Transdisciplinary product development
DOI:
https://doi.org/10.37886/Keywords:
transdisciplinarity, concurrent engineering, decision-making, business intelligence, dynamic programmingAbstract
Research Question (RQ): How can transdisciplinary approach increase the product development
process in future industry?
Purpose: The aim of the research is to develop a model of an effective product development in the
automotive industry based on the transdisciplinary approach.
Method: We used a qualitative research approach in order to develop a theoretical framework of
transdisciplinarity. The framework comprises the concurrent engineering and experts from
different disciplines. The framework was represented by a mathematical model which based on
stochastic dynamic programming.
Results: We developed a theoretical framework and a practical case of transdisciplinary product
development in the automotive industry. We presented a mathematical model and information
environment which supports such a model.
Organization: The findings of the research will provide higher productivity, lower operating
costs, change in personnel structure, higher added value, lower sales costs, lower administration
costs, reduction in growth of expenses, and lower costs of work equipment.
Society: The research impact on higher customer’s satisfaction, increased flexibility of operations,
better quality of information, improved control of sources, less waste materials and less pollution,
improved planning process, more favourable consideration of employees , improved portfolio
management, and better corporate presentation of company.
Originality: Transdisciplinary framework combines methods of concurrent engineering and
interdisciplinary approach in a process of product development. The development of such a
framework is a complete novelty and represents an original approach to product development,
which will be particularly suitable for the smart factories of the future. Transdisciplinary
framework was transformed into a mathematical model based on stochastic dynamic
programming. Model is supported by the existing information warehouse and represents a
potential for upgrade business intelligence.
Limitations / further research: Proposed model was implemented in automotive industry. In the
future it could be implemented also in other industries as a part of smart factories.
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