993. Integration and dynamic capability: evidence from product development in automobiles and...

T. Itoh

Abduction for creativity

International Journal of Technology Management

(2003)

T. Knudsen

The significance of tacit knowledge in the evolution of human language

Selection

(2002)

B. Levitt et al.

Organizational learning

Annual Review of Sociology

(1988)

G.S. Lynn et al.

Marketing and discontinuous innovation: the probe and learn process

California Management Review

(1996)

Cited by (67)

Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications
2022, Energy
Citation Excerpt :
Typically different criteria such as specific energy, specific power, cell capacity and heat transfer efficiency have been considered to evaluate the energy efficiency and thermal performances of Li-ion battery cell designs. Becker et al. [14], highlighted the role of model-based and virtual simulation tools for speeding up the product development at lower costs. In the context of Li-ion batteries modeling, physics-based approaches such as the well-established Newman-type electrochemical model [15] provide a deep understanding about the underlying physico-chemical phenomena in a Li-ion cell sandwich and has gained enormous popularity in cell design problems [16,17].
Large-scale commercialization of electric vehicles (EVs) seeks to develop battery systems with higher energy efficiency and improved thermal performance. Integrating simulation-based design optimization in battery development process expands the possibilities for novel design exploration. This study presents a dual-stage multiphysics simulation optimization methodology for comprehensive concept design of Lithium-ion (Li-ion) battery packs for EV applications. At the first stage, multi-objective optimization of electrochemical thermally coupled cells is performed using genetic algorithm considering the specific energy and the maximum temperature of the cells as design objectives. At the second stage, the energy efficiency and the thermal performances of each optimally designed cell are evaluated under pack operation to account for cell-to-pack interactions under realistic working scenarios. When operating at 1.5 C discharge current, the battery pack comprising optimally designed cells for which the specific energy and the maximum temperature are equally weighted delivers the highest specific energy with enhanced thermal performance. The most favorable pack design shows 8% reduction in maximum pack temperature and 16.1% reduction in module-to-module temperature variations compared to commercially available pack. The methodology for design optimization presented in this work is generic, providing valuable knowledge for future cell and pack designs that employ different chemistries and configurations.
Unveiling the relationship between drivers and capabilities for reduced time-to-market in start-ups: A multi-method approach
2021, International Journal of Production Economics
Reduced time-to-market (TTM) is mandatory in new product development, especially in uncertain environments. The capabilities for reducing TTM are well known in the literature. However, to the best of our knowledge, no study aims to present the mutual influence between these capabilities and drivers for reducing TTM. Moreover, this subject is insufficiently understood regarding start-ups, the focus of the present research. To mitigate this gap, this paper aims to identify the map of the relationship between the drivers and capabilities for reducing TTM in start-ups. A preliminary list of drivers and capabilities was identified through a Systematic Literature Review and then validated for start-ups in consultation with experts. The Interpretive Structural Modelling (ISM) method was used to develop a hierarchical model, and the analysis of the dependence and driving power of such drivers and capabilities was performed by Fuzzy MICMAC (Matriced’ Impacts Croise's Multiplication Applique'e a’ un Classement). The results showed that five drivers led start-ups to attain nineteen capabilities to reduce their TTM. These capabilities present synergy and can be organised in a structural model that shows the hierarchy among the capabilities, indicating which one should be developed with priority. Concerning practice, the results obtained can provide start-ups and policymakers with a much more efficient roadmap to bring products to market faster and improve the performance of companies.
Optimising lithium-ion cell design for plug-in hybrid and battery electric vehicles
2019, Journal of Energy Storage
Citation Excerpt :
For accelerated product development, many industries have established a model-led approach accelerating design iterations and increasing understanding gained from formalising empirical know-how [9,10]. Furthermore, Becker et al. argue that a model-led approach subtly helps to develop fundamental knowledge of underlying physical phenomena [10]. In the context of battery modelling, physics-based models can provide improved understanding of battery behaviour and a model-led approach can assist in accelerating the pace of battery development [11].
Increased driving range and enhanced fast charging capabilities are two immediate goals of transport electrification. However, these are of competing nature, leading to increased energy and power demand respectively from the on-board battery pack. By fine-tuning the number of layers versus active electrode material of a lithium ion pouch cell, tailored designs targeting either of these goals can be obtained. Achieving this trade-off through iterative empirical testing of layer choices is expensive and often produces sub-optimal designs. This paper presents a model-based methodology for determining the optimal number of layers, maximising usable energy whilst satisfying specific acceleration and fast charging targets. The proposed methodology accounts for the critical need to avoid lithium plating during fast charging and searches for the optimal layer configuration considering a range of thermal conditions. A numerical implementation of a cell model using a hybrid finite volume-spectral scheme is presented, wherein the model equations are suitably reformulated to directly accept power inputs, facilitating rapid and accurate searching of the layer design space. Electrode materials exhibiting high solid phase diffusion rates are highlighted as being equally as important for extended range as the development of new materials with higher inherent capacity. The proposed methodology is demonstrated for the common module design of a battery pack in a plug-in hybrid vehicle, thereby illustrating how the cost of derivative vehicle models can be reduced. To facilitate model based layer optimisation, the open-source toolbox, BOLD (Battery Optimal Layer Design) is provided.
Virtual shaker modeling and simulation, parameters estimation of a high damped electrodynamic shaker
2019, International Journal of Mechanical Sciences
Virtual shaker testing is a novel and valuable tool to predict a vibration test response as the coupling effect. This consists of simulating a physical shaker test by modeling the constitutive elements of a vibration test loop. This article presents the implementation and validation of a virtual shaker testing for a high-damped shaker. The shaker is modeled by mechanical lumped elements as a state-space system. In the case of a high damped electrodynamic shaker, the classical experimental modal estimation does not allow a proper identification of the system. This article presents a blocking structure approach as an alternative for shaker parameters determination. The obtained results are implemented in the virtual shaker testing model, simulations are performed and the model is validated by experiments.
Computational modelling of nano-composites (single walled carbon nanotubes) for engine
2019, Materials Today: Proceedings
Nanomaterials constitute a prominent sub-discipline in the materials science. Conventional materials like glass, ceramic, metals, polymers or semiconductors can be formed in a nanoscale proportion. They have various microstructural distinctive attributes such as nano-discs, nanotubes, nanocoatings, quantum dots, nanocomposites, and nanowires. The unique properties of nanoparticle derived materials and devices depend directly on the size and structure-dependent properties. This Paper shows the modern design requirements with the help of simulation to assure the properties of engine like faster, miniature, highly maneuverable, self-healing, lightweight warrant for materials, intelligence guided, smart, eco-friendly, with extraordinary mechanical and multifunctional properties while making the engine parts.
A novel tool for optimization and verification of layout and human logistics in digital factories
2018, Procedia CIRP
We introduce a novel digital factory layout tool that optimizes both the layout of machines and the corresponding ergonomic logistics considering space constraints. A model is constructed by tangible properties on machines and environment, regions on the floor and by ranking their mutual relations. An optimized layout is then computed based on the model, the relations and an ergonomic score for the human work tasks, which are automatically computed by digital manikins. The result is an optimized layout, visualized in 3D, with improved logistic routes. The layout tool has been implemented and successfully tested on a relevant industrial case.

View all citing articles on Scopus

¹: Tel.: +33 390242189; fax: +33 390242071.

View full text